Single-cell proteomics is a rapidly growing field that allows for the comprehensive analysis of individual cells’ proteins, leading to a deeper understanding of biological processes at the cellular level. In recent years, advances in technology and methodology have made it possible to uncover previously hidden aspects of cell biology using single-cell proteomics, leading to new discoveries and insights. These findings have significant implications for fields ranging from medicine to environmental science. This article will delve into the exciting world of single-cell proteomics and discuss some of the latest research in this innovative field.
Recently, advances in single-cell proteomics (SCP) have been made to address challenges faced during sample preparation. SCP analyzes the proteomes of single cells, which often have little starting material and require highly sensitive methods to detect low abundance proteins. One method, called NanoPOTS, reduces liquid-handling steps and increases protein yield per cell, resulting in the identification of 2- to 25-fold more peptides than traditional sample preparation. Another approach, SCoPE-MS, uses a carrier proteome that increases the amount of low abundance peptides to be detected by mass spectrometry, but requires accurate MS quantification due to low signal from peptides in single cells. To address this, Cheung et al. developed SCPCompanion to enable quality-control analysis of SCP-MS data.
Furthermore, Ctortecka et al. found that limiting carrier spikes to ≤20-fold was critical to accurate SCP analyses. An optimized workflow, SCoPE2, incorporated several improvements including optimizing instrument parameters and a Bayesian algorithm to enhance peptide sequence identification. Meanwhile, Schoof et al. developed an improved workflow for automated SCP using a high-resolution mass spectrometer with a Python package called SCeptre, which filters out outlier cells to avoid misleading biological conclusions. In addition, Kalxdorf et al. developed the IceR workflow that combines high identification rates of DDA with low missing value rates similar to data-independent acquisition (DIA) to address the challenge of missing values.
Lastly, Brunner et al. developed a method called true single-cell-derived proteomics (T-SCP), which combines miniaturized sample preparation with very low flow rate chromatography and a novel trapped ion mobility mass spectrometer. This method requires precise sample handling and results in 10-fold improved sensitivity over traditional sample preparation. By utilizing a diaPASEF acquisition mode coupled with very low flow rate chromatography, up to 2083 proteins per cell were quantified for HeLa cells.
In conclusion, recent advances in SCP have improved sample preparation, quantification, and identification of proteins in single cells. These advances have enabled the identification of previously undetected low abundance proteins and will have broad implications for understanding cellular heterogeneity and disease.
Uncovering the intricacies of biology has long been a challenge for science. However, with the advancements in single-cell proteomics, we are now equipped with a powerful tool that allows us to delve ever deeper into the mysteries of cellular function. By understanding the unique proteome of individual cells, we may be able to unlock novel insights and pave the way for breakthroughs in medicine and beyond. The potential of single-cell proteomics is vast, and we are just scratching the surface of what is to come. The future is bright, and exciting discoveries await.
