 The aim of my presentation today is to basically present some really satellite view of the microbiome. So we basically have an understanding and the same wording, the common language that we're going to speak. And also I'll present to you a little bit what's coming up. What are the teachers, the TAs that are doing the courses, just to remind you some of the very important people that helped us, great tailwaters for all the outfall bio K plus, this lunchtime to redo all your microbiome while you're here. And the big people in front of us as well in the process. So when we talk about microbiome, we also met that genome if it's in the environment, but here we talk mostly about humans. As humans we have 10 trillion cells and 23,000 genes. The microbiome and the microorganisms are the microbiome that kind of our friends get 100 trillion cells and 3 million genes. So essentially for every human cell, for every human cell you have 10 bacteria, you're more bacteria or microorganisms than humans. And this is basically a super organism that you interact with it. Essentially the microbiome is another organ. So what does it do? It's very influenced by the environment. And also there's some host genetics to it, so we'll show that to you as well. Some of the microbiomes basically digest the food that you're having. Essentially, I like the body phenols, that's not you doing this process and it's a bug. But sometimes things go awry and you may have toxins, so it's still in others. It's important basically for two things, it defends you against bad bugs and it helps you feed yourself, get the nutrients. And basically the equilibrium between this really controls some of the health and disease states. And it does a lot of function. It supplies nutrients and energy and if you have too much nutrients, obesity and the double-edged syndrome, so there's a lot of microbial products that work in controlling this balance. It also prevents cancer, pituitary protection and all of these and toxin and cross-nutrient. And if you have chronic inflammation, it can favor the promotion of cancer. It also inhibits pathogens, so it's there to defend you, essentially. And some are good bugs and some are a little worse. For instance, C.G. Steele and autochloroquine and the likes. And it's also a source of pathogens, so you have to be careful. It's also a source of antimicrobial resistance. So this, because there's a lot of exchange between these microorganisms in this environment. It's also involved in your normal gastrointestinal and immune function. And if you have too much inflammation, if you eat bad stuff that doesn't sit well with you, you can generate some inflammatory processes. And you have inflammatory bowel diseases. It's involved in the motility. So again, IVS, constipation, diarrhea, bloating in your eyes. And it's also involved in cardiovascular health and controlling the amounts of lipids that you have in your blood and stuff. So essentially, it's very well involved in cardio and metabolomic diseases. When we talk about the microbiome, it's not just that gut microbiome. We have microbiomes everywhere. So hair, nostrils, skin, colon. And they all, it's just one human here. And all of them have different compositions in bacteria. There's even somebody who did the microbiome of bugs that you find on your windshield in the summertime. So essentially, we are covered with microbiome, and all of these are fairly different. Something you should remember as well is that the microbiome, it changes with age. So when you're a baby, you have a certain microbiome. If you're fed by a formula, so that's the environmental component, or if you're fed a breast-fed, it's very different. Well, somewhat different. As soon as you take solid food, there you go. You've got your microbiome changes. As an infant or a toddler, basically, if you take antibiotic treatment and change, if you're malnutrition or you all have the same ones, and then if you're healthy, it goes through a certain progression. As an adult, if you're healthy or obese, you have different microbiome. And as you get older, your microbiome also changes. It evolves with you in time. And also, one thing, and you'll see that we have a small presentation from somebody from C.I.C.A., but your microbiome, if you're a woman or a man, is very, very different. So essentially, at puberty, you can start having differences between a male microbiome and a female microbiome. This is hormonal, but it's also due to food intake in some ways. I mean, I will never eat tofu. But some people do it. So we fought our way at the top of the food chain is not to eat tofu. And this is shown here in a little bit more detail also that if you're the BMI here, how fat you are, basically, body weight index, it changes as well, and it's different for men and women. And I think that's not surprising. So in some ways, when I started doing this work, I write grants, but I didn't think, you know, I should have the same amount of women and men in my studies. I think this is essential now to control for diet, age, and also food intake. So we sequence a lot right now. There's a cute little baby, you can read it. It showed us there's a lot of... We started to discover, we sequence and sequence a lot more. So there's aquatic microbiomes, animals, soil, and sediment, and waste, plants, and others, and we have all these bacteria. So recently, the sequence they put into NCBI, a great deal more of sequences. And what's very interesting is that this is a power of discovery in some ways. These new genomes, I think there's a little over a thousand, they have biosynthetic gene clusters of different metabolic processes. And each, basically, each of these bacteria is around two million bases. A lot of them have these biosynthetic gene clusters, and essentially some of them have a lot of them, even if they're not that big. There's a series of DNA segments and basically clusters that codes for enzymes that process different molecules. So there's a great deal of new chemistry and biology in these, and it's also something that's very interesting in terms of bioprospection. And I say that because right now there's a lot of efforts that are being done to essentially look to generate some of these databases. And I think you should, I just put a few there, there's some obviously on the Human Microbiome Project, lots of data there that if you want to download, sometimes you say, I'm going to do an experiment, but listen, why not go check if somebody else did something, or they could be your controls for your study, or if you may test your own hypotheses by using somebody else's data. So you're not being a parasite when you do that, even if you're a doctor, you ain't in general. You just need it. But in essence, there's also, if you're working in an environment, there's the same, you have a lot of tools everywhere. We're going to go over some of the tools in this class. So that's very interesting to know. And there's also this new one that just came out. There's a lot of microbiome data here, and it's a little bit more cleaned up than some of the databases that you can find out there. So what happens to the microbiome? So it changes a lot. Supposedly in this room, maybe 40% of our microbiomes are in common, and the rest is very specific to you. So that's one thing you'll have to remember. You are the best control for yourself. My microbiome looks a lot like mine during time. So doing these types of studies with the repeated sampling of the same microbiome. And there's a lot of interesting things that happen in some ways. We did a lot of studies treating healthy people with antibiotics, and you see a real shift in essentially in the bugs that are there. You select some, you select some, you make some disappear. It's all basically the level of sequencing as well. I don't remember that when we sequence, if you do that 10 times, the DNA will be sequenced 10 times. If you do that one time, the DNA will be sequenced one time. So if you change this, you have to go really, really deep to find species that are not there at very frequent ways. But it can change really rapidly. Obviously, antibiotics is a big kick in some ways, especially depending on the antibody. But let's say if you take somebody's anemic and takes iron pills, it's going to change a lot because bugs live iron, and it's very dynamic. It changes quite quickly. But it has a tendency to come back to some sort of homeostasis ground for yourself. I mean, because you're in an environment, you have your own genetics, you have your own food habits, it has a tendency to go back to normal. But when we did this particular experiment, we'll go over this in detail a little later when we do a more scientific presentation, we actually gave antibiotics to healthy people because we wanted to see just antibiotics. So we selected them for all sorts of processes in a sense that they didn't work in a lab or a farm. They were normal people, so none of them were scientists. And then essentially, we tried to basically control for a lot of variables. And then we gave them an antibiotic. And this is what happened, basically. This is a PCA, a principle component analysis. And this at the back here, this is the blue, the little gray here, this is where they all salt. Then we gave them an antibiotic for seven days. And at seven days, this is where they are. Basically, they all change. It's very distinguished. And then we came back 90 days later and asked them, that's kind of the paradigm. After 90 days, your microbiome is back to where it was. It's mostly there, it's a pale blue, but it's a lot bigger. And then some of these people, for instance this person, never came back. She's one who, in the course of the study, became anemic and we gave her iron. This is where she ended. So it's very dynamic. It can go really quickly. So in terms of doing microbiome work, it's a little bit difficult. So you have to think about these concepts. One other concept, they always say that brown bread is better than white bread. Is that true? You have to think about it. It's actually true, depending on your microbiome. Some people, the white bread will be better than the brown bread won't be. So you have to think a little bit outside of the box in some ways, because this is happening right now. Just a little foot for thought here. There's some really wonderful things that are happening in terms of the microbiome. We have this process where we can transfer healthy microbiome to people with specific infections. So these usually affect elderly people. Average age is 80. They get sick still and then they basically can die from it. And it's a lot of people. It's 40,000 people in the U.S. a year. But we have a cure rate of nearly 90% with this repopulation, basically reintroducing healthy microbiome into these people. Tell me about drugs that work that well. It's very, very interesting. There's a bit of a yuck factor, but in a sense this has been worked out right now and it's been done in our own hospital. So you have to just validate the pill that you're going to give to these people so you don't give some bad stuff into that. There was a very interesting paper. It was in a bio archive. It's not public shit, but they took a chili fish. It's a teeny vertebrate fish. And they took the microbiome of these younger fish and then gave them to older fish and then it lived longer. So it's also something that's really interesting in terms of what's happening with the microbiome and what we need to learn about it. There are even now companies that you can send your little poop to them and basically they will, not sure about the quality of the service, but they will tell you maybe you should eat this, maybe you should eat that. It's quite interesting. I'll see how long they survive. There are some ideas here about the power to drive co-evolution. So in some ways the microbiome works with us, our dyes change, so the bugs co-evolve with us as a human species. That's very interesting. We'll have a section also on the responses to drugs. There are some drugs and some bugs that don't go well together. For instance, if cardiac patients that have heart trouble and they give them digoxin, there's a bug called Ericatela lenta. If you have that, it will not work very well. You have big side effects. So we have, the bugs have a lot of effects in processing some of the drugs. And also some of the drugs will also control the type of microbiome you have. So it's a two-way combination. And as I said, and this is what interests me the most in some ways, I think it's a very new source of interesting metabolites in those biocytic gene clusters. There's plenty of opportunity to do big data in there and do machine learning and stuff. And we'll talk to you about that as we go along. So I didn't want to take, I want to do this pretty quickly so we don't get too late. I just want to tell you what's coming. So after me you'll have metagenomic, how to approach it. So we'll talk about the tools of the trade, time, 16S profiling, how we do the reprocessing. And this will be done by Robert. Now he has a beard so we didn't want to be recognized, I guess. But in some ways some of the tools of the trade will be shown to you. And some of these tools are always, in some ways, some sequencing. We do a lot of sequencing. I'm just showing you what the way we do it. But there's other methods to sequence DNA that's quite efficient as well. In essence, it all starts with the reads we get from the sequences and the unit called the camer. The camer is 21, 31, 41. In vectors, usually that range is good. And what we do is we assemble these reads with the room graphs. And then do the assemblies. And remarkably, if you're there about 1%, you'll be able to assemble 80% of your genome. So it's pretty good. And then what you can do, these are just a normal assembly. You can take a reference database. Let's say it's other species and basically cameraize it. So each one, you can see that there are thousands and hundreds of thousands here. And each one is assigned a different color. And then you color all the camers and then you go back in the graph and you get a colored the room graph. And then this colored the room graph, you can see and identify all of these assemblies, which species it is, very, very readily. Obviously, if you give a different reference database, if you give all the ones that say resistance genes, kinase or phosphatase, you can do this the same process and you can get how much in this microbiome are phosphatase present or classmates or genes of resistance. So these are very, very powerful to start asking. Not questions of who's there, but also a little bit, what are they doing a little bit? But it's not metatranspectomy, but that's John telling that. It's a very good indication of what's going on. A little later, the metagenomics, how to approach it. And I say carefully because there's been a lot of problems in some of the metagenomic systems up to now. We'll talk a little bit about the bigger picture, and that's the Morgan, with Metafalan, and Schuyum, and Sam. And Frederic, who's in my lab and loves scales for some reason. We'll talk to you a little bit more about Ray Meta and Pacros. I think the two of them share the process of explaining all of these common tools of the trade so you'll be able to analyze the microbiome more readily. One interesting process is to look at the biomarkers. How can we use it to predict or do interesting stuff? Fiona Breitman is going to come and tell you about this. There's supposedly two big enterotypes for humans. They've got microbiomes. So there's the bacteria assay and pre-botella. And these papers are being revisited in some ways. At one point in time it was even three, if I remember well. So I think most of us now realize it's some sort of continuum, but they can be useful trade-offs to see how it happens. And I'll talk to you about this as we go along. We'll talk about metatranscriptomics. So basically John Parkinson will do functional interrogation of those microbiomes, not just who's there, but what are they doing? I think that will be a nice lecture for you. I'm very happy here in Toronto. And Maxime will talk to you how to compare microbiome. If you have lots of microbiomes, how can you just visualize how to do this and that will be done with Ray-Soveya. We'll talk also about host drugs and the microbiome interaction. So we have some host genetics influences the microbiome that you get. There's some obvious host genetics. If you have cystic fibrosis it will definitely influence your microbiome, but there might be even more subtle ones. And there's a paper recently, I'll get it out to the TAs, that showed that the environment now is more important than the host to control your microbiome. So we'll see. I think it's always a given type. Also, a lot of the drugs you take can influence your microbiome. And it's okay, most of you guys don't take drugs, but it went well, hopefully. And then some of you basically later on who are presently elderly person takes between eight and 10 drugs a day. So we don't know. We know about hepatic toxicity, renal toxicity, but I think there's also some effects now that the drug companies are looking for microbiome toxicity for some of these drugs. And also, one of the problems is the drugs can be processed by your microbiome or influence the microbiome. And the microbiome can actually, this what happens for dioxin, it metabolizes drugs differently and creates some problems for you. And it's right here. So it's kind of nice. Vincenzo's here. We have this, this is kind of a new era in saying that there may be a lot of different control of the microbiome by the endocannabinoid systems. And I think our guest speaker is a Canada excellence researcher in microbiome and talked to us Tuesday or Wednesday. Wednesday. And essentially that will be, that's open to everybody in the whole Tuesday. Wednesday. So it's Tuesday, so we'll, that's open to some of the, to the whole community. We'll see for that. Okay, so I'm in a faculty of medicine, so I see this, and especially I'm in infectious disease, so you can see how I see the world right now is that we have us and our microbiomes, the drugs and the packaging, and there's a cycle now that we just used to do this and now I think we have to include the microbiome into the process because it seems to be a very important regulator of our health and also essential for, you know, staying healthy. So, microorganisms, they're our friend mostly and I think our gut feeling right now is that we should work together. They can help us in some ways. We can recreate states of microbiome that promote health and also there's a state of microbiome that's just terrible and leads you to diseases. So I'll just stop there because I just wanted to thank all the people from our group of machine learners that do some of the analysis and you'll see a lot of them. Frédéric and Alex here and Pierre and Maxim are here as TAs to help you along with some of these questions. I'll stop here because I just want to answer questions and see what are your interrogations about this field. It's a very new field. There's a lot of new questions and a lot of room for young scientists to emerge and start thinking about this type of research. So, thank you. So, any questions? Questions? How do you differentiate the effect of the phage versus the microbe when you transfer it to the animals, for instance? Is it the microbe or the phage that has an effect on it? Okay. It's not the phage. The phage is actually... I don't know in terms of... if it's a lithic phage or is there any difference for you or all the phage in general? In the environment, the biggest control of microbes are phages, bacteria phages. Many times it's an equilibrium. In a human, I don't think it's any different. So, you can stress, reactivate phages and phage can kill certain microbiomes, certain microbes that comprise the microbiome. So, I'm not sure if I answered your question properly, but you can't... Well, we like phages. We sequence a lot of those, too. And that's in the environment. They are the biggest control of the microbiome, the microbiome population. Sorry about that comment. It's the balsalt metabolism that controls the germination. It's the restoration of that metabolism. That's also tough. And also, it's a niche. You know, when you kill some things, another one moves in and that's how it's... a little bit like jelly. Yeah. I'm wondering if we'll cover at some point things along the lines of data quality, study quality. You've kind of alluded to... there's a lot of crappy data out there and it's important, especially if you're coming into the field to be able to evaluate, is this something that is worth following up on or should the study be completely repeated or things along those lines? Yeah. Well, I don't like to trust a bunch of colleagues, but... It's not... Data cannot be totally trusted. It's good to replicate. That's how we basically make sure that happens. There's a lot of sequence that's not right and, yeah, you should always be very careful about the data use, especially it becomes very problematic in... when we do big data analytics. We do some mass spec stuff. The spectral libraries are very terrible. So that's a big problem. Yeah, I think... Rob, you had a... You wanted to answer that or you had a question? Yeah, we will. I mean... It's not just this field, it's every field, and it's not bad intent. Sometimes it's bad science and sometimes it's just unaware of. But, yeah, you should control the sequences. But just issues, even if I want to do an experiment about what's the proper study design? What's the proper number of... Oh, this we'll talk about. In microbiology, I didn't realize I should be careful to put this the same amount of women and men into a microbiome research. Don't eat the same, don't have the same hormones. So this, now I'm more aware of it and by reading and by... and we have somebody who's going to talk to you about this because it's an important factor in designing studies. A lot of studies are, you know, white males. The number of women when you have to recruit children in our study... compared to all states in the development? As you see, the microbiome changes with age. So there's puberty, but there's also for women pre- and post-menopausal. So all of this you have to take into account. Adjustable? Well, yeah, so that means the study numbers have to be bigger. It's just that when you start to do a microbiome research and you want to go to a level where you want to do full shotgun sequencing, you need 15 to 20 billion base pairs. So every time, so you can do a certain number and it's very costly. I mean, every time you press the button on an Illumina machine, it's $25,000 and you can do maybe maybe 20, 25 microbiome. So you need big numbers but they're expensive to reach. So that's some of the limitations but there are tricks to do this puberty as well that might be a little bit cheaper and one of them is go look in the database of some, if there's something there that's okay as well, just to give you an idea. Thank you for that talk. So I was just interested about the cut microbiome. So yeah, I'm so glad to see that there are a lot of things right now, the data information about it. About the fish. Yeah. So in humans, is there any way to transfer the cut microbiome too? Yeah, we do it only for medical reasons and only, this is being done for people that have seeds of silk that's resistant to treatment now and then they do a transplant, a fecal transplant and essentially that works pretty well. It's just that there's some issues at one point in time that I was done that if you don't, some people do it at home, they're so desperate but sometimes if you transfer a microbiome for somebody who was obese to somebody who was thin, then you may have changed that thin person into an obese person. So this you can transfer some lab traits as well so that's why people are very careful in doing this and it's also you're not doing you're not giving a single agent, you're giving a big thing and that gets the authority kind of nervous there's also ethical concerns and legal concerns in doing some of that stuff. Is there someone like doing like a capsule stuff? Yeah, it's a capsule, don't worry. Okay, I'll take a few more questions and I'm here all week so you can ask me a lot of questions. So it's just a follow up on that so what's the when was the first transplant? How long is the pull-up now? It must have been a long time since the first transplant. No, it's been a while. I can't talk specifically about I can't remember the last time but we've done a lot of I can't remember the last time but we've done at our hospital something like 20 of to 20 now and sometimes it works the first time and sometimes we give another pill it's not a long treatment and the person it modulates really quickly and it chants to me the person The follow-ups are not that long but the reason they might not die from this but the average age of the people who get this so they die from something else sometimes Okay, two more questions So my issue is data collaborative at the national level because I found that like creating a research now we are doing a lot of micro miles that our data collaborative approaches really little and I don't see very obvious people are very segregated working but we never compare our data and we still do our data very well and I think that is happening in the U.S. as well but they are very hard working in terms of data collaborative at the national level but how about our Canadian research where are we now and how are we doing? Well I was in the U.S. for like 15 years so people have a realization that you can pay it by the public so the data is public and there are also rules and regulations when you receive grants now you can deposit the data and now CIHR adds the same rules and most of the funding agency want you to deposit the data the patients group or foundations they are like really crazy about you so it's happening it's a change of mentality and it's great that you think like that so I'm sure you're going to deposit your data and your colleagues will too Okay, last question I have a follow-up to one of the questions on the data quality so I was wondering whether bootstrapping because the data is what we have and that's going to be limited by the ability of the machine so it introduces biases and there are other steps beforehand so whether bootstrapping would be a good approach to use on building analysis together for vast results Okay bootstrapping always scares people if you do too much we have techniques to know if you're overfitting of the data I think we'll talk about that it's a complex issue but yeah it's a consideration I mean I can't if the data is not really good it doesn't work and you can't salvage it if you're lucky enough we try to do a lot of high throughput data so we can generate lots of data so that's statistical power but if you don't it's just inferences that you can get but we'll have a section in the machine learning to see that and also we can also compare we have comparisons of microbiome with others at large scale and you can see if there's some outliers out there and tease them out that's another possibility Alright, we'll stop here