Elucidation of tonic and activated B-cell receptor signaling in Burkitt's lymphoma provides insights into regulation of cell survival.

Burkitt's lymphoma (BL) is a highly proliferative B-cell neoplasm and is treated with intensive chemotherapy that, because of its toxicity, is often not suitable for the elderly or for patients with endemic BL in developing countries. BL cell survival relies on signals transduced by B-cell antigen receptors (BCRs). However, tonic as well as activated BCR signaling networks and their relevance for targeted therapies in BL remain elusive. We have systematically characterized and compared tonic and activated BCR signaling in BL by quantitative phosphoproteomics to identify novel BCR effectors and potential drug targets. We identified and quantified ∼16,000 phospho-sites in BL cells. Among these sites, 909 were related to tonic BCR signaling, whereas 984 phospho-sites were regulated upon BCR engagement. The majority of the identified BCR signaling effectors have not been described in the context of B cells or lymphomas yet. Most of these newly identified BCR effectors are predicted to be involved in the regulation of kinases, transcription, and cytoskeleton dynamics. Although tonic and activated BCR signaling shared a considerable number of effector proteins, we identified distinct phosphorylation events in tonic BCR signaling. We investigated the functional relevance of some newly identified BCR effectors and show that ACTN4 and ARFGEF2, which have been described as regulators of membrane-trafficking and cytoskeleton-related processes, respectively, are crucial for BL cell survival. Thus, this study provides a comprehensive dataset for tonic and activated BCR signaling and identifies effector proteins that may be relevant for BL cell survival and thus may help to develop new BL treatments

Comparative profiling identifies C13orf3 as a component of the Ska complex required for mammalian cell division

Proliferation of mammalian cells requires the coordinated function of many proteins to accurately divide a cell into two daughter cells. Several RNAi screens have identified previously uncharacterised genes that are implicated in mammalian cell division. The molecular function for these genes needs to be investigated to place them into pathways. Phenotypic profiling is a useful method to assign putative functions to uncharacterised genes. Here, we show that the analysis of protein localisation is useful to refine a phenotypic profile. We show the utility of this approach by defining a function of the previously uncharacterised gene C13orf3 during cell division. C13orf3 localises to centrosomes, the mitotic spindle, kinetochores, spindle midzone, and the cleavage furrow during cell division and is specifically phosphorylated during mitosis. Furthermore, C13orf3 is required for centrosome integrity and anaphase onset. Depletion by RNAi leads to mitotic arrest in metaphase with an activation of the spindle assembly checkpoint and loss of sister chromatid cohesion. Proteomic analyses identify C13orf3 (Ska3) as a new component of the Ska complex and show a direct interaction with a regulatory subunit of the protein phosphatase PP2A. All together, these data identify C13orf3 as an important factor for metaphase to anaphase progression and highlight the potential of combined RNAi screening and protein localisation analyses

PhenoFam-gene set enrichment analysis through protein structural information

<p>Abstract</p> <p>Background</p> <p>With the current technological advances in high-throughput biology, the necessity to develop tools that help to analyse the massive amount of data being generated is evident. A powerful method of inspecting large-scale data sets is gene set enrichment analysis (GSEA) and investigation of protein structural features can guide determining the function of individual genes. However, a convenient tool that combines these two features to aid in high-throughput data analysis has not been developed yet. In order to fill this niche, we developed the user-friendly, web-based application, PhenoFam.</p> <p>Results</p> <p>PhenoFam performs gene set enrichment analysis by employing structural and functional information on families of protein domains as annotation terms. Our tool is designed to analyse complete sets of results from quantitative high-throughput studies (gene expression microarrays, functional RNAi screens, <it>etc</it>.) without prior pre-filtering or hits-selection steps. PhenoFam utilizes Ensembl databases to link a list of user-provided identifiers with protein features from the InterPro database, and assesses whether results associated with individual domains differ significantly from the overall population. To demonstrate the utility of PhenoFam we analysed a genome-wide RNA interference screen and discovered a novel function of plexins containing the cytoplasmic RasGAP domain. Furthermore, a PhenoFam analysis of breast cancer gene expression profiles revealed a link between breast carcinoma and altered expression of PX domain containing proteins.</p> <p>Conclusions</p> <p>PhenoFam provides a user-friendly, easily accessible web interface to perform GSEA based on high-throughput data sets and structural-functional protein information, and therefore aids in functional annotation of genes.</p

The Human E3 ligase RNF185 is a regulator of the SARS-CoV-2 envelope protein. Zou et al

Supplementary data sets related to The Human E3 ligase RNF185 is a regulator of the SARS-CoV-2 envelope protein by Zou et al