Name: Is WGS the future of sequencing in the food industry?
Start: 2023-02-23T10:00:00.000-08:00
End: 2023-02-23T10:54:00.000-08:00

Hello everyone, and thank you for attending today's webinar. Is whole genome sequencing the future of sequencing in the food industry? My name is Jennifer Buckley and I'll be the moderator for this session. Before we begin, we want to cover a few housekeeping items. At the bottom of your screen are multiple application engagement tools that you can use all around. The engagement tools are resizable and movable, so feel free to move them around to get the most out of your desktop space. You can expand your slide area or maximize it to full screen by clicking the arrows on the top right hand corner. If you have any questions during the webcast, you can submit them through the Q&A engagement too. We will try to answer these during the webcast, but if we run out of time, they will be answered later via e-mail. Please know that we do capture all your questions. You are able to activate closed captioning for this webinar. You can activate it by pressing the CC button on the lower right corner of the media player. Just Please note this is only available in English. An on-demand version of the webcast will be available afterwards. So I'd like to introduce our speakers today. We have Christoph Noel, he's director of innovation in SGS in the UK and Joanna Cruz, whose manager of our Competence Center for Molecular Biology in Portugal. So with that, I'll now hand over to you, Christopher. Thank you, Jennifer. Uh, hello, everyone. Um. So yeah, the the agenda of this session is obviously just we just had the introduction, but it's about next generation of testing and particularly the whole genome sequencing, what kind of solution it can offer, the challenge, the applications because NCGS, whole genomes, all these different words can be a bit vague sometimes and confusing. We will also give you some practical examples on the whole genome for food testing and then. In conclusion, and obviously some some question and answers. So. First, obviously that just to to start obviously the. DNA sequencing has been has been around for for the last 50 years and obviously it was first very academic. Field and it took quite a while to to permeate into into the food industry and though it started in 77, obviously based with with Sanger and obviously the PCR development by Kary Mullis. The real breakthrough started in the late 1990s with the development of capillary system and then made the automating of the reading absolutely feasible and widely available. Without that, it would have not really been feasible to envisage to do genomes or whole genome, even for bacteria. And then in the 2000, we had the Human Genome project and that's where it started to become really the big topic of sequencing and it took nearly 13 years to complete with the cost of. In excess of 2.5 billion, which is about a dollar a base. And you can imagine that though bacteria is much smaller, if we couldn't do this in a in a time that is actually compatible with a service that would not have been even possible to think about introducing these kind of things in the food testing and then in the 2000, early 2000 next generation sequencing. Was becoming a reality and that was a complete revolution not only on methods but also the amount of data we can generate. And then when we started to have these kind of technology, it was then starting to become. A reality to have DNA sequencing widely available. Did you full genomes or generate vast amount of data, look at communities and things like that in. In in layout that we're not only academic but could become really a real feel for investigation. You know, food testing and overfield. Obviously medicine was pioneering in this, but we started to bring that to our world and the food testing. So what? Why was it a a real, real kind of step forward and a big revolution to have next generation while prior to that when we wanted to investigate? The bacteria genome, because that's the topic created here. We had to go through what we call shotgun sequencing and we were using Sanger sequencing to do that. It was still sequencing by synthesis, but it required a lot of steps like cloning for example, inserting bits of DNA into other bacteria so we could amplify a lot, a lot of very common sense steps. It was very noisy in terms obviously time, very expensive. There was problem with biases. Yeah, with all the different steps and techniques and it would take years to complete even a genome. And even though E coli was published in the early 2000s. It would be inconceivable with this type of message to even look at an investigation because it would have taken years, which is obviously not the timeframe we've got. And then with NGS appearing, it was still the same kind of idea in terms of sequencing it still by synthesis, but we call this parallel sequencing. And basically you're doing into a space that is probably the size of a microscopic slide or even smaller. Thousands and thousands if not millions of sequencing in one go and what would it would give us is a high throughput. So in that with this kind of technology, we were reducing the time it would take to generate. A lot of data. A genome would take not no, no years of days, but only few hours. For a cost that was manageable, and also what was really necessary for this to happen is to have a very powerful bioinformatic platform available. And because computers were getting much more powerful, space was not a problem. All these become a real tool that was easy to handle and easy to use into our setup. NGS is a big word, but there's loads of different, different technology and they all have their drawbacks and advantages, but they're all very complementary. And they can be used in combination to generate the best possible data. So when we talk about next generation sequencing, we're talking about the technology and what is interesting is to actually not only look at that, but what's this application, because it's a big kind of bundle of technology and yes, but what can we do with it? And we hear about whole genome sequencing, we hear about metabarcoding, metagenomics, well, actually what kind of application can they have for our? Food safety, food quality or authentication. And that's where it's actually really important to try to understand and decipher what is the technology and the different applications and that's what we're trying to do here. So when we had a GS and we started to think about applications in the in food system or in food safety, we could think at different fields and different level of application. Because we could generate vast amount of data using all sorts of different platforms that all have different advantages, well, we could start to think about using what we what we call metabarcoding or unplanned consequences. And this type of methods are looking at it's completely culture independent, so that means we don't have that bias. We can really look at an overall community without having to culture it and only a very small part of. Bacteria present in the environment actually culturable, so it was really giving us insight into what really is going on. So when you do metabarcoding you usually use a target and 60 Nets for example and. It's very kind of targeted still, but it allows you to have the survey of what is present, you can push that a notch and then you can decide to sequence now the overall DNA that is present in the sample and that's what's called metagenomics. So it's a whole genome of literally all the material, all the DNA that is present in the community. This is also obviously culture independent and that really allows us to characterize the diversity of the microbial community. So it can be useful for tracing microbes, but also predicting microbial gene function. So you can investigate pathways. You could start to think about how bacteria can cooperate, what can they do not do? In an environment trying to understand why your biofilm can actually sustain certain stress? Well, also in food processing. You know, if you think about sauerkraut and the different kind of bacteria and what kind of community have to come one after another and it is standing there, so it can be even useful not only in food safety but also on MPD. And then finally, the one that we're going to concentrate on with a with a case study in the first part is the whole genome sequencing. It's when you actually start to think about characterizing one single colony 1 Organism and trying to understand, for example, relatedness between these organisms found in the environment. There's different ways of doing this kind of investigation and the main one will look at usually and we hear about is SNP which is single nucleotide polymorphism and then it's basically looking at a overall genome of the bacteria. So the complete sequence we're talking about 3,000,000 bases for Listeria or about 5,000,000 for someone and then you investigate and you can compare almost based based the Organism so it gives you. You know, sense of how related those? Bacterias are and then you can also do a gene by gene doing what we call MSD for example, but your full genome scale. So let's have a look a bit more at an example and how we can actually use NGS into the food safety. So the typical case which is real case here is actually we isolated salmonella in four examples two days apart. Two were identified in the product in products and two were isolated from swabs. So if you go by what happens in the lab? You would obviously confirm them, and the confirmation will just tell you the answer. So it opens up a lot of questions, for example. Did the same strain? We're finding each samples are using the same real salmonella in the product and the swabs. Obviously in the lab you're always gonna have that kind of. In the back of your mind, is it not the lab strain? Do we, are we dealing with cross contamination? Is is it really an issue that is? With those samples and you can't really answer these because salmonella with this type of confirmation will just be salmonella and terrica. You don't know the strain or even further characterization. So what can we do? Well, what we used to do is using Sanger sequencing. So we're not even talking here of whole genome or even. Next generation sequencing, we were just looking at a very small part of the genome, usually 7 genes. And what we can do by doing this is actually going a bit deeper in terms of characterization of the bacteria. And what it could tell us is we're obviously dealing with some monetary care. We had a sequence type, it's a bar code. It's kind of designed by you sequence genes that are predefined and they are usually in schemes. National schemes. And then we've got databases where different version of each gene is referenced. That's what we call an L and then you generate basically a bar code and with that bar code you get a sequence data. And in that instance there were sequence Type 32, which was linked to your likely serovar infantis, but that was true also for the four isolate. So what do we get with that? Well, the survival was consistent with the environment and the product, which is good news for the lab, a bit LES for the customer because that would indicate that they have an issue and it is consistent with what? Is the sample and the type of product they're dealing with. Obviously we'll remove the the assumption that it could be a contamination will generate lab strain because obviously these will not be entered. Fantis and they would be different sequence type and this is already very sufficient because if you have. A sequence that is different. You have enough genetic difference to be able to say they are different types of late, but there's still some more questions that could be asked and can we learn more if we go deeper, we're doing next generation sequencing. Well, we start kind of all over again. You go back to your isolates, you do a DNA extraction, you there's loads of different roles and we'll go back, we'll go to across the bit later on. So you extract DNA, you prepare library, you use your eggs platform and you generate vast amount of data. Usually you cover at least 30 times up to 100 time the genome of that bacteria. So what you want to do is to make sure that what you're looking at is exactly the right sequence. You're reading every single letters of that genome at least 30 * 100 times, and then you generate a whole genome, and then you end up with about 4.7 up to 5.2 million base pair, and that's. Very long book to to analyze. So when you do that. Obviously you're gonna. Actually that's the temporal question was carried away here. So I'm going to have a little poll here. And the question is for yourself, do you use whole genomes specifically for any of the below option? The first one is pretty safe. Characterizing molecular microbial population? Are you probiotics? For other reasons or maybe in the future. So I'm going to give you about 30 seconds and if you could answer this, that would be really, really helpful. Because. Just the the example I'm giving you is a real sample in a service lab, but it will be really interesting to see there's other applications. Starting to. Evanses. We get a bit more time. Yes, I think people have entered, wanted to, uh, few new ones. That's 10 seconds in that leg. Reveal. The pool. OK. Let's see. So yes, so we can see that. Out of the people that have been using it is mainly food safety, but those few others and there's clearly an interest on using it. In the in the future, and I think that's the main. Kind of application we think straight away is food safety, but Joanna will show a bit later on where we can use that and notably in probiotics and characterization of strains, which is not only safety and perfect. Thank you very much. So to get back to our case study. Well, we we've generated then the the genome for the four isolates and then we could compare them. They're different ways of comparing. Once we've got a full genome, as I was saying, it's a lot, a lot of data. So you've got what we call single nucleotide polymorphism and what you do is you've got some specific one specific position across this genome that are of specific interest because they either hypervariable etcetera. All this is designed by MODELIZATION. And then we compare those strain on those specific positions and then we then build matrices and it's a little bit like an MST really you're looking at how many differences there is across those genomes and then these rules again on deciding what is considered a strain. Or different straits. And that's again highlighting how much the rules needs to be set up and need to be really well established because once we start to do those kind of technology, we need to always talk about the same thing. So once we have done this analysis well we can see that the the tree here the camera tree is really interesting because I think it's very visual it gives you clearly almost your answer is we had in that instance out of the four two groups a strain A and strain B and A strain has related from the swabs was the same and the one in the sample was the same but both strains went different so. What kind of information does it give us? Well, obviously we get the full print, full print of this isolate, and we now have full traceability and we start to see. A bit more complexity in that in that case study because we started with thinking, oh, there's. Once someone at issue, and it's probably still true, but there's a bit more to it, occurs. We have now 2 strains and we can ask even more questions is. All those trains appearing because there's a potential response to the environment, but could be also because when we culture there, we introduce a bias. And the reason I'm saying that is because you start from a swab or you start from a sample and the sample itself is still present during enrichment, for example, so that it actually builds towards one strain rather than another. There's all sorts of other questions that can be assessed, but more importantly, you know you already have two. Trains and they have. They seem to have. The preference is not quite that we've seen strangulate them better within one swab or for a sum. So. Can we find even more? Information, yes, because we actually have opened up a whole book. We have the whole genome of those isolates. So we can do factory mapping, tracing, tracking and tracing. We can investigate cross contamination. We can do investigations that way, like we used to do with MST. So we can do Linji break and it's much stronger because obviously we are not looking at 7 genes and only about 1000 or even LES of a gene. We are comparing with full gene and then. This is applicable to a lot of different pathogen, which all have some schemes and programs of genome sequencing like some analysts, Jerry Coli and many others. So we can do a manifest, we can do whole genome MNST, we can do single nucleotide polymorphism, but we cannot explore a lot of additional data. Notably, we could look at serology, which we can do to a certain extent with the MANESTY, but now we've got the whole genome, we can really look in details. What is actually encoded in DNA? We can assess some antimicrobial resistance. We can look at viral Inspector, we can look at plasmid. We can look at a lot. A lot of. Different traits that are actually invaded in DNA. But these data always more benefit, always beneficial. Do we always need to have all these data? Well, probably. But. It will always, always. Be critical to to have a lot of quality controls and make sure that all these announcers are done with very strict rules. And when we look at the sequencing, which is quickly summarized here, you've got all the wet labs, the side of things where you have to make sure the isolate is pure, for example. And although for eggs we're going to see if it's pure or not, it needs to be at that point really carefully cultured, but not. Too much culture because we might use some traits. The DNA quality is important the way we're going to do the library. The way we retrieve the data, what we're gonna put into this system needs to be of great quality, because obviously if it's not good, that and the start's not gonna be good at the end. So that's the wet lab stuff, but there's also. All the bioinformatic, because as I was saying, those technology generate such a huge amount of data that it's not going to be a matter of looking at reeds and traces like we used to 30 years ago. It's all going to be done by very powerful software. And we're going to have to assess the number of reads, the coverage, the error rate and what kind of software we're going to use. Because this is going to be really important because again, the models we're going to use, we're going to have. A real repercussion or a real impact on the quality of the data and the interpretation we're going to do with it? So. What is really important is to establish rules, as we're saying. So are we talking? The same language and having the the same references and it's very important because I was talking about genomes. What is a genome? What is a core genome, what is a pan genome? Core gene amnesty. There's a lot of new words that are here and that are now used and we need to define them very carefully because. We might not talk about the same thing. And then how is the data obtained? You know, is there some consensus standards, some standard operating procedure? Because we're talking about introducing this into service lab. So we need to have probably some very strict rules and for example, we start to have them because some ISO standard been generated. Giving definition, giving rules on how to do the, the, the technology, the wet lab. And that is very important because then we start to define framework, but there's also all sorts of programs that have been developed by. The FSA, the CDC not to believe Pulsenet where you've got whole programs where any kind of. Isolates linked to an outbreak will be sequenced and those these data is available for us to use and it's very important because the FDA, the UK pages, et cetera, we'll have those databases and that means those DNA, those genomes are there to be. Investigated even for further linkage to outbreak and etcetera out there, so. Knowing how that data has been generated is very important. How do service lab are going to generate this data? We need to be able to compare things and make sure that the quality is standardized. Then there's some questions about who holds the data. Obviously, because all this is linked to database, and database is curation has always been a questions who owns those databases, how they are created and how is the knowledge transferred? Is it also, there's always going to be some sort of retention of knowledge who wants the data and that's going to be really, really important because lab like ourselves are doing everything in house and that's the whole point sometimes. So we have the control of their data and we know exactly what happens. Do it and we can relay the relay that information so. Another very important aspect of all this is what we call the metadata, and basically is. Generating as a genome is now not the problem, it's all the data that is associated with it. You know, what is the sample? Where has it been collected, how many times has it been cultured? All this information will add extra value to the data, which is just a T&C's. If we don't have that data, there's not much more information we've got at the end of this. So it's very important to always link up to data and I think that's my part done and I'm going to hand out to Joanna now. Thank you very much for your attention. Thank you, kristoff. So in addition to it's used in the investigation of foodborne outbreaks, whole genome sequencing can also be useful to characterize other microbes, especially those that are interesting in terms of beneficial effects. So today, I'm going to talk to you a bit about how we can use it in the probiotics formulation industry. So, as I'm sure you all know, probiotics are live microorganisms that confirm that conferral health benefit to the hosts when present in adequate amounts. These are mostly lactic acid bacteria that belong to genus Lactobacillus or bacterium, among others. However, you also may be familiar with secondaries boulardii, which is a yeast commonly used against gastrointestinal disturbances caused by enteric pathogenic bacteria, and. Although the effects of probiotics can cover brain, cardiovascular and metabolic health, these are all the result of the direct effects in gut health and these include the inhibition of enteric pathogens through nutrient competition as well as production of bacteriocins and other micro antimicrobial substances. It also relies on the production of growth promoting substances such as folate or Abu flavin. Even in the bioconversion of substrates that can help, for example in the production of Mino acids from available substrates, biofilm formation is also critical to maintain the integrity of the gut barrier, and in addition, probiotics can also work as immunity modulators through the induction of specific immunity key players such as immunoglobulins. So as a result of this wide spectrum of functionalities of the increased awareness of on preventive healthcare and on the technological advances that allow the development of more efficient formulations, the global market for probiotics has surpassed $47 billion in 2021 and is now expected to increase at a compound annual growth rate of 7.5% until 2030. One of the the critical points for the success of this formulations in the market is the adherence to what somewhat? Strict, sorry, regulatory framework, especially in Europe where probiotics fall under the general food law. So the nutrition and Health claims regulation of 2006 is applicable to both nutrition and health claims, and it states that food business operators must obtain a prior European Union Commission approval to state the beneficial effects of their products, either through labeling or through advertising. This has resulted in the majority of the claims submitted to the FSA being either rejected or withdrawn and this is mostly due to the insufficient characterization, sorry, of the probiotic strains that are used and actually only one claim has been authorized so far. And this is the use of life yogurt cultures. And we can see that in the scientific opinion limited by the FSA, not only there is the description of the strains and their beneficial effects in the target populations and studies. Conducted to prove those effects, but it also states the minimum viable counts in the final product that is acceptable. And so, more recently, due to some differences in the understanding of these regulations, some countries have devised different approaches, mostly on labeling and on the use of the probiotic term. Just this year, France has allowed the use of the term probiotic as a nonspecific health claim as long as it is accompanied by specific authorized claims such as these. Live yogurt. Cultures. So, considering that most of the claims are rejected or withdrawn due to the lack of characterization, it is important to address the stages during probiotic formulation rollouts, especially during the process of strain selection and development as well as product and process development. So in order to be used as a probiotic candidate, strain has to be sufficiently characterized. It must be safe for the the purpose that it's. Intended to be used for. And um. Also the the the benefit, the benefits of the facts must be proven by at least one human positive clinical trial, or at least it must be long. This train must belong to a species that has a recognised benefit already, like like the the yogurt strengths. Finally, before being able to to be selected as a as a probiotic strain, this strain has to be resistant throughout shelf life so that the viable cell count remains at a dose that is effective throughout shelf life. So you can see where I'm going with this, and the question is how can hold genome sequencing help during this process of selecting? The probiotic strain. So as Christoph already mentioned, whole genome sequencing is the gold standard for gathering all genomic information and ambrosial string it allows us to characterize its full genome, including including any accessory genomes such as plasmids. And when we compare it to other molecular characterization approaches, whole genome sequencing allows us to achieve a full taxonomic identification, strain level and characterize function at the same time. This means that when performing holds enough sequencing, regardless of the platform that we are using, we will be able to gather the genomic data that can predict. Have to go. And microorganism, as well as its capacity to survive in the guts and urine shelf life. Moreover, hold genome sequencing is especially useful for a rapid assessment of risk factors through the identification of virulence and toxin producing genes, so as well as some antimicrobial resistance genes that can hinder the beneficial effects over formulation. As an example, I would like to show you the characterization of a Lactobacillus plantarum strain. It was isolated from raw milk, and that is. Characterized by holdingham sequencing. So the first thing that we can look at. This is the genome assembly statistics. This gives us an overview of the genome, genome size, GC content and the number of protein coding genes and of those protein coding genes, how many of them are assigned to known function. And this gives us an idea of how well described this genome is. After the genome assembly, the assessment of the obtained genomic data can show us the presence of probiotic market chains. So as you can see in this example. Of the 122 probiotic market genes I think that were identified, most of them were related to an antioxidant function, for example a reductase, which is commonly associated to oxidative stress adaptation that is critical for survival in the gut. The same goes for bile tolerance genes and acids stress adaptation genes. Umm. In addition, you can see that 20 genes related to adhesion were also identified and this is critical because this can be good predictors of probiotic potentials since these organisms will be competing with the pathogens for colonization of the gut wall. And a little distraction clearly has potential to be used as a probiotic. You can see that it's also were found some immunomodulation genes and some temperature stress genes also. Several antimicrobial resistance genes were also prompted. So it seems that before selecting this train for further product development, some experimental validation to confirm the safety of this train must be carried out. So this is an example of a typical screening of a probiotic strain that relies on the incredible amount of of genomic data and on function and safety predictions that is possible to obtain with holding them sequencing and that could not be possible. Using other molecular biology approaches, at least in this in this in the same time frame. So. Of course that when you have this information in your hand, you can also check the consistency of your formulation throughout time and potentially identify any microbial contamination in your in your product. So as you can imagine. Due to the resolution power holding them sequencing can also be of use. Great use to other industries and although I have discovered an example for probiotics from formulation it's applications extends further to starter cultures on on fermented foods and beverages such as beer or or confusion. So with this in mind. I would like to just wrap up on what we already covered today. So the take home message is that the the whole genome sequencing is the new gold standard for investigation of foodborne outbreaks and that while the standardization is critical as Christoph was mentioning, this will have to be highly reactive due to the to the dynamic nature of the of the technique itself. And finally, I would reinforce that the characterization of beneficial strains must be also tight to hold genome sequencing due to the registration power that this offers compared to other techniques. So this is what we had for you today. I I would just like to ask you that before we move to the Q&A section for you to please give us your feedback on this webinar by completing the available survey before you go. So now we have a couple of minutes left for questions. So please just submit any questions you may have on the Q&A tool that's available. Thank you so much for your attention. So maybe I'll. I'll start with a. A couple of questions that are already in the in the inbox. So Christoff, I think that the the first one is probably for you. So the question is can whole genome sequencing predict phenotypic traits such as antimicrobial resistance, virulence and serotype? Yeah. Thank you. Well, obviously, as we were saying is you've got the whole genome, that's exactly what it is. So you've got all that information so you can read, investigate and start to look at the potential of a bacteria that it have antimicrobial resistant genes present and therefore get in actually. Have those trades. It's always difficult to link the genome and the phenotypes of the phenotype is actually the trait that is expressed by by the the Organism having the the the genes in. The information potentially encoded is one thing. Can they actually express as another one? But you can as you were showing in your example. At least you know you can have some potential of antimicrobial resistance. It's not. If you are not having the genes for it, clearly you're not going to be. The fact that they are there is not always associated with the actual possibility to do it, but you certainly can look at it. And the violence. Yes, you can also do that because it's sometimes linked to plasma, but they might be retained, not retain. Those are kind of lava, but it's very important. And the stereotype. Yes you can. Essentially do that. That's what we were already doing with the MSD, which was really kind of. The beginning of of characterization, and it's it's it worked really well with certain Organism natively salmonella, not as well for for Listeria and other Organism, but because we've got a whole genome, we can really look into that and we can therefore do some stereotyping. But we always need to be careful to bring it back to the real functionality of those genes, because having all the information without certain the metadata again can be interesting because it can bring. This type of information and we can confirm. That the ability of all streams. Yes, definitely and it can lead us into the right direction and when we are searching for this, for this, for these functions. So, um, another question. Umm. I would go to maybe another question for you, Christoph. So the question is, do you see any other uses for holding them sequencing in food safety other than differentiating differentiating isolates from each other for surveillance tracking of sources? Of outbreaks or contaminations. Yeah and I think it it's, it's kind of linked to to the to the previous questions in a way because you. Again, you can, you can try to understand why Australian could survive in certain environment. You could, you could have wind formation on its capability to respond to jokes, additive stress and potentially. Be LES affected by certain cleaning regime or certain chemicals and things like that, so they there is an added value by having more information about about. Any kind of Organism. Because what we understand them better. We we we can then. Try to link some functionality or some. Environments and see why they could cope or not with this type of. The conditions and to link up to your example your it's exactly the same idea. Having these kind of insight in their genome can really help on understanding what they're capable of and what they could sustain on arm. So yes, way beyond just different safety. OK, let's move on to another question. Umm. So another question is, instead of reacting to an outbreak, would it make sense to proactively monitor the production environment using whole genome sequencing? I would say that yes it's definitely worth having a look on what's happening on your production environment before a disaster occurs and and you are you are in desperate need of recalling a product. So I would say I would say yes due to the resolution power that we now are able to reach using whole genome sequencing especially using a whole genome metagenomics, you can really go deep on the. Microbial populations that are living in your production environment. So yes, that is. That is one key, one key use for whole team sequencing. So I'll take another question. Do you like you'd like to add something, Christoph to that? No, I think, I think it's exactly that. No, you think you could. All this is really here. OK. So I'll take another question. So this next question is about startup cultures. So the question is, is it possible to identify yeast starter cultures using whole genome sequencing? Yes, definitely it is. It is possible. So we covered mostly bacteria here because it's probably the most common application. But yes, whole genome sequencing can be used for. Other microbes, including yeast. So actually for a beer. There are some example studies out there covering psychomancy species for ale or for lager beers, and it's possible using whole genome sequencing to even pinpoint flavor substances to specific genes in the genomes of these of these microbes. So yes, whole genome sequencing can be useful for for yeast starter cultures, for instance. Selling beer, but also in other fermented foods and beverages, such as Google Shepherds stance. So. I'm going through. Some of these questions. So uh, one question here about about time is how long does the the process of sequencing last because of? Do you want to cover this? Yes, it it really depends on what kind of Organism the platform. Really. But it can be relatively quick. Sanger was was extremely fast because we obviously investigating such a A a fraction of the genome. When it comes to whole genome, we're talking about few days. It really depends on how deep and what other questions if it's a. Relatedness, study that. That goes a little bit quicker, but if it starts if we start to look at functionality, looking at attributing and annotating. Genome where you actually look at genes and trying to find their function where they are. This is a bit more. In depth and therefore will take longer, but we're not talking about a month that was. The whole idea of NGS is allowing you to generate literally millions and millions of reads, so little bits of of of sequences in a matter of hours. So it can be as quick as few hours to 72, a bit longer for a run. And then there's all the bioinformatic that starts while the sequencing is going on. You need to. Then there's a lot of other functionality that can only start one. We've got the overall data. So we are talking about few days. It really depends on how how many samples, how what type of genome as well, because some of them will be more complicated to generic than others. Yes, definitely. There's an interesting question also on another application outside food, but I'm going to answer this one. So the question is, could whole genome sequencing be used to investigate pathogens and cosmetics and toiletries, and is so? If so, what are the benefits and what would be the approach to be the same as with food? Sorry, would the approach be the same as food? So I would say that. For cosmetics and toiletries, the most challenging part is actually obtaining DNA. So with these matrices the most the most hard work. Is in obtaining and obtaining DNA. But if you are able to obtain DNA then the the approach is pretty much the same. So this one is covered also. Umm. Uh, there's also an interesting question on reference standards. So is there any certified genomic reference standards available for different species? Do you want to take this one, Christoph? Well, there's a lot of programs for, for, for Listeria, salmonella, E coli and there's some some center of excellence throughout the world where they are actually characterized and it kind of make and there's also all the strains that we use in the lab that are ATC and ATC which is the bank where where all the strains are kept do also do their sequencing. So you could use their data which would have been reproduced. Several times like we do, and we do this in in houses we receive once our our our reference strains to see how it deviates. It's part of our of our. Quality controls so. Those genomes should be relatively stable. There was also genome DNA that can be kept because if you keep an Organism alive and you keep on culturing, you're gonna introduce some some some variation, especially because the Latin variant is so remote from time from from where usually the oscillators being found. But these DNA, yes they and they use internal control, that's obviously. But yes there is some genomes that are kind of this is the genome of Nottingham's train. XYZ and this is your your control and you can rerun it. So yes there is and obviously. We use databases. We've curated genomes. That's how we find our closest match. This is how we can do this SNP. This is the type of. Of databases that need to be extremely well curated because they could they could impact the overall result. So yes, there is. There is some references, but you can make your own because once you've you've got a specific salmonella and you've sequenced it and you sequence it 10 times, it becomes your reference to a certain extent because this is your gold standard. So there's loads of ways of doing it, but yes, there is there reference, which of course there is. Yeah. And in addition, in addition to that, the the use of, as you were saying, of reference traits that are deposited in in reference cultural collections and that have their genome fully sequenced. Sorry, it's crucial to, to the, to the success of this of these strategies and that goes a bit in in line in in to another question that we have is that. If there are taxonomic changes in bacteria that can impact the results. So we know that the bacteria are commonly the subjects to taxonomic revision. And so that's why it's very important to work with reference strains that are fully characterized and that are and that's and that have their their genome sequence available in the. In publicly, in public databases. Sorry. And I think those references are very important as well because as new technology arrived on the on the on the horizon we talk about NCGS again and there's loads of different technology to be able to do next generation and I think having those. References will be the way to actually really compare how good or how complementary methods are. So you're right but DNA once we have got the book and the way to reread it is it's that's where your references and then that's, that's very crucial to have that. Yeah absolutely. OK. So I think I'll cover pretty much all the all the questions we have, the ones that we weren't able to to to answer, they are captured and we will be answering them after this, this. After this webinar um. So I think that uh for for now, I'll give the section back to you. Jennifer, it was a pleasure to be with you today. Thank you so much. Yeah. Thank you very much. _1743715799099