 All right, I think we can start so welcome everybody to this latest instalment of the Canadian Biomanic Workshop series, focusing on microbiome. Welcome to Calgary. Just a first slide to let you know that all of the content that we're producing today is open source, freely available under the Creative Commons license so you're free to use any of it. There's a directory website where you can access all the material all of the lectures are going to be recorded are going to be available as well. So feel free to use and exploit any of this material as you see fit. So, this first lecture is this first module is really just kind of introduced orient ourselves to the actual workshop. So my name is John Parkinson I'll introduce myself a little bit later first thing I need to do is a land acknowledgement so I would like to acknowledge and pay tribute to the traditional territories of the peoples of treaty seven located in the hearts of southern countries, which include the Blackfoot Confederacy comprised of the six Seeker the pecani and khanai First Nations, the Zootini First Nation and the Stony Nakuda, including the Chiniki, there's poor and good Stony First Nations. The city of Calgary is also home to medicine nation of Alberta region three. So we're going to cover in this very first kind of introduction it's supposed to be just a short just to get us all in the same wavelength get us prepared about thinking about microbiome and little bit of history. By the way, can you hear me at the back. You can't hear me at the back so how about now is that helping. So I might use or somebody might want to use the, there is a microphone here but if I just raise my voice then that's good for you. Perfect. All right. Okay, so today it's just going to be a, or this morning, I'm just going to give you a brief overview of the workshop briefly discuss a little bit of history of the microbiome studies of the microbiome review some of the terms are all in the same page, and then just finish with kind of I guess more of a personal view of some of the challenges that we've been facing in microbiome studies as well as some of the opportunities. Okay, so just to introduce you to the team. So Morgan at the back, Google refers to him as a person in a striped shirt so give us a wave Morgan. We have near over there at the back and Sydney who have done a tremendous job in organizing and setting up all of the logistics for the workshop so fantastic well done them. And then, is she been here. Okay, so she been. I should put names on all of these, shouldn't I. So she been who has set up all the AWS services. He's the guy at the top with the cherry tree behind him. Robin, where are you Robin. There you go give a wave over over there Robin who's one of our ta is myself john Parkinson Laura where's Laura. Oh, there's Laura Laura Sakura at the back. We have Ryan over there and other ta henna. Hi henna. And Anita, who is going to be joining us I think on Thursday Friday, and then Kevin, where's Kevin. Okay so Kevin, we've introduced Kevin when he arrives. I'm just going to hand over to Sydney who's going to give us some important health and safety information. All right. So most important bathrooms, you leave any of these doors turned right had all the way to the end of the hallway where the elevators are and then there's bathrooms over there. There's a little bit of a track sorry. If there is an evacuation or any kind of emergency, leave these doors turn left go out the front doors you guys came in. Basically follow me essentially but you'll be going out turning right going around this building and there's a building over there with an atrium right next to us that that is the assembly point if there is any kind of emergency evacuation. I think that's it. So what was the disparate emergency instructions but that was the emergency instructions those the emergency instructions if there is a tornado. We're going to shelter in place right here so don't be alarmed. Is that likely. Okay they will not be any tornadoes this week. So, just to orient you with the schedule so kind of the format of this workshop is really do a kind of a one hour lecture before each module and then you'll have two or three hours to work through kind of a prepared tutorial that is available online. And then we have the TAs to help you work through that as well so there will be a TA who will put the workshop up here go through it and then other TAs that are kind of roaming around and helping people are getting stuck. So that's really the format so in the foot in this first day our drive stops going on it. We are going to start with Morgan session which is looking at kind of 16 s sequencing and we have a 16 s lab associated with that. And then this afternoon we're going to be looking at some stats and visualization tools. So today is really a 16 s day for those who are interested in 16 s so maybe raise your hands those of you who are interested in 16 s data. Okay, and raise your hands if you're interested in meta genomics data. Right, and raise your hands if you're interested in meta transcriptomics data. Okay, hopefully I'll be able to convince you on Friday that more of you should be doing meta transcriptomics. Tomorrow Thursday, that's all day on meta genomics. So Morgan will be covering taxonomic functional annotations, and then Laura is going to be covering many genome assemblies, generating mags and so forth. And then on Friday, we, myself and Ryan will be presenting this kind of meta transcriptomic tutorial and then in the afternoon, something that we've been introducing last few kind of rounds of this workshop is on sample collection and how you go about designing clinical trials because we found that participants find this aspect quite useful to hear how do we go about designing the clinical trial. What do we need to worry about when we're collecting samples maintain their integrity and make sure that we're minimizing the biases that are getting introduced in these kinds of these kinds of studies. A new thing that we have just introduced this year this June is students intros. So one of the more rewarding aspects I think to us as instructors is actually learning more about what the landscape of microbiome research is out there. And so for us, what we're going to be doing we're going to be introducing the work that we do. But we also want to hear about the work that you're doing and it gives us you know real good sense of what is happening in Canada in terms of microbiome studies so there are these kind of flash talks where you have a few minutes to kind of present the kind of work that you're doing and I think that'd be one of the more fun aspects. It will hopefully really promote networking as well so that people people who are working on similar problems. You can meet over lunch and discuss some of the challenges that you've been facing or some of the opportunities that you've also been encountering as well. So, just in context just in that context of introducing ourselves and the work that we're doing so to introduce work that goes on in my lab. So my name is John Parkinson. I'm a senior scientist at the hospital for sick children. I'm also cross pointed at the University of Toronto. Research in my lab covers these kind of four areas so we're interested in pathogen host microbiome interactions are using parasites and looking at what happens when you infect people with parasites or mice with parasites how does that impact the microbiome. So one study I'm really interested in and excited by is this microbiome and malnutrition in pregnancy so this is in collaboration with the Aga Khan University in Pakistan where we're following hundreds of young women and monitoring what happens over the course of their pregnancy how their microbiome changes, what happens if they have low BMI versus high BMI. So I'm very involved in studies in pediatric IVF sick kids. And lastly we work on chickens, because a few years ago I found out that it's a lot easier to get funding for chickens and chicken research and it is to get funded for kids research. Okay, so just for this kind of second half of this morning's introduction I just want to just get us in the mood of microbiome and where we are with microbiome. Can you hear me at the back by the way. Wonderful. Okay, so just this get us all in the same page. Individual bacterial species we know that they don't live in isolation actually form these kind of communities these very complex microbial communities and within these communities bacteria subject to a whole range of different systems featuring competition mutualism even co-dependence. And from a human health perspective we're seeing more and more kind of links with diseases from IBD diabetes malnutrition anorexia was one that came out recently. So, really, I think we're all kind of on the same. We're on the same page we really kind of should all be evangelical about how microbiome is impacting everything. So, again, can I get a raise of hands for those of you who are working in health, human health. Okay, and those of you who are working in non health related areas. Okay, that's great. That's great. We do have a little bit of a event on on, I guess, clinical and and human health side of things but overall we are kind of aware that microbiome does capture things beyond human health. And so we will be trying to place kind of microbiome outside health context. So we've seen a real explosion of microbiome studies in the last 15, 15 years or so. So this just a graph from PubMed showing the number of publications with microbiome in the title in 2007 there was only eight publications mentioned microbiome. And as we're all aware this has really been driven by advances in sequencing technology. To hold out these were two of the first studies that mentioned microbiome in the title. So one was a review article in the current opinion in lipidology. That was the very first article that mentioned microbiome. The second one was this one in science. Jeff Gordon was involved in it. And this was a meta genome analysis. So here they use 16s sequencing as well as metagenomics to study the distal gut microbiome of humans. And this was in the days when we didn't have this next generation sequencing it was all done using this sanga sequencing technology who's familiar with sanga sequencing technology. I don't know who you are but most of you are not. I am not going to tell you about sanga sequencing technology today. But it was very time consuming very costly. And so one of the one of the studies I kind of enjoy presenting is this one. Does anyone know who this man up here is. It is well done he that is great vendor. He was involved in the generation of the private side of the human genome consortium that was published back in 2001. He had this Institute called the Institute for genome research which was subsequently renamed as a JC vendor Institute JC VI. So he's not short of an ego. He had done the human microbiome. Sorry the human genome. They realized I had all this sequencing capacity so what to do with all these sanga machines that were not generating lots of sequence data they could sequence more bacteria or whatever. So he has this yacht it was called sorcerer to and he felt like going on a bit of an expedition with his yacht so he sailed around. I think the idea was to try and go around the world I think he gave up when he got to Hawaii. And then every so often he dump a bucket over the side drag up some water and then extract the DNA and then just sequence what was in there. So these first examples of metagenomics he generated 7.7 million sequencing reads which is a huge number of sequencing reads in those days where we're using sanga technology. There are these machines that would have 96 capillaries and each of those capillaries would run one sequence, and that would be just one machine so you'd have these banks of these machines doing this so they're running 24 seven. So in those days you got Nova Seed, Lumen and Nova Seed and so forth, and it just blows that sanga sequencing out of the water. However, we didn't have that in those days. So what he did during those 7.7 million sequencing reads he found 6 million new genes, and just in terms of preparing this kind of NCBI what was known in the NCBI was all dominated by eukaryotes. Lots of bacteria so it just shows, or it showed at the time just how skewed as sequence representation was in the sequence data sets. One of the things he was very interested in was, I guess climate change used to be a thing back in 2006 2007. So he was more concerned about climate change then. And so he was interested in these hydrogenases, which were supposed to be making the conversion of a lot of these biofuels much more efficient. And so he'd set this project or one of the context he'd set this project for was trying to identify new enzymes that could make these processes much more efficient. One of the things that's really driven microbiome research is really this idea of sequencing right so traditionally microbiology relying on doing culturing to try and identify what was in your particular sample sequencing provides a route to identify what's in there, particularly when bacteria can be challenging to isolate. And at the same time by doing sequencing you can also identify functions within that sample. However, the story is not as simple as that. So there's a colleague, Mike's your ex who is at McMaster, and he's really been promoting this idea of culture dependent sequencing or culture enriched sequencing. And just in this top graph and right here, the dark blue graph is what you get if you do culturing versus the orange rips is what you get if you do just sequencing. So I think this really shows that we shouldn't, or we should acknowledge that maybe sequencing isn't getting at what is all within the sample. Maybe these kind of culture enrichment techniques can help tell us more about what is happening in our particular sample. And then developed I think it's a set of about 40 or so different growth conditions, culture conditions that he would take a sample plate that's hard because those 40 conditions, grow the stuff up grow the bugs up and then in the dark blue, this is what you get when you do your culture, when you do your culture enrichment. This outer ring is what you get when you do your sequencing and the inner ring with light rays what you get that are shared between the two. So you can just capture way more when you're doing this kind of cultural enrichment so it's really, I think quite compelling. Now, when we're doing a microbiome study, what is it that we might be missing if we're just applying sequencing technology. So Mike reckons that he can recover using these cultural conditions, more than 95% of the tax are in any given sample. Okay definitions. This is so that we are all familiar with the terms that we're using when we describe microbiome so my microbiome is a collection of genetic material within an environment. I think people use it interchangeably with the set of microbes in the environment but it's really originally it was really focused on the collection of the genetic material. The microbiota are the set of microbes that are found in the environment, metagenome collection of genomes within environment. Important to distinguish that metagenomics is not the same as 16S survey so those are two very different things. Metatranscript tone collection of the transcripts within environments and then marker gene survey is so this is where we're doing an amplification sequencing of a targeted region that can act as a molecular barcode. So one of the early studies that was using the 16S kind of approach was this one from a colleague, Dan Frank published 2008, healthy individual individual with IBD, looking at the microbiome and the colon, you can see that individual with IBD very very different. But the problem with these kind of 16S studies as time has gone on is that we don't know if this is cause or correlation, whether the messed up microbiome of the IBD individual is really due to the disease or whatever it's causing the disease. So, we're probably all aware now those, those of you that are doing the metagenomics metatranscriptomics that there's more and more emphasis in terms of publishing and so forth to get more at the core of these kind of causal mechanistic relationships. And so we're putting more and more of this workshop kind of devoting it more in terms of metagenomics and we kind of shine a little bit away from 16S that's not saying that 16S doesn't have a place. I think it's incredibly useful because it's cheap to actually fill in the gaps because metagenomics as you know it's very expensive. And you can only selectively deploy it to certain sets of samples, whereas you might want to fill in the gaps in between and make sure that nothing has really changed at dramatic time points in your particular data sets. So, given this kind of cause correlation, metagenomics, metatranscriptomics, these are really starting to take off maybe metagenomics more as a way of providing more functional insights, mechanistic insights into what's happening within a microbiome. Again, one of my favorite studies to show 2012 from the Human Microbiome Consortium. This is 112 individuals, about nine different body sites, and the top graph shows what taxa are present in each of these individuals in each of these body sites. And they're very varied. So everybody has a very varied set of organisms that are present to each of these body sites, but when you look at the actual functions in this case it was keg metabolic pathways. These same communities all give you a similar breakdown of different functions. So this is suggesting maybe the community doesn't really matter in terms of who's there is actually what they are actually doing which is important. In terms of where does our microbiome come from, how do microbiomes develop the human microbiome. It changes as we age and I apologize for not putting the citation of this review here. The idea is that there are dramatic changes from birth up to about three years of age. And it's funny that they left at three years of age so as discussed with Morgan last night that there is very little data concerning the adolescent microbiome the adolescent microbiome. I think it's traditionally thought of as being very similar to the adult microphone but nobody's really looked. So, again, this is one of the interests that I have in terms of trying to look at what really happens in that kind of critical points in our development. One thing I want to emphasize, some of the main contributors in terms of what initiates a mode of delivery is probably the number one. The number one component that has the largest impact on our developing microbiome modes of feeding as well has a large impact as well as antibiotics obviously. One of the factors that does not seem to have an impact on developing infant microbiome is the placenta and the reason I bring this up is kind of a cautionary tale so that we can be aware when we're doing these microbiome studies. We can interpret these data sets and make sure that we are performing them in manners where we can actually be confident about the conclusions that we're drawing. So this was a study who's familiar with this story of the prep of the placental microbiome. Okay, just want to be okay great. So, this was a study that was published inside translational medicine 2014. The researcher collected placenta from 320 subjects under several conditions before 16S and metagenomics sequencing, and they did these kind of correlation studies and they found that placenta microbiome is similar to the oral microbiome. Okay, so there's this idea that somehow the microbes in your mouth were maybe somehow getting into your placenta. So there's a lot of claims and extrapolations from these kind of results. So, there was already a kind of a review of this particular study and they mentioned that this re-emphasize the importance of oral health during pregnancy. In fact, women may need to pay attention to their teeth even before they may become pregnant because the placenta develops early in pregnancy. This may be a challenge for low income women who can't afford dental care. Okay, so this is from the actual author and it's kind of like, whoa, this sounds really important and yet these are young, these are women, potentially young women who are already demonized by society and yet you give them another stick to beat them with, which is where you've got to maintain your oral health to make sure you have a healthy baby. So there's a lot of this kind of extrapolation from this one study, but at no point in this study was there any link between periodontal disease with the placental microbiome. And the other thing they found was only DNA sequence was detected, there was no live bacteria. So there's a lot of kind of extrapolation of what the implications of this research was, way beyond what the study actually said. And in fact, two years later, there was a study which looked at doing controls and basically taking air swabs or swabs of kits and looking at the ketones. So what happens if you just sequence from the kit or from the air, what do you get? And they found that the placental microbiome was indistinguishable from these controls, from these air swabs and so forth. So this is really quite a damning kind of indication of how a microbiome research can really go off the rails and even today we have a certain community of research who are convinced that there's a placental microbiome out there despite all of these studies. And I think there's one that came out a couple of months ago which definitively said there is no placental microbiome, and yet it's still kind of persist. So one of our microbiome studies we have to be a little bit cautious about how do we interpret our results and do the conclusions really are they really supported by the data. Okay, so I'm just going to finish with a couple of slides. What I personally think might be some of the more interesting challenges and opportunities. So looking at quantification, for example, hands up those of you who are now trying to control for quantification in examples. Okay, interesting. So we're seeing more and more of a push for by publications or reviewers suggesting that we need to start thinking about controlling for absolute versus relative quantification. So if you think about our sequencing, we know we're going to get 100% reads because it's all relative. So in terms of relative abundance you might say that this red tax on is in higher abundance in this particular sample versus this particular sample. However, where we control for absolute abundance we find that they're actually the same. So there's a number of ways that we can quantify as samples and they're spiking controls for example there's cell counting methods. So we need to think about how do we control for the absolute abundance within our data sets metabolites. How many of you are doing metabolites or incorporating some aspects of metabolomics. Okay, just for four or five. Okay, interesting. So, as we're starting to focus in on the functional potential of a microbiome we need to come up with kind of orthogonal data sets that can help confirm some of these kind of conclusions. So we can look at what's happening in terms of metabolic pathways within a particular microbiome. Does that correlate with the metabolites that we see within a particular sample. And the generational the integration of these kind of metabolomics data sets brings up another challenge which is, how do we integrate all of these different data sets or we've got microbiome data we might have some biomarker data of a biomarker data we might have metabolomics data we might have human genomic or genetic data, and we might have chart reviews as well so how do we integrate all of those different data sets to come up with how do we determine which of these factors one of the contributions of each of these different factors on health outcomes and I think there's a real need for methods to kind of take these kind of data sets which they're really not in a very mature kind of procedure at the moment these kind of methods. And so there's a real need there's a real opportunity for developing new methods that does a better roots or doing statistics and these kind of data integration. And this is potentially where modeling can help. Okay, so there's tools now that make you to model metabolic interactions within your bacterial community so you can do your sequencing you do your analytics you can build these models where you're starting to look at metabolic interactions within your data sets and that can tell you something and help make predictions as to what happens if I alter this microbiome once if I bring in this dietary additive what happens if I add in this organism, how does that impact the community. And I think that modeling we're going to see in the next two or three years, more, more and more these studies that are using modeling to help interpret these data sets. And finally, particularly for a human health or an animal health or one health perspective. The opportunities that we're seeing at the moment is, how do we go about modulating the microbiome. And so there's a number of different kind of products that have been created. So there's phase as prebiotics probiotics organic acids enzymes, probably a lot of the focus I think especially given the success of these people with transplants is really on the generation these complex communities, but the challenges have really best define and identify which of these products are most likely to be effective. And again, this is where these kind of microbiome studies can come in this is potentially where modeling can help as well.