Veneer is a webtool for rapid, standardized, and transparent interpretation, annotation, and reporting of mammalian cell surface glycoprotein capture data
Ontology highlight
ABSTRACT:
INSTRUMENT(S): Orbitrap Exploris 480
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Rebekah Gundry
PROVIDER: MSV000093424 | MassIVE | Fri Nov 17 11:18:00 GMT 2023
REPOSITORIES: MassIVE
Similar Datasets
Project description:Microscale cell surface capture of human cardiac cells and a B cell line.
2021-12-29 | MSV000088624 | MassIVE
Project description:uCSC data of B cells with and without PNGaseF; 4 PNGaseF vendor injections
2024-01-19 | MSV000093894 | MassIVE
Project description:Currently, no consensus exists regarding criteria required to designate a protein within a proteomic data set as a cell surface protein. Most published proteomic studies rely on varied ontology annotations or computational predictions instead of experimental evidence when attributing protein localization. Consequently, standardized approaches for analyzing and reporting cell surface proteome data sets would increase confidence in localization claims and promote data use by other researchers. Recently, we developed Veneer, a web-based bioinformatic tool that analyzes results from cell surface N-glycocapture workflows─the most popular cell surface proteomics method used to date that generates experimental evidence of subcellular location. Veneer assigns protein localization based on defined experimental and bioinformatic evidence. In this study, we updated the criteria and process for assigning protein localization and added new functionality to Veneer. Results of Veneer analysis of 587 cell surface N-glycocapture data sets from 32 published studies demonstrate the importance of applying defined criteria when analyzing cell surface proteomics data sets and exemplify how Veneer can be used to assess experimental quality and facilitate data extraction for informing future biological studies and annotating public repositories.
| S-EPMC11301670 | biostudies-literature
Project description:A detergents assisted glycoprotein capture method was developed to increase the coverage of N-glycoproteome of various samples.Application of this approach in the larger scale N-glycoproteomics analysis of the HEK 293 cell membrane led to the identification of 2253 unique N-glycosites from 953 proteins. Application of this approach to human serum resulted in the identification of 850 N-glycosylation sites without any immuno-depletion and fractionation.
2016-12-23 | PXD003485 | Pride
Project description:BackgroundThe development of novel targeted cancer therapies and/or diagnostic tools is dependent upon an understanding of the differential expression of molecular targets between normal tissues and tumors. Many of these potential targets are cell-surface receptors; however, our knowledge of the cell-surface proteins upregulated in pancreatic tumors is limited, thus impeding the development of targeted therapies for pancreatic cancer. To develop new diagnostic and therapeutic tools to specifically target pancreatic tumors, we sought to identify cell-surface proteins that may serve as potential tumor-specfic targets.MethodsMembrane glycoproteins on the pancreatic cancer cell lines BxPC-3 were labeled with the bifunctional linker biocytin hydrazide. Following proteolytic digestion, biotinylated glycopeptides were captured with streptavidin-coupled beads then released by PNGaseF-mediated endoglycosidase cleavage and identified by liquid chromatography-tandem mass spectrometry (MS). A protein identified by the cell-surface glycoprotein capture procedure, CD109, was evaluated by western analysis of lysates of pancreatic cancer cell lines and by immunohistochemistry in sections of pancreatic ductal adenocarcinoma and non- neoplastic pancreatic tissues.ResultsMS/MS analysis of glycopeptides captured from BxPC-3 cells revealed 18 proteins predicted or known to be associated with the plasma membrane, including CD109, which has not been reported in pancreatic cancer. Western analysis of CD109 in lysates prepared from pancreatic cancer cell lines revealed it was expressed in 6 of 8 cell lines, with a high level of expression in BxPC-3, MIAPaCa-2, and Panc-1 cells. Immunohistochemical analyses of human pancreatic tissues indicate CD109 is significantly overexpressed in pancreatic tumors compared to normal pancreas.ConclusionsThe selective capture of glycopeptides from the surface of pancreatic cancer cell lines can reveal novel cell-surface glycoproteins expressed in pancreatic ductal adenocarcinomas.
| S-EPMC4307595 | biostudies-literature
Project description:Command-line annotation software tools have continuously gained popularity compared to centralized online services due to the worldwide increase of sequenced bacterial genomes. However, results of existing command-line software pipelines heavily depend on taxon-specific databases or sufficiently well annotated reference genomes. Here, we introduce Bakta, a new command-line software tool for the robust, taxon-independent, thorough and, nonetheless, fast annotation of bacterial genomes. Bakta conducts a comprehensive annotation workflow including the detection of small proteins taking into account replicon metadata. The annotation of coding sequences is accelerated via an alignment-free sequence identification approach that in addition facilitates the precise assignment of public database cross-references. Annotation results are exported in GFF3 and International Nucleotide Sequence Database Collaboration (INSDC)-compliant flat files, as well as comprehensive JSON files, facilitating automated downstream analysis. We compared Bakta to other rapid contemporary command-line annotation software tools in both targeted and taxonomically broad benchmarks including isolates and metagenomic-assembled genomes. We demonstrated that Bakta outperforms other tools in terms of functional annotations, the assignment of functional categories and database cross-references, whilst providing comparable wall-clock runtimes. Bakta is implemented in Python 3 and runs on MacOS and Linux systems. It is freely available under a GPLv3 license at https://github.com/oschwengers/bakta. An accompanying web version is available at https://bakta.computational.bio.
| S-EPMC8743544 | biostudies-literature
Project description:Detailed knowledge of cell surface proteins for isolating well-defined populations of human pluripotent stem cells (hPSCs) would significantly enhance their characterization and translational potential. Normal H9 human embryonic stem cells and the KB3 human induced pluripotent stem cell lines were analyzed by Cell Surface Capture Technology, and in parallel transcript profiles from five independent samples (i.e., Replicas 1-5 for each) were performed to facilitate protein and transcriptomic comparisons. The study compared gene expression profiles of pluripotent stem cells with Cell Surface Capture technology generated N-glycoprotein surfaceome analyses of the same cell types.
2014-03-12 | E-GEOD-55805 | biostudies-arrayexpress
Project description:Detailed knowledge of cell surface proteins for isolating well-defined populations of human pluripotent stem cells (hPSCs) would significantly enhance their characterization and translational potential. Normal H9 human embryonic stem cells and the KB3 human induced pluripotent stem cell lines were analyzed by Cell Surface Capture Technology, and in parallel transcript profiles from five independent samples (i.e., Replicas 1-5 for each) were performed to facilitate protein and transcriptomic comparisons.
2014-03-12 | GSE55805 | GEO
Project description:The SARS-CoV-2 spike protein is a critical component of vaccines and a target for neutralizing monoclonal antibodies (nAbs). Spike is also undergoing immunogenic selection with variants that increase infectivity and partially escape convalescent plasma. Here, we describe Spike Display, a high-throughput platform to rapidly characterize glycosylated spike ectodomains across multiple coronavirus-family proteins. We assayed ∼200 variant SARS-CoV-2 spikes for their expression, ACE2 binding, and recognition by 13 nAbs. An alanine scan of all five N-terminal domain (NTD) loops highlights a public epitope in the N1, N3, and N5 loops recognized by most NTD-binding nAbs. NTD mutations in variants of concern B.1.1.7 (alpha), B.1.351 (beta), B.1.1.28 (gamma), B.1.427/B.1.429 (epsilon), and B.1.617.2 (delta) impact spike expression and escape most NTD-targeting nAbs. Finally, B.1.351 and B.1.1.28 completely escape a potent ACE2 mimic. We anticipate that Spike Display will accelerate antigen design, deep scanning mutagenesis, and antibody epitope mapping for SARS-CoV-2 and other emerging viral threats.
| S-EPMC8675084 | biostudies-literature
Project description:Trypanosoma brucei Lister 427 bloodstream forms were cultured in HMI-11 medium. Total RNA was prepared using Qiagen RNAeasy kits for single sample RNAseq to estimate VSG mRNA abundance (and not to reconstruct the transcriptome). The cDNA libraries were prepared and sequenced at the Beijing Genomics Institute (Shenzhen, China). Polyadenylated RNA was purified from total RNA, converted to cDNA using random hexamer primers sheared and size selected for fragments ~200 bp in length using the Illumina TruSeq RNA Sample Preparation Kit v2. RNAseq of the resulting libraries was used for the determination of transcript abundances. Sequencing was performed on an Illumina Hiseq 2000 (Illumina, CA) platform and 90 base paired end reads obtained. Four samples were analysed: 1. Trypanosoma brucei Lister 427 expressing VSG2 2. Trypanosoma brucei Lister 427 expressing VSG6 3. Trypanosoma brucei Lister 427 expressing VSG6 and a VSG2 transgender located in the active bloodstream expression site 28 days after electroporation 4. Trypanosoma brucei Lister 427 expressing VSG6 and a VSG2 transgender located in the active bloodstream expression site 44 days after electroporation.
2020-06-03 | E-MTAB-9122 | biostudies-arrayexpress