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

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.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Enzymatically prepared RNAi libraries

Large-scale RNA interference (RNAi) screens in mammalian cells have mainly used synthetic small interfering RNA (siRNA) or short hairpin RNA (shRNA) libraries. The RNAi triggers for both of these approaches were designed with algorithm-based predictions to identify single sequences for mRNA knockdown. Alternatives to these approaches have recently been developed using enzymatic methods. Here we describe the concepts of enzymatically prepared shRNA and siRNA libraries, and discuss their strengths and limitations

Transmission power optimization in live 3GPP LTE-A indoor deployment

As demand for mobile broadband grows, the need for greater indoor coverage and capacity becomes more urgent as the ubiquitous connection to the Internet is mentioned very often. Complementing macro capacity, small cells (femto-, pico-cells) offer a cost-effective way to meet this demand for complex indoor areas. Inspired by this increasing demand, we provide in this paper a comprehensive summary on our live trial of transmission power optimization within the full-featured 3GPP LTE-A indoor deployment. To deliver a comprehensive view on the configuration of TX power, we perform an evaluation between our previous results provided by our implemented PyLTEs software and our optimized configuration. In order to deliver a complete picture, the obtained data from simulator is complemented with the real measurement in LTE-A indoor deployment. Our findings show that performed changes lead to improved of all measured networks parameters as latency, RSRP, RSRQ, and RSSI. On top of this, the discussed changes are not bonded with the particular LTE deployment-therefore, the utilization is not restricted and can be implemented in various indoor LTE deployments. © 2016 IEEE

Transmission power optimization in live 3GPP LTE-A indoor deployment

As demand for mobile broadband grows, the need for greater indoor coverage and capacity becomes more urgent as the ubiquitous connection to the Internet is mentioned very often. Complementing macro capacity, small cells (femto-, pico-cells) offer a cost-effective way to meet this demand for complex indoor areas. Inspired by this increasing demand, we provide in this paper a comprehensive summary on our live trial of transmission power optimization within the full-featured 3GPP LTE-A indoor deployment. To deliver a comprehensive view on the configuration of TX power, we perform an evaluation between our previous results provided by our implemented PyLTEs software and our optimized configuration. In order to deliver a complete picture, the obtained data from simulator is complemented with the real measurement in LTE-A indoor deployment. Our findings show that performed changes lead to improved of all measured networks parameters as latency, RSRP, RSRQ, and RSSI. On top of this, the discussed changes are not bonded with the particular LTE deployment-therefore, the utilization is not restricted and can be implemented in various indoor LTE deployments. © 2016 IEEE

A systematic RNAi synthetic interaction screen reveals a link between p53 and snoRNP assembly.

TP53 (tumour protein 53) is one of the most frequently mutated genes in human cancer and its role during cellular transformation has been studied extensively. However, the homeostatic functions of p53 are less well understood. Here, we explore the molecular dependency network of TP53 through an RNAi-mediated synthetic interaction screen employing two HCT116 isogenic cell lines and a genome-scale endoribonuclease-prepared short interfering RNA library. We identify a variety of TP53 synthetic interactions unmasking the complex connections of p53 to cellular physiology and growth control. Molecular dissection of the TP53 synthetic interaction with UNRIP indicates an enhanced dependency of TP53-negative cells on small nucleolar ribonucleoprotein (snoRNP) assembly. This dependency is mediated by the snoRNP chaperone gene NOLC1 (also known as NOPP140), which we identify as a physiological p53 target gene. This unanticipated function of TP53 in snoRNP assembly highlights the potential of RNAi-mediated synthetic interaction screens to dissect molecular pathways of tumour suppressor genes