The analysis of the fundamental unit of life “Cell” can be correlated with a wide range of technologies depending on the experimental needs. Cell analysis is gaining importance in various fields of applications such as basic research, drug discovery, diagnosis of diseases (Infectious, genetic and other diseases) and cancer research. Analysis of heterogeneity of the cells in relation to gene, protein expression, transcription and epigenomics at the cellular level is expanding our understanding of complexity of cells. The Study of genomics, proteomics, transcriptomics and metabolomics at the single-cell level is known as single-cell analysis.
The single-cell analysis allows the study of the cell to cell variation within a population for understanding gene expression profiles. It helps to avoid the mistake of taking averages of entire cell populations and also aids in the discovery of previously undetected sub-populations. Initially, cell population was thought to be homogeneous and most biological assays were performed on population containing thousands and millions of cells resulting in a mixture of the biological status of each cell. However, the recent advancements of single-cell analysis techniques enable the opportunity to distinguish biological insights within individual cells and provide the hidden relationship between individual cells within the population.
In genomics, single-cell DNA sequencing is used to resolve the variation between individual cells, the most common parameters assayed in this type of analysis include the number of single-nucleotide variants (SNVs), which occurs approximately ∼1500 per human cell and subchromosomal copy-number variants (CNVs) that develop at least once in 30-70% of cells. Using single-cell DNA sequencing, the genomic heterogeneity of cell populations can be explored. Genetic changes, such as point mutations and copy number variation that occurs during disease and normal development processes, can be detected using the minute amounts of DNA from single cells. Applications of single-cell DNA sequencing include analysis of genetic heterogeneity within unicellular and multicellular organisms, detection of chromosomal anomalies in germline cells, preimplantation genomic screening of embryos, and defining the genetic composition of tumors for developing more targeted therapies.
Analysis of protein at the single-cell level could provide essential information on the state and function of a cell. Cytometer approaches based on fluorescence-activated cell sorting (FACS) and single-cell mass spectrometry became available for medium-throughput studies. flow cytometry, affinity assays, imaging, mass spectrometry, microfluidics and other technologies that enable analysis of proteins at the single cell level
In recent years single-cell RNA sequencing technology has grown rapidly. These techniques rely on the conversion of RNA into complementary DNA, which is then amplified to obtain large enough quantities for sequencing. Single-cell RNA technology often known as Transcriptome profiling of single cells in their natural environment depends on especially precise and non-invasive RNA capture methods. Transcriptome in-vivo analysis (TIVA) tags enable capturing of mRNA upon photo-activation from single cells in a live environment. Due to no damage to the cell or no tissue deformation during the procedure the application of TIVA technology is expanding when compared to laser capture micro-dissection and patch pipette aspiration techniques. Single-cell RNA technology can be used in many biological fields, from basic research to clinical applications for stem cell differentiation, embryogenesis, whole-tissue analysis and oncology.
The single-cell analysis technology is best fit for cancer research, stem-cell analysis, cell characterization, immunology, gene variation, diagnostics and prognosis, therapeutic antibodies and biologics, microbiology. The analysis of single-cell biology has significant challenges including, difficulty in isolation and separation of single cells, platform sensitivity, lengthy – time of cell culture and sample throughput. However, developing new techniques that have the ability to overcome these limitations are driving the interest in researcher particularly in single-cell genomics.
Advanced tools are enabling researchers to explore individual cells with clarity by allowing RNA and protein expression levels to be simultaneously analyzed. BD AbSeq conjugates enable simultaneous detection of protein and mRNA expression in a single experiment, this assay combines genomics and immunology technologies to facilitate even deeper single-cell analysis insights and enables high-parameter interrogation of cell-surface protein markers in a single panel.
Government funding and research grants are booming the single-cell analysis market. For instance, in September 2018, Celldom received $1.5 million grant from the National Institute of Health (NIH) to develop a single-cell analysis platform to analyze heterogeneity in cell populations for research and drug discovery. Similarly, in August 2018, Welcome Trust granted $8.2 million to Human cell atlas for the mapping of every single cell type in the human body.
According to IQ4I analysis, The Single-cell analysis market is expected to grow at the double-digit CAGR from 2018 to 2025 and expected to reach $3.5 billion by 2025. Geographically North America accounted for the largest revenue owing to the increase in government funding and increase in R&D investments. The Asia Pacific is expected to grow at a faster rate in single-cell analysis market.
The companies playing a major role in single-cell analysis market are Thermo Fisher Scientific (U.S.), Illumina Inc. (U.S.), Qiagen N.V. (Netherlands), Becton Dickinson and Company (U.S.), Danaher Corporation (U.S.), Bio-Rad Laboratories (U.S.), Agilent Technologies (U.S.), Fluidgm Corporation (U.S.), Merck KGaA (Germany) and others.