University Place

Gut Microbes and Circadian Rhythms

– Welcome everyone to Wednesday Nite @ the Lab. I’m Tom Zinnen. I work at the University of Wisconsin-Madison Biotechnology Center. I also work for the Division of Extension Wisconsin 4H. And on behalf of those folks and our other co-organizers, PBS Wisconsin, the Wisconsin Alumni Association, and the UW-Madison Science Alliance, thanks again for coming to Wednesday Nite @ the Lab. We do this every Wednesday night, 50 times a year. Tonight, it’s my pleasure to introduce to you Vanessa Leone. She’s a recently hired professor in the Department of Animal and Dairy Science here at UW-Madison. She was born in Menomonee Falls, Wisconsin, and went to Hartford Union High School. Then she came here to UW-Madison to study animal science as an undergrad and stayed in animal science to get her PhD. Then she went to the University of Chicago to the medical school there for her postdoc. She returned to UW-Madison in 2020 for her faculty position. Tonight, she’s gonna speak with us about gut microbes and circadian rhythms. Would you please join me in welcoming Vanessa Leone to Wednesday Nite @ the Lab?

– Well, thanks Tom for that wonderful introduction, and I’m so happy to be here today to talk to you about how we think the trillions of microorganisms that reside in and on our bodies influence our day versus night patterns and how we think this impacts our own metabolic health. So to give you a little background of myself, I’m Vanessa Leone and my laboratory is a newer laboratory at the University of Wisconsin-Madison. And we reside in the new Meat Science and Animal Biologics Discovery building. Now this building is tremendous and I hope that you all get the chance to come visit it as it really is a researcher’s playground. Now in my lab, I actually focus on the gut microbiome and how it influences metabolic health. And we like to think about lean versus obese gut microbiota qualities. So we know from several decades of research now that the type of diet that we take in can have a dramatic influence on the types of microbes that reside in our guts.

And we know that when we take in a healthy diet, we have what we call a eubiosis or a healthy community membership that does certain things and has a unique and high diversity. But if we take in a high fat diet, we can develop what we call a dysbiosis or a loss of diversity, and we change what that microbiota community can do. So we see that we have a decrease in beneficial molecules like short chain fatty acids, and perhaps a gain of function in other molecules that are made by the microbes, such as trimethylamine, which can influence both local and distal organs and contribute to things like cardiovascular disease, type 2 diabetes, and other disorders. Now today, what I’m going to be telling you about is I wanna give you some background and tell you a little bit about the role of diet and microbes in metabolic function. I wanna present to you some initial findings that my lab made, connecting circadian rhythmicity between hosts and microbes, and really give you an overview of how did we get here. Then I’ll lead into some advanced findings and show you how we think dietary intake can influence host and microbe oscillations or day versus night patterns in the small intestine. And we use a variety of approaches, including some in vitro studies or in a test tube or cell culture dish, as well as some in vivo studies using live animals such as mice to study and identify how this mechanistically is occurring. And then I’d like to provide you with some key takeaways for how you might be able to think about this in your day-to-day life. So we know that the prevalence of new age disorders has really increased dramatically over the past half century. So here I’m showing you maps only of the United States and you can see from 1985 to 2010, that there’s been this progressive march in both obesity and diseases that seem to correlate and go hand in hand such as type 2 diabetes.

These maps show that across the United States, nowadays greater than 26% of individuals are reporting obesity. But I always say that there’s a problem when they color these maps because that means things might be getting just a little bit worse. So as of 2018, in some states across the U. S. , there’s greater than 35% obesity reported. And this has become even worse in the last two years in that now several states actually have greater than 40% obesity reported. Now this is a major problem because we have no real interventions aside from lifestyle changes and for the morbidly obese, we can certainly do bariatric surgery, but that’s a very costly and invasive approach. So finding novel means to improve this is really important. Now we know that the development of obesity and metabolic diseases is multifactorial and complex, and certainly there’s a genetic component at play here. But there’s a number of environmental factors that can contribute and interact with our genes as well as what I hopefully will show you are microbial genes to change the situation and can lead to the onset of obesity and other metabolic diseases.

And three of the areas that I’ve been most interested in trying to understand is this cross-section between nutrition and the types of diet and diet ingredients that we’re taking in, the types of microbes that are driven by those dietary components, and how this interacts with our circadian system, which can in part drive our sleep-wake cycles. And I’ll tell you more about circadian rhythms as we go through the talk tonight. So what might be contributing to this increasing prevalence of Western disorders? Well, we know for sure that we may have considered ourselves at one point a hunter-gatherer type of society. But we’ve certainly deviated from that, where now we have high calorically dense food at our fingertips at all times of day that contain high saturated fat, high cholesterol, and high simple sugars. And we think that this can dramatically shape the gut microbiota community membership. And I think that this is probably still one of the best demonstrations for how gut microbes can actually impact and be influenced by diet. So here, this graph on one side of your screen showing a pie chart of the types of microbes that live in the GI tract of humans. And there was a group that was actually interested in trying to understand what is going on across cultures. So they examined children from Burkina Faso, Africa, and they compared them to children that reside in the EU or the European Union, specifically Italy. Now they looked at the microbes that reside in the gut of these children using some sequencing-based technologies, which you can see presented here in the pie chart.

And they wondered what really was correlating with these changes that they observed. So for example, you can see that the green in the pie chart is so dramatically different from the children from Burkina Faso, Africa on the top as compared to the green, that’s actually pretty absent in the pie chart that’s shown on the bottom from the children from the EU. And when the researchers actually went back to look at all the factors and lifestyle differences between these two groups of children, it turned out that their diets were so dramatically different. Where you can see that the children specifically in the EU are taking in quite a bit more fat and simple carbohydrates or simple sugars, whereas the children in Burkina Faso, Africa, had lower fat intake and presumably took in more complex carbohydrates, which we always talk about as being good for your health. Now when we think about causation, so I just showed you some association, but when we get to causation, how do we really know that microbes can influence things like the development of metabolic diseases? Well, through the use of some fancy technology called germ-free animals who are raised in complete absence of any microorganisms whatsoever, and you can see that the picture of the bubble in your screen there, we know that when we compare these mice to mice that have gut microbes for their entire life, that they have very different metabolism. So if we feed high-fat diet to animals that consistently have microbes their entire life, they will develop obesity just like you or I would if we were exposed to a poor diet. But if we expose that same diet to germ-free animals who have no microbes, they are typically resistant to the development of obesity, telling us that microbes actually can cause and play a causative role in the development of metabolic diseases. Now more interestingly, if we take this high fat microbiota from our obese animals, or humans in that case, and put them into germ-free animals, we can actually transfer that obesity to our germ-free animals. So this evidence very clearly demonstrates that microbes are causative in driving metabolic diseases. Now there’s lots of mechanisms that have been put forth for how gut microbes are contributing to this change in metabolic diseases, and several of them are listed here.

And while they do seem very complex, we as a group wondered if there were other novel mechanisms that maybe were driving the contribution of gut microbes in the development of diseases like obesity. So in our lab, what we ended up doing was trying to compare the genes that are actually expressed in highly metabolically active tissues like the liver. So when we compared to the genes between our germ-free animals that never had gut microbes as compared to the mice that were always raised with gut microbes, we noted that there were a number of genes as you would expect that were differentially expressed. And so you can see in this graph that those genes that actually fall above that red line are considered differentially expressed. Now something that came through in all of our analyses across tissues was that genes involved in circadian rhythm signaling were always differentially expressed between germ-free and their normal colonized counterparts. So we wondered, what do gut microbes actually have to do with driving circadian rhythms? Now circadian literally means “around a day” in Latin, circa dies. So these are systems and networks that actually govern what our bodies are doing during the day versus the night, when we’re asleep versus when we’re awake, when we should be feeding versus when we should be fasting. And all of these, almost all cells in our bodies have these genes that drive circadian rhythms in our bodies. And these rhythms occur over a 24-hour period that typically falls in line with the light-dark cycle that we are living in. And these systems are so important for telling our bodies when we should be be metabolizing, when we should be resting.

They’re involved in protecting us against cancer. They influence just about every system in our bodies. And we know that under particular instances, when these gene networks which are demonstrated here in the figure are disrupted by a number of different factors, in animals and mice specifically, we can actually genetically manipulate them to test how these genes interact with the circadian system or for people who experience shift work or sleep apnea or jet lag. These things can also impact our circadian rhythms. And even they’ve shown in mice that taking in a high-fat diet alone is enough to disrupt circadian networks in the body and contribute to further disruption of metabolism. Now in our lab, we really wondered then, how do microbes fit into this network? And in our lab, we take a number of different approaches. We can examine live animals and use in vivo model systems to sort of test and tease apart these host microbe interactions. We could also use cell culture models where we can actually look in a dish to see how these things interact. And our whole purpose of doing this is so that we can actually make findings that translate to you and I as humans or even to our companion animals who also have disturbances like obesity. So the bottom line of our initial work showed that gut microbes that reside in our intestine are actually there to help us sense dietary cues that translate into outputs to maintain circadian networks throughout the body.

So as pictured here, microbial oscillations or what the microbes are doing during the day versus the night are actually influenced by when, how much, and what we’re taking in. Now these get translated into certain molecules or chemicals that the microbes can make that are what we call a metabolome of that gut microbiota. Now these various metabolites can be then absorbed by the body and they can influence even distal sites such as the brain or the liver. And what we think happens when we’re taking in a proper diet is that this helps us to maintain rhythms of our circadian networks and ultimately promote wellness and healthy metabolism. But this can become disrupted, as I said, by taking in a simple, high-fat diet. And so when that occurs, we lose these day versus night patterns in the gut microbiota, the metabolome that they’re making becomes disrupted, and now our bodies’ tissues are seeing these metabolites at very different times of day. And this is not necessarily a good thing because we think that this can contribute to the development of obesity. Now there’s lots of ways to disrupt this network because it’s not just a one, a unidirectional interaction. So we know that if we disrupt our own circadian networks, so either in the brain or in other peripheral tissues like the liver, that this can also lead to negative consequences for the gut microbiota day versus night patterns as well. And this can happen through multiple different modalities, whether it be through genetic manipulation of the system, like I mentioned, we can do in mice or through jet lag, which we think that once these systems become disrupted, that can also contribute to the development of obesity.

Now there are some situations where we know we can actually restore these rhythms, and other groups have shown that if we do timed feeding for instance. So if we consolidate feeding of a poor diet, in this case in mice, to the dark cycle when the mice are most active, where you and I would be most active during the day, that we can actually restore some of these microbial oscillations in the gut. And this restores the signals that are seen by the brain and other peripheral tissues by the liver and this can promote wellness. Now this has been translated to humans as well. So early versus late eating in healthy humans can impact the diurnal patterns, not necessarily in the gut microbes, but as a proxy for the gut microbes, the salivary microbiota. So the organisms that reside in our mouths. So in this study, they actually looked at 10 healthy women and they examined early versus late eating. And in this case, they had a crossover design where each individual experienced early eating or late eating or vice versa during the trial. Now interestingly, what they ended up showing is that they examined the salivary microbiota at four time points over a 24-hour period. And they noted that there were unique day versus night patterns or diurnal patterns in microbes observed based off of time of eating.

And these patterns were inverted depending upon whether or not the people were having early versus late eating. And eating late actually increased taxa that were more associated with inflammation. So this is directly applicable to situations that you and I find ourselves in. Now in another study performed by the same group, they actually looked at the time of chocolate intake influence. And I always say, I wish I could have been part of this study. So they had a group and again, this was in healthy women who were taking no chocolate or chocolate in the morning or chocolate in the evening. And this was quite a substantial amount of chocolate. It was actually almost a complete Hershey bar of chocolate. And what they found was that in fact depending upon the time of day that people were eating the chocolate, that the microbiota were doing some really unique things. So microbes can create or make molecules called short-chain fatty acids, which typically can be seen as healthy for you or I.

And what they noted was that depending upon time of day of chocolate intake, there were differences in these patterns of molecule production by the microbes. Where when we had early chocolate intake, there was enhanced production of these possibly beneficial molecules relative to late chocolate intake. And what they also observed was that when we look at this type of graph, it’s called a principal coordinate plot, and what it allows us to do is to categorize and see how closely related one group is to another. And so when they looked at the microbiota signatures from these people, evening chocolate versus the morning chocolate had a very unique signature of gut microbiota relative to each other as well as to those who were not taking in any chocolate. Now this group didn’t observe any complete weight loss by just giving chocolate in the morning versus in the evening. However, they did show that there were changes in the microbiota and what they could do. And not only that, there were changes that were correlating with different types of microbes that were present or absent in the microbiota. So when we looked at who could actually make these types of molecules, we can see that the microbes that were making these molecules are differentially present or abundant, whether or not the people were having early chocolate versus late chocolate. So even though there were no overt changes in weight, morning chocolate seemed to enhance lipid oxidation and decreased fasting blood glucose, which we all know is good, like in the context of diabetes. Whereas evening chocolate actually increased skin heat dissipation and promoted regular sleep episodes.

So we know that these types of eating behaviors are influencing our gut microbes and they’re also changing our metabolism. Now when we were doing this research, we wondered, is taking food in by mouth an important factor when we consider the day versus night patterns of the gut microbiota? And so one way to kind of get around feeding by mouth is to use something called parenteral feeding, where nutrients are infused into the periphery at a constant rate. And there’s patients who have bowel issues where they actually can’t take in food by mouth, where parenteral nutrition can be a life-sustaining exposure. But we used this experimentally, not in humans but in mice, where we parenterally fed mice or we had their enterally-fed counterparts who were able to actually take in food by mouth. And what we thought we would see was that those animals that were parenterally fed would completely lose the rhythms in their microbes because we thought that diet and diet components would be the main driver of this phenomena. But that is actually not what we saw, excitingly enough. What we saw is that whether animals were enterally fed or parenterally fed, we still saw day versus night patterns in the types of microbes that are present. So these graphs here on the bottom show the relative abundances of specific microbes that are in the gut at any given time over a light, with the open bar, or a dark cycle, by the closed bar. So this is over a 24-hour period. And so you can appreciate that both of them had these up versus down patterns, which we think is really interesting because these microbes were not seeing any food by mouth.

And so this told us that there were other factors in the intestine, even absent food intake, that could help to contribute to driving these rhythms in our animals. So we wondered what could be made by the intestine that actually influences these rhythms, absent food intake? And a very astute colleague of ours who’s actually also an investigator at UW-Madison was really interested in how parenteral feeding could impact the production of what we call antimicrobial peptides in the gut. And so antimicrobial peptides do exactly almost what their name seems to say. They can target specific microbes in the gut and act to either prevent them from growing or in fact kill them as well. And so you can see that in our parenterally-fed animals here, they completely lost rhythms of one key antimicrobial peptide called regenerating islet-derived protein 3 gamma. And this was, the day versus night pattern was very nicely evident in their enterally-fed counterparts. Now Reg3 gamma, as we like to call it in the lab, is known to target gram-positive organisms, which would be something like Listeria, which is a food-borne pathogen. So it’s really important for maintaining the ecological health of the gut microbial community. Around this time that we made this finding, there was also a group who had shown that antibiotic depletion of the gut microbes could also eliminate this day versus night pattern in this host-derived antimicrobial peptide. Now we wondered, okay, there’s two different types of situations that are changing the gut microbes.

Either changing who is there and when or reducing their numbers in the case of antibiotic depletion. So we wondered, what happens under high-fat diet feeding? So this really rose the question for us, what are the dominant versus secondary drivers for microbial oscillations? So is it simply that the day versus night patterns or light versus dark exposures that we are experiencing are telling our brains something about what should be happening in the environment around us, which tunes into our intestine? Or is it really the types of food that we’re eating and when we’re taking this food in? Or is it a direct signal that’s occurring from time of day to what our intestines should be doing and what the microbes should also be doing at those times? Or is it something more realistic, where it’s more complex and all of these systems are interacting? And so this is really what we set out to find. So using our germ-free animals that I told you about earlier, we leveraged this as far as their physiology is concerned, and we compared them to their colonized mice counterparts that always have gut microbes present. And so we fed them a normal, healthy diet that’s high in fiber and low in fat, or what we call regular chow or RC, and we compared that to high fat-fed animals who take in a high fat, simple sugar chow diet or HF. And so then we simply wanted to see what happens to the circadian genes in this situation in the intestine and what happens to the antimicrobial peptide genes in this situation? So what we were really surprised to see is that regardless of the presence or absence of microbes or the types of diet that the animals were taking in, the circadian genes were almost identically expressed within the intestine, which was surprising to us. Kind of telling us that maybe the circadian rhythm or the circadian gene network isn’t necessarily in charge of driving rhythms of the gut microbes. But when we looked at the antimicrobial peptides, there was actually quite a different situation, specifically in our antimicrobial peptide of interest, Reg3 gamma. So here you can see that Reg3 gamma over a light-dark cycle, again, 24-hour period, is exhibiting this nice, beautiful diurnal pattern specifically in our healthy, regular chow-fed animals. Now that rhythm is absent in our high-fat fed animals as well as in microbes or in animals that have no microbes whatsoever. So this is telling us that it’s the type of diet that the animals are taking in as well as the presence of specific and key microbes.

And this was only true for Reg3 gamma because when we looked at other antimicrobial peptides, they’re just equally as important in the intestine. They were not differentially influenced by presence of microbes or the type of diet that was present. So we really began then to hone in on Reg3 gamma and wanted to understand this dynamic better. So we know that diet-induced gut microbes actually impact diurnal Reg3, but not the circadian gene expression patterns. So now that we noted that microbes and the type of diet-induced microbes that were present were important for this interaction, we wanted to know and learn more about the microbes themselves. So from our colonized animals, we were able to collect microbiota samples from the distal small intestine, which is a really important region of our gut for absorption of nutrients and other things that are important for our physiology and metabolism. And what we noted was as expected, high-fat diet was really driving a unique signature of microbes that reside in the intestine as compared to our regularly chow-fed animals. And what we noted was that this change was happening at a very high level of the gut microbiota composition. So this is what we call the phylum level. And so you can see that high-fat feeding has caused an expansion or an increase in Firmicutes and a reduction in Bacteroidetes, and this was anticipated.

But what we really wanted to understand was what happens as far as the day versus night patterns or diurnal patterns in this distal ileal gut bacteria. And so when we actually broke down those microbes that were oscillating versus non-oscillating, we found that under high-fat feeding conditions, here represented in the pie charts, that high fat-fed microbiota had far less day versus night patterns as compared to the regularly chow-fed animals. But our question was, are there specific community members or taxa that correlate with this Reg3 gamma expression that we were observing? And so we looked at that and we performed some very sophisticated correlation analyses, and we determined that indeed, Reg3 gamma expression was correlating with specific community members. So here we have Reg3 gamma expression on our X axis or the bottom axis, and our different microbes of interest on the Y axis or the axis to the left. And you can see that as Reg3 gamma increases in expression, that there are specific microbes that are also increasing at the same time, causing this to be a positive correlation. Now on the flip side, when we have high-fat feeding, we have lower Reg3 gamma expression, as anticipated. But we see that other community members from that gut microbiota community are emerging or increasing, and this is causing this to be a negative correlation. So we have some that seem to maybe be drivers of Reg3 gamma expression, and perhaps we have some that could be negative or inhibitors of Reg3 gamma expression. And this graph just depicts what the actual relative abundance looks like for these members of the community in the gut at any given time over a 24-hour period. So again, we can see that under regularly chow-fed feedings in the blue, that we have a nice day versus night pattern that’s absent in our high fat-fed animals.

And on the flip side, we see that there are some microbiota that emerge in the community under high fat-fed feeding that are typically lost or not present in regularly chow-fed animals that are typically metabolically healthy. So we think that Reg3 gamma exhibits clock-independent diurnal expression patterns in the distal ileum that are really driven instead by the presence of diet-induced microbiota. And feeding high-fat diet shifts this distal ileum bacterial community membership and reduces the percent that exhibits diurnal oscillations and relative abundance as compared to their healthy, regular chow-fed counterparts. And high-fat diet does appear to alter oscillations in specific community members, and this diet-dependent community member correlation with diurnal Reg3 gamma expression patterns we think is what’s really happening here under this disrupted feeding condition. But just because these microbiota are correlating, it doesn’t mean that they’re actually driving the situation. So we really had to kind of go back to the drawing board to decide how can we show that these microbes are actually driving this phenomena in the intestine? And so we really wanted to test whether specific community members within the lumen of the gut depicted here could actually interact with our gene expression and drive diurnal patterns of Reg3 gamma, or were there other members of the community that were actually inhibiting this from happening under high-fat feeding conditions. And so in this instance, we actually prepared some distal ileal content from the intestine and we exposed it to what we like to call mini guts in culture. And also with these mini guts, we actually prepared condition media from select microbes that we think are important for this interaction and driven by specific diets to see what they were actually doing directly to these mini guts as far as Reg3 gamma expression is concerned. So we use organoid technology in the lab to actually probe these host microbe interactions in a culture dish. So this goes back to the slide I showed you earlier where we use all kinds of techniques to kind of demonstrate what we think is happening in our bodies in what we call an in vivo condition.

So these organoids are actually derived from stem cells that are harvested from the intestine of an animal or a human as well. And they represent nearly all the cell types and distributions that are found in the gut, and they have a lot of the functional characteristics maintained. So they’ve been a fabulous technology to actually explore what is happening in the gut and when. What we found is that actually, regular chow-fed luminal contents can induce Reg3 gamma in our mini guts as expected. So you can see here that lysate collected from regularly chow-fed animals in the blue is inducing a higher level of expression of Reg3 in the intestine relative to our high fat-fed counterparts. And when we actually looked at the condition media from specific community members, we noted that those that are promoted by regular chow feeding or a healthy diet could actually induce Reg3 gamma expression, whereas those microbes that were promoted by a high-fat diet actually could not induce Reg3 gamma expression and perhaps even inhibited expression from occurring. So this was exciting to us because it was telling us that there was a direct effect of these microbes that are selected by diet on Reg3 gamma expression. Now we wanted to know what is it about these molecules that’s so important, or these microbes that’s so important for driving this expression that we’re observing? And so what we did was take these condition medias that we had prepared from specific microbes induced by diet, either Lacticaseibacillus rhamnosus GG or Peptostreptococcaceae stomatis, which is a big mouthful, so I’ll just call it P. stomatis from here on out. And what we noted was that small molecules from Lactobacillus could actually induce Reg3 gamma expression as anticipated, whereas small molecules from P. stomatis, which is promoted by high-fat diet had no capacity to induce. So this said that there were small molecules made by Lactobacillus that were actually driving this interaction. And we tried to do a couple different things to this condition media from Lactobacillus to see, could we break the system? So what we did was we took these conditioned medias that have small molecules and we actually heat-treated them to break down those molecules that they had made. And indeed when we did that, we saw that there was less capacity for those molecules to induce Reg3 gamma relative to the un-heat-treated counterpart here. So this tells us that these molecules that are being made by Lactobacillus are heat-sensitive and they’re unique to Lactobacillus. So other microbes do not have the capacity to do this. So we know that diet-induced microbial communities differentially influence Reg3 gamma expression in vitro, that there’s individual strains that are in the gut, representative of those selected by diet, that actually correlate with in vivo Reg3 gamma expression that we can actually recapitulate in vitro in our mini guts. And we know that Lacticaseibacillus rhamnosus GG induces Reg3 gamma expression, whereas microbes like Clostridiaceae and Peptostreptococcaceae selected by high-fat diet cannot induce Reg3 gamma expression and may actually inhibit it. And these are small molecules that are made by specific microbes that drive this interaction with Reg3 gamma. But we went a little bit further because we wanted to know, just because we can show this in the mini gut system doesn’t mean that it’s actually happening in the actual body of a mouse or a person.

So we leveraged our germ-free technology once again and we had mice that were fed either a high-fat diet or the regular chow diet and we added a single microbe, Lacticaseibacillus rhamnosus GG or LGG to these germ-free animals, and then we examined the expression of Reg3. And what we were really interested to find was that germ-free mice, as anticipated and as shown before, without any microbe, regardless of diet exposure, had really no expression levels, here shown in the green and the yellow. But when we looked at the monocolonization where we only added Lacticaseibacillus rhamnosus GG, we saw that on regular chow-fed diet, we saw an increase in expression as shown in the blue as compared to our high fat-fed counterparts shown in the red. And there was some evidence that over time, regular chow-fed animals mono associated with LGG had elevated Reg3 gamma expression as well. So this told us that it was the type of diet that was present as well as specific key community members like Reg3, like Lacticaseibacillus rhamnosus GG that are important for driving this phenomena in the intestine over a day versus night cycle. So our model system here is that diet drives what we call small intestinal eubiosis or health of those community members. So this is a good thing, and that these community members exhibit diurnal patterns in probably how much of them are present and what they’re actually doing during the day versus the night. And these interact with Reg3 gamma to drive diurnal rhythms on our side of the street, which helps to maintain and possibly even prevent the expansion of other community members. However, when we have high-fat feeding, we can drive a small intestinal dysbiosis, which means that we lose perhaps key community members. We no longer have them to interact and drive diurnal expression of something like Reg3, and this loss of Reg3 gamma expression allows for the expansion of other community members and ultimately, we think that this could contribute to the development of obesity and metabolic diseases.

Now others in the field have taken this further because we want to know, how can we translate these findings to the human condition. Well, one group, over the pond we’ll say, in Germany was actually looking at a large, regionally similar cohort of people. And it included a mix of people across healthy, obese, type 2 diabetes, represented as T2D with or without cardiovascular disease or CVD, and/or cancer. So very large cohort of individuals. And they had collections of stool or fecal collections from these people over day versus night patterns. And they also had a number of hosts, what we call metadata. So just information about their health, BMI, glucose levels, dietary intake, et cetera. And what they did was they applied some technologies here to look to see what was going on with the microbes in the feces from these individuals. And they had a cohort of healthy people and those with type 2 diabetes. And what they noted was that even from single time points that reassembled rhythms of microbiota community membership, that in healthy individuals, there were day versus night patterns that were evident in these microbiota.

But in the type 2 diabetes individuals, they noted that the patterns in these types of microbes were actually arrhythmic or had lost rhythms, very similar to what we had seen in our mice. So using some unsupervised machine learning techniques, they were actually able to identify an arrhythmic or loss of rhythm signature, risk signature in type 2 diabetes people. Now these 13 predictive taxa or 13 predictive community members, they then tested on other large cohorts to see how well did their predictive model work. And actually, just by applying this machine learning tool and identifying these 13 arrhythmic taxa in type 2 diabetics, they could actually stratify in other populations, healthy versus type 2 diabetics. And then we think that this could actually be used as a predictor to predict when somebody goes from healthy to pre-diabetic to diabetic. So this could become a very powerful clinical tool to understand the rhythms of the microbes and how they’re behaving under certain health conditions. So key takeaways from these findings are that time of feeding, coupled with diet composition, are primary drivers of microbial community membership and broader oscillatory capacity of that whole gut microbiota community. And that there’s key host, what we call innate immune components like Reg3 gamma and antimicrobial peptide that oscillates independently from the core circadian clock genes as we anticipated. Now diurnal Reg3 gamma expression does appear to depend on specific and select community members driven by diet, but there’s no doubt that there’s a bidirectional communication between Reg3 and gut microbes, which serves as maybe secondary signals to maintain local intestinal oscillations that we think can impact metabolic health. Now the future of chronobiome work.

The gut microbiome is a key feature of maintaining circadian networks and metabolism. We and others have shown that to be true. And we think that perhaps timed delivery of prebiotics, which are certain types of dietary fibers for example, or probiotics, microbes themselves, or postbiotics, small molecules like I described earlier, that could actually impact their influence on promoting restoration of the gut microbiome and host health. So can we use timed delivery to actually reset the clock, if you will, in the intestine? And I think in order to really push the system, we need to deeply phenotype subjects and include and understand their sleep-wake patterns, feeding patterns, work schedules, which will be essential to really understand the diurnal patterns of microbes that are already, as I showed you, being used to predict metabolic diseases. And ultimately, I don’t think this is going to be a one-size-all approach. Our key to understanding this is really understanding everyone’s unique chronotype. So whether you’re an owl versus lark, for example.

Now this work wouldn’t be possible without a number of people in my lab group and others around the world. And so I did wanna highlight some key contributors, including some technicians, Amal Kambal, and a recently graduated pre-doctoral student, Katya Frazier, who contributed to this work. And as I mentioned, Dr. Joseph Pierre, who was here to help us do the parenteral nutrition studies that I described. Now one wonderful thing about doing circadian research is that you get to see some very beautiful sunsets and some very beautiful sunrises, which is what I have depicted here on the slide. And I would be remiss if I didn’t call out our wonderful funding sources that we’ve received, both from the National Institutes of Health and others within the U. S. So with that, I wanted to say thank you for listening to this talk today. I hope you walk away feeling energized and excited about how to understand your chronotype. Because remember, you’re not just affecting your own health, but also the trillions of microorganisms that reside in and on your body and telling them what they should be doing during the day versus the night. So thank you.