ArticleClinical proteomics2018
The plasma peptidome.
Article in Clinical proteomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 28 citations in OpenAlex.
- Selected Ion Extraction of Peptides with Heavy Isotopes and Hydrogen Loss Reduces the Type II Error in Plasma Proteomics.ACS omega · 2025Article
- Trypsin Digestion Conditions of Human Plasma for Observation of Peptides and Proteins from Tandem Mass Spectrometry.ACS omega · 2024Article
- Therapy-induced secretion of spliceosomal components mediates pro-survival crosstalk between ovarian cancer cells.Nature communications · 2024Article
- Applications of Mass Spectrometry in the Characterization, Screening, Diagnosis, and Prognosis of COVID-19.Advances in experimental medicine and biology · 2024Article
- Intracellular peptides in SARS-CoV-2-infected patients.iScience · 2023Article
- Mitochondria and cytochrome components released into the plasma of severe COVID-19 and ICU acute respiratory distress syndrome patients.Clinical proteomics · 2023Article
- Peptidome profiling for the immunological stratification in sepsis: a proof of concept study.Scientific reports · 2022Article
- Applications of Tandem Mass Spectrometry (MS/MS) in Protein Analysis for Biomedical Research.Molecules (Basel, Switzerland) · 2022Review
- The plasma peptides of Alzheimer's disease.Clinical proteomics · 2021Article
- The plasma peptides of sepsis.Clinical proteomics · 2020Article
- Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data.Journal of proteome research · 2019Review
- The plasma peptides of breast versus ovarian cancer.Clinical proteomics · 2019Article
Corrections and comments
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Authors and funding
25 authors at 9 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIt may be possible to discover new diagnostic or therapeutic peptides or proteins from blood plasma using LC-ESI-MS/MS to identify, with a linear quadrupole ion trap to identify, quantify and compare the statistical distributions of peptides cleaved ex vivo from plasma samples from different clinical populations.
methodsA systematic method for the organic fractionation of plasma peptides was applied to identify and quantify the endogenous tryptic peptides from human plasma from multiple institutions by C18 HPLC followed nano electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS) with a linear quadrupole ion trap. The endogenous tryptic peptides, or tryptic phospho peptides (i.e. without exogenous digestion), were extracted in a mixture of organic solvent and water, dried and collected by preparative C18. The tryptic peptides from 6 institutions with 12 different disease and normal EDTA plasma populations, alongside ice cold controls for pre-analytical variation, were characterized by mass spectrometry. Each patient plasma was precipitated in 90% acetonitrile and the endogenous tryptic peptides extracted by a stepwise gradient of increasing water and then formic acid resulting in 10 sub-fractions. The fractionated peptides were manually collected over preparative C18 and injected for 1508 LC-ESI-MS/MS experiments analyzed in SQL Server R.
resultsPeptides that were cleaved in human plasma by a tryptic activity ex vivo provided convenient and sensitive access to most human proteins in plasma that show differences in the frequency or intensity of proteins observed across populations that may have clinical significance. Combination of step wise organic extraction of 200 μL of plasma with nano electrospray resulted in the confident identification and quantification ~ 14,000 gene symbols by X!TANDEM that is the largest number of blood proteins identified to date and shows that you can monitor the ex vivo proteolysis of most human proteins, including interleukins, from blood. A total of 15,968,550 MS/MS spectra ≥ E4 intensity counts were correlated by the SEQUEST and X!TANDEM algorithms to a federated library of 157,478 protein sequences that were filtered for best charge state (2+ or 3+) and peptide sequence in SQL Server resulting in 1,916,672 distinct best-fit peptide correlations for analysis with the R statistical system. SEQUEST identified some 140,054 protein accessions, or some ~ 26,000 gene symbols, proteins or loci, with at least 5 independent correlations. The X!TANDEM algorithm made at least 5 best fit correlations to more than 14,000 protein gene symbols with p-values and FDR corrected q-values of ~ 0.001 or less. Log
conclusionsThe random and independent sampling of pre-fractionated blood peptides by LC-ESI-MS/MS with SQL Server-R analysis revealed the largest plasma proteome to date and was a practical method to quantify and compare the frequency or log
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