Search

Background The clinical heterogeneity of SLE with its complex pathogenesis remains challenging as we strive to provide optimal management. The contribution of platelets to endovascular homeostasis, inflammation and immune regulation highlights their potential importance in SLE. Prior work from our group showed that the Fcγ receptor type IIa (FcγRIIa)–R/H131 biallelic polymorphism is associated with increased platelet activity and cardiovascular risk in SLE. The study was initiated to investigate the platelet transcriptome in patients with SLE and evaluate its association across FcγRIIa genotypes and distinct clinical features. Methods Fifty-one patients fulfilling established criteria for SLE (mean age = 41.1 ± 12.3, 100% female, 45% Hispanic, 24% black, 22% Asian, 51% white, mean SLEDAI = 4.4 ± 4.2 at baseline) were enrolled and compared with 18 demographically matched control samples. The FCGR2a receptor was genotyped for each sample, and RNA-seq was performed on isolated, leukocyte-depleted platelets. Transcriptomic data were used to create a modular landscape to explore the differences between SLE patients and controls and various clinical parameters in the context of FCGR2a genotypes. Results There were 2290 differentially expressed genes enriched for pathways involved in interferon signaling, immune activation, and coagulation when comparing SLE samples vs controls. When analyzing patients with proteinuria, modules associated with oxidative phosphorylation and platelet activity were unexpectedly decreased. Furthermore, genes that were increased in SLE and in patients with proteinuria were enriched for immune effector processes, while genes increased in SLE but decreased in proteinuria were enriched for coagulation and cell adhesion. A low-binding FCG2Ra allele (R131) was associated with decreases in FCR activation, which further correlated with increases in platelet and immune activation pathways. Finally, we were able to create a transcriptomic signature of clinically active disease that performed significantly well in discerning SLE patients with active clinical disease form those with inactive clinical disease. Conclusions In aggregate, these data demonstrate the platelet transcriptome provides insight into lupus pathogenesis and disease activity, and shows potential use as means of assessing this complex disease using a liquid biopsy.

Advances in mass-spectrometry have generated increasingly large-scale proteomics datasets containing tens of thousands of phosphorylation sites (phosphosites) that require prioritization. We develop a bioinformatics tool called HotPho and systematically discover 3D co-clustering of phosphosites and cancer mutations on protein structures. HotPho identifies 474 such hybrid clusters containing 1255 co-clustering phosphosites, including RET p.S904/Y928, the conserved HRAS/KRAS p.Y96, and IDH1 p.Y139/IDH2 p.Y179 that are adjacent to recurrent mutations on protein structures not found by linear proximity approaches. Hybrid clusters, enriched in histone and kinase domains, frequently include expression-associated mutations experimentally shown as activating and conferring genetic dependency. Approximately 300 co-clustering phosphosites are verified in patient samples of 5 cancer types or previously implicated in cancer, including CTNNB1 p.S29/Y30, EGFR p.S720, MAPK1 p.S142, and PTPN12 p.S275. In summary, systematic 3D clustering analysis highlights nearly 3,000 likely functional mutations and over 1000 cancer phosphosites for downstream investigation and evaluation of potential clinical relevance., Dysregulated phosphorylation is well-known in cancers, but it has largely been studied in isolation from mutations. Here the authors introduce HotPho, a tool that can discover spatial interactions between phosphosites and mutations, which are associated with activating mutation and genetic dependencies in cancer.

Translation initiation of most mammalian mRNAs is mediated by a 5′ cap structure that binds eukaryotic initiation factor 4E (eIF4E). However, inactivation of eIF4E does not impair translation of many capped mRNAs, suggesting an unknown alternate mechanism may exist for cap-dependent but eIF4E-independent translation. We show that DAP5, an eIF4GI homolog that lacks eIF4E binding, utilizes eIF3d to facilitate cap-dependent translation of approximately 20% of mRNAs. Genome-wide transcriptomic and translatomic analyses indicate that DAP5 is required for translation of many transcription factors and receptor capped mRNAs and their mRNA targets involved in cell survival, motility, DNA repair and translation initiation, among other mRNAs. Mass spectrometry and crosslinking studies demonstrate that eIF3d is a direct binding partner of DAP5. In vitro translation and ribosome complex studies demonstrate that DAP5 and eIF3d are both essential for eIF4E-independent capped-mRNA translation. These studies disclose a widespread and previously unknown mechanism for cap-dependent mRNA translation by DAP5-eIF3d complexes., Binding of eIF4E to the 5′ cap of mRNAs is a key early step in canonical translation initiation, but the requirement for eIF4E is not universal. Here the authors show that the eIF4G homolog DAP5 interacts with eIF3 to promote cap-dependent translation of a significant number of mRNA in an eIF4E-independent manner.

Background Exploration of large data sets, such as shotgun metagenomic sequence or expression data, by biomedical experts and medical professionals remains as a major bottleneck in the scientific discovery process. Although tools for this purpose exist for 16S ribosomal RNA sequencing analysis, there is a growing but still insufficient number of user-friendly interactive visualization workflows for easy data exploration and figure generation. The development of such platforms for this purpose is necessary to accelerate and streamline microbiome laboratory research. Results We developed the Workflow Hub for Automated Metagenomic Exploration (WHAM!) as a web-based interactive tool capable of user-directed data visualization and statistical analysis of annotated shotgun metagenomic and metatranscriptomic data sets. WHAM! includes exploratory and hypothesis-based gene and taxa search modules for visualizing differences in microbial taxa and gene family expression across experimental groups, and for creating publication quality figures without the need for command line interface or in-house bioinformatics. Conclusions WHAM! is an interactive and customizable tool for downstream metagenomic and metatranscriptomic analysis providing a user-friendly interface allowing for easy data exploration by microbiome and ecological experts to facilitate discovery in multi-dimensional and large-scale data sets. Electronic supplementary material The online version of this article (10.1186/s12864-018-4870-z) contains supplementary material, which is available to authorized users.

To address these issues, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) of the National Cancer Institute (NCI) has launched an Assay Portal (http://assays.cancer.gov) to serve as a public repository of well-characterized quantitative, MS-based, targeted proteomic assays. The purpose of the CPTAC Assay Portal is to facilitate widespread adoption of targeted MS assays by disseminating SOPs, reagents, and assay characterization data for highly characterized assays. A primary aim of the NCI-supported portal is to bring together clinicians or biologists and analytical chemists to answer hypothesis-driven questions using targeted, MS-based assays. Assay content is easily accessed through queries and filters, enabling investigators to find assays to proteins relevant to their areas of interest. Detailed characterization data are available for each assay, enabling researchers to evaluate assay performance prior to launching the assay in their own laboratory.