Conserved and specific features of Streptococcus pyogenes and Streptococcus agalactiae transcriptional landscapes.
5′ UTRs
Antisense transcription
Operons
Promoters
Regulatory RNAs
Regulatory network evolution
Journal
BMC genomics
ISSN: 1471-2164
Titre abrégé: BMC Genomics
Pays: England
ID NLM: 100965258
Informations de publication
Date de publication:
22 Mar 2019
22 Mar 2019
Historique:
received:
12
11
2018
accepted:
14
03
2019
entrez:
24
3
2019
pubmed:
25
3
2019
medline:
10
7
2019
Statut:
epublish
Résumé
The human pathogen Streptococcus pyogenes, or group A Streptococcus, is responsible for mild infections to life-threatening diseases. To facilitate the characterization of regulatory networks involved in the adaptation of this pathogen to its different environments and their evolution, we have determined the primary transcriptome of a serotype M1 S. pyogenes strain at single-nucleotide resolution and compared it with that of Streptococcus agalactiae, also from the pyogenic group of streptococci. By using a combination of differential RNA-sequencing and oriented RNA-sequencing we have identified 892 transcription start sites (TSS) and 885 promoters in the S. pyogenes M1 strain S119. 8.6% of S. pyogenes mRNAs were leaderless, among which 81% were also classified as leaderless in S. agalactiae. 26% of S. pyogenes transcript 5' untranslated regions (UTRs) were longer than 60 nt. Conservation of long 5' UTRs with S. agalactiae allowed us to predict new potential regulatory sequences. In addition, based on the mapping of 643 transcript ends in the S. pyogenes strain S119, we constructed an operon map of 401 monocistrons and 349 operons covering 81.5% of the genome. One hundred fifty-six operons and 254 monocistrons retained the same organization, despite multiple genomic reorganizations between S. pyogenes and S. agalactiae. Genomic reorganization was found to more often go along with variable promoter sequences and 5' UTR lengths. Finally, we identified 117 putative regulatory RNAs, among which nine were regulated in response to magnesium concentration. Our data provide insights into transcriptome evolution in pyogenic streptococci and will facilitate the analysis of genetic polymorphisms identified by comparative genomics in S. pyogenes.
Sections du résumé
BACKGROUND
BACKGROUND
The human pathogen Streptococcus pyogenes, or group A Streptococcus, is responsible for mild infections to life-threatening diseases. To facilitate the characterization of regulatory networks involved in the adaptation of this pathogen to its different environments and their evolution, we have determined the primary transcriptome of a serotype M1 S. pyogenes strain at single-nucleotide resolution and compared it with that of Streptococcus agalactiae, also from the pyogenic group of streptococci.
RESULTS
RESULTS
By using a combination of differential RNA-sequencing and oriented RNA-sequencing we have identified 892 transcription start sites (TSS) and 885 promoters in the S. pyogenes M1 strain S119. 8.6% of S. pyogenes mRNAs were leaderless, among which 81% were also classified as leaderless in S. agalactiae. 26% of S. pyogenes transcript 5' untranslated regions (UTRs) were longer than 60 nt. Conservation of long 5' UTRs with S. agalactiae allowed us to predict new potential regulatory sequences. In addition, based on the mapping of 643 transcript ends in the S. pyogenes strain S119, we constructed an operon map of 401 monocistrons and 349 operons covering 81.5% of the genome. One hundred fifty-six operons and 254 monocistrons retained the same organization, despite multiple genomic reorganizations between S. pyogenes and S. agalactiae. Genomic reorganization was found to more often go along with variable promoter sequences and 5' UTR lengths. Finally, we identified 117 putative regulatory RNAs, among which nine were regulated in response to magnesium concentration.
CONCLUSIONS
CONCLUSIONS
Our data provide insights into transcriptome evolution in pyogenic streptococci and will facilitate the analysis of genetic polymorphisms identified by comparative genomics in S. pyogenes.
Identifiants
pubmed: 30902048
doi: 10.1186/s12864-019-5613-5
pii: 10.1186/s12864-019-5613-5
pmc: PMC6431027
doi:
Substances chimiques
5' Untranslated Regions
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
236Subventions
Organisme : Labex Integrative Biology of Emerging Infectious Diseases
ID : na
Organisme : High Council for Scientific and Technological Cooperation between France-Israel "Complexity in Biology" program
ID : na
Références
Mol Microbiol. 2001 Jan;39(2):392-406
pubmed: 11136460
FEBS Lett. 2001 Apr 27;495(3):167-71
pubmed: 11334885
EMBO J. 2001 Dec 3;20(23):6845-55
pubmed: 11726520
EMBO Rep. 2002 Apr;3(4):373-7
pubmed: 11897659
FEMS Microbiol Lett. 2002 Jun 4;211(2):161-7
pubmed: 12076807
J Bacteriol. 2003 Aug;185(15):4291-7
pubmed: 12867436
Nucleic Acids Res. 2004 Jun 23;32(11):3354-63
pubmed: 15215335
Genome Res. 2004 Jul;14(7):1394-403
pubmed: 15231754
Proc Natl Acad Sci U S A. 2004 Jul 27;101(30):10943-8
pubmed: 15252202
Mol Microbiol. 2004 Sep;53(5):1515-27
pubmed: 15387826
Mol Microbiol. 2004 Dec;54(5):1250-68
pubmed: 15554966
Nucleic Acids Res. 2005 Jul 26;33(13):4096-105
pubmed: 16049021
J Infect Dis. 2005 Sep 1;192(5):771-82
pubmed: 16088826
PLoS Comput Biol. 2005 Aug;1(3):e25
pubmed: 16110342
Euro Surveill. 2005 Sep;10(9):179-84
pubmed: 16280610
J Bacteriol. 2006 Mar;188(6):2038-47
pubmed: 16513733
Mol Microbiol. 2006 Oct;62(2):491-508
pubmed: 16965517
EMBO J. 2006 Nov 15;25(22):5414-22
pubmed: 17066081
Genome Biol. 2007;8(2):R22
pubmed: 17313685
Mol Microbiol. 2007 Aug;65(3):671-83
pubmed: 17608796
PLoS Comput Biol. 2007 Jul;3(7):e126
pubmed: 17616982
Mol Microbiol. 2007 Dec;66(6):1506-22
pubmed: 18005100
PLoS One. 2008 Sep 12;3(9):e3197
pubmed: 18787707
Genome Biol. 2009;10(3):R25
pubmed: 19261174
PLoS One. 2009 Nov 02;4(11):e7668
pubmed: 19888332
Bioinformatics. 2010 Jan 1;26(1):139-40
pubmed: 19910308
BMC Bioinformatics. 2010 Sep 29;11:491
pubmed: 20920260
RNA Biol. 2011 Jan-Feb;8(1):11-3
pubmed: 21282983
Proc Natl Acad Sci U S A. 2011 Mar 22;108(12):5039-44
pubmed: 21383167
Nature. 2011 Mar 31;471(7340):602-7
pubmed: 21455174
Cell. 2011 Sep 30;147(1):147-57
pubmed: 21944167
RNA. 2012 May;18(5):900-14
pubmed: 22450757
Brief Bioinform. 2013 Mar;14(2):178-92
pubmed: 22517427
BMC Genomics. 2012 Oct 13;13:550
pubmed: 23062031
Nucleic Acids Res. 2013 Jan;41(Database issue):D226-32
pubmed: 23125362
BMC Microbiol. 2013 Jan 28;13:18
pubmed: 23356868
RNA Biol. 2013 Jul;10(7):1180-4
pubmed: 23611891
Nucleic Acids Res. 2013 Jul;41(13):6514-30
pubmed: 23649834
PLoS One. 2013 Jun 06;8(6):e64021
pubmed: 23762235
Infect Immun. 2013 Nov;81(11):4128-38
pubmed: 23980109
RNA. 2013 Oct;19(10):1341-8
pubmed: 23980204
Infect Immun. 2014 May;82(5):1744-54
pubmed: 24516115
Genome Biol Evol. 2014 Apr;6(4):741-53
pubmed: 24625962
Proc Natl Acad Sci U S A. 2014 Apr 29;111(17):E1768-76
pubmed: 24733896
RNA. 2014 Jun;20(6):882-98
pubmed: 24759092
MBio. 2014 Jul 01;5(4):e01398-14
pubmed: 24987095
Methods Enzymol. 2014;549:3-27
pubmed: 25432742
BMC Genomics. 2015 May 30;16:419
pubmed: 26024923
J Clin Invest. 2015 Sep;125(9):3545-59
pubmed: 26258415
RNA Biol. 2016;13(2):177-95
pubmed: 26580233
Mol Biol Evol. 2016 Jul;33(7):1870-4
pubmed: 27004904
MBio. 2016 May 31;7(3):
pubmed: 27247229
Nucleic Acids Res. 2017 Mar 17;45(5):2329-2340
pubmed: 28082390
Mol Oral Microbiol. 2017 Oct;32(5):390-403
pubmed: 28371435
Proc Natl Acad Sci U S A. 2017 Oct 3;114(40):E8498-E8507
pubmed: 28923955
Sci Rep. 2017 Sep 25;7(1):12241
pubmed: 28947755
Nucleic Acids Res. 2018 Nov 2;46(19):9971-9989
pubmed: 30107613
RNA Biol. 2018;15(10):1336-1347
pubmed: 30290721
Nucleic Acids Res. 1987 Apr 10;15(7):3085-96
pubmed: 3104883
Nucleic Acids Res. 1983 Apr 25;11(8):2237-55
pubmed: 6344016
Nucleic Acids Res. 1995 Jul 11;23(13):2351-60
pubmed: 7630711
J Med Microbiol. 1993 Sep;39(3):165-78
pubmed: 8366514