The Epistatic Landscape of Antibiotic Resistance of Different Clades of Mycobacterium tuberculosis
| Autor: | Oleg N. Reva, Dillon Muzondiwa, Hleliwe Hlanze |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Microbiology (medical) epistasis Diagnostic methods Tuberculosis antibiotic resistance 030106 microbiology Computational biology Drug resistance RM1-950 Biochemistry Microbiology Genome Mycobacterium tuberculosis 03 medical and health sciences Antibiotic resistance evolution medicine Pharmacology (medical) General Pharmacology Toxicology and Pharmaceutics Clade drug-resistant mutation biology biology.organism_classification medicine.disease 030104 developmental biology Infectious Diseases Epistasis Therapeutics. Pharmacology |
| Zdroj: | Antibiotics Volume 10 Issue 7 Antibiotics, Vol 10, Iss 857, p 857 (2021) |
| ISSN: | 2079-6382 |
| DOI: | 10.3390/antibiotics10070857 |
| Popis: | Drug resistance (DR) remains a global challenge in tuberculosis (TB) control. In order to develop molecular-based diagnostic methods to replace the traditional culture-based diagnostics, there is a need for a thorough understanding of the processes that govern TB drug resistance. The use of whole-genome sequencing coupled with statistical and computational methods has shown great potential in unraveling the complexity of the evolution of DR-TB. In this study, we took an innovative approach that sought to determine nonrandom associations between polymorphic sites in Mycobacterium tuberculosis (Mtb) genomes. Attributable risk statistics were applied to identify the epistatic determinants of DR in different clades of Mtb and the possible evolutionary pathways of DR development. It was found that different lineages of Mtb exploited different evolutionary trajectories towards multidrug resistance and compensatory evolution to reduce the DR-associated fitness cost. Epistasis of DR acquisition is a new area of research that will aid in the better understanding of evolutionary biological processes and allow predicting upcoming multidrug-resistant pathogens before a new outbreak strikes humanity. |
| Databáze: | OpenAIRE |
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