Inside Scientific Webinar: Sex, Sugar, Fat, and Heat: Factors That Affect Energy Budgets, Weight Management and Behaviors in Mice

Sarah: Good morning, good afternoon, and good evening everyone and welcome to our webinar entitled “Sex, Sugar, Fat, and Heat: Factors That Affect Energy Budgets, Weight Management and Behaviors in Mice”. This webinar has been sponsored by Sable Systems International. So, a big thank you to them for helping to make this event possible. Joining us today, we’re fortunate to have Dr. Lauren Woody, a postdoctoral fellow at the University of Pennsylvania, and Dr. Matt Morris, an assistant professor at the University of Kansas Medical Center. Their presentations will discuss applications of rodent metabolic phenotyping with a focus on the effects of sex, diet, and energy budgets. I’m Sarah McFarlane from the events team here at Inside Scientific, and I’m very pleased to be your host for today’s event.

Now, before we get started, I would just like to share a few housekeeping notes to help you get the most out of the webinar today. First, this webinar is being recorded and resources will be made available following the event. Next up, if the webinar panels look too big or too small, you can zoom in or out on your internet browser to adjust the viewing area. You can also resize some of these panels or make the media panel full screen. Please send questions, thoughts, and comments to us via the ask a question box next to the media window at any time. You can also take a look at the resources panel where you’ll find a few links and suggested readings associated with today’s event. We will also be running a number of audience polls during the webinar and a survey at the end, so please chime in and share your perspectives with us. And finally, if you do happen to experience any technical issues during the event, the easy fix tends to be a simple refresh of the webinar auditorium by refreshing your browser. This should successfully reestablish your streaming connection so you can see us clearly, or sorry, hear us clearly. However, if this doesn’t work and you continue to have issues, just use the ask a question box to communicate your issue with our team and we’ll help to get you back up and running.

And with that, I am pleased to welcome our first presenter, Dr. Lauren Woody. Lauren, the floor is yours whenever you’re ready. Thanks so much for joining us today.

Dr. Woody: All right, so I’m Lauren Woody. I’m going to discuss some of the work that I did at Auburn University looking at macronutrient timing of aspects of the Western diet and how that impacts physiology and metabolism in a male mouse model. So, my talk will follow this outline. First, I’ll discuss a little background on the Western diet, the circadian rhythms, and time-restricted feeding. Then I will go through the two papers where we time-restricted different aspects of the Western diet. And then I will quickly summarize and conclude.

So, first let me quickly talk about what is the Western diet and how does it disrupt circadian rhythms. So, whether we know it or not, circadian rhythms control just about everything that we do in a day. The word circadian comes from the Latin words circa and dies meaning around or about a day. And we all know that a rhythm is a predictable pattern that happens over and over. Circadian rhythms are patterns that happen about every 24 hours. I have examples of some biological circadian rhythms here from humans. Our blood pressure will peak in the morning to help get us up and ready for the day. Body temperature will peak in the afternoon, while melatonin stays low while the sun is out and peaks in the middle of the night to set the end of the circadian day.

These rhythms are controlled by a set of molecular core clock genes that function in a transcription translation feedback loop. This loop has a positive and a negative arm. The positive arm is made up of CLOCK/NPAS2 and BMAL1, which form a complex to upregulate the transcription of negative arm components, such as period and cryptochrome, as well as other clock-controlled genes. Period and cryptochrome will form a complex in the cytoplasm, which returns to the nucleus to inhibit the effects of CLOCK/NPAS2 and BMAL. Reverbs, on the other hand, will inhibit the transcription of BMAL, all of which will stop the activity of the positive arm and ultimately transcription of the negative arm. But once this transcription is halted, the positive arm will be released, starting this process all over again, which gives circadian rhythms their wave-like pattern of high points and low points.

The main anatomical site for circadian rhythm maintenance is the suprachiasmatic nucleus, located where the red circle is here in the hypothalamus of the brain. The SCN is considered the master clock, and it is entrained or set to the presence of daylight, while melatonin from the pineal gland acts to signal the end of the circadian day and create, once again, the wave-like pattern of activities that I showed in the first slide. So, although the SCN is the master circadian clock, every cell in the body possesses a set of core clock genes. Under healthy feeding circumstances, this allows the SCN to set the rhythm of all tissues to the presence of daylight. However, under unhealthy feeding conditions, such as after eating a Western diet, exemplified here by a high sugar and a high fat component, the peripheral tissues can become desynchronized from the SCN. This circadian desynchrony has been shown to be part of the etiology of diet-induced metabolic disease.

One method to mitigate diet-induced metabolic disease and circadian dysfunction has been time-restricted feeding, or TRF. TRF functions to align the timing of nutrient metabolism to the timing of nutrient consumption. And for humans, this means only eating during the active phase, normally from 9 a.m. to 6 p.m. TRF has been very successful in both rodent and human models with rodent models showing decreased body weight after time-restricted feeding, or TRF has actually prevented body weight gain on a high fat diet. It has also improved metabolic outcomes in humans, such as glucose tolerance and cardio metabolic outcomes in diabetic individuals. But what these studies have really focused on is timing the solid fat component of a Western diet. And as I showed you all on the last slide, the Western diet consists of a liquid high sugar component along with the solid high-fat component. So, our question became to determine the effects of time-restricting specific components of the Western diet and how that impacts the physiology and metabolism of a mouse model of diet-induced obesity. We really wanted to see if separating out the two and timing them separately could have an impact on TRF efficacy.

So, the first study is here when we time restricted the solid fat component of the Western diet. So, for the study, we had two groups of mice, a chow diet that was given tap water, and then the 40% high fat group that was given 4% sugar water to model a Western diet. We further split these two dietary groups up into either an ad libitum feeding schedule or a time restricted feeding schedule. The ad libitum animals had food access throughout the day, while the TRF animals had food access only for nine hours during their active period. So, I will remind you that mice are nocturnal animals, so their active phase is during the dark, which you can see here in this diagram. I’ll also remind you that we were only testing the timing of solid fat in this study. So, the tap water and the sugar water were ad libitum for both groups, no matter whether they were on an ad libitum feeding schedule or a time-restricted feeding schedule. We really wanted to see how ad libitum liquid sugar impacted the efficacy of solid fat time-restricted feeding.

Okay, so before I get into the data, I want to give a quick plug to my previous mentor. We performed all of our metabolic phenotyping studies using Sable Systems Promethion cages in the Auburn University metabolic phenotyping lab. You can see our setup in the photo on the left, and then my previous advisor is also the director of the AUMPL, and he is pictured here on the right, Mike Green.

Okay, so the first bit of data that we observed was percent body weight change, and so we had a run-in of ad libitum feeding for all of the groups for six weeks, and then began TRF for both the chow and western diet groups after six weeks, which you can see by the red arrow. The chow animals, or the chow groups are in the circles, the western diet groups are in triangles, and then both TRF groups are the open shapes, where ad-lib are the closed shapes. So, what we can see in percent body weight change is that the western diet animals gain significantly more weight than the chow-fed animals. and that this weight gain was not mitigated by time restricting the solid fat component of the Western diet. What we did observe though, looking over at the 12-week glucose tolerance test, is that time restricting the Western diet improved glucose tolerance. The Western diet additive animals, the closed triangles had significantly elevated blood glucose after administration of a glucose load, pretty much for the entire test, all the way up until 120 minutes. At sacrifice, we measured blood glucose, serum insulin, and used these numbers to calculate HOMA-IR. And what we observed here was that time-restricted feeding of the Western diet improved final serum insulin, so it reduced hyperinsulinemia. And then through that, resulted in an improved HOMA-IR score, So, the Western Diet TRF animals in the speckled bar there had a reduced score of insulin resistance when compared to the Western Diet ad libitum animals. So, time restricting the solid fat component of the Western Diet didn’t have a big effect on body weight, but it did improve glucose metabolism measures.

So, then we looked at some of our metabolic phenotyping data. I have energy expenditure here. I’ll remind you all that mice are nocturnal, meaning they have lower energy expenditure during the day and higher energy expenditure at night. We see this phenotype in both of our chow-fed groups, which are the open and closed circles. They have low EE during the day, which switches to high EE at night. This pattern was a lot flatter in our western ad libitum animals, the closed triangles. They had significantly elevated energy expenditure during the daytime compared to the chow-fed groups. This phenotype was slightly mitigated by time-restricting the Western diet, as you can see by the open triangles, which have an intermediate phenotype of energy expenditure during the daytime.

Now we looked at respiratory exchange ratio, which is a measure of what macronutrient the animals are consuming at a certain time. So, if anyone is unfamiliar, a score of 1 indicates carbohydrate utilization and a score of 0.7 indicates lipid utilization. So, we would expect nocturnal mice to be using lipids during the daytime and then switch to carbohydrate usage at night. Once again, we see this phenotype quite nicely in our chow fed groups, which are the open and closed circles. They switch from lipid utilization and then around DT12 begin utilizing carbohydrates. The Western diet adlib animals, however, had a very flat rhythm of RER. You can see the closed triangles are pretty much using lipids throughout the entire day, indicating that Western diet feeding impairs metabolic flexibility. But similar to energy expenditure, we saw that time restricting the Western diet improved the metabolic flexibility of animals. The open triangles have an intermediate phenotype indicating that TRF was effective in improving metabolic flexibility.

So, overall, we were able to conclude that time-restricted feeding of the solid fat component of the Western diet, but with ad libitum liquid sugar, does recover metabolic flexibility and decrease insulin resistance in our model. However, leaving the liquid sugar ad lib actually reduced the effect of time-restricted feeding on weight loss. We did not see a significant weight loss in our Western diet TRF animals. Now, I just hit the highlights of this paper, but another thing we looked at was improvements in liver health. And we also noticed that leaving liquid sugar ad libs decreased the efficacy of TRF in improving overall liver health, which is something that other papers have seen. Alright, so now our big question became, what is the effect of timing liquid sugar? It was obviously able to decrease the efficacy of solid TRF, so how would timing the liquid sugar on its own affect physiology and metabolism in our mice?

So, this brings me to the second paper, where we time-restricted liquid sugar access. For this paper, we had animals just on the chow diet; we just wanted to look at the effects of sugar water. And we used a 12% fructose glucose solution to really model high fructose corn syrup that is so commonly consumed in sodas and sweetened beverages in the Western world. So, we had four groups of animals. The control group was given tap water throughout the day. The ad libitum FG or ALFG group was given the sugar water throughout at the entire day. Whereas the early and late FG groups were only given sugar water during distinct six-hour periods during their active phase. So, the early fructose glucose group was given sugar water during the first six hours of activity, while the late fructose glucose group was only given sugar water during the last six hours of activity. And as you can see here, these groups were given tap water when they weren’t given sugar water.

Okay, so when we looked at percent body weight change, we did not observe an effect of the early or late fructose glucose availability on body weight. However, we did notice that the ad libitum fructose glucose group had significantly elevated percent body weight change starting at one week after treatment and then persisting out until the end of the study at nine weeks. At sacrifice, we observed that this body weight change was mainly due to increases in visceral and sub-Q fat pads, so we can see that the ALFG group has elevated visceral fat weight compared to control, whereas the ALFG had increased subcutaneous fat compared to control as well as EFG and LFG. So, these animals are gaining more weight. One would assume that they are consuming more kilocalories, but interestingly, this ended up being a little more nuanced than that. When we looked at total food kilocalories consumed per cycle, we broke it out into the day and night, we did not observe a significant difference among the groups for food kilocalorie consumption. When we looked at water kilocalorie consumption, however, of course we saw that the animals that had calories in their water were consuming more during the day and night. So, ALFG was consuming more liquid calories during the day, and then all of these sugar water groups were consuming more liquid calories during the night. But, when we totaled this food and water together to look at total kilocalorie consumption, we once again did not observe a significant difference among the groups for total kilocalories consumed. So, this is interesting. The ALFG animals are weighing more and have elevated fat pad mass, but they don’t appear to be consuming more kilocalories when it’s averaged over a day or a night.

So, what we did to look closer into this was use the really great resolution that Sable Systems cages will give you on a number of measures, but particularly food, water, and kilocalorie intake. So, what we did was break out these endpoints into four six-hour bins. So, the first two bins you’ll see over on the far left in yellow and orange are the inactive phase, so during the daytime, and then the second two bins are the active phase in the light blue and dark blue. So, when we looked at food kilocalorie consumption and looked at the percentage of total kilocalories that the animals ate within each one of these six-hour bins, we did not observe a significant difference among the four groups. So, we analyzed this with a chi-squared test, setting the control group as expected, and then looking to see if any of the treatment groups consumed a different amount of the proportion of calories during any one of the six-hour bins.

When we looked at water, of course, we saw that the EFG and LFG groups consumed more of their percentage of water during the time when they had sugar in it, sugar tastes good. So, they really weren’t interested in the regular water. They seem to wait until the sugar water was available to consume the majority of their water. But finally, when we looked at total kilocalories, here’s where we think we see a potential explanation for the increased weight gain in the ALFG group. Here at the ZT 6 to 11 bin, so the late inactive phase, the ALXG animals were consuming a greater percentage of their total calories during that time. So, we believe that this indicates elevated food, elevated calorie consumption during this late inactive period may be a particularly sensitive time for these calories to be converted resulted into fat and increased weight gain. Up until this point, however, we didn’t really see a difference between the EFG and LFG groups, and particularly we didn’t really see an effect of the EFG or LFG when compared to control, which is sort of interesting. We certainly expected sugar water at any time of day to have some type of effect.

We started to see a bit of a difference start to materialize when we looked at liver health. So, here we did an H&E stain looking at fat accumulation in the livers of the three groups. Normalized liver weight wasn’t different, but when we scored the livers for a non-alcoholic fatty liver disease, we did observe that the EFG animals actually had a decreased NAFLD score compared to the ALFG animals. And when looking at the H and E stain here, we can see that there was, there did appear to be increased fat deposition in the ALFG livers.

Then when we looked at a glucose tolerance and an insulin tolerance test, we saw something really interesting in the EFG group. So, the control group are the black circles, the ALFG are the open circles, EFG is the black triangles, and LFG is the open triangles. And what we observed here was that ALFG was not able to clear glucose load as quickly, both at the 15 and 30 minute time point. But interestingly, we saw that the EFG group was actually able to clear glucose load quicker. You can see that especially at the 13-minute time point, their blood glucose was lower than the other three groups. And then really interestingly, we observed that the EFG group actually appeared to be more insulin-tolerant, even than the control group. So, this was quite shocking. We were pretty puzzled by how this group that had sugar water at all could appear to be healthier in terms of insulin tolerance and glucose tolerance than the animals that were just given water.

We started to see a potential reason for this in our metabolic phenotyping data. So, here we have energy expenditure. Once again, the animals have low energy expenditure during the day and high energy expenditure at night. Now, what we observed here was that the EFG group actually had elevated EE during the first six hours of activity when they were given their early fructose glucose. And we saw in the late FG group that they had lower energy expenditure that only elevated until they were given their sugar water. So, this is interesting. It was pretty robust in the LFG group, but what we were really impressed by was the metabolic flexibility in our early FG group. So, the control animals were burning lipids during the day and then switched to carbohydrates during the night. But really incredibly, the EFG group was burning lipids during the day, switched to carbohydrates during the first six hours of activity when they had sugar in their water, but then immediately, once that sugar was taken away and they were given tap water, started burning lipids again. We can see in the last six hours of activity that those closed triangles are really going back down to lipid utilization. We saw a bit of a delay in this phenotype in the late FG, signaling that they have a similar type response to sugar water, but it was quite robust in the EFG group. So, what we think is happening here is that this early fructose glucose is actually playing into the natural rhythmicity of mice and amplifying their natural rhythmicity, and that that is potentially behind the metabolic benefits we observed in the EFG group.

Okay, so I’ll quickly conclude here. Overall, we found that time-restricting liquid sugar access to six-hour windows prevented increased body weight gain and fat pad weight, and that it protects liver health. So, we observed this in both the EFG and LFG groups. But the early active liquid sugar specifically, we believe, is enhancing the natural diurnal rhythm of mice. It induced selective carbohydrate utilization only when liquid sugar was available, and then increased lipid utilization.

Okay, so for an overall summary and conclusion, Western diet-induced obesity can disrupt the chronobiology of organismal metabolism. We observed that in our mice, especially fed the ad libitum Western diet or ALFG. Peripheral metabolic rhythmicity may be rescued by time-restricting macronutrients. We saw this in both time-restricting just the fat or time-restricting just the sugar. And then, overall, diet-induced disturbances in circadian biology certainly play an integral role in the development of metabolic diseases. And overall, this means that chronotherapeutic treatment should be explored, not just for time-restricted feeding, but also the timing of care, pharmaceutical application, and other sorts of diseases. Okay, so with that, I would like to quickly thank everyone at Auburn, all of the funding that I received while I was there. And then certainly everyone in the Green Lab. And as you can probably tell, I am no longer there, but if you want to know what’s currently going on at Auburn or in the AUMPL, please reach out to my old advisor, Mike Green. His email is here. If you have general questions about this presentation or any of the papers that I presented here, feel free to contact me at my Penn email address, which I have provided here. And that is it for me. Thank you all for your attention.

Sarah: Thanks Lauren. Great presentation. Okay, so thanks everyone for participating. I see lots of questions coming in, and I’m going to run a quick audience poll now. So, this poll question is, do you currently use metabolic phenotyping in your research, yes or no? And I’ll wait a couple seconds for everybody to answer there. So, as I said, our next presenter is about to get started. So, Matt, thank you so much for being here with us today, Dr. Matt Morris. So, you can get started whenever you’re ready.

Dr. Morris: Thanks everyone for registering and attending and thank you Inside Scientific and Sable for sponsoring the seminar series. So, my interest is all about energy, from mitochondria up to the whole body and how energy handling and energy homeostasis ultimately can break down and result in short-term diet-induced weight gain and ultimately overweight obesity. And so, if we make it really simple to start with, it’s just the idea of energy balance and that if we consume more calories than we burn, we gain weight and vice versa. And there’s a lot of work done on the intake side, on the regulation and control of the intake side, but not quite as much work on understanding the energy expenditure side and sometimes how they interact.

So, just to break-down energy expenditure and its components for a little more clarity, total energy expenditure can pretty simply be broken down into two major components of resting and non-resting energy expenditure. Resting energy expenditure is primarily comprised of basal metabolic rate, so the energy that we utilize just to maintain basic life function, and then non-shivering adaptive thermogenesis; so cold-induced or diet-induced, which we’ll talk about more later. And then non-resting can be broken out into the thermic effect of food or the cost of the metabolism and disposition of the nutrients we consume, and then activity energy expenditure. And for a second, I want to focus on activity energy expenditure because it’s the only one we have conscious control over, really. And it’s also the one that we can change the most or can change the most due to our behavior.

So, increased physical activity and exercise is really just included in all medical recommendations to prevent or treat and involve in the treatment of not just metabolic diseases, but neurodegenerative and sometimes cancer. And it functions in part, hypothetically, through the increase of energy expenditure. But everything that makes physical activity and exercise good for us as a system, as a being, makes it a complicated experimental tool because of all the different system, all the different pathways and systems and cell types and tissues that are activated during physical activity exercise, a lot of which don’t include any measure of or any change in energy expenditure. So, one of my big questions is then how can we study the independent role of energy expenditure are in various types of metabolism, particularly energy homeostasis.

So, this is a great paper by the Reitman Lab. But this is just demonstrating what many people have shown over and over again, that if we look at panel A, that the inverse increase in energy expenditure as you decrease the ambient temperature a mouse is exposed to. And as I said, many people have shown this. And if we take a look at where mice are typically housed, you’ll see about 50% of the energy expenditure in this mouse then is involved in maintaining its core temperature; it’s cold-induced thermogenesis. So, if we then think about moving this line towards the right, towards a more thermoneutral temperature, then we see that while the other components stay relatively similar, the cold-induced changes reduces a lot. And so, one of the things I was thinking about is because we have this near-linear relationship, then can we use this difference as an energy expenditure between these two temperatures as a way to experimentally isolate energy expenditure as a variable? And so that’s the purpose of the paper that I’m going to talk about. The data comes from the obesity paper. There’s also a considerable amount of data in the initial bio-archive preprint that didn’t make it to the final paper. But the idea is, can we investigate differences in energy expenditure independent of physical activity, and then use that as a system to investigate energy homeostasis, particularly when we challenge the animal with a short-term dietary challenge.

So, just briefly, this is the experimental paradigm for the work. We bring the mice in and individually house them at the temperature they’re going to be studied at from six weeks to nine weeks old on our low-fat diet. About four or five days before we start indirect calorimetry studies, we put the animals in this system to acclimate them. And then we collected data on the low-fat diet for one week. And then we switched all the animals to the high-fat, high-sucrose, described below, for another week to look at how they responded to this diet. And we collected body weight and echo MRI data at three points so that we could look at the change in body composition. So, just some baseline data on the low-fat diet. I’m going to focus mainly on the high-fat, high-sucrose data. I mean, the females weigh 20% less than the males. This is not a shocker. This is what we would expect. Housing temperature and sex impact on weight gain during this time. The 30-C mice did gain significantly more weight. They didn’t, neither group gained a lot during this one-week period on low-fat, but it was higher. And the body composition changes, the fat mass again was higher in the 30-C mice. But all of these variables are highly variable, all of these outcomes are highly variable during this one week of low-fat diet. And it’s not totally surprising considering there was no real challenge there metabolically; there’s a lot of variability even within mice on this.

We look at the indirect calorimetry data for this one week of low-fat diet. I’m really happy to say that I was able to recapitulate what many, many others have recapitulated, and that if we increase the temperature to 30 C, those mice have a 40% less total energy expenditure. And with the sexes here, the females are about 10% less, only the 20-C females actually reach significance. Energy intake is similarly reduced, though I’m not displaying it here graphically. We’re going to talk about how energy intake is coupled to total energy expenditure a little bit later, but the patterns are similar for energy intake on low-fat. And so, energy balance is similar. Now, this is interesting, considering the 30-C mice did actually gain significantly more weight, but their energy balance is equal during the low-fat diet phase. Resting energy expenditure is 50% less than the 30-C mice. Again, this is because they have reduced need for cold-induced thermogenesis to maintain core temperature. And again, no differences by sex in this case. But importantly, the non-resting energy is not different by temperature, with the females being about 10% lower. And finally, activity is not different by temperature, but in this case the females are higher. So, with those last two bits of data, I consider this at least a plausible model for using ambient temperature to produce differences in energy expenditure independent of differences in physical activity.

So, then we move on to look at how this model system adapted or changed or responded to this high-fat, high-sucrose, short-term dietary challenge. If we start with weight gain and body composition, what I have graphed here is the one-week weight gain on the diet, but as its components of fat mass in the darker bars and fat-free mass in the open or lighter bars. So, right off the bat, you’ll notice that the 30-C males gained significantly more weight than the 20-C males. Interestingly, in 20-C temperature, males and females gain the same weight, and across temperature, the females gain the same weight. If we look at fat mass, there is a sex by temp difference here, so 30-C mice gain more fat mass during the one week, and females gain less, and we’ll get to all the things as this is associated with. But what was really interesting was the change in fat-free mass, particularly these 20-C female mice, where they gained a disproportionate amount of fat-free mass compared to not only the females, but the 20-C males. And in fact, if we look at the proportional changes in body composition of the other three groups, they’re actually almost exactly the same. Even though they gain slightly different amounts, the proportion is similar across all these mice, those groups.

We start looking at energy homeostasis components. One, energy balance is highly associated with fat mass change. This is not shocking. There’s a lot of good data to show that 60% to 80% of excess energy balance is gained as fat mass. To keep things simple, we’re just going to talk about the total energy expenditure and energy intake increased in all the groups, but the differences were similar compared to the low-fat diet group. And differences in cage activity remained the same or similar, not the same, but similar to low-fat diet. The males did. We didn’t break it out statistically, but for the most part, the males lowered their physical activity on the high-fat, high-sucrose while the females maintained pretty much the same levels compared to low-fat.

So, what could be then impacting, further impacting energy metabolism, energy homeostasis to result in these differences in weight gain and body composition? And I want to bring up the energy flux, the idea of energy flux and energy coupling that I kind of hinted at earlier. We have to start with John Mayer’s data from the 50’s where he showed in rodents and in humans that you There’s a J-shaped distribution of food intake based on physical activity level. This data is from the paper where he assessed the activity and food intake of jute plant members in Bengal, India. So, as you move further to the right, the people are working harder and harder and harder, and they have increased energy intake to match that. What’s interesting is you move to the left of center of the graph, as the people begin to work less and less and less or have less physical activity, they actually begin to increase their energy intake as well. Others have gone on to describe this as regulated and non-regulated zones. A lot of the work is focused on the control of energy intake and appetite as part of that, while others have taken it even further to describe it as coupling. So, as we work harder, as we have greater physical activity, as the energy demand increases, the body is better able to match energy demand with energy intake at those higher levels of physical activity and energy expenditure. Whereas we reach a certain point, you know, to the left of center, where that whole system breaks down and we begin to consume more calories without an increase in energy demand.

So, to talk about this, we kind of had to come up with ways to present it. Now, energy flux has been defined by others as the energy content of the system, so energy intake and energy expenditure in this case. But I wanted a way to graphically depict this coupling, and so what we did was we graphed the data as 1 minus the excess energy, so the positive energy balance in this case, for the most part positive, divided by the energy flux. So, it’s the percentage of excess energy of the total flux. And then that’s just subtracted from 1 to make it higher. So, in this case, if we talk about the low-fat diet, you’ll see that the animals are, for the most part, pretty tightly coupled. We’re close to 100%. In fact, we’re over here. We had a few animals that had negative energy balances on the low-fat diet. But you’ll notice right off already that the 30-C mice have a lower coupling of total energy in this case. And that’s interesting, because we didn’t see a difference in energy balance, as I mentioned, but we did see a difference in weight gain during this.

If we transition then to the high-fat, high-sucrose data, first you’ll notice that all the groups lowered their energy coupling. This is not surprising, because positive energy balance went up in all the animals, in all the groups. But we have a difference still by temperature, but it’s important to point out now that we have this impact of sex, where the females are, again, more coupled, even during this energy challenge. And there’s quite a few reasons for this. They have lower energy balance, and they also had slightly lower energy flux to offset that. So, we’d have to spend some time parsing out why that occurs. But the big thing I want to point out is the magnitude of the difference. You know, it’s about 10% or so in the 20-C mice that it fell, but it’s nearly 20% in the 30-C mice. So, they just weren’t able, under this low energy expenditure condition, to match energy intake as appropriately. And I’ve kind of depicted that here in these simple diagrams, where the 20-C mice have this higher basal energy expenditure where they’re turning over. So when we challenge them with this diet, even though they eat more, that higher energy expenditure enables them to end up with a smaller energy balance, positive energy balance due to this diet, where you get the exact opposite effect with the 30-C minus, where they have this lower basal energy expenditure, and upon exposure to the high-fat I sucrose, they don’t adapt, appear to adapt well within this one week, and have a greater energy balance.

Other factors that could be impacting energy homeostasis? As Dr. Woody just described, another way to describe metabolic flexibility is as a response to a diet, in this case, a high-fat, high-sucrose. And what we graphed here is the change in respiratory quotient from the weekly average on the high-fat and the low-fat diet. And you’ll notice right off that the 20-C animals had a bigger change in their respiratory quotient. They burned more fat following transition to the high-fat, high-sucrose. But again, to point out, at least in the 30-C mice, it was significant that the females burned more fat or tended to increase fat oxidation or fat utilization to a greater extent than the males. But there’s problems with this representation that the 20-C mice eat more. So, RQ often is simply the food quotient. So, what is the macronutrient composition of the diet, and how much are they consuming? And the 20-C mice, even though the diet’s the same across the groups, the 20-C mice ate a lot more fat. So, you could suggest that they just burnt more fat because they ate more fat.

But I wanted to show you the data across the entire seven-day period for this measure. I wanted to show how quickly it occurs. I mean, just boom, immediately the animals reduce their respiratory quotient, and the 20-C mice have a greater initial drop, and they stay there. But I also want to point out the transitional or transitory pattern of the 30-C mice. This has been actually observed in humans before, where it takes four, five, six days or longer for the humans once switched to this high-fat diet to actually reach their maximal lipid utilization.

And finally, I kind of hinted at it, but I want to talk about diet-induced adaptive thermogenesis. So, this is the centrally mediated increase in peripheral thermogenesis on response to dietary changes, or to diet in general. And so, what we’ll see here is this is graphed as the change in resting energy expenditure, the change in total energy expenditure. Data looks similar to this. So, you’ll notice that the response to this, to the high-fat, high-sucrose, is much greater in the 20-C mice. So, those animals, excuse me, with the higher basal energy expenditure were able to increase this, or have a greater response in their adaptive thermogenesis in response to the diet compared to the 30-C mice. But the other thing I really want to point out is the divergent direction the female mice seem to go here, where we end up with the 20-C mice females having a much greater increase than the males, whereas it’s lower in the females at 30-C. They just couldn’t adapt the same. And so, there’s an interesting sex interaction there in response to diet as far as for this measure. And this is interesting because with the controversial discovery of functional brown and beige adipose tissue in humans, many, not many, some have suggested this is a potential therapeutic target in the treatment of overweight and obesity. But as I mentioned, I think one thing that will be really important if the companies are moving forward in this research line is to understand, or at least be proactive in investigating these potential sex differences, and that it also may synergize with the basal energy expenditure. So, while you might get one outcome of your test compound at 20-C, you might get an entirely different outcome at 30-C. And again, I wanted to show you how this data changes over the seven-day period. Again, we have a dramatic increase in both groups, but for the most part, the groups reach a steady state quite quickly, except those 20-C females, which again, take a couple of days to transition to maximal increases in resting energy expenditure.

But I have to describe the limitations, which are many. One, as the title suggests, this is only in mice. And this is only in C57/Bl6J mice. Many different sub-strains or types may have a different phenotype. So, the mechanisms of divergent energy expenditure. I said that physical activity was messy, and it did a lot of things beyond just increased energy expenditure. What we’re counting on here is the cold-induced thermogenesis primarily of the activation of brown or beige adipocytes and potentially the uncoupling of this calcium-fetal cycling in skeletal muscle to drive this thermogenic response in the 20-C compared to the 30-C mice, which could be complicating the outcomes that we have here. There was a really good paper that showed differences in short-term weight gain at different ages of mice by sex. And it showed that the male mice have pretty much the same proportional changes in body mass or in composition at three different ages, whereas the females do not. And so, what we see with the fat-free mass change here in these mice at 20-C, in particular the females, could be related to their age and may not be reproducible across other times or ages in this case. Thermal biology: Dr. Reitman just published another great paper on the impact of ambient temperature, and in this case, it was not just energy expenditure – he was looking at the thermal biology. Unfortunately, there was no female data really in that study and so we’re making a lot of assumptions here that thermal biology is the same, but across the sexes, and I think that’s kind of a dangerous assumption, because we have data that female mice have a higher core body temperature than male mice, and that female humans have different thermal biology in how they handle thermal stress. So, I think that’s something we need to think about when we move forward, as we move forward with these kind of studies. Another thing is the nutrient utilization. So, I was not able to calculate protein utilization in this study. And so, I’m making an assumption that their utilization of protein in particular is the same across sex, across temperature. I think that might be maybe a dangerous assumption as well. And finally, we weren’t able to calculate fecal energy loss to really get at the net energy intake in this system. We’ve added that capability, and so future studies will be able to look at that and utilize that to move forward.

In conclusion, then, I think this is a viable model. We can show that differences in energy expenditure mediate coupling of energy demand to energy intake, and that this impacts the response of energy balance and by composition of weight gain to dietary challenges. And these differences are more pronounced in the females. Changes in body composition – body weight was the same – but body composition was dramatic changes as were the responses in some of our outcomes. Again, I believe because the relationship is so nearly linear that you could use this modulation of housing temperature as a very powerful tool to pretty precisely modulate energy expenditure in your mouse models. And finally, though it was not the point of the paper, the ongoing controversy of mouse housing temperature and its impact on not only metabolic studies, but all of biomedical research, this paper just provides yet more data that, at the very least, you have to consider housing temperature and its impact on your experiment while you’re designing them. And maybe more importantly, while you’re interpreting the data, how your housing temperature could be impacting that (your outcomes).

With that, I’d like to thank my collaborators. But I’d really like to thank Roberto Noland, who was my technician at the time, who really helped me collect all this data. And I’d also like to thank the Kansas INBRE program, which funded this project in particular. And with that, I thank you for your attention, and I think it’s questions time.

Sarah: Thanks, Matt, for that great presentation. We are going to run one quick audience poll before we get started on our Q&A, so please be ready to participate. So, this poll is, which of the following animal models do you most often use? So, mouse, rat, human, other vertebrate, or invertebrate? And while I wait for those answers to roll in, I’m going to welcome back our speakers. So, Matt and Lauren, are you here with us? Perfect. Great. Okay, so it looks like we have most of those answers in now. I’ll give a couple more seconds. I still see some rolling in. Okay, so I’m going to move on to the Q&A. So, our first question here is for Lauren. Lauren, someone has asked, why did you just use male mice?

Dr. Woodie: Yeah, that’s a good question, especially given Dr. Morris’s talk. Female mice are obviously important, seeing as female humans make up about 50% of the population. So, that was a tough call, and it really came down to the fact that we were trying to measure rhythmicity, and it would have become a real monster of a study if we would have also had to take into account female reproductive cycling. So, they cycle about every five days or so. And the amount of, we actually thought about it, but the amount of controls that we would have had to add to our study just became, it became a monstrous study. So, unfortunately, we had to scale back and just look at the males at this point. But I certainly believe having another study just looking at females is a really valuable direction to go next. So, we observed this phenotype in males, I would love to see if it stood up in females as well.

Sarah: Great. Thanks for that answer. And this next question here is for Matt. Matt, do you think the smaller size of the female mice was involved in the observed energy metabolism data?

Dr. Morris: So, yes. To bring up another issue in indirect calorimetry of mice, you know, differences in size. So, the current accepted model is to use analysis of covariance to describe animals of different size. And while I did that in the paper, one of the problems that I’ve been trying to discuss with others is when you’re comparing males to females and they’re different size, do you covariate by their body weight or covariate by sex? Because they’re so different that is the fact that they’re female the reason they’re smaller, and so therefore you should use sex, or just use the most basic outcome and the fact that they’re smaller. So, if we do have analysis of covariance, in this case of total energy expenditure, the females actually have a greater weight-adjusted energy expenditure, which others have shown. And that’s not terribly surprising. But other things, like the 20-C mice, the smaller females, one of the reasons they have higher weight-adjusted energy expenditure, potentially, is because of their smaller size compared to the males, they have greater conductance or heat loss. So, they’re having to work harder to maintain their core temperature. I didn’t measure that. That’s just speaking out there. But yes, it’s very complicated, because not only are they not the same size, but then the entire, you know, difference of males versus females.

Sarah: Right. That makes sense. Cool. Great answer. So, we’re going to move on to our next question now. This question is for Lauren. Lauren, mice seem to be more dietary specialists than rats who naturally consume more sweet things. Would rats be a good model to examine these patterns?

Dr. Woodie: Yeah, rats would also work as well. So, what we were trying to do here was compare some of our results to the literature, particularly findings from Satchin Panda’s lab, where they noticed that TRF of the Western diet could reverse or protect against some of the metabolic outcomes of the solid high fat diet. So, they use mice there. And so, we followed up and continue to use mice in our studies, but certainly rats would be a great model. Also, if you ever wanted to do any type of behavior analysis, they perform much better. So, yeah, we chose mice to fit with the literature, so our results would fit, but rats would certainly work as well.

Sarah: Okay, great. I mean, that does make a lot of sense. So, we have another question here, Matt, this question is for you. You mentioned that fecal energy losses could be useful to quantify. Do you think that it’s possible that differences in fecal energy losses could differ among different classes of macronutrients, for example, lipids, fats, and carbohydrates?

Dr. Morris: Yes. I think we, not only would we end up doing straight fecal energy loss, we’d probably also be extracting at least lipids. I have at least a background in that, extraction of lipids. So, we’d be able to tell whether the lipids were different. I’d have to get into, I think lipids would be the primary component that we’d be seeing if things were actually changing. I could be entirely wrong there, but yeah, I’m just really excited to move forward with that idea, because I think sometimes the energy balance difference that is real life is not nearly as dramatic as we show sometimes. I’m really interested in moving forward with that. And there’s been some papers recently about the idea that fecal energy loss could be an adaptive response (in energy homeostasis). So, I think it’s going to be a really important part of our research as we move forward.

Sarah: Great, some cool future steps for you guys. So, we just hit noon, but we do have so many questions and I did want to answer a couple more, maybe just two more. If you can’t stay on with us, that’s okay. We will, like I said, be producing a recording of this and you can come back and watch the end of the Q&A if you’d like. But if, before you go, if you want to submit any questions for Matt and Lauren, you can do so using the Ask a Question panel and we will be sending out a Q&A report once the webinar is over and they’ve had time answer the questions. So, this next question is for you, Lauren. The question is, can you speculate on a mechanism for the drastic differences in total energy expenditure between the early versus late sugar drinkers? For example, could these differences be caused by differences in activity levels or in body temperature?

Dr. Woodie: Yeah, so I can’t speculate on body temperature because we do not have that capability in our metabolic phenotyping system, but one of the supplementary figures for that paper looked at activity and VO2, because the Weir equation is used to calculate the energy expenditure that I showed you guys, and baked into that is activity and VO2. So, when you see differences in energy expenditure, you think, okay, what’s actually going on with those two parameters as well? So, we looked at those thinking maybe the animals are getting super excited that they’re about to get sugar water. It’s exciting and it’s tasty. That was not the case. The EFG animals did not have increased activity before their sugar water and neither did the LFG animals. So, they weren’t changing their behavior or patterns of activity, but the VO2 followed patterns of energy expenditure. So, the EFG had higher VO2 during the first six hours and lower during the last, and the LFG had lower during the first and higher during the last. So, this timing of liquid sugar was really changing the metabolic patterns of the animals and thereby altering energy expenditure. So, that was really interesting. So, it was truly a metabolic shift rather than behavioral changes behind the energy expenditure.

Sarah: Great. So, I’m going to take one more question for Matt, but before I do, I just wanted to bring everyone’s attention to the survey that just appeared on your screen. We would really appreciate it if you took a couple of minutes to fill that out while Matt answers his last question. So, Matt, this last question for you is, did the difference in ambient housing temperature impact feeding behavior?

Dr. Morris: The answer to that question is no, for the most part. The only thing that really changed, so the length of feeding bouts didn’t change, the time between feeding bouts didn’t change. The biggest thing that changed was the amount of food they ate per feeding bout. The 20-C mice ate more every time they went to the hopper, but each of those feeding bouts was the same length as the 30-C mice, so their rate of food intake was higher, but all the other behaviors were the same. In fact, I went this morning and looked at the light and dark cycle comparison, and they both ate the same percentage of food in the light and dark cycle on the low-fat and on the high-fat, high sucrose. So, no, it didn’t really change their patterns at all, which I think I was kind of surprised actually. So, but no, the actual patterns or behaviors weren’t changed between the groups by sex or temperature.

Sarah: Okay, cool. All right, so I just want to thank our speakers again for their wonderful presentations and their insights, especially in the Q&A period. We really appreciate you being here today, and great job. Okay, so before you go, I just wanted to, again, bring your attention back to that survey. We’d love to get your feedback. If you do still have any questions, you can send them to us via the Ask a Question panel, and Lauren and Matt will get to take a look at those questions after the webinar is over, and they’ll be answering them in a document for everyone that will send around. So, thank you all for joining again today. When the recording of this webinar is ready, it will be posted and you’ll receive an email letting you know that it’s available. And finally, if you do have any last questions, please submit them now. In closing, we want to, again, thank you for taking part in this webinar and we want to thank our sponsor, Sable Systems International, for making this event possible. And with that, I will end the webinar, but I hope you all have a wonderful day or evening, wherever you are in the world. And we’ll see you next time you join for another webinar.  Thanks so much.