Bio305 Lecture on Gene Regulation in Bacterial Pathogens
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Transcript of Bio305 Lecture on Gene Regulation in Bacterial Pathogens
Bio305 Regulation of Bacterial Virulence
Professor Mark Pallen
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
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
Regulation of VirulenceA 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
Trp operon Post-translational Regulation
Stability of protein, controlled cleavage Covalent modifications
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
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
Operons and Promoters
Transcription factors
DNA binding domain fits into major groove
Dimerisation domain: may also be sensing domains
Sequence typically contains inverted repeats
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. DtxR regulon) 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
Regulation of Pathogen Gene ExpressionA 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
The DtxR regulon: not so simple!
Transcriptional Regulatory Networks Six basic network
motifs occur in TRNs
When combined can produce complex unpredictable counter-intuitive effects, understandable only through sophisticated models
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
Helix-Turn-Helix Regulators Many TFs contain
helix-turn-helix motif recognition helix stabilizing helix
AraC family ToxT in V. cholerae HilD, RamA in
Salmonella LysR family
QseA, QseD in EPEC
Stabilising helix
Recognition helix
turn
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
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
Two-Component Regulatory Systems
P
His
AspP
RNA polymera
se
Histidine sensor kinase
Response regulator
Signal
Two-Component Regulatory Systems TCSs that regulate toxin gene expression
BvgS/BvgA in Bordetella pertussis (pertussis toxin and adenylate cyclase toxin)
VirS/VirR in Clostridum perfingens (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
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 autoinducer molecule (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 Acyl homoserine lactone first to be
identified
http://upload.wikimedia.org/wikipedia/commons/c/cf/Quorum_sensing_diagram.png
Regulatory RNAs
Q: How can we study virulence gene expression and its regulation?
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
Clues from DNA sequences
Pathogen gene expressionDNA-protein interactions
Gel retardation assays Run DNA alone
alongside DNA and protein on gel
DNA bound to protein retarded in gel
Pathogen gene expressionDNA-protein interactions
Footprinting assay Mix DNA with protein Perform limited
digestion with DNAse I
Identify regions which are protected from digestion
A C G TFootprint
protected
Mix protein and labelled DNA
Protein protects DNA from nuclease
DNase
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
Measurement of pathogen gene expressionExpression must be
measured under defined environmental conditions
Stressful versus basal heat shock, acid stress,
starvation stress, etc In vitro versus in vivo
Broth or plate Inside cells, organs,
animal
Direct assay versus via assay of reporter ease versus artefacts
Single gene versus many
Opportunistic searches versus global surveys
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
lacZ fusions
promoterless lacZ
beta-galactosidase
rbs/ATG
rbs/AUG
substrate colour change
mRNA
promoter from test gene
lacZ fusions
promoterless lacZ transposon
Replica-plate onto X-gal plates
High iron Low iron
Select for further study
In Vivo Expression Technology (IVET) A genetic approach positively
selects for bacterial genes specifically induced when bacteria infect their host, but not expressed under lab conditions
IVET vectors contain random 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
Esssential in host LacZ
Random DNA provides promoter
http://commons.wikimedia.org/wiki/File:Mouse.svg
Measuring individual gene expression can be assayed by quantitative real-time
reverse transcription polymerase chain reaction (RT-PCR)
promoter terminator
1 2 3 4
1 2 3 4 1 2 3 4
PCR RT-PCR
transcript
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
Microarrays Arrange large number
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
Control cells Test cells
RNA-SeqWhole 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
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
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