A critical advancement in the field of proteomics is the increasing accessibility of single-cell analysis. While proteomics is inherently intricate, involving numerous protein modifications and interactions, emerging technologies are simplifying its study. Modern methodologies now permit the daily preparation of hundreds to tens of thousands of individual cells. Through highly parallelized techniques, researchers can examine thousands of single cells and, depending on the equipment and cell size, quantify hundreds to thousands of proteins and their modifications. This leap is especially crucial because it allows for the investigation of protein modifications, transport, synthesis, and degradation with enhanced throughput and quantitative precision. Such detailed measurements are beginning to unveil biological insights that would be obscured by averaging data from cell populations.
To enhance the sensitivity and reproducibility of single-cell proteomics, innovative sample preparation methods have been developed. The most recent and frequently employed technique involves conducting sample preparation within individual droplets on glass slides. Each droplet serves as a contained reaction environment where a single cell is isolated, labeled, and processed for subsequent analysis. This automated approach is instrumental in minimizing sample loss and contamination, which is particularly vital given the minute amount of material in single cells. The primary objective is to preserve as much material as possible and to ensure consistent processing across numerous cells before their analysis via mass spectrometry. Complementary to this, multiplexing strategies significantly boost the throughput of single-cell proteomics. These strategies enable an increase in sample throughput without compromising coverage depth or quantitative accuracy. Newly developed reagents facilitate the multiplexing of more cells, improve confidence in sequence identification, and aid in the discovery of peptide modifications. For instance, PSMtag for plexDIA enhances the identification of fragment ions compared to label-free peptides, boosting sequence identification confidence and sensitivity, while also allowing for the simultaneous analysis of multiple samples. When combined with a dual-column setup and nine-plex PSM reagents, this method can analyze over a thousand single-cell-sized samples daily, maintaining coverage depth comparable to label-free controls.
Further innovations include multiplexing in the time domain, where elution gradients of multiple samples are overlapped. This approach, being orthogonal to mass dimension multiplexing, significantly increases the number of single cells or data points analyzed per day. However, this dense data generation presents challenges related to interference and quantitative accuracy, underscoring the importance of computational methods. Tools like JMod, an open-source software from the Parallel Squared Technology Institute, are crucial for interpreting these complex, highly parallelized and multiplexed experiments. Benchmarking studies have shown JMod’s capability to maintain accurate quantification across a wide dynamic range, quantifying a vast number of precursors in a single mass spectrometry run. Such advancements have also revealed critical insights into protein synthesis, degradation, and cell proliferation. Metabolic pulse experiments in mice, combining heavy isotope feeding with multiplexed measurements, have allowed researchers to determine protein synthesis and degradation rates. By analyzing histones, which are not significantly degraded, scientists can quantify proliferation rates across various cell types, demonstrating that protein clearance accounts for a substantial portion of protein abundance variation. This contribution is particularly pronounced in cells with lower growth rates, as dilution becomes a less significant factor in protein clearance.
The advent of single-cell proteomics has unveiled considerable variation in protein abundance among individual cells of the same type, a phenomenon not always predictable from RNA measurements. Protein correlations within cells are stronger and more functionally coordinated than their RNA counterparts, driven by regulated protein synthesis and degradation, and the higher reliability of protein measurements. This unique insight highlights the critical role of protein degradation, as it profoundly influences how protein correlations diverge from transcript correlations. This technology also offers a more direct examination of amino acid incorporation by ribosomes, revealing that non-canonical protein sequences, differing from those predicted by the genetic code, are widespread and sometimes more abundant. These findings, facilitated by advanced mass spectrometry instruments like timsTOF and hybrid fragmentation techniques such as TimsOmni, significantly deepen our understanding of protein biology. The future of single-cell proteomics promises to further unravel biological complexity by allowing direct measurement of proteins in individual cells, thus providing access to biological variations unobservable through RNA analysis. This includes detailed examination of protein abundance, synthesis, degradation, modifications, and coordinated behavior across single cells. As throughput increases, alongside quantitative depth, these molecular measurements can be increasingly linked to biological phenotypes, fostering a more profound understanding of life processes. Efforts are also underway to make these technologies broadly accessible, with initial guidelines and a single-cell proteomics portal being established to promote data sharing and collaborative research within the scientific community.
