Comparative genomic analysis reveals differential genomic characteristics and featured genes between rapid- and slow-growing .

Menglu Zhang, Peihan Wang, Cuidan Li, Ofir Segev, Jie Wang, Xiaotong Wang, Liya Yue, Xiaoyuan Jiang, Yongjie Sheng, Asaf Levy, Chunlai Jiang, Fei Chen
Author Information
  1. Menglu Zhang: National Engineering Laboratory for AIDS Vaccine, School of Life Science, Jilin University, Changchun, China.
  2. Peihan Wang: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
  3. Cuidan Li: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
  4. Ofir Segev: Department of Plant Pathology and Microbiology, The Institute of Environmental Science, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot, Israel.
  5. Jie Wang: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
  6. Xiaotong Wang: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
  7. Liya Yue: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
  8. Xiaoyuan Jiang: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.
  9. Yongjie Sheng: Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun, China.
  10. Asaf Levy: Department of Plant Pathology and Microbiology, The Institute of Environmental Science, The Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem, Rehovot, Israel.
  11. Chunlai Jiang: National Engineering Laboratory for AIDS Vaccine, School of Life Science, Jilin University, Changchun, China.
  12. Fei Chen: CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing, China.

Abstract

Introduction: (NTM) is a major category of environmental bacteria in nature that can be divided into rapidly growing (RGM) and slowly growing (SGM) based on their distinct growth rates. To explore differential molecular mechanisms between RGM and SGM is crucial to understand their survival state, environmental/host adaptation and pathogenicity. Comparative genomic analysis provides a powerful tool for deeply investigating differential molecular mechanisms between them. However, large-scale comparative genomic analysis between RGM and SGM is still uncovered.
Methods: In this study, we screened 335 high-quality, non-redundant NTM genome sequences covering 187 species from 3,478 online NTM genomes, and then performed a comprehensive comparative genomic analysis to identify differential genomic characteristics and featured genes/protein domains between RGM and SGM.
Results: Our findings reveal that RGM has a larger genome size, more genes, lower GC content, and more featured genes/protein domains in metabolism of some main substances (e.g. carbohydrates, amino acids, nucleotides, ions, and coenzymes), energy metabolism, signal transduction, replication, transcription, and translation processes, which are essential for its rapid growth requirements. On the other hand, SGM has a smaller genome size, fewer genes, higher GC content, and more featured genes/protein domains in lipid and secondary metabolite metabolisms and cellular defense mechanisms, which help enhance its genome stability and environmental adaptability. Additionally, orthogroup analysis revealed the important roles of bacterial division and bacteriophage associated genes in RGM and secretion system related genes for better environmental adaptation in SGM. Notably, PCoA analysis of the top 20 genes/protein domains showed precision classification between RGM and SGM, indicating the credibility of our screening/classification strategies.
Discussion: Overall, our findings shed light on differential underlying molecular mechanisms in survival state, adaptation and pathogenicity between RGM and SGM, show the potential for our comparative genomic pipeline to investigate differential genes/protein domains at whole genomic level across different bacterial species on a large scale, and provide an important reference and improved understanding of NTM.

Keywords

References

  1. Tuberculosis (Edinb). 2019 Mar;115:96-107 [PMID: 30948183]
  2. Microorganisms. 2020 Sep 09;8(9): [PMID: 32916931]
  3. Biol Direct. 2012 Jan 10;7:2 [PMID: 22230424]
  4. Genome Biol. 2016 Nov 25;17(1):238 [PMID: 27887642]
  5. BMC Bioinformatics. 2013 Nov 26;14:341 [PMID: 24274019]
  6. Adv Biol Regul. 2012 Jan;52(1):229-38 [PMID: 22100882]
  7. J Microbiol Biotechnol. 2015 Feb;25(2):255-67 [PMID: 25248984]
  8. Sci Rep. 2017 Mar 27;7:45258 [PMID: 28345639]
  9. Infect Genet Evol. 2017 Dec;56:19-25 [PMID: 29030295]
  10. Nat Commun. 2010;1:147 [PMID: 21266997]
  11. Int J Syst Evol Microbiol. 2008 Jun;58(Pt 6):1432-41 [PMID: 18523191]
  12. Mol Biosyst. 2015 Apr;11(4):1184-93 [PMID: 25712329]
  13. Emerg Microbes Infect. 2019;8(1):1043-1053 [PMID: 31287781]
  14. Proc Natl Acad Sci U S A. 2016 Dec 6;113(49):E7947-E7956 [PMID: 27872278]
  15. Front Microbiol. 2020 Jan 21;10:3019 [PMID: 32038518]
  16. Nat Commun. 2022 Oct 23;13(1):6315 [PMID: 36274063]
  17. Infect Genet Evol. 2012 Jun;12(4):827-31 [PMID: 21684354]
  18. Front Microbiol. 2018 Feb 13;9:67 [PMID: 29497402]
  19. Genomics. 2010 Jan;95(1):7-15 [PMID: 19747541]
  20. Syst Biol. 2010 Jan;59(1):9-26 [PMID: 20525617]
  21. J Fish Dis. 2023 Jul;46(7):779-790 [PMID: 36989191]
  22. Annu Rev Genet. 2004;38:771-92 [PMID: 15568993]
  23. Int J Mycobacteriol. 2020 Apr-Jun;9(2):156-166 [PMID: 32474537]
  24. Int J Syst Evol Microbiol. 2005 Jan;55(Pt 1):293-302 [PMID: 15653890]
  25. Structure. 2003 Apr;11(4):375-85 [PMID: 12679016]
  26. Genome Res. 2007 Feb;17(2):192-200 [PMID: 17210928]
  27. J Biol Chem. 2004 Jul 23;279(30):31717-26 [PMID: 15145952]
  28. J Immunol Res. 2019 Apr 14;2019:1356540 [PMID: 31111075]
  29. J Biol Chem. 1993 Sep 15;268(26):19358-63 [PMID: 8366082]
  30. Microb Biotechnol. 2021 Jul;14(4):1539-1549 [PMID: 34019733]
  31. PLoS One. 2017 Mar 14;12(3):e0172831 [PMID: 28291784]
  32. Nat Rev Microbiol. 2020 Jul;18(7):392-407 [PMID: 32086501]
  33. Nat Rev Microbiol. 2011 Jun;9(6):467-77 [PMID: 21552286]
  34. Appl Environ Microbiol. 1992 Nov;58(11):3455-65 [PMID: 1482172]
  35. Infect Genet Evol. 2019 Aug;72:159-168 [PMID: 30654178]
  36. Diagn Microbiol Infect Dis. 2013 Jan;75(1):73-6 [PMID: 23114094]
  37. Genome Biol. 2015 Aug 06;16:157 [PMID: 26243257]
  38. Bioinformatics. 2014 Jul 15;30(14):2068-9 [PMID: 24642063]
  39. Microbiol Spectr. 2014 Oct;2(5): [PMID: 25429354]
  40. Mol Biol Evol. 2009 Jul;26(7):1641-50 [PMID: 19377059]
  41. Nucleic Acids Res. 2004 Oct 05;32(17):5260-79 [PMID: 15466593]
  42. Nat Genet. 2018 Jan;50(1):138-150 [PMID: 29255260]
  43. Sci Rep. 2018 Jun 18;8(1):9309 [PMID: 29915369]
  44. Proc Natl Acad Sci U S A. 2014 Sep 30;111(39):E4096-102 [PMID: 25225383]

Word Cloud

Created with Highcharts 10.0.0RGMSGMgenomicdifferentialanalysisNTMgenes/proteindomainsgenesgrowingmechanismscomparativegenomefeaturedenvironmentalgrowthmolecularadaptationmycobacteriarapidlyslowlysurvivalstatepathogenicityComparativespeciescharacteristicsfindingssizeGCcontentmetabolismimportantbacterialIntroduction:majorcategorybacterianaturecandividedbaseddistinctratesexplorecrucialunderstandenvironmental/hostprovidespowerfultooldeeplyinvestigatingHoweverlarge-scalestilluncoveredMethods:studyscreened335high-qualitynon-redundantsequencescovering1873478onlinegenomesperformedcomprehensiveidentifyResults:reveallargerlowermainsubstancesegcarbohydratesaminoacidsnucleotidesionscoenzymesenergysignaltransductionreplicationtranscriptiontranslationprocessesessentialrapidrequirementshandsmallerfewerhigherlipidsecondarymetabolitemetabolismscellulardefensehelpenhancestabilityadaptabilityAdditionallyorthogrouprevealedrolesdivisionbacteriophageassociatedsecretionsystemrelatedbetterNotablyPCoAtop20showedprecisionclassificationindicatingcredibilityscreening/classificationstrategiesDiscussion:Overallshedlightunderlyingshowpotentialpipelineinvestigatewholelevelacrossdifferentlargescaleprovidereferenceimprovedunderstandingrevealsrapid-slow-growingadaptiveevolutiongenomicsratenon-tuberculoustoxin-antitoxin

Similar Articles

Cited By

No available data.