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Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics.

ABSTRACT: We introduce STAMPS, a pathway-centric web service for the development of targeted proteomics assays. STAMPS guides the user by providing several intuitive interfaces for a rapid and simplified method design. Applying our curated framework to signaling and metabolic pathways, we reduced the average assay development time by a factor of ?150 and revealed that the insulin signaling is actively controlled by protein abundance changes in insulin-sensitive and -resistance states. Although at the current state STAMPS primarily contains mouse data, it was designed for easy extension with additional organisms.

SUBMITTER: Kopczynski D

PROVIDER: S-EPMC7586293 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Simple Targeted Assays for Metabolic Pathways and Signaling: A Powerful Tool for Targeted Proteomics.

Kopczynski Dominik D Hentschel Andreas A Coman Cristina C Schebb Nils Helge NH Hornemann Thorsten T Mashek Douglas G DG Hartung Nicole M NM Shevchuk Olga O Schött Hans-Frieder HF Lorenz Kristina K Torta Federico F Burla Bo B Zahedi René P RP Sickmann Albert A Kreutz Michael R MR Ejsing Christer S CS Medenbach Jan J Ahrends Robert R

Analytical chemistry 20200921 20

We introduce STAMPS, a pathway-centric web service for the development of targeted proteomics assays. STAMPS guides the user by providing several intuitive interfaces for a rapid and simplified method design. Applying our curated framework to signaling and metabolic pathways, we reduced the average assay development time by a factor of ∼150 and revealed that the insulin signaling is actively controlled by protein abundance changes in insulin-sensitive and -resistance states. Although at the curr ...[more]

PMID: 32865986

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Simple targeted assays for metabolic pathways and signaling: a powerful tool for targeted proteomics

Project description:We introduce STAMPS, a pathway centric web service for the development of targeted proteomics assays. STAMPS guides the user by providing several intuitive interfaces for a rapid and simplified method design. Applying our curated framework to signaling and metabolic pathways, we reduced average assay development time by a factor of ~150 and revealed that the insulin signaling is actively controlled by protein abundance changes in insulin sensitive and resistance states.

2021-03-22 | PXD013343 | Pride

VaRank: a simple and powerful tool for ranking genetic variants.

Project description:Background. Most genetic disorders are caused by single nucleotide variations (SNVs) or small insertion/deletions (indels). High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians. Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status) in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients. Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

| S-EPMC4358652 | biostudies-literature

Cnidarian Cell Cryopreservation: A Powerful Tool for Cultivation and Functional Assays.

Project description:Cnidarian primary cell cultures have a strong potential to become a universal tool to assess stress-response mechanisms at the cellular level. However, primary cell cultures are time-consuming regarding their establishment and maintenance. Cryopreservation is a commonly used approach to provide stable cell stocks for experiments, but it is yet to be established for Cnidarian cell cultures. The aim of this study was therefore to design a cryopreservation protocol for primary cell cultures of the Cnidarian Anemonia viridis, using dimethyl sulfoxide (DMSO) as a cryoprotectant, enriched or not with fetal bovine serum (FBS). We determined that DMSO 5% with 25% FBS was an efficient cryosolution, resulting in 70% of post-thaw cell survival. The success of this protocol was first confirmed by a constant post-thaw survival independently of the cell culture age (up to 45 days old) and the storage period (up to 87 days). Finally, cryopreserved cells displayed a long-term recovery with a maintenance of the primary cell culture parameters and cellular functions: formation of cell aggregates, high viability and constant cell growth, and unchanged intrinsic resistance to hyperthermal stress. These results will further bring new opportunities for the scientific community interested in molecular, cellular, and biochemical aspects of cnidarian biology.

| S-EPMC7761476 | biostudies-literature

MRMAssayDB: an integrated resource for validated targeted proteomics assays.

Project description:MotivationMultiple Reaction Monitoring (MRM)-based targeted proteomics is increasingly being used to study the molecular basis of disease. When combined with an internal standard, MRM allows absolute quantification of proteins in virtually any type of sample but the development and validation of an MRM assay for a specific protein is laborious. Therefore, several public repositories now host targeted proteomics MRM assays, including NCI's Clinical Proteomic Tumor Analysis Consortium assay portals, PeptideAtlas SRM Experiment Library, SRMAtlas, PanoramaWeb and PeptideTracker, with all of which contain different levels of information.ResultsHere we present MRMAssayDB, a web-based application that integrates these repositories into a single resource. MRMAssayDB maps and links the targeted assays, annotates the proteins with information from UniProtKB, KEGG pathways and Gene Ontologies, and provides several visualization options on the peptide and protein level. Currently MRMAssayDB contains >168K assays covering more than 34K proteins from 63 organisms; >13.5K of these proteins are present in >2.3K KEGG biological pathways corresponding to >300 master pathways, and mapping to >13K GO biological processes. MRMAssayDB allows comprehensive searches for a targeted-proteomics assay depending on the user's interests, by using target-protein name or accession number, or using annotations such as subcellular localization, biological pathway, or disease or drug associations. The user can see how many data repositories include a specific peptide assay, and the commonly used transitions for each peptide in all empirical data from the repositories.Availability and implementationhttp://mrmassaydb.proteincentre.com.Supplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC6184479 | biostudies-literature

A Simple Light Isotope Metabolic Labeling (SLIM-labeling) Strategy: A Powerful Tool to Address the Dynamics of Proteome Variations In Vivo.

Project description:Many quantitative proteomics strategies rely on in vivo metabolic incorporation of amino acids with modified stable isotope profiles into proteins. These methods give rise to multiple ions for each peptide, with possible distortion of the isotopolog distribution, making the overall analytical process complex. We validated an alternative strategy, simple light isotope metabolic labeling (SLIM-labeling), which alleviates many of these problems. SLIM-labeling is based on the in vivo reduction of the isotopic composition of proteins using metabolic precursors with a unique light isotope composition to label all amino acids. This brings a new dimension to in-depth, high resolution MS-based quantitative proteomics. Here, we describe a 12C-based SLIM-labeling strategy using U-[12C]-glucose as the metabolic precursor of all amino acids in the pathogenic yeast Candida albicans Monoisotopic ion intensity increased exponentially following 12C enrichment, substantially improving peptide identification scores and protein sequence coverage in bottom-up analyses. Multiplexing samples of 12C composition varying from natural abundance (98.93%) to 100% makes it possible to address relative quantification issues, keeping all the critical information for each peptide within a single isotopolog cluster. We applied this method to measure, for the first time, protein turnover at the proteome scale in Candida albicans and its modulation by inhibitors of the proteasome and vacuolar protein degradation systems.

| S-EPMC5672006 | biostudies-literature

BRED: a simple and powerful tool for constructing mutant and recombinant bacteriophage genomes.

Project description:Advances in DNA sequencing technology have facilitated the determination of hundreds of complete genome sequences both for bacteria and their bacteriophages. Some of these bacteria have well-developed and facile genetic systems for constructing mutants to determine gene function, and recombineering is a particularly effective tool. However, generally applicable methods for constructing defined mutants of bacteriophages are poorly developed, in part because of the inability to use selectable markers such as drug resistance genes during viral lytic growth. Here we describe a method for simple and effective directed mutagenesis of bacteriophage genomes using Bacteriophage Recombineering of Electroporated DNA (BRED), in which a highly efficient recombineering system is utilized directly on electroporated phage DNA; no selection is required and mutants can be readily detected by PCR. We describe the use of BRED to construct unmarked gene deletions, in-frame internal deletions, base substitutions, precise gene replacements, and the addition of gene tags.

| S-EPMC2597740 | biostudies-literature

Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia.

Project description:OBJECTIVE:Previous gene expression analysis identified a network of coexpressed genes that is associated with β-amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. METHODS:Data came from 834 community-based older persons who were followed annually, died, and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of β-amyloid and other common age-related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with β-amyloid load and other neuropathological indices as well as cognitive decline over multiple years preceding death. RESULTS:Average age at death was 88.6 years. Overall, 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more β-amyloid load (p = 1.0 × 10-7 ) and higher PHFtau tangle density (p = 2.3 × 10-7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, and AK4 and lower ITPK1 levels were associated with faster cognitive decline, and, unlike PLXNB1, these associations were not fully explained by common neuropathological indices, suggesting novel mechanisms leading to cognitive decline. INTERPRETATION:Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting β-amyloid deposition and another affecting resilience without a known pathological footprint. Ann Neurol 2018;83:78-88.

| S-EPMC6119500 | biostudies-literature

Arcadia: a visualization tool for metabolic pathways.

Project description:SummaryArcadia translates text-based descriptions of biological networks (SBML files) into standardized diagrams (SBGN PD maps). Users can view the same model from different perspectives and easily alter the layout to emulate traditional textbook representations.Availability and implementationArcadia is written in C++. The source code is available (along with Mac OS and Windows binaries) under the GPL from http://arcadiapathways.sourceforge.net/.

| S-EPMC2872004 | biostudies-literature

DrGaP: a powerful tool for identifying driver genes and pathways in cancer sequencing studies.

Project description:Cancers are caused by the accumulation of genomic alterations. Driver mutations are required for the cancer phenotype, whereas passenger mutations are irrelevant to tumor development and accumulate through DNA replication. A major challenge facing the field of cancer genome sequencing is to identify cancer-associated genes with mutations that drive the cancer phenotype. Here, we describe a powerful and flexible statistical framework for identifying driver genes and driver signaling pathways in cancer genome-sequencing studies. Biological knowledge of the mutational process in tumors is fully integrated into our statistical models and includes such variables as the length of protein-coding regions, transcript isoforms, variation in mutation types, differences in background mutation rates, the redundancy of genetic code, and multiple mutations in one gene. This framework provides several significant features that are not addressed or naively obtained by previous methods. In particular, on the observation of low prevalence of somatic mutations in individual tumors, we propose a heuristic strategy to estimate the mixture proportion of chi-square distribution of likelihood ratio test (LRT) statistics. This provides significantly increased statistical power compared to regular LRT. Through a combination of simulation and analysis of TCGA cancer sequencing study data, we demonstrate high accuracy and sensitivity in our methods. Our statistical methods and several auxiliary bioinformatics tools have been incorporated into a computational tool, DrGaP. The newly developed tool is immediately applicable to cancer genome-sequencing studies and will lead to a more complete identification of altered driver genes and driver signaling pathways in cancer.

| S-EPMC3769934 | biostudies-literature

Simple Tool for Rapidly Assessing the Quality of Multiplexed Single Cell Proteomics Data.

Project description:Recent advances in the sensitivity and speed of mass spectrometers coupled with improved sample preparation methods have enabled the field of single cell proteomics to proliferate. While heavy development is occurring in the label free space, dramatic improvements in throughput are provided by multiplexing with tandem mass tags. Hundreds or thousands of single cells can be analyzed with this method, yielding large data sets which may contain poor data arising from loss of material during cell sorting or poor digestion, labeling, and lysis. To date, no tools have been described that can assess data quality prior to data processing. We present herein a lightweight python script and accompanying graphic user interface that can rapidly quantify reporter ion peaks within each MS/MS spectrum in a file. With simple summary reports, we can identify single cell samples that fail to pass a set quality threshold, thus reducing analysis time waste. In addition, this tool, Diagnostic Ion Data Analysis Reduction (DIDAR), will create reduced MGF files containing only spectra possessing a user-specified number of single cell reporter ions. By reducing the number of spectra that have excessive zero values, we can speed up sample processing with little loss in data completeness as these spectra are removed in later stages in data processing workflows. DIDAR and the DIDAR GUI are compatible with all modern operating systems and are available at: https://github.com/orsburn/DIDARSCPQC. All files described in this study are available at www.massive.ucsd.edu as accession MSV000088887.

| S-EPMC10704589 | biostudies-literature

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