Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Enhanced competitive protein exchange at the nano-bio interface enables ultra-deep coverage of the human plasma proteome

We have developed a scalable system that leverages protein nano interactions to overcome current limitations of deep plasma proteomics in large cohorts. Introducing proprietary engineered nanoparticles (NPs) into a biofluid such as blood plasma leads to the formation of a selective and reproducible protein corona at the particle protein interface, driven by the relationship between protein-NP affinity and protein abundance. Here we demonstrate the importance of tuning the protein to NP surface ratio (P/NP), which determines the competition between proteins for binding. We demonstrate how optimized P/NP ratio affects protein corona composition, ultimately enhancing performance of a fully automated NP based deep proteomic workflow (Proteograph). By limiting the available binding surface of NPs and increasing the binding competition, we identify 1.2 to 1.7x more proteins with only 1% false discovery rate on the surface of each NP, and up to 3x compared to a standard neat plasma proteomics workflow. Moreover, increased competition means proteins are more consistently identified and quantified across replicates, yielding precise quantification and improved coverage of the plasma proteome when using multiple physicochemically distinct NPs. In summary, by optimizing NPs and assay conditions, we capture a larger and more diverse set of proteins, enabling deep proteomic studies at scale.

The Plasma Proteome

INTODUCTIONThere is an urgent need for a simple and sensitive method to elucidate the human plasma proteome to find markers of disease, or therapeutic factors. Human plasma proteome may be obtained from tryptic peptides that results from native digestion using commonly available, sensitive and robust analytical instruments such as linear quadrupole, tandem mass spectrometers. METHODSThe human plasma proteome was elucidated from three independent human EDTA plasma populations analyzed by precipitation with acetonitrile (ACN) for quaternary amine (QA) micro-chromatography prior to native tryptic digestion for nano liquid chromatography, electrospray ionization and tandem mass spectrometry (LC-ESI-MS/MS). The LC-ESI-MS/MS results from authentic plasma and blank injection MS/MS noise controls were parsed into SQL Server along with the fit of the MS/MS spectra from the rigorous X!TANDEM for analysis with the R statistical system. A total of 13,408 gene symbols from tryptic (TRYP) and/or phosphor/tryptic (STYP) peptides showed ≥ 10 peptides with an FDR q ≤ 0.01 from fit of MS/MS spectra by X!TANDEM and were resolved from the null distribution of background noise showed a Chi Square value of χ2 ≥ 9 (p ≤ 0.005). RESULTSNative digestion of human EDTA plasma permitted the identification and quantification of ~ 13,408 protein gene symbols in plasma that showed low FDR (q≤0.01) from the fit of peptide MS/MS spectra and where observation frequency was resolved from the null distribution of random MS/MS spectra of source noise from recordings of blank injections. There was good agreement between the orbital ion trap (OIT) and the sensitive linear ion trap (LIT) as well as the tryptic versus phospho/tryptic peptides. A distinct subset of human cellular proteins showed a variety of specific interaction domains that formed a highly interconnected network in the plasma. DISCUSIONThe agreement between the fit of the peptide MS/MS spectra by the rigorous X!TANDEM algorithm versus random MS/MS spectra controls from blank noise injections demonstrated the reliability of the experimental approach. The highly interconnected network in the plasma confirmed that digestion of plasma under native conditions permitted the identification and quantification of the proteins in a population of human plasma samples. CONCLUSIONIt was feasible to identify more than ten thousand proteins from human plasma with high confidence using a simple linear ion trap after precipitation, quaternary amine chromatography, native digestion and nano spray analysis with a linear quadrupole ion trap.

Global chemical modifications comparison of human plasma proteome from two different age groups

In this study, two groups of human plasma proteome at different age groups (old and young) were used to perform a comparison of global chemical modifications, as determined by tandem mass spectrometry (MS/MS) combined with non-limiting modification identification algorithms. The sulfhydryl in the cysteine A total of 4 molecular modifications were found to have significant differences passing random grouping tests: the succinylation and phosphorylation modification of cysteine (Cys, C) and the modification of lysine (Lys, K) with threonine (Thr, T) were significantly higher in the old group than in the young group, while the carbamylation of lysine was lower in the young group. We speculate that there is an increase in certain modified proteins in the blood of the old people which, in turn, changes the function of those proteins. This change may be one of the reasons why old people are more likely than young people to be at risk for age-related diseases, such as metabolic diseases, cerebral and cardiovascular diseases, and cancer.

Global chemical modifications comparison of human plasma proteomes from two different age groups

The chemical modification of proteins refers to the covalent group reaction involved in their amino acid residues or chain ends which, in turn, change the molecular structure and function of the proteins. There are many types of molecular modifications in the human plasma proteome, such as phosphorylation, methylation, and acetylation. In this study, two groups of human plasma proteome at different age groups (old and young) were used to perform a comparison of global chemical modifications, as determined by tandem mass spectrometry (MS/MS) combined with non-limiting modification identification algorithms. The sulfhydryl in the cysteine A total of 4 molecular modifications were found to have significant differences: the succinylation and phosphorylation modification of cysteine (Cys, C) and the modification of lysine (Lys, K) with threonine (Thr, T) were significantly higher in the old group than in the young group, while the carbamylation of lysine was lower in the young group. Cysteine residue is an important group for forming disulphide bonds and maintaining the structure of the protein. Differential cysteine-related sulfydryl modifications may cause structural and functional changes. Lysine is a basic amino acid, and the modification of its amino group will change the charge state of the protein, which may affect the structure and function of the protein. In summary, four types of protein chemical modifications and substitutes were found to be significantly different in the plasma proteome in different age groups and their probabilities of random generation are lower by passing random grouping test. We speculate that there is an increase in certain modified proteins in the blood of the old people which, in turn, changes the function of those proteins. This change may be one of the reasons why the old people are more likely than the young people to be at risk for age-related diseases, such as metabolic diseases, cerebral and cardiovascular diseases, and cancer.