Accelerating Scientific Study With Scalable Single-Cell Sequencing
Accelerating Scientific Study With Scalable Single-Cell Sequencing
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Single-cell sequencing is becoming more widely adopted by researchers working in a variety of fields. However, with a range of technologies now available, it can be difficult to determine which approach is best suited to address their biological questions of interest. Previously, single-cell sequencing solutions demanded that researchers invest in expensive lab equipment to get started. Now, Parse Biosciences is on a mission to provide researchers with an end-to-end single-cell sequencing technology that utilizes only basic lab equipment.
Technology Networks recently interviewed Alex Rosenberg, co-founder and CEO of Parse Biosciences to learn more about the company and its novel approach to single-cell sequencing.
Laura Lansdowne (LL): How has the advent of single-cell sequencing impacted scientific study?
Alex Rosenberg (AR): Single-cell sequencing has transformed the way researchers study biology. With the ability to truly study biology at single-cell resolution, there has been an explosion of insights and discoveries across every field, including immunology, oncology, neuroscience and developmental biology.
To understand why this is the case, it is worth looking back at how things were done before single-cell sequencing. You used to take a complex sample, for example, a brain slice, and you were then forced to grind it up and take a single measurement which averaged across all the heterogeneous cells types present. This meant that you would miss any biological phenomena that are restricted to a single cell type. It turns out that a lot of biological effects and even diseases are in fact driven by a single or a few different cell types.
Now, with single-cell sequencing, researchers can pinpoint changes that occur to specific cell types in complex tissues. This has been transformative in understanding key mechanisms behind disease progression, as well expanding our understanding of basic biology.
Kate Robinson (KR): How does your transcriptome technology work and how is it helping to run single-cell experiments?
AR: Our approach to single-cell sequencing is fundamentally different from anything else out there because we use something called combinatorial barcoding. All other solutions isolate individual cells into compartments, which typically requires complex microfluidics. In contrast, we are able to uniquely label the molecules within each individual cell without actually having to isolate single cells.
Our approach is inherently more scalable and allows users to use it without any custom instruments. With our Single Cell Whole Transcriptome kits, you can sequence 100,000 cells and 48 samples, which is much more than any other product out there. The fact that there is no custom instrument also means savings in capital costs and allows users to get started immediately.
Another big advantage of our kits is the flexibility they offer. For a lot of applications, you might collect biological samples over the course of several weeks. With existing solutions, you would have to run a separate single-cell experiment every time you collect a new sample. With our kits, you can rapidly fix and store your samples upon collection and then run a single experiment with all these samples in parallel at a later time.
It is also worth pointing out that we originally demonstrated this approach in Science in 2018, but since then we’ve incorporated huge improvements into our Whole Transcriptome kit. The workflow has been streamlined and the sensitivity is dramatically improved. Users of our Whole Transcriptome kit see a huge increase in the number of genes detected per cell.
KR: Could you elaborate on the idea that this kit allows single-cell experiments without expensive lab equipment?
AR: I already hinted at it a bit, but by leveraging split-pool combinatorial barcoding, we allow researchers to profile single-cell transcriptomes without microfluidic instruments. By assigning a specific barcode to each well into which cells are loaded, we can take advantage of the cell itself as its own compartment. We repeat a process of splitting cells into wells, adding well-specific barcodes to transcripts in cells, and then repooling cells, eventually labeling each cell with a unique combination of barcodes. Other single-cell approaches require special equipment that use advanced microfluidics to perform single-cell partitioning and barcoding.
KR: How does the data produced from the kit differ to that generated using flow cytometry?
AR: One of the big limitations with flow cytometry is that you’re limited to measuring just a few genes per cell. This can work okay when you know exactly what you are looking for, but you're always going to be missing out on most of the biology in your sample. The great thing about doing single-cell sequencing with our kits is that you can measure expression across all genes in an unbiased manner. This degree of resolution allows you to detect more subtle differences between cells that you would miss with flow cytometry. With the scalability of our kits, you can still profile large numbers of cells and samples, just as you would with flow cytometry. I expect that in the next few years a large portion of the flow cytometry market will switch over to single-cell sequencing.
LL: What applications do you envisage the kit enabling in the future?
AR: Researchers working in several different fields, are already leveraging our kit through our early access program. Experiments have run the gamut — from immunology, oncology and neuroscience, through to developmental biology.
I’ll share an interesting example with you. Some of the researchers have been using our kits to study neurosciences across different species. In the past, comparative genomics has enabled researchers to learn about how the nervous system evolved, but a lot of the available tools have been restricted to understanding genetic differences between species at the DNA level. What we’re seeing is that researchers using our kit can actually learn how the nervous system has evolved at the cellular level. This is critical to understanding neural circuits and how some species may have adapted to their specific environments.
We’re seeing new applications of single-cell sequencing on a daily basis. Really, we are only now experiencing the first wave of single-cell sequencing adoption. Over the next five years, I think it’s safe to say that we’re going to see a huge boom of applications and published research leveraging this technology.