2. Introductory Lectures
1: Pathogen Biology
2: Genetics of Bacterial Virulence
3: Regulation of Bacterial Virulence
Later lecture blocks from me on
Bacterial Genomics
Bacterial Protein Secretion
3. Learning Objectives
At the end of this lecture, the student will be able to
provide a definition of terms related to bacterial gene
regulation
describe the hierarchical regulation of bacterial gene
expression
outline the kinds of transcriptional regulators and
regulatory mechanisms found in bacteria
describe how gene expression can be analysed
experimentally
4. Regulation of Virulence
A multi-layered hierarchy
Changes in DNA sequence
Gene amplification
Genetic rearrangements e.g. flagellar phase variation
Transcriptional Regulation
Transcription Factors (TFs): proteins that bind DNA and alter
transcription
Simplest system: a TF that recognises a single signal and
regulates expression of a single gene
Translational Regulation
Trpoperon
Post-translational Regulation
Stability of protein, controlled cleavage
Covalent modifications
5. Pathogen gene expression
Gene expression is regulated
Inducible versus constitutive genes
Wasteful if always constitutive
Artificial constitutive constructs decrease fitness
In response to changes in environment
Signal sensing
Signal transduction
6. Operons and Promoters
Single genes rare: most genes are in operons
multiple genes encoded in single polycistronic mRNA
genes within an operon subject to common regulatory
mechanisms
Promoter
DNA sequence that defines the binding site of RNA
polymerase and transcription factors
TFs function act as activators of transcription or
repressors that prevent RNA polymerase binding to the
promoter
Operons often have more than one promoter and
can be subject to a complex hierarchy of regulation
8. Transcription factors
Dimerisation domain: may also be sensing domains
DNA binding domain fits
Sequence typically contains
into major groove
inverted repeats
9. Pathogen gene expression
Transcriptional regulatory networks (TRNs)
encompass TFs and their target genes
Simple networks of single TF/single operon are rare
Instead co-ordinate regulation of gene expression
multiple genes/operons co-regulated
by common regulator (regulon, e.g. DtxRregulon)
by common stimulus (stimulon or response, e.g. iron-
starvation response)
TRNs overlap; signal transduction pathways are
complex
mutations in global regulators cause pleiotropic effects
~ 50 global TRNs in E. coli
10. Regulation of Pathogen Gene Expression
A simple system: Diphtheria
tox gene regulated by
repressor DtxR
an iron-activated TF
Fe2+ binds DtxR which
represses expression of tox
Under iron limiting
conditions, 2Fe-DtxR-tox
operator dissociates and
toxin gene is expressed
12. Transcriptional Regulatory Networks
Six basic network motifs When combined can
occur in TRNs produce complex
unpredictable counter-
intuitive effects,
understandable only
through sophisticated
models
13. Global Regulation
Regulons combine in
ever-more complex TRNs
until they encompass all
gene expression in the
bacterial cell
Some regulators act
globally to co-ordinate
expression of 100s or
even 1000s of genes
Ma H et al. Nucl. Acids Res.
2004;32:6643-6649
14. Helix-Turn-Helix Regulators
Many TFs contain helix-
turn-helix motif Stabilising helix
recognition helix
stabilizing helix
turn
AraC family
ToxT in V. cholerae Recognition helix
HilD, RamA in
Salmonella
LysR family
QseA, QseD in EPEC
15. Signal transduction
External signal not always
transmitted directly to target to
be regulated
Can detected by a sensor and
transmitted to regulatory
machinery (signal transduction)
Can be extensive multi-
component signal transduction
pathways with partner switching
e.g. coupling protein secretion
and gene regulation in type III
secretion
16. Two-Component Regulatory Systems
Common kind of signal transduction occurs in two-
component regulatory systems
Sensor kinase: (cytoplasmic or membrane) detects
environmental signal and autophosphorylates
Response regulator: (cytoplasm) DNA-binding protein
that regulates transcription; phosphorylated by sensor
kinase
Some systems have multiple regulatory elements
~50 two-component systems in E. coli
Potential for cross-talk
18. Two-Component Regulatory Systems
TCSs that regulate toxin gene expression
BvgS/BvgA in Bordetellapertussis (pertussis toxin and
adenylatecyclase toxin)
VirS/VirR in Clostridumperfingens(alpha-toxin and others)
AgrA/AgrC in S. aureus (numerous toxins)
CovS/CovR in S. pyogenes(streptolysin S, streptokinase)
TCSs that regulate other virulence factors
OmpR/PhoP in enterics
SsrA/SsrB in Salmonella Spi2
19. Quorum sensing and virulence
mechanism by which bacteria
assess their population density
ensures sufficient number of
cells present before initiating
response that requires certain
cell density to have effect
Each species produces specific
autoinducermolecule (blue)
Diffuses freely across cell
envelope
Reaches high concentrations
inside cell only if many cells are
near
Binds to specific activator and
triggers transcription of specific
genes (red)
Several different classes of
autoinducers
Acylhomoserinelactone first to
be identified
http://upload.wikimedia.org/wikipedia/commons/c/cf/Qu
orum_sensing_diagram.png
22. Q: How can we study virulence gene
expression and its regulation?
23. Clues from DNA sequences
Sequence Analysis allows you to identify
Identify TFs by homology
Promoter consensus sequences
Binding sites for regulatory factors
RpoN, HIS, Crp, Lrp, Fur, etc
Operons
24. Pathogen gene expression
DNA-protein interactions
Gel retardation assays
Run DNA alone
alongside DNA and
protein on gel
DNA bound to protein
retarded in gel
25. Pathogen gene expression
DNA-protein interactions
Footprintingassay
Mix DNA with protein
Perform limited Mix protein and labelled DNA
digestion with DNAse I
Protein
Identify regions which protects DNA
DNase
from
are protected from nuclease
digestion protected
Footprint A C G T
26. Chromatin
Immunoprecipitation
nucleoprotein in cells is
cross-linked, extracted,
sonicated to give
sheared
DNA fragments
Anti-TF Ab used to
enrich the TF-cross-
linked DNA fragments.
IP DNA and control DNA
analysed using
microarray (ChIP-chip)
or high-throughput
sequencing (ChIP-seq)
http://commons.wikimedia.org/wiki/File:ChIP-sequencing.svg
27. Measurement of pathogen gene expression
Expression must be Direct assay versus via
measured under defined assay of reporter
environmental conditions
ease versus artefacts
Stressful versus basal
heat shock, acid stress, Single gene versus
starvation stress, etc many
In vitro versus in vivo Opportunistic searches
Broth or plate
Inside cells, organs, animal
versus global surveys
28. Reporter gene fusions
Fuse reporter gene to test gene
Exploit enzymatic activity of reporter gene product
Easier to measure reporter gene product
optimised universal assay
maybe less toxic to cells
Promoter traps to identify unknown genes
Responding to stimulus
Regulated by given regulator
29. lacZ fusions
promoter from test gene
rbs/ATG
promoterless lacZ
rbs/AUG
mRNA
beta-galactosidase
substrate colour change
30. lacZ fusions
promoterless lacZ transposon
Replica-plate onto X-gal
plates
High iron
Low iron
Select for further study
31. In Vivo Expression
Technology (IVET)
Esssential in
A genetic approach positively host LacZ
selects for bacterial genes
specifically induced when bacteria
infect their host, but not expressed
under lab conditions
IVET vectors contain random Random DNA provides promoter
promoter fragment and promoter-
less gene that encodes selective
marker required for survival in host
Random integration of IVET vector
into chromosome creates pool of
recombinant pathogens
Only bacteria that contain the
selective marker fused to a gene
that is transcriptionally active in the
host are able to survive
Post-selection screening for Lac-
colonies finds promoters that are
only active in vivo
http://commons.wikimedia.org/wiki/File:Mouse.svg
33. Measuring global gene expression
can be analysed using
microarrays
RNA-Seq
Can be applied to
in vitro conditions e.g. acid stress, heat shock
in vivo conditions after isolation of bacterial RNA from
infected cells and tissues
34. Microarrays
Arrange large number
Control cells Test cells
of hybridisation targets
in gridded array
Variety of approaches
Provides global
genome-wide survey of
1000s of genes
Assay changes in
expression of every
gene after change in
environment or in
regulator mutant
35. RNA-Seq
Whole Transcriptome Shotgun Sequencing
high-throughput sequencing of cDNA
advantages over microarrays
no probes or genome sequence needed
unbiased view of transcriptome
no interference from non-specific hybridisation
discovery of novel features, e.g. small RNAs
delineation of operons and untranslated regions
improved sequence annotation
precise high-resolution mapping of sequence data
much greater dynamic range
more discriminatory at high levels of gene expression
more sensitive at very low levels of expression
disadvantage: expense
36. RNA-Seq
Starting material
bacterial RNA
Optional subtraction of
tRNA and rRNA
Generation of cDNA
libraries
High-throughput
sequencing
Bioinformatics
Interpretation of cDNA
sequencing read
histograms
37. Summary
Gene expression, operons, promoters
Pathogen gene expression and its regulation
Transcription factors: HTH, TCS, RNAs
Methods to study virulence gene expression
Bioinformatics, Gel retardation, Footprinting
ChIP, Reporter gene fusions, IVET, RT-PCR
Global gene expression: microarrays, RNA-Seq