Lab Manager | Run Your Lab Like a Business

Ask the Expert

Innovations Driving Next-Generation Sequencing and PCR

J. Christopher Love, PhD, associate professor in chemical engineering at MIT, and Maroof Adil, PhD, postdoctoral researcher at the University of California, Berkeley, talk to contributing editor Tanuja Koppal, PhD, about advances in single-cell sequencing.

by Tanuja Koppal, PhD
Register for free to listen to this article
Listen with Speechify
0:00
5:00

 

Q: Is single-cell analysis a recent trend for sequencing applications?

A: The idea of single-cell analysis is not that new. Immunology is a field where single-cell technologies have been long recognized, and flow cytometry is a good example of a technology that has allowed us to examine different cells like T cells, B cells, and other components of the immune system that are defined by a set of protein markers or phenotypes. Traditionally, it was two to four markers, but now state-of-the-art technologies allow you to look at 16 to 32 different types of markers. Phenotyping with some of the advanced tools like mass cytometry allows you to look at 50 to 70 different protein markers to classify different types of cells. The advantage of using sequencing-based strategies for transcriptomics is an opportunity to look at thousands of different markers in a cell to examine their diversity and population with a much broader lens than what’s been possible before with other technologies.

Get training in Biosafety and Biosecurity and earn CEUs.One of over 25 IACET-accredited courses in the Academy.
Biosafety and Biosecurity Course

Q: Tell us about the Seq-Well technology that you have developed and what’s unique about it.

A: Seq-Well is a portable, low-cost platform for massively parallel single-cell RNA sequencing. A simple collection of laboratory supplies and a custom array of subnanoliter wells make it possible to isolate single cells from clinical biopsies and capture the mRNA for subsequent sequencing. The arrays allow co-localization of barcoded beads and cells and are sealed with a semipermeable membrane to facilitate lysis and hybridization. The arrays are chemically functionalized to enable the membrane to seal to the array and are molded silicone on glass. This low-cost system should facilitate studies of cells in a range of clinical settings and disease areas.Photo credit: Marc Wadsworth and Travis HughesThere have been a number of advances over the past three to five years in the ability to sequence DNA or mRNA from individual cells, as a way to understand genomic variants in cancer cells or to profile different populations of cells. Flow cytometry allows us to sort and sequence individual cells, but it is somewhat limited in throughput. If you wanted to look at thousands of cells, it could get very expensive on a per-cell basis. Over the past two or three years, a range of technologies has emerged for single-cell RNA sequencing that allows you to process thousands of cells at a time. Some of the first examples are oil and water emulsion systems that allow for the encapsulation and isolation of cells, along with reagents for capturing and sequencing the mRNA from the cells using barcodes. These tools require an instrument to facilitate the microfluidics set up and for processing of the samples, which limits access in certain locations, such as clinical research labs or biosafety level 3 (BSL-3) facilities, where containment is required.

One of the inspirations behind the Seq- Well platform was to facilitate better access in some of these more complicated research environments. For example, when working with tuberculosis samples in a BSL-3 facility or with clinical samples of HIV infections in South Africa, it would be helpful to have a portable technology that allows for the capture of information quickly and efficiently. The Seq-Well platform is based on a single microfabricated chip—it’s a lot like an ice cube tray for cells. There are very small containers to isolate both cells and reagents, in this case beads, to capture individual transcripts from the cells. The key insight was learning how to apply a semipermeable membrane in a reversible manner onto these arrays. It’s like putting a sticker that has holes in it on top of an ice cube tray. Doing this allows us to move reagents in and out of the array of wells to lyse the cells and capture them, and later we can remove the membrane to recover the beads for sequencing. So all we need is the chip, the membrane, a clamp to hold them together, a manipulation tool like a pipette, and some reagents. This is portable and very accessible, and we hope to offer this type of technology to labs that are interested in clinical research.

Q: Can you describe what this chip looks like and how it can be improved?

A: The chip that we are working with right now is similar to a 1x3-inch glass slide and we can vary the number of wells in the array. A typical experiment has 85,000 to 100,000 wells per array, which allows us to capture between approximately 1,000 and 20,000 cells efficiently with limited dilution. One of the features of this new platform that we found beneficial is the high recovery of cells when you have access to very sparse clinical samples, like cytobrushes and tissue biopsies, that can have a very small number of cells. By applying the cells to these arrayed wells, we can get better than 70 percent capture of cells from the clinical sample. Single-cell RNA sequencing relies on the efficient capture of the transcripts that are released from the cell, and that requires that high-quality reagents or beads be used. So there’s certainly an opportunity to improve the quality of the beads that are used.

For Seq-Well, the opportunity to link information from other types of assays, such as imaging, dynamic measurements, or functional assays, with transcriptomics would make it quite transformative. Let’s suppose we identified allergen-specific T cells in the context of peanut or other food allergies; then understanding the features of those cells in terms of how they behave and linking that to their transcriptional state would be very interesting. Of course, scaling the technology to make it very broadly available is also an area of interest for us. In our recent paper, we’ve included a link to the website that explains a lot of details on how to implement the assay (http://shalek.wpengine.com/ seq-well/). We hope that this type of tool can be used broadly in labs by people who may not be experts in single-cell technology development.

Q: How do you deal with variability in single-cell analysis when each cell is different?

A: One of the challenges with rare and special events is that they are more subject to variability and noise in measurements. People usually think that they can analyze only a few cells, but in reality, with new tools and techniques, you want to measure thousands of events. For instance, when looking at allergen-specific T cells that might be one out of about 10,000 cells, we want to measure several tens of thousands of events, if not hundreds of thousands of events, to accurately identify cells within the mix. Sequencing costs continue to drop, so being able to increase the number of cells that you can look at in each assay is going to be an important feature for single-cell technologies.

J. Christopher Love is an associate professor in chemical engineering and a member of the Koch Institute for Integrative Cancer Research at MIT. In addition, he is an associate member at the Eli and Edythe L. Broad Institute and at the Ragon Institute of MGH, MIT, and Harvard. Dr. Love received his PhD in physical chemistry from Harvard University in 2004. He extended his research into immunology at Harvard Medical School from 2004 to 2005 and at the Immune Disease Institute from 2005 to 2007. His research centers on using simple microsystems to monitor cells from clinical samples of chronic human diseases and on developing new approaches to manufacturing biologic drugs efficiently and affordably.

Applications for Single-Cell Sequencing

Maroof Adil, PhD, is a CIRM postdoctoral fellow at the University of California, Berkeley, in Dr. David Schaffer’s lab, where he works on stem cell technologies and biomaterials for regenerative medicine. He is using biomaterials to expand and differentiate human pluripotent stem cells into neurons to understand neurodevelopment and for regenerative medicine in the treatment of Parkinson’s disease, Huntington’s disease, and spinal cord injury. He is interested in understanding stem cell heterogeneity to further his research.


Q: For what projects have you used single-cell sequencing technology?

A: One of the projects that I am working on revolves around large-scale expansion of human pluripotent stem cells. This is motivated by the fact that human pluripotent stem cells, with their ability for infinite self-renewal, can potentially be an unlimited source of cells for a range of biomedical applications, such as cell replacement therapy, drug screening, or in vitro organogenesis. Many of these applications typically require the reproducible generation of a large number of target cell types. However, stem cell cultures are often heterogeneous. We are using single-cell RNA sequencing to investigate population heterogeneity within human pluripotent stem cells cultured in the lab.

Q: What has been your experience with single-cell sequencing, in terms of its pros and cons?

A: Single-cell RNA sequencing is undoubtedly a powerful technology that can provide a high-resolution snapshot of the population distribution within a biological sample. The present technology is easy to use and provides sequencing results in a matter of two or three days. At least for us, more time is spent in culturing the cells than in preparing samples and getting the data. However, as with most current single-cell technologies, it may be difficult to detect rare, minimally expressed transcripts. With the current setup, preparing large numbers of samples (>10) simultaneously can also be challenging. Automation of the library preparation steps could certainly facilitate high throughput analysis. Also, advanced bioinformatics tools and faster processing power could help keep up with the big data generation.

Adopting Adaptive PCR

F.R. (Rick) Haselton, PhD, professor, and Nicholas Adams, PhD, research assistant professor in the Biomedical Engineering department at Vanderbilt University, are working together to create user-focused diagnostic tools for infectious diseases and address the bottlenecks of getting these technologies into the hands of the people who need them most. Most recently, they worked together to use DNA enantiomeric structures as a means to more simply and accurately control PCR cycling, which has led to the creation of a new technique called adaptive PCR.


Q: Can you draw comparisons between traditional and adaptive PCR?

A: Traditional PCR relies on indirect temperature measurements, thermal calibrations, and cycling programs to achieve the PCR. In contrast, adaptive PCR directly monitors the critical DNA interactions during the reaction using fluorescently labeled L-DNAs. Cycling conditions therefore adapt to the thermal and chemical environment. Consequently, the instrument does not require the upkeep and operation constraints to maintain the thermal calibrations. This enables the development of less expensive, simpler, and more robust thermal cycling instruments.

Q: Where do you see adaptive PCR being used?

A: Our primary interest is in developing robust instruments and reagents for performing PCR outside the traditional laboratory environment. Although the simple and low-cost instrument design would have obvious benefits in the laboratory, we think the real appeal of adaptive PCR is for field applications, such as infectious disease diagnostics.

Q: What are some of the limitations of this new technique?

A: There were a lot of unknowns that had to be sorted out before we developed adaptive PCR. Since there weren’t any commercial instruments that were programmed to control thermal cycling based on fluorescent inputs, we had to build the system from the ground up. Also, it was unknown whether L-DNAs could be used to monitor and control the reaction. The pros are that the system is very robust and performs well under difficult-to-control environmental conditions and for unprocessed samples. The limitations are that the system is still very early in development and there are no commercial instruments that support adaptive PCR. We have started a company called Mirror Molecular to commercialize adaptive PCR and make it available to researchers and clinicians. Currently, our prototype runs a single sample at a time, but we plan to develop an instrument capable of analyzing multiple samples at once. Another research-focused application is to use the technique to amplify and produce quality DNA products for sensitive sequencing techniques.