The Two-Domain LysX Protein of Mycobacterium tuberculosis Is Required for Production of Lysinylated Phosphatidylglycerol and Resistance to Cationic Antimicrobial Peptides

The well-recognized phospholipids (PLs) of Mycobacterium tuberculosis (Mtb) include several acidic species such as phosphatidylglycerol (PG), cardiolipin, phosphatidylinositol and its mannoside derivatives, in addition to a single basic species, phosphatidylethanolamine. Here we demonstrate that an additional basic PL, lysinylated PG (L-PG), is a component of the PLs of Mtb H37Rv and that the lysX gene encoding the two-domain lysyl-transferase (mprF)-lysyl-tRNA synthetase (lysU) protein is responsible for L-PG production. The Mtb lysX mutant is sensitive to cationic antibiotics and peptides, shows increased association with lysosome-associated membrane protein–positive vesicles, and it exhibits altered membrane potential compared to wild type. A lysX complementing strain expressing the intact lysX gene, but not one expressing mprF alone, restored the production of L-PG and rescued the lysX mutant phenotypes, indicating that the expression of both proteins is required for LysX function. The lysX mutant also showed defective growth in mouse and guinea pig lungs and showed reduced pathology relative to wild type, indicating that LysX activity is required for full virulence. Together, our results suggest that LysX-mediated production of L-PG is necessary for the maintenance of optimal membrane integrity and for survival of the pathogen upon infection

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research