Mycobacterium tuberculosis ribosomal protein S1 (RpsA) and variants with truncated C-terminal end show absence of interaction with pyrazinoic acid.

Pyrazinamide (PZA) is an antibiotic used in first- and second-line tuberculosis treatment regimens. Approximately 50% of multidrug-resistant tuberculosis and over 90% of extensively drug-resistant tuberculosis strains are also PZA resistant. Despite the key role played by PZA, its mechanisms of action are not yet fully understood. It has been postulated that pyrazinoic acid (POA), the hydrolyzed product of PZA, could inhibit trans-translation by binding to Ribosomal protein S1 (RpsA) and competing with tmRNA, the natural cofactor of RpsA. Subsequent data, however, indicate that these early findings resulted from experimental artifact. Hence, in this study we assess the capacity of POA to compete with tmRNA for RpsA. We evaluated RpsA wild type (WT), RpsA ∆A438, and RpsA ∆A438 variants with truncations towards the carboxy terminal end. Interactions were measured using Nuclear Magnetic Resonance spectroscopy (NMR), Isothermal Titration Calorimetry (ITC), Microscale Thermophoresis (MST), and Electrophoretic Mobility Shift Assay (EMSA). We found no measurable binding between POA and RpsA (WT or variants). This suggests that RpsA may not be involved in the mechanism of action of PZA in Mycobacterium tuberculosis, as previously thought. Interactions observed between tmRNA and RpsA WT, RpsA ∆A438, and each of the truncated variants of RpsA ∆A438, are reported

The Physics of the B Factories

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field