See the proteome in a way that’s never been possible before

Proteomics is the study and functional analysis of proteins that are present in cells, tissues, and organs. (Proteins are the building blocks of the cell and are central molecules in the structure, function, and regulation of cells, tissues, and organs.) As such, proteomics tells us “what is” rather than “what could be”, giving us the closest look at a phenotype of interest and offering important understanding of protein activity at the molecular level.

Put another way, DNA is the blueprint of living organisms encoding instructions in RNA, and proteins are the functional building blocks that support the molecular mechanisms acting in living cells.

A proteome is the complete set of proteins translated by an organism. The genome encodes over 20,000 genes, however, it is estimated that there may be over one million distinct protein variants – called proteoforms – arising from dynamic mechanisms such as post-translational modifications (PTM), allelic variation, and alternative splicing.

Proteomics is used to study what is happening inside the body at a molecular level to explain the mechanisms underpinning human biology, including health and disease.

There are many types of proteomics analyses.

Protein Expression Proteomics is the quantitative study of how much of a given protein is present in a sample and how that differs between samples, particularly if there is a known variable that explains sample differences (e.g., healthy vs. cancer).

Structural Proteomics is the study of protein structures in three dimensions, including examining how protein sequence relates to structure, where the proteins are located in tissues, biofluids, and cells, and how proteins interact and form complexes (e.g., protein-protein interactions).

Functional Proteomics is the study of specific proteins and the characterization of how they act via protein signaling, disease mechanisms, or protein-drug interactions.

Common applications of proteomics correlate the involvement or association of the presence, absence, or intensity changes of proteins with a given health/disease state. To study human biology and how it relates to disease, some specific types of proteomics studies comprise biomarker discovery, quantitative trait loci studies, drug targets or discovery, and therapy response analyses.

Proteomics techniques can largely be distinguished into two types: sample preparation (separation and isolation of proteins) and protein identification/characterization.

Sample preparation includes various gel-based strategies and chromatography-based strategies. Liquid chromatography (LC) is commonly paired with Mass Spectrometry (LC-MS/MS) and can separate proteins in a complex mixture.

Protein identification/characterization includes Edman sequencing, which is the detection of amino acid sequence in peptides/proteins, affinity-based proteomics, which typically uses antibodies or aptamers to target specific proteins, and mass spectrometry (MS), which is the process by which proteins are ionized and their mass is calculated based on mass-to-charge ratios.

Reference: B Aslam, et al. Proteomics: Technologies and Their Applications. Journal of Chromatographic Science (2017). https://academic.oup.com/chromsci/article/55/2/182/2333796

Unbiased proteomics, like MS-based proteomics, enables broad analyses of the entire proteome, including proteoforms arising from PTMs, allelic variation, and alternative splicing, while targeted proteomics typically utilizes an analyte-specific reagent (ASR), like an antibody or aptamer, which binds known protein domains and is used to screen for a specific protein for which the ligand was designed.

Targeted technologies cannot distinguish between proteoforms, and it is possible that a protein altering variant may cause a conformational change or some epitopes to be inaccessible to ASRs. The approach also has the potential to impact molecular interactions resulting in missed protein variants.

There is a vast amount of information that can be discovered in proteomics today and in the future. However, technological improvements to address current research challenges will enable more comprehensive genetic association studies (like pQTLs), which combined with disease risk loci identified in GWAS, will help us better understand human health and disease. Combining proteomics with other forms of data will enable more large-scale studies that can be monitored over time to offer better systems level views of human biology, and support drug response analysis, drug discovery, and precision medicine.