We've updated our Privacy Policy to make it clearer how we use your personal data. We use cookies to provide you with a better experience. You can read our Cookie Policy here.


The Future of Single-cell Genomics is Here

Listen with
Register for free to listen to this article
Thank you. Listen to this article using the player above.

Want to listen to this article for FREE?

Complete the form below to unlock access to ALL audio articles.

Read time: 3 minutes

The field of single-cell genomics is advancing rapidly and is generating many new insights into complex biological systems, but conventional methods for isolating nucleic acids from an individual cell can present technical challenges and be financially limiting. Researchers are often left needing to compromise on performance, workflow simplicity and cell throughput (due to cost of sequencing). 

Thankfully, there is hope on the horizon in the form of new technology. BD Genomics recently announced an early access program for the BD Resolve™ Single-Cell Gene Expression platform. This system has the flexibility to capture and analyze hundreds to tens of thousands of individual cells in a broad range of sizes and types. 

To find out more about this exciting technology and why it is set to transform the field of single-cell genomics, I spoke to Dr. Vivek Bhalla, Assistant Professor of Medicine at the Stanford University Medical Center. He has been utilising the technology to study the regulation of processes in the kidney as part of an early-stage pilot program. 

JR: First off, could you provide me with an overview of the research you are currently engaged in and how you came to be involved with the BD Resolve early access program?

We have several research projects on the role of the kidney in common diseases such as diabetes and hypertension. For the latter, we study the mechanisms and consequences of sodium transport in the kidney. Each nephron, or each functional unit of the kidney, has a filter followed by 14 unique, specialized segments of the renal tubule. Thus, you can imagine that to truly grasp how the kidney processes any solute, e.g. sodium, one needs to ask, ‘what is happening in each segment of the tubule?’ and ‘how do changes in one segment affect other segments?’. Up to this point, the technology has not been available to answer these questions about the tubule in a high throughput manner. Thus, our interest in single cell transcriptomics was born. It was at this point, that BD reached out to me to establish a collaboration ahead of the early access program because of our interest in the technology that they have developed.

JR: Why does the BD Resolve Single Cell Analysis Platform lend itself to your research? What have you been using it for?

We use the BD Resolve platform to understand what is happening in each specialized cell type with a given treatment. We utilized a very tractable model of a widely used medication that blocks sodium transport in one of these specialized tubular segments and are using the platform to understand how blocking transport in one segment affects other segments. We have data to suggest that different parts of the tubule proliferate and grow in response to this medication, and different segments respond differently. We can then use this unique platform to look at common signaling pathways for proliferation and growth (that are expressed in every cell type) and how they compare across different segments and how that might explain the different responses that we observe for each part of the tubule.

JR: In real-world terms, how has it helped to expedite your work?

This technology gives us unbiased insight into different gene expression pathways that are turned ‘on’ or ‘off’ in different segments of the tubule. To do this without the Resolve platform would require laser capture microdissection of a single nephron from each experimental animal. However, this newer technology offers several advantages. We now obtain single cell resolution of gene expression from the entire organ, not just a single nephron. We can also examine specific cell types within each segment of the tubule which is impossible with microdissection. For example, the distal tubule is comprised of four very important but different types of cells that are interdigitated throughout the end of the nephron. The single cell analysis platform allows us to dissociate an entire kidney tubule, use gene expression data to deconvolute the data and label each type of cell, and then compare the same pathways across the cell types.

JR: In your recent presentation at AGBT you highlighted three “key powers” of this technology.  Can you explain what these are and, why you believe them to be so important for the future of single cell analysis?

Firstly, this technology allows one to determine the identity of a cell based on its gene expression pattern and then categorize gene expression patterns by cell type. We demonstrated that for the kidney across 14 cell types, and we can also use this technology to define novel cell types based on expression. One can utilize this in other spheres of human biology, e.g. to understand the types of tissue infiltrating cells in inflammation or infection. In the kidney, for the first time, we can demonstrate how the population of different cell types can change with a disease or treatment. Importantly, one can also distinguish between increased expression of genes within a cell type vs. increased number of that cell type with equivalent expression.


Secondly, when studying a system such as the renal tubule, or the immune cell repertoire, or the brain stem, there are so many specialized cell types that investigations into cell type-specific gene expression is extremely low throughput. The Resolve platform provides a comprehensive gene expression matrix for as many cell types as needed, and are defined by their gene expression profile.

Finally, the technology at its core is RNAseq so whether by whole transcriptome amplification or targeted panels of sequencing, the breadth of data within one cell type is also gold standard.

Dr. Vivek Bhalla was speaking to Jack Rudd, Senior Editor for Technology Networks.