Background Cancer patients are thought to have an increased risk of developing severe Coronavirus Disease 2019 (COVID-19) infection and of dying from the disease. In this work, predictive factors for COVID-19 severity and mortality in cancer patients were investigated. Patients and Methods In this large nationwide retro-prospective cohort study, we collected data on patients with solid tumours and COVID-19 diagnosed between March 1 and June 11, 2020. The primary endpoint was all-cause mortality and COVID-19 severity, defined as admission to an intensive care unit (ICU) and/or mechanical ventilation and/or death, was one of the secondary endpoints. Results From April 4 to June 11, 2020, 1289 patients were analysed. The most frequent cancers were digestive and thoracic. Altogether, 424 (33%) patients had a severe form of COVID-19 and 370 (29%) patients died. In multivariate analysis, independent factors associated with death were male sex (odds ratio 1.73, 95%CI: 1.18-2.52), ECOG PS ≥ 2 (OR 3.23, 95%CI: 2.27-4.61), updated Charlson comorbidity index (OR 1.08, 95%CI: 1.01-1.16) and admission to ICU (OR 3.62, 95%CI 2.14-6.11). The same factors, age along with corticosteroids before COVID-19 diagnosis, and thoracic primary tumour site were independently associated with COVID-19 severity. None of the anticancer treatments administered within the previous 3 months had any effect on mortality or COVID-19 severity, except cytotoxic chemotherapy in the subgroup of patients with detectable SARS-CoV-2 by RT-PCR, which was associated with a slight increase of the risk of death (OR 1.53; 95%CI: 1.00-2.34; p = 0.05). A total of 431 (39%) patients had their systemic anticancer treatment interrupted or stopped following diagnosis of COVID-19. Conclusions Mortality and COVID-19 severity in cancer patients are high and are associated with general characteristics of patients. We found no deleterious effects of recent anticancer treatments, except for cytotoxic chemotherapy in the RT-PCR-confirmed subgroup of patients. In almost 40% of patients, the systemic anticancer therapy was interrupted or stopped after COVID-19 diagnosis.

The Chromosome-Centric Human Proteome Project (C-HPP) aims at cataloguing the proteins as gene products encoded by the human genome in a chromosome-centric manner. The existence of products of about 82% of the genes has been confirmed at the protein level. However, the number of so-called "missing proteins" remains significant. It was recently suggested that the expression of proteins that have been systematically missed might be restricted to particular organs or cell types, for example, the testis. Testicular function, and spermatogenesis in particular, is conditioned by the successive activation or repression of thousands of genes and proteins including numerous germ cell- and testis-specific products. Both the testis and postmeiotic germ cells are thus promising sites at which to search for missing proteins, and ejaculated spermatozoa are a potential source of proteins whose expression is restricted to the germ cell lineage. A trans-chromosome-based data analysis was performed to catalog missing proteins in total protein extracts from isolated human spermatozoa. We have identified and manually validated peptide matches to 89 missing proteins in human spermatozoa. In addition, we carefully validated three proteins that were scored as uncertain in the latest neXtProt release (09.19.2014). A focus was then given to the 12 missing proteins encoded on chromosomes 2 and 14, some of which may putatively play roles in ciliation and flagellum mechanistics. The expression pattern of C2orf57 and TEX37 was confirmed in the adult testis by immunohistochemistry. On the basis of transcript expression during human spermatogenesis, we further consider the potential for discovering additional missing proteins in the testicular postmeiotic germ cell lineage and in ejaculated spermatozoa. This project was conducted as part of the C-HPP initiatives on chromosomes 14 (France) and 2 (Switzerland). The mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium under the data set identifier PXD002367.

BackgroundIn environmental sequencing studies, fungi can be identified based on nucleic acid sequences, using either highly variable sequences as species barcodes or conserved sequences containing a high-quality phylogenetic signal. For the latter, identification relies on phylogenetic analyses and the adoption of the phylogenetic species concept.Such analysis requires that the reference sequences are well identified and deposited in public-access databases. However, many entries in the public sequence databases are problematic in terms of quality and reliability and these data require screening to ensure correct phylogenetic interpretation.Methods and Principal FindingsTo facilitate phylogenetic inferences and phylogenetic assignment, we introduce a fungal sequence database. The database PHYMYCO-DB comprises fungal sequences from GenBank that have been filtered to satisfy stringent sequence quality criteria. For the first release, two widely used molecular taxonomic markers were chosen: the nuclear SSU rRNA and EF1-α gene sequences. Following the automatic extraction and filtration, a manual curation is performed to remove problematic sequences while preserving relevant sequences useful for phylogenetic studies. As a result of curation, ∼20% of the automatically filtered sequences have been removed from the database. To demonstrate how PHYMYCO-DB can be employed, we test a set of environmental Chytridiomycota sequences obtained from deep sea samples.ConclusionPHYMYCO-DB offers the tools necessary to: (i) extract high quality fungal sequences for each of the 5 fungal phyla, at all taxonomic levels, (ii) extract already performed alignments, to act as ‘reference alignments’, (iii) launch alignments of personal sequences along with stored data. A total of 9120 SSU rRNA and 672 EF1-α high-quality fungal sequences are now available.The PHYMYCO-DB is accessible through the URL http://phymycodb.genouest.org/.

Summary• In soil, some antagonistic rhizobacteria contribute to reduce root diseases caused by phytopathogenic fungi. Direct modes of action of these bacteria have been largely explored; however, commensal interaction also takes place between these microorganisms and little is known about the influence of filamentous fungi on bacteria.• An in vitro confrontation bioassay between the pathogenic fungus Gaeumannomyces graminis var. tritici (Ggt) and the biocontrol bacterial strain Pseudomonas fluorescens Pf29Arp was set up to analyse bacterial transcriptional changes induced by the fungal mycelium at three time-points of the interaction before cell contact and up until contact. For this, a Pf29Arp shotgun DNA microarray was constructed. Specifity of Ggt effect was assessed in comparison with one of two other filamentous fungi, Laccaria bicolor and Magnaporthe grisea.• During a commensal interaction, Ggt increased the growth rate of Pf29Arp. Before contact, Ggt induced bacterial genes involved in mycelium colonization. At contact, genes encoding protein of stress response and a patatin-like protein were up-regulated. Among all the bacterial genes identified, xseB was specifically upregulated at contact by Ggt but down-regulated by the other fungi.• Data showed that the bacterium sensed the presence of the fungus early, but the main gene alteration occurred during bacterial-fungal cell contact.

For the C-HPP consortium, dark proteins include not only uPE1, but also missing proteins (MPs, PE2-4), smORFs, proteins from lncRNAs, and products from uncharacterized transcripts. Here, we investigated the expression of dark proteins in the human testis by combining public mRNA and protein expression data for several tissues and performing LC-MS/MS analysis of testis protein extracts. Most uncharacterized proteins are highly expressed in the testis. Thirty could be identified in our data set, of which two were selected for further analyses: (1) A0AOU1RQG5, a putative cancer/testis antigen specifically expressed in the testis, where it accumulates in the cytoplasm of elongated spermatids; and (2) PNMA6E, which is enriched in the testis, where it is found in the germ cell nuclei during most stages of spermatogenesis. Both proteins are coded on Chromosome X. Finally, we studied the expression of other dark proteins, uPE1 and MPs, in a series of human tissues. Most were highly expressed in the testis at both the mRNA and protein levels. The testis appears to be a relevant organ to study the dark proteome, which may have a function related to spermatogenesis and germ cell differentiation. The mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium under the data set identifier PXD009598.

BackgroundAccurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes.ResultsOur proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data.ConclusionsPeptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu.Data are available via ProteomeXchange under identifier PXD010618.Electronic supplementary materialThe online version of this article (10.1186/s12864-019-5431-9) contains supplementary material, which is available to authorized users.

Spermatozoa acquire their fertilizing capacity during a complex maturation process that occurs in the epididymis. This process involves a substantial molecular remodeling at the surface of the gamete. Epididymis is divided into three regions (the caput, corpus, and cauda) or into 19 intraregional segments based on histology. Most studies carried out on epididymal maturation have been performed on sperm samples or tissue extracts. Here, we used MALDI imaging mass spectrometry in the positive and negative ion modes combined with spatial segmentation and automated metabolite annotation to study the precise localization of metabolites directly in the rat epididymis. The spatial segmentation revealed that the rat epididymis could be divided into several molecular clusters different from the 19 intraregional segments. The discriminative m/z values that contributed the most to each molecular cluster were then annotated and corresponded mainly to phosphatidylcholines, sphingolipids, glycerophosphates, triacylglycerols, plasmalogens, phosphatidylethanolamines, and lysophosphatidylcholines. A substantial remodeling of lipid composition during epididymal maturation was observed. It was characterized in particular by an increase in the number of sphingolipids and plasmalogens and a decrease in the proportion of triacylglycerols annotated from caput to cauda. Ion images reveal that molecules belonging to the same family can have very different localizations along the epididymis. For some of them, annotation was confirmed by on-tissue MS/MS experiments. A 3D model of the epididymis head was reconstructed from 61 sections analyzed with a lateral resolution of 50 μm and can be used to obtain information on the localization of a given analyte in the whole volume of the tissue.

Endometriosis is a common chronic gynaecological disease causing various symptoms, such as infertility and chronic pain. The gold standard for its diagnosis is still laparoscopy and the biopsy of endometriotic lesions. Here, we aimed to compare the eutopic endometrium from women with or without endometriosis to identify proteins that may be considered as potential biomarker candidates. Eutopic endometrium was collected from patients with endometriosis (n = 4) and women without endometriosis (n = 5) during a laparoscopy surgery during the mid-secretory phase of their menstrual cycle. Total proteins from tissues were extracted and digested before LC-MS-MS analysis. Among the 5301 proteins identified, 543 were differentially expressed and enriched in two specific KEGG pathways: focal adhesion and PI3K/AKT signaling. Integration of our data with a large-scale proteomics dataset allowed us to highlight 11 proteins that share the same trend of dysregulation in eutopic endometrium, regardless of the phase of the menstrual cycle. Our results constitute the first step towards the identification of potential promising endometrial diagnostic biomarkers. They provide new insights into the mechanisms underlying endometriosis and its etiology. Our results await further confirmation on a larger sample cohort.