Literature DB >> 29116638

Evolution of Phenotypic and Molecular Drug Susceptibility Testing.

Daniela M Cirillo1, Paolo Miotto2, Enrico Tortoli2.   

Abstract

Drug Resistant Tuberculosis (DRTB) is an emerging problem world-wide. In order to control the disease and decrease the number of cases overtime a prompt diagnosis followed by an appropriate treatment should be provided to patients. Phenotypic DST based on liquid automated culture has greatly reduced the time needed to generate reliable data but has the drawback to be expensive and prone to contamination in the absence of appropriate infrastructures. In the past 10 years molecular biology tools have been developed. Those tools target the main mutations responsible for DRTB and are now globally accessible in term of cost and infrastructures needed for the implementation. The dissemination of the Xpert MTB/rif has radically increased the capacity to perform the detection of rifampicin resistant TB cases. One of the main challenges for the large scale implementation of molecular based tests is the emergence of conflicting results between phenotypic and genotypic tests. This mines the confidence of clinicians in the molecular tests and delays the initiation of an appropriate treatment. A new technique is revolutionizing the genotypic approach to DST: the WGS by Next-Generation Sequencing technologies. This methodology promises to become the solution for a rapid access to universal DST, able indeed to overcome the limitations of the current phenotypic and genotypic assays. Today the use of the generated information is still challenging in decentralized facilities due to the lack of automation for sample processing and standardization in the analysis.The growing knowledge of the molecular mechanisms at the basis of drug resistance and the introduction of high-performing user-friendly tools at peripheral level should allow the very much needed accurate diagnosis of DRTB in the near future.

Entities:  

Keywords:  Molecular drug susceptibility test; Phenotypic drug susceptibility test

Mesh:

Substances:

Year:  2017        PMID: 29116638     DOI: 10.1007/978-3-319-64371-7_12

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  7 in total

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2.  Multiplexed Strain Phenotyping Defines Consequences of Genetic Diversity in Mycobacterium tuberculosis for Infection and Vaccination Outcomes.

Authors:  Allison F Carey; Xin Wang; Nico Cicchetti; Caitlin N Spaulding; Qingyun Liu; Forrest Hopkins; Jessica Brown; Jaimie Sixsmith; Rujapak Sutiwisesak; Samuel M Behar; Thomas R Ioerger; Sarah M Fortune
Journal:  mSystems       Date:  2022-04-18       Impact factor: 7.324

3.  MycoResistance: a curated resource of drug resistance molecules in Mycobacteria.

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Journal:  Database (Oxford)       Date:  2019-01-01       Impact factor: 3.451

Review 4.  Anti-tuberculosis drug resistance in Slovakia, 2018-2019: The first whole-genome epidemiological study.

Authors:  Matúš Dohál; Věra Dvořáková; Miluše Šperková; Igor Porvazník; Andrea Maurizio Cabibbe; Alberto Trovato; Andrea Spitaleri; Erik Michael Rasmussen; Kristián Pršo; Mária Škereňová; Daniela Maria Cirillo; Ivan Solovič; Juraj Mokrý
Journal:  J Clin Tuberc Other Mycobact Dis       Date:  2021-12-20

5.  GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

Authors:  Matthias I Gröschel; Martin Owens; Luca Freschi; Roger Vargas; Maximilian G Marin; Jody Phelan; Zamin Iqbal; Avika Dixit; Maha R Farhat
Journal:  Genome Med       Date:  2021-08-30       Impact factor: 11.117

6.  Whole-genome sequencing-based prediction and analysis of antimicrobial resistance in Yersinia enterocolitica from Ningxia, China.

Authors:  Yuan Yue; Mei Shen; Xiang Liu; Qiong Hao; Yutong Kang; Yanlin Che; Fang Li; Shenglin Chen; Shuai Xu; Huaiqi Jing; Zhen-Jun Li; Xue-Zhang Zhou
Journal:  Front Microbiol       Date:  2022-07-22       Impact factor: 6.064

7.  Impact of Molecular Drug Susceptibility Testing on the Time to Multidrug-resistant Tuberculosis Treatment Initiation.

Authors:  Doosoo Jeon; Hyungseok Kang; Yong Soo Kwon; Jae Joon Yim; Tae Sun Shim
Journal:  J Korean Med Sci       Date:  2020-09-07       Impact factor: 2.153

  7 in total

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