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Towards an understanding of global patterns of simple sequence repeat- mediated phase variation during host persistence of Campylobacter jejuni and Neisseria.

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Presentation on theme: "Towards an understanding of global patterns of simple sequence repeat- mediated phase variation during host persistence of Campylobacter jejuni and Neisseria."— Presentation transcript:

1 Towards an understanding of global patterns of simple sequence repeat- mediated phase variation during host persistence of Campylobacter jejuni and Neisseria meningitidis Edinburgh Workshop 29-30th September 2010 Chris Bayliss RCUK Research Fellow Department of Genetics University of Leicester

2 Outline Overview of my research areas Intro to SSRs and phase variation Measuring mutation rates/patterns Phase variation of C. jejuni genes in in vitro and in vivo models Models of SSR-phase variation Issues

3 My Research: Phase Variation Campylobacter jejuni Hb receptors/reversible selection model Mechanistic studies Neisseria meningitidis Haemophilus influenzae In vitro models Colonisation of chickens R-M systems/Phage infection Carriage samples Disease samples Impact of phase variation rate on population structure Selection of phase variants Combined model Experimental models/ Epidemiological samples In silico models

4 Consequences of Localised Hypermutation: Phase Variation ON OFF ON Frequency = to SELECTION /MUTATION SELECTION /MUTATION MUTATION

5 Streisinger Model


7 Insertion

8 Streisinger Model

9 Deletion

10 ATG………..CAAT(30)…..//………….TAGON ATG………..CAAT(29)…..TAGOFF ATG………..CAAT(28)……..TAGOFF ATG………..CAAT(27)…..//………….TAGON ATTATA……..TA(10)…….ATTAAA…//…ATGON ATTATA……..TA(9)…..ATTAAA…//…ATGOFF In-Frame Repeats Promoter-Located Repeats

11 Functions of the Products of Repeat-Associated Genes Adhesins LOS/LPS Biosynthetic Enzymes Iron Acquisition Proteins Capsule Biosynthetic Enzymes Restriction Enzyme Flagella Biosynthetic Enzymes

12 Long Tracts of Simple Sequence Repeats in Bacterial Genomes Repeat Type (min. no. rpts) G/C (8) A/T (10) Di (6) Tetra (5) Penta (3) H. influenzae (Rd) N. meningitidis (MC58) C. Jejuni (NCTC11168) E. coli (K12)

13 Length of PolyG/PolyC Repeat Tracts in C. jejuni Contingency Loci

14 Phase Variation of Simple Sequence Contingency Loci ON OFF ON SELECTION /MUTATION SELECTION /MUTATION What are the mutation rates of SSRs? What are the determinants of SSR mutation rates? What are the fitness implications of differing switching rates? What are the roles of selective and non-selective bottlenecks? What are the implications of multiple SSCL?

15 Campylobacter jejuni:- Phase Variation Frequencies

16 Campylobacter jejuni * Gram –ve commensal of gasterointestinal tract of birds and widespread environmental contaminant * Major agent of foodborne gasteroenteritis * Implicated in autoimmmune diseases such as Guillain-Barre syndrome

17 cj1139c lacZ cat G8 Reporter Constructs for Detecting Phase Variation in Campylobacter jejuni lacZ G8 G11 capA (cj0628/cj0629) CapA -CapA antibodies (surface-located autotransporter) T6-G11 Strain NCTC11168 ON

18 off variant on variant On-to-off Off-to-on

19 Colony Blots of C. jejuni strain probed with anti-CapA ON-to-OFF Freq. -ve = 0.03 (filter 1, 9/8/07) OFF-to-ON Freq. +ve = 0.03 (filter 4, 23/7/07)

20 MHA-VT plates MHA-VT-XGal plates

21 H. influenzaeN. meningitidisC. jejuni %G+C of Genome MMR Genes MutS/MutL/ MutH MutS/MutLNone SSR Mutation Frequencies 1x10 -3 (AGTC30)4x10 -5 (G12)4x10 -3 (G11) Mutational Pattern 90% +1/-1 Deletions>Insertions Unknown >95% +1/-1 Short: ins>del Long: del>ins Cis-Acting Factors Repeat Number Repeat Number Repeat Number Trans-Acting Factors PolI, RNaseHMMR, PolIVUnknown No environmental factors

22 Campylobacter jejuni:- In vitro/In vivo Passage

23 PCR-Based Measurement of Repeat Tract Length GGGGGGGGGG FAM

24 Multiple Passages of Growth in MHB Broth Plate Dilutions Colony Blotting Pick 30 colonies PCR Array Pick 30 colonies Colony Blotting PCR Array Day 0 Day 1 Day 2 Day 3 Day 4 Suspend inoculum Inoculate 5mL MHB Inoculate Plate Dilutions Inoculate 5mL MHB Inoculate Inoculate Pallet the cells

25 Analysis of Phase Variable Genes and Repeat Tracts Constant Inoculum (3.5x10 8 cfu; 6 tubes) Variable Inoculum (from 3.5 x10 8 to 3.5x10 3 cfu; 6 tubes) Inoculum Output CapA Frequency -ve

26 Drift, Bottlenecks, Selection and Hitch- Hiking 6 Genes = 64 Genotypes Random Drift Bottleneck Mutation/Bottleneck Selection Mutation/Selection 1139-off 0031-on 0685-on 1139-off

27 Neisseria meningitidis PorA Phase Variation, Immune Evasion and Variant-Specific Immune Responses During Carriage

28 Escape Assay Modified serum bactericidal assay using large inoculum (1x x10 7 cfu) and multiple passages LPS phase variants with switches in expression of lgtG mediate escape of mAb B5 (translational switching) Escape dependent on size of inoculum, amount of antibody and rate of phase variation Bayliss et al Infect. Immun. 76:5038

29 PV of porA mediates immune escape in vitro *Variants examined had 10C residues in the porA repeat tract *Escape is due to pre-existing variants 11C 10C +/- mAb % human serum +/- mAb % human serum +/- mAb % human serum

30 Correlation of porA PV Expression to Escape *Level of PorA expression is highest when 11C repeat units is present in 8047 *~ 3 fold of reduction in expression of porA Repeat tract changes to expression Whole cell ELISA and lysate western blotting 11C 10C 9C

31 Week 0Week 4Week 12Week 24Week -4

32 Phase Variation of NadA Volunteer1st2nd3rd4th V V V V V V V V Number of tetranucleotide repeats All volunteers colonised with Y:P1.21,16:CC174 OFF 9 and 12 rpts

33 Computer Models

34 Multiple simple sequence contingency loci Multiple loci = multiple potential genotypes Haemophilus influenzae strain Rd has 12 genes containing tetranucleotide repeat tracts, a potential 4096 genotypes (if two genotypes per locus, i.e. ON and OFF) Lic2 locus has three genotypes :- ON- Strong, ON-Weak and OFF (if all 12 loci had 3 genotypes then there is potential genotypes)

35 Computer Model 1 Population founded by single organism which divides by binary fission Three phase variable loci Switching occurs in both directions at the same rates Mutations occur during division giving one genotype of the parental phenotype and one mutant

36 Number of genotypes Number of populations x10 -6 (< 6)3.6x10 -5 (10)1.24x10 -4 (22) Mutation rate (repeat number) Effect of phase variation rate on the amount of genetic diversity produced in 20 generations

37 Effect of phase variation rate on the production of genotypes with multiple switches *Solution is when all three loci have switched from OFF to ON. *30 generations were used. *All cells of the parental genotype were removed at generation 20. *1000 replicates were performed Number of populations containing solution Mutation rate 3.6x x

38 Model 2 Effect of Interval Between Selective Environments Environment A Selection for ON Phenotype Environment B Selection for OFF Phenotype Number of Generations 2, ,000 Mike Palmer and Marc Lipsitch Variable Repeat Number 17 = ON = A 18 = OFF = B 19 = OFF = B 20 = ON = A etc 37 = OFF = B 38 = ON = A

39 Repeat Number Evolution of Repeat Tracts in the Absence of Selection

40 Environmental switch period: generations Fitness advantage:- 0.1 Evolution of Repeat Tracts with Selection and in a Fluctuating Environment

41 Environmental switch period: generations Fitness advantage:- 0.1

42 Environmental switch period: generations Fitness advantage:- 0.1

43 Environmental switch period:- 100 generations Fitness advantage:- 0.1

44 Summary Computer Simulation Model Selection is required to maintain large numbers of repeats in the repeat tracts Repeat number is determined by the frequency of the environmental switch Correlation between repeat number and environmental switch is also influenced by the conferred fitness advantage and mutational pattern

45 Model 3 Model phase shifts in multiple loci using known mutation rates (excludes mutational patterns) Assumes each locus switches independently of other loci (can set PV rate for each gene, but not scalable with tract length changes) Simple deterministic model, average of multiple trees from a Monte Carlo simulation, performed in Excel (maximum of 100 generations)

46 Gene cj0045cj0685cj1326capAcj1139cj0032 Tract PhenotypeOFFONOFF ON Binary code One Isolate B9.1 Sample from Chicken B9 Note:- genotype is not directly correlated with phenotype (i.e. cj0045 is OFF with 9 or 10 repeats Coded phenotypes of all 30 colonies for B9

47 Drift, Bottlenecks, Selection and Hitch- Hiking 6 Genes = 64 Genotypes Random Drift Bottleneck Mutation/Bottleneck Selection Mutation/Selection 1139-off 0031-on 0685-on 1139-off

48 Modelling Changes in the Distribution of Phase Variants:- no selection 6 Phase variable genes = ON/OFF = 64 genotypes Output 1 = all genes at G9 PV rate (0.0015) Output 2 = varied PV rates 0=off, 1=on Output = 100 generations

49 Scientific Issues What factors to include in a model – mutation rate, mutational pattern, population size, fitness, frequency of environmental switching, bottlenecks, number of loci, number of generations How to model – simulation of multiple populations or deterministic model of average solutions

50 Logistical Issues Data collection (sample bias) Computational power Biological and clinical relevance Simultaneous data collection and modelling (local collaborators) Relevance to systems biology Requirement for a modelling community

51 Jean-Philipe Gautier Jacques Marlet Fadil Bidmos Nathalie Ingouf Rebecca Richards Awais Anjum Vladimir Manchev Richard Haig Julian Ketley (University of Leicester) Neil Oldfield Del AlaAldeen Karl Wooldridge Michael Jones Paul Barrow (University of Nottingham) Michael Tretyakov Alexander Gorban (University of Leicester) Michael Palmer Marc Lipsitch Richard Moxon

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