 Oh, can I use that? A shirt, please? Absolutely. OK. Welcome, everyone. So welcome to today's, I can't shut it, welcome to today's presentation and defense seminar from Anna Lindahl, who's a candidate for PhD in the lab. Yes. So I want to see if you were confirming that. So I have a few notes I'd like to say before Anna takes the floor. Before coming to the IPID program, Anna was an undergraduate at the University of North Dakota, where she received a Bachelor of Science in chemistry with an emphasis in biochemistry. During her graduate years here at UW, Anna has done a considerable amount of service. And I want to highlight that, because I think it's quite special, and it speaks to who Anna is. She's served on the IPIV Student Faculty Liaison Committee. She was also, may still be, an officer of the Madison chapter for the Graduate Women in Science group. And I think probably most importantly, she was co-founder and leader of the Badgers at WID. Badgers is an acronym for Brilliant and Diverse Graduate Student Scholars, Research Scholars, yes. And if you've, those of you that have been a part of WID knows the impact that that group has had on our environment in a very positive way and continues to do so. And I'm really proud of Anna's participation and leadership in that endeavor. She's also, some of the awards include being a Kohler fellow as well as a trainee in the Molecular Bioscience's training grant. Some of her work as a Kohler fellow has included hosting a couple events at, is it WART radio, or is it W-O-R-T? Do you actually say it? Do you say WART, or do you say W-O-R-T? Yeah. So she's hosted the, I guess it's called the open access content for two of those sessions. So there's a couple of personal things I want to say that I think speak to not only, well, speak to the kind of person that Anna is. And there are things that as a PI really appreciate. The first is her willingness to help others. She seems like she's always the first one to volunteer to help. New people coming into lab, or if we need stuff done in the lab, she's often the first person to step up and really carry the load. And I really appreciate that. The other aspect I want to convey to you about Anna is her ability to have really broad integrated knowledge of science, of general science, but also of all the diverse things that are happening in the lab. She takes an active interest in the projects that are happening currently in the lab, as well as those sort of aspirational projects that we sit around and talk about. And she's so good at that that I consider you my lieutenant when it comes to, even if I'm in the room, Anna is usually in charge. But even if I'm not there, I completely trust her to be my lieutenant and carry the load at meetings that we're talking about, these pie in the sky scientific ideas. OK, so that's a few personal things about Anna. But today we're here to discuss and have her present, rather, her thesis work. And her thesis work, as you'll see, has to do with trying to understand reversible sedlation in the nucleus. You guys have probably all heard about histone sedlation. That's super cool. But it looks like there's a lot of other cool sedulations happening on proteins within the nucleus. And she's uncovered some really cool pathways that suggest that we shouldn't just be thinking about histones. And related to this work, she's developed tools, and she's also utilized, genetically modified mammals. I tried to get a pie in the sky. That's where you were in China those few weeks. OK. No, but she's taken the tools that are available to her in terms of metabolic regulation of acetyl-CoA levels. And she's utilized that to try to understand, again, the mechanisms of reversible sedlation in the nucleus that are not just histones. So without further ado, Anna? OK, thank you, John, for that wonderful introduction. So as John said, I'm going to talk today about my thesis project, which has been on the role of acetyl-CoA and acetyl-CoA synthesis pathways in regulating nuclear sedlation. And so first, I'm going to introduce to you post-translational modifications. And so these are modifications, covalent chemical modifications that regulate protein function across the cell. And so they happen on proteins, and they can modulate their function. There are a couple of famous examples. Phosphorylation signaling cascades is one that can very quickly and dynamically regulate activities across the cell. And another that we'll dive deeper into is the histone code, which is post-translational modifications of histone proteins, which can open and close chromatin and control gene expression. Now post-translational modifications are very abundant throughout the cell. Here is just a categorization of some of them from a database of post-translational modifications that shows that phosphorylation is the most abundant and well-characterized. But acetylation is the next most abundant modification in the cell, and there's still a lot of questions about its functional relevance. So acetylation is a reversible post-translational modification of proteins. And here I have a protein depicted with a lysine residue exposed. And you can see here in the isolated form we have the acetyl group in red that's been added to this protein. And so the addition of this is catalyzed by acetyltransferases using acetyl-CoA as a co-substrate. And the removal of this group is catalyzed by histone deacetylases, or HDACs, and a class of proteins called sirtuins. Now, as I've talked about or I've implied previously, so DNA is packaged into the nucleus around histone proteins. And so here we have a depiction of the cell, and this is the nucleus inside where DNA is compacted. And so here we have what looks like it's mitotic chromosomes, kind of the most compacted form of DNA. And then as we start to kind of magnify in, we get a somewhat looser packing. And then here we have the depiction of individual nucleosome core particles. And so these nucleosomes are made up of a histone octamer core of eight proteins, or four proteins that are repeated, so eight members. And they have, as you can see, flexible n-terminal tails that stick out from the globular core. And so these tails are extensively modified. So here's just a depiction of the H3 n-terminal tail sequence. And you can see here all of these different lollipops that are sticking off of it are different possible modifications that can happen to this histone tail. And then we have depicted here some proteins that can control this information. And so combinations of these modifications are thought to give rise to a code of information on how to read and express the genome. And so some of these proteins depicted here are either code readers, so they bind specific modifications or code writers and erasers that can add or remove some of these modifications to change gene expression. Histone code writers require metabolites as co-substrates to write chromatin modifications. So it's a direct connection between metabolism and the histone code. Here are a couple examples. Gluconaculation of proteins requires UDP-gluconac. Phosphorylation requires ATP and is affected by ATP and AMP levels. Histone methylation is sensitive to methionine and SAM, which is the methyl donor in the cell, as well as can be influenced. Demethylation can be influenced by alpha-ketoglutarate, which is a substrate, as well as a couple other metabolites that serve as inhibitors of this enzyme. And as I said, we're going to focus in on acetylation here. So acetylation is catalyzed by histone acetyltransferases or hats or cats that can also be abbreviated because lysine is abbreviated with a K. And so acetyl-CoA is the co-substrate and the acetyl donor in these reactions. And there are a couple of ways in the cell that you can synthesize acetyl-CoA. One of them is from acetate using the protein ACSS-2 to add an acetate group to CoA. And then the other is using citrate and pyruvate derived from glycolysis through either ATP-citrate lyase or acly and the pyruvate dehydrogenase complex PDC. And then removal of acetylation is influenced by NAD levels that are a co-substrate for certuins, as well as beta hydroxybutyrate and lactate, which can influence other classes of histone deacetylases. So one of the reasons we were interested in modulating acetyl-CoA levels and interested in acetyl-CoA synthesis is because it's a compartmentalized system. And so subcellular compartmentalization of acetyl-CoA synthesis controls concentrations across the cell. So here we have depicted, if you think of this whole slide as a cell, we have the nucleus over in this corner and the mitochondria here. And the rest is kind of the cytoplasm, where we have glycolysis that can occur and process glucose and imports pyruvate into the mitochondria. And then it can go through the TCA cycle in the mitochondria, as well as beta-oxidation. So then the only real exchange of kind of acetyl-CoA levels, although it's by proxy, is the export of citrate, which can then be cleaved by ATP-acetyl-Liase to create acetyl-CoA in the cytoplasm or in the nucleus. The other pathway that contributes to this is ACS, or ACS is 1 and 2 in mammals, 2 being the cytoplasmic, a nuclear form of this protein that takes acetate and makes acetyl-CoA. There was kind of a question when I jumped into this project that was posing the field on thinking about histone acetylation and acetyl-CoA levels and asking if histone acetylation levels are mediated by a global or a local production of acetyl-CoA. And so in a global model, you have these three pathways that can synthesize acetyl-CoA contributing to this large diffuse pool that can kind of freely diffuse throughout the cytoplasm and nucleus. And then histone acetyl-transferases pick up this acetyl-CoA kind of non-specifically and target where they're directed by other pathways. Whereas a local histone acetylation kind of model would have metabolites being passed along either a complex that actually interacts or some sort of metabolic hub or relative co-localization of proteins and then actually directly help target where this acetylation occurs. And so this kind of asks the question, is all acetyl-CoA created equal? Does it matter what pathway it's derived from? So there's a couple of different studies that had already previously come out when I started this project that had some conflicting data on whether it was global or local. And so the first one from Katie Wellin showed that ATP citrate liase and ACS2 both globally affect histone acetylation. And so here they focused on ATP citrate liase. They were able to show it's labeled here with GFP in green and this is mitochondria labeling and then the nucleus. And you can see in the overlay that ATP citrate liase is capable of being recruited into the nucleus. So then they looked at histone acetylation levels and they see in their control when they look at acetylation on a couple of different histones, kind of the baseline level. And when they remove ATP citrate liase from the system, they get a significant reduction in histone acetylation. It's quantified here as up to 50% on some of the histones. Now when they knock down ACS2, which is labeled by its older nomenclature here, you can see that there's not that much of an effect. And when it's quantified, it's at best 30%. Now when they knock down both proteins, you can see that histone acetylation levels are pretty much gone. They can get rid of close to 90% on some histones of the histone acetylation. Now when they add acetate to the media, because this is in a glucose dependent tissue culture system, and when they add acetate to the media, they can see that they can alter kind of the balance or the capabilities between ACS2 and ACLE. Where you can see they have their control levels and when they deplete ACLE, which is the glucose dependent system, they don't actually get that much of a loss of histone acetylation because they've provided acetate. And you can see here that they do get significant reduction again when they knock down both ACS2 and ACLE. Now another study showed and looked kind of in a more relevant metabolic system for ACS2. ACS2 is involved in lipogenesis, particularly under hypoxic conditions and in solid tumors. And so in a cancer cell line, they used hypoxia, so low oxygen conditions, to mimic kind of that metabolic condition for solid tumors, to be able to drive acetate dependent histone acetylation. And so here you can see that when they add acetate without the hypoxia, they don't really get a shift in acetylation. When they add the hypoxia, they get a reduction in acetylation because they haven't added acetate at that point. And then when they add acetate, they get a significant increase in this acetylation. And they were able to show then by removing ACS2 from the system with a knock down that they can get rid of this effect that's both acetate and hypoxia dependent. Showing that ACS2 is likely directly involved in this mechanism rather than some large metabolic change. To measure directly that ACS2 was involved in this, they actually label their acetate with an isotopic label on the carbon and they can show high levels of incorporation in a normal cell line that has their control knocked down. And then when they knock down ACS2, they get a significant reduction in multiple acetylation sites. But interestingly, the same study showed that there is some level of site specificity that might be going on where they look at for two genes involved in fatty acid synthesis, they look at multiple acetylation sites. So we have H3K9, H3K27, and H3K56. And as you can see when you add acetate here, which is the second bar, you get an upregulation of acetylation, which would be opening chromatin and turning these genes likely on. Now, when they add their ACS2 knock down, you can see that they lose this effect on all of these sites. But what's interesting is that they test ACLE, the ACLE locus, to see if ATP citrate liase, which is kind of the other enzyme involved in this system of synthesizing acetyl-CoA, to ask if it reacts similarly. And as you can see here, the answer is no. So ACLE acetylation is not acetate dependent and it's not ACS2 dependent, suggesting that it's not an entirely global concentration phenomenon, but there is some level of site specificity going on. Now, as John alluded to in his introduction, acetylation is a really abundant modification in the nucleus beyond histones. Histones are probably the best characterized nuclear acetylsite, or acetylated proteins in general. But large studies in the last couple of years have started to focus on nuclear acetylation because it's in part of really abundant modification in the nucleus. So this is just one proteomic study that the Chudhari lab put out a couple of years ago and across the bottom here, they're profiling different H-deck inhibitors and so they're looking at inhibiting the removal of the acetyl group. And what I want you to get from this graph, so there are about 8,000 sites they characterize in this study, there's a lot of red here. So there's a lot of nuclear proteins that they're able to characterize that are not just a little bit acetylated, but they're also enzymatically regulated. And from this study and all of these red acetyl sites, you can see that only 1.2% of the sites identified within this study are actually histone proteins themselves. So then that kind of begs the question, what are all these other proteins? So they characterize what proteins they had enriched for enzymatically regulated acetylation and they're able to see that they get enrichment for transcription, RNA processing, particularly splicing and mRNA processing and a lot of chromatin mediated important events in the nucleus. And so I kind of modified this question then for my thesis project and that instead of asking is histone acetylation global or local, I'm asking is nuclear protein acetylation mediated by this global mechanism that drives acetyl-CoA concentrations or a more local production of acetyl-CoA. And so to do this, we needed a method that instead of doing western blots for individual histone modifications, we can actually more globally profile nuclear proteins. And so to do that, we used mass spectrometry using a method in our lab that a previous graduate student had developed in conjunction with some work that I've done to improve this method for nuclear coverage. And what we use is a method that determines acetyl-stoichiometry. And so I'm gonna go through what stoichiometry is before we jump into some stoichiometry data. So many types of studies use relative quantitation between two different conditions and stoichiometry is a little bit different than that. So here we have depicted a relative quantitation experiment where we have protein X and protein Y and condition A and condition B. And you can see here all of these black dots are acetylated proteins. And so here we're going from one protein to five proteins and 10 proteins to 50. And the full change between those conditions of the relative quantitation is a five-fold increase in both of these contexts. Now, if we look at them in the context of the entire population of protein X and protein Y, you can see that we have one of 100 and five of 100 and 10 of 150 of 100. And so instead we're quantifying a 1% stoichiometry of acetylation to a 5% stoichiometry of acetylation and a 10% to a 50% change. And so one of the reasons we do this is because to interpret which acetylation modifications are more functionally relevant, it's certainly hard to prioritize between these two different sites. They kind of look the same in the data. Now, if we want to prioritize for follow-up, certainly a jump from 10% to 50% acetylation looks more like it would be functionally relevant to the cell, particularly if that acetylation were inhibitory. If you think about it jumping from 1% of your units to five that are non-functional, probably not that much of a challenge for the cell in comparison of jumping from 10% to 50% of your units being non-functional of any particular protein. So this is just a depiction of our mass spec method that we use this in. And so we perform our stoichiometry using a chemical labeling approach. So we first take our biological sample and then we label it with the C-deac anhydride. And so our endogenous acetylation has the naturally occurring isotopes of C12 and just regular hydrogen. And to be able to see the difference between endogenous and our chemical label afterwards, we use deuterated acetic anhydride so that we have a mass shift that we can detect by mass spectrometry. So then we do our digestion so we get chemically identical peptides because all lysines are acetylated at this point. And then we can do a form of separation and run both a spectral library generation and our quantitation samples. And so we use a method on the instrument called data independent acquisition which is a little bit different if you're familiar with shotgun. It's a little bit different than a shotgun approach. And so the biggest thing to kind of know about the difference is shotgun takes individual peptides and fragments them and then that pattern is used to identify the peptide whereas data independent acquisition takes windows of peptides together and so it takes this range and it puts everything together and fragments it and then you can take apart this data that you get and put it back into a spectrum based on a reference set of samples you've already generated. So now that we have this method that worked really well we wanted to look at specifically acetyl-CoA metabolism in some biologically relevant system. And so we decided to look at ACSS2 in particular and focus on two tissues, brain and liver and one of the reasons being the importance of acetate metabolism in the brain. And so here I want you to focus in on so we have pyruvate being derived into this relatively brain specific metabolite enacetyl spartate and so enacetyl spartate is a relatively abundant metabolite within the brain that's passed from neurons and axons into oligodendrocytes and then cleaved into lspartate and acetate and this acetate is then synthesized into acetyl-CoA and eventually into myelin which is kind of the coating around your brain and spinal cord that's the insulation that protects the wiring of the central nervous system. And so a loss of the ability to cleave and use this acetate ends up in neurodegeneration and eventual paralysis in a mouse and a rat model. And so we were interested because acetate supplementation in this model is able to rescue this problem so acetate synthesis into acetyl-CoA is very important. So we conducted or I conducted an acetyl proteomics study on we have an ACSS2 knockout set of mice that we got from a collaborator. And so we have our normally fed mice we have a wild type and an ACSS2 knockout and then we look at the dietary challenge of a prolonged 48 hour fasting period. And the reason we look at that is in part because of the fact that glucose dependent systems are likely depleted at this point and so acly compensation in the knockout is probably relatively low. And also the fact that at 48 hours fasting ketone body synthesis and utilization which is important between the liver and the brain is likely metabolically very active and important in this system and acetate metabolism is a part of that. So we were able to get really great data with this method. I was really excited when we got this data back. So I'm just gonna kind of go over globally what our coverage looked like and then get into what we have. And so if we look at brain and liver of the chromatin proteins we were able to profile I was able to see about 1500 proteins in brain and about 1200 chromatin proteins in liver and we were able to get about 8,000 peptides in brain and about 5,000 in liver and then see about 4,000 acetylcytes in brain and a little under 3,000 in liver. And kind of the numbers we were really excited about is these sites that we can quantify stoichiometry on. So that would mean we need to see the heavy and the light peptide. And so we're able to see the heavy and the light peptide of all of about 3,000 peptides in brain and about 2,000 of them in liver to be able to quantify stoichiometry on these sites. Now the other thing I was really excited about and one of the strengths of data independent acquisition that we utilize here is the fact that the coverage there's lots of good coverage and no missing or relatively low missing values in this system. And so for protein overlap as you can see here this is pretty much a circle. There was a lot of protein overlap even across tissues of chromatin proteins and our peptide overlap is also very good allowing us to compare across conditions. Because if we can get stoichiometry in one condition and then we can't see it in the other it's not very helpful for us to not know what's going on in both conditions and not be able to compare. So in thinking about our global and our local model of the production of acetyl-CoA we would think if acetyl-CoA levels were globally influencing acetylation in the nucleus that we would see some sort of global response. But we don't. So one of the first things I asked with this data is is the global distribution of acetylation skewed in any direction during either fasting or in the ACS is to knock out in either liver or brain. And as you can see here these distributions look very similar and when we do statistical testing on them they're definitely not significantly different. So now that we know that there's no global change we can kind of ask the question are individual sites changing, right? Because this global distribution isn't shifting but sites may be moving across this distribution. And so we looked at site level changes and I'll kind of orient you to this graph because we've designed this specifically for our stoichiometry data. So in this column here we have the ACS is to knock out and in this one we have the wild type and on top are the two are the brain samples and then on the bottom are the liver. And what these lines represent is a magnitude change of stoichiometry and the colors indicate which of the two conditions of our dietary conditions is higher. And so for example these two top protein sites in the ACS is to brain knockouts are about 0% acetylated in the fasted condition and then go to nearly 100% acetylation in the fed condition and they're colored red because the fed condition is higher. And then the next line under that's blue you can see that it's nearly 0% acetylated in the fed condition and it's much higher close to 80% in the fasted. So that's how you interpret this graph. And one of the things I want you to see from this is that we definitely have some different patterns. Some of them are tissue specific and some of them are interestingly genotype dependent. And so interestingly we get a larger amount of large magnitude changes in the brain. The liver's pretty clustered at lower magnitude changes of acetylation stoichiometry which we actually found a little bit of a surprise. The other thing I think that's very noticeable is that we have some of these larger acetylation changes and clusters that are missing in the ACS is to knockout that are present in the wild type suggesting that some of these changes between fed and fasted condition are ACS is to dependent. So this is another way to look at this data. This is a volcano plot where we have the statistical significance and we have the difference in stoichiometry across the bottom and the points that are significant are labeled and some of them are hard to see but this is within the brain and you can see the knockout and the wild type that there's significantly quite a few proteins in both the knockout and the wild type but what's interesting is subsets of them are different and so these aren't just the same proteins. But more starkly I think showing that the liver doesn't have much of a response is this liver volcano plot which when I outputted this data I was very surprised by actually went and double checked the quality of the data to make sure this was right. Where we have a large clustering of acetyl sites that don't actually change in stoichiometry between a fed and fasted condition and we don't see large differences between the knockout or the wild type either suggesting that chromatin acetylation in liver is not really ACS is too dependent and doesn't seem to be highly responsive to fasting. So now that we've looked at site specific changes we can ask questions about if it's localized production of acetyl CoA it's likely in localization with other pathways and so there may be specific functions that are enriched for in changing acetylation levels. And to do that a previous grad student in the lab and a post back worked on a way to look at functionality enrichment in acetyl stoichiometry data sets because it's a little bit different of a challenge than looking at it in like gene enrichment. And one of the reasons why is because when we look at pathway level trends we're looking for both enrichment of high stoichiometry as well as enrichment of acetylation across multiple sites on a single protein and across a pathway. And so this is just an example of a depiction of acetyl CoA synthesis from bacteria that Josh Beza worked on. And as you can see here we have all of these boxes or proteins involved in these pathways and all these lollipops are different acetyl sites. So you can see that we have some acetyl sites that are super acetylated. They could be close to 100%. And so those we wanna capture in our enrichment because they're high stoichiometry. But we also have many proteins that have lots of acetylated sites that each are lowly acetylated. And it's quite possible and we wanna account for the fact that these proteins function maybe just as affected by acetylation as one with a very high acetylation modification because the effect of acetylation may be additive across a protein or a pathway. And so that's how our QSSA analysis works is it accounts for both of these things. And so we wanted to look at our pathway level alterations and acetylation stoichiometry in our fed and fasted conditions in our wild type and knockout animals. And so I'll first go through the brain data. And so to orient you to this graph a higher QSSA score means more enrichment and a lower QSSA score is obviously not enrichment or close to de-enrichment. And if we look at the fed wild type, animals kind of what we would maybe consider a normal state for acetylation. You can see that metabolism is the most enriched for acetylation in this system. And then next is a subset of pathways involved in cell senescence, DNA damage, apoptosis and cell death that are highly acetylated. There's both highly stoichiometry sites, so ones that are close to 100%, as well as just a lot of sites enriched for in this pathway. Other pathways that are enriched for are the metabolism of proteins, the metabolism of RNA and HDAC class three signaling events, which is the SIR2 and family HDACs. So interestingly if we look at our fed ACS2 animals you can see that there's not much shift in our enrichment patterns. But when we start to look in our facet animals we can see that we do get some shift of enrichment. We have some more of these being more highly enriched and a little bit of a de-enrichment in metabolism in comparison to the fed animals. And also we have an induction of enrichment in the fasted condition of these pathways as well as metabolism of RNA and metabolism of proteins. And interestingly for some of these events within the fasted ACS2 knockout animals we get significantly less enrichment and many of these sites, the acetylation is pretty significantly reduced. Suggesting that they're ACS2 dependent and that this acetylation event is important in fasting. Now in liver I alluded to we don't have much change in acetylation and so some of this pathway information should be taken a little bit with a grain of salt because of the scale of change being different than the brain. But we do have interestingly some of the for enrichment in our fed wild type conditions, the cellular senescence pathways and program cell death being highly acetylated in comparison to some of the other pathways. Interestingly in the fed ACS2 knockouts this is relatively lost suggesting in a fed condition it may be ACS2 dependent but we don't see all that significant changes in the fasted between the two. Which when we looked at our site specific data there wasn't much shift in acetylation stoichiometry at all so this isn't really surprising. So just want to summarize this far before we jump into a couple more data points with this project. Fasting alters chromatin acetylation in an ACS2 dependent manner on specific pathways in brain particularly RNA processing pathways and nuclear regulation of metabolism. And also fasting and ACS2 dependent chromatin acetylation changes are relatively limited in the liver. So I talked about earlier that my project is asking about nuclear protein acetylation mediated by global or local production of acetyl CoA and certainly looking at this I can't skip histones. They're a very big portion of the acetyl group present in the nucleus. And so I looked at histone acetylation and thinking about a global versus a local mechanism we definitely thought initially that if a global mechanism were present we would get reduction of acetylation in an ACS2 dependent manner in the knockouts across many histone sites. Previously in tissue culture it didn't matter which lysine you picked on histones. If it was acetylated it was reduced. So what we see is that that's not the case and we actually get a pretty site specific response and it's specific to each tissue. And so here's characterized a heat map of the histone post-translational modifications that I looked at across. We have brain here and liver and a couple of the comparisons and I'll zoom in on the ones that are interesting for you. So the first one is looking at H4 acetylation that's specifically changing in brain. And what's interesting about this is that we have what looks like kind of a movement towards we get an up-regulation of the quadruple acetylated in our fasted wild type and then in our fasted knockouts we actually have an increase in the diantriacylated forms. And it looks like possibly what's going on is that acetylated histones are being pushed in the fasted condition towards quadruple acetylated or more acetylated groups and in the knockout they seem to kind of get stuck in these intermediate forms. Now the other interesting group that we saw was actually in brain rather than liver and this is the H3K18K23 peptide specifically acetylation at H3K18. And so what we see in this condition is again a fasted wild type induction of acetylation both of the diacetylated form here as well as the singly non-deconvoluted acetylation and we have a reduction of methylation it's not even detectable in that condition it's been reduced. And what happens is then when we knock that out we actually lose this induction of acetylation and so there's a fasted dependent acetylation of H3K18 that's lost in our knockout animals. And H3K18 acetylation is involved in enhancers and so it's helping to kind of turn on and off in long range interactions genes throughout the genome. So we were interested in looking at the effects then of these site specific acetylations what genes are being changed. If a global reduction of acetyl-CoA were going on we would think transcription in our knockouts would be globally reduced. But what we see is a more site specific pattern or a glow site specific pattern which is kind of similar to our histone data that looks like it's more specific rather than global. And so here we're looking at an RNA-seq data set and this is the log two full change of the ACS2 versus the wild type and the first two columns are brain and the second two are liver and we fed and fasted for each of those. And so and then I've clustered this data to look at kind of the pattern level of responses and what I hope you can see from this is there's very distinct kind of dietary and tissue specific response. These clusters don't have a lot of overlap except for cluster two across tissues or across diets and response. And interestingly since this was a pretty specific pattern I wanted to ask are there functionalities that these things have in common? Are there specific functions? And so I looked at pathway enrichment for these differentially expressed genes and one of the ones I'll draw your attention to that's interesting is in this cluster four, the purple cluster which is down-regulated in the absence of ACS2. We can see that RNA transport and the spliceosome are pretty heavily present in this pathway or in this gene data set which is interesting because in brain and our chromatin acetylation data we also have acetylation on these pathways being ACS2 dependent during fasting. So this is just another way to look at some of the pattern of this response and see that we don't see a lot of overlap across our conditions and tissues in a response. So we have our totally differentially regulated genes and we have our up-regulated and our down-regulated and there's not a ton of overlap. There is some particularly either shared between fasting or between tissues. So then I ask the question if there's not a lot of overlap in genes, is there an overlap in the mechanism driving them? And so I looked at transcription factor enrichment for these different genes that are changing and so we get this huge amount of overlap transcription factor enrichment and it's actually a network of proteins that interact of which the members P300 and CBP are part of and those are histone acetyl transferases and so we were really excited about this data because it certainly suggests that acetylation is heavily involved in controlling these transcriptional changes. And so here is the network of proteins and the interactions that they've had that have been characterized. The color of blue, the darkness is the fold enrichment and the size of the circle is the level of significance with all these being filtered for statistical significance. And so you can see here P300 is at the bottom of this and connected to many members of this network. I was very excited when I looked at some of the details of some of these other proteins because they're P300 co-activators and also substrates for acetylation. And so P300 acetylates a lot of these proteins and some of them, although I don't see many of them in my data set, some of them, the acetylation could be directly mediated by the ACS-2 derived acetyl CoA. So the kind of final question I asked in these animals is about metabolism because ACS-2 can be involved in metabolism as well as if we're looking at global production of acetyl CoA, we would expect global levels of acetyl CoA to change. And so I did metabolomics on these animals. And so you can see brain here and liver and this is looking at the log two fold change of these metabolites. And I've kind of characterized general categories here. And so kind of the major trends that came out of the metabolomic data is that we see in the facet versus the fed animals in the brain kind of a metabolic suppression going on, which is not surprising considering in the facet condition, there's probably not a lot of glucose around and the brain is heavily relying on ketone bodies at this point. Interestingly in liver, there's not a ton of pathways that jump out, although there is some misregulation or changing levels of cyclic AMP and citrate, which are definitely involved in metabolic signaling and citrate could be being utilized more to create acetyl CoA. When we look at global levels of acetyl CoA, so we're looking at the fold change of knockout versus wild type here to the left in brain, liver, of fed and facet and comparing between the two genotypes, we can see that we don't actually measure a global change in acetyl CoA levels or CoN's IMA, which is the precursor that ACS2 would be using. Suggesting that this isn't just a global concentrated mediated response, but many of the things we see are probably more locally driven. So I've shown you as part of this project that we have a tissue in site specific rather than a global histone acetylation response to the loss of ACS2, as well as the ACS2 dependent changes in transcription, share transcription factor network, although they don't have a lot of overlap amongst their identity. And then also that we have the loss of ACS2 not altering global acetyl CoA levels or CoN's IMA levels, suggesting the alterations we see in acetylation are more localized. So from all of this data, I've concluded that ACS2 promotes nuclear protein acetylation in a tissue in site specific manner in response to fasting, particularly in brain on RNA processing pathways and on metabolic pathways regulating metabolism in the nucleus. So instead of this global histone acetylation mechanism of large changes in acetyl CoA, we have this more localized mechanism that I believe my data heavily supports. So then I'm gonna tell one more short little vignette about another acetyl CoA synthesis pathway. And so if ACS2 is through a more localized manner, wanted to ask a question, are other acetyl CoA synthesis pathways also sharing this more local mechanism are they global instead? And so instead the pathway I focused in on for this next part is ATP citrate lyase, which cleaves citrate into acetyl CoA and oxovalacetate. And so asking the question on whether citrate acts through this mechanism or more similarly to ACS2. And just to remind you, ATP citrate lyase uses citrate from the mitochondria and cleaves it to create acetyl CoA and has been localized to both the cytoplasm and the nucleus. So interestingly, we didn't see ACS2 dependent changes of chromatin acetylation in the liver. But when we look at aclea and its significance in the liver, aclea has a more important metabolic role. People have shown previously that the loss of aclea results in protection from a high sugar diet induced fatty liver. And so here we're looking at kind of an initial characterization of a knockdown of aclea, where you can see this is their control and this is the removal of aclea from the system using a denovirus knockdown. And you can see a reduction in liver weight in a high sugar diet, suggesting that these liver don't get fat and these ones in white do get fatty liver. And you can actually look at the imaging. So here is I believe a red oil stain of looking for fat droplets. And you can see when aclea is present in the system and you add a high fructose diet, you get fat deposition in the liver. And if you lose aclea, you don't. And so we have a collaborator, Katie Wellin, who created a liver-specific knockout of ATP citrate liase. And I wanted to look at chromatin acetylation sites within the liver. And so we looked at a regular chow diet and a high fructose diet. And as you can see, we definitely get a genotype dependent response to both chow and fructose. Interestingly, there are subsets of sites that are lost in the fructose diet. Excuse me, suggesting that some of them may be acle dependent. So if we look at this data another way, we can see that there are many sites within the chow diet that are definitely in a glucose-driven system acle dependent and we get some spread of some other sites as well as some loss of sites in our fructose diet. So if we look at functionality in the system of what pathways are involved, we can see, excitingly, that many of the pathways we saw in brain and liver previously as being highly acetylated recapitulate that pattern here in our wild type, normally fed animals. Interestingly, in the acle knockouts in the chow diet, we get a loss of the HDAC class three pathway as well as P53 regulation of metabolic genes in the nucleus. Interestingly, the pattern seems to reverse itself in the fructose condition, suggesting there's a high enrichment for acetylation on this pathway, which is possibly helping induce fatty liver. And when we lose ATP-saturated lice in the system in the fructose diet, we can see a recapitulation of the regular chow diet suggesting that the acle knockout animals are insensitive to the fructose diet. And their acetylation response is also insensitive. So it looks like from this data that acle is promoting nuclear protein acetylation in liver in a site-specific manner in a response to fructose. And so instead of this global mechanism of acle, we also have data that supports that acle also functions through a more site-specific localized manner. So together, I think that these data suggest that many of these pathways are likely working through a localized mechanism rather than a global concentration dependent mechanism, which I think spigs the question then of what is some of the overlap of these pathways of derived acetylation and what is their mutual exclusivity as well as do they share upstream mechanisms and upstream signals or are they different? And so the major conclusions from my thesis work that I've touched on some of them is that I worked on developing a method to quantify site-specific lysine acetylation stoichiometry across subcellular compartments. I didn't go into detail about that today. As well as I found that ACS-2 promotes nuclear protein acetylation beyond histones in a tissue and site-specific response to fasting, particularly on pathways in which ACS-2 metabolically plays a role. Also that ACS-2 promotes nuclear acetylation beyond histones similarly to ACS-2 in a tissue and a site-specific manner and the response to a high fructose diet is lost in the absence of ACS-2 and this is also recapitulated in the loss of a response of chromatin acetylation. And finally, I didn't get to touch on this today but I also characterized an ACS-2 knockout tissue culture system to be able to serve as a viable model for more detailed studies of the ACS-2 and acolyte-driven chromatin acetylation mechanisms. So I would say the major conclusion from my work has been that acetylchoisynthesis pathways locally regulate chromatin protein acetylation rather than globally and then it's quite possible that many other connections between metabolism and chromatin are driven through a similar phenomenon which is significant in part because people are very interested in mediating the relationship between chromatin modifications and gene expression and metabolism particularly in diseases such as diabetes, fatty liver and there's been a lot of interest in cancer and whether dietary restrictions can make chemotherapeutics more effective. So with that, there's a lot of people I'd like to acknowledge. John has been a wonderful advisor throughout my time here at UW and I'm really thankful for joining his lab and the ability to ask questions that I was really interested in. I definitely had, I think, a little bit of a time wrestling with my project in the very beginning because it felt very beastly but I think through the independence he gives us to develop as scientists. I had a lot of failures in the beginning but also some successes which gave me a lot of confidence to tackle this problem. I'd also like to thank the members of the junior lab particularly and as the glue I think that holds us all together as well as James who helped me learn about mass spectrometry and taught me how to use the instrument because I was so afraid of breaking it the first time I used it. As well as Alexis who's been a partner on a lot of this acetylation stoichiometry journey. As well as I'd like to thank some previous graduate students Josh Beza who piloted the acetylation stoichiometry method and taught me a lot. Kim Kropp Kramer who helped me get started on the histone proteomics. As well as Michael Smolligan who started me out in doing some of my own data processing in R. And I'd also like to thank my thesis committee who I think over the years has asked a lot of great hard questions and definitely challenged me to think about my project in a broader way. As well as our collaborators on the Nambru Dury Lab particularly John Moffitt a scientist and Katie Wellins Lab at Penn particularly her graduate student Steven. And I'd also like to thank my funding during my time here. So and as I think this slide shows there's a lot of people that have come and gone in the Dany Lab and we've had a lot of great times. And so here's just a sampling of some photos, some old lab pictures because we can't keep a current one for more than a couple months I feel like before someone either comes or leaves. As well as some great times we've had outside of lab. Let's see this was the day I passed my pre-limb. So we've had a lot of fun together and it's been great to have great lab mates that I consider friends. So I've also had the privilege of joining a lot of communities in Madison. I'm gonna cry. And making a lot of great friends and connections have definitely helped Madison feel a lot like home. So here are just some groups of my friends from grad school. This is on my birthday. We threw a little party in Arkansas when we were down there on vacation. As well as I am a very passionate attender of plays and musicals and I've definitely found some co-conspirators who've joined me along the years. And then I've also found a great community at Christ Presbyterian Church here in town of some groups of people in their 20s and 30s. So young adults as well as the fact that I've been helping out with a middle school and high school youth group for the past five years and gotten to work with middle schoolers and high schoolers and learn so much about things like TikTok that I had no idea existed for the longest time. As well as I'd like to thank my family who's tolerated the fact that at the last minute I've occasionally had to cancel coming to birthdays or different things. And thankfully most of them have been pretty close to visit. And so it's been a great journey and we've added some people along the way. My sister likes to joke that my thesis is a kindergartner because Lillian, my niece, was born the day I joined John's Lab during the iPad Christmas party. And so she'll be starting kindergarten this fall. But with that, I wanna like to thank my dog captain who is the star of my Instagram account. But with that I'll take any questions. Yeah, yeah, so in the lab we have a method to do single amino acid digestion and look at actually global levels of assimilated lysine versus lysine as well as the fact that we can do a knockdown of ACS-2 in our acly knockout mefs. Now, those cells are probably very, very sick and it would have to be pretty quickly after you do the knockdown because when we've done acetate deprivation on those cells they definitely look like they're probably starting to die relatively soon. And so I actually think that maybe it might be better to do metabolic labeling of acetate and glucose and look at direct placement of those modifications that way using our stoichiometry method because then the cells are a little bit less stressed out because it certainly is hard to interpret if cells in essence is one of these big pathways that may be important and these cells are actively dying interpreting that data would be difficult. Yeah, that's a tough question. We haven't I think tackled or wrestled with that completely yet in our data because it's quite possible that much of it is through its metabolic activity. We have looked at protein abundance levels and there are some protein abundance levels that are changing. I would say looking globally at the data there are certainly more acetylation changes than there are protein abundance levels that I've characterized on chromatin. But there could be also changes in the mitochondria that are responding to these changes in metabolism as well. No, so we haven't done like RNA sequencing or QPCR in our acly, liver specific knockouts. So we can do that and we also need to circle back with Katie and see what she's already done. Right, for mice. So we haven't looked at day night fasting feeding cycles so I don't entirely know. But we have looked in tissue culture at some more, Alexis's project has looked more specifically at a very shorter time course in response to changes in serum levels. And so we do get a pretty rapid response in that system. So I would guess that it or hypothesize that at least some of these sites are relatively cyclic in their acetylation behavior in feeding and fasting. But it's probably only a subset of them, I would guess. Oh, I don't, that's not something I've looked at. It's quite possible. I do know that the transcripts, although it's interesting, so we don't see, or I don't see protein level changes that much. There might be some subtle changes and our collaborators looking at distribution using imaging. So that might be a method of changing their activity. But the transcript levels do cycle and people have found that, which I find interesting because we don't see protein cycling on levels changing. And actually to induce either strong changes in acly or ACSS2 protein abundance, you have to really stress out the system. So they can only, other people have only driven ACSS2 protein level changes in an acly knockout in like hypoxia with glucose deprivation. And it's this very contrived system that they kind of finally get a protein level response.