Structure-based pathogenicity relationship identifier for predicting effects of single missense variants and discovery of higher-order cancer susceptibility clusters of mutations.

We report the structure-based pathogenicity relationship identifier (SPRI), a novel computational tool for accurate evaluation of pathological effects of missense single mutations and prediction of higher-order spatially organized units of mutational clusters. SPRI can effectively extract properties determining pathogenicity encoded in protein structures, and can identify deleterious missense mutations of germ line origin associated with Mendelian diseases, as well as mutations of somatic origin associated with cancer drivers. It compares favorably to other methods in predicting deleterious mutations. Furthermore, SPRI can discover spatially organized pathogenic higher-order spatial clusters (patHOS) of deleterious mutations, including those of low recurrence, and can be used for discovery of candidate cancer driver genes and driver mutations. We further demonstrate that SPRI can take advantage of AlphaFold2 predicted structures and can be deployed for saturation mutation analysis of the whole human proteome.

Structural and functional insights into ABHD5, a ligand-regulated lipase co-activator.

Alpha/beta hydrolase domain-containing protein 5 (ABHD5) is a highly conserved protein that regulates various lipid metabolic pathways via interactions with members of the perilipin (PLIN) and Patatin-like phospholipase domain-containing protein (PNPLA) protein families. Loss of function mutations in ABHD5 result in Chanarin-Dorfman Syndrome (CDS), characterized by ectopic lipid accumulation in numerous cell types and severe ichthyosis. Recent data demonstrates that ABHD5 is the target of synthetic and endogenous ligands that might be therapeutic beneficial for treating metabolic diseases and cancers. However, the structural basis of ABHD5 functional activities, such as protein-protein interactions and ligand binding is presently unknown. To address this gap, we constructed theoretical structural models of ABHD5 by comparative modeling and topological shape analysis to assess the spatial patterns of ABHD5 conformations computed in protein dynamics. We identified functionally important residues on ABHD5 surface for lipolysis activation by PNPLA2, lipid droplet targeting and PLIN-binding. We validated the computational model by examining the effects of mutating key residues in ABHD5 on an array of functional assays. Our integrated computational and experimental findings provide new insights into the structural basis of the diverse functions of ABHD5 as well as pathological mutations that result in CDS.

Cancer DEIso: An integrative analysis platform for investigating differentially expressed gene-level and isoform-level human cancer markers.

Transcript isoforms regulated by alternative splicing can substantially impact carcinogenesis, leading to a need to obtain clues for both gene differential expression and malfunctions of isoform distributions in cancer studies. The Cancer Genome Atlas (TCGA) project was launched in 2008 to collect cancer-related genome mutation raw data from the population. While many repositories tried to add insights into the raw data in TCGA, no existing database provides both comprehensive gene-level and isoform-level cancer stage marker investigation and survival analysis. We constructed Cancer DEIso to facilitate in-depth analyses for both gene-level and isoform-level human cancer studies. Patient RNA-seq data, sample sheets, patient clinical data, and human genome datasets were collected and processed in Cancer DEIso. And four functions to search differentially expressed genes/isoforms between cancer stages were implemented: (i) Search potential gene/isoform markers for a specified cancer type and its two stages; (ii) Search potentially induced cancer types and stages for a gene/isoform; (iii) Expression survival analysis on a given gene/isoform for some cancer; (iv) Gene/isoform stage expression comparison visualization. As an example, we demonstrate that Cancer DEIso can indicate potential colorectal cancer isoform diagnostic markers that are not easily detected when only gene-level expressions are considered. Cancer DEIso is available at http://cosbi4.ee.ncku.edu.tw/DEIso/.

Predicting Oncogenic Missense Mutations.

With the rapid progress of cancer genome studies, many missense mutations in populations of somatic cells of different cancer types and at different stages have been identified. However, it is challenging to understand the implications of these cancer-related variants. We have developed a computational method that integrates structural, topographical, and evolutionary information for assessments of biochemical effects and the extent of deleteriousness of the cancer-related variants. We have mapped somatic missense mutations from the Catalogue of Somatic Mutations In Cancer (COSMIC) to 3D structures in the Protein Data Bank (PDB). Our results show that a large portion of these missense mutations is located on protein surface pockets, which often serve as a structural and functional unit of cancer variants. We provide detailed analysis of several examples and assessment on the importance of these variants, including prediction of previously unreported cancer-variants, along with independent evidence from the literature. Furthermore, we show our predictions can inform on the functional roles and the mechanism of predicted cancer variants.

HRPDviewer: human ribosome profiling data viewer.

Translational regulation plays an important role in protein synthesis. Dysregulation of translation causes abnormal cell physiology and leads to diseases such as inflammatory disorders and cancers. An emerging technique, called ribosome profiling (ribo-seq), was developed to capture a snapshot of translation. It is based on deep sequencing of ribosome-protected mRNA fragments. A lot of ribo-seq data have been generated in various studies, so databases are needed for depositing and visualizing the published ribo-seq data. Nowadays, GWIPS-viz, RPFdb and TranslatomeDB are the three largest databases developed for this purpose. However, two challenges remain to be addressed. First, GWIPS-viz and RPFdb databases align the published ribo-seq data to the genome. Since ribo-seq data aim to reveal the actively translated mRNA transcripts, there are advantages of aligning ribo-req data to the transcriptome over the genome. Second, TranslatomeDB does not provide any visualization and the other two databases only provide visualization of the ribo-seq data around a specific genomic location, while simultaneous visualization of the ribo-seq data on multiple mRNA transcripts produced from the same gene or different genes is desired. To address these two challenges, we developed the Human Ribosome Profiling Data viewer (HRPDviewer). HRPDviewer (i) contains 610 published human ribo-seq datasets from Gene Expression Omnibus, (ii) aligns the ribo-seq data to the transcriptome and (iii) provides visualization of the ribo-seq data on the selected mRNA transcripts. Using HRPDviewer, researchers can compare the ribosome binding patterns of multiple mRNA transcripts from the same gene or different genes to gain an accurate understanding of protein synthesis in human cells. We believe that HRPDviewer is a useful resource for researchers to study translational regulation in human.Database URL: http://cosbi4.ee.ncku.edu.tw/HRPDviewer/ or http://cosbi5.ee.ncku.edu.tw/HRPDviewer/.

YARG: A repository for arsenic-related genes in yeast.

Arsenic is a toxic metalloid. Moderate levels of arsenic exposure from drinking water can cause various human health problems such as skin lesions, circulatory disorders and cancers. Thus, arsenic toxicity is a key focus area for environmental and toxicological investigations. Many arsenic-related genes in yeast have been identified by experimental strategies such as phenotypic screening and transcriptional profiling. These identified arsenic-related genes are valuable information for studying arsenic toxicity. However, the literature about these identified arsenic-related genes is widely dispersed and cannot be easily acquired by researchers. This prompts us to develop YARG (Yeast Arsenic-Related Genes) database, which comprehensively collects 3396 arsenic-related genes in the literature. For each arsenic-related gene, the number and types of experimental evidence (phenotypic screening and/or transcriptional profiling) are provided. Users can use both search and browse modes to query arsenic-related genes in YARG. We used two case studies to show that YARG can return biologically meaningful arsenic-related information for the query gene(s). We believe that YARG is a useful resource for arsenic toxicity research. YARG is available at http://cosbi4.ee.ncku.edu.tw/YARG/.

SM22α suppresses cytokine-induced inflammation and the transcription of NF-κB inducing kinase (Nik) by modulating SRF transcriptional activity in vascular smooth muscle cells.

Vascular smooth muscle cell (VSMC) phenotypic modulation is characterized by the downregulation of SMC actin cytoskeleton proteins. Our published study shows that depletion of SM22α (aka SM22, Transgelin, an actin cytoskeleton binding protein) promotes inflammation in SMCs by activating NF-κB signal pathways both in cultured VSMCs and in response to vascular injury. The goal of this study is to investigate the underlying molecular mechanisms whereby SM22 suppresses NF-κB signaling pathways under inflammatory condition. NF-κB inducing kinase (Nik, aka MAP3K14, activated by the LTßR) is a key upstream regulator of NF-κB signal pathways. Here, we show that SM22 overexpression suppresses the expression of NIK and its downstream NF-κB canonical and noncanonical signal pathways in a VSMC line treated with a LTßR agonist. SM22 regulates NIK expression at both transcriptional and the proteasome-mediated post-translational levels in VSMCs depending on the culture condition. By qPCR, chromatin immunoprecipitation and luciferase assays, we found that Nik is a transcription target of serum response factor (SRF). Although SM22 is known to be expressed in the cytoplasm, we found that SM22 is also expressed in the nucleus where SM22 interacts with SRF to inhibit the transcription of Nik and prototypical SRF regulated genes including c-fos and Egr3. Moreover, carotid injury increases NIK expression in Sm22-/- mice, which is partially relieved by adenovirally transduced SM22. These findings reveal for the first time that SM22 is expressed in the nucleus in addition to the cytoplasm of VSMCs to regulate the transcription of Nik and its downstream proinflammatory NF-kB signal pathways as a modulator of SRF during vascular inflammation.

Molecular Basis of ABHD5 Lipolysis Activation.

Alpha-beta hydrolase domain-containing 5 (ABHD5), the defective gene in human Chanarin-Dorfman syndrome, is a highly conserved regulator of adipose triglyceride lipase (ATGL)-mediated lipolysis that plays important roles in metabolism, tumor progression, viral replication, and skin barrier formation. The structural determinants of ABHD5 lipolysis activation, however, are unknown. We performed comparative evolutionary analysis and structural modeling of ABHD5 and ABHD4, a functionally distinct paralog that diverged from ABHD5 ~500 million years ago, to identify determinants of ABHD5 lipolysis activation. Two highly conserved ABHD5 amino acids (R299 and G328) enabled ABHD4 (ABHD4 N303R/S332G) to activate ATGL in Cos7 cells, brown adipocytes, and artificial lipid droplets. The corresponding ABHD5 mutations (ABHD5 R299N and ABHD5 G328S) selectively disrupted lipolysis without affecting ATGL lipid droplet translocation or ABHD5 interactions with perilipin proteins and ABHD5 ligands, demonstrating that ABHD5 lipase activation could be dissociated from its other functions. Structural modeling placed ABHD5 R299/G328 and R303/G332 from gain-of-function ABHD4 in close proximity on the ABHD protein surface, indicating they form part of a novel functional surface required for lipase activation. These data demonstrate distinct ABHD5 functional properties and provide new insights into the functional evolution of ABHD family members and the structural basis of lipase regulation.