Literature DB >> 33613483

Evolution of Drug-Resistant Mycobacterium tuberculosis Strains and Their Adaptation to the Human Lung Environment.

Anna Allué-Guardia1, Juan I García1, Jordi B Torrelles1.   

Abstract

In the last two decades, multi (MDR), extensively (XDR), extremely (XXDR) and total (TDR) drug-resistant Mycobacterium tuberculosis (M.tb) strains have emerged as a threat to public health worldwide, stressing the need to develop new tuberculosis (TB) prevention and treatment strategies. It is estimated that in the next 35 years, drug-resistant TB will kill around 75 million people and cost the global economy $16.7 trillion. Indeed, the COVID-19 pandemic alone may contribute with the development of 6.3 million new TB cases due to lack of resources and enforced confinement in TB endemic areas. Evolution of drug-resistant M.tb depends on numerous factors, such as bacterial fitness, strain's genetic background and its capacity to adapt to the surrounding environment, as well as host-specific and environmental factors. Whole-genome transcriptomics and genome-wide association studies in recent years have shed some insights into the complexity of M.tb drug resistance and have provided a better understanding of its underlying molecular mechanisms. In this review, we will discuss M.tb phenotypic and genotypic changes driving resistance, including changes in cell envelope components, as well as recently described intrinsic and extrinsic factors promoting resistance emergence and transmission. We will further explore how drug-resistant M.tb adapts differently than drug-susceptible strains to the lung environment at the cellular level, modulating M.tb-host interactions and disease outcome, and novel next generation sequencing (NGS) strategies to study drug-resistant TB.
Copyright © 2021 Allué-Guardia, García and Torrelles.

Entities:  

Keywords:  Mycobacterium tuberculosis; bacterial–host interactions; drug resistance; evolution; next generation sequencing

Year:  2021        PMID: 33613483      PMCID: PMC7889510          DOI: 10.3389/fmicb.2021.612675

Source DB:  PubMed          Journal:  Front Microbiol        ISSN: 1664-302X            Impact factor:   5.640


  20 in total

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9.  Mycobacterium tuberculosis Cell Wall Permeability Model Generation Using Chemoinformatics and Machine Learning Approaches.

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10.  Host- and Age-Dependent Transcriptional Changes in Mycobacterium tuberculosis Cell Envelope Biosynthesis Genes after Exposure to Human Alveolar Lining Fluid.

Authors:  Anna Allué-Guardia; Andreu Garcia-Vilanova; Angélica M Olmo-Fontánez; Jay Peters; Diego J Maselli; Yufeng Wang; Joanne Turner; Larry S Schlesinger; Jordi B Torrelles
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