Proteomics

Proteomics relies on a suite of technologies to separate, identify, and quantify proteins. Two-dimensional gel electrophoresis (2-DE) was an early workhorse, separating proteins by isoelectric point and molecular weight, but it has largely been superseded by high-performance liquid chromatography (HPLC) coupled with mass spectrometry (MS). In a typical bottom-up workflow, proteins are digested into peptides, which are then analyzed by tandem mass spectrometry (MS/MS) to derive sequence information. Quantitative approaches include label-free quantification, stable isotope labeling with amino acids in cell culture (SILAC), and isobaric tags for relative and absolute quantification (iTRAQ/TMT). These methods enable comparative analysis of protein abundance across conditions, such as diseased versus healthy tissues.

Proteomics has become indispensable in biomedical research. It is used to catalog protein expression in various tissues and organisms, contributing to databases such as the Human Proteome Map. In clinical proteomics, the search for biomarkers for early disease detection is a major focus; for example, studies have identified candidate protein markers for ovarian and breast cancers. Proteomics also plays a role in drug discovery by revealing protein targets and off-target effects. In microbiology, proteomics helps understand pathogen–host interactions and antibiotic resistance mechanisms. Furthermore, structural proteomics, which aims to determine the three-dimensional structures of proteins on a large scale, has been accelerated by cryo-electron microscopy and computational prediction tools like AlphaFold.

Despite its power, proteomics faces significant challenges. The immense dynamic range of protein abundances in biological samples—spanning up to ten orders of magnitude—makes detecting low-abundance proteins difficult. Additionally, the complexity of post-translational modifications and protein isoforms complicates analysis. Recent advances include single-cell proteomics, which aims to profile proteins in individual cells, and top-down proteomics, which analyzes intact proteins to preserve modifications. Integration with genomics and transcriptomics (multi-omics) is becoming routine, providing a more holistic view of cellular function. Moreover, the development of data-independent acquisition (DIA) methods and improved bioinformatics tools are enhancing reproducibility and throughput.

Beyond the mainstream, proteomics has intriguing niche applications. Paleoproteomics, for instance, studies proteins from ancient remains, providing insights into evolutionary relationships and even the biology of extinct species like the woolly mammoth. In forensics, protein-based analysis can complement DNA evidence, especially when DNA is degraded. Proteomics also contributes to food science, verifying the authenticity of products like honey and wine. A lesser-known fact is that the term "proteome" was coined by Marc Wilkins in 1994, and the first proteomics journal, Proteomics, was launched in 2001. Additionally, the Human Proteome Organization (HUPO) coordinates global efforts to map the human proteome, with the goal of completing a draft by 2020—a milestone that was achieved in part.

Proteome

The entire set of proteins expressed by a genome, cell, tissue, or organism at a given time.

Mass spectrometry

An analytical technique that measures the mass-to-charge ratio of ions to identify and quantify molecules.

Post-translational modification

A covalent alteration of a protein after its synthesis, affecting its function, localization, or stability.

SILAC

Stable isotope labeling by amino acids in cell culture, a metabolic labeling method for quantitative proteomics.

Bottom-up proteomics

A workflow in which proteins are digested into peptides before mass spectrometric analysis.