A Multinational Analysis of Mutations and Heterogeneity in PZase, RpsA, and PanD Associated with Pyrazinamide Resistance in M/XDR Mycobacterium tuberculosis.

Pyrazinamide (PZA) is an important first-line drug in all existing and new tuberculosis (TB) treatment regimens. PZA-resistance in M. tuberculosis is increasing, especially among M/XDR cases. Noted issues with PZA Drug Susceptibility Testing (DST) have driven the search for alternative tests. This study provides a comprehensive assessment of PZA molecular diagnostics in M/XDR TB cases. A set of 296, mostly XDR, clinical M. tuberculosis isolates from four countries were subjected to DST for eight drugs, confirmatory Wayne's assay, and whole-genome sequencing. Three genes implicated in PZA resistance, pncA, rpsA, and panD were investigated. Assuming all non-synonymous mutations cause resistance, we report 90% sensitivity and 65% specificity for a pncA-based molecular test. The addition of rpsA and panD potentially provides 2% increase in sensitivity. Molecular heterogeneity in pncA was associated with resistance and should be evaluated as a diagnostic tool. Mutations near the N-terminus and C-terminus of PZase were associated with East-Asian and Euro-American lineages, respectively. Finally, Euro-American isolates are most likely to have a wild-type PZase and escape molecular detection. Overall, the 8-10% resistance without markers may point to alternative mechanisms of resistance. Confirmatory mutagenesis may improve the disconcertingly low specificity but reduce sensitivity since not all mutations may cause resistance

DataDock: An Open Source Data Hub for Research

Every research project necessitates data, often requiring sharing and collaborative review within a team. However, there is a dearth of good open-source data sharing and reviewing services. Existing file-sharing services generally mandate paid subscriptions for increased storage or additional members, diverting research funds from addressing the core research problem that a lab is attempting to work on. Moreover, these services often lack direct features for reviewing or commenting on data quality, a vital part of ensuring high quality data generation. In response to these challenges, we present DataDock, a specialized file transfer service crafted for specifically for researchers. DataDock operates as an application hosted on a research lab server. This design ensures that, with access to a machine and an internet connection, teams can facilitate file storage, transfer, and review without incurring extra costs. Being an open-source project, DataDock can be customized to suit the unique requirements of any research team, and is able to evolve to meet the needs of the research community. We also note that there are no limitations with respect to what data can be shared, downloaded, or commented on. As DataDock is agnostic to the file type, it can be used in any field from bioinformatics to particle physics; as long as it can be stored in a file, it can be shared. We open source the code here: https://github.com/lxaw/DataDockComment: 7 pages, 6 figures, submitted and in review at The 2024 World Congress in Computer Science, Computer Engineering, And Applied Computing (CSCE