Human Plasma Proteome Project Research Articles

Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics.

In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.

Advances and Utility of the Human Plasma Proteome.

The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data.

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

The Human Plasma Proteome Draft of 2017: Building on the Human Plasma PeptideAtlas from Mass Spectrometry and Complementary Assays.

Human blood plasma provides a highly accessible window to the proteome of any individual in health and disease. Since its inception in 2002, the Human Proteome Organization's Human Plasma Proteome Project (HPPP) has been promoting advances in the study and understanding of the full protein complement of human plasma and on determining the abundance and modifications of its components. In 2017, we review the history of the HPPP and the advances of human plasma proteomics in general, including several recent achievements. We then present the latest 2017-04 build of Human Plasma PeptideAtlas, which yields ∼43 million peptide-spectrum matches and 122,730 distinct peptide sequences from 178 individual experiments at a 1% protein-level FDR globally across all experiments. Applying the latest Human Proteome Project Data Interpretation Guidelines, we catalog 3509 proteins that have at least two non-nested uniquely mapping peptides of nine amino acids or more and >1300 additional proteins with ambiguous evidence. We apply the same two-peptide guideline to historical PeptideAtlas builds going back to 2006 and examine the progress made in the past ten years in plasma proteome coverage. We also compare the distribution of proteins in historical PeptideAtlas builds in various RNA abundance and cellular localization categories. We then discuss advances in plasma proteomics based on targeted mass spectrometry as well as affinity assays, which during early 2017 target ∼2000 proteins. Finally, we describe considerations about sample handling and study design, concluding with an outlook for future advances in deciphering the human plasma proteome.

Plasma Proteome Database as a resource for proteomics research: 2014 update

Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization’s (HUPO’s) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.

Recent Workshops of the HUPO Human Plasma Proteome Project (HPPP): A bridge with the HUPO CardioVascular Initiative and the emergence of SRM targeted proteomics

We hereby provide a two-year update on the HUPO Human Plasma Proteome Project (HPPP) informed by advances presented at the HPPP sessions at the HUPO World Congresses in Toronto in September 2009 and in Sydney in September 2010.

Gene Expression Profiling in a Mouse Model Identifies Fetal Liver- and Placenta-Derived Potential Biomarkers for Down Syndrome Screening

BackgroundAs a first step to identify novel potential biomarkers for prenatal Down Syndrome screening, we analyzed gene expression in embryos of wild type mice and the Down Syndrome model Ts1Cje. Since current Down Syndrome screening markers are derived from placenta and fetal liver, these tissues were chosen as target.Methodology/Principal FindingsPlacenta and fetal liver at 15.5 days gestation were analyzed by microarray profiling. We confirmed increased expression of genes located at the trisomic chromosomal region. Overall, between the two genotypes more differentially expressed genes were found in fetal liver than in placenta. Furthermore, the fetal liver data are in line with the hematological aberrations found in humans with Down Syndrome as well as Ts1Cje mice. Together, we found 25 targets that are predicted (by Gene Ontology, UniProt, or the Human Plasma Proteome project) to be detectable in human serum.Conclusions/SignificanceFetal liver might harbor more promising targets for Down Syndrome screening studies. We expect these new targets will help focus further experimental studies on identifying and validating human maternal serum biomarkers for Down Syndrome screening.

Data management and functional annotation of the Korean reference plasma proteome

As human plasma is clinically valuable, reference data from healthy donors can be a useful source for serological biomarker studies. To make a reliable protein catalog of the Korean plasma proteome, various experimental methods, such as 1-D HPLC, 2-D LC, and narrow ranged 2-DE prior to MALDI-TOF and LC-MS/MS, were used to identify unique plasma proteins in this population. To compile candidates with high confidence, two different search engines were used to select proteins with a false discovery rate of less than or equal to 1%. From this rigorous selection process, we initially identified 494 distinct Korean plasma proteins. After multilevel stepwise filtrations with stringent, identification parameters were applied to acquire plasma protein list with the maximum confidence; a total 185 distinct plasma proteins were identified and integrated into our Korean human plasma proteome project database along with several bioinformatics analysis results, including gene ontology, biological pathways, tissue expression, and disease association. This is the first publicly available single ethnic group-specific plasma proteome database (http://proteomix.org/khppp/).

THE HUPO Human Plasma Proteome Project

The Human Proteomics Organization (HUPO) Human Plasma Proteome Project (PPP) is a prominent example of the inherently collaborative nature of the overall community effort to characterize the proteome of humans in health and disease. The PPP Pilot Phase, called "Exploring the Human Plasma Proteome", engaged 55 laboratories, four technical committees, and vendors and sponsors on an international scale. Among other outcomes, the PPP generated a Core Dataset of 3020 proteins identified with two or more peptides, fully accessible at EBI/PRIDE, ISB/PeptideAtlas, and University of Michigan websites, a rich resource for follow-on analyses. The PPP provided extensive annotation, correlation of number of peptides with protein concentrations measured by immunoassay, an algorithm for choice of a representative protein for multiple proteins matching a given peptide, and independent analyses from the raw spectra. The next phase of the PPP will emphasize standardized procedures for specimen handling, potent new technology platforms for discovery and for targeted proteomics, and robust informatics efforts, including comparative analyses of other biofluids.

Report from the 2nd Annual US HUPO Meeting on the HUPO Human Plasma Proteome Project

Report from the 2nd Annual US HUPO Meeting on the HUPO Human Plasma Proteome Project

Comparative 2-DE proteomic analysis clarified that the stability of ITIH-4 is decreased under the storage at 4°C

Studies on blood plasma proteome were performed by two-dimensional gel electrophoresis (2-DE) and mass spectrometry (MS) using samples supplied from China and the United States by collaborations of Human Plasma Proteome Project of HUPO. The plasma proteins were separated by isoelectric focusing using capillary type polyacrylamide gel (PAG) with carrier ampholytes pH 3.5-10 in the first dimension and with SDS-PAGE using 15%, 12.5% and 8% gel in the second dimension. The protein spots were identified by peptide mass fingerprinting using electrospray ionization MS/MS (LC/MSD Trap XCT, Agilent). More than 145 protein spots were identified by LC-MS/MS. The 2-DE patterns showed that the samples stored at 4°C for 3 days lost inter-alpha-trypsin inhibitor heavy chain 4 (ITIH-4).

Do we want our data raw? Including binary mass spectrometry data in public proteomics data repositories

With the human Plasma Proteome Project (PPP) pilot phase completed, the largest and most ambitious proteomics experiment to date has reached its first milestone. The correspondingly impressive amount of data that came from this pilot project emphasized the need for a centralized dissemination mechanism and led to the development of a detailed, PPP specific data gathering infrastructure at the University of Michigan, Ann Arbor as well as the protein identifications database project at the European Bioinformatics Institute as a general proteomics data repository. One issue that crept up while discussing which data to store for the PPP concerns whether the raw, binary data coming from the mass spectrometers should be stored, or rather the more compact and already significantly processed peak lists. As this debate is not restricted to the PPP but relates to the proteomics community in general, we will attempt to detail the relative merits and caveats associated with centralized storage and dissemination of raw data and/or peak lists, building on the extensive experience gained during the PPP pilot phase. Finally, some suggestions are made for both immediate and future storage of MS data in public repositories.

Peptidomic analysis of human blood specimens: Comparison between plasma specimens and serum by differential peptide display

The human Plasma Proteome Project pilot phase aims to analyze serum and plasma specimens to elucidate specimen characteristics by various proteomic techniques to ensure sufficient sample quality for the HUPO main phase. We used our proprietary peptidomics technologies to analyze the samples distributed by HUPO. Peptidomics summarizes technologies for visualization, quantitation, and identification of the low-molecular-weight proteome (<15 kDa), the "peptidome." We analyzed all four HUPO specimens (EDTA plasma, citrate plasma, heparin plasma, and serum) from African- and Asian-American donors and compared them to in-house collected Caucasian specimens. One main finding focuses on the most suitable method of plasma specimen collection. Gentle platelet removal from plasma samples is beneficial for improved specificity. Platelet contamination or activation of platelets by low temperature prior to their removal leads to distinct and multiple peptide signals in plasma samples. Two different specimen collection protocols for platelet-poor plasma are recommended. Further emphasis is placed on the differences between plasma and serum on a peptidomic level. A large number of peptides, many of them in rather high abundance, are only present in serum and not detectable in plasma. This ex vivo generation of multiple peptides hampers discovery efforts and is caused by a variety of factors: the release of platelet-derived peptides, other peptides derived from cellular components or the clot, enzymatic activities of coagulation cascades, and other proteases. We conclude that specimen collection is a crucial step for successful peptide biomarker discovery in human blood samples. For analysis of the low-molecular-weight proteome, we recommend the use of platelet-depleted EDTA or citrate plasma.

Evaluation of prefractionation methods as a preparatory step for multidimensional based chromatography of serum proteins

Prefractionations of proteins prior to their proteolysis, chromatography, and MS/MS analyses help reduce complexity and increase the yield of protein identifications. A number of methods were evaluated here for prefractionating serum samples distributed to the participating laboratories as part of the human Plasma Proteome Project. These methods include strong cation exchange (SCX) chromatography, slicing of SDS-PAGE gel bands, and liquid-phase IEF of the proteins. The fractionated proteins were trypsinized and the resulting peptides were resolved and analyzed by multidimensional protein identification technology coupled to IT MS/MS. The MS/MS spectra were clustered, combined, and searched against the IPI protein databank using Pep-Miner. The identification results were evaluated for the efficacy of the different prefractionation methodologies to identify larger numbers of proteins at higher confidence and to achieve the best coverage of the proteins with the identified peptides. Prefractionation based on SCX resulted in the largest number of identified proteins, followed by gel slices and then the liquid-phase IEF. An important observation was that each of the methods revealed a set of unique proteins, some identified with high confidence. Therefore, for comprehensive identification of the serum proteins, several different prefractionation approaches should be used in parallel.

Exploring the Human Plasma Proteome

AbstractNo abstracts.

Centralized data analysis of a large interlaboratory proteomics project: A feasibility study

The human Plasma Proteome Project (PPP) is a large-scale collaboration between many laboratories. One of the most demanding tasks in the PPP involved the analysis of very large amounts of raw MS/MS data produced by the participants. The main approach for managing this task was letting the participants analyze their own data and submit the results to the central PPP repository as lists of identified proteins and peptides. To complement this distributed approach, we also performed centralized analysis of the raw MS/MS data provided by the participants. Due to the data redundancy inherent in such a project, centralized analysis has the potential to reduce the computational effort by reducing redundancy before the analysis. Centralized analysis can also unify the process and take advantage of data sharing among laboratories to improve protein identification and validation. The process we employed included removing low-quality spectra, clustering spectra by mutual similarity, and applying uniform peptide and protein identification procedures. To demonstrate the process, we analyzed 5.28 million MS/MS spectra derived by eight laboratories from tryptic peptides of serum and plasma proteins.