Twist Bioscience Corporation (TWST) Earnings Call Transcript & Summary

Welcome, everyone. Good afternoon, good morning depending on where you're joining us from. And welcome to this Twist Bioscience webinar, Methylation Biomarker Discovery for Complex Diseases using Twist Human Methylome. My name is Chris Thorne, and I am Senior Manager of Field Marketing here at Twist. Before we begin and I introduce our speaker, I'd like to discuss a few items of housekeeping. [Audio Gap] questions, and we'll do that at the end of the webinar. [Operator Instructions] There's some great resources, this content section includes links to not just Twist's related products and services [indiscernible] and you'll be hearing more about that during our talk today. If you'd like to contact a member of the Twist team, you can press [ Box ] and reach out to a member of our sales team, and they'll be in touch with you shortly thereafter. We will be asking you to take a short 1-minute survey, and this just helps us [Audio Gap] Services Product Manager at Diagenode. Matteo [ is a dean ] from the Paris-Saclay University, where he studied epigenetic mechanisms in mouse embryonic stem cells. [Audio Gap] Team and is now Epigenomic Services. So Matteo over to you.

Hi, everybody. Thank you, Chris, for the nice introduction, and thank you for Twist for the invitation of doing this webinar. So the title of the webinar is DNA Methylation Biomarker Discovery for Complex Diseases, Using Twist Human Methylome. And today, on the webinar, we're going to talk about doing a small introduction on DNA methylation, what is biomarker discovery, what is the human methylome panel, how are they using human methylome. Then, I will present to you a short case study where we compare data from human methylome and from the EPIC array. And then I will explain how we can go a little bit further going from a biomarker discovery to a biomarker validation and then throwing some conclusions. But first of all, what is DNA methylation. So DNA methylation is an epigenetic mechanism that occurs by the addition of the methyl group to the DNA mainly at cytosines. It can occur at different genomic locations such as gene bodies, promoter or noncoding region like [indiscernible] regions, modRNA, pericentromeric or centromeric region. And the DNA methylation, we can have an impact on genome regulation, mainly modifying the gene function or affecting the gene expression. It is also known that this specific to the cell type or to the tissue. And it is also well known that aberration of these DNA methylation profiles are an old marker in cancer. And in cancer, we can find 2 main different mechanisms, a global loss of methylation, which is called hypomethylation, which can result in genomic instability, but [don't just] call hypermethylation, specifically at some region, mainly at CpG-rich region, which usually induce transcriptional repression. Knowing that, DNA methylation can, aberration of the DNA methylation for cancer can be used as a biomarker for early disease detection. So how we can study DNA methylation? The gold standard to study DNA methylation is the use of bisulfite conversion. What is bisulfite conversion? Bisulfite conversion is a chemical reaction which transforms unmethylated cytosine to a uracil and then after PCR or library preparations time, while the presence of methylation over the cytosines will basically impede that modification to happen. And so, after conversion, when we sequence the data on the genome reference, we have seen on our library, we still have a C, that means that there was no conversion, so that C was methylated. While, when the genome reference, we have C but we actually sequence a T. That means that the C was non-methylated and converted to a G. In the last -- over the last 2 years, we have also coming on the market with another option of bisulfite conversion and a parallel option, which is the enzymatic conversion, which is shown here. And the principle is exactly the same, but instead of using a chemical reaction, we are using a series of enzymatic reaction to come at the same time. However, it's very harsh in damaging the DNA, the enzymatic conversion is not damaging and will lead to much -- a reduced loss of the DNA. So now that we have introduced the DNA methylation and why it is important to study DNA methylation, how can we use the DNA methylation for a biomarker discovery and what is the biomarker discovery? The biomarker discovery is a pipeline for which we can basically use a different sample that we know that we are -- we would like to find a sort of pattern that can differentiate one group to the other to see -- to find a sort of signature. So for doing that, of course, we want to use the most genome-wide solution. So screen as much as possible CpGs to find the ones that are really important and can discriminate in between the different group, treatment versus control, health investment versus patient. And for -- and to do that, we can, of course, use different options. We have the option for whole genome bisulfite sequencing for EMC, human methylome, the EPIC array -- and those are very useful for screening high number of biomarker. And due to that, we can really try to avoid using a high number of them. And here today in this webinar, we will focus on the biomarker discovery using the human methylome from Twist. But what is the human methylome, of course? The human methylome is a targeted NGS-based technology that analyzes DNA methylation at single nucleotide resolution, achieving a very high coverage. So we are talking here about an x. And just to compare the whole genome bisulfite sequencing is usually sequenced at 30x. So we have really a high difference here in coverage. And was designed, this panel was designed by Twist, and they have designed it using the recent data base like UCSC and sample ENCODE. And that panel basically genes, which are connected to roughly 4 million CpG sites and those 4 million CpG sites cover more than 80% of the CpG island. Human methylome panel overlap for more than 90% the probes of the EPIC array. What are the applications for the human methylome? So the application, so it is -- since it's by growth, it can be used for biomarker discovery and for monitoring in, for example, cancer in neurogenerative, neurodegenerative diseases, cardiovascular diseases, metabolic diseases, fertility or immunology. And what is really nice about human methylome is that it's very flexible in terms of what are the sample type and the input that you can use for that technology. So we can go from really clinical low-input samples, such as liquid biopsies and plasma cell DNA. We can use whole blood, PBMCs, flash frozen tissue but also FFPE tissue or cell culture in general. How it's important, so how we can use also the human methylome in cancer research. So, if we cross, so the panel of the human methylome with the database, which is called the nature of cancer genes and [ probiotic ] driver, we can find if, for example, the human methylome covers 277 genes that have been already reported to be important for breast cancer. It covers 150 genes that have been showed in this database to be important for colorectal cancer, 27 genes for the ovarian cancer and 190 genes for the pancreatic cancers. So it seems to be a very wide panel that can be used for many different type of subtype of cancers. At Diagenode, we have been working since many years. And as soon as they have launched the human methylome, we started a collaboration together to be one of the first services provider to provide the human methylome services. And how the human methylome services work at Diagenode. So we can start from a very different type of, as I told, before, so it could be genomic DNA, FFPE DNA, self-DNA, we attach the adapters to those DNA, we performed the enzymatic conversion with library amplification. And that's that, we have basically produced a [methyl-seq] genome-wide library operation, so it's over the whole genome. And after that, there is the ending of the human methylome panel probes, and we are basically just selecting for the part of the DNA, which contains the important CpGs that have been selected as more re-amplification, we go for sequencing and bioinformatics. So the whole workflow at Diagenode has been optimized. And for example, if you submit a matter in a cool plate and we can do that quite rapidly. So we had turnaround time, about 6 to 8 weeks. Where we have compared the data of the human methylome versus the EPIC array here at Diagenode. So a company, a U.S.-based company called [ Inner Bioscience ] came to us with the idea of -- with the pilot study to see whether it was possible basically to predict COVID hospitalization based on the genomic relation profiles, we can discriminate prior, whether there's a high or low risk of hospitalization. So for that, they collect a lot from samples. They have genomic DNA. So we have got 4 sample genomic DNA from PBMCs for non-hospitalized COVID patient and 4 samples from hospitalized COVID patients. And with the same DNA, we had performed a pilot study with EPIC array and with the human methylome. So the first thing that we have done is to compare and see whether the probe of the EPIC array, which are also included into the human methylome, were giving the same DNA methylation values. So we have performed a peer correlation in between the DNA methylation values obtained with the 2 technologies. And here, I'm showing to you all the 8 samples. And as you can see, we can see a very nice diagonal and [indiscernible] show a correlation of more than 95%, which strongly suggests that the 2 technologies are extremely valuable and interchangeable even though the EPIC array is bisulfite base and array-based while the human methylome is enzymatic based and NGS-based. Then we have done a deep look at the EPIC array results, and we have performed a pairwise comparison in between hospitalized versus non-hospitalized patients. So in between the more than 700,000 CpGs that are analyzed by the EPIC after filtering [ high GC ], we have found no significant DMCs, so differentially methylated Cs and only 2 significant DMRs, which stands for differentially methylated region. On the other hand, looking at the human methylome results, what we have observed is that with the human methylome, we're able to detect more than 18 million CpGs detected and half of those, roughly 9 million CpGs were covered with a high coverage. Of course, here, we have to make -- we have to mention that thanks to NGS, when we say that the human methylome target forming Twist technology which captured both trends into the NGS technology, which was sequenced both trends to the plus and the minus. When we say that the human methylome covers 4 million, we are actually doubling that number because every CpG has a plus and a minus in [indiscernible] region. So we can actually also measure the DNA methylation, and that's why we have here 9. And when we have performed, basically the comparison between hospitalized versus non-hospitalized on the human methylome results among the 7.7 million samples, we have found more than 12,000 differentially methylated Cs and more than 800 differentially methylated region when we have set the threshold at 25 and adjusted on 0.01. And this, you can see it here in the volcanic plot. And very interestingly, when we have used those more than 800 DMRs to perform a heat map and a hierarchical clustering, we have nicely observed that based on those 800 DMRs, using a hierarchical clustering, we're able to discriminate and separate very well between the 4 samples that were not hospitalized versus the 4 samples that were hospitalized. So those data, even though they are still a pilot product on a very limited number of samples is strongly suggest that the human methylome to thanks to this grower coverage is able these DNA methylation signature that can occur in such peculiar or complex diseases. And after -- on a more higher number, just to be sure, that higher number of samples, just to be sure and to finalize that those 800 DMRs and 12,000 DMCs are actually very healthy between non-hospitalized and hospitalized data. Then we will be able to move to a more custom target DNA methylation and moving from biomarker discovery to biomarker validation. And indeed, what is a biomarker validation? So the biomarker validation is the second step of the pipeline of biomarker discovery, where once we have finalized and find which one are [indiscernible] are really important to discriminate in between a different group, LCO treatment, cancer or healthy patient, then we're going to reduce the number of biomarkers only to the one that we are interested in or the critical ones and we can dramatically increase the number of samples just to validate the performance of the DNA methylation signature in a higher cohort, as it's shown in here. And how their practically done -- so once we have performed the human methylome screening with the human methylome, together with Twist, we will work and perform in the redesign of the Pro panel going down, so reducing from the 4 million to the CpGs to the specific number of CpGs that have been shown to be very importable by the study that was done before. We were talking about only 12,000 CpGs. And together with Twist, we will redesign the panel and then using the exact same workflow here as for the human methylome, just changing the part of the capture and instead of using the human methylome panel, we can use the custom panel, which will show to be important to discriminate for your specific biological question. And thanks to that, we can, of course, reduce the cost of the sequencing because it needs to -- that are captured and need to be sequenced, while increasing the coverage of those regions to be even more sensible for [indiscernible]. So coming to the conclusion of that webinar, what I've shown to you today is that the human methylome is a targeted NGS-based DNA methylation. Same, so in reality, we have a more than 30x coverage of real targeted CpGs and then a broader coverage than EPIC array. Human methylome is, of course, in cancer but also in other complex diseases. We can apply the human methylome to very difficult clinical samples such as plasma cell DNA or FFPE. And after the first biomarker discovery with Twist to reduce the panel from the human methylome in going to a more custom panel. To perform the success by market validation on a high sample volume, a high number of patients to validate and to confirm that the signature is the right one to go through. And in conclusion, why do you want to use the Diagenode as your targeted DNA methylation services? So -- we are happy to be selected by Twist as they are NGS for lab services provider. Of course, we have a huge experience in timed DNA methylation project from difficult samples using many different panels, the human methylome from sample to the analysis. We always designed the project in a very customized and collaborative way with our clients. So you will get -- you will have someone from our services team that will discuss with you the product design to design the best option ever where you will have a dedicated in-house expert for your product that you can -- that will follow up on all the steps of the project and we produce reliable and consistent bioinformatic-rate data with high-quality, ready for publication. And with that, I'm concluding the webinar of today. I will thank you, all of you for your attention, and I'm of course happy to take questions.

Matteo, thank you, so much. That was a fascinating presentation. So we're going to go to questions now. Suggest people, if you do have questions for Matteo, then you can ask those in the ask question box, and we'll try to get through close as we can. I can already see a few coming in. While I let people I wanted to just maybe question of my own for you or for your data set. It's quite striking data, is it not, that you've got with EPIC array no DMCs and only 2 DMRs and then you move on to the human data and you've got over 12,000 DMC [Audio Gap] I've got 879 DMRs. What -- is it just that the human methylome gives you a higher sensitivity there? What is your theory for those, that big difference?

So of course, the fact that when we have compared, and correlation in between the data of the EPIC array and human methylome that has said to us that probably, the CPGs that have been -- that are detected by the one informative for such a complex disease like, for example, COVID -- so we know, for example...

Sorry, is my sound not working particularly well?

Yes. I heard you not... So sometimes it...

My apologies, apparently the audio [indiscernible]. So I'm going to ask my colleague, Larissa. Just give me a moment and I'll try a different microphone.

So sorry for that. Chris' audio is really bad. So you're going to hear another voice from the background now, I just quickly ask my questions. I hope my audio's better. Matteo, please let me know.

I can hear you very well, Larissa.

Perfect. Okay. So then let's start from question 1. Michael asked, because you're sequencing alpha strands since the coverage then 37.5x -- or can you see every stranded read as a new read?

So when we say about the 130x, this is the -- this is not including the fact that we have this double strand, which is very specific for DNA methylation. So that sequencing compared to the 30x in the whole genome need to be specifically signaled from the last strand and then a specific signal for the mines. However, in one of my last slides, I say that we actually reach and that is really on a strength-specific CpG. So the final coverage per CPGs per targeted CPGs with the strand with the [ stored ] of 30x.

Okay, thank you for that. Now we have more questions from Carla, data from a targeted panel that signed by Twist.

Okay. So in terms of bioinformatic analysis, so there are many different -- so I'm not sure that there is -- so you can use the standard Bismark one, which is the most used into date right now, also at least internally at Diagenode, we are moving towards other softwares, which are more powerful and less time consuming than Bismark, but there is a specific software that you must use to analyze targeted DNA methylation data using either its human methylome panel.

Thank you, okay, the next question. Did you found DMCS is Twist good to look at methylation per CpGS or do you time your region with the probes and individual CpGS methylation measurements? Is it not possible? That's complicated.

Yes. Can you maybe reread the question?

Well, first question of this did you found BMCS, DMCS?

That DMCs, yes.

And the second one -- yes, just answer that, and we go to the next one.

So in terms of -- so I don't know if the question is about the case study. So if the question is about the case study. So again, we have found DMCs not in the EPIC array but in the [Audio Gap]

Okay, wait for me -- and the second question is, is Twist good to look at methylation per CpGS -- or do you take a region with the probes and individual CpGS methylation measurements? Is it not possible?

I'm not sure that I completely got the question, but I think that's basically what we thought that Twist had done with the human methylome. So they design probes. The probes are 120 [ MHz ]. And those probes will capture, contains the important CpGs. So you can have more than one CpGs in each fragment or captured by the same probes. And you can time the probes level. So this is very -- it can be done in a very customized way, especially for the custom panel because more the panel is smaller and more you want to capture to keep as much as possible of the part that you are interested in.

Okay. Thank you very much. Then we have -- can you speed up turnaround from 6 to 8 weeks to 6 to 8 hours for clinical use?

Very good question, very good question. So yes, no, the protocol requires quite some time because you have, of course, to extract DNA. We have to do a QC of DNA. And after the QC of DNA, the kind of sample that we are working with, we might or we might not need some DNA sharing. That's again a new QC and only then you can start with DNA level preparation at least 2 days in the lab. After that, you have the capture, so you can add one other day minimum. And then there is the sequencing. The sequencing itself today, 2 days. 24, 48 hours. So no, in time, in the hours of a working day, it is not possible to have, it's not possible to have it just one day.

Okay. Next question is, what is the minimum DNA amount for sea of DNA?

Okay. So here, gene, we have pushed more in general, the methylation system using Twist probe for some customized panel down to 10, 20 nanograms of self-DNA. With that, we are very comfortable. We know that we can -- the lighter operation can work, will work. However, of course, compared to the maximum input, which is around 200 nanograms, you would expect that you're going to have some PCR applications or something that will be discarded at the analysis.

Just say, we got a lot of questions, which is really, really nice, how engaging you are. So the next question is going to be, first, a big thank to you, very nice talk. And then, is human methylome applicable to sample taken from saliva mouth swab or long immune cells?

So, it is a great question. So the straight answer is, yes. Of course, when we are always to remember that those samples are quite contaminated, so you're going to have [ numerous ] cell, but also contamination to whatever the person, for example, just eaten before, so we can have eaten some chicken or some meat, of course. So you're going to have contamination for that and some bacteria. But of course, we can project we are doing the capture using probes that are specific only for the human. At the sequencing level, we're going to sequence only what is coming from the human, which is, can compare to, for example, doing a whole genome bisulfite sequencing for which, if you have 25% of contamination, you're going to lose 20% or 25% of reach over those...

And then we have the question, I guess, kind of regarding to that, how many milliliter block sample is required for this test?

Oh. So depending -- so usually, you have -- so if you're talking about cell-free DNA coming from blood, then we can -- if we have basically, if you do a blood draw of 10 mL, you perform the sensification to take out the plasma. The plasma is roughly half of that, so 4, 5 mL. And so from 4, 5 ml of plasma, we can reach something in between 10 and/or 20 nanograms of cell-free DNA and that's why we have validated all the 5 Twist probe panels in the range in between 10 and 20 nanograms. But if you're talking about whole blood. So you do expect to have a lot of DNA from, for example, a PAXgene tube, which if I remember right, we are about 10 mL. So for that, you're probably more reaching micrograms of DNA. And the library preparation method is -- the maximum input of the library preparation method is 200 nanograms. So we will be definitely fine with that.

So then we have a question regarding the EPIC array and not specifically the human methylome. Can we do the enzymatic conversion instead of the bisulfite conversion?

Okay. So on the Illumina array, so the Illumina array has been validated by Illlumina using the bisulfite conversion. It is something very interesting to check whether it is possible also to use the enzymatic conversion. It's something that, it could be tested. We haven't yet tested it, but it's something that could be very nice. But we have no -- we don't know whether there is something that can basically interfere with the Illumina steps after the conversion. But in theory, it is feasible. So if you are interested, please contact us, and we can discuss about that.

Ample questions coming up. Have you looked at methylation profiles for long COVID since this affects tens of millions. Also for ME, it stands for, oh my God, myalgic encephalomyelitis. Sorry for that, CFS, that can be quite similar.

Can you repeat the question, Larissa? So I'm not sure I got it right, so I want to answer it correctly.

Have you looked at the methylation profiles for long COVID since this effect has...?

Okay. Now I understand. So being at Diagenode and a services provider, so we don't do R&D ourselves. So we're always working together with some biotech companies, which came to us asking for with a specific biological question. And so, for that specific case studies I'm showing here. So the company was inherent bioscience and they want to see whether there is a signature. There was some possibility of using that signature to predict pilots, even though it was very interesting to work and to use the human methylone as a biomarker discovery for that. The projects have been stopped by them, and so we haven't gone through our accomplices. So no long COVID was done that. But this is something that might be very interesting. So, since there was a clear or at least a strong suggestion that there was a clear DNA methylation signature that could discriminate between high and low risk, we can think that there might be also a DNA methylation signature that can discriminate the presence or not of a long COVID into people.

Okay. Thank you very much for everything. Any question we now may couldn't have answer. When you put in your contact details, we're going to reach out to you, we have contact... Matteo is going to answer them directly. Also on your side on the right side, you see Matteo's email address and LinkedIn, so please feel free to contact him also directly. If a question later comes up maybe. Then a big thank you to Matteo for this great presentation. Thanks for doing it. It's lovely to work with you. And for everyone else, I hope you have a lovely day, we're having a survey popping up when you close the window, it would be really great if you could take part so we get feedback on how the webinar went for you. And then I wish everyone a lovely day. Thanks for joining and see you soon hopefully. Good day. Thanks for joining, and see you soon, hopefully. Good day. Thanks for joining, and see you soon, hopefully. Good day. Thanks for joining, and see you soon, hopefully.