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GEN Protocols Expert Exchanges: Single-Cell RNA Sequencing-Challenges and Solutions
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GEN Protocols Expert Exchanges: Single-Cell RNA Sequencing-Challenges and Solutions
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ANJALI SARKAR: Hello, fellow scientists and science lovers. This is Anjali Sarkar, Senior Science Editor at GEN and GEN Protocols, welcoming you to today's Expert Exchange titled, "Single-Cell RNA Sequencing Challenges and Solutions." GEN Protocols is a premier resource for emerging and veteran scientists and entrepreneurs in biotech who want to know the nitty-gritty of advances in biotechnology from a trusted source. Researchers from academia and industry share their technical challenges and solutions on GEN Protocols, showcase their expertise, and nurture collaborations.
ANJALI SARKAR: You can share your methods and technical insights on GEN Protocols year round. Together with a rich resource of up to date methods and applications, GEN Protocols brings you expert exchanges where experts in key areas of biosciences talk about specific technical developments. In today's Expert Exchange, I will be talking to Irene Whitney, who is Director of Applications and Collaborations at Honeycomb Biotechnologies.
ANJALI SARKAR: Before joining Honeycomb, Irene was a postdoctoral scholar at Harvard University's Center for Brain Science where she used high throughput single-cell sequencing methods to understand mechanisms of cellular diversification during neural development and transcriptional responses to injury. In today's session, Irene will discuss current challenges and emerging solutions in single-cell studies, particularly in the context of capturing, preserving, and processing single-cell samples for RNA sequencing.
ANJALI SARKAR: Welcome to GEN Protocols, Irene.
IRENE WHITNEY: Hi. Thank you so much for having me. I'm excited to get to talk to the GEN Protocols audience today.
ANJALI SARKAR: We, too, are excited to have you. So to start off, could you tell us a little about your journey into the field of single-cell studies? And what was your first single-cell research project?
IRENE WHITNEY: Yeah, absolutely. I was really fortunate in the timing of my post-doc in the lab of Joshua Sanes, where we had the opportunity to collaborate really early on with Evan Macosko, who developed drop-seq, which was one of the first high throughput single-cell technologies. And at the time, it was not even well accepted that profiling the transcriptome of thousands of individual cells and then clustering them together based on their unique gene expression profiles could even be used to define cell types, let alone these molecular cell types would then correspond to cell type definitions based on morphology or sort of functional or physiological features.
IRENE WHITNEY: So we were really able to establish that there is a high degree of harmonization in cell type identities across these different modalities. And we did this for a well defined neuronal cell class in the retina-- bipolar cells. And so it's kind of cool for me now to see that, really, the field takes for granted being able to use single-cell profiling to generate things like cell atlases where you're defining the composition of different tissues, or organs, or organisms.
IRENE WHITNEY: So really just to see how far the field has come in applying these types of technologies. I think the other thing I'm also grateful for, during that time when I first got introduced to single-cell technologies, was having that experience of putting the parts together yourself, rather than working from a commercial product out of the box. And so that's been interesting to contrast that to my time at Honeycomb Biotechnologies.
IRENE WHITNEY: So we're a single-cell genomics company and really being a part of that huge task of taking a technology developed in academia-- so in our case, Seq-Well developed at MIT by our academic co-founders-- and then transforming that into something that's a robust, reliable, and user-friendly commercial product. So I'm really fortunate that I've gotten to have the whole arc of the process, from the start of a new technology to something that is at the complete other end being a commercial product.
ANJALI SARKAR: Definitely. And I'd like to hear more about the technologies being developed at Honeycomb. But before we go into that, what are the nuances that exist in working with different cell types in the single-cell research field? Specifically, what are the challenges that researchers face in undertaking single-cell studies when the cell type is, say, more fragile than normal, such as neutrophils, or are structurally unique, like neurons with long processes?
ANJALI SARKAR: If you could enlighten us a bit on that.
IRENE WHITNEY: Yeah. I think it's sort of universal for any single-cell RNA seq technology that, before you get started, the first hurdle is going to be sample preparation and the ability to generate samples that have really high viability and have been prepared in a way that they accurately represent the composition of that starting material or tissue. So for me, one of the challenges during my academic career was trying to prepare these single-cell suspensions of adult neurons, which are particularly finicky and fragile, especially for getting high quality RNA out of them.
IRENE WHITNEY: So it really took us a long time. I don't want to say how much of my postdoc I spent optimizing our sample prep workflow and combining that with a single-cell platform in order to generate high quality data. And I think now, to address this, you're starting to see multiple new products being offered in the automated tissue, dissociation space, right? So trying to create more standardized methods of dissociation, remove that kind of variability that can happen in the process, whether it's like site or user, different hands, things like that.
IRENE WHITNEY: So really having that good sample prep is required for any successful single-cell RNA seq study, though we know that this is not always enough. Even if you've successfully generated a high quality single-cell suspension, as you mentioned a second ago, not all cell types are robust enough to be recovered on some single-cell platforms, especially those platforms that require microfluidics for droplet formation during the isolation of single-cell.
IRENE WHITNEY: So this can exert harsh shear forces that can damage or destroy fragile cell types. You mentioned neutrophils, eosinophils, basophils. These are some of the ones where we've seen that are quite susceptible depending on the type of platform that you're using. Whereas instead of droplet-based but working more with a nano or picowell-based technology, they don't necessarily have that same type of challenge when isolating single cells.
IRENE WHITNEY: Those types of technologies have a much gentler process, relying primarily just on gravity to capture cells on individual wells. So kind of a balance there of what cell types and what tissue types are you working with, how do you prepare the sample robustly, and then making choices about what platform or what technology is going to fit best with what you're trying to recover.
ANJALI SARKAR: It's interesting that you mentioned the automation of tissue dissociation to get single-cell samples. I was wondering, what does the need for automation in these single-cell studies, what kind of additional challenges do you think that poses in the single-cell field?
IRENE WHITNEY: I think from the dissociation side, I feel that there is a lot of distance still left to go because there is a lot of optimization that needs to happen for every different tissue type or sample type. They're not all going to be treated the same or treated equally. In terms of automation on the single-cell processing and library prep side, I think people are taking a lot of efforts in order to figure out how to do that in a more high throughput way.
IRENE WHITNEY: And so I think that's maybe a little bit further along than the automation of tissue dissociation.
ANJALI SARKAR: So once you've dissociated the tissue and managed to collect your single cells, what are some of the most widely used ways of capturing, preserving, and processing these single-cell samples for applications like RNA seq?
IRENE WHITNEY: Yeah. I think I've probably touched on the two most common technologies already in terms of droplet or nanowell based. But in general, most single-cell technologies rely on a bead to start with, isolating a single cell together with a single bead. The bead is coated in oligos that are designed to capture all the transcripts once the cells are lysed, and then also add a barcode onto those captured transcripts that's unique to each cell, right?
IRENE WHITNEY: So this is nice, it allows for pooling all of those captured materials together for any subsequent library preparation. So the high throughput isolation-- so when we're talking high throughput methods for isolation and capture of single cells and single beads together-- is most commonly achieved, these days, I think with either droplet-based or nanowell-based technologies.
IRENE WHITNEY: I think we're seeing some more recent advances in the space where these technologies are now starting to come in two different flavors, I would say. And that's with and without specialized instrumentation that's required for that capture. Now if you don't want to or can't immediately process what you've captured for your single cells, either because you can't do it at the same time or the location is where the sample was captured, most single-cell technologies do require some kind of upstream storage or preservation method.
IRENE WHITNEY: And so you're sort of asking about the preserving side of the workflow. And I would say the most common method there is cryopreservation for single-cell suspensions, and then storage in liquid nitrogen. Maybe a little less common is the fixation of single-cell suspensions with either formaldehyde or methanol-based solutions. And then alternative to that, you can see people freezing whole tissue prior to doing any kind of dissociation and using those approaches as the common ways for trying to preserve single-cell samples before moving on with RNA seq.
ANJALI SARKAR: Just to clarify, the beads that you mentioned earlier, do you mean magnetic beads?
IRENE WHITNEY: So there are some technologies that I believe do have magnetic beads for their transcript capture. This would be different-- what people often think of as magnetic beads is when you're doing library cleanup steps and you're using SPRI beads for cleaning up your library. So this is different than that. So for capturing transcripts, technologies often rely either on a gel-based bead or a polystyrene type of bead that's been designed to be coated in oligos for that transcript capture of live cells.
ANJALI SARKAR: And you mentioned just now that the idea or the notion of freezing the entire tissue prior to isolating single cells at a later point in time. Could you talk a bit about the challenges of this, considering that a lot of cells lyse or are lost during the thawing process? What kind of challenge does that pose?
IRENE WHITNEY: Yeah. No, it's a really important question. And it relates back to what we were talking about a second ago in terms of, it all starts with sample preparation. And so if sample storage is part of your workflow, that's going to impact your sample preparation and your sample quality. So each of those common storage methods that I just mentioned, each have different drawbacks in terms of the quality of the subsequent single-cell RNA seq data.
IRENE WHITNEY: So with cryopreservation, this often requires high numbers of starting cells, in the millions, in order to have effective recovery after thawing. So it's not really an option if you're working with sparse samples. And then even if you do start with more abundant samples, it's not unusual or unexpected to see a 50% loss of the number of cells after you thaw before going into your single-cell platform.
IRENE WHITNEY: And I think that type, the cryopreservation as a storage method, is also really highly subject to batch effects, even when receiving cells from a commercial vendor. So at Honeycomb, we had this challenge during the beta testing of our HIVE single-cell RNA seq solution. So we wanted to provide all of our beta sites around the world with the same samples so we could get an ideal comparison of the performance of the HIVE in their hands.
IRENE WHITNEY: And so we provided them with commercially acquired, cryopreserved splenocytes. And we ended up seeing this huge range in the viability of these samples after thawing before they could even be loaded into the HIVE. And now we've also even seen that there are some cell types that are more sensitive to cryopreservation and are disproportionately damaged or destroyed.
IRENE WHITNEY: So you end up significantly altering the composition of a sample due to storage. I also mentioned fixation, so using formaldehyde or methanol-based reagents for that. And I think we see that second most to cryopreservation, I think largely because there's some concerns for negative impacts of these solutions on the quality and the recovery of RNA after fixation. And then, yeah, you also asked about just freezing whole tissue as a solution, if you want to collect in one site, freeze it, ship to another, and then move on with the rest of your workflow.
IRENE WHITNEY: The problem with whole tissue and freezing is it eliminates your ability to dissociate a sample into a single-cell suspension, rather you could only take frozen tissue and then dissociate it into single nuclei, which only have a fraction of the total RNA in a cell that's then available to be recovered. So you're taking a hit on the amount of data that you can recover if you're starting with frozen tissue.
ANJALI SARKAR: Of course. So you mentioned this comparison that you did in your beta testing phase. Could you tell us a bit more about how your proprietary HIVE seq technology at Honeycomb compares to, say, the droplet and picowell-based technologies that are commercially available?
IRENE WHITNEY: Yeah, sure. So the HIVE is a picowell-based technology. So it doesn't rely on droplets or microfluidics for capturing single cells. And I think one of the things that we've focused on a lot is, is there a way to incorporate sample storage into the workflow where you don't have that same kind of loss of data quality or loss of sample like these other examples we just talked about? And so with the HIVE, after you load your single-cell suspension into the HIVE, you have the ability to add a cell preservation solution that doesn't have any harsh cross-linking fixatives or anything like that and where you can stably store cells in the HIVE and then ship them to another location, or store them and process them later with the rest of the workflow for making your single-cell libraries.
IRENE WHITNEY: So we've now been able to see data out to nine months of storage where you're able to generate single-cell data that looks equivalent if you had the ability to work with fresh samples. Fresh is what we think of as the gold standard in the single-cell RNA seq field in terms of sample quality and data quality.
ANJALI SARKAR: You mentioned this gentleness and getting a bit closer to this, the gentleness of the procedure. Comparing it to these formaldehyde fixations that you mentioned earlier, are these harsher methods really compatible? Or how compatible are they with downstream RNA seq? Does that affect the sequence readouts in any way?
IRENE WHITNEY: Yeah. I mean, I think these are the important kinds of questions someone has to ask any time they're getting started with a single-cell experiment where there isn't a universal solution, right? There has to be compromise somewhere. And depending on what your experimental logistics are and what the data is that you need to generate to answer your biological questions, that's going to drive, what [AUDIO OUT] are you more comfortable making?
IRENE WHITNEY: So if your sample collection logistics is that you're getting in a clinical sample late in the day, you don't have time to take it all the way through processing and library prep, and so if you end up using a fixation method or something like that, you have a better workflow, but you might see an impact in the data quality, right? So if this means that you're not recovering the same kind of transcripts that you would if you didn't have to use fixation.
IRENE WHITNEY: So I think it's all a balance. There's no perfect solution. And like I said, there's no universal solution. It's all about which platform, which storage method, which technology is right for you. And I think even with the HIVE, we don't think that we have created the magic bullet, right? It's more about enabling people that are trying to work with distributed collection sites or time courses and maybe have more fragile cells and things like that.
IRENE WHITNEY: So it just depends on what you're trying to accomplish.
ANJALI SARKAR: So in future versions of the HIVE technology that you've developed, what are the areas that you think this technology needs to improve in?
IRENE WHITNEY: Yeah, that's a good question. I think we've been talking pretty much just about RNA, right? And I think our technology, along with all the other ones that you're seeing emerging in this field, needing to step into that multiomics space where you're adding on other layers of types of data in addition to RNA. And so that's something that we think about a lot in terms of what's important for people in being able to achieve their research and what they're working on.
IRENE WHITNEY: Yeah.
ANJALI SARKAR: OK. Yeah, we'll definitely come back to the multiomics perspective to look at it a bit more. But before that, you mentioned all these challenges in transporting the single-cell samples further upstream into tissue samples or long distance or long term storage. Could you talk a bit about the limitations of these different technologies in the context of cell viability after thawing as well as the diversity of the transcriptome seen in post hoc studies?
IRENE WHITNEY: Yeah. I mean, I think like I was talking about earlier in terms of, for example, working with cryopreservation where you can really see a negative impact on sample viability, we've seen that the longer duration that a sample can spend being stored by something like cryopreservation, especially if you are starting maybe from a less ideal sample, that kind of viability or that kind of sample quality can continue to degrade over time.
IRENE WHITNEY: Rather than being stable and trying to be able to have different logistics or different experimental setup where, maybe, you do need to have some kind of long time course or a longitudinal study or things like that where you want to batch your samples, store them stably, and then generate your single-cell data all together, batched together at the end of the study. And so if your method for storage continues to take a hit in data quality, the longer and longer that goes out, the more you end up having to compromise on the ideal setup for your experiment.
ANJALI SARKAR: Definitely. So how do today's single-cell RNA sequencing solutions improve upon the existing technologies, do you think?
IRENE WHITNEY: I mean, I think one I touched on briefly already, commenting that for both droplet and nanowell-based technologies where we're starting to see this trend and there being two different flavors-- with and without specialized instrumentation. So I think we're seeing development of more instrument-free single-cell solutions. So you don't want to have constraints on where and when you do your experiments. So Honeycomb has done this as well with the HIVE, which it's just a disposable handheld device, as we talked about before, that's using picowells instead of a microfluidic droplet-based approach.
IRENE WHITNEY: And then I think we've been recircling back around the other major limitation that we're starting to see improvements around, and that's the current sample storage methods. And obviously, that's been a big area of focus for us. We really had the benefit of getting input from some of our early pharma collaborators when designing the HIVE so that we could take their input and incorporate it into design choices that make it ideal for things like distributed studies where it requires the ability to stably preserve a single-cell sample for shipping and storage over an extended period of time.
IRENE WHITNEY: So like I talked about before, we addressed this particular challenge with our cell preservation solution. And so I think that having the instrument-free and the ability to store samples is really what opens up a lot of access and opportunities to using single-cell technologies in areas where maybe the solutions that existed didn't enable high enough quality of data to be generated.
ANJALI SARKAR: Just so that I'm clear, I'd like you to repeat this point that you had mentioned earlier of the increase in shearing that you see with microfluidic techniques as compared to picowell-based techniques, including the HIVE solution. So the reduction in the shearing that you see with the picowell technique is due to both the picowell per se as well as the buffer. Is that it, or are there other nuances in the strategy that enable this lack-- or reduction in shearing?
IRENE WHITNEY: Yeah. It's actually just a simple design of working with picowells and how you isolate and capture single cells in a well, as opposed to how you isolate and capture single cells in a droplet. So droplets-- some droplet technologies require, like we've been talking about, microfluidics. So you've got a chip that you're flowing your samples through, along with things like oil and reagents.
IRENE WHITNEY: And in order to push all of those things through the chip and create the droplets, like we've mentioned, there are these shear forces that get exerted during the process. So it's a very active process for isolating and capturing cells. When you're working with nanowell or picowell-based technologies, it's very passive in terms of how do you isolate and capture that single cell, where you oftentimes only need just the force of gravity in order for a cell to settle down into the bottom of a well, right?
IRENE WHITNEY: So that's what I'm referring to when I'm talking about a much gentler process, where it's much more passive and you're not exerting these additional forces as part of the isolation method.
ANJALI SARKAR: Excellent. Thank you for that. And what are some of the challenges in scaling up the sample number for current single-cell approaches? And in the context of that, could you also talk about controls used for studies in both a smaller scale as well as when you scale up your experiments?
IRENE WHITNEY: Yeah. I mean, I think talking about scaling up also brings us back to this point we've talked about a couple of times now, which is constraints of working with a platform that requires specialized instrumentation. So a lot of times, the throughput on those types of platforms is relatively low, like the number of samples you can run in parallel at once. Whereas with the HIVE and other instrument-free solutions, you have a lot greater flexibility.
IRENE WHITNEY: You don't have a set number of ideal samples to run at once. With the HIVE, because each device is its own individual entity, you can run as few or as many in parallel as you want. So for example, our R&D team, it's not unusual for them to do 24, 48 samples in parallel. And then-- sorry, I think I'm trying to remember the second half of your question in terms of scaling up for single-cell technology.
ANJALI SARKAR: The question was around what kind of controls would be involved--
IRENE WHITNEY: Oh, right. Thank you. Yes. Thank you. Thank you for that. Yeah, that's something that's interesting and it's come up a lot, especially in some of the conversations that we've been having with lab service providers or CROs, where they have customers that want to ship them samples for single-cell sequencing and them wanting to have some kind of internal control so that they can show their customers, oh, there might have been something wrong with your sample, but our processes for generating the data were robust.
IRENE WHITNEY: So something that we've developed that's specific to our library prep workflow are these molecular controls, where they basically can be inserted at different points in the library prep workflow and run in parallel with regular samples. And so when you get to your QC step at the end, and you want to say, OK, does my single cell library look good, is it the right concentration, are the fragment sizes in the right range?
IRENE WHITNEY: And for whatever reason, if something doesn't look good with your library QC, you can look at the different multiple controls we have and have a pretty good idea where something might have gone wrong in the workflow. So for a standard user who's working with the same sample type over and over again and things like that, we would recommend only working with these controls in the very beginning when you're new to the technology.
IRENE WHITNEY: But if you're a very high throughput user, something like a CRO where you've got so many samples coming through and you want that assurance that you're executing the library prep, including those controls, more routinely, would be something that we would recommend and see as being beneficial.
ANJALI SARKAR: Great advice. Thank you. And you already mentioned multiomics and the expansion of Honeycomb's technology in the future into encompassing multiomics approaches. But as you see single-cell technologies expanding into multiomics, what types of other single-cell data in addition to RNA sequencing data do you see critical for clinical research?
IRENE WHITNEY: Yeah. I think there, there's a relatively straightforward path, I think, in just seeing what has proved valuable when working at a bulk level and then applying that with single-cell resolution. So the few that I think are most essential moving forward is being able to have protein expression in addition to RNA. I think the other one, especially in the clinical setting, having T-cell receptor and B-cell receptor repertoire profiling, especially more in the immunology space.
IRENE WHITNEY: When you're talking more in the oncology space, things like ATAC for looking at chromatin accessibility and being able to layer all of those additional assays or type of data on top of RNA and then providing a lot more granular resolution for cell types and even cell states. I think one area that's interesting is with protein expression. Right now there's more limitations there, really only being able to have visibility on expression of extracellular proteins.
IRENE WHITNEY: I think something that's interesting to watch in this space is seeing steps that people are starting to take in expanding this capability for looking at intracellular proteins as well. So I think that's something that's going to be interesting to see how that evolves.
ANJALI SARKAR: Definitely. Considering the finickiness of techniques that are involved in proteomics that require very gentle handling of samples for one to visualize the protein at the end-- be it hydrophobic, transmembrane proteins, or intracellular, as you were saying-- do you think that the current technologies, including Honeycomb's technology for single-cell capturing and preservation, are close to achieving that kind of gentle storage that will allow intracellular proteins and hydrophobic proteins to be also detected along with RNA in multiomics approaches?
ANJALI SARKAR: Or do you think we still have a long way to go?
IRENE WHITNEY: I don't know. I think that's a good question. So I don't think that my background allows me to speak with enough certainty on that. Although one thing that, as I've understood it to be, especially when trying to get intracellular proteins, is that it's actually not necessarily an issue of gentleness. But because you're trying to get intracellular proteins, that needing things that are more robust in order to break things apart and capture those intracellular materials.
IRENE WHITNEY: One thing that comes up a lot in conversation-- again, coming back to this idea of different technologies are going to have different benefits, different drawbacks. And there's a lot of great things about working with droplet-based technologies. I used droplet-based technologies from my whole postdoc. Working with readily available fresh tissue, things like that, it was beneficial.
IRENE WHITNEY: But there are constraints when you're working with a droplet because you're trying to fit in a lot of reagents that have a lot of different things that they need to do in terms of lysing a cell, capturing transcripts, starting to do some first strand synthesis, things like that. But droplets themselves have physical constraints on being able to be formed and be maintained. And so as you start to play around with trying to capture and recover different compartments or components of a cell, with a droplet, you have to work with the physical constraints of maintaining that droplet formation.
IRENE WHITNEY: With the HIVE, it's a little bit different than other picowell technologies. So the way I described it before is you're having these cells captured into individual wells. And the way the HIVE is designed, it comes preloaded with those transcript capture beads that we already talked about. They're in each of the wells. But you still need a way to create an individual isolated compartment.
IRENE WHITNEY: Like with a droplet, you need to do the same with a well. And the way that we do that with the HIVE is we apply a semipermeable membrane to the surface of the array and seal it on there. And that's what gives you your individual reaction chambers, if you will. And the design of the membrane is such that small micromolecules can be applied in bulk to the surface of the membrane and diffuse through, diffuse into the picowells.
IRENE WHITNEY: But then your larger macromolecules-- your RNA, your protein, things like that-- are going to be too big to diffuse out, so that's what gives you your single-cell resolution. But the semipermeable membrane, that's going to be more robust than something like a droplet in terms of creating those isolated reaction chambers. And so that does give us a little bit more flexibility in terms of the solutions and reagents that we can be applying to our system in terms of trying to recover different things from cells.
ANJALI SARKAR: And as we wrap up, I'd like to ask you, once we develop a new technology such as these single-cell technologies, there's always talk about how these are being applied in medical/clinical research, biomedical research, and particularly personalized medicine. So in your opinion, what impact are single-cell studies having on health care and medicine currently and in the years to come?
IRENE WHITNEY: Yeah. No, that's definitely a big topic of discussion here as we try to understand. We're at this phase where single-cell technologies have been well established in academia, and now we're starting to see them move and transition into biopharma, into the clinical space. I think we'll see this evolve over a few phases, right? So you can think maybe starting first with the use of, maybe, clinical samples to generate single cell data as more discovery and development-based efforts, so helping to reveal new biology, identify new biomarker profiles, and then to progress this type of knowledge so that maybe it can be applied to clinical trials for patient stratification or determining what the appropriate drug combinations should be matched to a patient-specific tumor heterogeneity or defining what differentiates responders from nonresponders over the course of a trial.
IRENE WHITNEY: And then I think, finally longer term, getting to a place where this can be streamlined enough where the path from taking a patient sample to generating single-cell data can actually be something that's really easily interpretable and actionable. So bringing this type of technology all the way forward into that diagnostic space, but I do think that's where there's the longest road is to get to that in terms of contributing to personalized medicine.
ANJALI SARKAR: Thank you, Irene. This brings us to the end of today's GEN Protocols Expert Exchange. Thank you so much for an enlightening discussion.
IRENE WHITNEY: Yeah, absolutely. Always happy to talk about the world of single cell, at least as I know it. So it's very fun for me. I appreciate it.
ANJALI SARKAR: And if you in the audience have been watching this episode of Expert Exchange and have any questions on methods used in single-cell research that you would like us to cover in future sessions, please email us your questions and suggestions at editors@genprotocols.com. And a reminder to all scientists and researchers among our viewers, GEN Protocols is open for submissions year round.
ANJALI SARKAR: We welcome your protocols in all aspects of biotechnology. This is Anjali Sarkar, Senior Science Editor at GEN Protocols. Until next time, good luck in your research and stay safe. [MUSIC PLAYING]
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ANJALI SARKAR: Hello, fellow scientists and science lovers. This is Anjali Sarkar, Senior Science Editor at GEN and GEN Protocols, welcoming you to today's Expert Exchange titled, "Single-Cell RNA Sequencing Challenges and Solutions." GEN Protocols is a premier resource for emerging and veteran scientists and entrepreneurs in biotech who want to know the nitty-gritty of advances in biotechnology from a trusted source. Researchers from academia and industry share their technical challenges and solutions on GEN Protocols, showcase their expertise, and nurture collaborations.
ANJALI SARKAR: You can share your methods and technical insights on GEN Protocols year round. Together with a rich resource of up to date methods and applications, GEN Protocols brings you expert exchanges where experts in key areas of biosciences talk about specific technical developments. In today's Expert Exchange, I will be talking to Irene Whitney, who is Director of Applications and Collaborations at Honeycomb Biotechnologies.
ANJALI SARKAR: Before joining Honeycomb, Irene was a postdoctoral scholar at Harvard University's Center for Brain Science where she used high throughput single-cell sequencing methods to understand mechanisms of cellular diversification during neural development and transcriptional responses to injury. In today's session, Irene will discuss current challenges and emerging solutions in single-cell studies, particularly in the context of capturing, preserving, and processing single-cell samples for RNA sequencing.
ANJALI SARKAR: Welcome to GEN Protocols, Irene.
IRENE WHITNEY: Hi. Thank you so much for having me. I'm excited to get to talk to the GEN Protocols audience today.
ANJALI SARKAR: We, too, are excited to have you. So to start off, could you tell us a little about your journey into the field of single-cell studies? And what was your first single-cell research project?
IRENE WHITNEY: Yeah, absolutely. I was really fortunate in the timing of my post-doc in the lab of Joshua Sanes, where we had the opportunity to collaborate really early on with Evan Macosko, who developed drop-seq, which was one of the first high throughput single-cell technologies. And at the time, it was not even well accepted that profiling the transcriptome of thousands of individual cells and then clustering them together based on their unique gene expression profiles could even be used to define cell types, let alone these molecular cell types would then correspond to cell type definitions based on morphology or sort of functional or physiological features.
IRENE WHITNEY: So we were really able to establish that there is a high degree of harmonization in cell type identities across these different modalities. And we did this for a well defined neuronal cell class in the retina-- bipolar cells. And so it's kind of cool for me now to see that, really, the field takes for granted being able to use single-cell profiling to generate things like cell atlases where you're defining the composition of different tissues, or organs, or organisms.
IRENE WHITNEY: So really just to see how far the field has come in applying these types of technologies. I think the other thing I'm also grateful for, during that time when I first got introduced to single-cell technologies, was having that experience of putting the parts together yourself, rather than working from a commercial product out of the box. And so that's been interesting to contrast that to my time at Honeycomb Biotechnologies.
IRENE WHITNEY: So we're a single-cell genomics company and really being a part of that huge task of taking a technology developed in academia-- so in our case, Seq-Well developed at MIT by our academic co-founders-- and then transforming that into something that's a robust, reliable, and user-friendly commercial product. So I'm really fortunate that I've gotten to have the whole arc of the process, from the start of a new technology to something that is at the complete other end being a commercial product.
ANJALI SARKAR: Definitely. And I'd like to hear more about the technologies being developed at Honeycomb. But before we go into that, what are the nuances that exist in working with different cell types in the single-cell research field? Specifically, what are the challenges that researchers face in undertaking single-cell studies when the cell type is, say, more fragile than normal, such as neutrophils, or are structurally unique, like neurons with long processes?
ANJALI SARKAR: If you could enlighten us a bit on that.
IRENE WHITNEY: Yeah. I think it's sort of universal for any single-cell RNA seq technology that, before you get started, the first hurdle is going to be sample preparation and the ability to generate samples that have really high viability and have been prepared in a way that they accurately represent the composition of that starting material or tissue. So for me, one of the challenges during my academic career was trying to prepare these single-cell suspensions of adult neurons, which are particularly finicky and fragile, especially for getting high quality RNA out of them.
IRENE WHITNEY: So it really took us a long time. I don't want to say how much of my postdoc I spent optimizing our sample prep workflow and combining that with a single-cell platform in order to generate high quality data. And I think now, to address this, you're starting to see multiple new products being offered in the automated tissue, dissociation space, right? So trying to create more standardized methods of dissociation, remove that kind of variability that can happen in the process, whether it's like site or user, different hands, things like that.
IRENE WHITNEY: So really having that good sample prep is required for any successful single-cell RNA seq study, though we know that this is not always enough. Even if you've successfully generated a high quality single-cell suspension, as you mentioned a second ago, not all cell types are robust enough to be recovered on some single-cell platforms, especially those platforms that require microfluidics for droplet formation during the isolation of single-cell.
IRENE WHITNEY: So this can exert harsh shear forces that can damage or destroy fragile cell types. You mentioned neutrophils, eosinophils, basophils. These are some of the ones where we've seen that are quite susceptible depending on the type of platform that you're using. Whereas instead of droplet-based but working more with a nano or picowell-based technology, they don't necessarily have that same type of challenge when isolating single cells.
IRENE WHITNEY: Those types of technologies have a much gentler process, relying primarily just on gravity to capture cells on individual wells. So kind of a balance there of what cell types and what tissue types are you working with, how do you prepare the sample robustly, and then making choices about what platform or what technology is going to fit best with what you're trying to recover.
ANJALI SARKAR: It's interesting that you mentioned the automation of tissue dissociation to get single-cell samples. I was wondering, what does the need for automation in these single-cell studies, what kind of additional challenges do you think that poses in the single-cell field?
IRENE WHITNEY: I think from the dissociation side, I feel that there is a lot of distance still left to go because there is a lot of optimization that needs to happen for every different tissue type or sample type. They're not all going to be treated the same or treated equally. In terms of automation on the single-cell processing and library prep side, I think people are taking a lot of efforts in order to figure out how to do that in a more high throughput way.
IRENE WHITNEY: And so I think that's maybe a little bit further along than the automation of tissue dissociation.
ANJALI SARKAR: So once you've dissociated the tissue and managed to collect your single cells, what are some of the most widely used ways of capturing, preserving, and processing these single-cell samples for applications like RNA seq?
IRENE WHITNEY: Yeah. I think I've probably touched on the two most common technologies already in terms of droplet or nanowell based. But in general, most single-cell technologies rely on a bead to start with, isolating a single cell together with a single bead. The bead is coated in oligos that are designed to capture all the transcripts once the cells are lysed, and then also add a barcode onto those captured transcripts that's unique to each cell, right?
IRENE WHITNEY: So this is nice, it allows for pooling all of those captured materials together for any subsequent library preparation. So the high throughput isolation-- so when we're talking high throughput methods for isolation and capture of single cells and single beads together-- is most commonly achieved, these days, I think with either droplet-based or nanowell-based technologies.
IRENE WHITNEY: I think we're seeing some more recent advances in the space where these technologies are now starting to come in two different flavors, I would say. And that's with and without specialized instrumentation that's required for that capture. Now if you don't want to or can't immediately process what you've captured for your single cells, either because you can't do it at the same time or the location is where the sample was captured, most single-cell technologies do require some kind of upstream storage or preservation method.
IRENE WHITNEY: And so you're sort of asking about the preserving side of the workflow. And I would say the most common method there is cryopreservation for single-cell suspensions, and then storage in liquid nitrogen. Maybe a little less common is the fixation of single-cell suspensions with either formaldehyde or methanol-based solutions. And then alternative to that, you can see people freezing whole tissue prior to doing any kind of dissociation and using those approaches as the common ways for trying to preserve single-cell samples before moving on with RNA seq.
ANJALI SARKAR: Just to clarify, the beads that you mentioned earlier, do you mean magnetic beads?
IRENE WHITNEY: So there are some technologies that I believe do have magnetic beads for their transcript capture. This would be different-- what people often think of as magnetic beads is when you're doing library cleanup steps and you're using SPRI beads for cleaning up your library. So this is different than that. So for capturing transcripts, technologies often rely either on a gel-based bead or a polystyrene type of bead that's been designed to be coated in oligos for that transcript capture of live cells.
ANJALI SARKAR: And you mentioned just now that the idea or the notion of freezing the entire tissue prior to isolating single cells at a later point in time. Could you talk a bit about the challenges of this, considering that a lot of cells lyse or are lost during the thawing process? What kind of challenge does that pose?
IRENE WHITNEY: Yeah. No, it's a really important question. And it relates back to what we were talking about a second ago in terms of, it all starts with sample preparation. And so if sample storage is part of your workflow, that's going to impact your sample preparation and your sample quality. So each of those common storage methods that I just mentioned, each have different drawbacks in terms of the quality of the subsequent single-cell RNA seq data.
IRENE WHITNEY: So with cryopreservation, this often requires high numbers of starting cells, in the millions, in order to have effective recovery after thawing. So it's not really an option if you're working with sparse samples. And then even if you do start with more abundant samples, it's not unusual or unexpected to see a 50% loss of the number of cells after you thaw before going into your single-cell platform.
IRENE WHITNEY: And I think that type, the cryopreservation as a storage method, is also really highly subject to batch effects, even when receiving cells from a commercial vendor. So at Honeycomb, we had this challenge during the beta testing of our HIVE single-cell RNA seq solution. So we wanted to provide all of our beta sites around the world with the same samples so we could get an ideal comparison of the performance of the HIVE in their hands.
IRENE WHITNEY: And so we provided them with commercially acquired, cryopreserved splenocytes. And we ended up seeing this huge range in the viability of these samples after thawing before they could even be loaded into the HIVE. And now we've also even seen that there are some cell types that are more sensitive to cryopreservation and are disproportionately damaged or destroyed.
IRENE WHITNEY: So you end up significantly altering the composition of a sample due to storage. I also mentioned fixation, so using formaldehyde or methanol-based reagents for that. And I think we see that second most to cryopreservation, I think largely because there's some concerns for negative impacts of these solutions on the quality and the recovery of RNA after fixation. And then, yeah, you also asked about just freezing whole tissue as a solution, if you want to collect in one site, freeze it, ship to another, and then move on with the rest of your workflow.
IRENE WHITNEY: The problem with whole tissue and freezing is it eliminates your ability to dissociate a sample into a single-cell suspension, rather you could only take frozen tissue and then dissociate it into single nuclei, which only have a fraction of the total RNA in a cell that's then available to be recovered. So you're taking a hit on the amount of data that you can recover if you're starting with frozen tissue.
ANJALI SARKAR: Of course. So you mentioned this comparison that you did in your beta testing phase. Could you tell us a bit more about how your proprietary HIVE seq technology at Honeycomb compares to, say, the droplet and picowell-based technologies that are commercially available?
IRENE WHITNEY: Yeah, sure. So the HIVE is a picowell-based technology. So it doesn't rely on droplets or microfluidics for capturing single cells. And I think one of the things that we've focused on a lot is, is there a way to incorporate sample storage into the workflow where you don't have that same kind of loss of data quality or loss of sample like these other examples we just talked about? And so with the HIVE, after you load your single-cell suspension into the HIVE, you have the ability to add a cell preservation solution that doesn't have any harsh cross-linking fixatives or anything like that and where you can stably store cells in the HIVE and then ship them to another location, or store them and process them later with the rest of the workflow for making your single-cell libraries.
IRENE WHITNEY: So we've now been able to see data out to nine months of storage where you're able to generate single-cell data that looks equivalent if you had the ability to work with fresh samples. Fresh is what we think of as the gold standard in the single-cell RNA seq field in terms of sample quality and data quality.
ANJALI SARKAR: You mentioned this gentleness and getting a bit closer to this, the gentleness of the procedure. Comparing it to these formaldehyde fixations that you mentioned earlier, are these harsher methods really compatible? Or how compatible are they with downstream RNA seq? Does that affect the sequence readouts in any way?
IRENE WHITNEY: Yeah. I mean, I think these are the important kinds of questions someone has to ask any time they're getting started with a single-cell experiment where there isn't a universal solution, right? There has to be compromise somewhere. And depending on what your experimental logistics are and what the data is that you need to generate to answer your biological questions, that's going to drive, what [AUDIO OUT] are you more comfortable making?
IRENE WHITNEY: So if your sample collection logistics is that you're getting in a clinical sample late in the day, you don't have time to take it all the way through processing and library prep, and so if you end up using a fixation method or something like that, you have a better workflow, but you might see an impact in the data quality, right? So if this means that you're not recovering the same kind of transcripts that you would if you didn't have to use fixation.
IRENE WHITNEY: So I think it's all a balance. There's no perfect solution. And like I said, there's no universal solution. It's all about which platform, which storage method, which technology is right for you. And I think even with the HIVE, we don't think that we have created the magic bullet, right? It's more about enabling people that are trying to work with distributed collection sites or time courses and maybe have more fragile cells and things like that.
IRENE WHITNEY: So it just depends on what you're trying to accomplish.
ANJALI SARKAR: So in future versions of the HIVE technology that you've developed, what are the areas that you think this technology needs to improve in?
IRENE WHITNEY: Yeah, that's a good question. I think we've been talking pretty much just about RNA, right? And I think our technology, along with all the other ones that you're seeing emerging in this field, needing to step into that multiomics space where you're adding on other layers of types of data in addition to RNA. And so that's something that we think about a lot in terms of what's important for people in being able to achieve their research and what they're working on.
IRENE WHITNEY: Yeah.
ANJALI SARKAR: OK. Yeah, we'll definitely come back to the multiomics perspective to look at it a bit more. But before that, you mentioned all these challenges in transporting the single-cell samples further upstream into tissue samples or long distance or long term storage. Could you talk a bit about the limitations of these different technologies in the context of cell viability after thawing as well as the diversity of the transcriptome seen in post hoc studies?
IRENE WHITNEY: Yeah. I mean, I think like I was talking about earlier in terms of, for example, working with cryopreservation where you can really see a negative impact on sample viability, we've seen that the longer duration that a sample can spend being stored by something like cryopreservation, especially if you are starting maybe from a less ideal sample, that kind of viability or that kind of sample quality can continue to degrade over time.
IRENE WHITNEY: Rather than being stable and trying to be able to have different logistics or different experimental setup where, maybe, you do need to have some kind of long time course or a longitudinal study or things like that where you want to batch your samples, store them stably, and then generate your single-cell data all together, batched together at the end of the study. And so if your method for storage continues to take a hit in data quality, the longer and longer that goes out, the more you end up having to compromise on the ideal setup for your experiment.
ANJALI SARKAR: Definitely. So how do today's single-cell RNA sequencing solutions improve upon the existing technologies, do you think?
IRENE WHITNEY: I mean, I think one I touched on briefly already, commenting that for both droplet and nanowell-based technologies where we're starting to see this trend and there being two different flavors-- with and without specialized instrumentation. So I think we're seeing development of more instrument-free single-cell solutions. So you don't want to have constraints on where and when you do your experiments. So Honeycomb has done this as well with the HIVE, which it's just a disposable handheld device, as we talked about before, that's using picowells instead of a microfluidic droplet-based approach.
IRENE WHITNEY: And then I think we've been recircling back around the other major limitation that we're starting to see improvements around, and that's the current sample storage methods. And obviously, that's been a big area of focus for us. We really had the benefit of getting input from some of our early pharma collaborators when designing the HIVE so that we could take their input and incorporate it into design choices that make it ideal for things like distributed studies where it requires the ability to stably preserve a single-cell sample for shipping and storage over an extended period of time.
IRENE WHITNEY: So like I talked about before, we addressed this particular challenge with our cell preservation solution. And so I think that having the instrument-free and the ability to store samples is really what opens up a lot of access and opportunities to using single-cell technologies in areas where maybe the solutions that existed didn't enable high enough quality of data to be generated.
ANJALI SARKAR: Just so that I'm clear, I'd like you to repeat this point that you had mentioned earlier of the increase in shearing that you see with microfluidic techniques as compared to picowell-based techniques, including the HIVE solution. So the reduction in the shearing that you see with the picowell technique is due to both the picowell per se as well as the buffer. Is that it, or are there other nuances in the strategy that enable this lack-- or reduction in shearing?
IRENE WHITNEY: Yeah. It's actually just a simple design of working with picowells and how you isolate and capture single cells in a well, as opposed to how you isolate and capture single cells in a droplet. So droplets-- some droplet technologies require, like we've been talking about, microfluidics. So you've got a chip that you're flowing your samples through, along with things like oil and reagents.
IRENE WHITNEY: And in order to push all of those things through the chip and create the droplets, like we've mentioned, there are these shear forces that get exerted during the process. So it's a very active process for isolating and capturing cells. When you're working with nanowell or picowell-based technologies, it's very passive in terms of how do you isolate and capture that single cell, where you oftentimes only need just the force of gravity in order for a cell to settle down into the bottom of a well, right?
IRENE WHITNEY: So that's what I'm referring to when I'm talking about a much gentler process, where it's much more passive and you're not exerting these additional forces as part of the isolation method.
ANJALI SARKAR: Excellent. Thank you for that. And what are some of the challenges in scaling up the sample number for current single-cell approaches? And in the context of that, could you also talk about controls used for studies in both a smaller scale as well as when you scale up your experiments?
IRENE WHITNEY: Yeah. I mean, I think talking about scaling up also brings us back to this point we've talked about a couple of times now, which is constraints of working with a platform that requires specialized instrumentation. So a lot of times, the throughput on those types of platforms is relatively low, like the number of samples you can run in parallel at once. Whereas with the HIVE and other instrument-free solutions, you have a lot greater flexibility.
IRENE WHITNEY: You don't have a set number of ideal samples to run at once. With the HIVE, because each device is its own individual entity, you can run as few or as many in parallel as you want. So for example, our R&D team, it's not unusual for them to do 24, 48 samples in parallel. And then-- sorry, I think I'm trying to remember the second half of your question in terms of scaling up for single-cell technology.
ANJALI SARKAR: The question was around what kind of controls would be involved--
IRENE WHITNEY: Oh, right. Thank you. Yes. Thank you. Thank you for that. Yeah, that's something that's interesting and it's come up a lot, especially in some of the conversations that we've been having with lab service providers or CROs, where they have customers that want to ship them samples for single-cell sequencing and them wanting to have some kind of internal control so that they can show their customers, oh, there might have been something wrong with your sample, but our processes for generating the data were robust.
IRENE WHITNEY: So something that we've developed that's specific to our library prep workflow are these molecular controls, where they basically can be inserted at different points in the library prep workflow and run in parallel with regular samples. And so when you get to your QC step at the end, and you want to say, OK, does my single cell library look good, is it the right concentration, are the fragment sizes in the right range?
IRENE WHITNEY: And for whatever reason, if something doesn't look good with your library QC, you can look at the different multiple controls we have and have a pretty good idea where something might have gone wrong in the workflow. So for a standard user who's working with the same sample type over and over again and things like that, we would recommend only working with these controls in the very beginning when you're new to the technology.
IRENE WHITNEY: But if you're a very high throughput user, something like a CRO where you've got so many samples coming through and you want that assurance that you're executing the library prep, including those controls, more routinely, would be something that we would recommend and see as being beneficial.
ANJALI SARKAR: Great advice. Thank you. And you already mentioned multiomics and the expansion of Honeycomb's technology in the future into encompassing multiomics approaches. But as you see single-cell technologies expanding into multiomics, what types of other single-cell data in addition to RNA sequencing data do you see critical for clinical research?
IRENE WHITNEY: Yeah. I think there, there's a relatively straightforward path, I think, in just seeing what has proved valuable when working at a bulk level and then applying that with single-cell resolution. So the few that I think are most essential moving forward is being able to have protein expression in addition to RNA. I think the other one, especially in the clinical setting, having T-cell receptor and B-cell receptor repertoire profiling, especially more in the immunology space.
IRENE WHITNEY: When you're talking more in the oncology space, things like ATAC for looking at chromatin accessibility and being able to layer all of those additional assays or type of data on top of RNA and then providing a lot more granular resolution for cell types and even cell states. I think one area that's interesting is with protein expression. Right now there's more limitations there, really only being able to have visibility on expression of extracellular proteins.
IRENE WHITNEY: I think something that's interesting to watch in this space is seeing steps that people are starting to take in expanding this capability for looking at intracellular proteins as well. So I think that's something that's going to be interesting to see how that evolves.
ANJALI SARKAR: Definitely. Considering the finickiness of techniques that are involved in proteomics that require very gentle handling of samples for one to visualize the protein at the end-- be it hydrophobic, transmembrane proteins, or intracellular, as you were saying-- do you think that the current technologies, including Honeycomb's technology for single-cell capturing and preservation, are close to achieving that kind of gentle storage that will allow intracellular proteins and hydrophobic proteins to be also detected along with RNA in multiomics approaches?
ANJALI SARKAR: Or do you think we still have a long way to go?
IRENE WHITNEY: I don't know. I think that's a good question. So I don't think that my background allows me to speak with enough certainty on that. Although one thing that, as I've understood it to be, especially when trying to get intracellular proteins, is that it's actually not necessarily an issue of gentleness. But because you're trying to get intracellular proteins, that needing things that are more robust in order to break things apart and capture those intracellular materials.
IRENE WHITNEY: One thing that comes up a lot in conversation-- again, coming back to this idea of different technologies are going to have different benefits, different drawbacks. And there's a lot of great things about working with droplet-based technologies. I used droplet-based technologies from my whole postdoc. Working with readily available fresh tissue, things like that, it was beneficial.
IRENE WHITNEY: But there are constraints when you're working with a droplet because you're trying to fit in a lot of reagents that have a lot of different things that they need to do in terms of lysing a cell, capturing transcripts, starting to do some first strand synthesis, things like that. But droplets themselves have physical constraints on being able to be formed and be maintained. And so as you start to play around with trying to capture and recover different compartments or components of a cell, with a droplet, you have to work with the physical constraints of maintaining that droplet formation.
IRENE WHITNEY: With the HIVE, it's a little bit different than other picowell technologies. So the way I described it before is you're having these cells captured into individual wells. And the way the HIVE is designed, it comes preloaded with those transcript capture beads that we already talked about. They're in each of the wells. But you still need a way to create an individual isolated compartment.
IRENE WHITNEY: Like with a droplet, you need to do the same with a well. And the way that we do that with the HIVE is we apply a semipermeable membrane to the surface of the array and seal it on there. And that's what gives you your individual reaction chambers, if you will. And the design of the membrane is such that small micromolecules can be applied in bulk to the surface of the membrane and diffuse through, diffuse into the picowells.
IRENE WHITNEY: But then your larger macromolecules-- your RNA, your protein, things like that-- are going to be too big to diffuse out, so that's what gives you your single-cell resolution. But the semipermeable membrane, that's going to be more robust than something like a droplet in terms of creating those isolated reaction chambers. And so that does give us a little bit more flexibility in terms of the solutions and reagents that we can be applying to our system in terms of trying to recover different things from cells.
ANJALI SARKAR: And as we wrap up, I'd like to ask you, once we develop a new technology such as these single-cell technologies, there's always talk about how these are being applied in medical/clinical research, biomedical research, and particularly personalized medicine. So in your opinion, what impact are single-cell studies having on health care and medicine currently and in the years to come?
IRENE WHITNEY: Yeah. No, that's definitely a big topic of discussion here as we try to understand. We're at this phase where single-cell technologies have been well established in academia, and now we're starting to see them move and transition into biopharma, into the clinical space. I think we'll see this evolve over a few phases, right? So you can think maybe starting first with the use of, maybe, clinical samples to generate single cell data as more discovery and development-based efforts, so helping to reveal new biology, identify new biomarker profiles, and then to progress this type of knowledge so that maybe it can be applied to clinical trials for patient stratification or determining what the appropriate drug combinations should be matched to a patient-specific tumor heterogeneity or defining what differentiates responders from nonresponders over the course of a trial.
IRENE WHITNEY: And then I think, finally longer term, getting to a place where this can be streamlined enough where the path from taking a patient sample to generating single-cell data can actually be something that's really easily interpretable and actionable. So bringing this type of technology all the way forward into that diagnostic space, but I do think that's where there's the longest road is to get to that in terms of contributing to personalized medicine.
ANJALI SARKAR: Thank you, Irene. This brings us to the end of today's GEN Protocols Expert Exchange. Thank you so much for an enlightening discussion.
IRENE WHITNEY: Yeah, absolutely. Always happy to talk about the world of single cell, at least as I know it. So it's very fun for me. I appreciate it.
ANJALI SARKAR: And if you in the audience have been watching this episode of Expert Exchange and have any questions on methods used in single-cell research that you would like us to cover in future sessions, please email us your questions and suggestions at editors@genprotocols.com. And a reminder to all scientists and researchers among our viewers, GEN Protocols is open for submissions year round.
ANJALI SARKAR: We welcome your protocols in all aspects of biotechnology. This is Anjali Sarkar, Senior Science Editor at GEN Protocols. Until next time, good luck in your research and stay safe. [MUSIC PLAYING]
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