Proteomic analysis of Enterococcus faecalis cell …...Proteomic analysis of Enterococcus faecalis...
Transcript of Proteomic analysis of Enterococcus faecalis cell …...Proteomic analysis of Enterococcus faecalis...
Proteomic analysis of Enterococcus faecalis cell
membrane proteins under alkaline stress conditions
A Thesis submitted in fulfilment of the requirements for
admission to the degree of Doctor of Philosophy
Peter Cathro
MDS, Cert Tert T
School of Dentistry
The University of Adelaide
South Australia
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Table of Contents Abstract ................................................................................................................................. iv
Statement of Authorship ....................................................................................................... vi
Acknowledgements .............................................................................................................. vii
Chapter 1. Introduction .......................................................................................................... 1
1.1 Apical periodontitis ...................................................................................................... 1
1.1.1 Endodontic disease ............................................................................................... 1
1.1.2 Prevalence ............................................................................................................. 3
1.1.3 Polymicrobial nature ............................................................................................. 4
1.1.4 Factors influencing persistent apical periodontitis ............................................... 4
1.2 Enterococcus faecalis .................................................................................................. 5
1.2.1 The genus .............................................................................................................. 5
1.2.2 Strains of E. faecalis ............................................................................................. 5
1.2.3 Gram-positive features .......................................................................................... 6
1.2.4 The genomics of E. faecalis .................................................................................. 8
1.2.5 Pathogenicity island .............................................................................................. 8
1.2.6 The role of E. faecalis in persistent apical periodontitis ....................................... 9
1.2.7 Carbohydrate uptake ............................................................................................. 9
1.2.8 Stress response .................................................................................................... 10
1.2.9 Biofilm growth .................................................................................................... 11
1.3 Proteomics ................................................................................................................. 13
1.3.1 Definition ............................................................................................................ 13
1.3.2 Proteomic techniques .......................................................................................... 13
1.3.3. Mass spectrometry ............................................................................................. 15
1.3.4 Liquid chromatography tandem mass spectrometry ........................................... 15
1.4 Bioinformatics ........................................................................................................... 16
1.5 Membrane proteome of E. faecalis ............................................................................ 17
1.6 Quantification and labelling ....................................................................................... 18
1.7 Continuous culture in the post-genomic era .............................................................. 21
1.8 Overall aims of the study ........................................................................................... 21
Chapter 2. Experimental Investigations ............................................................................... 23
2.1 Effect of alkaline pH on growth rate and phenotypic expression of E. faecalis V583 . 23
2.1.1 Abstract ............................................................................................................... 23
2.1.2 Background ......................................................................................................... 23
2.1.3 Methods .............................................................................................................. 25
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2.1.4 Results ................................................................................................................. 26
2.1.4.1 pH 8 .............................................................................................................. 26
2.1.4.2 pH 11 ............................................................................................................ 28
2.1.4.3 Phenotypic differences ................................................................................. 29
2.1.5 Discussion ........................................................................................................... 29
2.1.6 Conclusion .......................................................................................................... 31
2.2 1D SDS-PAGE and in-solution proteomic analysis of E. faecalis membrane proteins: Pilot study ........................................................................................................................ 32
2.2.1 Abstract ............................................................................................................... 32
2.2.2 Background ......................................................................................................... 32
2.2.3 Methods .............................................................................................................. 33
2.2.3.1 Growth conditions ........................................................................................ 33
2.2.3.2 In solution digestion ..................................................................................... 34
2.2.3.3 1D SDS-PAGE ............................................................................................ 34
2.2.3.4 Liquid chromatography - Orbitrap tandem mass spectrometry (LC MS/MS) of protein samples .................................................................................................... 35
2.2.3.5 Data analysis ................................................................................................ 35
2.2.4 Results ................................................................................................................. 36
2.2.5 Discussion ........................................................................................................... 36
2.2.5.1 Cell wall digestion ....................................................................................... 37
2.2.5.2 Cell surface shaving ..................................................................................... 37
2.2.5.3 Cell surface labelling ................................................................................... 38
2.2.6 Conclusion .......................................................................................................... 40
2.3 Isolation and identification of E. faecalis membrane proteins using membrane shaving and one-dimensional SDS-PAGE coupled with mass spectrometry ............................... 41
2.3.1 Abstract ............................................................................................................... 41
2.3.2 Background ......................................................................................................... 41
2.3.3 Methods .............................................................................................................. 43
2.3.3.1 Growth conditions ........................................................................................ 43
2.3.3.2 1D SDS-PAGE ............................................................................................ 43
2.3.3.3 Membrane shaving ....................................................................................... 44
2.3.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry .. 45
2.3.3.5 Protein analysis ............................................................................................ 47
2.3.4 Results ................................................................................................................. 47
2.3.5 Discussion ........................................................................................................... 51
2.3.6 Conclusions ......................................................................................................... 54
2.4 Influence of Enterococcus faecalis V583 cell membrane protein expression on biofilm formation and metabolic responses to alkaline stress ...................................................... 56
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2.4.1 Abstract ............................................................................................................... 56
2.4.2 Background ......................................................................................................... 57
2.4.3 Methods .............................................................................................................. 61
2.4.3.1 Growth conditions ........................................................................................ 61
2.4.3.2 Membrane shaving ....................................................................................... 61
2.4.3.3 Peptide ICPL labelling ................................................................................. 61
2.4.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry .. 62
2.4.3.5 Protein analysis ............................................................................................ 63
2.4.4 Results ................................................................................................................. 64
2.4.4.1 Continuous culture ....................................................................................... 64
2.4.4.2 ICPL labelling .............................................................................................. 64
2.4.5 Discussion ........................................................................................................... 66
2.4.6 Conclusion .......................................................................................................... 75
Chapter 3. Overall Discussion ............................................................................................. 76
3.1 Proteins implicated in biofilm formation ................................................................... 80
3.2 Correlation between metabolism and peptidoglycan turnover .................................. 81
3.3 Correlation to bacteriocin resistance .......................................................................... 82
3.4 Membrane proteins associated with stress response .................................................. 83
3.5 Future Studies ............................................................................................................ 84
3.5.1 Construct and characterise individual markerless deletion mutants of EF0114 and EF1927 and a double-knockout mutant ....................................................................... 84
3.5.2 Determine regulation of EF0114 and EF1927 gene expression ......................... 84
Chapter 4. Overall Conclusion ............................................................................................. 86
Chapter 5. References .......................................................................................................... 88
Appendix 1 ........................................................................................................................... 96
Appendix 2 ........................................................................................................................... 97
Appendix 3 ......................................................................................................................... 101
Appendix 4 ......................................................................................................................... 106
Appendix 5 ......................................................................................................................... 111
Appendix 6 ......................................................................................................................... 112
Appendix 7 ......................................................................................................................... 113
Appendix 8 ......................................................................................................................... 114
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Abstract
Background: Enterococcus faecalis is able to survive in a number of biological niches,
which are often nutrient limited and in which the pH can vary greatly. Endodontic (root
canal) treatment of a tooth with a severely inflamed, infected or necrotic pulp usually
involves the chemo-mechanical debridement of the canal(s) using metal files, irrigants such
as sodium hypochlorite and often inter-appointment medicaments such as calcium hydroxide
(~pH 12.5 to 12.8) placed in the main root canal to help in the elimination of surviving
bacteria. E. faecalis is commonly recovered from endodontic infections that have persisted
following treatment with this highly alkaline medicament. The expression of the cell
membrane proteins under alkaline conditions at a biologically relevant growth rate may
increase our understanding of how E. faecalis can adapt and persist.
Aims:
1. To determine the phenotypic changes of E. faecalis V583 when grown at a slow growth
rate at pH 11.
2. To investigate and quantify cell membrane protein expression of E. faecalis V583, at pH
11 compared to pH 8, at an imposed growth rate using continuous culture.
Methods: E. faecalis ATCC V583 was grown in a chemostat at pH 8 (control) and pH 11.
Under each pH condition, the maximum growth rates were determined and an imposed
growth rate of one-tenth the organism’s maximum growth rate (μrel) was used for growth at
pH 8 or 11. After steady state had been achieved, cells were harvested, lysed and membrane
proteins were fractionated by ultracentrifugation, homogenisation in carbonate buffer, and
membrane shaving. Following chymotrypsin digest (in the presence of RapiGest®) of the
membrane fraction, heavy- or light-isotope-coding protein labels (ICPL) were added to
samples from pH 8 or 11. Heavy-labelled (pH 11) and light-labelled (pH 8) samples were
combined and the relative proportion of membrane proteins were identified using Liquid
chromatography, electrospray ionisation (LC-ESI) mass spectrometry and MaxQuant
analysis. The MaxQuant labelled ratios of membrane associated proteins were log2
transformed, and the proteins that deviated by more than one standard deviation (SD) from
the mean were considered to be up- or down-regulated.
Results: The mean generation time at pH 8 was 1.16 hours and 7.7 hours at pH 11. One-
tenth of the maximum growth rate (0.1 μrel) was determined and set at 0.059 h-1 for pH 8 and
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0.009 h-1 for pH 11. The extreme alkaline conditions produced co-aggregation of the cells
into flocs (a variant of biofilm formation) with the appearance of an extracellular matrix.
These observations are consistent with a shift towards spontaneous biofilm formation.
Six proteins had a log2 H/L ratio (pH 11/pH 8) greater than one SD of the mean including:
Polysaccharide biosynthesis family protein EF0669 (2SD), Glycosyl hydrolase, family 20
EF0114 (4SD), Glycerol uptake facilitator protein EF1927 (1SD), whilst five proteins had a
log2 ratio one SD less of the mean: PTS system IIC component EF1838 (1D), PTS system
IID component EF0456 (2SD), C4-dicarboxylate transporter EF0108 (1SD), PTS system
mannose-specific IID component EF0022 (1SD).
Conclusion: When cultured at an imposed slow growth rate, extreme alkaline conditions
resulted in a reduced mean generation time and altered expression of several membrane
proteins. Collectively these membrane proteins appear to be involved in the transition to
biofilm formation seen at pH 11. It was hypothesised that the capsule observed at pH 11
protects the cell from destructive OH- ions whilst concentrating H+ ions and substrates
required for the electrochemical gradient close to the cell membrane.
Keywords: Enterococcus faecalis, isotope-coding protein labels (ICPL), alkaline pH,
membrane shaving.
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Statement of Authorship
This work contains no material which has been accepted for the award of any other degree
or diploma in any university or other tertiary institution and, to the best of my knowledge
and belief, contains no material previously published or written by another person accept
where due reference has been made in the text.
I give consent to this copy of my thesis, when deposited in the University Library, being
made available for loan and photocopying, subject to the provisions of the Copyright Act
1968.
Signed:
Peter Cathro Date:
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Acknowledgements
I would like to thank a number of people who provided guidance and encouragement during
the course of this work.
Dr Peter Zilm, who has been a mentor, colleague and friend over many years and without
whose support this thesis and our other joint research endeavours would not have been
possible.
Dr Stephen Kidd, for his dedication and willingness to supervise this project and his
wonderful insights into the world of bioinformatics.
Associate Prof Neville Gully, for his help in guiding this and other research projects over
the years.
Dr Peter McCarthy, for his expert research skills and “rescuing” my precious samples.
Prof Peter Hoffmann, for his support and generous help facilitating the proteomic
components of the project.
Camilla, Samuel, Emily & Alfred, my wonderful family, I cannot thank them enough for
their ongoing love and care of me.
This study was supported by several grants from the Australian Dental Research Foundation,
The Dental School University of Adelaide and the Australian Society of Endodontology.
I sincerely thank the staff at the Adelaide Proteomic Centre for their excellent technical
assistance.
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Chapter 1. Introduction
1.1 Apical periodontitis
1.1.1 Endodontic disease
Teeth consist of two main components, namely the crown and the root. The crown is
comprised of enamel, dentine and the extension of the pulp tissues from the root. The root
is generally below the gingival margins and is covered with cementum. The root is largely
comprised of dentine and contains the pulp in the root canals. The pulp consists primarily of
loose connective tissue predominated by fibroblasts, undifferentiated mesenchymal cells,
collagenous fibres, blood vessels (arterioles, venules), and neural tissue (Mjör & Fejerskov
1979). In the development of teeth, the pulp plays a major role in the production of dentine,
which ultimately encloses the pulp tissue once root development is complete. The dental
pulp is therefore normally protected by dentine and enamel but may become infected
subsequent to caries, defective restorations or traumatic injuries to the tooth (Kakehashi et
al 1966). The pulp has a limited capacity to launch an effective immune response to invading
bacteria, and due to being enclosed by hard tissues there is minimal ability for tissue
expansion with inflammation, resulting in an increased intrapulpal pressure which may cause
marked pain for the patient. Unresolved inflammation can cause either a gradual or rapid
destruction of the pulp in a coronal-apical direction. As a natural consequence of microbial
infection, the pulp may become necrotic, with infectious microorganisms colonizing the
main body of the root canal, penetrating into the dentinal tubules, lateral canals or
anastomoses, the formation of biofilms and ultimately resulting in infection and/or
inflammation of the periapical tissues (termed apical periodontitis) (Figure 1) (Moller et al
1981, Sundqvist et al 1998, Love 2001, Nair 2006).
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Figure 1. Light microscopic view demonstrating an infected root canal system with biofilm formation (BF) in an accessory canal (AC) and the presence of apical periodontitis (AP) (Nair 2006).
Endodontics is primarily concerned with the prevention or elimination of apical
periodontitis. If the pulp becomes inflamed it may be reversibly damaged, i.e. it has the
ability to heal. This occurs through the normal inflammatory and repair process seen
throughout the body and also by the increased deposition of dentine to "wall-off" the pulp
from the advancing irritants (Bjørndal 2002). If the bacterial assault on the pulp overcomes
the ability for repair, then the pulp becomes irreversibly damaged and eventually becomes
necrotic with no mechanisms available to manage the invading bacteria or their toxic by-
products (e.g. endotoxins) (Barthel et al 1997). The ultimate outcome of the pulp disease
process is a root canal space that is pulpless and infected (Jansson et al 1993)
The treatment options for a tooth with irreversible pulpitis or an infected root canal system
are usually limited to extraction or endodontic therapy. The management of an infected root
canal system relies on the use of antimicrobial strategies involving a number of procedures
including instrumentation, irrigation, medication and a restoration to prevent
recontamination. Following access to the root canals, instrumentation is carried out with
endodontic files that enlarge the root canals and create a shape that facilitates the placement
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of irrigants, medicaments and ultimately the root filling (obturation) material.
Instrumentation allows for some limited mechanical removal of bacteria (Byström &
Sundqvist 1981), but it is the use of antimicrobial irrigants such as sodium hypochlorite or
dressings such as calcium hydroxide used as an inter-appointment medicament (Byström &
Sundqvist 1985, Byström et al 1985) that are crucial in significantly reducing microbial
numbers. The release of hydroxide ions (~pH 12) from calcium hydroxide is thought to be
responsible for its antimicrobial effect, causing lipid peroxidation which results in
destruction of the phospholipid component of bacterial cell walls (Siqueira & Lopes 1999).
The effects of an alkaline pH are known to cause a dramatic reduction in the viability of
bacteria, for example, the survival of Enterococcus faecalis has been shown to decrease to
0.001% at pH 11 and 0.00001% at pH 12 compared to the growth at pH 7 (Appelbe &
Sedgley 2007). On a cellular level, the response to an extreme alkaline environment has been
attributed to the activation of proton pumps to help maintain pH homeostasis (Evans et al
2002) or more generalised survival responses with a common set of proteins being expressed
(Petrak et al 2008, Wang et al 2009).
During endodontic treatment, the combination of the antimicrobial strategies aid in removing
organic matter from the canal, such as pulp tissue, and in eliminating bacteria. Following the
disinfection stages, the root canal is then usually obturated with gutta-percha and an
appropriate sealer to prevent (or at least reduce) the recontamination of the root canal system
or the entry of periradicular fluid. Collectively the stages of root canal treatment render the
canal a hostile, nutrient depleted environment, making bacteria survival a challenge. Even
in this hostile environment, bacteria can survive and lead to persistent apical periodontitis
(Sedgley et al 2005).
1.1.2 Prevalence
Billions of teeth are retained through root canal treatment, and in high or very highly
developed countries this represents the equivalent of two treatments per patient (Pak et al
2012). The root canal system is not a simple evenly tapered shape, but rather is complex
with many accessory canals and webs, which provide safe-harbours for bacteria (Nair 2006,
Vertucci 1984). Completed to a high standard, endodontic therapy enjoys a very high success
rate in the order of 85 to 95% (Sjögren et al 1997, Elemam & Pretty 2011). If the primary
treatment has failed and re-treatment is attempted, then the expected success drops to the
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order of 60 to 80% (Sjögren et al 1990, Elemam & Pretty 2011). Correlating success rates
to the amount of teeth treated means that hundreds of millions of teeth have persistent
infection. Endodontic treatment can be expensive, and as such there is a health and financial
burden to individuals and society in managing endodontic infections and retaining teeth for
life.
1.1.3 Polymicrobial nature
Utilizing molecular techniques, an average of 20 taxa are recovered per tooth with a primary
endodontic infection (Munson et al 2002), but over 391 bacterial taxa have been detected in
different samples of primary infections (Siqueira & Rôças 2009).
Initially the infected root canal is populated with a mixed anaerobic population dominated
by obligate anaerobes (Byström & Sundqvist 1981). Following irrigation and medication
protocols, Gram-negative bacteria are not usually recovered, with Fusobacterium
nucleatum, Prevotella sp. and Campylobacter rectus being notable exceptions (Byström &
Sundqvist 1985, Sakamoto et al 2007). In contrast, Gram-positive facultative or anaerobic
bacteria have been found to survive the endodontic treatment protocols and include
streptococci, Parvimonas micra, Actinomyces sp., Propionibacterium sp.,
Pseudoramibacter alactolyticus, Lactobacilli and E. faecalis (Chávez de Paz et al 2005,
Gomes et al 1996). If the primary treatment fails with evidence of persistent infection, then
E. faecalis is the most frequently recovered species, with prevalence occurring in up to 90%
of cases (Molander et al 1998, Siqueira & Rôças 2009).
1.1.4 Factors influencing persistent apical periodontitis
Root canal therapy can be considered to fail for two main reasons. The first is that the
microbial numbers were not reduced sufficiently during the initial treatment, allowing
persistence of the disease process (Nair 2006). The second is recontamination of the root
canal system, usually as a result of a defective restoration or the progression of caries (Ray
& Trope 1995). If there is evidence of infection associated with a root filled tooth, then the
clinical options would include monitoring, extraction, re-treatment or apical surgery. The
success of re-treatment is principally related to the cause of the infection. If the canals were
poorly treated in the first instance without procedural errors, success can be high, but if the
primary treatment was carried out to a high technical standard, or if procedural errors had
occurred, then the success rate is lower.
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This lowered success rate is primarily due to a shift in the bacterial population residing in
the root canal system (Molander et al 1998) and also the limitations in overcoming iatrogenic
errors that may have been created when the root canal was initially treated. Errors include
transportation (deviation from the true root canal), ledging, apical blockages and perforation.
If calcium hydroxide medicament is used in the management of a primary infection, the
diffusion of hydroxyl ions into the dentinal tubules takes 3 to 4 weeks to penetrate to the
outer layers of dentine (Nerwich et al 1993). The initially high pH has been reported to be
buffered by dentine, thereby reducing the antimicrobial effect of calcium hydroxide
(Haapasalo et al 2000). In contrast, Athanassiadis et al (2010) report that dentine did not
inactivate calcium hydroxide when used in a commercial paste formulation and that E.
faecalis was unable to survive this medicament.. If root canal therapy fails, then E. faecalis
is commonly recovered and like most bacteria, it has the ability to form a biofilm that is
firmly attached to the dentinal tubules within the root canal system (Seet et al 2012).
1.2 Enterococcus faecalis
1.2.1 The genus
Enterococci species belonging to the genus are ubiquitous and are found in a wide variety of
habitats including food, soil, waterlines, sewage, and the human gastro-intestinal tract
including the oral cavity (Franz et al 1999). Typically, enterococci can tolerate high salt
concentrations (up to 6.5%), a wide pH range (4.6 to 12), a wide temperature range (10 to
45C), desiccation, bile acids, detergents, antimicrobials including certain antibiotics,
pancreatic secretions (pH ≥10) and they can survive pasteurisation.
1.2.2 Strains of E. faecalis
E. faecalis is an opportunistic bacterium, being a major cause of infective endocarditis,
urinary tract infections and bacteraemia, and with intrinsic resistance to many antibiotics and
antimicrobial agents representing a significant nosocomial burden (Paulsen et al 2003, Korja
et al 2005).
E. faecalis strain MMH594 was responsible for a number of life threatening infections
following trauma or conditions requiring life support and seems to be the prototype from
which strains E. faecalis V586 and V583 have evolved (Huycke et al 1991, Shankar et al
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2002). The vancomycin resistant serial isolates (V583 and V586) were obtained from blood,
urine and stool cultures from a chronically infected patient (Sahm et al 1989). Shankar et al
(2002) identified that the modulation of many of the resistance features including
transposases, transcriptional regulators, and aggregation substance present in the isolates
were contained within a pathogenicity island. However, none are known to code for
antibiotic resistance. Cytolysin (a toxin) and the surface protein Esp, which is involved in
colonisation and biofilm formation are common virulence factors in E. faecalis clinical
isolates. The genes coding for these could be localised on the chromosome of V586, but the
organism appears to be phenotypically non-cytolytic, even though it contains the cytolysin
operon. The genes encoding cytolysin and Esp however, were not found in V583. E. faecalis
V583 (esp-, cyl-) seems to occur through the spontaneous deletion of DNA from the V586
genome, occurring at a frequency of approximately 1 in 103 when V586 was cultivated in
vitro (Shankar et al 2002).
1.2.3 Gram-positive features
E. faecalis is a Gram-positive facultative bacterium. Gram-positive bacteria are surrounded
by a thick and rigid single cell wall, which is composed primarily of peptidoglycan (Figure
2). This is in contrast to the double membrane seen in Gram-negative bacteria (Cordwell
2006, Solis & Cordwell 2011).
Figure 2. Cell wall architecture of Gram-positive bacteria from Solis and Cordwell (2011).
The surface of Gram-positive bacteria comprises proteins, biological molecules such as
teichoic, lipoteichoic, teichuronic acids (providing a net negative charge), slime capsules
and biofilms (Solis & Cordwell 2011). Of all the bacterial genes, it is estimated that
approximately 20 to 30% encode for membrane proteins (Padan et al 2005). Bacterial
surface proteins have a number of different functions but are principally involved in cellular
homeostasis of the cell in response to the extracellular environment.
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The roles include:
1. Nutrient acquisition and the control of metabolic activities
2. Transport of waste products out of the cell
3. Chelation of iron and other important growth factors
4. Signal transduction of the external environment
5. Colonisation, adherence to surfaces.
6. Communication with other bacteria and quorum sensing
7. Defence against host immune responses, toxins, antibiotics and other antimicrobial
agents
8. Adaption to environmental changes
9. Biofilm formation with the production of extracellular polymeric substances (EPS)
(Cordwell 2006, Benachour et al 2009, Opsata et al 2010, Solis & Cordwell 2011).
As the surface proteins are in close contact with the external environment and have direct
communication with the cytoplasm, they are also targets for potential vaccines and
antibiotics (Solis & Cordwell 2011).
A central role of cell membrane proteins is in the regulation of metabolic pathways. This can
be by signaling into the cell the environmental changes in the amount and availability of
various carbohydrates, oxygen concentration, environmental stresses, exposure to
bacteriocins and toxins (Dressaire et al 2008, Mehmeti et al 2012), with the responses
occurring in complex and strain-dependent manners (Bizzini et al 2010). Any of these
environmental conditions may have a dramatic effect on the growth rate of the organisms as
energy (ATP) is diverted from biomass to survival mechanisms.
The rigid cell wall provided by the heavy cross-linking between peptidoglycan strands in
Gram-positive bacteria creates difficulties when examining protein expression of cell
membrane proteins (Cordwell 2006). Additional proteomic challenges include the relatively
low abundance of membrane proteins compared to cytosolic proteins, the innate
hydrophobic nature of membrane proteins which have poor solubility and the technical
difficulties of recovering pure surface fractions without contamination of cytosolic proteins
(Solis & Cordwell 2011).
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1.2.4 The genomics of E. faecalis
Paulsen et al (2003) reported the complete genome sequence for E. faecalis V583,
identifying 3337 predicted protein-encoding open reading frames (ORFs) with over a quarter
of the genome consisting of mobile or foreign DNA, which are thought to contribute to the
accumulation of drug resistance and virulence factors. As with genomic studies of bacteria,
a large proportion of the genes that have been identified have not been functionally
classified. Many of these however are predicted to encode for membrane-associated proteins
(Cordwell 2006).
E. faecalis has a strong similarity with other low-GC Gram-positive bacteria with a set of
conserved genes that are involved in transcription, translation, protein synthesis and
transport (PTS and ABC transporters) (Paulsen et al 2003).
1.2.5 Pathogenicity island
The cluster of virulence determinants in the pathogenicity island (PAI) of E. faecalis V583
occurs between the ORFs EF0479 - EF0628 and matches the ORFs within E. faecalis
MMH594 (EF0001 to EF0129) reported by Shankar et al (2002). The PAI is approximately
150 kilobases, and varies only slightly between strains V583 and V586 and MMH594
(Shankar et al 2002).
Genes within the PAI code for transposases, transcriptional regulators and also for proteins
that have functions in adaptation to the environment, including survival and virulence
(Shankar et al 2002). The PAI has a great deal of similarity with other low-GC Gram-
positive bacteria and is therefore likely acquired by horizontal gene transfer (Paulsen et al
2003).
Adhesins (aggregation substance and hemagglutinin), DNA-damage inducible proteins, zinc
metalloprotease and components of the phospho-transferase system (PTS) are some of the
known virulence traits that are encoded in the PAI (Shankar et al 2002, Paulsen et al 2003,
Benachour et al 2009). As stated above, E. faecalis V583 is deficient in both the cytolysin
and Esp genes and only a limited number of membrane proteins associated with virulence
have been identified (Maddalo et al 2011).
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1.2.6 The role of E. faecalis in persistent apical periodontitis E. faecalis is a common commensal organism in the human gastrointestinal tract (surviving
the pH extremes of gastric acid) and the oral cavity (Sedgley et al 2004). Its presence in the
oral microbiome of an individual may also reflect the recent ingestion of certain cheeses and
fermented foods where they contribute to flavour and preservation (Sedgley et al 2004,
Zehnder & Guggenheim 2009, Opsata et al 2010).
During the management of endodontic disease, calcium hydroxide is often used as a general
antimicrobial dressing that is spun into the root canal and left for a period of time typically
from one week to a few months. It has been demonstrated that use of this medicament with
a high pH can effect a 99% reduction in viability of E. faecalis V583 (Plutzer 2009).
E. faecalis is more commonly isolated from persistent infections compared to primary
infections (89.6% versus 67.5%) (Sedgley et al 2006) suggesting that it has the capacity to
survive chemo-mechanical procedures (Yap et al 2014) and to survive in a nutrient limited
environment (Sedgley et al 2005).
1.2.7 Carbohydrate uptake
E. faecalis, like most bacteria, are able to utilise a large variety of carbon sources and can
adapt to the changing environment (Bizzini et al 2010). In response to the concentration
gradient of nutrients, the presence of specific carbon sources, and to physical and chemical
stresses, there are a number of sensory-regulator systems that function by phosphorylating
histidine, serine, and aspartate residues on the proteins involved (Postma et al 1993). One of
these systems is the phosphoenolpyruvate (PEP)-PTS, which couples phosphorylation to the
translocation of carbohydrates across the cell membrane. The PEP-PTS is also involved in
the regulation of a number of metabolic pathways (Postma et al 1993).
E. faecalis V583 has over 35 probable PTS-type sugar transporters with the genome
encoding for the uptake of 15 different sugars which are metabolised by the Embden-
Meyerhof and pentose phosphate pathways (Paulsen et al 2003). In addition to PEP-PTS,
the membrane transport for sugar and polyol utilisation can occur through ABC (ATP-
binding cassette transporter family), MIP (major intrinsic protein transporter family), and
Gnt (gluconate transporter family) systems (Paulsen et al 2003). The transport of
carbohydrates by non-PTS systems require ATP to be expended for transport and
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phosphorylation, however the PTS system utilises PEP which provides the energy for uptake
and is energetically equivalent to ATP (Postma et al 1993). As the use of the PTS system is
energy efficient, it helps explain why normally the PTS is used for the uptake of glucose,
fructose or sucrose, and the metabolism of less favourable carbon sources are repressed, e.g.
glycerol, via the ATP-dependent phosphorylation by glycerol kinase (GlpK) to yield
glycerol-3-phosphate (Paulsen et al 2003, Deutscher et al 2006, Bizzini et al 2010).
1.2.8 Stress response
Cellular stress response has been defined as a defence reaction of cells to damage that
environmental forces inflict on macromolecules (Kultz 2005). E. faecalis has a number of
ORFs that have a potential role in responses to oxidative stress, osmotic stress and genes
related to metal-ion resistance and cation homeostasis mechanisms which may play a role in
pH, salt, metal and desiccation resistance (Paulsen et al 2003).
In response to environmental stress, a limited number of proteins, or protein families that are
expressed have been identified (Wang et al 2009). E. faecalis has been shown to up-regulate
certain proteins as part of a stress response to glucose starvation (Giard et al 1997), and the
major heat shock proteins DnaK and GroEL to elevated temperatures, acid, bile salts
(Flahaut et al 1996) and alkaline stress responses (Flahaut et al 1997).
The understanding of the mechanisms by which a small proportion of an E. faecalis
population can survive elevated pH levels remains incomplete and uncertain. It has been
proposed that the toxic effects of high pH are primarily regulated by a membrane proton
pump, which maintains optimal cytoplasmic pH levels (Evans et al 2002). There is however
conflicting evidence on the role of protein synthesis in response to calcium hydroxide. Evans
et al (2002) used chloramphenicol to inhibit protein synthesis and found no effect on cell
survival. They concluded that stress-induced protein production is not important for survival
of E. faecalis at high pH. Distel et al (2002) showed no difference in the protein profiles of
planktonic bacteria that had been subjected to a calcium hydroxide dressing in tooth roots
compared to the inoculum culture. Although only a few cells could be recovered from the
root canals, when they were examined by phase contrast microscopy, the cells were seen to
be embedded in an extracellular matrix (indicative of a biofilm). To extract protein from the
cells, trichloroacetic acid (TCA) was applied to whole cells and the resultant pellet
suspended in x2 SDS-PAGE sample buffer. A separate lysozyme treatment was used to
11
produce cell-free lysates. SDS-PAGE was performed on the cell lysates but there was
difficulty resolving the proteins, as the matrix was only partially soluble with trichloroacetic
acid (TCA)/SDS and lysozyme treatment followed by SDS-PAGE did not produce well-
separated proteins. Apart from a protein smear, only a single band at 32 kDa was resolved.
The authors concluded that the protein smear suggests the presence of active proteases in the
sample and that more research was needed to resolve all the proteins associated with the
putative biofilm.
In contrast, Flahaut et al (1997) found that chloramphenicol treatment of a culture at pH 10.5
resulted in a 9% decrease in alkaline tolerance and that 37 proteins from whole cells were
induced more than two-fold by alkaline stress, with nine proteins being amplified more than
five-fold. Appelbe & Sedgley (2007) investigated the effect on gene expression on E.
faecalis after prolonged exposure to alkaline pH on planktonic bacteria grown aerobically.
The authors identified increased levels of gene transcripts for ftsZ, pbp5, dnaK, napA, tsf,
and groEL between 72 and 120 hours when grown at a pH of 10. Transcripts of ftsZ, a gene
involved in cell division increased by 37-fold. Proteomic studies on the oral bacterium, F.
nucleatum have also identified ftsZ, dnaK (HSP70) and groEL (HSP60) as being regulated
by growth pH (Zilm et al 2007).
1.2.9 Biofilm growth
Biofilms can be defined as bacterial communities that are encased in a matrix of extracellular
polymeric substance (EPS), that are adherent to each other (flocs) and/or to biotic or abiotic
surfaces or interfaces which exhibit altered growth phenotypes (Costerton et al 1995, Donlan
& Costerton 2002). Bacteria within a biofilm display a distinctive phenotype, with an altered
cell surface and metabolic profile and collectively they form an organised community. These
features provide the bacteria with an increased resistance to antibacterial agents and stressful
environments (Costerton et al 1995). Cellular adhesion and the alteration in phenotype seem
to result from the expression of a factor that de-represses a large number of genes which
would not normally be expressed in planktonic culture (Costerton et al 1995).
Biofilm formation can be regarded as a generalised adaptation to many environmental
conditions; this has involved ecological, industrial and anatomical niches and includes an
infected, necrotic root canal system (Nair 2006). Biofilm production has been shown to
increase with an increase in pH (Zilm & Rogers 2007, Hostacka et al 2010). Zilm and Rogers
12
(2007) found that elevated pH (greater than 8.2) produces a shift from a planktonic lifestyle
to the spontaneous flocculation and biofilm formation by F. nucleatum. It is therefore
possible, that the use of calcium hydroxide may induce the formation of E. faecalis biofilms,
which in turn may serve as a protective system to facilitate survival in the high pH conditions
associated with endodontic medicaments such as calcium hydroxide and other potential
antimicrobial agents. Wilson et al (2014) demonstrated that different E. faecalis isolates,
when subjected to sub-minimum inhibitory concentration (MIC) levels of antimicrobial
agents such as sodium hypochlorite (NaOCl), calcium hydroxide, clindamycin, and
tetracycline showed significant clonal variation in biofilm formation. In particular, two
isolates increased biofilm formation in tetracycline and one in the presence of NaOCl.
The protective strategies include comparatively slow growth, the acquisition of large
complex nutrient molecules, export of harmful metabolic waste products, horizontal gene
transfer within and between species and the development of a protective physiochemical
environment to enhance microbial survival (Stewart & Costerton 2001, Socransky &
Haffajee 2002). An additional survival strategy of some bacteria is the ability to transform
into dormant, very small (±0.3 µm) spherical ultra-microbacteria that can be fully
resuscitated many years later (Costerton et al 1995).
The majority of studies in the endodontic literature that investigated the efficacy of irrigants
and medicaments have used bacteria grown in the planktonic phase as a batch culture.
Bacteria grow rapidly in an ideal growth environment but can also be killed relatively easily
when the environment is changed. There is a shift in more recent investigations to examine
the effect of irrigants and medicaments on endodontic pathogens that have been grown as a
biofilm rather than the planktonic phase (Dunavant et al 2006).
Only a limited number of membrane proteins associated with biofilm formation in E. faecalis
have been identified and include major facilitator family transporter (EF0082), Ornithine
carbamoyltransferase (EF0105), Na+/H+ antiporter (EF0402), ABC transporter, ATP
binding/permease protein (EF0790), phosphate import ATP-binding protein PstB 1
(EF1755) and a predicted protease Eep (EF2380) (Maddalo et al 2011).
13
1.3 Proteomics
1.3.1 Definition
The complete genomes for a large number of bacteria have been reported. However, it is the
profile of protein expression that provides bacteria the ability to respond phenotypically to
changes in the environment (Costerton et al 1995).
Proteomics is the study of the complete set of proteins expressed as a result of gene and
cellular function of any organism (Aebersold & Mann 2003, Yang et al 2012). With changes
in genetic and environment factors, and under certain growth conditions only a limited
number of proteins are expressed. The wide range of differential expression makes the study
of proteomics complicated (Wolff et al 2008, Lottspeich 2009). In addition, proteins are
more heterogeneous than gene expression and are prone to a variety of post-translational
modifications (PTM) (Fleron et al 2010) making the dynamic range and complexity of
proteins a challenge to study, especially if quantitative analysis is required (Lottspeich
2009).
1.3.2 Proteomic techniques
As mentioned previously, proteomic analysis of Gram-positive membrane and cell wall
proteins is challenging. Various proteomic methods have been utilised to analyse the
proteome of microorganisms under consideration. One of the most commonly used methods
is to separate the low abundant proteins from the more abundant by the use of
multidimensional gel-based separation steps (Lottspeich 2009). Once the sample has been
separated into protein ‘spots’, they can be enzymatically digested to peptides and then
analysed and identified using mass spectrometry.
Two-dimensional gel electrophoresis (2-DE) has been a popular technique to study bacterial
proteins. In the first dimension, the proteins are separated by isoelectric focusing and then
the use of mass-based sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-
PAGE) in the second (Cordwell 2006, Lottspeich 2009).
A number of limitations of the use of 2-DE in proteomics have been identified. Proteins that
have extremely low or high-molecular weights are often not visible on the gels. With regards
to membrane proteins, they are not particularly soluble in 2-DE buffers, so proteins that are
14
hydrophobic, that are either extremely acidic or alkaline or contain many trans-membrane
domains are often under-represented (Cordwell 2006, Wang et al 2009, Solis & Cordwell
2011). With the advent of genomic sequencing it is possible to predict the proteome in silico
of the whole cell and identify proteins that are positively or negatively hydrophobic in nature.
The grand average of hydropathy (GRAVY) score is a measure of the hydrophobicity of
proteins with a negative GRAVY score being more hydrophilic in nature and more
compatible with 2-DE analysis, whilst for proteins with positive GRAVY scores there is a
higher chance of them having a trans-membrane location. A large number of trans-
membrane domains (greater than three) are difficult to resolve utilizing 2-DE separation
(Cordwell 2006). Gel-based proteomics have additional limitations, including
reproducibility and the inability to reliably quantify protein expression (Lottspeich 2009).
To help overcome some of the inadequacies of gel based techniques, methods have been
developed to enrich bacterial surface proteins which involve differential solubility and
membrane protein enrichment, but these techniques seem to be more successful for Gram-
negative membrane proteins (Cordwell 2006).
Prior to mass spectrometry identification, the proteins under investigation need to be
enzymatically digested into peptides. This is problematic with membrane proteins as they
are surrounded by lipids, which need to be solubilised by detergents before they can be
enzymatically digested. Trypsin is the most commonly used enzyme for protein digestion,
however a further complication is that there are very few cleavage sites for trypsin in
membrane proteins (Wolff et al 2008).
Newer non-gel based strategies have been developed to provide analysis of bacterial
membrane proteins - for example, multi-dimensional protein identification technology
(MudPIT). A cell lysate is subjected to tryptic digest followed by two-dimensional liquid
chromatography; a strong cation exchange in the first dimension followed by reverse-phase
chromatography in the second. The peptides are then identified using tandem mass
spectrometry (MS/MS) by either electrospray ionisation (ESI) or matrix -assisted laser
desorption ionisation mass spectrophotometry (MALDI-MS) (Cordwell 2006). A number of
disadvantages have been acknowledged with MudPIT, including difficulties with
quantification and the under sampling of minor peptides (Lottspeich 2009).
SDS has good solubilising efficiency of integral membrane proteins (IMPs) and therefore
SDS-PAGE has been proposed for separation of bacterial surface proteins. Bands are cut
15
from the gels, subjected to digestion (usually with trypsin) and analysed by liquid
chromatography and tandem mass spectrometry (LC-MS/MS). Whilst this method is good
for protein identification, it is unsuitable for the quantification of protein expression between
two biological samples unless eluted proteins are labelled before enzymatic digestion
(Cordwell 2006).
1.3.3. Mass spectrometry
With the development of protein ionisation methods, and the availability of whole genome
databases, mass spectrometry has become an incredibly powerful tool for the analysis of
complex protein samples (Aebersold & Mann 2003).
Mass spectrometers consist of three main components. The first is an ion source. Ionisation
of the analytes in solutions is achieved using either electrospray ionisation (ESI) or from
dry, crystalline matrix samples with matrix-assisted laser desorption/ionisation (MALDI).
ESI can be used in conjunction with liquid based chromatography, which has proven to be
useful for the analysis of complex structures (Aebersold & Mann 2003). The second
component of the mass spectrometer is a mass analyser used to measure the mass-to-charge
(m/z) ratio and the third component is a detector that registers the number of ions at each m/z
value.
1.3.4 Liquid chromatography tandem mass spectrometry
Peptides produced from the proteolytic digestion of proteins are separated based on their
hydrophobicity by liquid chromatography and enter the mass spectrometer where they are
then ionised (Ryu 2014). The resulting range of peptides, with defined mass-to-charge ratios
(m/z), forms the precursor ion spectra (MS1 spectra). Individual ionised peptides with high
intensities from the MS 1 spectrum are then fragmented into ions to form a resultant MS/MS
spectrum of one peptide. The MS1 spectra are used for peptide quantification whilst the data
from the tandem mass spectra is mainly used for peptide identification (Ryu 2014).
16
1.4 Bioinformatics
Tandem mass spectrometry records peptide sequences based on the mass and intensity of
the fragment ions in the MS/MS spectra. As amino acids, except isoleucine and leucine, have
a known and unique mass, the peptide sequence can be determined either manually or by the
use of automated algorithms which is necessary if the genome sequence is unknown (Ryu
2014). If a suitable protein sequence database is available then a number of programs are
available for identification of peptides by matching the MS/MS spectra against the selected
database (Arrey et al 2010). Following determination of the charge state and mass of the
precursor ion, the enzyme used for digestion and selection of the appropriate data-base,
peptide sequences with theoretical masses that are within a mass tolerance are considered as
theoretical candidate peptide sequence possibilities (Ryu 2014). The theoretical spectrum is
then matched with the observed MS/MS spectra. The theoretical spectra that has the highest
correlation to the observed spectra is assigned the peptide sequence. Common examples of
database-searching software include Sequest and Mascot.
A limitation with the assignment of theoretical to observed peptide sequence spectra is that
it may be incorrect due to “noise” of the MS/MS data, incomplete inclusion of peptides in
databases and incorrect peptide assignments.
Cox and Mann (2008) described a software package that uses a set of algorithms to extract
information from raw MS data. It focuses on the features of mass and intensity of the peptide
peaks in the MS spectra, rather than the MS/MS fragmentation spectra. By improvements in
determining the mass accuracy in the MS data, an increased proportion of fragmentation
spectra can be achieved. The same authors have provided evidence that the false-discovery
rate of peptide and protein identification is stringent using the MaxQuant algorithms (de
Godoy et al 2008).
Protein subcellular localisation can be predicted with bioinformatics techniques on species
whose genome has been sequenced (Zhou et al 2008). For the determination of membrane
protein localisation, tools that calculate the hydrophobicity in helical stretches of
transmembrane proteins give an indication of the anchoring and orientation of the protein. It
also indicates secretion signal domains for transmembrane protein (Solis & Cordwell 2011).
There are many different algorithm tools and many have been incorporated into one pipeline,
17
e.g. Augur (Billion et al 2006), Surface Localisation Extracellular Proteins (SLEP)
(Giombini et al 2010) and LocateP (Solis & Cordwell 2011).
Zhou et al (2008) developed and presented the most detailed and accurate sub-cellular
location (SCL) of Gram-positive bacteria. LocateP combines existing high-precision
subcellular-location identifiers with further improvements in the identification of specific
SCLs such as N-anchored proteins. The authors/designers have designated seven protein
locations for Gram-positive bacteria: intracellular, multi-transmembrane, N-terminally
membrane anchored, C-terminally anchored, lipid- anchored, LPxTG-type cell-wall
anchored, and secreted/released proteins (Figure 3).
Figure 3. LocateP subcellular localisation for Gram-positive bacteria (Zhou et al 2008).
1.5 Membrane proteome of E. faecalis
There have been limited studies on the membrane-embedded proteins of E. faecalis, and
prior to 2011 only nine had been identified (Benachour et al 2009, Bøhle et al 2011),
representing approximately 1.5% of the predicted membrane embedded proteome (Maddalo
et al 2011)
Maddalo et al (2011) increased the recovery of membrane-embedded proteins to 10%. After
using a buffer containing lysozyme, the cells were passed through a french press and the
membrane fractions were solubilised in n-dodecyl -D-maltoside (DDM) and fractions were
18
separated by anion exchange chromatography. Fractions were then collected and subjected
to non-denaturing blue native-PAGE (BN-PAGE) in the first dimension, followed by SDS-
PAGE in the second dimension. Protein spots were excised manually from the gel and the
peptides were analysed by mass spectrometry. The MS/MS data was processed by
qualitative analysis software and all hits were verified with the E. faecalis OG1RF genome
by BLASTN. Bioinformatic analysis of amino acid sequence was carried out with
SignalP3.0 (to identify cleavable signal peptide), SCAMPI (to identify transmembrane
helices) and PRED-LIPO (to identify lipoproteins). The authors identified six proteins
associated with biofilm formation and 11 having a role in virulence.
The technique described by Maddalo et al (2011) appears to be the most comprehensive
study of the membrane proteome of E. faecalis to date. In order to investigate how the
membrane proteins are involved in survival strategies under different environmental
settings, quantitative analysis of membrane proteins would be of particular interest.
1.6 Quantification and labelling
Two-dimensional LC-MS/MS protocols have been useful in mapping surface proteins;
however the technique doesn’t allow comparative analysis between samples. This can be
overcome by using amino acid tags or labels (Cordwell 2006). Reproducible protein
quantification of membrane proteins is problematic and has led to the publication of a
number of protocols, each with their respective strengths and weaknesses (Cordwell 2006,
Solis & Cordwell 2011).
The ICAT protocol covalently labels cysteine residues of protein lysates derived from two
different experimental conditions with either the light (12C) or heavy (13C) stable isotopes of
the same chemical reagent (Gygi et al 1999). Following digestion, labelled peptides are then
combined and analysed by MS. Protein expression is quantified by identifying the light- and
heavy-labelled peptides with the ratio of ion signal intensities or peak areas being directly
related to peptide abundance. A major disadvantage of this method is that the protocol does
not detect proteins that do not contain, or contain only one cysteine residue (Lottspeich 2009,
Cordwell 2006). A further complication is that some peptides can remain bound to the avidin
column and chemical modification can be difficult when dealing with small samples (Ong
et al 2002). The main advantage of using ICAT is that there is an improvement in dealing
19
with proteins that are poorly resolved using 2DE systems such as hydrophobic membrane
proteins.
Isobaric Tag for Relative and Absolute Quantitation (iTraQ) is an alternative protocol to
ICAT. The iTraQ system uses four N-terminal-binding tags, which allows for increased
proteome coverage as proteins with a single or no cysteine residues are also included. The
four isobaric tags are comprised of an amine-specific reactive group, a neutral linker group
and a reporter region (Cordwell 2006). The tags have an identical mass, but contain
differences in mass in their reporter and linker regions. The iTraQ system can accommodate
the comparative analysis of up to four different samples in a single experiment.
Quantification of protein abundance is determined by comparing the relative proportion of
individual peaks in the fragmentation spectra following MS/MS of iTraQ tagged peptides
(Wiese et al 2007).
A significant difference compared to ICAT labelling is that isotopic labelling with iTraQ
tags occurs after enzymatic digestion of the protein. This increases the sample complexity
and generally favours proteins of high abundance (DeSouza et al 2005). Limitations of
iTRAQ include poor detectability of the reporter ions in several types of mass spectrometers
(Paradela et al 2010) and that quantification of iTRAQ labelling is performed in the low
mass range of the MS/MS spectra (Leroy et al 2010).
Isotope Coding Protein Label (ICPL) is a non-isobaric technique used to label primary
amines found in proteins. The N-hydroxysuccinimide (NHS) label is directed to all lysine
residues and protein N-termini, and is used in a top-down proteomic approach. Lysine
residues are more abundant than the cysteine groups and therefore a larger number of
peptides can be quantified compared to the ICAT technique (Brunner et al 2010). Depending
on the ICPL reagent kit used, up to four different proteome states can be analysed in the one
experiment (Brunner et al 2010).
Quantification is determined by comparing the relative abundance of the differentially
labelled peptides, measured as either peak intensity or area (Paradela et al 2010). There have
been very few published papers that have utilised ICPL and none seem to have reported the
investigation of E. faecalis with this labelling technique.
20
The main steps using ICPL for comparative analysis of samples are detection and then
quantification and identification of differentially expressed peptides labelled with different
isotopic markers. For each lysine residue the peptide mass is increased by 105.02, 109.05,
111.04 or 115.07 Da respectively depending on the label used. Depending on the number of
states compared, the peptides consequently appear as doublets, triplets or quadruplets in the
MS-spectra (Brunner et al 2010b). For the analysis of complex samples, an additional
fractionation step (e.g. by 1D-PAGE) is required and the workflow has been described by
Paradela et al (2010) (Figure 4).
Figure 4. Diagram of the standard experimental workflow used in the analysis of ICPL- labelled samples from Paradela et al (2010).
Conventional ICPL protocols label the proteins prior to enzymatic digestion, which means
the samples can be combined to reduce technical variance in downstream processes (Turvey
et al 2014). The disadvantage is that only 60 to 70% of the identified proteins can be
quantified (Fleron et al 2010, Leroy et al 2010). Three reasons have been presented. The
first is that not all lysine containing peptides of a particular protein are sighted in a particular
LC-MS run, probably because the post labelling trypsin digestion results in rather long
peptides (Leroy et al 2010). The second is that ICPL reacts with lysine, which can interfere
with protease digestion (Fleron et al 2010). The third is that only lysine-containing peptides
can be quantified (Leroy et al 2010). Paradela et al (2010) found that only between 54% and
21
64% of Salmonella enterica identified proteins were amenable to quantification and
therefore proposed modifying the technique by labelling at the peptide level (not protein
level) immediately after protein digestion.
Labelling at the peptide level should allow tagging of all peptides as they target the N-
terminal primary amine, which would mean that potentially all proteins could be quantified
(Leroy et al 2010). Fleron et al (2010) and Leroy et al (2010) utilised ICPL labelling at the
peptide level and to our knowledge, this has not been used to investigate protein expression
in E. faecalis.
1.7 Continuous culture in the post-genomic era
Hoskisson and Hobbs (2005) presented an excellent overview on the value of continuous
culture using the chemostat, which was developed simultaneously in 1950 by Monod, and
Novick and Szilard. The chemostat enables the study of bacterial growth in defined physio-
chemical conditions that are constant and separated from the fluctuations present when
bacteria are grown in batch culture. The principle underlying continuous culture is that the
growth rate of an organism, relative to its maximum growth rate is determined by the
availability of a limiting nutrient. Growth medium is pumped into the chemostat and is
balanced by the outflow of depleted medium and a combination of living and dead cells.
Chemostat usage was prevalent in the 1960s and became widely accepted as a way of
culturing cells under conditions which closely resembled the in vivo environment. More
recently continuous culture has experienced resurgence when utilizing techniques such as
proteomics, transcriptomics and metabolomics as they require growth in a stable
environment where single growth parameters can be manipulated and others held constant.
The use of a chemostat enables the acquisition of reliable biological samples and is ideally
suited to proteomic studies investigating biological responses to specific growth conditions.
1.8 Overall aims of the study
Previous studies investigating the stress response of E. faecalis to high pH have focused
predominantly on the transcription of generalised stress response genes coding for
intracellular proteins and the response of proton/nutrient pumps. An understanding of
changes in cell membrane protein expression at alkaline pH may help to elucidate other
mechanisms for adaptation and survival associated with endodontic therapy. The aim of this
22
study was to grow E. faecalis in continuous culture at pH 8 and pH 11, using conditions
appropriate to an endodontically treated root canal and compare the phenotype and
differential membrane protein expression. ICPL was used in conjunction with MS/MS for
identification and quantification of up- and down regulated proteins.
23
Chapter 2. Experimental Investigations
2.1 Effect of alkaline pH on growth rate and phenotypic expression of E. faecalis V583
2.1.1 Abstract
The mechanisms by which E. faecalis can persist in a highly alkaline environment are poorly
understood. The majority of studies investigating survival use bacteria grown in batch
culture, which does not replicate the growth rate in the organism’s natural environment. The
maximum growth rate was determined for E. faecalis V583 at pH 8 and pH 11 and with the
use of a chemostat, an imposed growth rate was set at one-tenth of the relative maximum
growth rate for each pH condition. After growth equilibration was achieved in the chemostat,
samples were harvested and prepared for SEM analysis. The maximum growth rate
decreased from 1.16 hours at pH 8 to 7.7 hours at pH 11. At pH 11 there was evidence of
spontaneous biofilm production.
Keywords: Enterococcus faecalis, Alkaline pH, Biofilm
2.1.2 Background
Bacteria inhabit a wide range of environment conditions, but ultimately spend most of their
time in a starving or non-growing state (Hecker & Volker 2001), and many have the capacity
to adapt to changing conditions. E. faecalis is a commensal organism found in the human
oral cavity, gastro-intestinal tract and vagina. Within the gastro-intestinal tract it survives an
acidic pH, but it is also found to persist in root canals that have been treated with the strongly
alkaline medicament calcium hydroxide and with a limited nutrient supply (Distel et al 2002,
Siqueira & Rôças 2004).
Expression of intracellular, membrane-associated and extracellular proteins play a crucial
role in the response to a changing extracellular environment, but there is conflicting evidence
on the role of protein expression in response to calcium hydroxide. The majority of the
proteins identified to be associated with a response to an increase in pH are intracellular and
the role of membrane-associated and extracellular proteins remains unclear (Flahaut 1997,
Evans 2002, Appelbe & Sedgley 2006, Zilm et al 2007).
24
The majority of studies in the endodontic literature that have investigated the efficacy of
irrigants and medicaments have used bacteria grown in the planktonic phase in batch culture.
Bacteria replicate by binary fusion, which is a form of asexual reproduction producing two
daughter cells. In a closed system, four phases of growth have been determined, namely the
lag phase, the log phase, the stationary phase, and the final death phase. The growth through
these phases is usually reliably reproducible when faced with a new nutrient rich
environment. The lag phase is characterised by initial growth that is slow as the bacteria
adapts to the environment and prepares for rapid growth (Prats et al 2006).
The log phase or exponential phase is when the most rapid replication is undertaken and the
rate of division is termed the growth rate, with the time taken for the population to double
being termed the generation time (td). The exponential phase continues until the nutrient
source starts to become depleted and thereby limits rapid growth. This latter phase is termed
the stationary phase in which there may be induction of stress proteins in an attempt to adapt
to the restricted conditions (Hecker & Völker 2001).
The final phase is death, when the bacteria ultimately die. Under ideal conditions growth
rate is high with cellular division occurring rapidly but under conditions of nutrient
depravation, reproduction is slowed down. In extreme conditions it is thought that some
bacteria, including E. faecalis may even enter a viable but non-cultivatable state (Portenier
et al 2003).
The transition between growth phases (lag, log and stationary) in a closed system involves
sudden differences in the environment with each change dramatically affecting the
bacterium’s chemical composition, structure and functionality (Keevil et al 1987). Genomic
or proteomic studies on bacteria in a closed system are virtually impossible as gene
expression are likely to be growth phase dependent.
Alternatively, continuous culture in a chemostat more closely resembles growth in the
organism’s natural environment as the growth rate is dependent upon a limiting nutrient and
physiological conditions such as oxygen levels, pH can be tightly controlled. Steady state is
achieved in a chemostat when bacteria grow at a constant rate in a constant environment
(Hoskisson & Hobbs 2005). If a single growth parameter is changed, such as nutrient supply,
25
pH or oxygen level, the steady state of the culture will re-establish to reflect the changed
environment.
In a closed system the td during log phase is fixed but in continuous culture the specific
growth rate (μ) becomes variable and can be set to closely represent the in vivo environment.
At steady state, μ is numerically equal to the Dilution rate (D) of the growth medium in the
culture vessel (Keevil et al 1987). The dilution rate is a function of the flow rate of the
nutrient medium and the volume of the culture vessel, such that:
Td= Ln2/µ
At steady state, D=µ and therefore Td = Ln2/D
D (h-1) = Flow rate (mLhr -1)/ Volume of culture vessel (mL)
The purposes of this study were two-fold. The first was to determine the effect of an
increased pH on the maximum growth rate of E. faecalis V583 when grown in a chemostat,
and the second was to investigate the phenotypic changes when the culture was grown at a
tenth of the relative maximum growth rate at pH 8 and pH 11.
2.1.3 Methods
E. faecalis ATCC V583 strain was purchased from Cryosite (NSW, Australia) and
maintained on Columbia blood agar (Oxoid, Victoria, Australia) at 37°C. Culture purity was
periodically checked by culturing onto Bile Aesculin agar (Oxoid). E. faecalis was grown
by continuous culture using a model C30 BioFlo Chemostat (New Brunswick Scientific,
Edison NJ USA) with a culture volume of 365 mL. Growth was initiated by inoculating the
growth chamber containing Todd Hewitt Broth (THB) (92 g/4 L) with a 24 hour THB-grown
batch culture of the organism. THB was pumped through the chemostat and growth pH was
maintained at 8.0 by the automatic addition of 2 M KOH or 2 M HCl using a Fermac 260
pH controller (ElectroLab, Tewkesbury UK). Half the volume of the culture vessel was then
removed and quickly re-filled with THB. When the culture temperature had stabilised and
was also maintaining the controlled pH level, 10 mL aliquots were removed each hour and
the biomass determined by measuring the optical density (OD560 nm). The OD readings were
log transformed against time and the maximum growth rate (μmax) determined. Duplicate
replicates were performed for pH 8 growth conditions.
26
After the µmax was determined at pH 8, the medium flow rate was set at 0.1 rel (21.5 mL/h-
1) giving a dilution rate of 0.059 h-1 and an estimated generation time of 11.69 hours which
is typical of natural ecosystems (Hamilton et al 1979). After equilibration (ten generations),
10 mL cell culture samples were harvested daily over a four week period and pooled. The
pH in the chemostat was then incrementally increased to 11. After a period of approximately
one month (~60 generations) and using the same protocol as used for pH 8, attempts were
made to determine the maximum growth rate whilst maintaining the controlled pH level.
The procedure was repeated numerous times but there were large variations in the growth
curves and the exponential growth phase could not reliably be determined.
As an alternative, 30 mL of the THB growth medium was transferred to sterile tubes,
adjusted to pH 11 with the addition of KOH and then inoculated with 3 mL of E. faecalis
V583 recovered from the chemostat in which the growth conditions had been maintained at
pH 11 for approximately six weeks. 1 mL aliquots were removed each hour and the biomass
determined by measuring the optical density (OD560 nm). The maximum growth rate was
determined as above in triplicate.
Bacteria grown at each pH were harvested by centrifugation (6,000x g), at 4°C for 20
minutes. 1 mL of each sample was used for SEM analysis. Standard SEM sample processing
was undertaken. After the samples had undergone critical point of drying they were coated
with carbon and gold and analysed under a SEM (Philips XL 30, field emission SEM;
Eindhoven, The Netherlands).
2.1.4 Results
2.1.4.1 pH 8
The maximum mean generation time for E. faecalis grown in batch culture in THB at pH 8
was 1.27 hours and 1.05 hours, resulting in an average of 1.16 hours.
The dilution rate for maximum growth (μmax) was determined by the following equation
Td = ln2/D, where Td is the doubling time and D the Dilution rate.
D= 0.69/1.16
= 0.59 h-1 (μmax)
27
The dilution rate was set to 0.1 μrel (.059 h-1). The flow rate (F= mL/h) in a chemostat
chamber of 365 mL was determined by:
D = F/vol
μmax D = 0.59 h-1
0.1 μrel D = 0.059 h-1
F = 0.059 x 365 mL(volume of chemostat)
= 21.5 mL/hr-1
The generation time was determined by the following equation:
Td = ln2/D
0.69/0.059 h-1 = 11.69 hours
Steady state was achieved over ten generations (116.9 hours) before harvesting cells for
analysis.
A SEM of bacterial cells grown at pH 8 is shown in Figure 5. The cocci shaped cells show
little evidence of an extracellular matrix.
28
Figure 5. SEM of E. faecalis grown at pH 8 in continuous culture with an imposed generation time of 12 hours (0.1 μrel).
2.1.4.2 pH 11
The mean generation time, for E. faecalis grown in batch culture in THB at pH 11 was 7.7
hours for all replicates (Appendix 1).
Using the same equations as for pH 8, the dilution rate at maximum growth (μmax) was .09
h-1. Growth at 0.1 μrel, therefore was indicative of a generation time of 77 hours. Steady state
was achieved after 10 generations (770 hours) and the flow rate set to 3.3 mL/hr-1 (365 mL
working volume of chemostat x 0.009h-1).
29
2.1.4.3 Phenotypic differences
An observation of note was that that chemostat chamber became coated with a biofilm at pH
11. SEM analysis (Figure 6) revealed round cocci cells surrounded by an extracellular
matrix.
Figure 6. SEM of E. faecalis grown at pH 11 in continuous culture with an imposed generation time of 77 hours (0.1 μrel).
2.1.5 Discussion
During balanced growth, the cell’s composition, size, metabolism and protein expression
respond to changes in growth rate (Mehmeti et al 2012). Many publications examining
protein expression in bacteria use an overnight planktonic culture, which in many cases does
not represent growth of the organism in vivo. Many bacteria grow in nature as a biofilm,
however the heterogeneous physiological state of biofilm inhabitants makes it difficult to
quantify changes in protein expression in response to external stimuli. In an attempt to mimic
environmental conditions, a relative growth rate (μrel) can be determined and used to provide
an indication of gene expression in natural habitats. Comparisons of protein expression
which are dependent upon environmental conditions such as pH can then be investigated.
When a tooth is undergoing endodontic therapy the chemo-mechanical phase will limit the
30
nutrient availability to microorganisms in the canal and those that have penetrated the
dentinal tubules by removing necrotic pulp tissue. The additional application of a calcium
hydroxide dressing will initially create an alkaline environment (~pH 12) but as the
medicament diffuses through dentine, the pH is buffered and reduces to ~pH 9 to 10
(Nerwich et al 1993, Siqueira & Lopes 1999).
The maximum growth rate of E. faecalis at pH 11 was approximately eight times lower than
when grown at pH 8. The decreased growth rate is an indication of a stressful environment
in which greater metabolic energy is required for cell survival whilst genes involved in cell
division are repressed (Padan et al 2005). In order to represent a more realistic in vivo
environment within a root canal, the supply (flow) of THB was reduced to give a relative
growth rate of one-tenth the maximum growth rate for each pH condition. This was an
arbitrary parameter as the actual in vivo growth rate within a root canal is unknown. However
the mean generation time for dental plaque ranges from 3 to 4 hours for developing
supragingival plaque and 3 to 14 hours for organisms colonizing tooth fissures (Socransky
et al 1977, Hamilton et al 1979).
At pH 11 there was phenotypic evidence of clumping of the cells into flocs (a variant of
biofilm formation) with coatings around the cells consistent with the production of
extracellular polymeric substances (EPS). Survival of E. faecalis has been shown to decrease
to 0.001% at pH 11 (Appelbe & Sedgley 2007) and in combination with the spontaneous
production of EPS, which would contribute to optical density readings, helps explain the
difficulty trying to establish the μmax at pH 11 within the chemostat.
There are numerous adaptations of alkali-tolerant bacteria that facilitate their ability to grow
at alkaline pH including cation/proton transporters, proton capture at the cell surface, acid
production from the metabolism of certain amino acids and sugar fermentation, and
modifications to the secondary cell wall polymers (Padan et al 2005). Of the survival
strategies, the cation/proton antiporters are reported to play the dominant role in alkali-
tolerant and extremely alkaliphilic bacteria (Padan et al 2005) and is perhaps the most
important survival strategy for E. faecalis (Evans et al 2002). The import of H+ ions into the
cell provides two main functions; the first is to lower the cytoplasmic pH and the second is
to provide the proton motive force required for ATP generation by ATP synthase.
31
2.1.6 Conclusion
The maximum growth rate was determined and found to be different for E. faecalis grown
at pH 8 and 11. Growth at pH 11 significantly reduced the generation time compared to
growth at pH 8. The extreme alkaline conditions produced a shift towards spontaneous
biofilm formation which was consistent with the appearance of an extracellular matrix. The
exact mechanism(s) by which E. faecalis is able to adapt and survive this extreme alkaline
pH, in particular the membrane proteins remains poorly understood and warrants further
investigation.
32
2.2 1D SDS-PAGE and in-solution proteomic analysis of E. faecalis membrane proteins: Pilot study
2.2.1 Abstract
The study of Gram-positive bacterial membrane proteins is hampered by their
hydrophobicity, extreme iso-electric points and relatively low abundance compared to
cytosolic proteins. The aim of this pilot study was to investigate two protocols to recover
and optimise membrane protein identification. Using E. faecalis V583 grown in batch
culture, cells were harvested by centrifugation and then lysed with a French Press. The cell
envelope was separated by centrifugation and dissolved in SDS buffer. The first approach
utilised in-solution digestion with typsin. In the second approach, 1D SDS-PAGE was used
with two prominent bands cut from the gel and then subjected to in-gel tryptic digestion.
LC-MS/MS was performed on the peptides from both approaches, The majority of proteins
identified from both protocols were identified as having a cytoplasmic location. The results
highlight the need to optimise the resolution of the membrane protein fraction to increase
membrane protein purity prior to identification by mass spectrometry
Keywords: Enterococcus faecalis, 1 D SDS-PAGE
2.2.2 Background
E. faecalis is a Gram-positive facultative anaerobic bacteria, and as such contains a cell
envelope that encapsulates the cytoplasmic proteins. The cell envelope consists of a
cytoplasmic membrane in which peripheral and transmembrane proteins are embedded and
the cell wall, which is comprised of a peptidoglycan layer.
Cell wall anchored proteins transcend the peptidoglycan layer and have external cell
projections. Lipoproteins similarly transcend the peptidoglycan layer but also extend to the
cytoplasmic membrane. Peripheral proteins can be identified on the internal surface of the
cytoplasmic membrane, whilst cell wall associated proteins are found on the external surface
of the cytoplasmic membrane and the external surface of the peptidoglycan layer.
The study of cell surface proteins is difficult due to the heavy cross-linking between
peptidoglycan strands which provides a rigid surface, the relative low abundance compared
to cytosolic proteins, their poor solubility, intrinsic hydrophobic nature, alkaline iso-electric
33
points and problematic isolation of pure surface fractions (Nandakumar et al 2005, Cordwell
2006, Solis & Cordwell 2011, Yang et al 2012)
The fundamental stages in the isolation of membrane-associated proteins include growth of
the bacteria, separation of the membrane proteins from the intracellular proteins, digestion
into peptides before analysis by mass spectrometry (MS).
The aim of this pilot study was to evaluate the application of mechanical cell lysis of E.
faecalis using a French Press, separation of the membrane fraction with centrifugation,
recovery of the membrane proteins with either in solution enzymatic digestion or separation
with 1D SDS-PAGE, followed by liquid chromatography tandem mass spectrometry for
protein identification.
2.2.3 Methods
2.2.3.1 Growth conditions
E. faecalis ATCC V583 strain was purchased from Cryosite (NSW, Australia) and
maintained on Columbia blood agar (Oxoid, Victoria, Australia) at 37°C. Culture purity was
periodically checked by culturing onto Bile Aesculin agar (Oxoid). 1000 mL sterile Todd
Hewitt Broth (THB) was inoculated with 1 mL of an overnight broth and incubated at 37°C
for 3 days. Bacteria were harvested by centrifugation (6,000x g), at 4°C for 20 minutes. Cells
were washed twice with saline (0.9% w/v) at 4°C and cells were finally resuspended in 12
mL of ice cold saline. Cells were lysed by two passes (60,000 kPa) through a SLM Aminco
French Press (Thermo Fisher Scientific). Endogenous proteinase activity was controlled
during lysis by the addition of 100 L of bacterial protease inhibitor cocktail (Sigma-
Aldrich, St. Louis MO USA). Nucleic acids were then degraded by the addition of
Deoxyribonuclease I (2000 Units), Ribonuclease A (1000 Units) and MgCl2 (50 mM) and
incubated on ice for 60 minutes. Intact cells were removed by centrifuging twice (8,000x g
at 4C for 5 minutes) and removing the supernatant.
The cell envelope and cytoplasmic contents were separated by centrifugation (15,000x g)
for 20 minutes at 4C. The cell envelope proteins were dissolved in 0.5 mL SDS 4x buffer
with agitation using a 1 mL pipette for 15 minutes. The sample was boiled for 5 minutes,
allowed to cool then centrifuged (12,000x g) for 5 minutes at room temperature. 400 µL of
34
supernatant was then removed and 1.2 mL of Milli Q H2O added. The protein concentration
was determined using a RCDC kit (BioRad, Hercules CA USA).
2.2.3.2 In solution digestion
An aliquot containing 1 mg protein in 1 mL of SDS buffer was prepared for MS analysis
following trypsin digest with reduction and acylation as per the following protocol
(performed by staff at the Adelaide Proteomics Centre).
The sample was precipitated with 6 mL of ice-cold acetone and centrifuged (15,000x g). The
pellet was then resuspended in 0.5 mL Guanidine/Tris/EDTA buffer and sample was then
processed by:
1. 0.5 mL of sample was added onto a VivaspinTM concentrator (Vivaproducts,
Massachusetts, USA) and reduced to a volume of about 80 µL.
2. Reduced with 5 µL 1 M dithiothreitol (DTT) in 100 mM ammonium bicarbonate.
3. Alkylated with 20 µL of 0.55 M iodoacetamide (IAA) (Sigma-Aldrich).
4. Digested with 20 µg of sequencing grade modified trypsin (Promega Corporation,
Madison, Wisconsin, USA) in 50 mM ammonium bicarbonate
The sample peptides were extracted and reduced by vacuum centrifugation to approximately
5 µL then resuspended with 50 µL 0.1% FA in 3% Acetonitrile (ACN).
2.2.3.3 1D SDS-PAGE
40 uL of sample (1.0 mg mL-1) was loaded onto a Criterion TGX Precast gel (BioRad) and
separation performed at 200 V constant voltage. After completion, two prominent resolved
protein ‘bands’ were cut from the gel and subjected to in-gel tryptic digestion. Briefly, the
samples were washed in 500 µL of 50 mM ammonium bicarbonate (NH4HCO3) and
processed as follows:
1. Destained with 50 mM ammonium bicarbonate in 30% ACN.
2. Reduced with 0.5 µmol DTT in 100 mM ammonium bicarbonate.
3. Alkylated with 2.75 µmol IAA in 100 mM ammonium bicarbonate.
4. Digested with 100 ng of sequencing grade modified trypsin (Promega) in 5 mM
ammonium bicarbonate in 10% ACN
5. Resulting peptides were extracted using 3 washes of 1% formic acid (FA) in water, 1%
FA in 50% ACN and 100% ACN respectively.
35
The volumes of the resulting peptide extracts were reduced by vacuum centrifugation to
approximately 1 µL then resuspended with 0.1% FA in 2% ACN to a total volume of ~10
µL.
2.2.3.4 Liquid chromatography - Orbitrap tandem mass spectrometry (LC MS/MS) of protein samples
LC MS/MS was performed using the Ultimate 3000 RSL HPLC (Dionex, Germany) and the
LTQ Orbitrap XL ETD mass spectrometer (Thermo Fisher Scientific) coupled via the
Nanospray Source I (Thermo Fisher Scientific). The HPLC and Mass Spectrometer were
connected using a Nanospray Source I (Thermo Fisher Scientific) and a nanospray emitter
(New Objective, MA). The column used was Acclaim® PepMap RSLC 75 µm x 15 cm
(Dionex) as the analytical column and Acclaim® PepMap RSLC 75 µm x 2 cm as the
enrichment column.
Two µL of sample was loaded on the enrichment column at a flow rate of 3 µL min-1 in
Mobile Phase A (0.1% FA in 2% v/v ACN) and resolved with 2 to 40% B gradient of Mobile
Phase B (0.1% FA in 80% w/v ACN) over 30 minutes at a flow rate of 300 nL min-1.
Ionizable species (300 < m/z < 2000) were trapped and the six most intense ions eluting at
the time were fragmented by collision-induced dissociation (CID) or electron transfer
dissociation (ETD) dependent on charge state and mass-to-charge ratio (m/z). The following
data-decision tree was used for selecting precursors for ETD instead of the default CID
fragmentation:
Charge state 3 and m/z < 650
Charge state 4 and m/z < 900
Charge state 5 and m/z < 950
Active exclusion was used to exclude a precursor ion for 5 seconds after selection for
fragmentation.
2.2.3.5 Data analysis
Data analysis was performed using the XCalibur software (Version 2.0.7, Thermo Fisher
Scientific). MS/MS spectra were extracted and submitted to the Mascot search engine using
36
Proteome Discoverer (Version 1.3, Thermo Fisher Scientific). Protein localisation was
determined using PSORT.
2.2.4 Results
Identification of the three membrane proteins from the most highly resolved 1D SDS-PAGE
gel bands were all predicted as having a cytoplasmic localisation. The majority of the 65
identified proteins from the in-solution digest (Appendix 2) were also predicted to have a
cytoplasmic location. Due to the low number of identified proteins obtained with both
protocols and the propensity for a cytoplasmic localisation, no further analysis of these
proteins was conducted.
2.2.5 Discussion
For species in whose genome has been sequenced, high-throughput computational methods
have been developed to predict the subcellular localisation of proteins (Zhou et al 2008).
Combining the predicted locations from the 1D-SDS-PAGE bands and the in-solution
samples, it became readily apparent that before any further proteomic studies were
conducted, it was necessary to optimise the membrane protein fraction using alternative
protocols to increase membrane protein purity.
Future experiments were therefore directed at pre-fractionation of the proteome so that cell
wall and membrane proteins could be enriched and specifically characterised. Similar
techniques have been used for secretomics, phosphor-proteomics, and metallo-proteomics
(Yang et al 2012).
Nandakumar et al (2005) investigated various cell lysis and solubilisation methods to
enhance proteomic analysis of membrane and cell wall associated proteins from
Staphylococcus aureus. The authors used the enzyme lysostaphin to lyse bacterial cells
instead of mechanical disruption which can cause heating of the sample and is prone to
cytosolic protein contamination. It also reduces multiple ultracentrifugation steps which can
result in a loss of low abundant proteins. Following lysostaphin treatment, solubilisation of
membrane proteins using a combination of urea, thiourea, amidosulfobetaine 14 (ASB 14)
and dithiothreitol (DTT) yielded the best sample range for subsequent 2DE and mass
spectrometric analysis (Nandakumar et al 2005). 2DE however has severe limitations for
37
investigating the predominantly hydrophobic membrane proteins, due to limited solubility
and their abundance is often too low to be readily observed (Solis & Cordwell 2011).
Alternative techniques used for producing surface-enriched protein preparations have been
described by Solis and Cordwell (2011).
2.2.5.1 Cell wall digestion
Enzymatic digestion of the peptidoglycan wall, under isotonic conditions allows the
protoplast to remain intact and for the selective release of surface proteins (Figure 7A).
2.2.5.2 Cell surface shaving
Cell surface-exposed proteins are removed by enzymatically shaving the surface (Figure
7B). Released peptides are then subjected to mass spectrometry (Cordwell 2006) to identify
and quantitate proteins. A major advantage is that there is little or no contamination from
cytoplasmic proteins (Rodríguez-Ortega 2006).
Proteolytic digestion of the exposed regions of membrane proteins from intact cells utilises
proteases, for example trypsin, that are site-specific over a short incubation period. All
surface proteins, including membrane-embedded proteins that traverse the cell wall are
targeted. It is important that the cell does not rupture and are therefore kept under isotonic
conditions that limit osmotic disruption. False positive strategies have been employed to
help reduce the number of cytosolic contaminants (Solis & Cordwell 2011).
Benachour et al (2009) used enzymatic treatment with mutanolysin or in vivo trypsinolysis
to extract the outer surface proteins from E. faecalis JH2-2, and then analysed them by gel
electrophoresis or with liquid chromatography-electrospray ion trap tandem mass
spectrometry. The authors found eight secreted proteins and 38 cell surface proteins. Two of
the proteins were common to both groups and 35 of the 44 proteins had signal peptide or
transmembrane domains consistent with an extracellular localisation. The authors concluded
that the in vivo trypsinolysis could be amenable to micro-preparative separations allowing
high-throughput analysis to identify bacterial membrane proteomes. Conventional trypsin
treatment led to cell lysis, but after several attempts the authors found that trypsin digestion
in ammonium bicarbonate (pH 8) containing 0.5 mol L-1 sucrose for cells in the stationary
phase worked well.
38
2.2.5.3 Cell surface labelling
Impermeable tags or other molecules such as Cy dyesTM and biotin are used to bind to
surface-exposed proteins on intact cells, but not to the inner components of the cell (Figure
7C). The membrane-embedded proteins are also not targeted. The protein fractions are then
extracted and the tagged proteins identified by fluorescent imaging using differential in-gel
electrophoresis (DIGE) or affinity chromatography. Biotin has a low molecular weight and
has a high specificity for avidin, which allows for an easy and selective purification process
(Solis & Cordwell 2011). However extreme care must be taken not to induce cell lysis or to
affect cell permeability as all of the cytoplasmic proteins will be labelled (Solis & Cordwell
2011).
Surface labelling coupled to strong cation exchange (SCX) chromatography and LC-MS/MS
is an emerging technology in the identification of cell envelope proteins.
Figure 7. Summary of cell envelope fractionation techniques from Solis & Cordwell (2012). (A) Cell wall digestion for Gram-positive organisms, (B) Cell surface shaving for Gram-positive organisms, (C) Cell surface labelling for Gram-positive and Gram-negative organisms, (D) Membrane precipitation/extraction for Gram-positive and Gram-negative morphologies, (E) Membrane shaving applicable to Gram-positive or Gram-negative organisms.
Integral membrane proteins have a number of functions including initiation of signal
transduction pathways and detection of external environment changes. This group of
39
proteins is particularly difficult to analyse as they are integrated with the membrane and have
poor solubility. The following techniques have been developed:
1. GeLC-MS/MS
SDS is an effective detergent to dissolve highly hydrophobic membrane proteins, but this is
not compatible with 2-DE. A label-free quantitative proteomic strategy termed GeLC-
MS/MS has been developed in which membrane proteins can be separated by 1-D SDS-
PAGE and then bands of equal size can be excised, digested, purified and analysed by LC-
MS/MS (Solis & Cordwell 2011, Yang et al 2012). The SDS denatures all proteins in a cell
lysate, but must then be removed before downstream analysis methods. Combinations of
other separation or enrichment techniques can be used in conjunction with GeLC-MS and
biotinylation. The disadvantages of this technique are poor reproducibility and resolution
(Yang et al 2012).
2. Sodium carbonate precipitation
Membranes have traditionally been enriched by differential centrifugation or by
precipitation by sodium carbonate (pH~11), which allows solubilisation of peripheral, and
integral membrane proteins in strong detergents. In contrast to cell-wall digestion, cell-
surface shaving and cell-surface labelling, the cells are lysed and then the membrane fraction
enriched by precipitation with sodium carbonate (Solis & Cordwell 2011). Following
precipitation, detergents such as SDS or zwitterionic detergents can be used to extract
proteins. SDS is extremely effective for solubilising proteins, but it is not compatible with
isoelectric focusing (IEF), however it is compatible with 1-D SDS-PAGE (Solis & Cordwell
2011).
3. Proteinase-K/chymotrypsin shaving of membranes
Membrane shaving is different to cell surface shaving in that the membrane has been
previously extracted and purified, and all proteins within the membrane are targeted rather
than just surface exposed proteins. Membrane shaving can be achieved with the use of
proteases such as chymotrypsin, pronase or proteinase-K, which allow mild digestion in the
presence of detergents and high surface coverage by releasing membrane-embedded
peptides. There is no need for membrane solubilisation and the peptides that are generated
can be directly analysed by LC-MS/MS (Solis & Cordwell 2011).
40
Wolff et al (2008) investigated the efficacy of three fractionation approaches and found that
a combined approach of 1D SDS-PAGE and membrane shaving produced the highest
recovery of membrane associated proteins.
2.2.6 Conclusion
Membrane-embedded proteins are especially difficult to study due to the innate
hydrophobicity of the transmembrane domain. Recovery of the E. faecalis membrane
proteins utilizing in-solution enzymatic digestion or separation with 1D SDS-PAGE
followed by liquid chromatography tandem mass spectrometry for protein identification was
hampered by ‘contamination’ with cytosolic proteins. Searching the proteomic literature, a
number of fractionation protocols have been used to enrich for integral membrane proteins
with membrane shaving showing the greatest promise (Wolff et al 2008). Optimisation of
membrane protein isolation for E. faecalis requires verification before being used on
precious experimental samples.
41
2.3 Isolation and identification of E. faecalis membrane proteins using membrane shaving and one-dimensional SDS-PAGE coupled with mass spectrometry
2.3.1 Abstract
E. faecalis is a significant nosocomial pathogen which is able to survive in diverse
environments and resist killing with antimicrobial therapies. The expression of cell
membrane proteins play an important role in how bacteria respond to environmental stress.
As such, the capacity to identify and study membrane protein expression is critical to the
understanding of how specific proteins influence bacterial survival. E. faecalis V583 was
grown in batch culture and the cells were lysed with a French Press. The membranes were
fractionated by ultracentrifugation, homogenisation in carbonate buffer, and then by either
membrane shaving or by 1Dimensional-SodiumDodecyl Sulfonic acid-Poly Acrylamide Gel
Electrophoresis (1D SDS-PAGE), coupled with Liquid Chromotography-Electro Spray
Ionisation mass spectrometry (LC-MS). Two hundred and twenty two membrane-associated
proteins were identified which represents approximately 24 percent of the predicted
membrane-associated proteome. One hundred and seventy were isolated using 1D-SDS-
PAGE and 68 with membrane shaving, with 36 proteins being common to both techniques.
Ninety seven percent of the proteins identified by membrane shaving were membrane
associated with the majority being integral membrane proteins (89%). The majority of
proteins identified with known physiology are involved with transportation across the
membrane. The combined 1D-SDS-PAGE and membrane shaving approach produced the
greatest number of membrane proteins identified from E. faecalis to date.
Keywords: Enterococcus faecalis, Proteomics, 1D-SDS-PAGE, Membrane shaving, Mass
spectrometry
2.3.2 Background
The cytoplasmic membrane of a bacterium plays a crucial role in homeostasis and the ability
to invade, adapt and respond to the extracellular environment. Membrane proteins that are
expressed have a wide variety of functions including nutrient uptake, response to
environmental stress, adhesion, virulence, biofilm formation and antibiotic resistance
(Paulsen et al 2003, Bourgogne et al 2008). Integral membrane proteins are also important
42
in the initiation of signal transduction pathways, allowing the bacterial cell to adjust its
physiology to changes in the external environment (Solis & Cordwell 2011).
Enterococcus faecalis is a Gram-positive facultative anaerobe that is resistant to vancomycin
and as such represents a significant nosocomial burden. E. faecalis is used within the food
industry in certain cheeses and sausages and is a commensal organism within the
gastrointestinal tract (Fisher & Phillips 2009, Zehnder & Guggenheim 2009). However, it
has also been recovered from patients suffering endocarditis, bacteraemia, urinary tract
infections, wound infections and meningitis (Richards et al 2000). It is often present in teeth
with root canal fillings that have evidence of persistent infection (Siqueira & Rôças 2004).
E. faecalis demonstrates a remarkable ability to survive a wide range of environmental
conditions including the extremes of gastric acid and high pH used in dental medicaments
(Nakajo et al 2006). The complete genome sequence has been published by Paulsen et al
(2003) but only a fraction of the total 781 (approximately) membrane proteins have been
isolated and identified (http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py). Nine
membrane embedded proteins were identified in E. faecalis V583 by Bøhle et al (2011) and
64 in E. faecalis OG1X by Maddalo et al (2011), the latter being the most comprehensive
study of the membrane proteome to date. The diversity of function makes membrane proteins
potential targets for the development of drugs or medicaments, which may improve the
efficacy of current therapeutic strategies.
Proteomic studies of cell membrane proteins are hampered by their low abundance and the
hydrophobic nature of the trans-membrane domain (Speers et al 2007). Standard proteomic
approaches combining 1- or 2D-polyacrylamide gel electrophoresis (PAGE) and mass
spectrometry generally use strong chaotropic agents or strong detergents (traditionally SDS)
to solubilise membrane proteins which are ultimately poorly represented against highly
abundant cytoplasmic proteins. A number of fractionation protocols have therefore been
used to enrich for bacterial membrane proteins before identification by mass spectrometry
(Solis & Cordwell 2011).
Enrichment of membrane proteins is an obvious approach to significantly reduce sample
complexity and improve the resolution of the bacterial membrane proteome. This is typically
achieved by isolation of membranes following cell lysis and by differential centrifugation or
precipitation with cold sodium carbonate. Sodium carbonate linearises and precipitates
membranes which then allows solubilisation of peripheral and integral membrane proteins
43
in detergents (Solis & Cordwell 2011). These can then be separated using techniques such
as anion exchange chromatography (Maddalo et al 2011) and 1D-SDS-PAGE (Wolff et al
2008). While membrane enrichment reduces sample complexity, the associated downstream
separation steps can still produce losses of poorly solubilised and/or highly hydrophobic
membrane proteins. Proteins containing multiple transmembrane domains are particularly
difficult to recover and are rarely identified, if at all (Wolff et al 2008). Accordingly,
methods that reduce sample complexity without introducing sample-hungry fractionation
steps are highly desirable. Recently, the generation and isolation of transmembrane domain
(TMD) peptides using membrane shaving has been shown to complement other membrane
enrichment techniques (Speers et al 2007, (Wolff et al 2008). Briefly, membrane shaving
involves treating extracted membranes with proteinase-K to digest exposed hydrophilic
domains leaving behind only the membrane-embedded domains, which are then digested
using chymotrypsin. The transmembrane domain (TMD) peptides are then separated and
identified directly using mass spectrometry (Speers et al 2007).
Recently, Wolff et al (2008) used LC-MS/MS to compare 1D-SDS-PAGE, strong cation
exchange (SCX) chromatography and membrane shaving to resolve the membrane proteome
of Staphylococcus aureus. They identified 271 integral membrane proteins (IMPs) and found
1D-SDS-PAGE and membrane shaving approaches to be highly complementary. Membrane
shaving yielded almost exclusively IMPs (96.7%).
In this present study, the protocols used by Wolff et al (2008) have been adapted with the
aim of increasing the current resolution and identification of the membrane proteome of E.
faecalis.
2.3.3 Methods
2.3.3.1 Growth conditions
As per section 2.2.3.1 (page 33).
2.3.3.2 1D SDS-PAGE
The protein concentration of the cell-free lysate was determined using the Coomassie Plus
(Bradford) Assay Kit (Thermo Fisher Scientific) and membrane proteins were purified from
100 mg of crude protein. Following ultracentrifugation (100,000x g, 60 minutes, 4C) the
44
pellet was homogenised in 8 mL high salt buffer (20 m MTris-HCl, pH 7.5, 10 mM EDTA,
1M NaCl) containing Protease inhibitor and incubated for 30 minutes at 4C on a rotary
shaker. The solution was then ultracentrifuged (100,000x g, 60 min, 4C) and the pellet
homogenised in 8 mL/100 mM Na2CO3-HCl, pH 11, 10 mM EDTA, 100 mM NaCl.
Following ultracentrifugation, (100,000x g, 60 minutes, 4C) the pellet containing the
bacterial membrane was washed with 8 mL, 50 mM triethylammonium bicarbonate (TEAB)
pH7.8 buffer and then ultracentrifuged (100,000x g, 60 minutes, 4C) before the pellet was
homogenised in 500 μL/50 mM TEAB, pH 7.8 buffer. The protein concentration was
determined according to the Bradford Assay described above. An aliquot containing 20 μg
of the purified membrane protein was reduced with 4 mM Tributylphosphine (TBP)
(BioRad) at 50C for 30 minutes. Alkylation of the samples was performed with 10 mM
iodoacetamide (BioRad) in the dark for 30 minutes. The sample (500 uL) was then purified
using a 2D clean-up kit (BioRad) following the manufacturer’s instructions.
20 uL was loaded onto a Criterion TGX Precast gel (BioRad) and separation performed at
200 V constant voltage. After completion, the gel lane was cut into 12 equal sized pieces
and subjected to in-gel tryptic digestion. Briefly, the bands were reduced with 10 mM
dithiothreitol (DTT) in 100 mM ammonium bicarbonate. Alkylation of proteins was
performed using 2.75 mol iodoacetamide (IAA) in 100 mM ammonium bicarbonate.
Overnight digestion was performed using 100 ng of sequencing grade modified trypsin
(Promega Sydney, NSW Australia) in 5 mM ammonium bicarbonate containing 10%
acetonitrile (ACN). The digest was stopped by addition of 30 L of 1% formic acid followed
by 15 minutes in a sonicating water bath. The supernatant was kept and two further
extractions using 50 L of 1% formic acid in 50% ACN and 50 ul of 100% ACN with
sonication for 15 minutes were performed. For each gel piece, extracts were pooled. The
volumes of the resulting peptide extracts were reduced by vacuum centrifugation to
approximately 2 L then re-suspended with 0.1% TFA in 2% ACN to a total volume of ~10
L.
2.3.3.3 Membrane shaving
The protein concentration of the cell-free lysate was determined as described previously and
adjusted to 1 mg/mL-1 with saline. An aliquot containing 60 mg of protein was pelleted by
ultracentrifugation (100,000x g at 4C for 1 hour) and the membranes were washed in
phosphate buffered saline (PBS) followed by further ultra-centrifugation (100,000x g at 4C
45
for 1 hour). The pellet was carefully re-suspended in 1000 L of carbonate buffer (200 mM
Na2CO3 pH 11.0) using an insulin syringe to homogenise the pellet. The sample was
incubated on ice for 1 hour and homogenised every 15 minutes. The protein concentration
of the homogenised pellet was determined and the concentration adjusted to 1 mg/mL-1 with
carbonate buffer. With the sample at room temperature, solid urea (BioRad) was added to a
concentration of 8 M. Samples were reduced with 4 mM Tributylphosphine (TBP) (BioRad)
at 50C for 30 minutes. Alkylation of the samples was performed with 10 mM IAA in the
dark for 30 minutes. Proteinase K (Sigma-Aldrich) was then added to the sample in an
enzyme:protein ratio of 1:50 and incubated overnight at 35C on a shaker. An equal volume
of 10% ACN (Thermo Fisher Scientific) in water was added and the sample was cooled on
ice for 15 minutes. Samples were then ultracentrifuged (100,000x g at 4C for 1 hour) and
the supernatant was discarded and the pellet rinsed with 50 mM TEAB (pH 8.4 to 8.6) to
remove residual urea. Membranes were then pelleted by centrifugation (100,000x g) at 4C
for 1 hour.
The pellet was re-suspended in 200 l of TEAB 10 mM calcium chloride and 0.5% RapiGest
(Waters. Milford Massachusetts, USA). 4 g of chymotrypsin (Sigma-Aldrich) was added
and digestion performed for 6 hours at 30C (with shaking). RapiGest® was removed by
incubation in 0.25 M HCl solution (pH<2) for 45 minutes at 37C.
The sample was then centrifuged three times (20,000x g at 4C for 15 minutes) each time
collecting the supernatant containing peptides.
The resultant supernatant was then analysed with LC-MS/MS by staff at the Adelaide
Proteomics centre. Peptides were desalted and concentrated using C18 spin column (Thermo
(Pierce) Rockford, IL USA). Peptides were eluted using ACN:TFA:H2O (70:0.5:29.5, v/v)
and freeze dried. The lyophilised peptides were re-suspended using ACN:TFA:H2O
(2:0.1:97.9, v/v). The volumes of the resulting peptide extracts were reduced by vacuum
centrifugation to approximately 2 L then re-suspended with 0.1% TFA in 2% ACN to a
total volume of ~10 L.
2.3.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry
Peptides were separated on an Ultimate 3000 HPLC system (Dionex) coupled to a LTQ
Orbitrap XL mass spectrometer (Thermo Fisher Scientific). Samples (5 uL) were injected
46
into a trapping column (Acclaim PepMap100, C18, pore size 100 Å, particle size 3 µm, 75
µm ID × 2 cm length) and then resolved on a separation column (Acclaim PepMap RSLC,
C18, pore size 100 Å, particle size 2 µm, 75 µm inner diameter (ID) × 15 cm length). The
HPLC solvent A was 2% ACN, 0.1% FA in water and solvent B was 80% ACN, 0.1% FA
in water. Peptides were eluted at 300 nL/min-1 flow rate with the following 100 minutes
gradient: 4% B for 10 min, gradient to 40% B over 50 min, gradient to 90% B in 20 min,
90% B for 10 min, gradient from 90% to 4% B in 30 s, 4% B for 19.5 minutes. The LTQ
Orbitrap XL instrument was operated in data-dependent mode to automatically switch
between full scan MS and MS/MS acquisition. Instrument control was through Thermo Tune
Plus and Xcalibur software (Thermo Scientific).
A full scan MS spectra (m/z = 300 to 1700) was acquired in the Orbitrap analyser and
resolution in the Orbitrap system was set to r = 60,000. The standard mass spectrometric
conditions for all experiments were spray voltage, 1.25 kV, no sheath and auxiliary gas flow,
heated capillary temperature, 200°C, predictive automatic gain control (AGC) enabled, and
an S-lens RF level of 50 to 60%. All unassigned charge states and charge state of +1 were
rejected. The six most intense peptide ions with charge states ≥2 and minimum signal
intensity of 1000 were sequentially isolated and fragmented in the high-pressure linear ion
trap by low energy CID. An activation q = 0.25, activation time of 30 ms and normalised
collision energy of 35% were used. The resulting fragment ions were scanned out in the low-
pressure ion trap at the “normal scan rate” (33,333 amu s-1) and recorded with the secondary
electron multipliers.
Raw data files were subjected to the Proteome Discoverer software (Thermo Scientific) to
set up the workflow, files were then submitted to MASCOT (Version 2.2; Matrix Science
Inc., Boston, USA, 2007) by the Proteome Discoverer Daemon (Thermo Scientific). Peak
lists in the range from 350 m/z to 5000 m/z were searched against the NCBInr database with
the enzyme setting of trypsin for the 1D gel pieces, and enzyme setting of chymotrypsin for
the membrane shaving samples. Protein identifications were made on the basis of having at
least two unique peptides. These unique peptides were required to have different sequences
or different variations of the same sequence, for example, containing a modified residue or
missed cleavage site. Multiple charge states were not considered as unique.
47
2.3.3.5 Protein analysis
The proteins identified from both 1D SDS-PAGE and membrane shaving isolation
techniques were searched using the Locate P database (http://www.cmbi.ru.nl/locatep-
db/cgi-bin/locatepdb.py) to determine the predicted localisation. The total number of
membrane-associated proteins and intracellular proteins were determined for each
membrane enrichment protocol and for proteins common to both techniques. The
membrane-associated proteins were then cross matched with the published results of Paulsen
et al (2003), Ruffuveille et al (2011), Maddalo et al (2011) and Bøhle et al (2011) for
comparison with previous identifications and predicted roles in biofilm formation, stress and
virulence.
The NCBI protein data base (http://www.ncbi.nlm.nih.gov) was searched using the gene
name derived from Locate P to obtain the FASTA format for each membrane associated
protein, which was then used to search with TMHMM Server v.2.0
(http://www.cbs.dtu.dk/services/TMHMM/) for a prediction of the number of
transmembrane helices and also searched with ExPASy ProtParam
(http://web.expasy.org/protparam/) for the GRAVY scores.
2.3.4 Results
A total of 513 proteins were identified with both 1D SDS-PAGE and membrane shaving
protocols. The predicted localisation of the proteins identified were categorised with both
LocateP and the LocateP prediction by SwissProt classification (Table 1). The IMPs include
LocateP predictions of Multi-transmembrane, Multi-transmembrane (lipid modified N-
termini) and N-terminally membrane anchored locations. For the purposes of this study, the
membrane-associated proteins include the Lipid-anchored locations in addition to IMPs
(Figure 3).
48
Predicted localisation
LocateP prediction by
SwissProt Classification 1D
SD
S
PA
GE
Sha
ving
1D &
S
havi
ng
No.
of
iden
tifi
ed
prot
eins
No.
in th
e E
. fae
cali
s V
583
geno
mea
Per
cent
of
pred
icte
d id
enti
fied
Multi-transmembrane Membrane 92 58 32 118 581 20
Multi-transmembrane
(lipid modified N-termini)
Membrane 3 1 1 3 7 43
N-terminally membrane anchored
Membrane 41 3 1 43 193 22
Lipid-anchor Extracellular 34 6 2 38 74 51LPxTG cell-wall
anchor Cell Wall 1 1 2 42 5
Secreted Extracellular 9 0 0 9 55 16Intracellular Cytoplasmic 299 1 300 2303 13
a Data from LocateP (Zhou et al 2008)
Table 1. Predicted localisation and number of identified membrane proteins using 1D-SDS-PAGE and membrane shaving.
Four hundred and seventy nine proteins were identified using 1D SDS-PAGE with 170 of
these predicted to be membrane-associated (35.5%) and 299 intracellular (62.4%). The
membrane shaving protocol yielded a total of 70 proteins with 68 (97%) predicted to be
membrane-associated, one intracellular (1.4%) and one attached to the cell wall (1.4%).
There were 36 membrane associated proteins that were common to both 1D SDS-PAGE and
membrane shaving approaches giving a total of 202 unique membrane-associated proteins.
This represents 24% of the total 855 predicted proteins (Zhou et al 2008) (Table 2). Of the
202 membrane-associated proteins recovered, 164 were IMPs which represent 21% of the
781 predicted IMPs. In addition to membrane-associated proteins, two proteins were
predicted to be located on the cell wall, one from each protocol, and there were nine secreted
proteins identified using 1D SDS-PAGE. In total, 213 proteins that were not cytosolic were
identified.
The 1D SDS-PAGE and membrane shaving protocols resulted in 58 and 25 proteins
respectively that were common to the membrane associated proteins identified by Maddalo
et al (2011) and Bohle et al (2011) with 15 proteins common to both protocols. Hence, 145
proteins were unique to the present study (Appendix 3).
49
Ballering et al (2009) described 68 genetic loci predicted to be involved in biofilm formation
by E. faecalis. The 1D-SDS-PAGE and membrane shaving protocols in the current study
identified the expression of four and five corresponding proteins respectively with two being
common to both protocols (Appendix 3).
Paulsen et al (2003) genomic study predicted 50 proteins played a role in the organism’s
stress response. In the present study, 12 and 6 proteins were identified using 1D SDS-PAGE
and membrane shaving respectively, with five identified in both protocols (Appendix 3).
Of the 148 proteins in E. faecalis implicated in virulence, (Paulsen et al 2003, Reffuveille et
al 2011) 28 and 7 were identified using 1D SDS-PAGE and membrane shaving respectively,
with two being common to both protocols. The physiological classification of identified
membrane associated proteins was determined by cross referencing with Paulsen et al
(2003), Wolff et al (2008), Maddalo et al (2011) and Reffuveille et al (2011). Of the 213
proteins with known function, the majority are involved with membrane transport (Table 2).
Function 1D SDS-PAGE
Membrane Shaving
Common to both Total
Percentage of all
membrane associated proteins
Transport & binding 40 33 16 57 26.76
Virulence 28 7 2 33 15.49Protein
translocation & processing
7 4 1 10 4.69
Stress 10 4 4 10 4.69Metabolism 7 7 3.29
Miscellaneous 10 0 10 4.69Cell
membrane/cell wall division
9 2 1 10 4.69
Unknown 57 16 7 76 35.68
Table 2. Physiological classification of the 213 membrane proteins identified from 1D-SDS-PAGE and membrane shaving protocols.
50
The 1D-SDS-PAGE protocol favoured the recovery of proteins with a smaller number of
TMDs, whereas the membrane shaving protocol was useful in recovering proteins within the
full range of 0 to 14 TMDs, but especially those with a higher number. The percentage of
proteins identified and the number of TMDs in relation to the isolation protocol is shown in
Figure 8.
Figure 8. Allocation of membrane associated proteins in respect to their number of TMDs using 1D-SDS-PAGE or membrane shaving.
The GRAVY scores (the sum of hydropathy values of all amino acids divided by the protein
length) given for proteins identified by 1D-SDS-PAGE and membrane shaving are shown
in Figure 9.
51
Figure 9. Frequency of GRAVY indices of membrane associated proteins recovered with 1D-SDS-PAGE and membrane shaving protocols.
2.3.5 Discussion
In the present study, the combined approaches of Na2CO3/1D-SDS-PAGE and membrane
shaving have identified approximately 24% of the theoretical membrane proteome of E.
faecalis V583. To our knowledge, this is the best recovery to date (Zhou et al 2008) and is
approximately twice that of previous reports (Maddalo et al 2011). Maintaining intact cells
as spheroplasts or cell lysis prior to membrane enrichment are the two main approaches used
to identify surface attached, secreted or cell membrane proteins. Bøhle et al (2011) employed
proteolytic shaving of the intact bacterial cells with trypsin and recovered 36 surface-located
proteins, of those with surface located/exposed domains, three (0.5%) were annotated as
integral membrane proteins. The low recovery was thought to be due to limited accessibility
of the proteins and the limited ability of trypsin to penetrate the cell wall (Bøhle et al 2011).
Alternatively the ability of trypsin to cleave sites in membrane proteins necessary for mass
spectrometry identification could also limit detection (Wolff et al 2008). In contrast to the
intact-cell methods, Maddalo et al (2011) lysed cells with a French Press before membrane
purification and enriched cell membranes by ultracentrifugation. In a similar fashion, this
method was used in the current study to create the crude membrane extract and the cell
membrane was precipitated using carbonate buffer as previously described (Eymann et al
2004, Speers et al 2007, Wolff et al 2008). Enrichment with sodium carbonate has been
52
shown to linearise and precipitate membranes, and allows solubilisation of peripheral and
transmembrane proteins in strong detergents (Solis & Cordwell 2011).
Membrane-embedded proteins are especially difficult to recover due to the hydrophobic
nature of the transmembrane domain. Following purification of the cell membrane, Maddalo
et al (2011) separated the proteins using anion exchange chromatography and identified
them by mass spectrometry. One hundred and two proteins were resolved with 64 (63%)
identified as membrane embedded. The authors predicted that they had experimentally
identified ~10% of the membrane embedded proteome of strain OG1X, which was the
largest recovery of such proteins at the time. The 102 proteins identified could be classified
as 64 membrane-embedded (63%), 9 lipoproteins (9%), 16 soluble components of
membrane proteins complexes (16%) and 13 were soluble with no predicted membrane
association (13%).
From in silico analysis, there are 781 predicted membrane-embedded proteins in the E.
faecalis V583 genome ((http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py) and in the
present study, the combined approaches resolved 21 percent (164 proteins). The 1D SDS-
PAGE approach resulted in a total number of 479 proteins identified with 170 being
membrane associated (35.5%) and 299 intracellular. This is a very similar result to Wolff et
al (2008) for S. aureus who reported 572 proteins with 179 being IMPs (31.3%).
In the present study two complementary membrane fractionation techniques were combined
to isolate and identify the highest number of membrane-associated proteins from E. faecalis.
Wolff et al (2008) identified 182 proteins in S. aureus using membrane shaving, of which
176 (96.7%) were determined to be IMPs. Recovery of IMPs using this protocol was much
lower with only 68 proteins recovered, however the proportion of proteins being IMPs was
similar (97%). The discrepancy in the total number of proteins identified could be due to the
mass spectrometry search parameters used, for example, setting the number of missed
cleavages. If the digest is not completely perfect and peptides remain with intact cleavage
sites, increasing the level of missed cleavages increases the number of calculated peptide
masses to be matched against the experimental data. However, this increases the number of
random matches and therefore reduces discrimination
(http://www.matrixscience.com/help/search_field_help.html). Wolff et al (2008) searched
with no enzyme specificity and with chymotrypsin allowing four missed cleavage sites. In
53
order to improve the reliability of identification, a search allowing two missed cleavages was
undertaken and an additional search only with chymotrypsin was also undertaken.
Highlighting the complimentary nature of the isolation protocols, 1D SDS-PAGE favoured
the recovery of proteins with a lower number of TMDs and negative GRAVY scores,
indicative of hydrophilic proteins. The protocol was superior for isolating N-terminally
membrane anchored (with usually 1 TMD) and Lipid-anchored proteins. Membrane shaving
was especially good at the recovery of proteins with a large number of TMDs and identified
predominantly hydrophobic proteins with a positive GRAVY score which demonstrates that
this approach is particularly suitable for the identification of very hydrophobic proteins and
is consistent with the analysis of S. aureus (Wolff et al 2008). In the present study, 1D-SDS-
PAGE produced the largest recovery of proteins in all cell locations including the
intracellular region. In contrast, membrane shaving recovered only one intracellular protein
with the majority predicted to be multi-transmembrane or N-terminally anchored to the
membrane (~89%). Proteinase K was used on purified membrane extracts
(ultracentrifugation and carbonate precipitation) thus targeting protein domains that are
surface exposed (Solis & Cordwell 2011). An acid-labile detergent (Rapigest) was then used
to dissolve the hydrophobic bilayer of the membrane and chymotrypsin added to further
digest the liberated membrane-spanning peptides, which were then analysed using LC-ESI
mass spectrometry.
The majority of the identified integral membrane proteins are described as being involved
in transport and binding proteins (28.2%). The high incidence of proteins dedicated to
transport and a large number of proteins with unknown function is a similar finding to
Maddalo et al (2011). This is also consistent with the large theoretical number of predicted
transport membrane proteins in the proteome (Paulsen et al 2003).
The total number of proteins expressed or recovered may vary according to the growth
conditions or protein extraction protocols and likely contributes to some of the differences
between the present study and other published studies. Sixty seven proteins identified in the
present study were common to Maddalo et al (2011) and Bøhle et al (2011). Ballering et al
(2009) carried out a comprehensive analysis of the genetic determinants of biofilm formation
in the core genome of E. faecalis. Of the 68 genes identified by Ballering et al (2009),
Maddalo et al (2011) identified six of these membrane proteins, whilst this study identified
nine.
54
Paulsen et al (2003) reported the complete genome sequence of E. faecalis V583 and
predicted 50 genes from the whole genome to have a potential role in the organism’s stress
response. This study identified one membrane protein associated with oxidative stress
[EF3257], eight for osmotic stress [EF0295, EF0568, EF0875, EF1493, EF1494, EF2612,
EF2613, EF2614] and three for metal-ion resistance [EF1519, EF1938, EF2623]. This
represents 24% of the predicted stress proteins. In addition to the virulence proteins
determined by Paulsen et al (2003), Reffuveille et al (2011) reviewed the identification of
lipoprotein-encoding genes and their potential involvement in virulence. Of the virulence-
related genes predicted to be surface exposed, this study identified thirty three. Growth
conditions in the present study could be considered ideal in terms of nutrient availability,
temperature and pH so it is perhaps not surprising that the recovery of proteins associated
with roles in stress or virulence was low.
A fundamental consideration in identifying membrane proteins is to limit the contamination
by highly abundant cytosolic proteins. The formation of spheroplasts was thought to reduce
cytosolic protein contamination. Seven of the 27 proteins recovered by Benachour et al
(2009) and 34 of the 69 recovered by Bøhle et al (2011) were identified as cytosolic proteins.
This may reflect the intra-cellular association of these proteins with the cell membrane, or
alternatively, may have been due to cell lysis prior to treatment with trypsin. The released
cytosolic proteins may then have re-associated with the cell envelope and escaped
proteolytic degradation. In this study, the 1D SDS-PAGE protocol resulted in 299
intracellular (cytosolic) proteins identified despite membrane precipitation. In contrast,
membrane shaving appeared to be an excellent method to reduce cytoplasmic contamination
as only one protein (EF021) was identified. EF021 is a 50S ribosomal protein, and is one of
the 33 cytosolic proteins identified by Bøhle et al (2011).
2.3.6 Conclusions
A workflow combining 1D-SDS-PAGE and membrane shaving was successful in the
recovery of integral membrane proteins from E. faecalis V583. Of the 202 membrane
associated proteins identified, 81% were membrane embedded and represents approximately
21 % of the predicted membrane-embedded proteome.
These protocols will form a basis for further research into E. faecalis by investigating protein
expression under different growth conditions and aid in the understanding of how E. faecalis
55
adapts to its environment. Whilst the techniques allow for greater purity of membrane
samples, they do not allow for comparison and quantification of protein expression.
56
2.4 Influence of Enterococcus faecalis V583 cell membrane protein expression on biofilm formation and metabolic responses to alkaline stress
NOTE: The cells recovered from Section 2.1 were used to determine cell membrane protein
expression to alkaline stress. For the purposes of maintaining standalone chapters, the
methods and results of Section 2.1 have been repeated.
2.4.1 Abstract
E. faecalis is commonly found in endodontic infections and can resist highly alkaline root
canal medicaments used in endodontic therapy leading to persistent apical periodontitis.
Here we describe the expression and role that cell membrane proteins play in extreme
alkaline conditions. E. faecalis V583 was grown in a chemostat at pH 8 and pH 11 at one-
tenth the organism’s relative maximum growth rate. Cells were lysed and membranes
fractionated by ultracentrifugation, homogenisation in carbonate buffer, and membrane
shaving. Isotope-coding protein labels were added at the peptide level to each sample and
then combined. The relative proportion of membrane proteins was identified using LC-ESI
mass spectrometry and MaxQuant analysis. Ratios of membrane proteins were log2
transformed, with proteins deviating by more than 1 SD of the mean considered to be up- or
down-regulated. Six proteins were up-regulated at pH 11 including EF0669 (polysaccharide
biosynthesis family), EF1927 (glycerol uptake facilitator) and EF0114 (glycosyl hydrolase).
Five proteins were down regulated including EF0108 (C4-dicarboxylate transporter),
EF1838 (PTS system IIC component), EF0456 (PTS system IID component), EF0022 (PTS
mannose-specific IID component). Growth at pH 11 produced biofilm formation and a shift
in metabolism towards glycerol utililisation. Collectively the protein expression was
consistent with a generalised stress response, in addition to creating a microenvironment that
would help facilitate the necessary membrane potential and proton motive force required for
survival in an extreme alkaline environment.
Keywords: Enterococcus faecalis, ICPL, Alkaline pH, Membrane shaving, Biofilm
57
2.4.2 Background
Enterococcus faecalis is a Gram-positive anaerobe that is found in milk products such as
cheese and in fermented sausages for raw consumption (Zehnder & Guggenheim 2009). It
is a common commensal organism in the gastrointestinal tract (surviving the pH extremes
of gastric acid) and the oral cavity (Sedgley et al 2004). The dental pulp is normally protected
from bacteria by dentine and enamel but may become infected subsequent to caries or
traumatic injuries to the tooth (Kakehashi et al 1966). The pulp has a limited capacity to
launch an effective immune response to invading bacteria and due to being enclosed by hard
tissues, inflammation results in an increased intrapulpal pressure, which may cause marked
pain for the patient. As a natural consequence of microbial infection, the pulp may become
necrotic with infectious microorganisms colonizing the main body of the root canal,
penetrating into the dentinal tubules, lateral canals or anastomoses, and ultimately resulting
in inflammation of the periapical tissues (apical periodontitis) (Moller et al 1981). These
microorganisms may then constitute a reservoir to maintain and sustain infection and re-
infection of the root canal system and surrounding tissues, protected from the host immune
cells, systemic antibiotics and root canal treatment (Athanassiadis et al 2007).
One of the fundamental goals in endodontics is the management of apical periodontitis by
using antimicrobial strategies with the outcome of endodontic therapy depending on the
reduction or elimination of microorganisms (Siqueira & Lopes 1999). Endodontic treatment
of a tooth with a severely inflamed, infected or necrotic pulp usually involves the chemo-
mechanical debridement of the canal(s) using metal files, irrigants such as sodium
hypochlorite and often inter-appointment medicaments such as calcium hydroxide (~pH
12.5 to 12.8) placed in the main root canal to help in the elimination of surviving bacteria
(Siqueira & Lopes 1999). The minimum recommended inter-appointment time should be no
less than 7 days, but longer periods have been considered desirable (3 to 4 weeks) to allow
penetration and to maximise hydroxyl ion concentration (from calcium hydroxide) in the
peripheral dentine (Nerwich et al 1993). Calcium hydroxide medicament kills bacteria by
direct contact through pH effects. The release and diffusion of hydroxyl ions, which are
highly oxidant free radicals, show extreme reactivity inducing lipid peroxidation and
consequently the destruction of the phospholipid component of bacterial cell walls (Siqueira
& Lopes 1999). In addition, cellular protein denaturation occurs by the breakdown of ionic
bonds, leading to suppression of enzyme activity and disruption of cellular metabolism,
inhibition of DNA replication by splitting DNA and the formation of free radicals inducing
58
lethal mutations (Siqueira & Lopes 1999). Calcium hydroxide is known to dramatically
reduce the bacterial load of the root canal system with survival of E. faecalis dropping to
0.001% at pH 11 and 0.00001% at pH 12 (Appelbe & Sedgley 2007). The combination of
other antimicrobial strategies aid in removing organic matter from the canal, such as pulp
tissue and in eliminating bacteria. Following the disinfection stages, the root canal is usually
obturated with gutta-percha and an appropriate sealer to prevent (or at least reduce) the
recontamination of the root canal system or the entry of periradicular fluid. Collectively the
stages of root canal treatment render the canal a hostile, nutrient depleted environment
making bacteria survival a challenge. However, even in this hostile environment, bacteria
can survive and lead to persistent apical periodontitis..
In teeth that have been root filled, infection may persist due to inadequate microbial
elimination (Nair 2006) or due to reinfection of the root canal system usually as a result of
a defective coronal restoration or caries (Ray & Trope 1995). E. faecalis is more commonly
isolated from persistent infections compared to primary infections (89.6% versus 67.5%)
(Sedgley et al 2006) suggesting that it has the capacity to survive the chemo-mechanical
procedures (Yap et al 2014) and to survive in a nutrient limited environment (Sedgley et al
2005). In addition, it has been postulated that a virulence factor of E. faecalis in failed
endodontically treated teeth is the ability to invade dentinal tubules in the presence of human
serum and to adhere to collagen (Love 2001).
It remains uncertain as to whether there are specific survival mechanisms to alkaline stress
such as the activation of ion-transport systems to balance intracellular and external pH levels
(Evans et al 2002), intrinsic resistance, neutralisation of medicaments by bacterial cells, or
products, an alteration in gene expression to the specific changes in the environmental
condition (Siqueira & Lopes, 1999) or whether a more generalised adaptive survival
response occurs with a common set of proteins being expressed (Petrak et al 2008, Wang et
al 2009).
Biofilms are defined as matrix-enclosed bacterial populations adherent to each other and/or
to surfaces or interfaces encased in a matrix of extracellular polymeric substance (EPS), and
exhibiting altered growth phenotypes (Costerton et al 1995, Donlan and Costerton 2002).
Biofilm formation can be regarded as a generalised adaptation to environmental conditions
including an infected, pulpless root canal system (Nair 2006) and production has been shown
to increase with an increase in pH (Zilm & Rogers 2007, Hostacka et al 2010). Zilm and
59
Rogers (2007) found that elevated pH (greater than 8.2) produces a shift from a planktonic
lifestyle to the spontaneous flocculation and biofilm formation by F. nucleatum. The
protective strategies of biofilms include comparatively slow growth, reduced antibiotic
susceptibility, the uptake of large complex nutrient molecules, removal of potentially
harmful metabolic products, the exchange of genetic material and the transfer of virulence
factors, and the development of an appropriate physiochemical environment to facilitate
microbial survival (Stewart & Costerton 2001, Socransky & Haffajee 2002, Distel et al
2002). Dense biofilms of bacteria have been located within the dentinal tubules, isthmuses
and irregularities, which can protect bacteria deeper in the biofilm or deeper inside dentinal
tubules (Siqueira & Lopes 1999, Nair 2006).
Distel et al (2002) demonstrated that when E. faecalis was inoculated into roots medicated
with calcium hydroxide the canals became colonised by the cells, initially in short chains
which then developed into biofilms. This transformation may either be the normal growth
state (Seet et al 2012), or serve as a protective system to facilitate survival in the high pH
and/or limited nutrient environment. It has not been determined in the literature as to whether
this response to high pH is a generalised response to an extreme environment, similar to
those proposed for antibiotic resistance, or whether the increased pH triggers a different
biofilm response.
During balanced growth, the cell’s composition, size, metabolism and protein expression
respond to changes in growth rate (Mehmeti et al 2012). Many publications examining
protein expression in bacteria use an overnight planktonic culture, which in many cases does
not represent growth of the organism in vivo. Many bacteria grow in nature as a biofilm with
growth rate regulated by nutrient availability, however it is difficult to quantify changes in
protein expression that occur over a long period of time with the interaction of a number of
variables potentially having an impact on survival. A chemostat can be used in an attempt to
mimic environmental conditions such as reduced growth rates and changes in gene
expression can be observed following changes to the single environmental condition under
consideration.
Cytoplasmic membrane proteins play a crucial role in responding to stressful environmental
conditions including defence against antibiotics and other antimicrobial agents, signal
transduction, transport, binding, energy metabolism and biofilm production (Opsata et al
2010, Solis & Cordwell 2011). The regulation of bacterial metabolic pathways from glucose
60
to other carbohydrates can be influenced by changes in available energy sources, oxygen
concentration, growth rate, exposure to bacteriocins and toxins (Dressaire et al 2008,
Mehmeti et al 2012) which occurs in a complex and strain-dependent manner (Bizzini et al
2010).
Membrane-embedded proteins are especially difficult to study due to the innate
hydrophobicity of the transmembrane domain. A number of fractionation protocols have
been used to enrich for integral membrane proteins with membrane shaving showing the
greatest promise (Wolff et al 2008). Membrane shaving for E. faecalis was demonstrated to
be highly effective in Section 2.3, with 97% of the proteins identified being membrane
associated, 89% of which were integral membrane proteins.
In order to compare the protein expression of organisms grown in two or more different
conditions, labelling techniques such as isotope coding protein label (ICPL) can be
employed. ICPL is a non-isobaric technique in which N-hydroxysuccinimide (NHS) labels
the primary amine on lysine residues and the protein or peptide N-termini. The technique
therefore improves proteome coverage compared to ICAT protocols (Section 1.6), which
rely on labelling less abundant cysteine residues (Brunner et al 2010, Fleron et al 2010).
Quantification is determined by mass spectrometry by comparing the relative abundance of
differentially labelled peptides (Paradela et al 2010). Conventional ICPL protocols label
isotopically at the protein level and therefore samples can be combined to reduce technical
variance in downstream processes (Turvey et al 2014). However, for quantitative analysis,
labelling at the protein level has the disadvantage in that only 60 to 70% of the identified
proteins may be accurately quantified (Fleron et al 2010, Leroy et al 2010). This could be a
result of incomplete sighting of lysine containing peptides with LC-MS or possible ICPL
reactions with lysine residues altering the normal sequence sites to trypsin digest (Fleron et
al 2010). In order to overcome these technical issues, Fleron et al (2010) and Leroy et al
(2010) utilised ICPL labelling at the peptide level, but this has not been used to investigate
protein expression in E. faecalis.
In order to develop new treatment strategies to eradicate E. faecalis from persistent
endodontic infections, the mechanisms through which it can form biofilms and survive must
be understood and further research on E. faecalis biofilms may contribute to this
understanding (Distel et al 2002). The present study compared the membrane proteome
expression in E. faecalis grown at one-tenth the maximum growth rate (μrel) using continuous
61
culture set at a growth pH of 8 and 11. Membrane protein purification and protein expression
were performed using membrane shaving, chymotrypsin digest of the membrane fraction in
the presence of RapigestTm detergent and ICPL labelling. The aim of this study was to
identify and understand the role of cell membrane proteins associated with the adaptive
response to extreme alkaline conditions by E. faecalis.
2.4.3 Methods
2.4.3.1 Growth conditions
As per section 2.1.3 (page 25).
Cells from both pH 8 and pH 11 growth conditions were washed twice with saline (0.9%
w/v) at 4oC and were finally resuspended in 12 mL of ice cold saline. Cells were lysed by
two passes (60,000 kPa) through a SLM Aminco French Press (Thermo Fisher Scientific).
Endogenous proteinase activity was controlled by the addition of 100 L of bacterial
protease inhibitor cocktail (Sigma-Aldrich). Nucleic acids were then degraded by the
addition of Deoxyribonuclease I (2000 Units), Ribonuclease A (1000 Units) and MgCl2 (50
mM) and incubated on ice for 60 minutes. To separate unbroken cells, the suspension was
centrifuged twice (8,000x g at 4C for 5 minutes).
2.4.3.2 Membrane shaving
As per 2.3.3.3 (page 44) membrane shaving was conducted on both the pH 8 and pH 11
samples.
MALDI spectroscopy was performed by the staff at the Adelaide Proteomics Centre to
establish the relative concentration of peptides in both the pH 8 and pH 11 samples so that
pH 8 and 11 samples could be normalised when comparing protein expression.
2.4.3.3 Peptide ICPL labelling
Both pH 8 and pH 11 samples were lyophilised and the peptides resuspended in 30 L TEAB
(40 mM, pH 8.5). The samples were then vortexed for 30 sec and then sonicated for 5
minutes.
62
2 L of ICPL_0 label (Serva quadruplex kit) was added to the pH 8 sample and 2 L of
ICPL_6 label (Serva quadruplex kit) was added to the pH 11 sample and both were overlaid
with Argon. The samples were vortexed for 30 seconds and then sonicated for 1 minute
before incubation for 60 minutes at room temperature. A further 1 L of ICPL label was
added to each sample (0 and 6 respectively) and incubated for a further 60 minutes at room
temperature. 2L of STOP solution was added to each sample and incubated for 20 minutes
at room temperature. Equal volumes of sample pH 8 and sample pH 11 (with ICPL-labels)
were loaded into a Protein LoBind tube, mixed gently and then desalted and concentrated
using C18 spin column. Peptides were eluted using ACN:TFA:H2O (70:0.5:29.5, v/v) and
freeze-dried. The lyophilised peptides were re-suspended using ACN:TFA:H2O (2:0.1:97.9,
v/v). The volumes of the resulting peptide extracts were reduced by vacuum centrifugation
to approximately 2 L then re-suspended with 0.1% TFA in 2% ACN to a total volume of
~10 L.
2.4.3.4 Liquid chromatography - electrospray ionisation tandem mass spectrometry
Peptides were separated on an Ultimate 3000 HPLC system (Dionex) coupled to a LTQ
Orbitrap XL mass spectrometer (Thermo Fisher Scientific). Samples (5 uL) were injected
into a trapping column (Acclaim PepMap100, C18, pore size 100 Å, particle size 3 µm,
75µm ID × 2 cm length) and then resolved on a separation column (Acclaim PepMap RSLC,
C18, pore size 100 Å, particle size 2 µm, 75 µm inner diameter (ID) × 15 cm length). The
HPLC solvent A was 2% ACN, 0.1% FA in water and solvent B was 80% ACN, 0.1% FA
in water. Peptides were eluted at 300 nL/min-1 flow rate with the following 100 minutes
gradient: 4% B for 10 minutes, gradient to 40% B over 50 minutes, gradient to 90% B in 20
minutes, 90% B for 10 minutes, gradient from 90% to 4% B in 30 seconds, 4% B for 19.5
minutes. The LTQ Orbitrap XL instrument was operated in data-dependent mode to
automatically switch between full scan MS and MS/MS acquisition. Instrument control was
through Thermo Tune Plus and Xcalibur software (Thermo Fisher Scientific).
A full scan MS spectra (m/z = 300 to 1700) were acquired in the Orbitrap analyser and
resolution in the Orbitrap system was set to r = 60,000. The standard mass spectrometric
conditions for all experiments were spray voltage, 1.25 kV, no sheath and auxiliary gas flow,
heated capillary temperature, 200°C, predictive automatic gain control (AGC) enabled, and
an S-lens RF level of 50 to 60%. All unassigned charge states and charge state of +1 were
rejected. The 6 most intense peptide ions with charge states ≥2 and minimum signal intensity
63
of 1000 were sequentially isolated and fragmented in the high-pressure linear ion trap by
low-energy CID. An activation q = 0.25, activation time of 30 ms and normalised collision
energy of 35% were used. The resulting fragment ions were scanned out in the low-pressure
ion trap at the “normal scan rate” (33,333 amu s-1) and recorded with the secondary electron
multipliers.
Raw data files were subjected to the Proteome Discoverer software (Thermo Scientific) to
set up the workflow. Files were then submitted to MASCOT (Version 2.2 2007; Matrix
Science Inc, Boston USA) by the Proteome Discoverer Daemon (Thermo Fisher Scientific).
Peak lists in the range from 350 m/z to 5000 m/z were searched against the NCBInr database
with the enzyme setting of chymotrypsin. Protein identifications were made on the basis of
having at least two matching unique peptides. These unique peptides were required to have
different sequences or different variations of the same sequence, for example, containing a
modified residue or missed cleavage site. Multiple charge states were not considered as
unique.
2.4.3.5 Protein analysis
Data from the MASCOT search was searched through MAXQUANT (version 1.3.0.5). The
ICPL_6 labelled proteins from pH 11 conditions were designated as “H” (heavy)-labelled,
whilst ICPL_0 labelled proteins from pH 8 conditions were designated “L” (Light). The
search allowed for protein quantification on a single H/L count (i.e. just one peptide ratio)
and was restricted to ENTFA V583. The proteins were searched using the LocateP database
(http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py) to determine the predicted
localisation. The total number of membrane-associated proteins and intracellular proteins
were determined. The NCBI protein database (http://www.ncbi.nlm.nih.gov) was used to
obtain the FASTA format for each membrane-associated protein, which was then used to
search with ExPASy ProtParam (http://web.expasy.org/protparam/) for the GRAVY scores
(a measure of protein hydrophobicity).
The MAXQUANT H/L ratios of membrane-associated proteins were log2 transformed, and
the proteins that deviated by more than 1 standard deviation of the mean were considered to
be up- or down regulated.
64
2.4.4 Results
2.4.4.1 Continuous culture
As per section 2.1.4 (page 26).
2.4.4.2 ICPL labelling
A total of 136 proteins were identified and ~90% (123 proteins) with both an ICPL_6
(Heavy) and ICPL_0 (Light) label could be quantified between the pH 11 and pH 8 samples
(Appendix 4). The predicted localisation of the proteins identified was categorised with both
LocateP and the LocateP prediction by SwissProt classification (Table 3).
Predicted localisation
LocateP prediction by
SwissProt Classification
No. of identified proteins
No. of genes that encode E. faecalis
V583 genomea
Percent of predicted identified
Multi-transmembrane Membrane 72 581 12.4Multi-transmembrane
(lipid modified N-termini) Membrane 3 7 42.9
N-terminally membrane anchored Membrane 3 193 1.6
Lipid-anchor Extracellular 4 74 5.4LPxTG cell-wall anchor Cell Wall 1 42 2.4
Secreted Extracellular 2 55 3.6Intracellular Cytoplasmic 51 2303 2.2
a Data from LocateP (Zhou et al 2008)
Table 3. Predicted localisation and number of identified membrane proteins using membrane shaving.
Seventy-eight proteins were classified as integral membrane proteins (IMPs) (57.4%)
representing 10% of the predicted number (781) in the genome database (Paulsen et al 2003,
Zhou et al 2008) (http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py). The majority of
membrane associated proteins were involved with membrane transport (Figure 12).
65
Figure 12. Physiological classification of membrane proteins identified using membrane shaving.
The majority of proteins identified had a positive GRAVY score (the sum of hydropathy
values of all amino acids divided by the protein length), which provides a measure of protein
hydrophobicity (Figure 13).
Figure 13. Frequency of GRAVY indices of membrane associated proteins, positive gravy scores represent proteins that are hydrophobic in nature.
Comparing the abundance ratios between the two growth conditions, six proteins had a log2
H/L ratio (pH 11/pH 8) greater than 1SD of the mean: Phage tail protein EF2096 (3SD),
0
2
4
6
8
10
12
‐1.2 ‐1 ‐0.8 ‐0.6 ‐0.4 ‐0.2 0 0.2 0.4 0.6 0.8 1 1.2 1.4
No.ofProteins
GRAVY
DISTRIBUTIONOFGRAVYSCORES
66
Membrane protein EF1541 (1SD), Polysaccharide biosynthesis family protein EF0669
(2SD), Glycosyl hydrolase, family 20 EF0114 (4SD), Uncharacterised protein EF2938
(1SD), Glycerol uptake facilitator protein EF1927 (1SD). Whilst five proteins had a log2
ratio 1 SD less of the mean: PTS system IIC component EF838 (1D), PTS system IID
component EF0456 (2SD), Predicted nucleoside ABC transporter EF0177 (1SD), C4-
dicarboxylate transporter EF0108 (1SD), PTS system mannose-specific IID component
EF0022 (1SD) (Appendix 5).
2.4.5 Discussion
The experimental model using ICPL means that only peptides that are labelled with either
heavy or light isotopes are included in the comparative analysis, and only proteins identified
at pH 11 matched to proteins expressed at pH 8 were investigated further. The ratio of the
ion intensities represented the relative abundance of the protein in the original samples.
Within the membrane shaving protocol, proteinase-K almost exclusively yields peptides
from the exposed hydrophilic domains in membrane proteins (e.g. loops), while
chymotrypsin cleaves at the carboxy terminus of phenylalanine, tyrosine and tryptophan and
is effective at cutting the hydrophobic domains found in trans-membrane proteins. The
majority of the identified proteins had a positive GRAVY score (Figure 11), which is
consistent with the hydrophobic nature of transmembrane proteins and the efficacy of the
membrane shaving protocol.
From in silico analysis, there are 781 predicted membrane-embedded proteins of E. faecalis
V583 (http://www.cmbi.ru.nl/locatep-db/cgi-bin/locatepdb.py) and in the present study the
combined approaches of membrane shaving, ICPL and LC-MS and quantification with
MAXQUANT protocols resolved approximately 10%. This is a comparatively good result
considering proteins needed to be present in both pH 8 and pH 11 growth conditions, and is
consistent with the findings of Maddalo et al (2011). Maddalo et al (2011) identified ~10%
of the membrane embedded proteome of strain OG1X, being the largest recovery of such
proteins to date. As a membrane shaving protocol preselects for only membrane-associated
proteins, the intracellular proteins identified were not included in comparative analysis
between the pH 8 and pH 11 growth conditions.
67
The efficacy of calcium hydroxide medicament in vivo can be reduced by a decrease in
hydroxyl ion concentration due to the buffering effect of dentine as well as the low solubility
and diffusibility of calcium hydroxide from the medicament paste, making a rapid rise in pH
levels difficult to achieve (Siqueira & Lopes 1999). The maximum pH level that is achieved
throughout the tooth root is thought to be ~pH 9 to 10 (Nerwich et al 1993). This current
study design ensured that the E. faecalis cells were exposed to a constant pH 11 by the
controlled addition of KOH to the chemostat, thereby allowing investigation of the direct
chemical effect on the cells over a long period of time. The maximum growth rate decreased
from 1.0 hour at pH 8, to 7.7 hours at pH 11. This reduction is consistent with pH being the
most important variable of growth in enterococcus species (Fisher & Phillips 2009).
Sampling of the chemostat occurred after 10 generations (117 hours for pH 8 and 770 hours
for pH 11) in which the bacterial populations would have reached steady state and there had
been sufficient time for the cells to adapt to the growth conditions.
There was a dramatic change in the phenotypic appearance of the culture at pH 11 compared
to pH 8, with aggregation of the cells and evidence of an extracellular capsule encasing
bacterial cells (Figure 2). Collectively, these observations are consistent with the formation
of floating biofilms (flocs) which are not attached to an interface, but which share the
characteristics of biofilms (Zilm & Rogers 2007, Flemming & Wingender 2010). The change
in phenotype is consistent with the SEM observations made by Distel et al (2002) of E.
faecalis exposed to a calcium hydroxide medicament for 77 days.
In this study the up-regulation of polysaccharide biosynthesis family protein (EF0669) was
observed (Figure 14), This most likely has a physiological role in the export of teichoic acid
associated with cell wall/membrane/envelope biogenesis
(http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi).
68
Figure 14. Predicted interaction of E. faecalis cell membrane proteins up- and down-regulated at pH 11.
Shankar et al (2002) examined the genomes of two different strains of antibiotic resistant E.
faecalis and found that virulence determinants were clustered on a large pathogenicity island
(PAI) of approximately 150 kb, which varies only slightly between strains. Of note, EF0669
is homologous to EF0559, which is encoded in the pathogenicity island and therefore
associated with virulence.
In most biofilms the extracellular matrix accounts for approximately 90% of the dry mass
with the extracellular polymeric substances (EPS) consisting of polysaccharides, proteins,
nucleic acids and lipids (Flemming & Wingender 2010). The production and composition of
extracellular polymeric substances is not generic amongst bacteria and is dependent on the
microflora in the milieu (mono or multi-species), as well as the environmental conditions
including nutrient supply, oxygen tension, pH, type of surface attachment, period of growth.
Some of these factors will have variation even within the biofilm structure, e.g. nutrient
availability, oxygen tension and pH.
EPS forms the scaffold for the overall architecture of the biofilm and is responsible for
adhesion and cohesion within the biofilm (Flemming & Wingender 2010). Gram-positive
69
organisms have a thick and rigid cell wall that covers the cytoplasmic membrane and is
heavily cross-linked between peptidoglycan strands (Solis & Cordwell 2011). External to
the peptidoglycan layer, some bacteria secrete further material, which is normally of a
polysaccharide nature as a capsule or is totally dissociated from the cell as amorphous slime
(Sutherland 2007).
Thurlow et al (2009) demonstrated that serotype C (which includes strain V583) and D
serotypes of E. faecalis produce capsular polysaccharides which attach to the peptidoglycan
layer. Determining the composition of an EPS is technically difficult, however Hancock and
Gilmore (2002) identified the capsular carbohydrates most commonly expressed by clinical
isolates to be glycerol, phosphate, glucose and galactose residues. Based on their results,
polysaccharide produced by E. faecalis V583 can be classified as a heteropolysaccharide
(HePS) from lactic acid bacteria (LAB) (De Vuyst & de Vin 2007) with glycerol and
phosphate groups attached to the carbohydrate backbone. Heteropolysaccharides are formed
from two or more sugars, although they rarely contain more than three or four (Sutherland
2007).
Apart from immobilizing cells, EPS has an additional function, which includes incorporating
extracellular enzymes such as hydrolases and lyases, thereby creating a versatile external
‘digestive system’ allowing the dissolution and uptake of nutrients from lysed cells and the
EPS itself (Flemming & Wingender 2010). Glycosyl hydrolase (EF0114) is a matrix-
degrading enzyme (N-acetyl-β-hexosamindase) encoded by the dspB locus. Glycosidases
from pathogens can degrade host glycoproteins, e.g. human immunoglobulin G (IgG),
thereby protecting the bacteria from the immune response (Garbe et al 2014). The ability of
E. faecalis to release glycans from RNaseB (high-mannose glycoprotein) has been ascribed
to the protein EF0114 of E. faecalis V583 with potential activity targeting N-linked glycans
(Collin & Fischetti 2004, Bøhle et al 2011).
The glycosyl hydrolase EF0114 is an endoglycosidase (EndoE) that contains two enzymatic
domains. The α domain contains a family 18 glycosyl hydrolase (GH18) motif while the β
domain contains a family 20 glycosyl hydrolase (GH2O) motif (Collin & Fischetti 2004).
GH18 hydrolyses the polymer of beta-1,4-linked N-acetylglucosamine (GlcNAc) and GH2O
(Beta-N-acetylhexosaminidases) catalyses the removal of beta-1,4-linked N-acetyl-D-
hexosamine residues from the non-reducing ends of N-acetyl-beta-D-hexosaminides
including N-acetylglucosides and N-acetylgalactosides. The GH2O enzymes also include
70
dispersin B (40 kDa glycoside hydrolase produced by the periodontal pathogen,
Aggregatibacter actinomyecetemcomitans which is involved in biofilm dispersion
http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi?seqinput=NP_813917.1).
The function of glycosyl hydrolase in the current study cannot definitively be determined,
but as there are no immunological cells present, the role is more likely to be either degrading
EPS components for nutrient uptake or involvement in biofilm dispersion - the final step in
the life cycle of a biofilm (Flemming & Wingender 2010, Rendueles & Ghigo 2012). The
net outcome of dispersion can enable colonisation of other niches or rescue of bacteria
trapped in the nutrient- and oxygen-deprived matrix (Rendueles & Ghigo 2012).
The most striking observation in this study at pH 11 is that two proteins associated with
nutrient acquisition (glycosyl hydrolase and glycerol uptake facilitator) were up-regulated
whilst the proteins associated with the PTS system and associated glucose metabolism were
down-regulated even though glucose was available for uptake by the PTS (Figure 14).
Carbon catabolite repression (CCR) occurs when sugars such as glucose, fructose, or sucrose
are available in sufficient quantity that the synthesis of enzymes necessary for the transport
and metabolism of less favourable carbon sources are repressed (Deutscher et al 2006).
Regulation is often determined by the concentration of glycolytic intermediates. Glycerol
kinase is responsible for the phosphorylation of glycerol during uptake. The dominant
mechanism for glycerol kinase (Figure 14) repression results from allosteric inhibition by
the glycolytic intermediate, fructose 1,6 bisphosphate (FBP) (Brückner & Titgemeyer 2002).
A major role in carbon catabolite repression is undertaken by the bacterial
phosphoenolpyruvate phosphotransferase system (PEP:PTS), which catalyses the uptake
and phosphorylation of a wide range of carbohydrates (Brückner & Titgemeyer 2002,
Deutscher et al 2006) (Figure 14).
The PEP system phosphorylates a number of hexoses including N-acetylmannosamine,
glucose, mannose, glucosamine, and N-acetylglucosamine (Deutscher et al 2006) with the
mannose PTS being the major uptake system for mannose and glucose in bacteria (Figure
14) (Postma et al 1993). In E. faecalis, phosphate produced by the enzymatic action of
enzyme I (EI) on phosphoenolpyruvate (PEP) are donated to glycerol kinase by an
intermediate histidine containing protein (HPr) (Maurer et al 2001). When glucose is
71
available, the phosphates generated by EI from PEP are used to phosphorylate glucose,
thereby depleting available phosphate for glycerol kinase and rendering it inactive. In
addition, if glucose is available the concentration of FBP will be high and this will
allosterically repress glycerol kinase. When glucose is not available, the phosphate generated
by PEP and EI leads to the phosphorylation of HPr which then donates the phosphate group
to glycerol kinase resulting in the phosphorylation and uptake of glycerol (Figure 14).
The carbohydrate specificity of the PTS system resides in the enzyme IIs (EIIs) which
consist of an integral membrane domain (Deutscher et al 2006). In this study the PTS
mannose specific IID protein (EF0022), PTS system IIC component (EF1838) and PTS
system IID component (EF0456) were all down regulated at pH 11 by more than 1SD of the
mean, suggestive of a shift away from PEP:PTS carbohydrate uptake. The imposed growth
rate was set at one-tenth relative to the maximum growth rate for pH 8 and pH 11 conditions,
and therefore the relative nutritient availability provided by Todd Hewitt Broth was the same
for the different pH conditions under investigation. The altered membrane protein expression
between samples grown at pH 11 and pH 8 are therefore due to the change in pH rather than
a change in nutrient availability.
Glycerol can be an important energy source for pathogenic bacteria and enters cells by
energy-independent facilitated diffusion. Amongst the genes implicated in glycerol
metabolism, three are grouped into an operon coding for glycerol kinase (GlpK), glycerol-P
oxidase (GlpO), and the glycerol diffusion facilitator protein (GlpF1)(glycerol uptake
facilitator) (Bizzini et al 2010). Glycerol facilitator (GlpF) catalyses the equilibration of
glycerol gradients across the cytoplasmic membrane and the subsequent metabolism of
glycerol allows a net (steady state) flux of glycerol into the cell (Deutscher et al 2006).
Glycerol is phosphorylated by glycerol kinase to yield glycerol-3-phophate which is then
oxidised to dihydroxyacetone phosphate, an intermediate of the glycolytic pathway, by
glycerol 3-phosphate oxidase and reversibly isomerised to glyceraldehyde 3-phosphate
(Figure 14) (Bizzini et al 2010).
Glycerol forms one of the repeating units of the extracellular polysaccharide of E. faecalis
(Hancock & Gilmore 2002) with additional potential sources of glycerol coming from the
recycling of lysed cells within the biofilm matrix (Flemming & Wingender 2010).
72
With the up-regulation of the glycosyl hydrolase protein (EF0114) at pH 11 it is likely that
glycerol would potentially be released from the extracellular polysaccharide matrix and be
available for ATP synthesis. Under the principals of carbon catabolite repression, glycerol
metabolism would be repressed by the availability of PTS substrates. Indeed, Deutscher et
al (1993) demonstrated that when E. faecalis is grown in a glycerol containing medium,
GlpK (glycerol kinase) synthesis was induced, however if glucose or mannitol was added to
the medium containing glycerol, the synthesis of GlpK was strongly repressed. The results
from the present study show that at pH 11, some proteins associated with the Man-PTS
systems were down-regulated (suggesting inhibition) whilst the glycerol uptake facilitator
was up-regulated.
Bizzini et al (2010) reported that E. faecalis V583 did not grow on glycerol in aerobic
conditions. Opsata et al (2010) reported a similar finding in which E. faecalis V583 produced
acid from glucose but did not show detectable acid production from glycerol. Bizinni et al
(2010) concluded that strain V583 has an unknown defect in glycerol catabolism although it
is equipped with the entire set of genes. Opposed to the concept of a defect in glycerol
metabolism, Opsata et al (2010) investigated four bacteriocin resistant mutants of E.
faecalis. Two spontaneous mutants were obtained after exposure to the bacteriocin, pediocin
PA-1. Bacteriocins are peptides or proteins which have antimicrobial action against other
bacteria by permeabilisation of the cell membrane using specific membrane targets such as
the mannose phosphotransferase system with the IIC and IID components involved as
receptors (Figure 14) (Opsata et al 2010, Kjos et al 2011).
A third spontaneous mutant obtained by selecting colonies resistant to 2-deoxyglucose (2-
DG - a glycolytic inhibitor) was found to also be resistant to pediocin PA-1. A fourth was
obtained by constructing a strain with an inactivated mannose PTS operon mpt. When the
pediocin resistant mutants were grown in a glucose medium, the mutants showed reduced
glucose consumption but metabolised glycerol quickly. Transcriptional analysis revealed the
most pronounced effects in the pediocin resistant mutants were the strong reduction in gene
expression of the mannose PTS operon.
The combined up-regulation of glycosyl hydrolase family 20 (EF0114) and glycerol uptake
facilitator (EF1927) plus the down-regulation of mannose PEP:PTS was observed in the
mutant strains resistant to bacteriocin reported by Opsata et al (2010). A similar protein
expression was shown in the present study to alkaline pH. This indicates that regulation of
73
these proteins could be part of a more generalised stress response rather than a specific
response to increased pH. The association with a coordinated stress response is strengthened
by EF0022 (PTS Mannose-specific IID) being homologous to the PTS mannose specific IID
component protein EF0553 found in the pathogenicity island of E. faecalis V583 (Shankar
et al 2002).
Whilst the down regulation in the PEP:PTS could be a result of a general stress response
similar to that seen for bacteriocin resistance, it may reflect an adaption to a specific
ecological niche resulting in the choice of an alternative carbohydrate (Brückner &
Titgemeyer 2002).
C4 dicarboxylate transporter (EF0108) was down-regulated in this study. C4- dicarboxylates
(e.g. succinate, fumarate, and malate) and the C4- dicarboxylic amino acid, aspartate are
metabolised by bacteria under aerobic and anaerobic conditions. In the absence of a
functional citric acid cycle, fumarate is used as an electron acceptor during anaerobic
respiration (Janausch et al 2002). The most widely studied C4- dicarboxylate carriers are
those of Escherichia coli, consisting of four different secondary carriers (DcuA, DcuB,
DcuC, and DCtA), which have different roles in uptake, antiport, and efflux of C4-
dicarboxylates (Zientz et al 1999). During glucose fermentation by E. coli, DcuC is an efflux
carrier, expressed with relatively high activities but repressed in the presence of oxygen.
However, inactivation of dcuC significantly increased the fumarate:succinate exchange and
a subsequent increase in the uptake of fumarate by the alternative carriers DcuA and DcuB
carriers (Zientz et al 1999). Searching for the individual carriers in the NCBI
(http://www.ncbi.nlm.nih.gov) and UniProt (http://www.uniprot.org) databases revealed
that only the DcuC carrier seems to be associated with E. faecalis. Whilst direct comparisons
to E.coli must be interpreted with caution, it is possible that the down regulation of EF0108
is an adaptive response to increase the uptake of succinate, which has been shown to play a
role in the creation of the electrical potential difference of the membrane (Kaim & Dimroth
1999).
Von Ballmoos et al (2008) provided an excellent description of the role of ATP synthase
which produces the majority of ATP for the cell. F0F1 ATP synthases are nano-sized rotary
engines with the F0 component in the membrane and the F1 component in the cytoplasm
connected with a rotor (c-ring). Whilst the MaxQuant results in this study predicted EF2610
(F0F1 ATP synthase) to have an intracellular location, there is a membrane component to
74
this protein, which was up-regulated at pH 11. ATP synthase can convert energy stored in
the transmembrane ion gradient into torque causing mechanical rotation of the rotary engine,
which is then converted into the chemical bond energy of ATP from ADP and inorganic
phosphate. In the reverse mode, (ATPase) F1 converts the energy of ATP hydrolysis into
torque causing the F0 motor to pump ions out of the cell. The energy stored in the
transmembrane ion gradient has two components: the ion concentration difference (ΔpH or
ΔpNa+) and the electrical potential difference ΔΨ, which are thermodynamically equivalent
(Kaim & Dimroth 1999) and collectively termed the electrochemical gradient. Usually ATP
synthase operates in the ATP synthesis direction but a low membrane potential is a kinetic
challenge. In addition, the rapid proton capture at the external membrane surface may
concentrate the protons close to the membrane making ATP synthesis energetically feasible
in a high pH environment (von Ballmoos et al 2008). Historically it was thought that ATP
could be synthesised by ATP synthase entirely by ΔpH (Jagendorf & Uribe 1966). However,
Kaim and Dimroth (1999) provided conclusive evidence that a transmembrane voltage is
indispensable for generation of the rotational torque required and cannot be replaced by large
ΔpH or ΔpNa+. Kaim and Dimroth (1998a, 1998b) demonstrated that ATP synthesis was
equally effective with succinate, malonate or maleinate but not with fumarate. In order to
improve the efficacy of both succinate and ATP synthase, it would be desirable to have a
higher concentration of H+ ions on the external surface of the cell.
Upon consideration of the phenotypic changes seen at pH 11 and the physiological roles of
the proteins that were up and down regulated it is proposed that cellular aggregation and the
extracellular polymeric substance coating the cells can act to trap protons near the cell
surface in a microenvironment. This would increase the proton motive force and also
concentrate and acidify succinate, thereby creating the electrical potential difference with an
overall greater transmembrane ion gradient, which would facilitate ATP production by ATP
synthase. The role of secondary cell wall polymers in Bacillus, such as teichuronic acid and
teichuronopeptide, against an alkaline challenge has been assigned to their cation binding
capability, thereby increasing the concentration of H+ ions (Padan et al 2005). The extension
of this effect to the formation of EPS and flocs therefore seems conceivable.
The proton motive force can also be increased by interaction of the bacterial cell with a
surface that has a negative charge. As two surfaces with ionisable surface groups approach
each other, a counterion concentration increases in the solution between the two surfaces,
which for negatively charge surfaces results in an increased concentration of H+ ions (Hong
75
& Brown 2010). This then creates a decrease in the cell surface pH and an increase in ATP
production (Hong & Brown 2010). Whilst the authors were looking at the ionic charge of
surfaces such as crushed and ground glass beads, the alkaline environment in the chemostat
would have caused amino acids present in the EPS to becoming negatively charged. This
possibly could have an effect on the electrostatic potential of the cell, which in turn could
have an additive effect on cellular bioenergetics.
2.4.6 Conclusion
Comparisons of the membrane protein profiles between E. faecalis grown at an imposed
slow growth rate in continuous culture at pH 11 compared to pH 8 resulted in a limited
number of up- and down regulated proteins. Collectively the membrane proteins seem to be
involved in the formation of a protective capsule/EPS that protects the cell from the
destructive OH- ions whilst at the same time concentrating H+ ions and substrates required
for the electrochemical gradient close to the cell membrane (Figure 12). The production of
the EPS is facilitated by an increase in polysaccharide biosynthesis, a shift to glycerol
metabolism as the favoured carbohydrate source with an associated down regulation of the
PTS system:nutrient acquisition via the actions of glycosyl hydrolase and glycerol uptake
facilitator. The roles of membrane proteins in this coordinated response to increased pH have
not been previously reported and may help explain the adaptation of a sub-population of
cells to an extreme alkaline pH and therefore survival of E. faecalis whilst in the presence
of the medicaments used in endodontic therapy.
76
Chapter 3. Overall Discussion
The stress response of bacteria to alkaline pH is complex, adaptive and contributes to
virulence and persistence in the environment. Most studies investigating the stress response
have grown bacteria in a planktonic state, or if a biofilm model was used, short periods of
time have been utilised (usually in the order of days to a week). This is in stark contrast to
the nutrient depleted environment that would occur clinically. E. faecalis has been shown to
survive for over a year in root canals ex vivo that had been obturated (Sedgley et al 2005).
The examination of gene expression to increased alkaline conditions coding for intracellular
proteins (Appelbe & Sedgley 2007), or the identification of proteins released into the
extracellular culture (Chávez de Paz et al 2007) have been used to investigate the adaptive
or stress responses of E. faecalis. However to our knowledge the role that cell membrane
proteins play has not been investigated previously.
The aims of this research project were to determine the effect of an extreme alkaline pH on
growth rate, morphology and cell membrane protein expression of E. faecalis.
The first study compared the maximum growth rates in pH 8 and pH 11 conditions. Having
established the maximum growth at pH 8 using continuous culture, the growth rate was
reduced to one tenth of the maximum and sampling commenced after ten generations.
However at pH 11, it was difficult to establish the maximum growth rate using the chemostat
by tipping out most of the contents of the vessel chamber and rapidly filling it with pH
adjusted media. The most likely reason for this is that survival would have dramatically
decreased at the elevated pH (Appleble & Sedgely 2007). Subsequently the time required to
have seen an increase in optical density would have been too great. Alternatively the
maximum growth rate at pH 11 was determined by transferring, 30 mL of the growth
medium was transferred to sterile tubes, adjusting the pH to 11 with the controlled addition
of KOH and then inoculating them with 3 mL of E. faecalis V583 recovered from the
chemostat in which the growth conditions had been maintained at pH 11 for approximately
six weeks.
E. faecalis is classified as being neutrophilic with its optimum growth in the range of pH 7
to 7.5 (Flahaut et al 2007). The results from Chapter 2.1 have demonstrated that a shift from
growth at pH 8, to the extreme alkaline pH 11 resulted in continued survival, albeit at a
reduced maximum growth rate. In order to mimic in-vivo conditions E. faecalis was grown
77
at an imposed growth rate of one tenth the maximum growth rate determined for pH 8 and
pH 11. SEM analysis revealed that neither the imposed growth rate nor a pH of 8 had an
impact on the morphology of the cells, compared to those commonly reported in batch
culture (Chávez de Paz et al 2007). The cocci were round, connected into small chains and
in clumps with evidence of cell division. There was however a dramatic change in the
phenotypic appearance at an imposed slow growth rate and pH 11 with evidence of cellular
aggregation, floc formation and capsule formation. The relative growth rate was kept
constant between growth at pH 8 and pH 11 ensuring that the effects observed are solely
related to an increased pH rather than a change of nutrient supply. In addition, the
aggregation observed is most likely due to the effects of pH rather than the imposed limited
growth rate as a similar finding was reported by Chávez de Paz et al (2007) who
demonstrated aggregation of E. faecalis in both planktonic and biofilm states at exposure to
pH 10.5 for only 4 hours. The SEM images of E. faecalis at pH 11 clearly showed that in
addition to aggregation there had been the production of extracellular polymeric substances.
This is consistent with the extrusion of cellular proteins, slime / capsule production on the
bacteria envelope and/or a shift to biofilm formation (Zilm & Rogers 2007, Chávez de Paz
et al 2007). Bacteria recovered from root canal infections have greater potential to resist
alkaline stress if grown as a biofilm compared to planktonic culture (Chávez de Pas et al
2007). It is known that cell membranes play a role in the production and/or transport of
proteins to the extracellular matrix and a main aim of this research project was to establish
which cell membrane proteins play a role in the adaption of E. faecalis to survive the extreme
alkaline conditions and what role the cell membrane proteins play in the high pH phenotype.
In order to establish an appropriate protocol for the recovery of membrane proteins, batch
grown cells were used and formed the basis of Section 2.2. The initial intention was to
separate the cell membranes from the intracellular contents following cell lysis with a French
Press, and then use either fractionation of the membrane proteins with 1D-SDS-PAGE or in-
solution trypsin digestion before identification and quantitative comparisons with isotope
labelling, mass spectrometry and software analysis. Unfortunately it became obvious very
quickly that the recovery of membrane proteins was hampered by the overwhelming amount
of intracellular proteins with both approaches (Appendix 2). On searching the proteomic
literature a number of enrichment protocols have been reported, each seemingly with
advantages and disadvantages. Wolff et al (2008) established that 1D-SDS-PAGE and
membrane shaving were the most complementary techniques for the isolation of membrane
proteins of the Gram-positive S. aureus. The 1D-SDS and shaving protocols had not been
78
utilised on E. faecalis and required verification before any further proteomic studies were
undertaken on samples that would be difficult and time consuming to collect. This formed
the basis for the experiments in Section 2.3. The fractionation techniques proved to be highly
complementary, but in particular the membrane-shaving protocol improved the resolution of
IMPs, which are notoriously difficult to recover due to their innate hydrophobic nature. Due
to the very low survival of cells at pH 11, and the small number of proteins that can be
recovered from the membrane, only the membrane shaving protocol was used to study the
cell membrane protein profile most likely to be involved in the phenotypic changes and
differences in growth observed at different pH.
Quantative proteomic comparison of two or more samples requires differential labelling so
that the relative peaks/areas can be identified using mass spectrometry. There are a variety
of labelling techniques reported in the literature with ICPL seeming to overcome many of
the limitations of other techniques such as ICAT and iTRAQ. The next most important
decision was whether to label the samples at either the protein or peptide level. Whilst
labelling at the protein level is easier to track the progression of the proteins within the
workflow, a number of protein identifications can be “lost”. As IMP’s are low in number
and difficult to recover the decision was made to opt for labelling at the peptide level to
increase the chances of identification and subsequent quantification.
Accurate quantification of the H/L ratio is dependent on equal loading of labelled samples.
50 mg of crude extract from both the pH 8 and pH 11 samples were re-adjusted after
carbonate enrichment and before proteinase-K and chymotrypsin digests. Prior to ICPL-
labelling the relative peptide concentrations from each sample pH was performed by MALDI
spectroscopy and it was determined that the proportions were close to 1:1 (Appendix 6).
The experimental model using ICPL means that only peptides that have either a heavy or
light isotope attached are included in the comparative analysis between pH 8 and 11. The
ratio of the ion intensities represents the relative abundance of the protein in the original
samples. Approximately 90% of the proteins identified were quantified which is slightly
lower than the >95% reported previously (Fleron et al 2010, Leroy et al 2010) (Appendix
7). There was an equal labelling efficiency between the samples ICPL_0 and ICPL_6
(Appendix 8). Leroy et al (2010) developed an optimised post-digest protocol by increasing
the buffer capacity of the labelling solution, the reactant/substrate ratio and the reaction time
allowed. This suggests that further refinement of the post-digest ICPL-labelling protocol is
79
warranted in future experiments. The recovery and identification of IMPs is hampered by
the hydrophobic nature of these proteins and the relative absence of the lysine and arginine
targets for tryptic cleavage, which are mainly absent in the transmembrane domain and more
common in exposed hydrophilic domains (Fischer et al 2006). Paradela et al (2010) noted
that there is a significant set of proteins that are only identified and quantified when
particular proteases (endoGluC or trypsin) were used. Utilisation of several proteases could
increase the total number of proteins identified, a finding verified by Leroy et al (2010).
Proteinase-K almost exclusively yields peptides from exposed hydrophilic domains in
membrane proteins e.g. loops. Chymotrypsin cleaves at the carboxy terminus of
Phenylalanine-Tyrosine-Tryptophan (FYW) and is effective at cutting the hydrophobic
domains found in trans-membrane proteins. It is possible that a cleavage at both hydrophilic
and hydrophobic amino acids could have facilitated an increase in protein identification.
Fischer and Poetsch (2006) suggest that two different digestions, one with chymotrypsin and
one with trypsin/cyanogen bromide appear attractive if high sequence coverage is desired.
This warrants further investigation in studying the E. faecalis proteome.
The quantification software analysed the ratio of heavy to light labelled samples only,
therefore proteins that were expressed at only pH 8 or pH 11 were not considered.
The results of Section 2.4 related well to the membrane shaving strategy utilised in Section
2.3. A greater number of proteins were identified and predicted to be located in the multi-
transmembrane region (72 versus 58) and multi-transmembrane (lipid modified N-termini)
region (3 versus 1), the same number in the N-terminally membrane anchored region (3) and
LPxTG cell-wall anchor region (1), and slightly less in the lipid anchored region (4 versus
6). There were a greater number of intracellular proteins isolated in Chapter 3 compared to
membrane shaving in Chapter 2 (51 versus 1). This may be due to an association of these
proteins with the cell membrane, which is possible as they were present in both the pH 8 and
pH 11 samples or it may be due to incomplete fractionation of the membrane proteins.
Alternatively, changes in pH can also trigger release of cytosolic proteins to the extracellular
location. Identification of certain cytoplasmic proteins that have been released from the cell
have been used as markers, reflecting a highly coordinated physiological regulation to the
environment (Chávez de Paz et al 2007).
80
As a membrane shaving protocol selects only membrane-associated proteins, the
intracellular proteins identified were not included in the comparative analysis between pH 8
and pH 11.
Of the 82 membrane-associated proteins identified in the ICPL study, 48 were also recovered
in Chapter 2 (1D SDS-PAGE and membrane shaving), 36 of which were isolated with the
membrane shaving protocol. Considering that there are predicted to be 855 membrane-
associated genes in the genome database (Paulsen et al 2003, Zhou et al 2008), there is a
high correlation between the experiments in both chapters and this provides some validation
to the protein identifications in both studies. A further indication of validity can be derived
by the majority of the identified proteins having a positive GRAVY score, which is a
measure of increased hydrophobicity. Integral membrane proteins are predominantly
hydrophobic and the majority of the proteins identified had multiple trans-membrane
domains (TMDs), which once again supports the membrane location of thr proteins
identified.
In Section 2.4, as only ~10% of the predicted membrane proteins were recovered, care must
be taken when interpreting comparisons between the two samples. The additional 90% of
cell membrane proteins could either not be expressed in the growth conditions, or the protein
recovery techniques were incomplete. As a threshold level, only proteins that showed a
labelling ratio (H/L) greater than or less than 1SD of the mean were considered up- or down
regulated. This produced a limited number of proteins which could be considered to play an
important role in the shift to different growth conditions.
The function and possible interactions of these proteins were discussed in Section 2.4.
3.1 Proteins implicated in biofilm formation
Microorganisms grown in biofilms are phenotypically and physiologically different from the
same microorganism grown in liquid culture, and both alkaline and acidic environments can
signal cellular stress responses than can increase survival (Chávez de Paz et al 2007).
Ballering et al (2009) described 68 genetic loci predicted to be involved in biofilm formation
by E. faecalis. Whilst the number that are intracellular or membrane-associated are
unknown, two corresponding membrane proteins were expressed in this study EF0910
(peptide ABC transporter permease) and EF2380 (probable permease), both of which had a
81
lower H/L ratio than the mean, but did not reach the 1SD threshold. Peptide ABC transporter
permeases are membrane transport proteins that facilitate the diffusion of peptides in or out
of the cell by passive transport. Why these proteins would have reduced expression in the
pH 11 samples cannot be determined with this study.
The proteins EF0114 (Glycosyl hydrolase) and EF0669 (Polysaccharide biosynthesis) are
not listed by Ballering et al (2009) as being implicated in biofilm formation, but were up-
regulated in this present study. It is not possible to determine whether these particular
proteins would have a role in biofilm or peptidoglycan production/turnover. However, it
seems conceivable that there are additional, but as yet un-reported, proteins associated with
the transition to the biofilm state.
3.2 Correlation between metabolism and peptidoglycan turnover
STRING is a database of known and predicted protein interactions (http://string-db.org).
Through text-mining, the EF0669 (Polysaccharide biosynthesis family protein) which was
up-regulated at pH 11 is thought to have an interaction with EF0694 (PTS system fructose-
specific family, IIBC component), which was identified in the MaxQuant data (Figure 15).
This interaction provides evidence of the linkage of production of EPS (via Glucose-1-P)
and the glycolytic pathway in glycerol metabolism.
82
Figure 15. Known and predicted associations for EF0669 determined with String. (http://string-db.org/newstring_cgi/show_network_section.pl?identifier=226185.EF0669 version 9.1 leuS (leucyl-tRNA synthetase), murE (UDP-N-acetylmuramoylalanyl-D-glutamate—L-lysine ligase).
3.3 Correlation to bacteriocin resistance
In the transcriptional analysis of E. faecalis mutants which were resistant to the bacteriocin
pediocin PA-1, there was a strong reduction in gene expression of the mannose PEP:PTS
operon (EF0019-EF0022) (Opsata et al 2010). The PTS mannose specific IID EF0022
protein was also down regulated in the current study study at pH 11 samples by more than
1SD. EF0456 (another PTS mannose-specific IID component) protein was up-regulated in
the study by Opsata et al (2010) but down regulated more than 1SD in this study, and
similarly for EF0108 (C4 dicarboxylate transporter). Other proteins that were down-
regulated in this study and presented by Opsata et al (2010) but that did not reach the 1SD
threshold included EF0020 PTS mannose specific IIAB protein, and EF0021 (PTS mannose
specific protein), both of which are likely to interact with EF0022. EF0020 has an
intracellular location and although the membrane shaving protocol is designed to fractionate
membrane associated proteins, it was expressed in and recovered from both the pH 8 and pH
11 samples and is likely to have a strong association to the membrane. EF0021 is located on
the membrane as a multi transmembrane lipid N-terminally anchored. In addition EF0717
83
(PTS system fructose specific II ABC component) was also in common with the current
study and has a multi transmembrane location.
In contrast to the down-regulated proteins reported by Opsata et al (2010), EF 0636 (Na+/H+
antiporter protein) had a trend to being up-regulated (but not as much as to reach the 1SD
threshold). This could be explained by the alkaline pH. Appelbe and Sedgley (2007)
considered the expression of a selective range of genes to increasing pH. They reported that
the Na+/H+ antiporter (napA) was the only membrane protein gene studied and was found to
be unregulated at pH 10 but down- regulated at pH 7 and 11. The authors suggested that
once the internal pH of the cells had stabilised and the cells adapted, the increased expression
of napA may have no longer been necessary.
Glycosyl hydrolase family 20 (EF0114) and Glycosyl uptake facilitator (EF1927) were up-
regulated (greater than 1 SD) membrane associated proteins also found in the study by
Opsata et al (2010). Others that did not reach the 1SD threshold included EF3108 (peptide
ABC transporter) and EF0958 (PTS system IIABC component), EF0077 (an uncharacterised
protein) and EF1344 (Sugar ABC transporter). The following proteins were up-regulated in
Opsata et al (2010) but with a trend to being down regulated in the current study (but that
did not reach the 1SD threshold): EF0097 (Regulatory protein), EF1529 (PTS sys II C
component), EF1802 (PTS sys IID), EF1901 (Divalent metal cation transport), EF2213 (PTS
sys II BC component), EF3327 (citrate transporter) and EFA0067 (PTS system II ABC).
Collectively there is a strong relationship between this study and that of Opsata et al (2010).
Many proteins that were up-regulated in Opsata et al (2010) seem to show a greater
consistency, with an overall PEP:PTS controlled mechanism to induce glycerol metabolism.
This could be likely as glycerol would be a component of the EPS and the up-regulation of
glycosyl hydrolase would release this as an alternative energy source to substrates taken up
by the PEP:PTS.
3.4 Membrane proteins associated with stress response
Paulsen et al (2003), from their genomic study, predicted 50 proteins to play a role in the
organism’s stress response. In the present study four were identified, with none of them
being regulated by the imposed threshold of 1SD of the mean. Three had a reduced H/L
ratio: EF3257 (oxidoreductase, pyridine nucleotide-disulfide family), EF2623 (cadmium-
84
translocating P-type ATPase), and EF1938 (cation-transporting ATPase) and one had a
greater H/L ratio EF1494 (Na+/H+ antiporter).
3.5 Future Studies
Following the preliminary results of this thesis, future studies should be directed at
investigating the role in survival of the differentially expressed membrane proteins. In
particular - EF0114 (putative glycosyl hydrolase) and EF1927 (glycerol uptake facilitator
protein) appear to be implicated in biofilm turnover and nutrient acquisition.
3.5.1 Construct and characterise individual markerless deletion mutants of EF0114 and EF1927 and a double-knockout mutant
To address the cellular and molecular role of EF0114 and EF1927 in the survival of E.
faecalis, the creation of non-polar deletions in EF0114 and EF1927 in E. faecalis V583 by
allelic exchange mutagenesis as previously described (Gebhard et al., 2014) could be
considered. Putative EF0114 mutants, EF1927 mutants and the double-knockout
EF0114/EF1927 mutants could be confirmed by PCR and Southern hybridisation analysis
(Gebhard et al., 2014). It is hypothesised that the mutants will be less likely to form a biofilm
compared to wild-type strains and would therefore be more vulnerable to pH stress and
nutrient-depleted environments. The ability of the mutant to produce a biofilm at high
growth pH could also be tested using biofilm assays as previously described (Toledo-Arana
et al 2001, Hancock & Perego 2004, Wilson et al 2015).
3.5.2 Determine regulation of EF0114 and EF1927 gene expression
To study further the EF0114 and EF1927 expression in response to extreme alkaline pH,
confirmation of the proposed EF0114 and EF1927 gene organisation using RT-PCR with
primers that anneal to EF0114 or EF1927 and genes flanking them as previously described
(Gauntlett et al., 2008, Shaaly et al., 2013) could be investigated. RNA could be isolated
from batch grown cultures in pH11 and pH7conditions and the transcriptional start site of
EF0114 and EF1927 mapped by 5’RACE (rapid amplification of cDNA ends) as previously
described (Robson et al., 2009, Shaaly et al., 2013). Transcriptional fusions using promoter
EF0114 and EF1927 fusions to lacZ coud be constructed and measured (β-galactosidase
activity) as previously described (Gebhard et al., 2014). A study of the changes in EF0114
and EF1927 promoter activity under a variety of environmental conditions and challenges
85
to different compounds (e.g., pH, nutrient deprivation,) would be useful to determine
precisely what signals lead to activation (or repression) of EF0114 and EF1927 gene
expression. These studies would complement the characterisation studies with the ΔEF0114,
ΔEF1927 and ΔEF0114/EF1927 mutant strains, and point to the cellular and molecular roles
of these genes.
86
Chapter 4. Overall Conclusion
It has been previously established that E. faecalis is commonly recovered from root canals
with persistent infection and that whilst the survival of E. faecalis when exposed to high pH
is reduced markedly, a small population has the ability to persist. The main survival strategy
has been principally attributed to the effective use of proteins associated with proton pumps.
As membrane proteins play an important role in the survival mechanisms of bacteria, the
aim of this thesis was to investigate the change in expression of cell membrane proteins
when E. faecalis is grown at a biologically relevant growth rate and at an extreme alkaline
pH. With the use of continuous culture, optimisation of a membrane shaving protocol and
the use of ICPL labelling, this thesis has demonstrated that additional membrane proteins
play a role in a survival strategy, with a limited number identified as being up- or down-
regulated.
Following an extensive search of the literature, it became apparent that a subset of the
membrane proteins identified have roles in peptidoglycan/biofilm turnover and a shift from
glucose to glycerol metabolism. A similar metabolic shift has been reported in mutants that
are resistance to bacteriocins and lead to the conclusion that one of the responses to an
extreme alkaline is part of a generalised stress response mediated by the down-regulation in
the PEP:PTS system, whilst another is the shift to biofilm formation with the production of
extracellular polysaccharides. It is proposed that the EPS and cellular aggregation had the
additional benefit of increasing the cellular membrane electrochemical gradient in extremely
alkaline conditions. Bacteriocins are known to target the IIC and IID receptors of the Man-
PEP:PTS, but what remains unclear is the signal pathways that cause the down-regulation
of the PEP:PTS system in extreme pH. Potentially it is more energetically efficient for the
cells to utilise glycerol if available. To our knowledge this is the first study to report the cell
membrane response of E. faecalis V583 grown at a biologically relevant growth rate to a
high alkaline environment. Collectively these findings can help explain some additional
adaptational responses to those already determined such as the up-regulation of ATPase and
proton pumps. The fact that a small population of E. faecalis is able to survive an extreme
alkaline environment should not be used as a reason to abolish the use of calcium hydroxide
as an inter-appointment medicament, rather additional antimicrobial strategies should be
developed and employed to aid in the ultimate goal of elimination of microorganisms from
the root canal system. Following the findings within this thesis, the use of molecular and
microbiological platforms can now be used to develop inhibitors to those membrane proteins
87
that are implicated in biofilm formation. Targeting membrane proteins is an attractive
alternative to antibiotic use and has the potential for new drug development for use in
endodontics and beyond.
88
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Appendix 1
Maximum growth curve of E. faecalis in THB media adjusted to pH 11.
Td = ln2/D, where Td is the doubling time and D the Dilution rate.
D= 0.69/7.7
= 0.09 h-1 (μmax)
If the dilution rate is set to 0.1 μrel, then the flow (F) required to achieve this relative growth
rate in a chemostat chamber of 365mL volume is calculated by:
D = F/vol
μmax D = 0.09 h-1
0.1μrel D =0.009 h-1
F = 0.009 x 365
= 3.3 mL/hr -1
y=0.0397x‐ 0.6646R²=0.9819
‐0.7
‐0.6
‐0.5
‐0.4
‐0.3
‐0.2
‐0.1
00 5 10 15
LogOD560
time(hrs)
pH11OD560
Series1
Linear(Series1)
Linear(Series1)
97
Appendix 2
Identification of E.faecalis membrane proteins from the most highly resolved 1D-SDS-
PAGE gel bands and LC-ESI mass spectrometry.
L-lactate dehydrogenase 1 OS=Enterococcus faecalis GN=ldh1 PE=3 SV=1 - [LDH1_ENTFA]
Elongation factor Tu OS=Enterococcus faecalis GN=tuf PE=3 SV=1 - [EFTU_ENTFA]
Seryl-tRNA synthetase 1 OS=Enterococcus faecalis GN=serS1 PE=3 SV=1 - [SYS1_ENTFA]
UDP-N-acetylglucosamine 1-carboxyvinyltransferase 1 OS=Staphylococcus saprophyticus subsp.
saprophyticus (strain ATCC 15305 / DSM 20229) GN=murA1 PE=3 SV=1 - [MURA1_STAS1]
The proteins identified were all predicted to have a cytoplasmic localisation.
Identification of E.faecalis membrane proteins using in-solution digestion and LC-ESI
mass spectrometry.
ORB120817-01 12-072-3 SH (batch grown E. faecalis V583)
Description
Elongation factor Tu OS=Enterococcus faecalis GN=tuf PE=3 SV=1 - [EFTU_ENTFA]
L-lactate dehydrogenase 1 OS=Enterococcus faecalis GN=ldh1 PE=3 SV=1 - [LDH1_ENTFA]
Cell division protein ftsZ OS=Enterococcus faecalis GN=ftsZ PE=3 SV=2 - [FTSZ_ENTFA]
30S ribosomal protein S3 OS=Enterococcus faecalis GN=rpsC PE=3 SV=1 - [RS3_ENTFA]
Arginine deiminase OS=Enterococcus faecalis GN=arcA PE=3 SV=1 - [ARCA_ENTFA]
50S ribosomal protein L19 OS=Enterococcus faecalis GN=rplS PE=3 SV=1 - [RL19_ENTFA]
30S ribosomal protein S5 OS=Enterococcus faecalis GN=rpsE PE=3 SV=1 - [RS5_ENTFA]
50S ribosomal protein L14 OS=Enterococcus faecalis GN=rplN PE=3 SV=1 - [RL14_ENTFA]
30S ribosomal protein S13 OS=Enterococcus faecalis GN=rpsM PE=3 SV=1 - [RS13_ENTFA]
30S ribosomal protein S4 OS=Enterococcus faecalis GN=rpsD PE=3 SV=1 - [RS4_ENTFA]
Uridylate kinase OS=Enterococcus faecalis GN=pyrH PE=1 SV=1 - [PYRH_ENTFA]
50S ribosomal protein L5 OS=Enterococcus faecalis GN=rplE PE=3 SV=1 - [RL5_ENTFA]
98
Elongation factor Tu OS=Ureaplasma parvum serovar 3 (strain ATCC 27815 / 27 / NCTC 11736)
GN=tuf PE=3 SV=1 - [EFTU_UREP2]
6-phosphofructokinase OS=Enterococcus faecalis GN=pfkA PE=3 SV=1 - [K6PF_ENTFA]
Cell division protein ftsA OS=Enterococcus faecalis GN=ftsA PE=3 SV=2 - [FTSA_ENTFA]
60 kDa chaperonin OS=Enterococcus faecalis GN=groL PE=3 SV=2 - [CH60_ENTFA]
50S ribosomal protein L6 OS=Enterococcus faecalis GN=rplF PE=3 SV=1 - [RL6_ENTFA]
50S ribosomal protein L4 OS=Enterococcus faecalis GN=rplD PE=3 SV=1 - [RL4_ENTFA]
30S ribosomal protein S2 OS=Enterococcus faecalis GN=rpsB PE=3 SV=1 - [RS2_ENTFA]
50S ribosomal protein L2 OS=Enterococcus faecalis GN=rplB PE=3 SV=1 - [RL2_ENTFA]
50S ribosomal protein L3 OS=Enterococcus faecalis GN=rplC PE=3 SV=1 - [RL3_ENTFA]
50S ribosomal protein L22 OS=Enterococcus faecalis GN=rplV PE=3 SV=1 - [RL22_ENTFA]
30S ribosomal protein S12 OS=Enterococcus faecalis GN=rpsL PE=3 SV=1 - [RS12_ENTFA]
DNA-directed RNA polymerase subunit beta' OS=Enterococcus faecalis GN=rpoC PE=3 SV=1 -
[RPOC_ENTFA]
Enolase OS=Enterococcus faecalis GN=eno PE=1 SV=1 - [ENO_ENTFA]
30S ribosomal protein S9 OS=Enterococcus faecalis GN=rpsI PE=3 SV=1 - [RS9_ENTFA]
30S ribosomal protein S10 OS=Enterococcus faecalis GN=rpsJ PE=3 SV=1 - [RS10_ENTFA]
50S ribosomal protein L21 OS=Enterococcus faecalis GN=rplU PE=3 SV=1 - [RL21_ENTFA]
Elongation factor G OS=Enterococcus faecalis GN=fusA PE=3 SV=1 - [EFG_ENTFA]
Trigger factor OS=Enterococcus faecalis GN=tig PE=3 SV=1 - [TIG_ENTFA]
30S ribosomal protein S11 OS=Enterococcus faecalis GN=rpsK PE=3 SV=1 - [RS11_ENTFA]
Septation ring formation regulator EzrA OS=Enterococcus faecalis GN=ezrA PE=3 SV=1 -
[EZRA_ENTFA]
50S ribosomal protein L1 OS=Enterococcus faecalis GN=rplA PE=3 SV=1 - [RL1_ENTFA]
50S ribosomal protein L17 OS=Enterococcus faecalis GN=rplQ PE=3 SV=1 - [RL17_ENTFA]
Glyceraldehyde-3-phosphate dehydrogenase OS=Streptococcus pyogenes GN=gap PE=1 SV=2 -
[G3P_STRPY]
ATP-dependent Clp protease ATP-binding subunit ClpE OS=Lactococcus lactis subsp. lactis GN=clpE
PE=2 SV=1 - [CLPE_LACLA]
DNA-directed RNA polymerase subunit alpha OS=Enterococcus faecalis GN=rpoA PE=3 SV=1 -
[RPOA_ENTFA]
99
Serine hydroxymethyltransferase OS=Enterococcus faecalis GN=glyA PE=3 SV=1 - [GLYA_ENTFA]
DNA-directed RNA polymerase subunit beta OS=Enterococcus faecalis GN=rpoB PE=3 SV=1 -
[RPOB_ENTFA]
50S ribosomal protein L18 OS=Enterococcus faecalis GN=rplR PE=3 SV=1 - [RL18_ENTFA]
Phosphate import ATP-binding protein PstB 2 OS=Enterococcus faecalis GN=pstB2 PE=3 SV=1 -
[PSTB2_ENTFA]
ATP synthase subunit beta OS=Enterococcus faecalis GN=atpD PE=3 SV=1 - [ATPB_ENTFA]
GTPase Der OS=Enterococcus faecalis GN=der PE=3 SV=1 - [DER_ENTFA]
Ribonuclease Y OS=Enterococcus faecalis GN=rny PE=3 SV=1 - [RNY_ENTFA]
Foldase protein prsA OS=Enterococcus faecalis GN=prsA PE=3 SV=1 - [PRSA_ENTFA]
Chaperone protein DnaK OS=Enterococcus faecalis GN=dnaK PE=2 SV=1 - [DNAK_ENTFA]
Protein RecA OS=Enterococcus faecalis GN=recA PE=3 SV=2 - [RECA_ENTFA]
Translation initiation factor IF-2 OS=Enterococcus faecalis GN=infB PE=3 SV=1 - [IF2_ENTFA]
V-type sodium ATPase subunit K OS=Enterococcus hirae GN=ntpK PE=1 SV=1 - [NTPK_ENTHR]
rRNA adenine N-6-methyltransferase OS=Clostridium perfringens GN=ermBP PE=3 SV=1 -
[ERM1_CLOPE]
ATP-dependent Clp protease proteolytic subunit OS=Enterococcus faecalis GN=clpP PE=3 SV=1 -
[CLPP_ENTFA]
Ribosome-associated factor Y OS=Streptococcus pyogenes serotype M6 GN=M6_Spy1371 PE=1 SV=1
- [RAFY_STRP6]
Ornithine carbamoyltransferase, catabolic OS=Enterococcus faecalis GN=arcB PE=3 SV=1 -
[OTCC_ENTFA]
30S ribosomal protein S19 OS=Enterococcus faecalis GN=rpsS PE=3 SV=1 - [RS19_ENTFA]
50S ribosomal protein L10 OS=Enterococcus faecalis GN=rplJ PE=3 SV=1 - [RL10_ENTFA]
50S ribosomal protein L33 3 OS=Enterococcus faecalis GN=rpmG3 PE=3 SV=1 - [RL333_ENTFA]
30S ribosomal protein S6 OS=Enterococcus faecalis GN=rpsF PE=3 SV=1 - [RS6_ENTFA]
Probable RNA methyltransferase Daro_1157 OS=Dechloromonas aromatica (strain RCB)
GN=Daro_1157 PE=3 SV=1 - [Y1157_DECAR]
Probable GTP-binding protein EngB OS=Enterococcus faecalis GN=engB PE=3 SV=1 -
[ENGB_ENTFA]
100
Ribosome maturation factor rimP OS=Clostridium beijerinckii (strain ATCC 51743 / NCIMB 8052)
GN=rimP PE=3 SV=1 - [RIMP_CLOB8]
30S ribosomal protein S17 OS=Enterococcus faecalis GN=rpsQ PE=3 SV=1 - [RS17_ENTFA]
Glycine dehydrogenase [decarboxylating] OS=Bradyrhizobium japonicum GN=gcvP PE=3 SV=1 -
[GCSP_BRAJA]
V-type ATP synthase alpha chain OS=Enterococcus faecalis GN=atpA PE=3 SV=2 - [VATA_ENTFA]
30S ribosomal protein S18 OS=Enterococcus faecalis GN=rpsR PE=3 SV=1 - [RS18_ENTFA]
DNA primase OS=Neisseria meningitidis serogroup A GN=dnaG PE=3 SV=1 - [PRIM_NEIMA]
101
Appendix 3
E.faecalis membrane-associated proteins identified following membrane shaving or
1D-SDS-PAGE and LC-ESI mass spectrometry.
Protein in 1D gel bands common to the membrane shaving protocol are highlighted in bold:
(M) Proteins identified by Maddalo et al (2011)
(B) Proteins identified by Bøhle et al (2011)
(Bio) Proteins reported to be involved in biofilm formation (Ballering et al 2009)
(S) Proteins reported to be involved in stress as reported by (P) Paulsen et al (2003)
(V) Proteins reported to be involved in virulence as reported by (P) Paulsen et al (2003) and
(R) Reffuveille et al (2011).
102
103
104
105
106
Appendix 4
Identification and quantification of proteins identified from samples following
membrane shaving, ICPL labelling (pH 11 -Heavy and pH 8 -Light), LC-ESI mass
spectrometry and MaxQuant analysis.
Fasta headers Ratio H/L
Log2
>P00766 SWISS-PROT:P00766 Chymotrypsinogen A - Bos taurus (Bovine). 1.0142 0.0203
>P02672 SWISS-PROT:P02672 (Bos taurus) Fibrinogen alpha chain precursor
NaN
>P20930 SWISS-PROT:P20930 Tax_Id=9606 Gene_Symbol=FLG Filaggrin NaN
>Q0VBK2 TREMBL:Q0VBK2;Q8C1M7 Tax_Id=10090 Gene_Symbol=Krt80 Keratin 80
4.5524
>Q3ZBD7 SWISS-PROT:Q3ZBD7 (Bos taurus) Glucose-6-phosphate isomerase
NaN
>tr|H7C705|H7C705_ENTFA Membrane protein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0516 PE=4 SV=1
EF0516 @Multi-transmembrane
0.072697
-3.7819
>sp|P0DM31|ENO_ENTFA Enolase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=eno PE=3 SV=1
EF1961 Intracellular 0.39653
-1.3344
>tr|Q82YN1|Q82YN1_ENTFA Aggregation substance PrgB OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=prgB PE=4 SV=1;>tr|Q839L6|Q839L6_ENTFA Aggregation substance PrgB OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0149 PE=4 SV=1;>sp|P1795
EF_B0011 @LPxTG Cell-wall anchored
0.033415
-4.9033
>sp|P23530|PT1_ENTFA Phosphoenolpyruvate-protein phosphotransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=ptsI PE=1 SV=2
EF0710 Intracellular 0.32079
-1.6402
>sp|P37062|NAPE_ENTFA NADH peroxidase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=npr PE=1 SV=2
EF1211 Intracellular 0.67521
-0.5665
>sp|Q47758|DDL_ENTFA D-alanine--D-alanine ligase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=ddl PE=3 SV=2
EF0843 Intracellular 0.19876
-2.3309
>tr|Q820V7|Q820V7_ENTFA Crp/FNR family transcriptional regulator OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0107 PE=4 SV=1
EF0107 Intracellular 0.072235
-3.7911
>tr|Q82YR5|Q82YR5_ENTFA PTS system, IIABC components OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_A0067 PE=4 SV=1
EFA0067 @Multi-transmembrane
0.058294
-4.1005
>tr|Q82YU8|Q82YU8_ENTFA Pheromone shutdown protein TraB OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=traB-1 PE=4 SV=1
EFA0002 multi-transmembrane
0.079048
-3.6611
>sp|Q82YV1|YIDC_ENTFA Membrane protein insertase YidC OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=yidC PE=3 SV=1
EF3331 multi-trans Lipid modified N-termini
0.075636
-3.7247
>tr|Q82YV5|Q82YV5_ENTFA Citrate transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3327 PE=4 SV=1
EF3327 multi-transmembrane
0.16191
-2.6267
>tr|Q82YY6|Q82YY6_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3295 PE=4 SV=1
EF3295 multi-transmembrane
0.16144
-2.6309
>tr|Q82YZ7|Q82YZ7_ENTFA ATP-dependent Clp protease, ATP-binding subunit ClpC OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=clpC PE=3 SV=1
EF3282 Intracellular 0.016 -5.9657
>tr|Q82Z22|Q82Z22_ENTFA Oxidoreductase, pyridine nucleotide-disulfide family OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3257 PE=4 SV=1
EF3257 multi-transmembrane
0.08396
-3.5741
>sp|Q82Z41|RPOC_ENTFA DNA-directed RNA polymerase subunit beta OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rpoC PE=3 SV=1
EF3237 Intracellular 0.21037
-2.2489
>tr|Q82Z45|Q82Z45_ENTFA Dps family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3233 PE=3 SV=1
EF3233 Intracellular 0.20564
-2.2818
>tr|Q82Z82|Q82Z82_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3188 PE=4 SV=1
EF3188 Intracellular NaN
>sp|Q82ZA2|MUTS_ENTFA DNA mismatch repair protein MutS OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=mutS PE=3 SV=1
EF3167 Intracellular 17.147 4.0998
>tr|Q82ZB8|Q82ZB8_ENTFA CDP-diacylglycerol--glycerol-3-phosphate 3-phosphatidyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pgsA PE=3 SV=1
EF3148 multi-transmembrane
0.11136
-3.1666
107
>tr|Q82ZE6|Q82ZE6_ENTFA DAK2 domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3114 PE=4 SV=1
EF3114 Intracellular 0.77226
-0.3728
>tr|Q82ZF2|Q82ZF2_ENTFA Peptide ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3108 PE=3 SV=1
EF3108 multi-transmembrane
0.2601 -1.9428
>tr|Q82ZH8|Q82ZH8_ENTFA Acetyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3079 PE=4 SV=1
EF3079 Intracellular NaN
>sp|Q82ZJ1|RS15_ENTFA 30S ribosomal protein S15 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rpsO PE=3 SV=1
EF3065 Intracellular 0.73759
-0.4391
>tr|Q82ZN9|Q82ZN9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_3011 PE=1 SV=1
EF3011 Intracellular 0.733 -0.4481
>tr|Q82ZV7|Q82ZV7_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2940 PE=4 SV=1
EF2940 Intracellular 21.192 4.4054
>tr|Q82ZV9|Q82ZV9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2938 PE=4 SV=1
EF2938 multi-transmembrane
0.68974
-0.5358
>tr|Q830J2|Q830J2_ENTFA Small hydrophobic molecule transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2790 PE=4 SV=1
EF2790 multi-transmembrane
0.16187
-2.6270
>tr|Q830S5|Q830S5_ENTFA Conserved domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2697 PE=4 SV=1
EF2697 multi-transmembrane
0.2021 -2.3068
>tr|Q830W1|Q830W1_ENTFA Membrane protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2657 PE=4 SV=1
EF2657 multi-transmembrane
0.12742
-2.9723
>tr|Q830X1|Q830X1_ENTFA GntP family permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2647 PE=4 SV=1
EF2647 multi-transmembrane
0.48367
-1.0479
>tr|Q830Z1|Q830Z1_ENTFA Cadmium-translocating P-type ATPase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cadA PE=3 SV=1
EF2623 multi-transmembrane
0.1157 -3.1115
>sp|Q831A3|ATPA_ENTFA ATP synthase subunit alpha OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=atpA PE=3 SV=1
EF2610 Intracellular 19.412 4.2788
>tr|Q831G3|Q831G3_ENTFA Phage integrase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2546 PE=4 SV=1
EF2546 Intracellular NaN
>tr|Q831R5|Q831R5_ENTFA PTS system IIBC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2435 PE=4 SV=1
EF2435 multi-transmembrane
0.069858
-3.8394
>tr|Q831T6|Q831T6_ENTFA HD domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2413 PE=4 SV=1
EF2413 multi-transmembrane
0.10615
-3.2358
>sp|Q831U3|SYGB_ENTFA Glycine--tRNA ligase beta subunit OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=glyS PE=3 SV=1
EF2406 Intracellular 0.35237
-1.5048
>sp|Q831U9|RS2_ENTFA 30S ribosomal protein S2 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rpsB PE=3 SV=1
EF2398 Intracellular 0.56002
-0.8364
>tr|Q831W9|Q831W9_ENTFA Amino acid permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2377 PE=4 SV=1
EF2377 multi-transmembrane
0.084883
-3.5583
>tr|Q832G0|Q832G0_ENTFA PTS system IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2269 PE=4 SV=1
EF2269 multi-transmembrane
NaN
>tr|Q832L3|Q832L3_ENTFA PTS system, IIBC components OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2213 PE=4 SV=1
EF2213 multi-transmembrane
0.084387
-3.5668
>tr|Q832L7|Q832L7_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2209 PE=4 SV=1
EF2209 secretory(released with CS)
0.50157
-0.9954
>tr|Q832P2|Q832P2_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2179 PE=4 SV=1
EF2179 multi-transmembrane
0.45117
-1.1482
>sp|Q832R4|Y2154_ENTFA UPF0397 protein EF_2154 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2154 PE=3 SV=1
EF2154 multi-transmembrane
0.060692
-4.0423
>tr|Q832X2|Q832X2_ENTFA Phage tail protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2096 PE=4 SV=1
EF2096 multi-transmembrane
16.003 4.0002
>tr|Q832Z3|Q832Z3_ENTFA ABC transporter, permease protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2075 PE=3 SV=1
EF2075 multi-transmembrane
0.18702
-2.4187355
>tr|Q832Z4|Q832Z4_ENTFA ABC transporter ATP-binding protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2074 PE=3 SV=1
EF2074 Intracellular 0.21429
-2.2223
>tr|Q833A6|Q833A6_ENTFA Cytochrome d ubiquinol oxidase, subunit I OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cydA PE=4 SV=1
EF2061 multi-transmembrane
0.13989
-2.8376
>tr|Q833A7|Q833A7_ENTFA Cytochrome d ubiquinol oxidase, subunit II OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cydB PE=4 SV=1
EF2060 multi-transmembrane
0.19673
-2.3457
>tr|Q833A9|Q833A9_ENTFA Transport ATP-binding protein CydD, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_2058 PE=4 SV=1
EF2058 multi-transmembrane
0.098574
-3.3426
>sp|Q833I2|SYD_ENTFA Aspartate--tRNA ligase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=aspS PE=3 SV=1
EF1970 Intracellular 4.0235 2.0084
>sp|Q833J0|TPIS_ENTFA Triosephosphate isomerase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=tpiA PE=3 SV=1
EF1962 Intracellular NaN
108
>tr|Q833K9|Q833K9_ENTFA Cation-transporting ATPase, E1-E2 family OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1938 PE=3 SV=1
EF1938 multi-transmembrane
0.10043
-3.3157
>tr|Q833L8|Q833L8_ENTFA Glycerol uptake facilitator protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=glpF PE=3 SV=1
EF1927 multi-transmembrane
0.71856
-0.4768
>tr|Q833P3|Q833P3_ENTFA Divalent metal cation transporter MntH OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=mntH PE=3 SV=1
EF1901 multi-transmembrane
0.1167 -3.0991
>sp|RL19_ENTFA 50S ribosomal protein L19 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rplS PE=3 SV=1
EF1898 Intracellular 0.1541 -2.6980
>tr|Q833U0|Q833U0_ENTFA PTS system IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1838 PE=4 SV=1
EF1838 multi-transmembrane
0.037888
-4.7221
>tr|Q833W5|Q833W5_ENTFA General stress protein A OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=gspA-1 PE=4 SV=1
EF1810 Intracellular NaN
>tr|Q833X3|Q833X3_ENTFA PTS system IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1802 PE=4 SV=1
EF1802 multi-transmembrane
0.068453
-3.8687
>tr|Q833X5|Q833X5_ENTFA Ig-like domain (Group 4) family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1800 PE=4 SV=1
EF1800 secretory(released with CS)
0.9608 -0.0576
>sp|Q834A7|SECA_ENTFA Protein translocase subunit SecA OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=secA PE=3 SV=1
EF1763 Intracellular 1.0793 0.1100
>tr|Q834B2|Q834B2_ENTFA Phosphate ABC transporter, permease PstA OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1757 PE=3 SV=1
EF1757 multi-transmembrane
0.12781
-2.9679
>sp|Q834C0|LGT_ENTFA Prolipoprotein diacylglyceryl transferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=lgt PE=3 SV=1
EF1748 multi-transmembrane
0.078991
-3.6621
>tr|Q834D9|Q834D9_ENTFA Uracil permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1720 PE=4 SV=1
EF1720 multi-transmembrane
0.14546
-2.7813
>tr|Q834J3|Q834J3_ENTFA Membrane protein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1657 PE=4 SV=1
EF1657 multi-transmembrane
0.46832
-1.0944
>tr|Q834N0|Q834N0_ENTFA DNA topoisomerase 4 subunit A OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=parC PE=3 SV=1
EF1614 Intracellular 0.16268
-2.6198
>tr|Q834N1|Q834N1_ENTFA Formate acetyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pflB PE=3 SV=1
EF1613 Intracellular 0.21435
-2.2219
>tr|Q834N6|Q834N6_ENTFA Cardiolipin synthase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1608 PE=3 SV=1
EF1608 multi-transmembrane
0.40662
-1.2982
>tr|Q834Q6|Q834Q6_ENTFA Cysteine synthase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=cysK PE=3 SV=1
EF1584 Intracellular NaN
>tr|Q834S3|Q834S3_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1560 PE=4 SV=1
EF1560 Intracellular 0.21932
-2.1888
>tr|Q834T7|Q834T7_ENTFA LysM domain protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1546 PE=4 SV=1
EF1546 N-Terminally anchored(No CS)
0.066148
-3.9181
>tr|Q834U2|Q834U2_ENTFA Membrane protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1541 PE=4 SV=1
EF1541 multi-transmembrane
1.3641 0.4479
>tr|Q834V2|Q834V2_ENTFA PTS system, IIC component, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1529 PE=4 SV=1
EF1529 multi-transmembrane
0.12373
-3.0147
>tr|Q834Y3|Q834Y3_ENTFA V-type ATPase, subunit K OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1494 PE=3 SV=1
EF1494 multi-transmembrane
0.11227
-3.1549
>sp|Q835G1|G6PI_ENTFA Glucose-6-phosphate isomerase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pgi PE=3 SV=1
EF1416 Intracellular 0.24676
-2.0188
>tr|Q835G2|Q835G2_ENTFA Glutamate dehydrogenase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=gdhA PE=3 SV=1
EF1415 Intracellular 0.22441
-2.1557
>tr|Q835H4|Q835H4_ENTFA Colicin V production family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1403 PE=4 SV=1
EF1403 multi-transmembrane
0.21887
-2.1918
>tr|Q835K1|Q835K1_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1376 PE=4 SV=1
EF1376 multi-transmembrane
0.24866
-2.0077
>tr|Q835K7|Q835K7_ENTFA Drug resistance MFS transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1370 PE=4 SV=1
EF1370 multi-transmembrane
0.071447
-3.8069
>tr|Q835M4|Q835M4_ENTFA Pyruvate dehydrogenase (Acetyl-transferring) E1 component, alpha subunit OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pdhA PE=4 SV=1
EF1353 Intracellular 0.38256
-1.3862
>tr|Q835N2|Q835N2_ENTFA Sugar ABC transporter sugar-binding protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1345 PE=4 SV=1
EF1345 Lipid anchored NaN
>tr|Q835N3|Q835N3_ENTFA Sugar ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1344 PE=3 SV=1
EF1344 multi-transmembrane
0.17773
-2.4922
>sp|Q835R7|DNAK_ENTFA Chaperone protein DnaK OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=dnaK PE=3 SV=1
EF1308 Intracellular 0.36296
-1.4621
109
>tr|Q835Y0|Q835Y0_ENTFA Glycosyl hydrolase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1238 PE=4 SV=1
EF1238 Intracellular 0.88887
-0.1699
>tr|Q836A9|Q836A9_ENTFA CCS family citrate carrier protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1207 PE=4 SV=1
EF1207 multi-transmembrane
0.053083
-4.2356
>tr|Q836B0|Q836B0_ENTFA Malate dehydrogenase, decarboxylating OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1206 PE=3 SV=1
EF1206 Intracellular 0.10005
-3.3212
>tr|Q836E7|Q836E7_ENTFA Fructose-bisphosphate aldolase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=fba PE=4 SV=1
EF1167 Intracellular 1.6982 0.7640
>tr|Q836E8|Q836E8_ENTFA YitT family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1166 PE=4 SV=1
EF1166 multi-transmembrane
0.072398
-3.7879
>tr|Q836Q1|Q836Q1_ENTFA Mn2+/Fe2+ transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1057 PE=4 SV=1
EF1057 multi-transmembrane
0.2247 -2.1539
>tr|Q836R2|Q836R2_ENTFA Pyruvate kinase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=pyk PE=3 SV=1
EF1046 Intracellular 0.32995
-1.5996
>tr|Q836U9|Q836U9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1006 PE=4 SV=1
EF1006 N-Terminally anchored(No CS)
0.19972
-2.3239
>tr|Q836V5|Q836V5_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0998 PE=3 SV=1
EF0998 Intracellular 0.57795
-0.7909
>tr|Q836Y6|Q836Y6_ENTFA PTS system, IIABC components OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0958 PE=4 SV=1
EF0958 multi-transmembrane
0.32656
-1.6145
>tr|Q837A3|Q837A3_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0940 PE=4 SV=1
EF0940 multi-transmembrane
0.10793
-3.2118
>tr|Q837D3|Q837D3_ENTFA Peptide ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0910 PE=3 SV=1
EF0910 multi-transmembrane
0.088689
-3.4951
>tr|Q837D4|Q837D4_ENTFA Peptide ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0909 PE=3 SV=1
EF0909 multi-transmembrane
0.090092
-3.4724
>tr|Q837D6|Q837D6_ENTFA Peptide ABC transporter peptide-binding protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0907 PE=1 SV=1
EF0907 Lipid anchored 0.15352
-2.7035
>tr|Q837E3|Q837E3_ENTFA Aldehyde-alcohol dehydrogenase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=adhE PE=4 SV=1
EF0900 Intracellular 0.50738
-0.9788
>sp|Q837G9|KUP_ENTFA Probable potassium transport system protein kup OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=kup PE=3 SV=1
EF0872 multi-transmembrane
0.13056
-2.9372
>tr|Q837M0|Q837M0_ENTFA PTS system IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0816 PE=4 SV=1
EF0816 multi-transmembrane
NaN
>sp|Q837R0|CLPP_ENTFA ATP-dependent Clp protease proteolytic subunit OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=clpP PE=3 SV=1
EF0771 Intracellular 0.079263
-3.6572
>tr|Q837W1|Q837W1_ENTFA PTS system fructose-specific family, IIABC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0717 PE=4 SV=1
EF0717 multi-transmembrane
0.067327
-3.8926
>sp|ef0715|TIG_ENTFA Trigger factor OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=tig PE=3 SV=1
EF0715 Intracellular 0.20125
-2.3129
>tr|Q837X7|Q837X7_ENTFA Acetyltransferase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0698 PE=4 SV=1
EF0698 Intracellular NaN
>tr|Q837Y1|Q837Y1_ENTFA PTS system fructose-specific family, IIBC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0694 PE=4 SV=1
EF0694 multi-transmembrane
0.14066
-2.8297
>tr|Q838A3|Q838A3_ENTFA Polysaccharide biosynthesis family protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0669 PE=4 SV=1
EF0669 multi-transmembrane
5.1847 2.3742
>tr|Q838D4|Q838D4_ENTFA Na+/H+ antiporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=nhaC-2 PE=4 SV=1
EF0636 multi-transmembrane
0.43277
-1.2083
>tr|Q838D5|Q838D5_ENTFA Amino acid permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0635 PE=4 SV=1
EF0635 multi-transmembrane
0.21012
-2.2507
>tr|Q838G6|Q838G6_ENTFA Lipoprotein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0501 PE=4 SV=1
EF0501 Lipid anchored 0.16964
-2.5594
>tr|Q838J1|Q838J1_ENTFA PTS system IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0456 PE=4 SV=1
EF0456 multi-transmembrane
0.047351
-4.4004
>tr|Q838K6|Q838K6_ENTFA Di-/tripeptide transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0440 PE=3 SV=1
EF0440 multi-transmembrane
0.15007
-2.7362
>tr|Q838Z0|Q838Z0_ENTFA PTS system, IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0292 PE=4 SV=1
EF0292 multi-transmembrane
0.069477
-3.8473
>tr|Q839B1|Q839B1_ENTFA ATP-dependent zinc metalloprotease FtsH OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=ftsH PE=3 SV=1
EF0265 multi-transmembrane
0.17125
-2.5458
110
>tr|Q839C8|Q839C8_ENTFA Amino acid ABC transporter amino acid-binding/permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0247 PE=4 SV=1
EF0247 multi-transmembrane
0.35538
-1.4925
>tr|Q839D7|Q839D7_ENTFA Membrane protein, putative OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0235 PE=4 SV=1
EF0235 multi-transmembrane
0.26829
-1.8981
>tr|Q839E4|Q839E4_ENTFA Protein translocase subunit SecY OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=SecY PE=3 SV=1
EF0227 multi-transmembrane
0.11158
-3.1638
>sp|Q839F7|RL16_ENTFA 50S ribosomal protein L16 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rplP PE=3 SV=1
EF0213 Intracellular 0.14185
-2.8175
>sp|Q839G3|RL4_ENTFA 50S ribosomal protein L4 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=rplD PE=3 SV=1
EF0207 Intracellular 0.051672
-4.2744
>sp|Q839G8|EFTU_ENTFA Elongation factor Tu OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=tuf PE=3 SV=1
EF0201 Intracellular 0.32755
-1.6102
>sp|Q839G9|EFG_ENTFA Elongation factor G OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=fusA PE=3 SV=1
EF0200 Intracellular 0.37521
-1.4142
>tr|Q839I5|Q839I5_ENTFA ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0180 PE=4 SV=1
EF0180 multi-transmembrane
0.098503
-3.3436
>tr|Q839I6|Q839I6_ENTFA ABC transporter, permease protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0179 PE=4 SV=1
EF0179 multi-transmembrane
NaN
>tr|Q839I8|Q839I8_ENTFA Basic membrane protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0177 PE=4 SV=1
EF0177 Lipid anchored 0.035342
-4.8224
>tr|Q839P8|Q839P8_ENTFA Glycosyl hydrolase, family 20 OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0114 PE=4 SV=1
EF0114 N-Terminally anchored(No CS)
59.515 5.8951
>tr|Q839Q4|Q839Q4_ENTFA C4-dicarboxylate transporter OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0108 PE=4 SV=1
EF0108 multi-transmembrane
0.045102
-4.4706
>sp|Q839Q5|OTCC_ENTFA Ornithine carbamoyltransferase, catabolic OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=arcB PE=3 SV=1
EF0105 Intracellular 0.33526
-1.5766
>tr|Q839R1|Q839R1_ENTFA Regulatory protein PfoR OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0097 PE=4 SV=1
EF0097 multi-trans Lipid modified N-termini
0.11155
-3.1642
>tr|Q839S9|Q839S9_ENTFA Uncharacterized protein OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0077 PE=4 SV=1
EF0077 multi-transmembrane
0.26825
-1.8983
>sp|Q839V7|SYE_ENTFA Glutamate--tRNA ligase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=gltX PE=3 SV=1
EF0043 Intracellular 0.11727
-3.0920
>tr|Q839W8|Q839W8_ENTFA ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0032 PE=4 SV=1
EF0032 multi-transmembrane
0.43277
-1.2083
>tr|Q839X7|Q839X7_ENTFA PTS system mannose-specific IID component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0022 PE=4 SV=1
EF0022 multi-transmembrane
0.03762
-4.7323
>tr|Q839X8|Q839X8_ENTFA PTS system mannose-specific IIC component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0021 PE=4 SV=1
EF0021 multi-trans Lipid modified N-termini
0.11907
-3.0701
>tr|Q839X9|Q839X9_ENTFA PTS system mannose-specific IIAB component OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_0020 PE=4 SV=1
EF0020 Intracellular 0.035382
-4.8208
>sp|Q839Z5|DNAA_ENTFA Chromosomal replication initiator protein DnaA OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=dnaA PE=3 SV=1
EF0001 Intracellular NaN
>sp|Q93K67|ARCA_ENTFA Arginine deiminase OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=arcA PE=3 SV=1
EF0104 Intracellular 0.3216 -1.6366
>sp|Q9RPP2|EEP_ENTFA Probable protease eep OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=eep PE=3 SV=2
EF2380 multi-transmembrane
0.12031
-3.0551
>tr|Q835Y6|Q835Y6_ENTFA ABC transporter permease OS=Enterococcus faecalis (strain ATCC 700802 / V583) GN=EF_1232 PE=3 SV=1
EF1232 multi-transmembrane
0.17978
-2.4756
111
Appendix 5
Abundance ratio of ICPL labeled proteins identified from pH 11 (intensity H) and pH
8 (intensity L) samples using MaxQuant and represented with Perseus software.
112
Appendix 6
Determination of relative sample concentrations between pH 8 and pH 11 samples
Prior to ICPL-labelling the relative peptide concentrations from each sample pH was
performed by matrix assisted laser desorption ionisation (MALDI) spectroscopy.
Comparative concentrations of pH 8 and pH 11 samples.
113
Appendix 7
Relative abundance of labeled proteins from the original pH 8 and p H11 samples
Log scale ratio of sum of unlabeled N-termini species to the sum of labeled N-termini
Species.
114
Appendix 8
Log scale ICPL_0 intensity versus ICPL_6 intensity. By plotting ICPL_0 intensity
versus ICPL_6 intensity indicated that there was similar labelling efficiency between
the groups.