1. Towards modeling epigenetic phase variation of virulence factors
Intro: there is a reason I am before Mustafa!! Towards, vs fait accompli
Marjan van der Woude
Centre for Immunology and Infection
DEPARTMENT OF BIOLOGY

2. Expression of Virulence factors
Haraga 2008
Infectious dose
Bottlenecks

3. Phase variation: Heritable yet reversible gene expression
Cell division
Cell divisions
Switch frequency
restreak
1 in cells switch per generation
lacZ reporter

4. Cells in a clonal population may never have identical phenotype2.
In absence of and despite of varying environmental conditions 1.
Variable level of response within population
Phase variation
Results in heterogeneous clonal population with cells expressing (ON) and not expressing gene(OFF).

5. Why study population heterogeneity?
Interesting biology we may be missing:
Host- pathogen /commensal interactions, interaction with (abiotic) environment, biofilms, resistance
Losick lab
Mention salmonellla mechanisms unknown! And coli…..
If it is really that important should every pathogen have it or is this a reflection of the nature of interactions- which host, how long (vibrio short, etc)
End argue that this is a fascinating but also critical towards understanding the behaviour of populations in natural environments- modeling disease
Wider implications:
Combating Infectious Disease
Diagnostics, Epidemiology, Vaccine development

6. Biological significance of phase variation?
Evade the immune system
?Alters host pathogen interactions?
OFF phase: loss of antigen leads to loss function - functional redundancy?
Baumler !
A future event which is possible but can not predicted with certainty
Bacillus subtilis (soil) (4.2 Mb genome)
swrA gene (SSM) - swarming behavior
Kearns DB, et al 2004 Mol Microbiol. 52:
PV of adhesins:
?Facilitates bacterial dispersal?
(from biofilms or colonized host tissue)

7. Phase variation: Heritable yet reversible gene expression
Cell division
Cell divisions
Switch frequency
restreak
1 in cells switch per generation
lacZ reporter

8. Reporter fusions to analyze PV: gfp: Green Fluorescent Protein
Also for Flow cytometry
Alternatives:
lux
lacZ
Native protein
Single cells: overlay of phase contrast (all cells) and fluorescent image (ON cells, GFP+)

9. Analyze and Visualize an infrequent event
Microbial Challenge #1
Getting the data:
Analyze and Visualize an infrequent event
Lab vs during infection!
Suitability
-population, individual cells
-lab, in vitro or infection model
Sensitivity (need single copy for PV)
Reporter relation to “native” protein?

10. Phase variation controlled by DNA methylation
(epigenetic)
OxyR
OFF
-35
-10
GATCs
Protein CDS
promoter ON
Protein CDS
Dam
Example: OxyR is a repressor but can only bind if 3 Dam target sequences (GATC) are unmethylated. Once OxyR is bound, Dam can not access GATC.

11. Competition DNA binding protein and processive enzyme
OFF UM ON
METH
Stochastic elements: competition, concentration of proteins (local and cellular) HM
Competition DNA binding protein and processive enzyme
Actual DNA and protein concentration (at site) [Kaminska et al 2010]
Role passage DNA replication fork(s) [Kaminska et al 2010]
Other growth related variables

12. Significance OxyR binding affinity
Role of each GATC
OFF ON
WTK12
GATC mutants x
(NA locked Off)
Altered switch frequency
GATC-I mutant On to OFF especially altered: increased almost 10 fold
Effect DESPITE sufficient OxyR x
WTRS218
Altered switch frequency

13. Microbial Challenge #2 Microbial Challenge #3 Getting the data:
Acquiring relevant numerical data
(low concentration proteins and enzyme)
Lab vs during infection!
Relevant: in cell vs in vitro!
Microbial Challenge #3
Reduce complexity w/o oversimplifying
(include DNA replication, growth?)

14. OxyR and Dam-dependent PV: variation on a theme
E. coli
agn family
OFF ON
Salmonella enterica sp.
gtr ON
OFF
Sarah Broadbent

15. “Molecular Rules” Dam-dependent PV?ON
OFF
agn family
Dam processivity- inter and intra? Location
RNA polymerase
DNA replication
gtr family
Agn- outer membrane protein family in E. coli
Gtr- LPS modification operons in Salmonella
Both with evidence of past horizontal (phage) transfer

16. Expression of gtr can affect Salmonellae serotyping >2500 serovars
Strain
LT2
14028
DT104
SL1344
TR7095 …
Genus Species Subspecies Serotypes
>98% of human clinical isolates
Typhimurium
Typhi
Choleraesuis
Paratyphi
Enteriditis …
Enterica (I)
Salamae (II)
Arizonae (IIIa)
Diarizonae (IIIb)
Houtenae (IV)
Indica (VI)
Serotyping main way that outbreaks are characterized!
Bongori (V) …
Salmonella
Serotypes (Kauffmann-White scheme)
Based on immunoreactivity of two surface antigens
i) O Antigen (LPS)
ii) H Antigen (Flagellar) …
Enterica … … …

17. gtr operons modify the O-antigen
0.1
Enteritidus PT4_II
Gallinarum_II
Dublin_III
Typhi CT18_II
Typhi TY2_I
Paratyphi A_I
Typhimurium D23580_BTP1
Cholerasuis_II
Infantis_II
Cholerasuis_III
Infantis_I
Cholerasuis_I
Hadar_1
Phage ST104
Phage ST64T
Typhimurium DT104_III
Paratyphi A_III *
Phage P22
Hadar_II
Typhimurium SL1344_II
Typhimurium D23580_II
Typhimurium DT10_I
Typhimurium DT2_I
Typhimurium LT2_II
Choleraesuis_IV *
Infantis_III
Typhi CT18_I
Typhi TY2_II
Paratyphi A_II *
Enteritidus PT4_I
Gallinarum_I
Typhimurium DT2_II
Typhimurium LT2_I
Typhimurium SL1344_I
Typhimurium DT104_II
Paratyphi B
Typhimurium D23580_I
Group 3
SPI16-like
Group 4
Group 1
Group 2
∆gtrA
∆gtrB
gtrC
(Pseudo gtrB)
L C + increasing #O repeats
∆oafA
∆Lt2_I
∆Lt2_II WT
ptac Lt2_1
Lipid-core
LPS gel
gtr P22 Glc:O1 1 6
oafA OAc:O5
gtrABC Lt2_I Glc:O122 1 4
Gal Rha Man
Abe
O4, O12 ?
S. Typhimurium LT2 O-antigen
Which gtr cluster conveys which O-serotype?

18. Model for gtr phase variation;Dam and OxyR
gtrA
OxyR B
OxyR C
-10
-35 +1
OxyR A
RNApol
CH3
CH3
CH3
CH3
gtrA
OxyR C
-10
-35 +1
OxyR A
OxyR B
OFF
OxyR
Broadbent et al 2010

19. modifies the O-antigen and phase varies
gtrABC:
modifies the O-antigen and phase varies
0-4 copies of gtr-family operons per Salmonella genome (phage remnants)
Also on phage genomes
If 3 of 4 copies PV then one can have 8 phenotypic variants in a population just from the gtr family!
Combine with PV of possibly as many as 11 adhesins …..
Rmeind: agn with 2 GATC’s: altered switch rates!
(Neisseria PV over 210 variants theoretically possible!)

20. Predict PV rates / regulation based on DNA sequence and paramters?
WebLogo of 33 gtr regulatory regions identifies putative important elements
Predict PV rates / regulation based on DNA sequence and paramters?
Spacing closest two gatcs same as agn gatcII and gatcIII-
mutate either of those in agn and loose phase variation
OxyR half b.s.motif : ATAG/T.T…A.CTAT

21. Salmonella LPS modification project
BIOCHEMISTRY
Relate genes to chemical modification
ROLE OF MODIFICATION
Host-Pathogen interactions
From molecular stochastic events to how it effects host -pathogen stohcastic events
MOLECULAR
-Genome sequencing
SEROTYPING
-Improve ? Complete, Molecular diagnostics
EXPRESSION
-Phase variation /Regulated?

22. Can we predict Dam-dependent PV from DNA sequence
Can we predict Dam-dependent PV from DNA sequence? Any methylation dependent PV? * *
LPS modification DNA methyl
End : signficance virulence (and funding…???) * * *
OxyR and Dam
Lrp and Dam
from
van der Woude and Baumler, 2004

23. “Molecular Rules” Dam-dependent PV?ON
OFF
agn family
Dam processivity- inter and intra? Location
RNA polymerase
DNA replication
gtr family
Pap family
Lrp, needs PapI

24. Devising and executing experiments within adhering to those wishes
Microbial Challenge #4
Testing relevance
Choosing the strain and conditions that represent a natural situation of relevance
Lab vs during infection!
Relevant: in cell vs in vitro!
Microbial Challenge #5
Devising and executing experiments within adhering to those wishes

25. Challenge(s) #6 What is enough data to make modeling feasible?
How to decide if modeling is a worthwhile endeavor for the system?
If the system is the best for the modeling?
Lab vs during infection!
Relevant: in cell vs in vitro!

26. With previous support from NSF
Renata Kaminska
Sarah Broadbent
Mark Davies
Matt Lakins
previous lab members
Support from
With previous support from NSF
Centre for Immunology and Infection
DEPARTMENT OF BIOLOGY