Integrating genomic, transcriptomic, and phenotypic information to explore drug resistance in Mycobacterium tuberculosis sub-lineage 4.2.2.2.

Tesfaye Gebreyohannis Hailemariam, Abaysew Ayele, Tesfaye Gelanew, Abay Atnafu, Michael Brennan, Melaku Tilahun, Dawit Hailu Alemayehu, Zemedkun Abebe Debella, Yared Merid, Workineh Shibeshi, Abraham Aseffa, Kidist Bobosha, Yonas Hirutu, Simon J Waddell, Ephrem Engidawork
Author Information
  1. Tesfaye Gebreyohannis Hailemariam: Department of Pharmacology and Clinical Pharmacy, School of Pharmacy, College of Health Science, Addis Ababa University, P.O.Box 9086, Addis Ababa, Ethiopia.
  2. Abaysew Ayele: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  3. Tesfaye Gelanew: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  4. Abay Atnafu: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  5. Michael Brennan: Department of Global Health and Infection, Brighton and Sussex Medical School, University of Sussex, BN1 9PX, Brighton, United Kingdom.
  6. Melaku Tilahun: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  7. Dawit Hailu Alemayehu: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  8. Zemedkun Abebe Debella: Addis Ababa Institute of Technology, Addis Ababa Univeristy, P.O. Box 1000, Addis Ababa, Ethiopia.
  9. Yared Merid: Hawassa University College of Medicine and Health Sciences, P.O.Box 1560, Hawassa, Ethiopia.
  10. Workineh Shibeshi: Department of Pharmacology and Clinical Pharmacy, School of Pharmacy, College of Health Science, Addis Ababa University, P.O.Box 9086, Addis Ababa, Ethiopia.
  11. Abraham Aseffa: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  12. Kidist Bobosha: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia. ORCID
  13. Yonas Hirutu: Armauer Hansen Research Institute, P.O.Box 1005, Addis Ababa, Ethiopia.
  14. Simon J Waddell: Department of Global Health and Infection, Brighton and Sussex Medical School, University of Sussex, BN1 9PX, Brighton, United Kingdom.
  15. Ephrem Engidawork: Department of Pharmacology and Clinical Pharmacy, School of Pharmacy, College of Health Science, Addis Ababa University, P.O.Box 9086, Addis Ababa, Ethiopia. ORCID

Abstract

AIMS: Mycobacterium tuberculosis (Mtb) remains a major global health challenge, particularly due to increasing drug resistance. Beyond the well-characterized mutations, the mechanisms involved in driving resistance appear to be more complex. This study investigated the differential gene expression of Ethiopian drug-resistant Mtb sub-lineage 4.2.2.2 clinical isolates through an integrated approach combining phenotypic, transcriptomic, and genomic analyses.
METHOD AND RESULTS: RNA sequencing was performed by isolating RNA from six Mtb strains (three drug-sensitive and three drug-resistant) during mid-logarithmic phase growth. Drug resistance was assessed through whole-genome analysis and phenotypic testing using the BACTEC Mycobacteria growth indicator tube (MGIT)™ 960 system. RNA profiling revealed significantly reduced expression of six genes: Rv0096, Rv2780, Rv3136, Rv3136A, Rv3137, and Rv3230c in drug-resistant isolates. These genes are not associated with known drug targets nor resistance mechanisms. Additionally, a discrepancy was noted between phenotypic resistance profiles and whole genome-based predictions, with the latter suggesting broader resistance. For instance, the missense mutation in rpoB p.Ser450Leu and katG p.Ser315Thr were identified with no change in phenotypic drug sensitivity to rifampicin and isoniazid, respectively.
CONCLUSION: Identification of these differentially expressed genes and their networks could be useful in unraveling the complexities of Mtb drug resistance and in understanding the impact that drug resistance conferring mutations have on the physiology of drug-resistant Mtb.

Keywords

References

  1. Bioinformatics. 2014 Apr 1;30(7):923-30 [PMID: 24227677]
  2. Nat Biotechnol. 2019 Aug;37(8):907-915 [PMID: 31375807]
  3. Curr Protoc Bioinformatics. 2020 Mar;69(1):e96 [PMID: 32162851]
  4. BMC Bioinformatics. 2013 Jan 31;14:33 [PMID: 23363224]
  5. Cells. 2020 Mar 03;9(3): [PMID: 32138343]
  6. Commun Biol. 2021 Mar 25;4(1):410 [PMID: 33767335]
  7. Biomolecules. 2020 Jun 08;10(6): [PMID: 32521604]
  8. Sci Rep. 2019 Mar 26;9(1):5204 [PMID: 30914757]
  9. Nat Commun. 2021 Dec 15;12(1):7312 [PMID: 34911948]
  10. Int J Mol Sci. 2022 May 05;23(9): [PMID: 35563545]
  11. Nat Genet. 2016 May;48(5):544-51 [PMID: 27064254]
  12. Tuberculosis (Edinb). 2019 Sep;118:101858 [PMID: 31430694]
  13. Methods Mol Biol. 2018;1736:117-128 [PMID: 29322464]
  14. Int J Immunopathol Pharmacol. 2016 Sep;29(3):443-9 [PMID: 27069023]
  15. Microbiol Spectr. 2023 Dec 12;11(6):e0468522 [PMID: 37882511]
  16. J Vis Exp. 2021 Sep 18;(175): [PMID: 34605806]
  17. PLoS One. 2023 Sep 8;18(9):e0285063 [PMID: 37682820]
  18. Int J Infect Dis. 2025 Jan;150:107325 [PMID: 39631498]
  19. Front Microbiol. 2024 Mar 04;15:1359188 [PMID: 38516013]
  20. Emerg Microbes Infect. 2020 Dec;9(1):2632-2641 [PMID: 33205698]
  21. Infect Drug Resist. 2023 Oct 26;16:6859-6870 [PMID: 37908783]
  22. PLoS Pathog. 2022 Jul 13;18(7):e1010705 [PMID: 35830479]
  23. Commun Biol. 2023 Feb 7;6(1):156 [PMID: 36750726]
  24. J Bacteriol. 2006 Dec;188(24):8460-8 [PMID: 17028284]
  25. Tuberculosis (Edinb). 2013 Jan;93(1):96-101 [PMID: 23182912]
  26. Sci Rep. 2019 Oct 25;9(1):15354 [PMID: 31653940]
  27. Antimicrob Agents Chemother. 2019 Aug 23;63(9): [PMID: 31209015]
  28. PLoS One. 2022 Dec 30;17(12):e0279644 [PMID: 36584023]
  29. Data Brief. 2020 Oct 17;33:106416 [PMID: 33102665]
  30. Front Cell Infect Microbiol. 2022 Sep 02;12:990312 [PMID: 36118045]
  31. J Biol Chem. 2018 Jun 29;293(26):10102-10118 [PMID: 29752410]
  32. Proc Natl Acad Sci U S A. 2002 Mar 19;99(6):3684-9 [PMID: 11891304]
  33. Tuberculosis (Edinb). 2009 Nov;89(6):448-52 [PMID: 19800845]
  34. J Bacteriol. 2004 Oct;186(19):6605-16 [PMID: 15375142]
  35. Emerg Infect Dis. 2024 Oct;30(3):560-563 [PMID: 38407162]
  36. Sci Rep. 2019 Jun 26;9(1):9305 [PMID: 31243306]
  37. Mol Cell Proteomics. 2018 Sep;17(9):1685-1701 [PMID: 29844232]
  38. Int J Pept Protein Res. 1980 Mar;15(3):211-24 [PMID: 7380605]
  39. PLoS Med. 2008 Apr 1;5(4):e75 [PMID: 18384229]
  40. Curr Issues Mol Biol. 2006 Jul;8(2):97-111 [PMID: 16878362]

Grants

  1. /Wellcome Trust
  2. #H3A-18-003/NIH HHS

MeSH Term

Mycobacterium tuberculosis
Antitubercular Agents
Phenotype
Transcriptome
Microbial Sensitivity Tests
Humans
Tuberculosis, Multidrug-Resistant
Genome, Bacterial
Bacterial Proteins
Genomics
Drug Resistance, Bacterial
Drug Resistance, Multiple, Bacterial
Rifampin
Gene Expression Profiling
Mutation
Ethiopia

Chemicals

Antitubercular Agents
Bacterial Proteins
Rifampin

Word Cloud

Created with Highcharts 10.0.0resistancedrug2Mtbphenotypicdrug-resistantMycobacteriumtuberculosisRNAmutationsmechanismsexpressionsub-lineage4isolatestranscriptomicgenomicsixthreegrowthgenespAIMS:remainsmajorglobalhealthchallengeparticularlydueincreasingBeyondwell-characterizedinvolveddrivingappearcomplexstudyinvestigateddifferentialgeneEthiopianclinicalintegratedapproachcombininganalysesMETHODANDRESULTS:sequencingperformedisolatingstrainsdrug-sensitivemid-logarithmicphaseDrugassessedwhole-genomeanalysistestingusingBACTECMycobacteriaindicatortubeMGIT960systemprofilingrevealedsignificantlyreducedgenes:Rv0096Rv2780Rv3136Rv3136ARv3137Rv3230cassociatedknowntargetsAdditionallydiscrepancynotedprofileswholegenome-basedpredictionslattersuggestingbroaderinstancemissensemutationrpoBSer450LeukatGSer315ThridentifiedchangesensitivityrifampicinisoniazidrespectivelyCONCLUSION:IdentificationdifferentiallyexpressednetworksusefulunravelingcomplexitiesunderstandingimpactconferringphysiologyIntegratinginformationexploreEthiopiaRNAseqdiscordancedrug-resistancelineage

Similar Articles

Cited By

No available data.