Understanding the basics of single-cell omics

Single-cell omics is an exciting, highly multi-faceted field that can answer fundamental questions for scientists and clinicians. Here, we look at the different omics approaches: what they are, where they are used, and current and future trends.

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What is single-cell omics?

There are many practical or fundamental questions in biology and medicine that we cannot answer by taking the usual approach of analyzing large cell samples. Sometimes, we need to analyze cells individually to understand their more subtle differences. In other cases, you might only have a single cell available for a study.

This is the world of single-cell omics: an umbrella term that covers a range of ‘omics’ techniques when applied to a single cell. Under this umbrella we include genomics, transcriptomics, proteomics and metablomics.

The market for single-cell omics has increased rapidly in recent years and is expected to continue growing to 1.5 billion USD by 2022 (BCC Research, 2018). This growth will encompass both clinical and nonclinical markets, such as research and drug development.

Read about the emergence and applications of single-cell sequencing

Compared to conventional omics, the limited starting sample in single-cell omics techniques has implications in almost every aspect of the workflow. Cell isolation, sample preparation, and analysis all differ substantially from equivalent assays carried out on cell populations.

In cell isolation for example, individual cells need to be compartmentalized before analysis. This is possible through droplet-based systems (e.g. 10x Genomics) or microwell systems (e.g. Dolomite Bio, Honeycomb), among others.

So, what exactly are the different single-cell omics, and how are they used?

Single-cell genomics

Single-cell genomics focuses on a cell’s DNA. It can be used, for example, to study DNA heterogeneity in cell populations or in applications where only a few cells are available for analysis. The subfield of single-cell epigenomics examines DNA methylation and, by extension, gene regulation in individual cells.

The rapid growth in users, technologies, and applications of next-generation sequencing (NGS) and third generation sequencing has been a key factor in bringing genomic analysis to the single-cell level.

Oncology is an area where both of these factors come into play. Cancer is increasingly recognized as a disease of the single cell, which means that studying the genome of single cells can provide information unavailable to traditional molecular assays. Single-cell analysis also enables detection of circulating tumor cells (CTCs) in liquid biopsies—often a single-cell event.

Another key area for single-cell genomics is preimplantation diagnostics of embryos created by in vitro fertilization (IVF). This application is also characterized by very small sample sizes, demonstrating the need for single-cell accuracy.

Single-cell transcriptomics

Single-cell transcriptomics studies RNA, making it well suited for analyzing differences in gene expression between single cells. The fastest-growing technique in this area is single-cell RNA-seq (scRNA-seq), which can provide gene expression profiles of individual cells.

The field of immunology can benefit substantially from single-cell transcriptomics techniques like scRNA-seq. For example, immune cell populations are highly heterogeneous, so looking at individual cells provides vastly improved data compared with cell population data.

Flow cytometry is a common technique used to study individual immune cells at the protein level. However, this method can only evaluate a protein if a suitable antibody is available. It does not measure gene expression at the RNA level, something that can be achieved by using RNA-seq.

Single-cell proteomics

Single-cell proteomics evaluates cells’ protein content. The technique is in its infancy compared to its DNA and RNA counterparts, but the expectations are high. A cell’s proteome is a more direct indicator of cell function than nucleic acids, and studying it can provide deeper insights into cell behavior.

The main technologies available for analyzing the proteome at single cell level are mass spectrometry and antibody-based platforms.

The IsoLight™ system from IsoPlexis is one example of a technology that provides this single-cell sensitivity. Isolight uses more than 12 000 microchambers on a chip to capture single cells and an ELISA-based antibody barcode array to analyze more than 40 secreted functional proteins per cell simultaneously.

The technological limitations associated with single-cell protein assays will, at least for the near future, mainly be applied in fundamental biomedical research. Examples include understanding of tumor cell heterogeneity and therapeutic resistance, monitoring immune responses, and high-throughput drug screening.

Single-cell metabolomics

Single-cell metabolomics is the study of cell metabolites, such as sugars, lipids, glycolytic products, and phosphate compounds. While also in the early stages, single-cell metabolomics has the potential to answer key questions for both researchers and clinicians.

Techniques available to study metabolites at the single-cell level include nuclear magnetic resonance (NMR), capillary electrophoresis, liquid/gas chromatography, mass spectrometry, and fluorescence microscopy.

Applications for single-cell metabolomics lie in a range of clinical research areas, most importantly metabolic disorders, but also cancer research, pharmacology and toxicology, and drug discovery. Another key area is agricultural research such as crop improvement, safety assessment of GM crops, and biofuel generation.

Future trends: towards a multiomics approach

In the coming years, the field of single-cell omics is expected to see rapid growth. This growth is driven by a range of factors including:

• Emergence of automated, high-throughput platforms for single-cell analysis.
• Growing need for studying heterogeneous cell systems.
• Increasing demand for noninvasive tests in oncology.
• Consolidated funding through large-scale research initiatives and single-cell core facilities.

Another interesting trend is the emergence of single-cell multiomics. This approach aims to improve efficiency and data quality through the study of multiple analytes simultaneously, for example, combined analysis, splitting samples, or by converting one class of analytes into another.

An example of such a multiomics approach cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) . This method combines the capture and sequencing of RNA inside the cell with the use of barcoded antibodies that interact with epitopes on the cell surface.

In oncology, the ability of individual cells to resist chemotherapy can lead to cancer relapse or metastasis, and this ability might depend on both genomic and epigenomic factors. In these situations, combined multiomics approaches can hold the key to developing a complete understanding of drug resistance.

Nevertheless, many technological challenges remain in studying single cells effectively at the molecular level. These challenges exist in all different stages of the workflow, including cell isolation, sample preparation, amplification, and analysis. However, as new technologies continue to launch in rapid succession, there is considerable potential for growth.

At Cytiva, we are passionate about supporting scientists working in the fast-developing field of single-cell omics. One way in which scientists can benefit from our technology is the through our VIA Extractor™ tissue disaggregator. This first-in-kind device provides semi-automated sample disaggregation of human and animal solid tissue and tumor samples into viable single cells, ready for various single-cell omics analyses.

Find out more about VIA Extractor™ tissue disaggregator