SNVDis:A Proteome-wide Analysis Service for Evaluating nsSNVs in Protein Functional Sites and Pathways

Amino acid changes due to non-synonymous variation are included as annotations for individual proteins in UniProtKB/Swiss-Prot and RefSeq which present biological data in a pro- tein- or gene-centric fashion. Unfortunately, proteome-wide analysis of non-synonymous single- nucleotide variations （nsSNVs） is not easy to perform because information on nsSNVs and func- tionally important sites are not well integrated both within and between databases and their search engines. We have developed SNVDis that allows evaluation of proteome-wide nsSNV distribution in functional sites, domains and pathways. More specifically, we have integrated human-specific data from major variation databases （UniProtKB, dbSNP and COSMIC）, comprehensive sequence feature annotation from UniProtKB, Pfam, RefSeq, Conserved Domain Database （CDD） and pathway information from Protein ANalysis THrough Evolutionary Relationships （PANTHER） and mapped all of them in a uniform and comprehensive way to the human reference proteome pro- vided by UniProtKB/Swiss-Prot. Integrated information of active sites, pathways, binding sites, domains, which are extracted from a number of different sources, provides a detailed overview of how nsSNVs are distributed over the human proteome and pathways and how they intersect with functional sites of proteins. Additionally, it is possible to find out whether there is an over- or under-representation of nsSNVs in specific domains, pathways or user-defined protein lists. The underlying datasets are updated once every 3 months. SNVDis is freely available at http：//hive.bio- chemistry.gwu.edu/tool/snvdis.

A strategy for uncovering germline variants altering anti-tumor CD8 T cell response

Among many factors known to alter the outcomes of T cell receptor(TCR)-induced proximal signaling,the role of human germline variants in dictating the individuality of the anti-tumor CD8 T cell response has remained challenging to address.Here,we describe a convenient strategy for molecular and functional characterization of phosphotyrosine-altering non-synonymous single nucleotide variations(pTyr-SNVs)that directly impact TCR-induced proximal phosphotyrosine motif-based signaling pathways.We devise an experimental co-cultivation set-up comprising a C57BL/6 mouse-derived metastatic melanoma cell line engineered to constitutively present ovalbumin(OVA)antigens and retrovirally engineered syngeneic major histocompatibility complex(MHC)Class I restricted OVA TCR-transgenic CD8 T cells(OT-I).Using the synthetic version of pTyr-SNV rs1178800678-G/T-encoding integrin alpha 4(ITGA4)p.S1027I variant as a prototype,we show that under identical TCR stimulation conditions,genetically determined membrane-proximal immunoreceptor tyrosin activation motif(ITAM)results in increased tyrosine phosphorylation of 70 kDa zeta-chain-associated protein(ZAP70)and the levels of cytotoxic effector molecule granzyme B(GZMB),which in turn result in enhanced cytotoxic activity against metastatic melanoma cell line.This strategy paves the way for rapid molecular and functional characterization of anti-tumor immune response-linked germline pTyr-SNVs so as to improve our understanding of the genetic basis of individual-to-individual differences in anti-tumor CD8 T cell response.

Structure-based Comparative Analysis and Prediction of N-linked Glycosylation Sites in Evolutionarily Distant Eukaryotes

The asparagine-X-serine/threonine （NXS/T） motif, where X is any amino acid except proline, is the consensus motif for N-linked glycosylation. Significant numbers of high-resolution crystal structures of glycosylated proteins allow us to carry out structural analysis of the N-linked glycosylation sites （NGS）. Our analysis shows that there is enough structural information from diverse glycoproteins to allow the development of rules which can be used to predict NGS. A Python-based tool was developed to investigate asparagines implicated in N-glycosylation in five species： Homo sapiens, Mus musculus, Drosophila melanogaster, Arabidopsis thaliana and Saccharo- myees cerevisiae. Our analysis shows that 78 % of all asparagines of NXS/T motif involved in N-gly- cosylation are localized in the loop/turn conformation in the human proteome. Similar distribution was revealed for all the other species examined. Comparative analysis of the occurrence of NXS/T motifs not known to be glycosylated and their reverse sequence （S/TXN） shows a similar distribu- tion across the secondary structural elements, indicating that the NXS/T motif in itself is not bio- logically relevant. Based on our analysis, we have defined rules to determine NGS. Using machine learning methods based on these rules we can predict with 93% accuracy if a particular site will be glycosylated. If structural information is not available the tool uses structural prediction results resulting in 74% accuracy. The tool was used to identify glycosylation sites in 108 human proteins with structures and 2247 proteins without structures that have acquired NXS/T site/s due to non-synonymous variation. The tool, Structure Feature Analysis Tool （SFAT）, is freely available to the public at http：//hive.biochemistry.gwu.edu/tools/sfat.