Bio305 Lecture on Gene Regulation in Bacterial Pathogens


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Bio305 Lecture on Gene Regulation in Bacterial Pathogens

  1. 1. Bio305 Regulation of Bacterial Virulence Professor Mark Pallen
  2. 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. 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. 4. 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  Trpoperon Post-translational Regulation  Stability of protein, controlled cleavage  Covalent modifications
  5. 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. 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
  7. 7. Operons and Promoters
  8. 8. Transcription factors Dimerisation domain: may also be sensing domainsDNA binding domain fits Sequence typically containsinto major groove inverted repeats
  9. 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. 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
  11. 11. The DtxR regulon: not so simple!
  12. 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. 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 genesMa H et al. Nucl. Acids Res.2004;32:6643-6649
  14. 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. 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. 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
  17. 17. Two-Component Regulatory Systems Signal Histidine sensor kinase His P Response regulator P RNA Asp polymeras e
  18. 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. 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 orum_sensing_diagram.png
  20. 20. Regulatory RNAs
  21. 21. Q: How can we study virulence geneexpression and its regulation?
  22. 22. 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
  23. 23. 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
  24. 24. 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
  25. 25. ChromatinImmunoprecipitation 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)
  26. 26. Measurement of pathogen gene expressionExpression 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
  27. 27. 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
  28. 28. lacZ fusionspromoter from test gene rbs/ATG promoterless lacZ rbs/AUG mRNA beta-galactosidase substrate colour change
  29. 29. lacZ fusions promoterless lacZ transposon Replica-plate onto X-gal plates High iron Low iron Select for further study
  30. 30. In Vivo ExpressionTechnology (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
  31. 31. Measuring individual gene expression can be assayed by quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) promoter terminator transcript 1 2 3 4 1 2 3 4 1 2 3 4 PCR RT-PCR
  32. 32. 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
  33. 33. 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
  34. 34. 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
  35. 35. 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
  36. 36. 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