In recent years, microfluidics has been increasingly applied to applications across the materials sciences and chemistry fields. The biology sector however has been slower to embrace this technology – often due to the inconvenience of the systems requiring scientists to become experts in microfluidic set-up. With increasing numbers of commercially available, easy-to-use instruments, this is now beginning to change, driving the research specifically in the single cell market to understand cell diversity and tissue heterogeneity, as well as allow the quantification of gene expression at the single cell level.

Our understanding of single cells in the human body, how they differ throughout development or disease within or between patients, and how this knowledge can be applied to personalised medicine, is still in its infancy. It was not until 2015, when high throughput single cell applications based on microfluidic droplet technology were first published, that we were able to start scratching the surface of this exciting new area.1,2 Already, single cell RNA-Seq (scRNA-Seq) methods have increased our knowledge of cell development, immunology and immunotherapy, as well as tumour heterogeneity, lineage analysis and clonal evolution.3,4,5,6


Technology advances and novel applications

One of the key drivers of the acceptance and widespread use of high throughput scRNA-seq has been the commercial availability of easy-to-use microfluidics-based droplet instruments. These systems enable scientists to encapsulate tens of thousands of single cells together with barcoded oligo beads in a matter of minutes. The mRNA of each cell is captured on a single uniquely barcoded bead, reversed transcribed and prepared for sequencing. The use of the uniquely barcoded beads allows each sequencing read to be associated with its original cell, thus empowering transcriptome analysis of thousands of cells at the single cell level.

While this technology is maturing, scientists have begun to transfer the approach from use of single cells to the use of individual nuclei as a proxy for a whole cell. This approach now offers scientists the ability to study gene expression of cells that are difficult to isolate, such as brain cells, as well as cells obtained from archived tissue, potentially opening this technology up for clinical studies.7,8

Another area of interest is the ability to characterize and understand the immune system at a cellular level. Single cell technologies hold the potential to fully identify the range of cell types and states involved in immune responses, as well as to increase our knowledge of immune cell development and differentiation.9 New scRNA-Seq technologies overcome previous technical limitations, such as only being able to analyze a select few RNA molecules at one time, which hindered its use in immunology research.4 Improved sensitivity, reproducibility and throughput now ensure individual immune cells can be profiled at a higher degree of accuracy and in high numbers. It is, for example, now possible to identify tumour-associated macrophages that are crucial to determining tumour fate.10 Researchers are also looking into immune cell states and the immune cell activation for the discovery of genes that act as drivers for immune cell activation and responses.9,10

Aside from scRNAseq, other technologies that enable investigation of not only transcriptomic, but also genomic, epigenetic or proteomic cell targets or interactions are now increasingly applied to single cell studies. Methods such as CITE-seq, CNV analysis or ATAC seq are already available as standard protocols and applications on some commercial systems, or are in the process of being developed.11,12,13


Mapping the human cell atlas

The rapid advances in single cell technology have revolutionised our understanding of single cells and their role in health and immunity. The Human Cell Atlas (HCA), an international collaboration project that launched in 2016, has set out to create a comprehensive reference map of all human cells and their function within the body, and use this knowledge to understand human health as well as diagnosing, monitoring and treating disease. While an ambitious project, with the availability of easy-to-use tools and instruments for high throughput single cell research, this is now becoming an achievable goal, and will enable the identification of cell types and markers in diseases like cancer to facilitate drug development, treatment approaches and ultimately personalised healthcare.



The single cell market is young and fast moving. As new protocols and applications are developed, the widespread availability of flexible, automated and easy-to-use microfluidic-based droplet systems is crucial to support the ever-growing list of applications enabling further insight into cell diversity throughout development or disease.


Heike Fiegler, VP of Biology Products, Blacktrace Holdings Ltd



  1. Macosko, E et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell, 2015, 161, 1202-1214.
  2. Klein, A et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell, 2015, 161, 1187-1201.
  3. Treutlein, B et al. Reconstructing lineage hierarchies of the distal lung epithelium using single-cell RNA-seq. Nature, 2014, 509,
  4. Stubbington, MJT et al. Single-cell transcriptomics to explore the immune system in health and disease. Science, 2017, 358, 58-63.
  5. Patel, AP et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science, 2014, 344, 1396-1401.
  6. Navin, N et al. Tumour evolution inferred by single-cell sequencing.Nature, 2011, 472, 90.
  7. Habib, N et al. Massively parallel single-nucleus RNA-seq with DroNc-seq. Methods, 2017, 14(10), 955.
  8. Haque, A et al. A practical guide to single-cell RNA-sequencing for biomedical research and clinical applications. Genome medicine,2017, 9, 75.
  9. DeKosky, B. J et al. High-throughput sequencing of the paired human immunoglobulin heavy and light chain repertoire. Nature biotechnology, 2013, 31(2), 166
  1. Proserpio, V and Mahata, B. Single‐cell technologies to study the immune system. Immunology, 2016, 147, 133-140.
  2. Stoeckius, M et al. Simultaneous epitope and transcriptome measurement in single cells. Nature methods, 2017, 14, 865.
  3. Waldron, D. Technique: Single-cell CNV detection. Nature Reviews Genetics, 2016, 17, 128.
  4. Pott, S and Lieb, JD. Single-cell ATAC-seq: strength in numbers. Genome biology, 2015, 16, 172.