MGIT Enriched Shotgun Metagenomics for Routine Identification of Nontuberculous Mycobacteria: a Route to Personalized Health Care.

Currently, nontuberculous mycobacteria (NTM) are identified using small genomic regions, and species-level identification is often not possible. We introduce a next-generation sequencing (NGS) workflow that identifies mycobacteria to (sub)species level on the basis of the whole genome extracted from enriched shotgun metagenomic data. This technique is used to study the association between genotypes and clinical manifestations to pave the way to more personalized health care. Two sets of clinical isolates (explorative set [n = 212] and validation set [n = 235]) were included. All data were analyzed using a custom pipeline called MyCodentifier. Sequences were matched against a custom hsp65 database (NGS-hsp65) and whole-genome database (NGS-WG) created based on the phylogeny presented by Tortoli et al. (E. Tortoli, T. Fedrizzi, C. J. Meehan, A. Trovato, et al., Infect Genet Evol 56:19-25, 2017, https://doi.org/10.1016/j.meegid.2017.10.013). Lastly, phylogenetic analysis was performed and correlated with clinical manifestation. In the explorative set, we observed 98.6% agreement between the line probe assay and the NGS-hsp65 database. In the validation set, 99.1% agreement between the NGS-WG and NGS-hsp65 databases was seen on the complex level. We identified a cluster of Mycobacterium marinum isolates not represented by the Tortoli et al. phylogeny. Phylogenetic analysis of M. avium complex isolates confirmed misclassification of M. timonense and M. bouchedurhonense and identified subclusters within M. avium although no correlation with clinical manifestation was observed. We performed routine NGS to identify NTM from MGIT enriched shotgun metagenomic data. Phylogenetic analyses identified subtypes of M. avium, but in our set of isolates no correlation with clinical manifestation was found. However, this NGS workflow paves a way for more personalized health care in the future.

Implementation of Semiautomated Antimicrobial Susceptibility Interpretation Hardware for Nontuberculous Mycobacteria May Overestimate Susceptibility.

Nontuberculous mycobacteria (NTM) cause severe opportunistic infections and have a rising incidence in most settings. Rising diagnostic need must be met by national reference laboratories, which rely on Clinical and Laboratory Standards Institute (CLSI) guideline-approved manual readout of microtiter plates for antimicrobial susceptibility testing (AST) to determine antibiotic minimum inhibitory concentrations (MICs). Interpretation of these plates leads to different outcomes between laboratories. The SensiTitre Vizion digital MIC viewing system (Vizion) offers a more streamlined approach using semiautomated reading. Here, we conducted a blinded trial comparing the outcome of AST between manual readout and Vizion readout for 132 NTM isolates, amounting to 727 individual tests for antibiotic susceptibility ranging across 13 individual antibiotics with established CLSI breakpoints. From this, we calculated specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV) and the F1 value, as well as assessing major error (ME) and very major error (VME) rates. We find that Vizion-assisted AST produces significantly lower MICs (paired Wilcox signed rank test; P < 0.0001). The Vizion had an accuracy of 89,40%, producing 61 MEs (8.39%) and 16 VMEs (2.20%). The calculated specificity was 0.8370, the sensitivity was 0.9550, the PPV was 0.8460, the NPV was 0.9520, and the F1 score was 0.8970. We show that discrepant readings mostly stem from CLSI guideline breakpoints being close to, or overlapping, the MIC50 values, leading to small discrepancies crossing the breakpoint, contributing to VMEs and MEs. Using the Vizion in standard clinical diagnostics for NTM might lead to an overestimation of antibiotic susceptibility.

Linking minimum inhibitory concentrations to whole genome sequence-predicted drug resistance in Mycobacterium tuberculosis strains from Romania.

Mycobacterium tuberculosis drug resistance poses a major threat to tuberculosis control. Current phenotypic tests for drug susceptibility are time-consuming, technically complex, and expensive. Whole genome sequencing is a promising alternative, though the impact of different drug resistance mutations on the minimum inhibitory concentration (MIC) remains to be investigated. We examined the genomes of 72 phenotypically drug-resistant Mycobacterium tuberculosis isolates from 72 Romanian patients for drug resistance mutations. MICs for first- and second-line drugs were determined using the MycoTB microdilution method. These MICs were compared to macrodilution critical concentration testing by the Mycobacterium Growth Indicator Tube (MGIT) platform and correlated to drug resistance mutations. Sixty-three (87.5%) isolates harboured drug resistance mutations; 48 (66.7%) were genotypically multidrug-resistant. Different drug resistance mutations were associated with different MIC ranges; katG S315T for isoniazid, and rpoB S450L for rifampicin were associated with high MICs. However, several mutations such as in rpoB, rrs and rpsL, or embB were associated with MIC ranges including the critical concentration for rifampicin, aminoglycosides or ethambutol, respectively. Different resistance mutations lead to distinct MICs, some of which may still be overcome by increased dosing. Whole genome sequencing can aid in the timely diagnosis of Mycobacterium tuberculosis drug resistance and guide clinical decision-making.