Single-Cell Analysis: Considerations & Applications

Single-Cell Analysis: Considerations & Applications

Variety is the spice of life. And living cells agree. Billions of cells comprise the thousands of species and people that live on our planet. Each cell within a cell population can look and act differently, even within the same tissue. The many cell types that comprise our body’s tissues affect how cells respond to treatment and other environmental stimuli.

So, how do we characterize these responses?

That’s where single-cell assays come in. These assays feature workflows to isolate and profile individual cells. The workflows are classified within the ‘omics and make molecular profiling at a high-throughput rate possible for single cells. From proteins to nucleic acids, researchers can tease apart a cell’s molecular traits and leverage them to treat disease.

In this article, we will introduce these methods and show how Excedr can help you propel your ‘omics efforts for single-cell profiling.

Multiomics Characterization: Introducing the ‘Omics

The ‘omics suffix has been around for decades. It was first applied for biomedical research in 1986 when Dr. Thomas H. Roderick helped name a new journal specializing in genome research: Genomics. Since then, researchers have expanded the ‘omics suffix to other datasets. The three most common of these are:

Today, the ’omics have been expanded to study phenotypes at a single-cell level. To this end, researchers modified existing workflows with single-cell technologies. These modifications enable single-cell isolation and lysis, biomolecule extraction and labeling, and single-cell bioinformatics analysis. We will cover each of these aspects as we explore each ‘omics.

Single-Cell Genomics & Epigenomics: Identifying Genetic Variability & Gene Modifications

Cellular diversity begins at the genome. In single-cell genomics, researchers sequence the genomes of different cells with sequencing techniques. Single-cell genome sequencing reveals genomic differences between cells, a key driver of cellular heterogeneity. Some of these differences arise from mutations that drive diseases such as breast cancer. However, these differences create the need to determine which mutations are more likely to drive disease. To answer this question, researchers can leverage genome-wide association studies (GWAS). With GWAS, researchers have linked loci in individual cells to cardiac diseases and stem cell differentiation.

DNA can undergo biochemical modifications that affect which genes are expressed. Below are just some of the modifications that DNA can harbor:

Genomic modifications in individual cells can also occur beyond a genome sequence. The study and collection of these modifications are known as epigenetics and epigenomics, respectively. Such efforts allow researchers to obtain a comprehensive picture of a cell’s phenotypic potential.

A single-cell genomics and epigenomics study commonly begins with extracting the chromosomes from single cells. These cells are obtained with microfluidics, inspired partly by fluorescence-associated cell sorting (FACS). Much like FACS, researchers can produce liquid systems that isolate single cells for extracting DNA (insert Excedr article link). The workflows then prepare libraries to sequence the DNA.

Library preparation protocols for single-cell epigenomics also feature several alterations. These include:

Single-Cell Transcriptomics: Teasing Apart Gene Expression

A typical RNA sequencing (RNA-Seq) study profiles the mRNA produced by all cells within a sample. The dataset would reflect the average gene expression patterns within a cell population. Nonetheless, gene expression varies greatly between cells, whether mammalian or microbial. Substantial heterogeneity also arises in cells from different tissues and among cells comprising the same tissue. Hence, new technologies that extend existing RNA-Seq workflows are needed to conduct single-cell transcriptome analysis.

To meet this need, researchers have developed single-cell RNA sequencing (scRNA-seq). Using scRNA-seq helped discover rarer phenotypes that may contribute to worsening disease phenotypes. For instance, scRNA-seq can help with diagnostics research by identifying cancer stem cell subpopulations that are correlated with the progression of human fatal renal cancer cell carcinomas. scRNA-seq can also identify phenotypes characteristic of breast cancer cell subtypes that remain dormant before inducing breast cancer relapse.

The success of scRNA-seq workflows in biomedical research lies in extending existing RNA-seq methods to profile a single cell’s mRNA transcripts. Most of these workflows comprise the following steps before any data analysis is performed:

Researchers can also contextualize single-cell gene expression within the tissues where they reside with spatial transcriptomics. Here, researchers obtain positional information about the cells they are sequencing and map gene expression back to those cells. This data can generate cell atlases that differentiate cell states and cell types within tissues. Such efforts have aided the visualization of tumor cell subpopulations that populate the tumor microenvironment. Single-cell transcriptomics has also helped researchers identify changes in immune cell composition with tumor progression.

Single-Cell Proteomics: Profiling a Cell’s Tools

Researchers have also begun to appreciate the collection of proteins unique to individual cells. However, conventional proteomics assays fail to account for heterogeneity in protein levels and identify lower-abundance proteins. Single-cell proteomics addresses this by characterizing protein abundances in each cell with two techniques. They are:

Completing the ‘Omics: Data Analysis with Bioinformatics

Irrespective of the kinds of biomolecules assayed and the insights to be gained, single-cell assays require computational tools to analyze the data. To meet this need, researchers have developed numerous bioinformatics tools to assess the quality of the data and glean biological insights from individual cells. Across all bioinformatics workflows, some features arise:

Excedr leases the technologies you need to conduct a single-cell study

We’ve covered two kinds of machines you will need to conduct a single-cell ‘omics study: the next-generation sequencer and the mass spectrometer. If you’re in need of a new or refurbished unit, Excedr can lease exactly what you need, regardless of brand or manufacturer. . This is because we don’t carry any inventory, and instead provide a brand agnostic service that puts your needs first. Rather than be tied to a specific vendor or reseller, you can simply let us know what unit you’re interested in and we can procure it for you and your lab.

Here are just some of the mass spectrometer manufacturers we have leased from in the past:

We have also helped sequencing facilities set up their operations by supplying sequencers from the following brands:

Lease the tools to enhance your single-cell assays

Cellular life is teeming with diverse cell types and subpopulations. Profiling these populations requires tools that separate the cells and characterize them with high resolution and accuracy. Tools typically used to characterize whole samples are also capable of profiling individual cells. By using mass spectrometers, sequencers, and other specialized instrumentation, researchers have made great clinical strides in studying biological phenomena at the single-cell level.

Excedr’s leasing program can help you establish your single-cell assays by leasing you the equipment your lab needs to study the heterogeneity of single cells. From reducing upfront costs to extending cash runway, speak with our team today to learn exactly how we can help.