The HUPO Plasma Proteome Project's groundbreaking discoveries
Published: October 15, 2023
Imagine if a single teaspoon of your blood could reveal not just your current health status, but predict future diseases, monitor treatment effectiveness, and unlock personalized medical solutions. This isn't science fiction—it's the promise of plasma proteomics, a field revolutionized by the Human Proteome Organization's Plasma Proteome Project (HPPP). In 2007, scientists from around the world gathered to consolidate findings from this ambitious endeavor, which aimed to catalog and characterize all proteins circulating in human blood 3 .
Orders of magnitude in protein concentration range in blood plasma
Blood plasma represents the most complex human proteome, containing thousands of proteins that serve as vital indicators of physiological and pathological states. These proteins range from abundant albumin (measured in milligrams per milliliter) to rare signaling molecules (measured in picograms per milliliter), spanning an astonishing 10 orders of magnitude in concentration. The HPPP emerged as a response to the formidable challenges of analyzing this proteome, with its 2007 workshop report marking a critical milestone in clinical proteomics and laying the foundation for modern biomarker discovery 1 3 .
The HUPO Plasma Proteome Project was initiated in 2002 as an international collaborative effort to overcome the major challenges in plasma proteomics—particularly the extreme dynamic range of protein concentrations and analytical sensitivity limitations that had previously hampered comprehensive analysis. Led by distinguished scientists including Gil Omenn and colleagues from multiple countries, the project brought together 35 collaborating laboratories across 13 nations, creating an unprecedented scientific consortium dedicated to mapping the plasma proteome 3 .
HUPO Plasma Proteome Project officially launched with international collaboration
Pilot phase with standardized protocols and multi-laboratory framework
Data analysis and integration from all participating laboratories
Workshop report published with comprehensive findings
The pilot phase designed a sophisticated multi-laboratory framework to evaluate:
This collective effort generated a core dataset of 3,020 proteins identified with two or more peptides—an extraordinary achievement at the time that immediately became an invaluable resource for biomedical researchers worldwide 3 .
The HPPP's success hinged on innovative methodological approaches that combined multiple technologies to overcome the inherent challenges of plasma proteomics. The project employed both mass spectrometry-based and affinity-based proteomic approaches, each with complementary strengths 1 .
The project also established critical sample handling protocols, recommending platelet-depleted plasma over serum for most studies, rapid processing, aliquoting, and storage at -80°C or in liquid nitrogen to preserve protein integrity 4 . These methodological advances created a new standard of rigor for plasma proteomics studies.
The 2007 workshop report synthesized extraordinary findings from the collaborative effort, revealing the astonishing complexity of the plasma proteome and establishing new frameworks for plasma protein analysis.
The integrated analysis identified 15,710 different International Protein Index (IPI) protein IDs using a sophisticated algorithm that accounted for multiple matches of peptide sequences. From these, the project established a core dataset of 3,020 proteins identified with two or more peptides—a landmark achievement in proteomics 3 . This core set represented proteins with the highest confidence identifications and immediately became a reference resource for the scientific community.
The characterized proteins were annotated with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations, providing rich biological context. The database allowed examination of specialized subsets, such as 1,274 proteins identified with three or more peptides, enabling researchers to explore specific protein classes of interest 3 .
A crucial finding was the recommendation to use plasma instead of serum, with EDTA or citrate for anticoagulation, based on comprehensive comparisons of reference specimens. This guidance helped standardize future studies and improve cross-study comparisons 3 .
| Protein Category | Number Identified | Representative Examples |
|---|---|---|
| Signaling Proteins | 893 | Cytokines, growth factors |
| Metabolic Enzymes | 642 | Transferases, hydrolases |
| Transport Proteins | 387 | Albumin, transferrin |
| Immunoglobulins | 124 | IgG, IgA, IgM variants |
| Extracellular Matrix | 87 | Collagens, fibronectin |
| Unknown Function | 56 | Novel proteins |
One of the most innovative approaches featured in the 2007 workshop report was the Accurate Mass and Time (AMT) tag strategy implemented by a team using high-resolution mass accuracy capillary LC-FT-ICR MS 5 . This experiment exemplified the technological sophistication driving the project's success.
The researchers analyzed HUPO reference serum and citrated plasma samples from African Americans, Asian Americans, and Caucasian Americans, in addition to internal reference materials. The AMT tag strategy leveraged previously published "shotgun" proteomics experiments to perform global analyses on these samples in triplicate in less than 4 days total analysis time—a remarkable throughput achievement for the era 5 .
The experimental workflow consisted of:
The AMT approach identified 722 International Protein Index redundant proteins (22% with multiple peptide identifications), corresponding to 377 protein families as determined by ProteinProphet. The samples yielded a similar number of identified redundant proteins in plasma samples (average 446 ± 23) as in serum samples (average 440 ± 20) 5 .
Perhaps most impressively, the researchers used Z-score normalization to compare relative protein abundances, revealing both known differences (such as fibrinogens in plasma versus serum) and previously unrecognized differences in peptide abundances from proteins like soluble activin receptor-like kinase 7b and glycoprotein m6b 5 .
| Metric | Plasma Samples | Serum Samples |
|---|---|---|
| Average proteins identified | 446 ± 23 | 440 ± 20 |
| Average unique peptides | 956 ± 35 | 930 ± 11 |
| Analysis time per sample | < 18 hours | < 18 hours |
| False discovery rate | < 1% | < 1% |
This experiment demonstrated that the AMT tag strategy not only improved sample throughput but also provided a basis for estimated quantitation—a crucial requirement for biomarker studies 5 .
The HPPP evaluation revealed that comprehensive plasma proteome analysis requires a multifaceted approach using multiple technology platforms. The following table details essential research reagents and their functions in plasma proteomics studies.
| Reagent/Resource | Function | Application in HPPP |
|---|---|---|
| EDTA-anticoagulated plasma | Prevents coagulation while preserving protein integrity | Recommended specimen type for most studies |
| Protease inhibitor cocktails | Inhibits protein degradation during processing | Added immediately after blood collection |
| Immunoaffinity columns | Deplete high-abundance proteins | Remove albumin, immunoglobulins to enhance detection of low-abundance proteins |
| Trypsin | Proteolytic enzyme for protein digestion | Cleaves proteins into peptides for MS analysis |
| ICAT (Isotope-Coded Affinity Tags) | Isotope labeling for quantification | Compare protein abundance between samples |
| ITRAQ (Isobaric Tags for Relative and Absolute Quantitation) | Multiplexed protein quantification | Simultaneously compare multiple samples in single MS run |
| Reference peptide libraries | AMT tag databases for peptide identification | Enable high-confidence peptide identification without MS/MS |
The 2007 HPPP workshop report established a new foundation for plasma proteomics that continues to support advances in biomedical research. The project demonstrated that combining multiple technologies provided more comprehensive proteome coverage than any single approach, highlighting the importance of methodological diversity 3 5 .
The HPPP's most enduring contribution may be its publicly available database (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride), which became a template for subsequent proteomic data sharing initiatives. This open resource philosophy accelerated progress throughout the field and inspired the creation of specialized resources like the Plasma Peptide Atlas, which continues to expand with new data contributions from researchers worldwide 6 .
Today, the legacy of the HPPP lives on through continued advancements in mass spectrometry sensitivity, computational proteomics, and large-scale biomarker validation studies. The project's findings helped transform plasma from a biological fluid into a strategic resource for understanding human biology and disease—bringing us closer to the era of truly personalized medicine 1 7 .
As proteomic technologies continue to evolve, becoming more sensitive, quantitative, and accessible to clinical laboratories, the foundation laid by the HPPP ensures that each new discovery builds upon a robust framework of standardized methods and shared knowledge. What began as an international effort to map the plasma proteome has ultimately created a lasting infrastructure for biological discovery and medical innovation.