GenoMycAnalyzer: a web-based tool for species and drug resistance prediction for Mycobacterium genomes.

BACKGROUND: Drug-resistant tuberculosis (TB) is a major threat to global public health. Whole-genome sequencing (WGS) is a useful tool for species identification and drug resistance prediction, and many clinical laboratories are transitioning to WGS as a routine diagnostic tool. However, user-friendly and high-confidence automated bioinformatics tools are needed to rapidly identify M. tuberculosis complex (MTBC) and non-tuberculous mycobacteria (NTM), detect drug resistance, and further guide treatment options. RESULTS: We developed GenoMycAnalyzer, a web-based software that integrates functions for identifying MTBC and NTM species, lineage and spoligotype prediction, variant calling, annotation, drug-resistance determination, and data visualization. The accuracy of GenoMycAnalyzer for genotypic drug susceptibility testing (gDST) was evaluated using 5,473 MTBC isolates that underwent phenotypic DST (pDST). The GenoMycAnalyzer database was built to predict the gDST for 15 antituberculosis drugs using the World Health Organization mutational catalogue. Compared to pDST, the sensitivity of drug susceptibilities by the GenoMycAnalyzer for first-line drugs ranged from 95.9% for rifampicin (95% CI 94.8-96.7%) to 79.6% for pyrazinamide (95% CI 76.9-82.2%), whereas those for second-line drugs ranged from 98.2% for levofloxacin (95% CI 90.1-100.0%) to 74.9% for capreomycin (95% CI 69.3-80.0%). Notably, the integration of large deletions of the four resistance-conferring genes increased gDST sensitivity. The specificity of drug susceptibilities by the GenoMycAnalyzer ranged from 98.7% for amikacin (95% CI 97.8-99.3%) to 79.5% for ethionamide (95% CI 76.4-82.3%). The incorporated Kraken2 software identified 1,284 mycobacterial species with an accuracy of 98.8%. GenoMycAnalyzer also perfectly predicted lineages for 1,935 MTBC and spoligotypes for 54 MTBC. CONCLUSIONS: GenoMycAnalyzer offers both web-based and graphical user interfaces, which can help biologists with limited access to high-performance computing systems or limited bioinformatics skills. By streamlining the interpretation of WGS data, the GenoMycAnalyzer has the potential to significantly impact TB management and contribute to global efforts to combat this infectious disease. GenoMycAnalyzer is available at http://www.mycochase.org .

pncA Large Deletion is the Characteristic of Pyrazinamide-Resistant Mycobacterium tuberculosis belonging to the East Asian Lineage.

BACKGROUND: Pyrazinamide (PZA) is often used as an add-on agent in the treatment of multidrug-resistant tuberculosis, regardless of phenotypic drug susceptibility testing (pDST) results. However, evaluating the effectiveness of PZA is challenging because of its low pH activity, which can result in unreliable pDST results. This study aimed to investigate the genomic characteristics associated with PZA resistance that can be used to develop genotypic DST. MATERIALS AND METHODS: A publicly available whole genome sequencing (WGS) dataset of 10,725 Mycobacterium tuberculosis complex genomes (3,326 phenotypically PZA-resistant and 7,399 phenotypically PZA-susceptible isolates) were analyzed. RESULTS: In total, 2,934 pncA non-silent mutations were identified in 2,880 isolates (26.9%). Detected mutations were found throughout the entire coding region of pncA in a scattered pattern, of which the most frequent mutation was p.Q10P (n = 278), followed by p.H57D (n = 167) and c.-11A>G (n = 122). The sensitivity and specificity of the group 1 or 2 mutations reported by the World Health Organization (WHO) mutational catalogue were 73.0% and 98.9%, respectively. We further identified 18 novel pncA mutations that were significantly associated with phenotypically PZA-resistant. In addition to these mutations, we identified 102 large deletions in the pncA gene, and all but two isolates were phenotypically resistant to PZA isolates. Notably, pncA deletions were mutually exclusive to pncA mutations, and more than half of the isolates with pncA large deletions belonged to the East Asian lineage (67.6%). The sensitivity, specificity, positive predictive value, and negative predictive value of the pooled variants (group 1 or 2 mutations, novel resistance-associated mutations, and large deletions of the pncA gene) were 79.0%, 98.9%, 97.0%, and 91.3%, respectively. The area under the curve (AUC) value for the pooled variants was significantly higher than the AUC value for the group 1 or 2 mutations (P <0.001), indicating that the pooled variants have a better discriminative ability for predicting PZA resistance. CONCLUSION: Using WGS, we found that the pncA mutations are scattered without specific mutational hotspots, and large deletions associated with PZA resistance are more common in the East Asian lineage of M. tuberculosis isolates. Our data also demonstrated the reliability of group 1 or 2 mutations presented in the WHO mutation catalogue and the need for further investigation on group 3 mutations, contributing to the evaluation of the current knowledge base on mutations associated with the PZA-resistant M. tuberculosis complex.

tReasure: R-based GUI package analyzing tRNA expression profiles from small RNA sequencing data.

BACKGROUND: Recent deep sequencing technologies have proven to be valuable resources to gain insights into the expression profiles of diverse tRNAs. However, despite these technologies, the association of tRNAs with diverse diseases has not been explored in depth because analytical tools are lacking. RESULTS: We developed a user-friendly tool, tRNA Expression Analysis Software Utilizing R for Easy use (tReasure), to analyze differentially expressed tRNAs (DEtRNAs) from deep sequencing data of small RNAs using R packages. tReasure can quantify individual mature tRNAs, isodecoders, and isoacceptors. By adopting stringent mapping strategies, tReasure supports the precise measurement of mature tRNA read counts. The whole analysis workflow for determining DEtRNAs (uploading FASTQ files, removing adapter sequences and poor-quality reads, mapping and quantifying tRNAs, filtering out low count tRNAs, determining DEtRNAs, and visualizing statistical analysis) can be performed with the tReasure package. CONCLUSIONS: tReasure is an open-source software available for download at https://treasure.pmrc.re.kr and will be indispensable for users who have little experience with command-line software to explore the biological implication of tRNA expression.

Rapid and sensitive detection of Salmonella species targeting the hilA gene using a loop-mediated isothermal amplification assay.

Salmonella species are among the major pathogens that cause foodborne illness outbreaks. In this study, we aimed to develop a loop-mediated isothermal amplification (LAMP) assay for the rapid and sensitive detection of Salmonella species. We designed LAMP primers targeting the hilA gene as a universal marker of Salmonella species. A total of seven Salmonella species strains and 11 non-Salmonella pathogen strains from eight different genera were used in this study. All Salmonella strains showed positive amplification signals with the Salmonella LAMP assay; however, there was no non-specific amplification signal for the non-Salmonella strains. The detection limit was 100 femtograms (20 copies per reaction), which was ~1,000 times more sensitive than the detection limits of the conventional polymerase chain reaction (PCR) assay (100 pg). The reaction time for a positive amplification signal was less than 20 minutes, which was less than one-third the time taken while using conventional PCR. In conclusion, our Salmonella LAMP assay accurately detected Salmonella species with a higher degree of sensitivity and greater rapidity than the conventional PCR assay, and it may be suitable for point-of-care testing in the field.