Mass spectrometry, an old method with new … spectrometry, an old method with new applications Dr....

Freiburg, 12.06.2007

Mass spectrometry, an old method with new applications

Dr. Markus Kostrzewa

Bruker Daltonik GmbH

Uppsala, November 7th 2007


MALDI BioTyper Reliable identification of microorganisms on species and subspecies level using MALDI-TOF MS fingerprinting


From sample to fingerprint

Bioinformatics

Application examples


From sample to fingerprint


MALDI-TOF MS microorganism identification

Identified species

Select a colony

Prepare onto a MALDI target plate

Unknown microrganism

?

Data interpretation

Generate MALDI-TOF profile spectrum


Target/Acceleration

Time-of-Flight Molecular Mass Desorption/Ionisation

Detector Drift Region

m/z

a.i.

Mass

Spectra

Laser

MALDI-TOF mass spectrometry


MALDI-TOF instruments

ultraflex

autoflex

microflex

MALDI-TOF mass spectrometry


Sample preparation

• Direct “cell smear“ method

most simple method, applicable to many bacteria

• Organic solvent extraction

improved quality for difficult bacteria, yeast, fungi

• Mechanical cell disruption (e.g. sonication)

In case of very ridgid cell walls

Compatibility of different procedures

Protocols for inactivation and shipment of microorganisms are available


E.coli 4

36

4.0

6

53

80

.64

62

54

.64

6

31

5.4

9

50

96

.01

71

57

.65

7

27

3.8

7

64

10

.90

78

70

.62

83

68

.99

0

1000

2000

3000

4000

5000

Inte

ns. [a

.u.]

4000 4500 5000 5500 6000 6500 7000 7500 8000

m/z

ribosomal Protein m/z

RL36 4364,33

RS32 5095,82

RL34 5380,39

RL33meth. 6255,39

RL32 6315,19

RL30 6410,60

RL35 7157,74

RL29 7273,45

RL31 7871,06

RS21 8368,76

MALDI-TOF MS profile spectrum Positive linear mode

Mass range 2-20 kDa


Filamentous fungi, yeast, gram+ and gram- bacteria

Aspergillus fumigatus

0

1000

2000

3000

Inte

ns.

[a.u

.]

Bacillus subtilis

0

2000

4000

6000

8000

Inte

ns.

[a.u

.]

Candida albicans ATCC 10231

0.0

0.2

0.4

0.6

0.8

1.0

Escherichia coli DH5alpha

0

500

1000

1500

2000

2500

3000 4000 5000 6000 7000 8000 9000 10000 m/z

Broad applicability of MALDI-TOF MS profiling


Psdm. oleovorans B396_Medium 360

0

1000


0

1000


0

1000


0

1000


0 500

1000

Psdm. oleovorans B396_MRS10

0 1000 2000

Psdm. oleovorans B396_YPD

0 1000 2000

4000 5000 6000 7000 8000 9000 10000 11000 m/z

Pseudomonas oleovorans grown on different media

Low influence of culture conditions


Bioinformatics


MALDI BioTyper 2.0 - GUI

Unknown samples

Match against microbial reference database

Identification result


MALDI BioTyper 2.0 – realtime analysis

Wizard guiding through setup from measurement to data analysis

BioTyper Automation Control Wizard

Define Project

Analyte Placement

Select Methods

Start

MALDI BioTyper 2.0: realtime Analysis

• Start Automation Control Wizard.

• Use a SOP and do not bother with instrument settings.

• Results available directly after measurement


Color-coded identification result.

MALDI BioTyper 2.0 – result table


MALDI BioTyper - score based pattern matching

Calculation of a matching score based on:

Rel Score % matches of the reference spectrum

(e.g. 6 / 10 = 0.6)

Rel P-Num. % matches of the unknown spectrum

(e.g. 6 / 20 = 0.3)

I-Corr. value of intensity correlation

Unknown microorganism is matched against each Main spectrum in a library. Ranking according to matching score, threshold for ID

Robust standard method for species ID


Pseudo-Gel view

M/Z [Da]

File

no.

4000 5000 6000 7000 8000 9000 10000 11000 12000

1 2 3 4 5 6 7 8 910111213141516171819202122232425262728293031323334353637383940

Neisseria meningitidis serotypes

A

W135

X

Y

How about subtyping?

Pseudo-Gel view

M/Z [Da]

File

no.

6100 6200 6300 6400 6500 6600 6700 6800 6900 7000 7100

1 2 3 4 5 6 7 8 910111213141516171819202122232425262728293031323334353637383940


MALDI BioTyper – weighted pattern matching

Identification Results weighted

Detected Species log(Score)

--------------------------------------------------------------

Sp. 1 Serogruppe_A 2.677

Serogruppe_Y 2.150

Serogruppe_W135 2.044

Serogruppe_X 2.026

Sp. 2 Serogruppe_W135 2.339

Serogruppe_Y 2.123

Serogruppe_X 1.784

Serogruppe_A 1.571

Sp. 3 Serogruppe_X 2.665


Serogruppe_Y 1.902

Serogruppe_A 1.136

Sp. 4 Serogruppe_Y 2.294


Serogruppe_X 1.958

Serogruppe_A 1.617

Neisseria meningitidis serogroups

Correct identification of subspecies through weighting of specific peaks.

Expansion of pattern matching towards subspecies detection.


Correlation analysis

Composite Correlation Index Map

Species

Specie

s

2 4 6 8 10 12

2

4

6

8

10

12

Color code:

dark red – highest correlation

dark blue – lowest correlation

Correlation analysis of different Salmonella enterica serovars: Correlation analysis according to Arnold & Reilly, RCMS, 1998, modified

1. 1849_Hadar_VAB

2. 371_enteritidis_VAB

3. 042_typhimurium_O5_VAB

4. 104_enteritidis_VAB

5. 123_typhimurium_O5_VAB

6. 163_Virchow_VAB

7. 188_Dublin_VAB

8. 202_Infantis_VAB

9. 242_Infantis_VAB

10. 285_Virchow_VAB

11. 506_Hadar_VAB

12. 754_Agona_VAB


Microorganism databases

Acetobacter aceti subsp. aceti Acetobacter pasteurianus subsp.lovaniensis Acetobacter pasteurianus subsp.pasteurianus Actinomadura aurantiaca Actinomadura libanotica Actinomadura livida Agrobaterium tumefaciens Arthrobacter globiformis Arthrobacter oxydans Arthrobacter pyridinolis Arthrobacter sulfureus Bacillus alcalophilus Bacillus cohnii Bacillus sphaericus Brevibacillus brevis Brevibacterium linens Cellulomonas flavigena Cellulomonas turbata Corynebacterium glutamicum Comamonas testosteronii Gluconobacter oxydans subsp. oxydans Gluconobacter oxydans subsp.oxydans Gordonia amarae Gordonia rubropertincta Gordonia terrae Halomonas denitrificans Halomonas elongata Halomonas elongata Halomonas halmophila Halomonas halmophila Hydrogenophaga flava Hydrogenophaga pseudoflava

Methylobacterium mesophilicum Methylobacterium organophilum Methylobacterium radiotolerans Methylobacterium rhodesianum Paracoccus versutus Paracoccus versutus Pseudomonas balearica Pseudomonas fluorescens Pseudomonas fluorescens Pseudomonas oleovorans Pseudomonas putida Pseudomonas stutzeri Pseudonocardia hydrocarbonoxydans Rhizobium leguminosarum Rhodococcus coprophilus Rhodococcus fascians Rhodococcus globerulus Rhodococcus rhodnii Rhodococcus rhodochrous Rhodococcus ruber Sinorhizobium meliloti Starkaya novella Starkaya novella Streptomyces albus Streptomyces avidinii Streptomyces azureus Streptomyces badius Streptomyces griseus Streptomyces hirsutus Streptomyces lavendulae Streptomyces phaeochromogenes Streptomyces violaceoruber Streptomyces viridisporus

Libraries:

• Generation of reference pattern for new

microorganisms by users

• Ready-to-use libraries with microbial strains for direct identification (BioTyper 2.0)


MALDI BioTyper – database development

DSMZ, Braunschweig, Germany

German Culture Collection

IEB/Czech Culture Collection

Czech Culture Collection

Robert Koch Institute, Berlin, Germany

Infectious disease control centre

Friedrich Loeffler Institute, Riems, Germany

Veterinary infectious disease control centre

Hans Knoell Institute, Jena, Germany

Streptomycetes strain collection

Institute of Environmental Sciences, Leipzig, Germany

Environmental biology

Institute for Bacteriology and Mycology, Leipzig, Germany

Veterinary microbiology

Max-Planck-Istitute für Molecular Biology

Plant Pathogens

LBCM, Lorient, France

Marine microbiology

Partners in database assembly (1)


University of Lausanne, Switzerland

U.S. Department of Agriculture, Agricultural Research Service, USA

VetOMICS centre, Vienna, Austria

Food microbiology

Institute for Laboratory Medicine, University Hospital Leipzig, Germany

Institute for Clinical Chemistry, Mannheim; Germany

Institute for Medical Microbiology, Immunology and Parasitology, U. of Bonn, Germany

Institute for Microbiology and Hygiene, Charité, Berlin

Institute for Medical Microbiology, University Hospital, Giessen

Institute for Paradontology + Institute for Hygiene, Münster, Germany

Institute of Physico Chemical Medicine, Moscow, Russia

Hopital Pitié-Salpêtrière, Paris, France

University hospital, Inst. Of Bacteriology, Strassbourgh, France

Institute of Clinical Microbiology, Szeged, Hungary

Children’s Hospital of the King/EVMS, Norfolk, USA

Clinical microbiology

Partners in database assembly (2)




Status of the Bruker microorganism database, June 2007:

>2500 database entries

>1420 different species

>220 different genera

Steadily growing!

Very high proportion of reference and type strains!


Application examples


42

63

.38

51

64

.55

64

60

.15

72

45

.48

44

94

.22

75

13

.30

61

76

.31

56

73

.61

86

00

.46

89

89

.05

96

31

.46

82

39

.00

69

29

.01

* Arthrob_sulfureus_B571\0_F8\1\1SLin

0

2000

4000

6000

8000

Inte

ns.

[a.u

.]

42

63

.21

51

64

.04

44

93

.98

72

53

.89

64

60

.00

61

75

.92

56

73

.45

89

89

.24

86

00

.54

96

31

.12

75

13

.41

69

28

.55

82

38

.88

* DSM 20167T\0_G4\1\1SLin, Smoothed, "Baseline subt."

0

1000

2000

3000

4000

5000

6000

Inte

ns.

[a.u

.]

4000 5000 6000 7000 8000 9000m/z

DSMZ / microflex / 2006 / source: DSMZ quality

control

Bruker / autoflex / 2005 / source: UFZ Leipzig

Arthrobacter sulfureus DSM 20157 from different sources

High reproducibility and applicability


High reproducibility and applicability

Measurement of one sample using three different Bruker MALDI TOF instruments

0

1

2

3

4

4 x10

5000 6000 7000 8000 9000 10000 11000 m/z

autoflex II TOF/TOF

microflex LT

ultraflex III TOF/TOF

• Analysis of 24 non-fermenting bacteria with microflex LT/MALDI BioTyper

• Measurement of the same extracts again after 2 months, on three different MALDI TOF instruments with adopted, standardized parameter files

• Very reproducible spectra could be generated on the three instruments

• Same identification results over time and regardless the used instrument


Taxonomic application

Dendrogram for Clostridia in coop. with Prof. Krüger, Dr. Grosse-Herrenthey, Prof. Böhnel

Very high similarity with 16S rDNA results Presentation in the ClinProt Forum Publication in prep.


Industrial application

• Microbial contamination in a facial creme produced by a large health&beauty

product manufacturing facility in North America

• Source of the contaminant – water supply?

• Cultivation of both water supply biofilm bacteria and of contaminant

• Inactivation and shipment to Bruker lab in Billerica

• BioTyper analysis (matching of profile spectra against Bruker db, PCA, MSP

score based dendrogram)

• Parallel analysis by API and Vitek 2 (both Biomerieux) and RiboPrinter

(DuPont Qualicon)


Industrial application

Contaminant of facial creme Herbaspirillum huttiensis DSM 10281T

Water supply biofilm:

Burkholderia cenocepacia LMG 12614

API failed in ID, Vitek 2 only identified creme contaminant!

Riboprinter confirmed BioTyper result!

MALDI BioTyper result:


Biochemical test: Enteroccocus species, motility negative

MALDI BioTyper: Mixed culture

Staphylococcus epidermidis and Enterococcus faecalis

MALDI BioTyper Identification Results:

Detected Species log(Score)

--------------------------------------------------------------------------------------

Staphylococcus epidermidis 10547 CHB 2.236

Staphylococcus epidermidis CHB 2.175

Enterococcus faecalis 11756 1_CHB 2.158

Enterococcus faecalis ATCC 7080 THL 2.118

Enterococcus faecalis 20247_4 CHB 2.050

Enterococcus faecalis ATCC 29212_CHB 2.047

Enterococcus faecalis ATCC 29212 THL 2.024

Staphylococcus epidermidis DSM 3269 2.004

Staphylococcus epidermidis ATCC 14990 THL 1.973

Staphylococcus epidermidis 6b s ESL 1.900

Clinical application


Re-examination “Enterococcus“


Clinical application

MALDI BioTyper analysis of 35 biochemically characterized clinical Klebsiella isolates from Russia (Prof. Govorun, IPCM)

Six BioTyper results were deviating from the original identification,

Further analysis by 16S rDNA sequencing:

biochemical tests BioTyper 16S RNA sequencing

Klebsiella ornithinolytica 306 Klebsiella pneumoniae Klebsiella pneumoniae

Klebsiella oxytoca 201 Klebsiella pneumoniae Klebsiella pneumoniae

Klebsiella oxytoca 234 Escherichia coli Escherichia coli

Klebsiella oxytoca 250 Morganella morganii Morganella morganii

Klebsiella ozaenae 36 Klebsiella pneumoniae Klebsiella pneumoniae

Klebsiella rhinoscleromatis 72 Stenotrophomonas maltophilia

Stenotrophomonas sp.

MALDI BioTyper: All deviating results were confirmed by sequencing!


• Minimal sample preparation

• Powerful bioinformatic approaches

• Species to strain resolution, mixture detection

• High throughput at low costs per analysis

• Non-expert identification possible

• Dedicated databases of high quality

MALDI BioTyper

MALDI BioTyper:

Highest quality in microorganism ID at low costs


• How about virus detection?

• What to do, if the microorganism cannot be cultivated?

• How to handle mixed populations?

• How to handle new emerging agents?

But…


Automated Microorganism

Detection System

IBIS Biosciences / Bruker Daltonics

For research use only, not for use in diagnostic procedures


• Over 1,000 infectious microbes known to cause disease in

humans*

• 217 viral species

• 538 bacterial species

• 307 fungi

• 66 parasitic protozoa

• Numerous strain variations of each species (i.e., >100 strains of

Streptococcus pyogenes)

• Emergence of multi-drug resistant and highly pathogenic strain

types

• Unknown and uncultivable pathogens

Problems Addressed by Ibis T5000

* Taylor et al., Phil. Trans. R. Soc. Lond. B (2001) 356, 983-989.


Objectives of the system

• Broad identification of all clinical microbes

Bacteria, Viruses, Fungi, Protozoa

• No culture

• Mixed populations of microbes (single method for simultaneous wide range identification)

• Quantitative

• High resolution genotyping and strain identification

• Identify emerging agents not previously seen

• Costs effective, high throughput


1. Identify genomic regions for identification

Informative variable DNA sequences flanked by conserved sequences

How does it work?

2. Amplify variable

genomic regions

Using broad-range

PCR-primers

3. Measure nucleic acid mass

ESI-TOF mass spectrometry

4. Identify micro organisms

Base-composition fingerprints


• Exact mass measurement is used to back-calculate base

compositions consistent with the measured molecular weight.

• The four letter code and their exact masses:

A = 313.0576 T = 329.0526

G = 289.0464 C = 304.0461

Base calculations I

Exact Mass of both strands facilitates unambiguous

base composition determination


ppm

0-25

50

100

250

500

# comp pairs

1

13

66

378

1447

AwGxCyTz

AzGyCxTw

Base calculations II


(M-30H+)30-

MW = 32,588.90

A28 G29 C25 T24

800 900 1000 1100 1200 1300 m/z

33- 31-

29-

27-

25-

35-

37-

39-

41-

1089 1093 m/z

Electrospray Ionization does not break DNA


Animal Reservoirs

of Infectious

Agents

Environmental

Surveillance of

Public Places

Clinical

Diagnostics/

Biosurveillance

Water Quality

Biosurveillance

What kind of samples?


Bruker micrOTOF™

mass spectrometer

Magnetic bead-based

desalting station for PCR

plates AND autosampler

Signal analysis and sample tracking software

Instrument Overview

For research use only, not for use in diagnostic procedures

Robotics Arm

And

Plate Hotel

Amplicon

desalting

Module

Infusion

Module

micrOTOF

Sample tracking software and extensive microorganism database


Example 1

Broad Bacterial Identification

Pneumonia Epidemic in Marine Recruits

Collaborator: CMDR Kevin Russell M.D.

Naval Health Research Center

Outbreaks of Severe Pneumonia at a recruit training camp,

San Diego 2002/2003

- Hundreds ill

- 160 hospitalized

- 1 death

Identify the pathogens and co-pathogens

Determine the pathogen strain genotype


Example of a Broad-Range Test

Primary pathogen:

• Streptococcus pyogenes (GAS)

• emm-type 3

known virulent strain

Secondary pathogens:

• Haemophilus influenzae

• Neisseria meningitidis

5 other military facilities

• Determined these sites had a mixture of strain types

Throughput

• >200/samples per day

*Ecker et al. (2005) Proc.

Natl. Acad. Sci. Vol. 102:

p8012-8017

T5000 in routine use at Naval Health Research Center

S. Pyogenes

[A38 G31 C29 T23]

PCR Calibrant

[A34 G29 C27 T26]

Primer 356: rplB

S. Pyogenes

[A24 G37 C30 T25]

H influenzae

[A23 G37 C26 T27]

Neisseria meningitidis

[A27 G34 C27 T27]

Primer 347: 16S rDNA

Organism

Cumulative

Estimate of

Genomes/Swab

Relative Abundances

Haemophilus influenzae 7.38E+05 1.00

Neisseria meningitidis 3.77E+05 0.51

Streptococcus pyogenes 1.89E+05 0.26


Sampath R, Russell KL, Massire C, Eshoo MW, Harpin V, Blyn LB, Melton R, Ivy C, Pennella T, Li F, Levene H, Hall TA, Libby

B, Fan N, Walcott DJ, Ranken R, Pear M, Schink A, Gutierrez J, Drader J, Moore D, Metzgar D, Addington L, Rothman R,

Gaydos CA, Yang S, St George K, Fuschino ME, Dean AB, Stallknecht DE, Goekjian G, Yingst S, Monteville M, Saad MD,

Whitehouse CA, Baldwin C, Rudnick KH, Hofstadler SA, Lemon SM, Ecker DJ.: Global surveillance of emerging influenza virus

genotypes by mass spectrometry. PLoS ONE. 2007 May 30;2:e489.

.

Ecker JA, Massire C, Hall TA, Ranken R, Pennella TT, Agasino Ivy C, Blyn LB, Hofstadler SA, Endy TP, Scott PT, Lindler L,

Hamilton T, Gaddy C, Snow K, Pe M, Fishbain J, Craft D, Deye G, Riddell S, Milstrey E, Petruccelli B, Brisse S, Harpin V, Schink

A, Ecker DJ, Sampath R, Eshoo MW.: Identification of Acinetobacter species and genotyping of Acinetobacter baumannii by multilocus

PCR and mass spectrometry. J Clin Microbiol. 2006 Aug;44(8):2921-32.

Hofstadler SA, Drader JJ, Schink A.: Selective Ion Filtering by Digital Thresholding: A Method To Unwind Complex ESI-Mass Spectra

and Eliminate Signals from Low Molecular Weight Chemical Noise. Anal Chem. 78(2): 372-378. January 15, 2006.

Hall TA, Budowle B, Jiang Y, Blyn L, Eshoo M, Sannes-Lowery KA, Sampath R, Drader JJ, Hannis JC, Harrell P, Samant V,

White N, Ecker DJ, Hofstadler SA: Base composition analysis of human mitochondrial DNA using electrospray ionization mass

spectrometry: a novel tool for the identification and differentiation of humans. Anal Biochem. 2005 Sep 1;344(1):53-69.

Ecker DJ, Sampath R, Blyn LB, Eshoo MW, Ivy C, Ecker JA, Libby B, Samant V, Sannes-Lowery KA, Melton RE, Russell K,

Freed N, Barrozo C, Wu J, Rudnick K, Desai A, Moradi E, Knize DJ, Robbins DW, Hannis JC, Harrell PM, Massire C, Hall TA,

Jiang Y, Ranken R, Drader JJ, White N, McNeil JA, Crooke ST, Hofstadler SA.: Rapid identification and strain-typing of respiratory

pathogens for epidemic surveillance.Proc Natl Acad Sci U S A. 2005 May 31;102(22):8012-7. Epub 2005 May 23.

Sampath R, Hofstadler SA, Blyn LB, Eshoo MW, Hall TA, Massire C, Levene HM, Hannis JC, Harrell PM, Neuman B, Buchmeier

MJ, Jiang Y, Ranken R, Drader JJ, Samant V, Griffey RH, McNeil JA, Crooke ST, Ecker DJ.: Rapid identification of emerging

pathogens: coronavirus.Emerg Infect Dis. 2005 Mar;11(3):373-9.

http://www.ibisbiosciences.com/pubs.html

List of Selected References


• Minimal sample preparation

• Proteomic Profile

• Open System

• Bacteria, Yeast, Fungi

• Requires cultivation step

• Applications:

• Strain quality control

• Food contaminations

• Medical microbiology

• Water control

• Environmental

• PCR

• DNA Analysis

• Closed system

• Viruses included

• No cultivation step

• Main applications:

• Hospital-associated infections

• Infection control

• Influenza infections

• Surveillance studies

MALDI BioTyper T5000

Two systems for complementary applications in

microorganism identifications!

Comparison


Acknowledgement

www.ibisbiosciences.com

www.bdal.de and www.bdal.com

Dr. Wolfgang Pusch

Dr. Gerold Schwarz


Shaun Lonergan

David J. Ecker, Ph.D.

Steven A. Hofstadler, Ph.D.

Vanessa Harpin

Ibis Biosciences

Thomas Maier

Kristina Schlosser

Thomas Wenzel

Thorsten Mieruch

Stefan Klepel

Uwe Renner

Jan-Henner Wurmbach

Karl-Otto Kräuter

Alexander Rueegg


BioTyper-team: Ibis-Bruker-team:


Questions?

Thank you!!

Mass spectrometry, an old method with new … spectrometry, an old method with new applications Dr....

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