Although ACE2 is the primary receptor for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, a systematic assessment of host factors that regulate binding to SARS-CoV-2 spike protein has not been described. Here, we use whole-genome CRISPR activation to identify host factors controlling cellular interactions with SARS-CoV-2. Our top hit was a TLR-related cell surface receptor called leucine-rich repeat-containing protein 15 (LRRC15). LRRC15 expression was sufficient to promote SARS-CoV-2 spike binding where they form a cell surface complex. LRRC15 mRNA is expressed in human collagen-producing lung myofibroblasts and LRRC15 protein is induced in severe Coronavirus Disease 2019 (COVID-19) infection where it can be found lining the airways. Mechanistically, LRRC15 does not itself support SARS-CoV-2 infection, but fibroblasts expressing LRRC15 can suppress both pseudotyped and authentic SARS-CoV-2 infection in trans. Moreover, LRRC15 expression in fibroblasts suppresses collagen production and promotes expression of IFIT, OAS, and MX-family antiviral factors. Overall, LRRC15 is a novel SARS-CoV-2 spike-binding receptor that can help control viral load and regulate antiviral and antifibrotic transcriptional programs in the context of COVID-19 infection.
As high-throughput techniques including proteomics become more accessible to individual laboratories, there is an urgent need for a user-friendly bioinformatics analysis system. Here, we describe FunRich, an open access, standalone functional enrichment and network analysis tool. FunRich is designed to be used by biologists with minimal or no support from computational and database experts. Using FunRich, users can perform functional enrichment analysis on background databases that are integrated from heterogeneous genomic and proteomic resources (>1.5 million annotations). Besides default human specific FunRich database, users can download data from the UniProt database, which currently supports 20 different taxonomies against which enrichment analysis can be performed. Moreover, the users can build their own custom databases and perform the enrichment analysis irrespective of organism. In addition to proteomics datasets, the custom database allows for the tool to be used for genomics, lipidomics and metabolomics datasets. Thus, FunRich allows for complete database customization and thereby permits for the tool to be exploited as a skeleton for enrichment analysis irrespective of the data type or organism used. FunRich (http://www.funrich.org) is user-friendly and provides graphical representation (Venn, pie charts, bar graphs, column, heatmap and doughnuts) of the data with customizable font, scale and color (publication quality).
Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization's (HUPO's) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.
Significance It is believed that the Bcl-2 family protein Bok has a redundant role similar to Bax and Bak in regulating apoptosis. We report that this protein interacts with the key enzyme involved in uridine biosynthesis, uridine monophosphate synthetase, and positively regulates uridine biosynthesis and chemoconversion of 5-fluorouracil (5-FU). Bok-deficient cell lines are resistant to 5-FU. Bok down-regulation is a key feature of cell lines and primary colorectal tumor tissues that are resistant to 5-FU. Our data also show that through its impact on nucleotide metabolism, Bok regulates p53 level and cellular proliferation. Our results have implications for developing Bok as a biomarker for 5-FU resistance and for the development of BOK mimetics for sensitizing 5-FU-resistant cancers.
Intercellular communication was long thought to be regulated exclusively through direct contact between cells or via release of soluble molecules that transmit the signal by binding to a suitable receptor on the target cell, and/or via uptake into that cell. With the discovery of small secreted vesicular structures that contain complex cargo, both in their lumen and the lipid membrane that surrounds them, a new frontier of signal transduction was discovered. These "extracellular vesicles" (EV) were initially thought to be garbage bags through which the cell ejected its waste. Whilst this is a major function of one type of EV, i.e., apoptotic bodies, many EVs have intricate functions in intercellular communication and compound exchange; although their physiological roles are still ill-defined. Additionally, it is now becoming increasingly clear that EVs mediate disease progression and therefore studying EVs has ignited significant interests among researchers from various fields of life sciences. Consequently, the research effort into the pathogenic roles of EVs is significantly higher even though their protective roles are not well established. The "Focus on extracellular vesicles" series of reviews highlights the current state of the art regarding various topics in EV research, whilst this review serves as an introductory overview of EVs, their biogenesis and molecular composition.
Exosomes are a class of extracellular vesicles that are secreted by various cell types. Unlike other extracellular vesicles (ectosomes and apoptotic blebs), exosomes are of endocytic origin. The roles of exosomes in vaccine/drug delivery, intercellular communication and as a possible source of disease biomarkers have sparked immense interest in them, resulting in a plethora of studies. Whilst multidimensional datasets are continuously generated, it is difficult to harness the true potential of the data until they are compiled and made accessible to the biomedical researchers. Here, we describe ExoCarta (http://www.exocarta.org), a manually curated database of exosomal proteins, RNA and lipids. Datasets currently present in ExoCarta are integrated from both published and unpublished exosomal studies. Since its launch in 2009, ExoCarta has been accessed by more than 16,000 unique users. In this article, we discuss the utility of ExoCarta for exosomal research and urge biomedical researchers in the field to deposit their datasets directly to ExoCarta.
Milk is considered as more than a source of nutrition for infants and is a vector involved in the transfer of bioactive compounds and cells. Milk contains abundant quantities of extracellular vesicles (EVs) that may originate from multiple cellular sources. These nanosized vesicles have been well characterized and are known to carry a diverse cargo of proteins, nucleic acids, lipids and other biomolecules. Milk-derived EVs have been demonstrated to survive harsh and degrading conditions in gut, taken up by various cell types, cross biological barriers and reach peripheral tissues. The cargo carried by these dietary EVs has been suggested to have a role in cell growth, development, immune modulation and regulation. Hence, there is considerable interest in understanding the role of milk-derived EVs in mediating inter-organismal and cross-species communication. Furthermore, various attributes such as it being a natural source, as well as its abundance, scalability, economic viability and lack of unwarranted immunologic reactions, has generated significant interest in deploying milk-derived EVs for clinical applications such as drug delivery and disease therapy. In this review, the role of milk-derived EVs in inter-organismal, cross-species communication and in drug delivery is discussed.
Exosomes are small extracellular 40-100 nm diameter membrane vesicles of late endosomal origin that can mediate intercellular transfer of RNAs and proteins to assist premetastatic niche formation. Using primary (SW480) and metastatic (SW620) human isogenic colorectal cancer cell lines we compared exosome protein profiles to yield valuable insights into metastatic factors and signaling molecules fundamental to tumor progression. Exosomes purified using OptiPrep™ density gradient fractionation were 40-100 nm in diameter, were of a buoyant density ~1.09 g/mL, and displayed stereotypic exosomal markers TSG101, Alix, and CD63. A major finding was the selective enrichment of metastatic factors (MET, S100A8, S100A9, TNC), signal transduction molecules (EFNB2, JAG1, SRC, TNIK), and lipid raft and lipid raft-associated components (CAV1, FLOT1, FLOT2, PROM1) in exosomes derived from metastatic SW620 cells. Additionally, using cryo-electron microscopy, ultrastructural components in exosomes were identified. A key finding of this study was the detection and colocalization of protein complexes EPCAM-CLDN7 and TNIK-RAP2A in colorectal cancer cell exosomes. The selective enrichment of metastatic factors and signaling pathway components in metastatic colon cancer cell-derived exosomes contributes to our understanding of the cross-talk between tumor and stromal cells in the tumor microenvironment.
Abstract Background Protein-protein interaction (PPI) databases have become a major resource for investigating biological networks and pathways in cells. A number of publicly available repositories for human PPIs are currently available. Each of these databases has their own unique features with a large variation in the type and depth of their annotations. Results We analyzed the major publicly available primary databases that contain literature curated PPI information for human proteins. This included BIND, DIP, HPRD, IntAct, MINT, MIPS, PDZBase and Reactome databases. The number of binary non-redundant human PPIs ranged from 101 in PDZBase and 346 in MIPS to 11,367 in MINT and 36,617 in HPRD. The number of genes annotated with at least one interactor was 9,427 in HPRD, 4,975 in MINT, 4,614 in IntAct, 3,887 in BIND and <1,000 in the remaining databases. The number of literature citations for the PPIs included in the databases was 43,634 in HPRD, 11,480 in MINT, 10,331 in IntAct, 8,020 in BIND and <2,100 in the remaining databases. Conclusion Given the importance of PPIs, we suggest that submission of PPIs to repositories be made mandatory by scientific journals at the time of manuscript submission as this will minimize annotation errors, promote standardization and help keep the information up to date. We hope that our analysis will help guide biomedical scientists in selecting the most appropriate database for their needs especially in light of the dramatic differences in their content.
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