1887

Chapter 32 : Functional Transcriptomics for Bacterial Gene Detectives

MyBook is a cheap paperback edition of the original book and will be sold at uniform, low price.

Preview this chapter:
Zoom in
Zoomout

Functional Transcriptomics for Bacterial Gene Detectives, Page 1 of 2

| /docserver/preview/fulltext/10.1128/9781683670247/9781683670230_Chap32-1.gif /docserver/preview/fulltext/10.1128/9781683670247/9781683670230_Chap32-2.gif

Abstract:

Transcriptional profiling is a valuable part of the functional genomics toolbox. Since the developments in nanotechnology and imaging that led to the invention of next-generation sequencing ( ), study of the bacterial transcriptome at the level of the individual nucleotide has proved fruitful. Scientists are now generating increasing amounts of transcriptomic data that need to be managed, analyzed, and stored in an appropriate manner ( ). The current need for systematic and accessible approaches for the analysis of gene expression has focused bioinformatic efforts into developing tools for processing transcriptomic data.

Citation: Perez-Sepulveda B, Hinton J. 2019. Functional Transcriptomics for Bacterial Gene Detectives, p 549-561. In Storz G, Papenfort K (ed), Regulating with RNA in Bacteria and Archaea. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.RWR-0033-2018
Highlighted Text: Show | Hide
Loading full text...

Full text loading...

Figures

Image of Figure 1
Figure 1

Bacterial functional transcriptomics is facilitated by RNA-seq technology. The development of RNA-seq has expanded the range of transcriptome-based techniques that address a variety of biological questions. DROP-seq, RNA-seq of single cells compartmentalized in a droplet; scRNA, single-cell RNA-seq; dRNA-seq, differential RNA-seq; Term-seq, global mapping of 3′ ends of transcripts; ChIP-seq, chromatin immunoprecipitation followed by sequencing; RIP-seq, native RNA immunoprecipitation followed by RNA-seq; GRAD-seq, gradient profiling by RNA-seq; TraDIS, transposon-directed insertion site sequencing; Tn-seq, transposon sequencing. See reference for more details of these techniques. Image by Eliza Wolfson (https://lizawolfson.co.uk) is used under the terms of a creative commons CC-BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode).

Citation: Perez-Sepulveda B, Hinton J. 2019. Functional Transcriptomics for Bacterial Gene Detectives, p 549-561. In Storz G, Papenfort K (ed), Regulating with RNA in Bacteria and Archaea. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.RWR-0033-2018
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of Figure 2
Figure 2

Environmental and genetic regulation of four sRNAs that are iron responsive and/or induced by oxidative stress. Gene expression data are presented for the sRNAs OxyS, RyhB-1, RyhB-2, and STnc3080 (these data can be visualized online at https://tinyurl.com/ya7s466m and https://tinyurl.com/yb5wz7dt). Data are shown as differential expression profiles involving six discrete heat-map blocks, each block being normalized to the condition on the left-hand side. The heat maps show differential expression, a strategy that lacks accuracy when expression levels are extremely low. Absolute (A) and relative (B) expression levels of Typhimurium grown under 21 different conditions (SalComMac). (C) Relative expression levels of the wild-type (WT) and mutant Typhimurium 4/74 grown under different conditions (SalComRegulon). Before experimental validation is considered, it should be ensured that the levels of absolute expression of particular sRNAs are above the expression threshold of 10 TPM units ( ). EEP, early exponential phase; MEP, mid-exponential phase; LEP, late exponential phase; ESP, early stationary phase; LSP, late stationary phase; InSPI2, SPI2-inducing minimal media.

Citation: Perez-Sepulveda B, Hinton J. 2019. Functional Transcriptomics for Bacterial Gene Detectives, p 549-561. In Storz G, Papenfort K (ed), Regulating with RNA in Bacteria and Archaea. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.RWR-0033-2018
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of Figure 3
Figure 3

Environmental and genetic regulation of four sRNAs involved in the envelope stress response. Gene expression data are shown for the sRNAs RybB, RyeF, MicA, and RprA (these data can be visualized online at https://tinyurl.com/y9mskb6j and https://tinyurl.com/ybnr6jja). Panels A, B, and C are as described in the legend to Fig. 2 .

Citation: Perez-Sepulveda B, Hinton J. 2019. Functional Transcriptomics for Bacterial Gene Detectives, p 549-561. In Storz G, Papenfort K (ed), Regulating with RNA in Bacteria and Archaea. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.RWR-0033-2018
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of Figure 4
Figure 4

Environmental and genetic regulation of six sRNAs that respond to oxygen or osmolarity. Gene expression data are shown for the sRNAs FnrS, MicA, SraL, MntS (RybA), STnc1330, and STnc4260 (these data can be visualized online at https://tinyurl.com/yat8qrql and https://tinyurl.com/y8f533gy). Panels A, B, and C are as described in the legend to Fig. 2 .

Citation: Perez-Sepulveda B, Hinton J. 2019. Functional Transcriptomics for Bacterial Gene Detectives, p 549-561. In Storz G, Papenfort K (ed), Regulating with RNA in Bacteria and Archaea. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.RWR-0033-2018
Permissions and Reprints Request Permissions
Download as Powerpoint
Image of Figure 5
Figure 5

Visualization of the STnc1330 sRNA transcript. RNA-seq reads are mapped to the Typhimurium 4/74 genome (plus strand), showing STnc1330 expression under different conditions ( ). (A) MEP, anaerobic shock, and NaCl shock (https://tinyurl.com/STnc1330-NaCl); (B) InSPI2 and InSPI2 low Mg2 (https://tinyurl.com/STnc1330-LowMg); (C) WT InSPI2 versus Δ (https://tinyurl.com/STnc1330-PhoPQ); (D) WT LSP versus Δ (https://tinyurl.com/STnc1330-RpoS). Height of colored tracks represents the normalized sequencing reads at that locus (scale, 0 to 100). All arrows indicate the direction of transcription; TSSs are indicated by bent arrows and predicted Rho (ρ)-independent terminators are denoted by stem-loop structures.

Citation: Perez-Sepulveda B, Hinton J. 2019. Functional Transcriptomics for Bacterial Gene Detectives, p 549-561. In Storz G, Papenfort K (ed), Regulating with RNA in Bacteria and Archaea. ASM Press, Washington, DC. doi: 10.1128/microbiolspec.RWR-0033-2018
Permissions and Reprints Request Permissions
Download as Powerpoint

References

/content/book/10.1128/9781683670247.chap32
1. MacLean D,, Jones JD,, Studholme DJ . 2009. Application of ‘next-generation’ sequencing technologies to microbial genetics. Nat Rev Microbiol 7 : 287 296.[PubMed]
2. Stephens ZD,, Lee SY,, Faghri F,, Campbell RH,, Zhai C,, Efron MJ,, Iyer R,, Schatz MC,, Sinha S,, Robinson GE . 2015. Big data: astronomical or genomical? PLoS Biol 13 : e1002195.[CrossRef][PubMed]
3. Wang R,, Perez-Riverol Y,, Hermjakob H,, Vizcaíno JA . 2015. Open source libraries and frameworks for biological data visualisation: a guide for developers. Proteomics 15 : 1356 1374.[CrossRef][PubMed]
4. Toker L,, Feng M,, Pavlidis P . 2016. Whose sample is it anyway? Widespread misannotation of samples in transcriptomics studies. F1000 Res 5 : 2103.[CrossRef]
5. Heiss JA,, Just AC . 2018. Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO. Clin Epigenetics 10 : 73.[CrossRef][PubMed]
6. Bécavin C,, Koutero M,, Tchitchek N,, Cerutti F,, Lechat P,, Maillet N,, Hoede C,, Chiapello H,, Gaspin C,, Cossart P . 2017. Listeriomics: an interactive web platform for systems biology of Listeria. mSystems 2 : e00186-e16.[CrossRef]
7. Slager J,, Aprianto R,, Veening JW . 2018. Deep genome annotation of the opportunistic human pathogen Streptococcus pneumoniae D39. Nucleic Acids Res.[CrossRef]
8. Kröger C,, MacKenzie KD,, Alshabib EY,, Kirzinger MW,, Suchan DM,, Chao TC,, Akulova V,, Miranda-CasoLuengo AA,, Monzon VA,, Conway T,, Sivasankaran SK,, Hinton JC,, Hokamp K,, Cameron AD . The primary transcriptome, small RNAs, and regulation of antimicrobial resistance in Acinetobacter baumannii ATCC 17978. Nucleic Acids Res.[CrossRef]
9. Ilyas B,, Tsai CN,, Coombes BK . 2017. Evolution of Salmonella-host cell interactions through a dynamic bacterial genome. Front Cell Infect Microbiol 7 : 428.[CrossRef][PubMed]
10. Mekalanos JJ . 1992. Environmental signals controlling expression of virulence determinants in bacteria. J Bacteriol 174 : 1 7.[CrossRef][PubMed]
11. Silhavy TJ . 2000. Gene fusions. J Bacteriol 182 : 5935 5938.[CrossRef][PubMed]
12. DeRisi JL,, Iyer VR,, Brown PO . 1997. Exploring the metabolic and genetic control of gene expression on a genomic scale. Science 278 : 680 686.[CrossRef][PubMed]
13. Schena M,, Shalon D,, Davis RW,, Brown PO . 1995. Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270 : 467 470.[CrossRef][PubMed]
14. Nagalakshmi U,, Wang Z,, Waern K,, Shou C,, Raha D,, Gerstein M,, Snyder M . 2008. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320 : 1344 1349.[CrossRef][PubMed]
15. Colgan AM,, Cameron AD,, Kröger C,, Colgan AM,, Srikumar S,, Händler K,, Sivasankaran SK,, Hammarlöf DL,, Canals R,, Grissom JE,, Conway T,, Hokamp K,, Hinton JC . 2017. If it transcribes, we can sequence it: mining the complexities of host-pathogen-environment interactions using RNA-seq. Curr Opin Microbiol 36 : 37 46.[CrossRef][PubMed]
16. Wang Z,, Gerstein M,, Snyder M . 2009. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10 : 57 63.[CrossRef][PubMed]
17. Mäder U,, Nicolas P,, Richard H,, Bessières P,, Aymerich S . 2011. Comprehensive identification and quantification of microbial transcriptomes by genome-wide unbiased methods. Curr Opin Biotechnol 22 : 32 41.[CrossRef][PubMed]
18. Höfer K,, Jäschke A . 2018. Epitranscriptomics: RNA modifications in bacteria and archaea. Microbiol Spectr 6 : RWR-0015-2017.[CrossRef][PubMed]
19. Saliba AE,, C Santos S,, Vogel J . 2017. New RNA-seq approaches for the study of bacterial pathogens. Curr Opin Microbiol 35 : 78 87.[CrossRef][PubMed]
20. Conesa A,, Madrigal P,, Tarazona S,, Gomez-Cabrero D,, Cervera A,, McPherson A,, Szcześniak MW,, Gaffney DJ,, Elo LL,, Zhang X,, Mortazavi A . 2016. A survey of best practices for RNA-seq data analysis. Genome Biol 17 : 1 19.
21. Aikawa C,, Maruyama F,, Nakagawa I . 2010. The dawning era of comprehensive transcriptome analysis in cellular microbiology. Front Microbiol 1 : 118.[CrossRef][PubMed]
22. Creecy JP,, Conway T . 2015. Quantitative bacterial transcriptomics with RNA-seq. Curr Opin Microbiol 23 : 133 140.[CrossRef][PubMed]
23. Levin JZ,, Yassour M,, Adiconis X,, Nusbaum C,, Thompson DA,, Friedman N,, Gnirke A,, Regev A . 2010. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nat Methods 7 : 709 715.[CrossRef][PubMed]
24. The GTEx Consortium . 2013. The Genotype-Tissue Expression (GTEx) project. Nat Genet 45 : 580585.[CrossRef][PubMed]
25. Faria JP,, Overbeek R,, Xia F,, Rocha M,, Rocha I,, Henry CS . 2014. Genome-scale bacterial transcriptional regulatory networks: reconstruction and integrated analysis with metabolic models. Brief Bioinform 15 : 592 611.[CrossRef][PubMed]
26. Lucchini S,, Rowley G,, Goldberg MD,, Hurd D,, Harrison M,, Hinton JC . 2006. H-NS mediates the silencing of laterally acquired genes in bacteria. PLoS Pathog 2 : e81.[CrossRef][PubMed]
27. Smith C,, Stringer AM,, Mao C,, Palumbo MJ,, Wade JT . 2016. Mapping the regulatory network for Salmonella enterica serovar Typhimurium invasion. mBio 7 : e01024-16.[CrossRef][PubMed]
28. Tomljenovic-Berube AM,, Mulder DT,, Whiteside MD,, Brinkman FS,, Coombes BK . 2010. Identification of the regulatory logic controlling Salmonella pathoadaptation by the SsrA-SsrB two-component system. PLoS Genet 6 : e1000875.[CrossRef][PubMed]
29. Cloots L,, Marchal K . 2011. Network-based functional modeling of genomics, transcriptomics and metabolism in bacteria. Curr Opin Microbiol 14 : 599 607.[CrossRef][PubMed]
30. McDermott JE,, Yoon H,, Nakayasu ES,, Metz TO,, Hyduke DR,, Kidwai AS,, Palsson BO,, Adkins JN,, Heffron F . 2011. Technologies and approaches to elucidate and model the virulence program of Salmonella. Front Microbiol 2 : 121.[CrossRef][PubMed]
31. Yoon H,, McDermott JE,, Porwollik S,, McClelland M,, Heffron F . 2009. Coordinated regulation of virulence during systemic infection of Salmonella enterica serovar Typhimurium. PLoS Pathog 5 : e1000306.[CrossRef][PubMed]
32. Métris A,, Sudhakar P,, Fazekas D,, Demeter A,, Ari E,, Olbei M,, Branchu P,, Kingsley RA,, Baranyi J,, Korcsmáros T . 2017. SalmoNet, an integrated network of ten Salmonella enterica strains reveals common and distinct pathways to host adaptation. NPJ Syst Biol Appl 3 : 31.[CrossRef][PubMed]
33. Laczny CC,, Sternal T,, Plugaru V,, Gawron P,, Atashpendar A,, Margossian HH,, Coronado S,, der Maaten L,, Vlassis N,, Wilmes P . 2015. VizBin—an application for reference-independent visualization and human-augmented binning of metagenomic data. Microbiome 3 : 1 7.[CrossRef][PubMed]
34. Barquist L,, Vogel J . 2015. Accelerating discovery and functional analysis of small RNAs with new technologies. Annu Rev Genet 49 : 367 394.[CrossRef][PubMed]
35. Srikumar S,, Kröger C,, Hébrard M,, Colgan A,, Owen SV,, Sivasankaran SK,, Cameron AD,, Hokamp K,, Hinton JC . 2015. RNA-seq brings new insights to the intra-macrophage transcriptome of Salmonella Typhimurium. PLoS Pathog 11 : e1005262.[CrossRef][PubMed]
36. Kröger C,, Colgan A,, Srikumar S,, Händler K,, Sivasankaran SK,, Hammarlöf DL,, Canals R,, Grissom JE,, Conway T,, Hokamp K,, Hinton JC . 2013. An infection-relevant transcriptomic compendium for Salmonella enterica serovar Typhimurium. Cell Host Microbe 14 : 683 695.[CrossRef][PubMed]
37. Colgan AM,, Kröger C,, Diard M,, Hardt WD,, Puente JL,, Sivasankaran SK,, Hokamp K,, Hinton JC . 2016. The impact of 18 ancestral and horizontally-acquired regulatory proteins upon the transcriptome and sRNA landscape of Salmonella enterica serovar Typhimurium. PLoS Genet 12 : e1006258.[CrossRef][PubMed]
38. Havelaar AH,, Kirk MD,, Torgerson PR,, Gibb HJ,, Hald T,, Lake RJ,, Praet N,, Bellinger DC,, de Silva NR,, Gargouri N,, Speybroeck N,, Cawthorne A,, Mathers C,, Stein C,, Angulo FJ,, Devleesschauwer B, World Health Organization Foodborne Disease Burden Epidemiology Reference Group . 2015. World Health Organization global estimates and regional comparisons of the burden of foodborne disease in 2010. PLoS Med 12 : e1001923.[CrossRef][PubMed]
39. Hammarlöf DL,, Canals R,, Hinton JC . 2013. The FUN of identifying gene function in bacterial pathogens; insights from Salmonella functional genomics. Curr Opin Microbiol 16 : 643 651.[CrossRef][PubMed]
40. Altuvia S,, Weinstein-Fischer D,, Zhang A,, Postow L,, Storz G . 1997. A small, stable RNA induced by oxidative stress: role as a pleiotropic regulator and antimutator. Cell 90 : 43 53.[CrossRef]
41. Chareyre S,, Mandin P . 2018. Bacterial iron homeostasis regulation by sRNAs. Microbiol Spectr 6 : RWR-0010-2017.[CrossRef][PubMed]
42. Kim JN . 2016. Roles of two RyhB paralogs in the physiology of Salmonella enterica. Microbiol Res 186-187 : 146 152.[CrossRef][PubMed]
43. Calderón IL,, Morales EH,, Collao B,, Calderón PF,, Chahuán CA,, Acuña LG,, Gil F,, Saavedra CP . 2014. Role of Salmonella Typhimurium small RNAs RyhB-1 and RyhB-2 in the oxidative stress response. Res Microbiol 165 : 30 40.[CrossRef][PubMed]
44. Padalon-Brauch G,, Hershberg R,, Elgrably-Weiss M,, Baruch K,, Rosenshine I,, Margalit H,, Altuvia S . 2008. Small RNAs encoded within genetic islands of Salmonella Typhimurium show host-induced expression and role in virulence. Nucleic Acids Res 36 : 1913 1927.[CrossRef][PubMed]
45. Massé E,, Gottesman S . 2002. A small RNA regulates the expression of genes involved in iron metabolism in Escherichia coli. Proc Natl Acad Sci U S A 99 : 4620 4625.[CrossRef][PubMed]
46. Coornaert A,, Lu A,, Mandin P,, Springer M,, Gottesman S,, Guillier M . 2010. MicA sRNA links the PhoP regulon to cell envelope stress. Mol Microbiol 76 : 467 479.[CrossRef][PubMed]
47. Guo MS,, Updegrove TB,, Gogol EB,, Shabalina SA,, Gross CA,, Storz G . 2014. MicL, a new σ E-dependent sRNA, combats envelope stress by repressing synthesis of Lpp, the major outer membrane lipoprotein. Genes Dev 28 : 1620 1634.[CrossRef][PubMed]
48. Gogol EB,, Rhodius VA,, Papenfort K,, Vogel J,, Gross CA . 2011. Small RNAs endow a transcriptional activator with essential repressor functions for single-tier control of a global stress regulon. Proc Natl Acad Sci U S A 108 : 12875 12880.[CrossRef][PubMed]
49. Waters LS,, Sandoval M,, Storz G . 2011. The Escherichia coli MntR miniregulon includes genes encoding a small protein and an efflux pump required for manganese homeostasis. J Bacteriol 193 : 5887 5897.[CrossRef][PubMed]
50. Silva IJ,, Ortega ÁD,, Viegas SC,, García-Del Portillo F,, Arraiano CM . 2013. An RpoS-dependent sRNA regulates the expression of a chaperone involved in protein folding. RNA 19 : 1253 1265.[CrossRef][PubMed]
51. Chao Y,, Papenfort K,, Reinhardt R,, Sharma CM,, Vogel J . 2012. An atlas of Hfq-bound transcripts reveals 3′ UTRs as a genomic reservoir of regulatory small RNAs. EMBO J 31 : 4005 4019.[CrossRef][PubMed]
52. Skinner ME,, Uzilov AV,, Stein LD,, Mungall CJ,, Holmes IH . 2009. JBrowse: a next-generation genome browser. Genome Res 19 : 1630 1638.[CrossRef][PubMed]
53. Westesson O,, Skinner M,, Holmes I . 2013. Visualizing next-generation sequencing data with JBrowse. Brief Bioinform 14 : 172 177.[CrossRef][PubMed]
54. Kröger C,, Dillon SC,, Cameron AD,, Papenfort K,, Sivasankaran SK,, Hokamp K,, Chao Y,, Sittka A,, Hébrard M,, Händler K,, Colgan A,, Leekitcharoenphon P,, Langridge GC,, Lohan AJ,, Loftus B,, Lucchini S,, Ussery DW,, Dorman CJ,, Thomson NR,, Vogel J,, Hinton JC . 2012. The transcriptional landscape and small RNAs of Salmonella enterica serovar Typhimurium. Proc Natl Acad Sci U S A 109 : E1277 E1286.[CrossRef][PubMed]
55. Hammarlöf DL,, Kröger C,, Owen SV,, Canals R,, Lacharme-Lora L,, Wenner N,, Schager AE,, Wells TJ,, Henderson IR,, Wigley P,, Hokamp K,, Feasey NA,, Gordon MA,, Hinton JC . 2018. Role of a single noncoding nucleotide in the evolution of an epidemic African clade of Salmonella. Proc Natl Acad Sci U S A 115 : E2614 E2623.[CrossRef][PubMed]

This is a required field
Please enter a valid email address
Please check the format of the address you have entered.
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error