Drs2p-related P-type ATPases Dnf1p and Dnf2p Are Required for Phospholipid Translocation across the Yeast Plasma Membrane and Serve a Role in Endocytosis

Plasma membranes in eukaryotic cells display asymmetric lipid distributions with aminophospholipids concentrated in the inner and sphingolipids in the outer leaflet. This asymmetry is maintained by ATP-driven lipid transporters whose identities are unknown. The yeast plasma membrane contains two P-type ATPases, Dnf1p and Dnf2p, with structural similarity to ATPase II, a candidate aminophospholipid translocase from bovine chromaffin granules. Loss of Dnf1p and Dnf2p virtually abolished ATP-dependent transport of NBD-labeled phosphatidylethanolamine, phosphatidylserine, and phosphatidylcholine from the outer to the inner plasma membrane leaflet, leaving transport of sphingolipid analogs unaffected. Labeling with trinitrobenzene sulfonic acid revealed that the amount of phosphatidylethanolamine exposed on the surface of Δdnf1Δdnf2 cells increased twofold relative to wild-type cells. Phosphatidylethanolamine exposure by Δdnf1Δdnf2 cells further increased upon removal of Drs2p, an ATPase II homolog in the yeast Golgi. These changes in lipid topology were accompanied by a cold-sensitive defect in the uptake of markers for bulk-phase and receptor-mediated endocytosis. Our findings demonstrate a requirement for Dnf1p and Dnf2p in lipid translocation across the yeast plasma membrane. Moreover, it appears that Dnf1p, Dnf2p and Drs2p each help regulate the transbilayer lipid arrangement in the plasma membrane, and that this regulation is critical for budding endocytic vesicles

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 science. © The Author(s) 2019. Published by Oxford University Press