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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Infectious Disorders - Drug Targets</journal-id><journal-title-group><journal-title xml:lang="en">Infectious Disorders - Drug Targets</journal-title><trans-title-group xml:lang="ru"><trans-title>Infectious Disorders - Drug Targets</trans-title></trans-title-group></journal-title-group><issn publication-format="print">1871-5265</issn><issn publication-format="electronic">2212-3989</issn><publisher><publisher-name xml:lang="en">Bentham Science</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">645767</article-id><article-id pub-id-type="doi">10.2174/0118715265274164240117104534</article-id><article-categories><subj-group subj-group-type="toc-heading"><subject>Medicine</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Identification of Genes Encoded Toxin-Antitoxin System in Mycobacterium Tuberculosis Strains from Clinical Sample</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Sundaram</surname><given-names>Karthikeyan</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><name><surname>Kagithakara Vajravelu</surname><given-names>Leela</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><name><surname>Velayutham</surname><given-names>Ravichandiran</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff3"/></contrib><contrib contrib-type="author"><name><surname>Mohan</surname><given-names>Utpal</given-names></name><email>info@benthamscience.net</email><xref ref-type="aff" rid="aff4"/></contrib></contrib-group><aff id="aff1"><institution>Department of Microbiology,, SRM Medical College Hospital and Research Centre</institution></aff><aff id="aff2"><institution>Department of Microbiology, SRM Medical College Hospital and Research Centre</institution></aff><aff id="aff3"><institution>Department of Natural Products, National Institute of Pharmaceutical Education and Research</institution></aff><aff id="aff4"><institution>Department of Medicinal Chemistry, National Institute of Pharmaceutical Education and Research</institution></aff><pub-date date-type="pub" iso-8601-date="2024-08-01" publication-format="electronic"><day>01</day><month>08</month><year>2024</year></pub-date><volume>24</volume><issue>8</issue><issue-title xml:lang="ru"/><history><date date-type="received" iso-8601-date="2025-01-11"><day>11</day><month>01</month><year>2025</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Bentham Science Publishers</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Bentham Science Publishers</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/></permissions><self-uri xlink:href="https://journals.eco-vector.com/1871-5265/article/view/645767">https://journals.eco-vector.com/1871-5265/article/view/645767</self-uri><abstract xml:lang="en"><p id="idm46466589636496">Background:The toxin-antitoxin system is a genetic element that is highly present in Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis. The toxin-antitoxin sys-tem comprises toxin protein and antitoxin protein or non-encoded RNA interacting with each other and inhibiting toxin activity. M. Tuberculosis has more classes of TA loci than non-tubercle bacilli and other microbes, including VapBC, HigBA, MazEF, ParDE, RelBE, MbcTA, PemIK, DarTG, MenTA, one tripartite type II TAC chaperone system, and hypothetical proteins.</p><p id="idm46466589640496">Aims:The study aims to demonstrate the genes encoded toxin-antitoxin system in mycobacterium tuberculosis strains from clinical samples.</p><p id="idm46466589644464">Materials and Methods:The pulmonary and extra-pulmonary tuberculosis clinical samples were collected, and smear microscopy (Ziehl-Neelsen staining) was performed for the detection of high bacilli (3+) count, followed by nucleic acid amplification assay. Bacterial culture and growth assay, genomic DNA extraction, and polymerase chain reaction were also carried out.</p><p id="idm46466589649520">Results:The positive PTB and EPTB samples were determined by 3+ in microscopy smear [20], and the total count of tubercle bacilli determined by NAAT assay was 8.0×1005 in sputum and 1.3×1004 CFU/ml in tissue abscess. Moreover, the genomic DNA was extracted from culture, and the amplification of Rv1044 and Rv1045 genes in 624 and 412 base pairs (between 600-700 and 400-500 in ladder), respectively, in the H37Rv and clinical samples was observed.</p><p id="idm46466589658896">Conclusion:It has been found that Rv1044 and Rv1045 are hypothetical proteins with 624 and 882 base pairs belonging to the AbiEi/AbiEii family of toxin-antitoxin loci. Moreover, the signifi-cant identification of TA-encoded loci genes may allow for the investigation of multidrug-resistant and extensively drug-resistant tuberculosis.</p></abstract><kwd-group xml:lang="en"><kwd>Tuberculosis</kwd><kwd>toxin-antitoxin system</kwd><kwd>toxin</kwd><kwd>antitoxin</kwd><kwd>pathogenesis</kwd><kwd>Mycobacterium tuberculosis</kwd></kwd-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Tandon H, Sharma A, Wadhwa S, et al. Bioinformatic and mutational studies of related toxinantitoxin pairs in Mycobacterium tuberculosis predict and identify key functional residues. J Biol Chem 2019; 294(23): 9048-63. doi: 10.1074/jbc.RA118.006814 PMID: 31018964</mixed-citation></ref><ref id="B2"><label>2.</label><mixed-citation>Global tuberculosis report. Who int 2023. 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