SummaryDAPAR and ProStaR are software tools to perform the statistical analysis of label-free XIC-based quantitative discovery proteomics experiments. DAPAR contains procedures to filter, normalize, impute missing value, aggregate peptide intensities, perform null hypothesis significance tests and select the most likely differentially abundant proteins with a corresponding false discovery rate. ProStaR is a graphical user interface that allows friendly access to the DAPAR functionalities through a web browser.Availability and implementationDAPAR and ProStaR are implemented in the R language and are available on the website of the Bioconductor project (http://www.bioconductor.org/). A complete tutorial and a toy dataset are accompanying the packages.

Cytokinesis requires the constriction of ESCRT-III filaments on the side of the midbody, where abscission occurs. After ESCRT recruitment at the midbody, it is not known how the ESCRT-III machinery localizes to the abscission site. To reveal actors involved in abscission, we obtained the proteome of intact, post-abscission midbodies (Flemmingsome) and identified 489 proteins enriched in this organelle. Among these proteins, we further characterized a plasma membrane-to-ESCRT module composed of the transmembrane proteoglycan syndecan-4, ALIX and syntenin, a protein that bridges ESCRT-III/ALIX to syndecans. The three proteins are highly recruited first at the midbody then at the abscission site, and their depletion delays abscission. Mechanistically, direct interactions between ALIX, syntenin and syndecan-4 are essential for proper enrichment of the ESCRT-III machinery at the abscission site, but not at the midbody. We propose that the ESCRT-III machinery must be physically coupled to a membrane protein at the cytokinetic abscission site for efficient scission, uncovering common requirements in cytokinesis, exosome formation and HIV budding.

SummarySalmonella is a human and animal pathogen that causes gastro-enteric diseases. The key to Salmonella infection is its entry into intestinal epithelial cells, where the bacterium resides within a Salmonella-containing vacuole (SCV). Salmonella entry also induces the formation of empty macropinosomes, distinct from the SCV, in the vicinity of the entering bacteria. A few minutes after its formation, the SCV increases in size through fusions with the surrounding macropinosomes. Salmonella also induces membrane tubules that emanate from the SCV and lead to SCV shrinkage. Here, we show that these antipodal events are utilized by Salmonella to either establish a vacuolar niche or to be released into the cytosol by SCV rupture. We identify the molecular machinery underlying dynamic SCV growth and shrinkage. In particular, the SNARE proteins SNAP25 and STX4 participate in SCV inflation by fusion with macropinosomes. Thus, host compartment size control emerges as a pathogen strategy for intracellular niche regulation.

In MS-based quantitative proteomics, the FDR control (i.e. the limitation of the number of proteins that are wrongly claimed as differentially abundant between several conditions) is a major postanalysis step. It is classically achieved thanks to a specific statistical procedure that computes the adjusted p-values of the putative differentially abundant proteins. Unfortunately, such adjustment is conservative only if the p-values are well-calibrated; the false discovery control being spuriously underestimated otherwise. However, well-calibration is a property that can be violated in some practical cases. To overcome this limitation, we propose a graphical method to straightforwardly and visually assess the p-value well-calibration, as well as the R codes to embed it in any pipeline. All MS data have been deposited in the ProteomeXchange with identifier PXD002370 (http://proteomecentral.proteomexchange.org/dataset/PXD002370).

The intestinal microbiota modulates host physiology and gene expression via mechanisms that are not fully understood. Here we examine whether host epitranscriptomic marks are affected by the gut microbiota. We use methylated RNA-immunoprecipitation and sequencing (MeRIP-seq) to identify N6-methyladenosine (m 6 A) modifications in mRNA of mice carrying conventional, modified, or no microbiota. We find that variations in the gut microbiota correlate with m 6 A modifications in the cecum, and to a lesser extent in the liver, affecting pathways related to metabolism, inflammation and antimicrobial responses. We analyze expression levels of several known writer and eraser enzymes, and find that the methyltransferase Mettl16 is downregulated in absence of a microbiota, and one of its target mRNAs, encoding S-adenosylmethionine synthase Mat2a, is less methylated. We furthermore show that Akkermansia muciniphila and Lactobacillus plantarum affect specific m 6 A modifications in mono-associated mice. Our results highlight epitranscriptomic modifications as an additional level of interaction between commensal bacteria and their host.

SummarySirtuin 2 is a nicotinamide-adenine-dinucleotide-dependent deacetylase that regulates cell processes such as carcinogenesis, cell cycle, DNA damage, and infection. Subcellular localization of SIRT2 is crucial for its function but is poorly understood. Infection with the bacterial pathogen Listeria monocytogenes, which relocalizes SIRT2 from the cytoplasm to the chromatin, provides an ideal stimulus for the molecular study of this process. In this report, we provide a map of SIRT2 post-translational modification sites and focus on serine 25 phosphorylation. We show that infection specifically induces dephosphorylation of S25, an event essential for SIRT2 chromatin association. Furthermore, we identify a nuclear complex formed by the phosphatases PPM1A and PPM1B, with SIRT2 essential for controlling H3K18 deacetylation and SIRT2-mediated gene repression during infection and necessary for a productive Listeria infection. This study reveals a molecular mechanism regulating SIRT2 function and localization, paving the way for understanding other SIRT2-regulated cellular processes.

Shigella flexneri invades host cells by entering within a bacteria-containing vacuole (BCV). In order to establish its niche in the host cytosol, the bacterium ruptures its BCV. Contacts between S. flexneri BCV and infection-associated macropinosomes (IAMs) formed in situ have been reported to enhance BCV disintegration. The mechanism underlying S. flexneri vacuolar escape remains however obscure. To decipher the molecular mechanism priming the communication between the IAMs and S. flexneri BCV, we performed mass spectrometry-based analysis of the magnetically purified IAMs from S. flexneri-infected cells. While proteins involved in host recycling and exocytic pathways were significantly enriched at the IAMs, we demonstrate more precisely that the S. flexneri type III effector protein IpgD mediates the recruitment of the exocyst to the IAMs through the Rab8/Rab11 pathway. This recruitment results in IAM clustering around S. flexneri BCV. More importantly, we reveal that IAM clustering subsequently facilitates an IAM-mediated unwrapping of the ruptured vacuole membranes from S. flexneri, enabling the naked bacterium to be ready for intercellular spread via actin-based motility. Taken together, our work untangles the molecular cascade of S. flexneri-driven host trafficking subversion at IAMs to develop its cytosolic lifestyle, a crucial step en route for infection progression at cellular and tissue level.

Motivation: Quantitative mass spectrometry-based proteomics data are characterized by high rates of missing values, which may be of two kinds: missing completely-at-random (MCAR) and missing not-at-random (MNAR). Despite numerous imputation methods available in the literature, none account for this duality, for it would require to diagnose the missingness mechanism behind each missing value. Results:A multiple imputation strategy is proposed by combining MCAR-devoted and MNAR-devoted imputation algorithms. First, we propose an estimator for the proportion of MCAR values and show it is asymptotically unbiased under assumptions adapted to label-free proteomics data. This allows us to estimate the number of MCAR values in each sample and to take into account the nature of missing values through an original multiple imputation method. We evaluate this approach on simulated data and shows it outperforms traditionally used imputation algorithms. Availability:The proposed methods are implemented in the R package imp4p (available on the CRAN Giai Gianetto (2020)), which is itself accessible through Prostar software.