Venturing into the world of single-cell proteomics

Single-cell proteomics offers us deep insights into the inner workings of a single cell by looking at its protein content. Find out what this exciting field can teach us about cell heterogeneity, biomarkers, and many other aspects of individual cells.

For much of the time since molecular biology techniques first emerged, they have relied on analyzing samples extracted from populations of cells, rather than single cells. Many techniques lacked the sensitivity to study individual cells, and even obtaining single cells from tissues efficiently could be challenging.

However, in recent years rapid advances in multiple analysis methods have given rise to the emerging field of single-cell omics, a collection of techniques aimed at studying single cells at the molecular level. Here, we look at single-cell proteomics: how does it work, what can you do with it, and what does the future hold?

What is single-cell proteomics?

Single-cell proteomics is the study of the protein composition, structure, and interactions in individual cells. As proteins are responsible for carrying out many cell functions, studying the proteome provides more direct information about cell behavior than just studying DNA or RNA.

A key reason for investigating the proteome at the single cell level is to look at cell heterogeneity within seemingly homogeneous populations. While studies carried out on populations of cells can provide average values, revealing differences within that population requires single-cell analysis. Other reasons include very small samples sizes or studying organisms that are challenging to culture.

Although the field of single-cell proteomics is far less established than, for example, single-cell DNA or RNA sequencing, rapid growth is expected in the coming years. According to BCC research, the market size for single-cell protein analysis in 2017 was estimated to be around 133 million USD: for 2022 this figure is expected to grow to 295 million, a more than 100% increase in five years.

Single-cell proteomics technology overview

One reason why single-cell proteomics is lagging relative to other single-cell omics approaches is the substantial challenge of isolating, handling, and analyzing the protein content of a single cell. First off, unlike DNA and RNA, proteins cannot be amplified. Proteins can also degrade quickly and are often ‘stickier’, which can lead to sample loss or biased results in many analytical methods.

Nevertheless, there is a wide range of analysis technologies that are potentially suitable for single-cell proteomics. In a 2020 review, Labib et al. proposed the following classification of analysis methods, based on the location of target proteins (1).

Table 1. Methods for single-cell protein analysis

Each of these methods has distinct benefits in this application, such as good target sensitivity (e.g. microfluidics), broad dynamic range (e.g. microengraving, SCBCs), and the ability to measure many proteins per cell (e.g. mass cytometry and IsoLight™). However, with all these techniques, good performance in one area is coupled with drawbacks in others.

The potential of single-cell proteomics

Single cell proteomics has the potential to answer fundamental questions in biology and expand our understanding of cell behavior. It can, for example, be applied in cancer research when studying tumor heterogeneity, drug resistance, or cancer immunotherapy.

In recent years, our understanding of the heterogeneous nature of tumors has increased substantially. Cell growth is rapid and error-prone, leading to subpopulations with varying characteristics. Drug candidates to target these tumors might only be effective on certain subpopulations, and this mechanism can manifest itself as a good initial response, while having a high risk of relapse and drug resistance.

Single-cell proteomics approaches can identify these subpopulations at the protein level and give deep insights into the effects of a drug on the ensemble of cell populations within a tumor.

In cancer immunotherapy, understanding the proteome of immune cells, such as T cells, and their targets is extremely valuable in developing successful therapies. For example, tumor cells can express mutated epitopes called neoantigens, which distinguish tumor cells from normal cells and makes them a potential target for immunotherapy. Understanding these epitopes and their interactions with T cell receptors could guide the development of cancer immunotherapies targeting neoantigens.

Improving sample preparation in single cell proteomics

One area of the single cell proteomics where substantial improvements are possible is sample preparation. To get reliable and powerful data, scientists need to analyze large numbers of cells, so automation and standardization become critical factors.

Sample disaggregation requires removing live single cells from their surrounding extracellular matrix (ECM). This type of tissue processing can be carried out by mechanical, chemical, or enzymatic means (or a combination). The key aim in sample preparation is maintaining a high cell viability and retrieving a population that is representative of the tissue sample, for example, by using the Cytiva VIA Extractor™.

The next step, protein isolation, can be standardized and is amenable to automation through the use of magnetic beads, such as Cytiva Mag Sepharose™ or Sera-Mag™ SpeedBeads Protein A/G magnetic particles. These magnetic beads can simplify target protein enrichment by pull-down or immunoprecipitation from single cells through reliable and efficient capture of low abundance proteins.

Outlook for single-cell proteomics

A wide range of different analysis techniques holds potential for supporting single-cell proteomics studies. In the coming years we expect that at least several of these techniques will overcome some of their associated drawbacks and improve throughput, number of proteins analyzed, or sensitivity.

Taking things a step further, single-cell multi-omics — combining different omics techniques — is fast becoming a way of getting an even more complete picture of the state of a single cell. Examples include CITE-seq and REAP-seq, which offer a combined approach that looks at both RNA and protein levels. In the coming years, these along with other multi-omics strategies could give us a more detailed picture of the inner working of a cell than ever before.

At Cytiva, we support scientists working in the fast-developing field of single-cell omics with ongoing innovation. For example, scientists can benefit from the breakthrough technology in our VIA Extractor™ tissue disaggregator. This first-in-kind device provides semi-automated sample disaggregation, processing human and animal solid tissue and tumor samples into viable single cells, ready for various single-cell omics analyses.