Cross-platform Clinical Proteomics using the Charite Open Standard for Plasma Proteomics (OSPP)
Wang, Z.; Farztdinov, V.; Sinn, L. R.; Tober-Lau, P.; Ludwig, D.; Amari, F.; Textoris-Taube, K.; Freiwald, A.; Welter, A. S.; Wei, A. A. J.; Luckau, L.; Kurth, F.; Selbach, M.; Hartl, J.; Muelleder, M.; Ralser, M.
Show abstract
The role of plasma and serum proteomics in characterizing human disease, identifying biomarkers, and advancing diagnostic technologies is rapidly increasing. However, there is an ongoing need to improve proteomic workflows in terms of accuracy, reproducibility, platform transferability, and cost-effectiveness. Here, we present the Charite Open Peptide Standard for Plasma Proteomics (OSPP), a panel of 211 extensively pre-selected, stable-isotope-labeled peptides combined in an open, versatile, and cost-effective internal standard for targeted and untargeted proteomic studies. The selected peptides are well suited for chemical synthesis, and distribute well over the captured analytical dynamic range and chromatographic gradients, and show consistent quantification properties across platforms, in serum, as well as in EDTA-, citrate, and heparin plasma. Quantifying proteins that function in a wide range of biological processes, including several that are routinely used in clinical tests or are targets of FDA-approved drugs, the OSPP quantifies proteins that are important for human disease. On an acute COVID-19 in-patient cohort, we demonstrate the application of the OSPP to i) achieve patient classification and biomarker identification ii) generate comparable quantitative proteomics data with both targeted and untargeted approaches, and iii) estimate peptide quantities for successful cross-platform alignment of proteomic data. The OSPP adds low costs per proteome sample, thus making the use of an internal standard accessible. In addition to the standards, corresponding spectral libraries and optimized acquisition methods for several platforms are made openly available.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Hybrid-DIA: Intelligent Data Acquisition for Simultaneous Targeted and Discovery Phosphoproteomics in Single Spheroids 97%
- IceR improves proteome coverage and data completeness in global and single-cell proteomics 97%
- SugarQuant: a streamlined pipeline for multiplexed quantitative site-specific N-glycoproteomics 97%
Similar papers in this journal
- Performance Characteristics of Zeno Trap Scanning DIA for Sensitive and Quantitative Proteomics at High Throughput 96%
- Mass spectrometry-based quantification of proteins and post-translational modifications in dried blood: longitudinal sampling of patients with sepsis in Tanzania 95%
- Parallel Analyses by Mass Spectrometry (MS) and Reverse Phase Protein Array (RPPA) Reveal Complementary Proteomic Profiles in Triple-Negative Breast Cancer (TNBC) Patient Tissues and Cell Cultures 95%
Similar papers in this journal
- Microphysiological Drug-Testing Platform For Identifying Responses To Prodrug Treatment In Primary Leukemia 87%
- Rapid antifouling nanocomposite coating enables highly sensitive multiplexed electrochemical detection of myocardial infarction and concussion markers 87%
- Microfluidic interfaces for chronic bidirectional access to the brain. 87%
Similar papers in this journal
- Deep Proteome Profiling of Metabolic Dysfunction-Associated Steatotic Liver Disease 93%
- Quantitative proteomics and phosphoproteomics of urinary extracellular vesicles define diagnostic and prognostic biosignatures for Parkinson’s Disease 92%
- Minimal Correlation but Complementary Diagnostic Utility for Plasma Cell-free RNA and Proteins 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.