Analysis of Horizontal Gene Transfers of Potential Relevance to Microbial Virulence

Fiona Brinkman Simon Fraser University,

Greater Vancouver, British Columbia, Canada

Overview

1. High pathogen-host protein similarities: detecting horizontal gene transfer

2. Characteristics of proteins/genes putatively horizontally acquired by bacterial pathogens

3. Implications

4. Proposal: How we should be combating bacterial pathogens

Yersinia Type III secretion system

Approach

Idea: Could we identify novel virulence factors by identifying bacterial pathogen proteins more similar to host proteins than you would expect?

1. Primary sequence similarity approach – identifies possible horizontal gene transfer

(2. Structural similarity approach)

• For each complete bacterial and eukaryote genome: BLASTP (and MSP Crunch) analysis of all deduced proteins, searched against non-redundant SWALL database

• Overlay NCBI taxonomy information

• Query database for bacterial proteins who’s top BLASTP scoring “hit” is eukaryotic (and eukaryotic proteins who’s top hit is bacterial)

• Initial Assumption: Three Domains of life (Bacteria, Eukarya, and Archaea) are so divergent that top hits to another Domain are rare

Unusual similarities between Bacteria & Eukaryote genes: Sequence similarity-based approach

• Problem: If a gene transfer occurs from a eukaryote to an ancestor of closely related bacteria top hit will be to other bacteria

• Therefore, perform similar query, but filtering different taxonomic groups from the analysis…

Unusual similarities between Bacteria & Eukaryote genes: Sequence similarity-based approach

Bacteria 1 closely related Bacteria 2 bacteria (same species,

family, etc)

Eukaryote

BAE-watch Database: Bacterial proteins with unusual similarity with Eukaryotic proteins

Problem: Proteins highly conserved in the three domains of life

Top hit to a protein from another domain may occur by chance.

“StepRatio” score helps detect these.

Example:Glucose-6-Phosphate Reductase

Example of a case with a high StepRatio:

Enoyl ACP reductase

PhyloBLAST – a tool for analysisBrinkman et al. (2001) Bioinformatics 17:385-387.

BAE-watch: Analysis of Haemophilus influenzae Rd-KW20 proteins for unusual eukaryotic protein similarities

Genome data for…

Anthrax Necrotizing fasciitis Cat scratch disease Paratyphoid/enteric feverChancroid Peptic ulcers and gastritisChlamydia Periodontal diseaseCholera PlagueDental caries PneumoniaDiarrhea (E. coli etc.) SalmonellosisDiphtheria Scarlet feverEpidemic typhus ShigellosisMediterranean fever Strep throatGastroenteritis SyphilisGonorrhea Toxic shock syndromeLegionnaires' disease Tuberculosis Leprosy TularemiaLeptospirosis Typhoid feverListeriosis UrethritisLyme disease Urinary Tract InfectionsMeliodosis Whooping cough Meningitis +Hospital-acquired infections

Bacterial Pathogens

Chlamydophila psittaci Respiratory disease, primarily in birdsMycoplasma mycoides Contagious bovine pleuropneumoniaMycoplasma hyopneumoniae Pneumonia in pigsPasteurella haemolytica Cattle shipping feverPasteurella multicoda Cattle septicemia, pig rhinitisRalstonia solanacearum Plant bacterial wiltXanthomonas citri Citrus cankerXylella fastidiosa Pierce’s Disease - grapevines

Bacterial wilt

Trends in this Sequence-based Analysis

• Identifies the strongest cases of lateral gene transfer between bacteria and eukaryotes

• Most common:

Bacteria Unicellular Eukaryote

Makes sense:

Bacteria to Multicellular eukaryote must involve germline

Eukaryote to Bacteria must not involve introns

Trends in this Sequence-based Analysis

• Identifies nuclear genes with potential organelle origins

• A control: Method identifies all previously reported Chlamydia trachomatis “plant-like” genes.

First case: Bacterium Eukaryote Lateral Transfer

0.1

Bacillus subtilis

Escherichia coli

Salmonella typhimurium

Staphylococcus aureus

Clostridium perfringens

Clostridium difficile

Trichomonas vaginalis

Haemophilus influenzae

Acinetobacillus actinomycetemcomitans

Pasteurella multocida

N-acetylneuraminate lyase (NanA) of the protozoan Trichomonas vaginalis is 92-95% similar to NanA of Pasteurellaceae bacteria.

de Koning et al. (2000) Mol Biol Evol 17:1769-1773

Pasteurellaceae

N-acetylneuraminate lyase – role in pathogenicity?

Pasteurellaceae

•Mucosal pathogens of the respiratory tract

T. vaginalis

•Mucosal pathogen, causative agent of the STD Trichomonas

N-acetylneuraminate lyase (sialic acid lyase, NanA)

Involved in sialic acid metabolism

Role in Bacteria: Proposed to parasitize the mucous membranes of animals for nutritional purposes

Role in Trichomonas: ?

Hydrolysis of glycosidic linkages of terminal sialic residues in glycoproteins, glycolipids SialidaseFree sialic acid

Transporter

Free sialic acid NanA

N-acetyl-D-mannosamine + pyruvate

Another case: A Sensor Histidine Kinase for a Two-component Regulation System

Signal Transduction “In General”

Histidine kinases more common in bacteria

Ser/Thr/Tyr kinases more common in eukaryotes

However, a histidine kinase was recently identified in fungi, including pathogens Fusarium solani and Candida albicans

How did it get there?

Candida

Neurospora crassa NIK-1

Fusarium solani FIK2 Streptomyces coelicolor SC4G10.06c

Candida albicans CaNIK1

Escherichia coli RcsC

Erwinia carotovora RpfA / ExpSEscherichia coli BarASalmonella typhimurium BarA

Pseudomonas aeruginosa GacS

Pseudomonas fluorescens GacS / ApdAPseudomonas tolaasii RtpA / PheN

Pseudomonas syringae GacS / LemA

Pseudomonas viridiflava RepAAzotobacter vinelandii GacS

0.1

Streptomyces coelicolor SC7C7.03

Xanthomonas campestris RpfCVibrio cholerae TorS

Escherichia coli TorS

Fusarium solani FIK1Fungi

Pseudomonas aeruginosa PhoQ

100

100

51100

100

100

100

100100

100

100

100

100

86

54

39

100

100

Streptomyces Histidine Kinase. The Missing Link?

Virulence Factor ( )in every organism examined to date

Brinkman et al. (2001) Infection and Immunity 69:5207-5211

“Plant-like” genes in Chlamydia• Proteins: Unusually high number most similar to plant

proteins

• Previous proposal: Obtained genes from a plant-like amoebal host?

(A relative of Chlamydiaceae infects Acanthamoeba. Chlamydiaceae: Obligate intracellular pathogens)

• However Acanthamoeba relationship to plants very controversial

“Plant-like” genes in ChlamydiaNCBI GI Protein description Subcellular localization in plants

4377270 Glycyl tRNA Synthetase Chloroplast

4376626 cADP/ATP Translocase Chloroplast

4376667 cGlycogen Hydrolase Chloroplast

4377189 GTP Cyclohydratase & DHBP Synthase Chloroplast

4377237 cBeta-Ketoacyl-ACP Synthase Chloroplast

4376686 cEnoy-Acyl-Carrier Reductase Chloroplast

4376591 cThioredoxin Reductase Chloroplast

4377185 Metal Transport P-type ATPase Chloroplast

4377346 Similar to NA+/H+ Antiporter Chloroplast

4376650 cPhosphate Permease Chloroplast

4376637 GcpE protein Chloroplast

4376637 Tyrosyl tRNA Synthetase Chloroplast

4377360 cMalate Dehydrogenase Chloroplast

4376763 GTP Binding protein Chloroplast

4376911 cADP/ATP Translocase Chloroplast

3329179 Phosphoglycerate Mutase Chloroplast

4377281 cGlycerol-3-Phosphate Acyltransferase Chloroplast

4376993 ABC Transporter ATPase Chloroplast

4376509 dDeoxyoctulonosic Acid Synthetase Chloroplast

4376872 eSugar Nucleotide Phosphorylase Chloroplast

“Plant-like” genes in Chlamydia

6578112 rRNA Methytransferase Chloroplast

3329217 HSP60 Chloroplast

3328745 cPhosphoribosylanthranilate Isomerase Chloroplast

6578104 cAspartate Aminotransferase Chloroplastf

4377328 cPolyribonucleotide Nucleotidyltransferase Chloroplastf

4377362 Putative D-Amino Acid Dehydrogenase Chloroplastg

4377331 Cytosine Deaminase Chloroplast?h

4376915 Lipoate-Protein Ligase A Mitochondrial

4377272 Glycogen Synthase N/Ai

4377065 cDihydropteroate Synthase N/Ai

4377239 cInorganic Pyrophosphatase N/Ai

4376904 Uridine 5’-Monophosphate Synthase N/Ai

4377173 cUDP-Glucose Pyrophosphorylase N/Ai

4376815 GutQ/Kpsf Family Sugar-Phosphate Isomerase Mitochondrial?j

“Plant-like” genes in Chlamydia

• Endosymbiotic theory

• Rickettsia: Many eukaryotic-like genes

• Synechocystis: Many plant-like genes

• Does Chlamydia share an ancient ancestral relationship with the ancestor of the Chloroplast?

Chlamydiaceae share an ancestral

relationship with Cyanobacteria and

Chloroplast0.1

Pyrococcus furiosus (Archaea)

Thermotoga maritima

Aquifex pyrophilus

Bacillus subtilis

Chlamydophila pneumoniae

Chlamydophila psittaci

Chlamydia muridarum

Chlamydia trachomatis1000

7041000

Chlamydomonas reinhardtii

Klebsormidium flaccidum

Zea mays

Nicotiana tabacum1000

988

998

Synechococcus PCC6301

Synechocystis PCC6803

Microcystis viridis1000

1000

1000

530

Escherichia coli

Zea mays mitochondrion

Rickettsia prowazekii

Caulobacter crescentus

868986

764

349

1000

538

Chloroplasts

Cyanobacteria

Chlamydiaceae

16S rRNA

Chlamydiaceae share an ancestral relationship with Cyanobacteria and Chloroplast

L3

L4

L23

L2

S19

L22 S3

L16 L29

S17

L14

L24

L5

S14 S8

L6

L18 S5

L30

L15S10

EscherichiaBacillusThermatogaSynechocystisChlamydia

Unique shared-derived characters unite Chlamydiaceae and Synechocystis

Chlamydiaceae “plant-like” genes reflect an ancestral relationship with Cyanobacteria and the Chloroplast

• Chlamydiaceae do not appear to be exchanging DNA with their hosts

• Existing knowledge of Cyanobacteria may stimulate ideas about the function and control of pathogenic Chlamydia?

Brinkman et al. (2002) Genome Research 12:1159-1167.

Overview

1. High pathogen-host protein similarities: detecting horizontal gene transfer

2. Characteristics of proteins/genes putatively horizontally acquired by bacterial pathogens

3. Implications

4. Proposal: How we should be combating bacterial pathogens

Horizontal Gene Transfer and Bacterial Pathogenicity

Transposons: ST enterotoxin genes in E. coli

Prophages:Shiga-like toxins in EHECDiptheria toxin gene, Cholera toxinBotulinum toxins

Plasmids:Shigella, Salmonella, Yersinia

Pathogenicity Islands:

Uro/Entero-pathogenic E. coliSalmonella typhimuriumYersinia spp.Helicobacter pyloriVibrio cholerae

Pathogenicity Islands

Associated with

– Atypical %G+C– tRNA sequences– Transposases, Integrases and other mobility genes– Flanking repeats

IslandPath: Aiding identification of Pathogenicity Islands and other Genomic Islands

Yellow circle = high %G+C

Pink circle = low %G+C

Region of unusual dinucleotide bias

tRNA gene lies between the two dots

rRNA gene lies between the two dots

Both tRNA and rRNA lie between the two dots

Dot is named a transposase

Dot is named an integrase

_

Hsiao et al. (2003) Bioinformatics 19: 418-420

Dinucleotide bias analysis

Genome divided into “ORF-clusters” of 6 consecutive ORFs

For each ORF cluster,the average absolute dinucleotide relative abundance difference is

where f (fragment) is derived from sequences in an ORF-cluster g (genome) is derived from all predicted ORFs in the genome

Dinucleotide relative abundance is *XY = f*XY/f*Xf*Y

where f*X denotes the frequency of the mononucleotide X f*XY the frequency of the dinucleotide XY

|)(*)(*|16

1),(* gfgf xyxy

See Hsiao et al. (2003) Bioinformatics 19: 418-420

and Karlin, S. and Burge, C (1995). Trends in Genetics 1995 11:283-90 for review

Dinucleotide bias analysis

ORF-clusters sampled in an overlapping manner (shift by one ORF at a time)

The mean is calculated by averaging the results from all ORF-clusters in the genome

Regions with greater than 1 standard deviation away from the mean are marked on the IslandPath graphical display with strikethrough lines

Why did we use 6 ORFs per cluster?- Not enough bp in a single ORF to get a good estimate - 4.5kb (corresponding to approximately 6-8 ORFs) is required for “reliable estimation

of nucleotide composition” (Lawrence and Ochman, J Mol Evolution 1997 44:383-97)

),(* gf

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Boxes: Known islands in the Salmonella typhi genome

What features best predict Islands?

Examined prevalence of features in over 200 known islands

• 94% of islands contain >25% dinucleotide bias (majority have >75% dinucleotide bias coverage)

• Mobility genes identified in >75% (but ID recently improved)

• Atypical %G+C (above cutoff used in Brinkman et al., 2002) not over 50% coverage on average, and tRNA genes not observed with >50% of known islands

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Boxes: “Insertions” in the Salmonella typhi genome verses Salmonella typhimurium

Properties of genes in these islands?

Defined a “putative island” as

– 8 or more genes in a row with dinucleotide bias

Functional category analysis Any difference for genes in islands verses genome?

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Hypothetical genes are more common in putative islands vs the genome

(Paired T test P= 6.8E-19)

Genome

Put. Islands

Analysis 1: COG functional category analysis

Analysis 2: SUPERFAMILY HMM search results

SUPERFAMILY: a set of HMMs built from SCOP superfamilies

Fewer ORFs in the putative islands were assigned to a SUPERFAMILY class

Genome

Put Islands

Paired T test P= 3.3E-14

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Analysis 3: Gene size in Putative Islands vs. “Non-Islands”

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100

150

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Me

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bp

)ORFans (genes with no homologs among 60 microbial genomes) tend to be shorter genesAre genes in putative islands shorter as well on average?

In most cases, average ORF length in putative islands is shorter

Non Island

Put. Islands

Paired T test P= 7.1E-34

Analysis 4: COG analysis after removing ORFs <300 bp

Genes may be less well predicted in such island/atypical dinucleotide bias regions

Some genomes still show marked increase % hypothetical genes in islands verses genome

Hypothetical genes more common in islands?

Paired T test P= 0.0016

0

10

20

30

40

50

60

70

80

% h

yp

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Genome

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Summary: Bacteria gene transfer analysis

• No cases identified in our database to date of clear, recent horizontal gene transfer between bacteria and a multicellular eukaryote (involving >80% sequence similarity)

The pathogens studied are not commonly acquiring genes from their hosts, or vice versa

• Bacterial and eukaryotic pathogens may have exchanged genes

• Overall increased prevalence of hypothetical genes in putative bacterial genomic islands? Cautionary note about gene prediction accuracy

Overview

1. High pathogen-host protein similarities: detecting horizontal gene transfer

2. Characteristics of proteins/genes putatively horizontally acquired by bacterial pathogens

3. Implications

4. Proposal: How we should be combating bacterial pathogens

Implications: Evolution of Pathogenicity

Pathogen mimicry of their host: Convergent evolution or genes selectively maintained

Gene exchange between pathogens: “Arms Deals”

Pathogens and “The Art of War”

“What is of supreme importance in war is to attack the enemy's strategy. Next best is to disrupt his alliances by diplomacy. The next best is to attack his army. And the worst policy is to attack cities.”

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GOVERNMENTGenome CanadaGenome Prairie

Genome BCGovt of Saskatchewan

Functional Pathogenomics of Mucosal Immunitywww.pathogenomics.ca

• BC Pathogenomics group Ann M. Rose, Yossef Av-Gay, David L. Baillie, Fiona S. L. Brinkman, Robert

Brunham, Artem Cherkasov, Rachel C. Fernandez, B. Brett Finlay, Hans Greberg, Robert E.W. Hancock, Steven J. Jones, Patrick Keeling, Audrey de Koning, Don G.

Moerman, Sarah P. Otto, B. Francis Ouellette, Nancy Price, William Hsiao.

• Jeff Blanchard (NCGR, New Mexico) and Olof Emanuelsson (Stockholm Bioinformatics Center)

• Peter Wall Institute for Advanced Studies, Genome Canada