Wayne’s Assay: A Screening Method for Indirect Detection of Pyrazinamide Resistance in Mycobacterium Tuberculosis Clinical Isolates

Wabale, Vaishali

doi:10.15406/jbmoa.2017.05.00123

Cited by 1 publication

(3 citation statements)

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“…These approaches may be biased, with a risk of missing the correct physical/biological implications of PZAse mutations because PZA resistance could also be attributed to other factors besides PZAse activity itself, like differential PZAse expression levels [ 84 ] or dysfunction in other targets like panD [ 85 ], and many others still unknown [ 86 ]. This problem is explicit when a strain has PZAse mutations that do not affect the PZAse enzymatic function, but mutations in other critical genes [ 14 , 87 , 88 ] that generate PZA resistance in the bacteria. These cases would erroneously attribute PZAse mutations that do not affect the enzymatic function, the apparent effect of causing PZA resistance.…”

Section: Discussionmentioning

confidence: 99%

“…Alternate assays comprise the MODS [ 17 ] and MODS-PZA [ 18 ] methods, based on microscopic observation and the colorimetric Wayne test and variants like the reported by Aono et al ., 2018 [ 19 ] or Alcántara et al ., 2019 [ 20 ]. The latter detect expelled POA in the extracellular environment, a biomarker of PZA resistance [ 14 , 21 ], and indirectly measures the PZAse activity [ 20 ]. Nevertheless, the high cost, duration, or lack of reproducibility of these tests limit their use.…”

Section: Introductionmentioning

confidence: 99%

“…Mutations directly affecting the active site (AS) (Cys138, Asp8, and Lys96), or the metal coordination site (MCS) (Asp49, His51, His57, and His71) are more likely to impair PZAse function [13]. Current knowledge of pncA gene sequences has shown that PZA resistant strains are associated with pncA mutations scattered throughout the entire gene which deplete the PZAse function [10,[14][15][16]. It is important to highlight that a failure in the PZAse function strictly causes resistance to PZA.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of Mycobacterium tuberculosis pyrazinamidase function based on structural stability, physicochemical and geometrical descriptors

et al. 2020

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Background Pyrazinamide is an important drug against the latent stage of tuberculosis and is used in both first- and second-line treatment regimens. Pyrazinamide-susceptibility test usually takes a week to have a diagnosis to guide initial therapy, implying a delay in receiving appropriate therapy. The continued increase in multi-drug resistant tuberculosis and the prevalence of pyrazinamide resistance in several countries makes the development of assays for prompt identification of resistance necessary. The main cause of pyrazinamide resistance is the impairment of pyrazinamidase function attributed to mutations in the promoter and/or pncA coding gene. However, not all pncA mutations necessarily affect the pyrazinamidase function. Objective To develop a methodology to predict pyrazinamidase function from detected mutations in the pncA gene. Methods We measured the catalytic constant (k cat ), K M , enzymatic efficiency, and enzymatic activity of 35 recombinant mutated pyrazinamidase and the wild type (Protein Data Bank ID = 3pl1). From all the 3D modeled structures, we extracted several predictors based on three categories: structural stability (estimated by normal mode analysis and molecular dynamics), physicochemical, and geometrical characteristics. We used a stepwise Akaike’s information criterion forward multiple log-linear regression to model each kinetic parameter with each category of predictors. We also developed weighted models combining the three categories of predictive models for each kinetic parameter. We tested the robustness of the predictive ability of each model by 6-fold cross-validation against random models. Results The stability, physicochemical, and geometrical descriptors explained most of the variability (R 2 ) of the kinetic parameters. Our models are best suited to predict k cat , efficiency, and activity based on the root-mean-square error of prediction of the 6-fold cross-validation. Conclusions This study shows a quick approach to predict the pyrazinamidase function only from the pncA sequence when point mutations are present. This can be an important tool to detect pyrazinamide resistance.

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