Single-cell proteomics enables advances in disease research


Single-cell technologies are transforming our understanding of human health and disease. Single-cell genomics and transcriptomics are mature disciplines that can be used to study over a million individual cells (1). However, the man

biology cannot be understood by DNA and RNA analysis alone. It also requires the study of proteins and protein modifications, lipids and metabolites.

Proteins are biochemically active and also serve as signaling molecules. As a result, it’s no surprise that about 95% of drugs target proteins. However, protein molecules cannot be amplified like DNA or RNA to perform single cell proteomics measurements. Thus, novel and highly sensitive technologies are needed to decipher this complexity at the single-cell level and contribute to our understanding of emerging issues surrounding health and disease (2).

Landscape of single-cell omics

Protein function is frequently modulated by post-translational modifications, such as phosphorylation and ubiquitylation, which can alter the functional course of the cell with rapid kinetics. Processes such as endogenous proteolysis and glycosylation are known to play a role in oncological mechanisms (3,4). Additionally, gene expression is affected by so-called expression bursts, resulting in additional variations that would be automatically normalized by post-translational regulatory processes in the case of proteins (5). Also, alternative splicing of RNA transcripts can result in additional protein variants. Single-cell proteomics technologies are now entering the mainstream thanks to the pioneering work of a relatively small group of dedicated scientists and the emergence of highly sensitive mass spectrometers. Typical estimates of the protein content of individual cells are on the order of 200 picograms (equivalent to one billionth of a milligram). In a recent study, qualitative and quantitative information for up to 1400 proteins was obtained from single cells using a unique unbiased proteomics approach that did not require complex isobaric labeling chemistries to stimulate peptide signals. (6). Cluster analysis of the data could distinguish between cell types and cell cycle stages, although the technology does not specifically target known and verified markers.

Technological advances

This microheterogeneity in seemingly homogeneous cell populations plays a key role in the critical pathways followed by biological systems. The underlying microheterogeneity is caused by variations in genes and their expression, and understanding these variations at the single-cell level helps identify the few cells that act as a seed for the development of cancer, for example. The study of DNA and RNA molecules in the cell is one of the most common approaches in single cell biology and has also helped to motivate the measurement of proteins at the single cell level. Exponential advances have been made in single-cell DNA and RNA sequencing technologies, and depending on the application, various sequencing techniques can be used for these studies (2).

With the help of these advanced technologies, studies involving the measurement of single-cell transcriptomes of over one million single cells are now feasible (1) and have revealed novel biology as well as highlighted the heterogeneity of single cells – thus opening new fields of biology and medicine. A common factor in all of these approaches is the ability to amplify DNA and RNA molecules to virtually any desired amount, bringing these molecules into a detectable or quantifiable range (7).

Unbiased single cell proteomics has been performed in recent years by specialized research groups involving nano-fluidics that are not yet readily adopted by the general research community. These applications often focus on minimizing loss during sample preparation and sample multiplexing to increase signal intensity (8,9). Despite these solutions, however, the field still needs innovations that can increase the sensitivity of the mass spectrometer.

Mobility spectrometry of trapped ions

The development of parallel accumulation and serial fragmentation (PASEF) (10) has provided a spectroscopic technique used with liquid chromatography coupled with proteomics-based mass spectrometry (LC-MS) to improve the speed and sequencing sensitivity. PASEF makes efficient use of the ion beam and, with the intelligent selection of ion precursors eluted from a Trapped Ion Mobility Spectrometry (TIMS) run, achieves fast MS/MS identification speed. In addition, the ions are spatially and temporally focused inside the TIMS cell, resulting in a significant increase in sensitivity. This allows the analysis of low sample amounts, in the low nanogram peptide loading range.

TIMS measurements also provide collision cross-section (CCS) values ​​and the separation of isomeric species that are mobility-compensated but mass-aligned and mitigate ratio compression in multiplexed quantification approaches. The introduction of these 4D proteomics capabilities has bridged the gap between the demands of the most demanding proteomics approaches, such as clinical research proteomics, companion diagnostics research, and personalized medicine research, and the solutions actually available. on the market.

Conclusion

Next-generation sequencing technologies are now a multi-billion dollar industry (11) that promises to help deliver personalized medicine and precision therapies that will help fight complex and heterogeneous conditions, such as cancer and Alzheimer’s disease.

Single-cell protein technologies have the potential to transform our understanding of cell biology at the macromolecular level and answer fundamental questions regarding protein dynamics, cell differentiation trajectories and disease mechanisms. These processes act at the nano and microscopic level but fundamentally influence higher-order macroscopic behavior. Therefore, it is essential that these processes are understood at the highest possible spatial resolution.

References

1. J. Cao, et al., Nature 566, 496-502 (2019).
2. G. Chen, B. Ning and T. Shi, Front. Broom.April 5, 2019.
3. LA Liotta and EF Petricoin, J Clin Invest. 116(1) 26–30 (2006).
4. MA Connelly, et al., J Transl Med 15, 219 (2017).
5. GK Marinov, et al., Genome Res. 24, 496–510 (2014).
6. AD Brunner, et al., bioRxiv 12.22.423933 (2020).
7. CFA de Bourcy, et al., PLOS ONE 9(8)e105585 (2014).
8. D. Hartlmay, et al., bioRxiv 04.14.439828 (2021).
9.N. Slavov, Current Opinion in Chemical Biology 60, 1–9 (2021).
10. F. Meier, et al., Cell proteomics Mol. 17(12) 2534-2545 (2018).
11. Markets and Markets, Single Cell Analysis Market by Cell Type (Human, Animal, Microbial), Product (Consumables, Instrument), Technique (Flow Cytometry, NGS, PCR, Microscopy, MS), Application (Research, Medical), End User ( pharmaceuticals, biotechnology, hospitals)—Global forecasts to 2026, marchesetmarches.comFebruary 2020.

About the Author

Gary Kruppa, PhD, is vice president of proteomics, Bruker Daltonics.

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