Dr. Jared Rutter Links Mitochondrial Overload To Cell Damage

Jared Rutter 博士指出线粒体能量超载与细胞损伤存在关联 线粒体充当着动态资源分配者的角色，其能量超载会产生诱发细胞衰老、癌症和心力衰竭的活性氧（ROS）。 Jared Rutter 博士重新定义了新陈代谢，指出它并非全身体统一的单一速率，而是由约 30 万亿个独立细胞代谢共同构成的动态复合体。对话重点探讨了线粒体如何作为决策中枢，决定将营养物质燃烧以提供 ATP 能量，还是分流用于构建促进生长与修复的细胞生物量。内容涵盖了线粒体的内共生进化起源、线粒体丙酮酸载体（MPC）的关键作用、乳酸作为关键燃料的功能，以及癌症如何通过瓦伯格效应（Warburg Effect）劫持代谢资源分配。此外，讨论还涉及过量能量超载及活性氧（ROS）在推动衰老和疾病方面的细胞危害。 线粒体因摄入过量能量而超载时会产生大量活性氧（ROS），引发氧化应激并损伤蛋白质和基因组 DNA，从而加速细胞衰老与功能障碍。 (0:00) 人体代谢并非单一统合的系统，而是由大约 30 万亿个受到动态调控的独立细胞代谢共同构成的复合反映；衰老的普遍特征则是线粒体逐渐失去活力和效率。 (2:29) 线粒体起源于远古宿主细胞吞噬细菌的内共生事件，是复杂真核生命演化的关键转折；它保留了独立且呈环状的 DNA，在人类遗传中严格遵循母系遗传。 (8:36) 线粒体在不同组织中表现出高度的功能分工：心肌细胞的线粒体几乎专用于生成 ATP 以维持跳动，而肠道干细胞的线粒体则主要用于合成生物质以支撑快速分裂。 (22:02) 丙酮酸是细胞代谢的核心枢纽，细胞在此决定是将养分运入线粒体氧化生成 ATP，还是将其转化为核酸、脂质和蛋白质等生物质材料。 (33:34)

Dr. Jared Rutter argues that mitochondria act as dynamic decision-making hubs rather than simple cellular powerhouses, balancing whether nutrients are converted into ATP or preserved as building blocks for cellular growth and replication. Dual-Genome Origins and Localized Energy Delivery (8:36) Mitochondria originated through an ancient endosymbiotic event in which an ancestral host engulfed a bacterium, creating the metabolic foundation for all complex eukaryotic life. Unlike other organelles, mitochondria retain a circular, bacterial-like genome located in the cytoplasm that is inherited exclusively from the maternal lineage. This arrangement establishes a dual-genome system requiring precise co-regulation between mitochondrial and nuclear DNA. Mitochondria distribute dynamically across the cell rather than sitting in fixed locations. In neurons with axons up to a meter long, mitochondria travel to nerve terminals to power neurotransmission locally. Similarly, in crawling immune cells, they cluster at the leading edge to deliver adenosine triphosphate (ATP) precisely where physical movement and membrane remodeling take place. Pyruvate Allocation and the Mitochondrial Carrier (33:34) Glycolysis breaks down six-carbon glucose molecules into three-carbon pyruvate, placing cells at a critical metabolic fork. Pyruvate can either enter the mitochondria to be fully oxidized with oxygen into carbon dioxide and high volumes of ATP, or remain in the cytoplasm to be converted into lactate and biomass precursors like lipids, proteins, and nucleic acids. Tissues vary widely in this allocation: continuous-duty heart muscle cells focus on maximal ATP generation, whereas rapidly dividing gut stem cells, which regenerate the intestinal lining every 5 to 7 days, direct carbon into structural materials. Dr. Rutter's lab and independent collaborators identified the mitochondrial pyruvate carrier complex (MPC1 and MPC2) around 2008–2012 by triangulating genetic studies across yeast, fruit flies, and human cells. In mouse models, full knockout of the MPC genes is embryonic lethal at 12 to 13 days of gestation. Selective deletion of the MPC in adult cardiomyocytes does not immediately starve the heart—since it can switch to burning fatty acids—but causes cells to divert glucose into biomass, leading to pathological cardiac hypertrophy and eventual heart failure. Reinterpreting Cancer Metabolism and Evolutionary Resistance (91:32) Cancer cells undergo a metabolic rewiring commonly termed the Warburg effect, where they consume high levels of glucose and reduce mitochondrial oxygen consumption despite ample oxygen. Dr. Rutter clarifies that this does not stem from broken or defective mitochondria, as Otto Warburg originally postulated in the 1920s. Instead, cancer cells purposefully depress mitochondrial oxidation to preserve carbon backbones for rapid biomass accumulation and cell duplication. This heightened glucose consumption is directly exploited by diagnostic tools like FDG-PET imaging. Treating cancer remains uniquely difficult because malignant cells originate from host tissue, meaning therapies targeting stem-like proliferative machinery often cause collateral toxicity in regenerative tissues like hair follicles and the gut lining. Furthermore, intra-tumoral evolutionary pressure means that single-agent interventions eradicating 99.9% of a tumor leave a 0.1% resistant fraction that repopulates the malignancy. To counter this, Dr. Rutter and Huberman advocate for multi-drug combination regimens alongside a classification framework that groups tumors by metabolic and mutational signatures rather than solely by their organ site of origin. Substrate Hierarchies and Excess Energy Toxicity (116:34) Cells enforce strict substrate oxidation hierarchies to prevent acute cellular toxicity. Free fatty acids are burned with priority because an unmanaged accumulation of intracellular lipids rapidly disrupts cellular membrane integrity. Lactate is similarly cleared and oxidized as a vital, mobile fuel source by the heart and brain, contradicting older notions that viewed it merely as an exercise-induced metabolic waste product. When caloric intake chronically overpowers the system, excess energy builds up inside mitochondria before it can be converted into ATP. This overfueled state triggers elevated production of reactive oxygen species (ROS). These unstable oxygen molecules damage cellular proteins, lipids, and both nuclear and mitochondrial DNA, driving genomic mutations, cellular dysfunction, and the biological aging process. A central question moving forward is how to identify and measure precise metabolic intermediates non-invasively at the single-cell level, while exploring whether volatile compounds released through skin or breath can reliably diagnose metabolic alterations before clinical pathology appears.

犹他大学生物化学教授与霍华德·休斯医学研究所研究员Jared Rutter博士指出，线粒体并非单纯的能量生产工厂，而是动态决定细胞资源分配的核心调控枢纽。机体代谢是体内约30万亿个单细胞代谢决策的综合体现，线粒体通过权衡“产能”与“构建生物量”，深层主导着组织功能、衰老进程与肿瘤恶变。 内共生演化与线粒体的亚细胞定位 (8:36) 线粒体起源于远古时期宿主单细胞吞噬自由生活细菌的内共生事件，这一跨物种联盟使得真核生物具备了支持复杂生命形式的高效代谢机制。线粒体在胞质基质中保留了类似细菌的微型环状线粒体DNA（mtDNA），在哺乳动物中严格遵循母系遗传；受精卵仅继承母方的胞质与线粒体，精子只提供细胞核基因组。这种双基因组协调系统决定了线粒体功能依赖核基因与线粒体基因的紧密配合。 同时，线粒体在细胞内并非静态分布，而是根据局部能量需求动态迁移。在长达一米的神经元轴突中，线粒体长途运输至神经末梢以保障神经递质释放所需的ATP供应；在迁移的白细胞中，线粒体高度富集在运动前缘，直接为细胞骨架形变与膜重塑提供动力。近年研究还证实，单个细胞内部可并存功能异质的线粒体亚群，分别特异性负责能量提取或生物量合成。 丙酮酸转运抉择与MPC载体的关键调控 (51:44) 葡萄糖通过糖酵解途径裂解为三碳化合物丙酮酸，构成了细胞代谢的关键分岔路口。细胞必须在此做出功能性抉择：是将丙酮酸转运入线粒体彻底氧化释放大量ATP，还是保留在胞质中合成核酸、脂质与蛋白质等生物量。Jared Rutter实验室与合作者在2008至2012年间，通过酵母、果蝇和人类细胞系的跨物种比对，鉴定了长达数十年未知的线粒体丙酮酸载体（MPC1与MPC2）。该复合物构成了丙酮酸穿透线粒体内膜的专用物理通道。 不同组织的代谢策略截然不同。心肌细胞在成年期几乎不发生细胞更新，依赖线粒体彻底氧化底物以维持终身机械搏动；当小鼠心肌细胞特异性敲除MPC时，细胞无法将葡萄糖衍生丙酮酸导入线粒体，转而将养分错误分流用于制造细胞结构生物量，导致心肌细胞病理性肥大并最终死于心力衰竭。相反，肠道干细胞每5至7天完成一次上皮更新，其代谢网络天然偏向保留糖酵解中间体用于生物量合成与细胞分裂。 底物利用优先级、乳酸角色与能量毒性 (84:29) 细胞在氧化底物的选择上遵循基于急性生存与解毒机制的严格优先级。游离脂肪酸由于过量累积会导致细胞膜受损与急性脂毒性，因而被细胞优先氧化处理；相较之下，长期高血糖虽具慢性危害，但细胞对急性葡萄糖过载的耐受度相对更高。长期被视为代谢废物的乳酸，在现代生化研究中已被确认为关键的循环循环燃料，不仅被心肌细胞等组织高效摄取氧化，有氧运动诱导产生的血液循环乳酸还能穿越屏障刺激大脑合成脑源性神经营养因子（BDNF）。 然而，过度的能量输入会引发严重的“能量毒性”。当食物中提取的化学能超过细胞即时转化为ATP的能力时，过载的能量会使线粒体跨膜电位处于高负荷状态，极易产生大量活性氧（ROS）。过度溢出的ROS会造成核DNA和线粒体DNA突变，破坏蛋白质与核酸构型，成为驱动机体生理衰老与代谢退行性病变的核心分子诱因。 瓦伯格效应真相与肿瘤代谢分类的前景 (91:32) 奥托·瓦伯格于1920年代提出癌细胞即使在氧气充足下也优先进行糖酵解（瓦伯格效应），并推测癌症根源在于线粒体功能受损。Rutter博士阐释现代生物化学推翻了这一论断：肿瘤细胞内的线粒体并未永久损坏，而是通过主动下调氧耗与ATP生成，刻意保存碳骨架以合成支持失控分裂所需的新细胞建材。这一强烈的葡萄糖攫取特征正是临床FDG-PET肿瘤显像的生化基石。 癌症治疗的核心难点在于肿瘤源自机体自身组织，缺乏外来抗原，且极易劫持正常干细胞的增殖通路导致化疗产生强烈脱靶毒性。此外，肿瘤微环境演化极易使残留的0.1%耐药细胞群体死灰复燃。对此，Rutter主张肿瘤分类应摆脱基于解剖器官位置（如乳腺癌、肝癌）的传统框架，转向基于基因突变谱和代谢表型的机制分类；治疗策略应效仿抗HIV的多靶点联合疗法，从多个代谢与信号节点同时切断癌细胞的物质分配通道。 Rutter博士的研究确立了线粒体作为细胞资源分配中枢的理论模型，但如何非侵入性、高分辨率地实时监测人体单细胞亚细胞代谢物状态仍具技术挑战。虽然呼气与皮肤挥发性代谢物检测展示出基于代谢重构的疾病早期筛查潜力，但将针对MPC等代谢靶点的干预安全转化至临床，仍需克服在抑制异常增殖与维持正常组织更新之间的精准权衡难题。

[0:00] Andrew Huberman: the powerhouse of the cell [22:02] Dr. Jared Rutter: change on the fly scenario of biblical proportions [33:34] Andrew Huberman: squeezing lumber arriving at a site—a cell either burns the lumber for heat or uses it as structural material to build a bigger house [83:23] Andrew Huberman: yeast are much smarter than us because they know how to make their own alcohol [112:58] Dr. Jared Rutter: it's one thing if I'm going to measure that, do I have to cut off my arm, shave it into slices, and measure it? Nobody wants that.

[0:00] There's a widely accepted hypothesis [0:03] that mitochondria with excess energy [0:07] leads to problems. Many people that that [0:09] are listening have probably heard of [0:10] reactive oxygen species. This is forms [0:13] of oxygen that become reactive and end [0:14] up spinning out and damaging proteins [0:18] and nucleic acids. And I think it is [0:21] widely accepted that one of the [0:23] contributors to that is mitochondria [0:26] that have too much energy. Basically, [0:28] the form that energy takes when it's [0:30] extracted from the food we eat and [0:32] before it's converted to ATP is powering [0:35] the mitochondria. And when that [0:37] mitochondria is overpowered, that leads [0:40] to a state that is very susceptible to [0:42] generation of these reactive species [0:44] that end up damaging our genome, [0:45] creating mutations and damaging proteins [0:48] and creating many of the problems that [0:50] we see. Welcome to the Hubberman Lab [0:52] podcast, where we discuss science and [0:55] science-based [music] tools for everyday [0:56] life. [1:00] I'm Andrew Huberman and I'm a professor [1:02] of neurobiology and opthalmology at [1:05] Stanford School of Medicine. My guest [1:07] today is Dr. Jared Ruer. Dr. Jared Ruer [1:10] is a professor of biochemistry at [1:12] University of Utah and an investigator [1:14] with the Howard Hughes Medical [1:16] Institute. He is one of the world's top [1:18] experts in the biology of mitochondria [1:20] and metabolism. Mitochondria are known [1:22] as the powerhouse of the cell. But as [1:25] you'll learn today, they do far more [1:27] than just power our cells. They also [1:29] determine how much energy goes into [1:31] making new cells, to making sure that [1:33] cells stay healthy, and to fighting off [1:35] disease. Today's conversation explains [1:37] how mitochondria do that, and clarifies [1:40] what your metabolism really is. And in [1:43] doing so, you will learn that you don't [1:44] have one metabolism. Your metabolism as [1:48] it's called is actually a reflection of [1:49] the constellation of all the metabolisms [1:52] of all the cells in your body. So [1:54] today's conversation will teach you the [1:55] real biology of mitochondria and it will [1:58] provide a framework for you to make [2:00] better decisions on the behalf of your [2:02] health. So what follows is a [2:03] conversation about mitochondria and [2:05] metabolism unlike any that you've heard [2:07] from one of the world's premier experts [2:09] in this topic. Before we begin, I'd like [2:11] to emphasize that this podcast is [2:12] separate from my teaching and research [2:14] roles at Stanford. It is however part of [2:16] my desire and effort to bring zero cost [2:18] to consumer information about science [2:20] and science related tools to the general [2:22] public. In keeping with that theme, [2:23] today's episode does include sponsors. [2:26] And now for my discussion with Dr. Jared [2:28] Ruer. Dr. Jared Ruer, welcome. [2:31] >> Thank you. Thanks for having me on. [2:32] >> I have many questions about metabolism, [2:35] mitochondria, and I know many people do [2:37] as well. Most people hear the word [2:40] metabolism and they think calories in, [2:42] calories out. They hear the word [2:44] mitochondria and they probably think the [2:46] powerhouse of the cell and that's all [2:48] great. People are becoming more educated [2:51] about cells and their bits and pieces [2:53] and what they do. You have a very [2:55] different perspective that is very [2:57] important I believe for people to [2:58] understand. Maybe we could start off by [3:00] talking about how the metabolism of any [3:04] one cell in our body relates to what we [3:08] call our metabolism, the collective [3:09] metabolism of all those cells. And as [3:12] you go, if you could take any liberties [3:14] you want to tell us what we probably [3:16] don't know about the quote unquote [3:18] powerhouses of the cell. [3:19] >> Yeah. You know, when we think about [3:20] metabolism, as you say, I think all of [3:22] us think about metabolism in terms of [3:24] our body's metabolism, our metabolic [3:27] rate, as you say, calories in, calories [3:29] out. What that is really our body's [3:31] metabolism is basically [3:34] the the sum total of what we ingest, you [3:37] know, what we eat, what we drink, what [3:39] we breathe, [3:40] that enters our body and gets processed. [3:44] And the results of that processing are [3:47] individual molecules, amino acids and [3:49] sugars and so forth that then distribute [3:52] throughout the body go into individual [3:55] cells and enter this process that we [3:58] call metabolism and we call cellular [4:00] metabolism. [4:01] And I think it's reasonable to think of [4:04] cellular metabolism as almost like a [4:07] map. There's an entry point. A molecule [4:09] of glucose or sugar comes into a cell [4:12] and that sugar can be chemically [4:14] modified in a variety of ways to fulfill [4:17] the needs of that cell. And then that [4:19] cell does whatever it needs to do with [4:21] the molecules it takes in to fulfill its [4:25] particular functions. And then that [4:27] leads to the um release of waste [4:29] products that we eliminate from our [4:31] body. And that is sort of the organismal [4:34] metabolism, the metabolism of our body. [4:37] And as you allude to, I think something [4:41] that maybe many people don't understand [4:44] is that cellular piece of it. The [4:47] metabolism of our body is really the sum [4:50] total of the metabolism of each one of [4:54] our 30 trillion cells or so. That's [4:56] really where my passions lie are those [4:59] individual cells and how they choose to [5:02] take up certain nutrients, how they [5:05] choose how to process them, turn them [5:07] into other things, how they use them to [5:10] fulfill their particular functions, and [5:12] how that's regulated. the masterful [5:15] coordination of each of those cells [5:19] working together to allow us to be [5:22] sitting here talking to one another and [5:25] go out and run or whatever we do. It's a [5:27] beautiful orchestration, but that [5:30] happens at the level of of individual [5:32] cells. And I think that's one of the [5:33] fascinating things that is maybe a [5:35] little bit less understood. if we were [5:37] to just take the single cell view for a [5:41] moment and I know that aging isn't a [5:43] like your specific area of interest but [5:45] one thing that's always intrigued me [5:47] because my postto adviser once came down [5:49] the hall and said why do I have so much [5:51] less energy than I used to and he had a [5:52] ton of energy so that I like I wonder [5:54] what he used to be like but it's a great [5:56] question he used to do this every once [5:58] in a while like just ask these very [5:59] basic questions that no one else on our [6:01] halls at Stanford could really answer [6:03] why does a kid have so much energy and [6:06] when we're older We don't what people [6:07] say well people are moving less the [6:09] tissues are wearing out but at the level [6:12] of energy production are we aware as [6:15] biologists at this point in history as [6:17] to why a young cell could be muscle cell [6:20] it could be neuron whatever versus an [6:23] older version of that cell why it it [6:27] either produces less energy I don't know [6:29] if it does I'm guessing it might but why [6:31] the whole body just seems to have less [6:33] get up and go do we have an answer for [6:35] Yeah, I think we have a partial answer [6:38] for that. I think that's a that's [6:40] definitely a frontier of science is [6:42] trying to understand exactly what goes [6:44] wrong during aging. There's many aspects [6:46] to it. As you alluded to, one of my [6:48] passions also is the mitochondria. And I [6:51] think it's almost universally the case [6:54] that mitochondria become less energized, [6:57] less effective, let's say, as we age. [7:00] And the reasons for for that are to some [7:03] extent clear but I think largely unclear [7:06] but that is definitely a feature of the [7:09] aging process. You know there there is [7:12] this sort of aspect of accumulation of [7:15] damage. You know living in the world we [7:17] live in as I alluded to before this [7:19] orchestration of metabolism that happens [7:22] throughout the body. That's hard. It's [7:24] expensive. And it's expensive not only [7:26] in terms of what we need to eat to fuel [7:28] it, but it's expensive in terms of the [7:30] damage that can come as a side effect of [7:32] that. And the accumulation of that [7:35] damage over time is certainly correlated [7:38] strongly with aging. And I think there's [7:40] some really nice evidence in models [7:43] where we can do genetics, you know, in [7:45] in animal models that suggests that that [7:47] accumulation of damage is a big part of [7:50] the aging process. And it's a huge area [7:53] of interest in the field is trying to [7:55] understand how you can decrease the [7:58] onset of damage, how you can reverse [8:00] damage that comes. One thing that I like [8:02] about how you ask that question is [8:04] thinking about that in the context of [8:06] the cell, which again I don't think we t [8:08] tend to think of aging as a cellular [8:11] phenomenon, but I think fundamentally it [8:13] almost has to be. We are made up of [8:14] cells and the processes that lead to [8:17] aging are the accumulation of processes [8:19] that happen at the level of individual [8:21] cells. And I think in a way we're at the [8:23] precipice of understanding a lot of this [8:25] because of the tools that we are um [8:27] starting to have access to that will [8:29] help us better understand cause and [8:31] effect and the specific molecular [8:34] features of of the aging process. Let's [8:37] talk about mitochondria. Perhaps [8:38] surprisingly, I'm going to ask you why [8:40] you study them with the caveat that they [8:44] are incredibly interesting. They are [8:46] involved in energy production and [8:47] metabolism. But what what specifically [8:49] drew you to mitochondria versus all the [8:52] other pieces of cells or parts of the [8:55] body or organs that you could have [8:56] worked on? Why the mitochondria? What [8:58] what's so sticky about those as a place [9:00] to I mean you devote a significant [9:02] fraction of your life to them? Yeah, [9:04] it's an area of cell biology, an area of [9:07] sort of the details of how life works. [9:10] One of these things that is, in my view, [9:13] just a brilliant example of taking in [9:18] chemistry of incredible complexity and [9:21] making it work effectively [9:24] inside of a a living cell. Mitochondria [9:27] are believed to have been the result of [9:30] an endo symbiotic event where a [9:32] bacterium a free-living bacterium [9:35] was engulfed by another cell and in a [9:39] way kind of domesticated. [9:42] So wild to think about totally wild. I'm [9:44] sure people are following, but in case [9:45] there's somebody who's not, [9:47] >> what Jared is saying is that our cells [9:50] basically were invaded by a bacterium [9:54] and then that bacterium became part of [9:56] our stable genome going forward. It went [10:00] into the what we call the germ line and [10:01] therefore was propagated from parents to [10:04] kids. And so now mitochondria live in [10:06] us, but they didn't start off living in [10:09] us. [10:09] >> That's right. And I and we hear that [10:11] about the gut microbiome like we have [10:12] these trillions of bacteria that live in [10:14] us and we colonize and we can recolonize [10:15] take antibiotics and then you need to [10:17] replenish eat your yogurt and so on. But [10:19] but the fact that the mitochondria made [10:21] it stably into our genome and are [10:23] transmitted from one generation to the [10:25] next. We think of them as us but you're [10:28] saying there is solid evidence that they [10:30] came from outside of humans. [10:32] >> I think that's the only model that I [10:34] think any of us as scientists have any [10:37] good reason to believe. And you know [10:40] that's fascinating history, right? That [10:43] there was a bacteria and another cell [10:45] that got together and and together that [10:47] combination could do things that that [10:49] any one of either of them on their own [10:52] could not do and that they work together [10:55] in in some way to enable the evolution [10:59] of complex life. you know ukarotes which [11:02] are the the type of cell that resulted [11:04] from that combined situation that we [11:07] were just talking about. These are all [11:09] the organisms that we see around us. [11:12] Plants, animals, fungi even are all the [11:15] result of these two cells getting [11:17] together and making peace so to speak [11:21] and uh teaming up to make this [11:23] synergistic cell. [11:24] >> Is it synergistic? for forgive me for [11:26] interrupting, but when I think about [11:28] viruses, I think viruses have their own [11:30] sort of intelligence. They kind of they [11:32] hijack the genomes of cells and they [11:33] either kill those cells or if they're [11:35] really smart, they keep them those cells [11:37] alive and use those cells to continue to [11:39] live and then propagate through like the [11:41] behavior of an animal like the rabies [11:43] virus like, oh, let's get this animal [11:44] aggressive so that it bites and then I [11:46] mean viruses don't think, but they have [11:48] an intelligence. Do we know that the [11:50] mitochondria were benefiting the cells [11:52] and the cells were benefiting the [11:54] mitochondria or could have this been a [11:56] takeover by the by the mitochondria? [11:58] >> I mean, this is a a bit of a [11:59] philosophical question. Of course, we [12:02] don't have a record of of what exactly [12:04] happened when and who benefited in real [12:06] time, but one thing we do know is all of [12:09] complex life resulted [12:12] from cells that underwent that event. [12:14] One time or multiple times, but all of [12:16] complex life evolved from that. And I [12:19] think that tells us that more than [12:20] likely complex life could not result [12:24] from a bacteria on its own or the archa [12:29] the the the cell that became the host [12:31] for that bacteria. So I think you can [12:35] make a compelling argument that this was [12:37] beneficial. And one reason it was [12:39] beneficial because it enabled a form of [12:41] metabolism that wasn't possible before [12:44] and enabled now a more complex cell to [12:47] be able to do things metabolically to be [12:49] more metabolically efficient and and and [12:52] diversified that it could enable you [12:54] know again complex life to evolve and [12:57] totally fascinating history but I think [13:00] as you alluded to also has very [13:03] interesting implications for life today. [13:06] I would like to take a quick break and [13:08] acknowledge one of our sponsors, JWVE. 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[14:36] I've been doing therapy for a long time, [14:38] and while it's not always easy, every [14:40] time I do a therapy session, I come away [14:43] feeling better and knowing that the time [14:44] was well spent. With BetterHelp, they [14:46] make it extremely easy to find an expert [14:48] therapist who can help provide the [14:50] benefits that come through effective [14:51] therapy. And the data say it works. [14:54] BetterHelp has an average rating of 4.9 [14:56] out of five for its live sessions based [14:58] on over 1.7 million client reviews. [15:01] Also, because BetterHelp is done [15:02] entirely online, it's extremely [15:04] timeefficient. If you would like to try [15:06] BetterHelp, go to [15:07] betterhelp.com/huberman [15:10] to get 10% off your first month. Again, [15:12] that's betterhelp.com/huberman. [15:16] Could we explore a little bit of how [15:19] mitochondria getting into these cells [15:20] were able to make it stably into their [15:22] genome and propagate? This isn't going [15:24] to be a conversation about genetics per [15:26] se, but I maybe as a just two points of [15:29] background for people like if any of our [15:31] cells have something put into them, but [15:33] let's say a physical object like a [15:35] splinter, little tiny piece of splinter [15:37] stays in the cell and then you procreate [15:39] with somebody, you don't expect that [15:40] child will have that little bits of [15:42] splinter in their cells. But if the germ [15:45] line, right, so the the eggs or the [15:47] sperm have something incorporated into [15:49] them, then potentially it could [15:51] propagate is why they call germline as [15:53] opposed to sematic cells. I think most [15:54] people aren't aware of that. It makes [15:55] perfect sense once you hear it, but [15:57] you're talking about many, many, many [15:58] years ago [16:00] >> a cell having this bacterium go into it [16:03] and then it was somehow able to stably [16:06] represent itself in the genome. So that [16:07] that propagated forward and eventually [16:10] >> it has to be in the germ line of [16:11] whatever you know primordial homo [16:15] sapiens were there otherwise [16:18] >> your kids I you wouldn't have [16:19] mitochondria in us how do we think that [16:22] might have happened [16:23] >> the main genome of the cell the cellular [16:26] genome DNA contained typically in the [16:29] nucleus of the cell mitochondria exists [16:32] in the cytool outside the nucleus one of [16:35] the interesting things about [16:36] mitochondria which I think is totally [16:38] fascinating and has really interesting [16:40] disease implications and worthy of [16:43] talking about. We may or may not come [16:44] back to it is that mitochondria have [16:47] their own separate genome that is sort [16:49] of a relic of the bacterium that they [16:53] are the descendants of. It's in a circle [16:55] like the bacterial genomes. Whereas the [16:58] nuclear genome of a ukareotic cell is [17:01] linear chromosomes. And that genome [17:04] performs very essential functions and [17:06] codes very important proteins that [17:09] enable our mitochondria to function as [17:12] the powerhouse of the cell which we uh [17:15] know them to be to enable the extraction [17:17] of usable energy from the food that we [17:19] eat. So, as you alluded to, those [17:22] cytoplasmic mitochondria [17:25] somehow make it from generation to [17:27] generation. And one of the interesting [17:28] features of them being cytoplasmic [17:31] is they're completely inherited from the [17:35] mom, from the egg, cuz as you know, when [17:38] the sperm invades the egg, the the [17:40] genome from the sperm gets into the the [17:42] egg, fertilizes it. The cytoplasm of the [17:45] sperm does not. So the mitochondrial [17:48] genome of you came completely from your [17:51] mother. Mine came completely from my [17:53] mother. And again that has interesting [17:55] implications for the inheritance of uh [17:58] diseases that are mitochondrial on [18:00] origin. But that's sort of how we think [18:03] it works. It basically propagates from [18:05] the egg upon fertilization. Then it gets [18:09] distributed to all the cells including [18:10] the the germ line that that fertilized [18:13] embryo will have and then gets passed on [18:16] to the next generation in [snorts] the [18:18] same way [18:18] >> ratcheting toward the actual functioning [18:21] of mitochondria. Maybe um you give a [18:24] beautiful picture of the mitochondria [18:26] not uh in the nucleus of the cell but in [18:29] the cytoplasm. So still inside the cell [18:31] and most people probably remember from [18:33] their high school biology a picture of a [18:34] cell always looks round. Mhm. [18:36] >> I'm guessing you're going to tell us [18:37] that the mitochondria can be distributed [18:40] lots of places in a cell cuz a lot of [18:42] cells aren't round. A lot of them look [18:43] hairy or they have long extensions like [18:45] neurons. [18:47] Is it fair to say that you can find [18:48] mitochondria everywhere in a cell? So no [18:51] matter what shape it is, it's got [18:52] mitochondria everywhere. And if so, what [18:53] is the importance of having mitochondria [18:56] distributed spatially through the cell? [18:58] So maybe we go so people know where [18:59] we're going. We we'll talk about the [19:00] spatial distribution because it turns [19:02] out that's very important. We'll talk [19:03] about the functioning and then I want to [19:05] talk about time as a factor and that can [19:07] be a little bit abstract for people. So [19:09] we'll come to that. [19:10] >> Yeah. Spatially, [19:12] you know, I I one of my scientist [19:14] colleagues might call me on this but to [19:16] my know I can't think of a place that [19:18] exists in cells where there aren't [19:20] mitochondria. [19:21] And I think as you alluded to I it's a [19:23] little bit dangerous for me to talk [19:25] about neurons with a neuroscientist. I [19:27] am not a neuroscientist but one of the [19:30] brilliant bodies of work that's been [19:32] done on mitochondria has been done in [19:34] neurons. It's fascinating these these [19:37] neurons that have one meter long [19:38] projections and mitochondria [19:42] transit from the cell body down those [19:44] projections and as best we can tell [19:48] those mitochondria play essential roles [19:50] at the ends of those projections [19:52] typically being able to generate again [19:54] usable energy. They're extracting the [19:57] energy from the food that we eat and [20:00] powering the neurotransmission the the [20:03] functions of those nerve nerve [20:04] terminals. And I think that's true of [20:06] virtually every cell in our body. The [20:08] extraction of energy and turning it into [20:10] use a usable form typically in the form [20:12] of ATP adenosine triphosphate. Obviously [20:15] that is the energy currency that's used [20:18] by almost every cell in our body and [20:20] that is a key function of mitochondria. [20:22] We'll probably come to functions of [20:24] mitochondria that are outside of just [20:27] extracting energy, but that is a [20:29] critical function of mitochondria and [20:31] that ATP is needed in virtually every [20:35] place of every cell and by having local [20:39] production that makes it more efficient. [20:41] So I think spatial distribution is a key [20:42] part of that. It's fascinating. There's [20:45] been beautiful work that's shown that [20:48] when a cell is crawling as cells [20:49] sometimes do you know like an immune [20:51] cell that sees something it's chasing [20:55] there will be a distribution of [20:56] mitochondria towards that leading edge [20:59] of the cell which is very energetically [21:02] expensive to crawl for a cell requires a [21:05] lot of ATP and mitochondria will [21:08] congregate at that leading edge where [21:09] that ATP is being consumed to make ATP [21:12] right there so it can be used I think [21:14] it's fascinating example of that local [21:17] uh demand for energy. [21:19] >> I'm asking some highle questions I [21:21] realize, but is there any reason to [21:24] believe that a a given mitochondria [21:26] knows what cell it belongs to? [21:28] >> Like the like are they different? Is is [21:31] are the mitochondria in one cell type so [21:33] very different than the mitochondria in [21:34] another cell type? or the mitochondria [21:36] between like let's say a neuron of the [21:38] eye versus let's get out and since [21:41] you're saying you don't want to talk [21:42] neurons as a per se like is two adjacent [21:45] skin cells they're both skin cells they [21:46] have mitochondria in them but do they [21:48] know which cell they belong to [21:51] >> and do your mitochondria I'm guessing [21:53] because they came from your mom's genome [21:55] they know that they're different than my [21:56] mitochondria but how much identity do [21:59] they have [22:00] >> yeah I would say this is a topic that is [22:02] at the frontier of what we No, you're [22:05] you're asking some questions that are [22:07] right at the edge of our current [22:09] knowledge. Yeah, mitochondria are [22:11] different. To a first approximation, you [22:13] could say that virtually every cell in [22:15] our body has slightly different [22:17] mitochondria [22:18] that are particularly suited to the [22:20] demands of that cell. a heart muscle [22:23] cell, a cardiammyioite, that cell [22:27] kind of has one job and that's to [22:30] contract [22:32] every second of every minute of every [22:34] hour of every day for our entire life. [22:36] And when it coordinates that contraction [22:38] with the other cells in the heart, that [22:40] enables our heart to beat. That's what [22:42] its job is. [22:43] >> Is there any turnover of those cells? We [22:45] know neurons don't tend to turn over. [22:46] >> Very little. Very little. [22:48] >> Well, that's reassuring. [22:48] >> Very very little. I'm glad you [22:51] >> you can imagine that it would be hard to [22:53] replace that in real time, right? That's [22:55] a I'm a hockey fan and that's a change [22:57] on the fly scenario of biblical [23:00] proportions. So that those [23:01] cardiammyioytes, [23:03] >> their mitochondria is wired [23:06] >> to consume whatever it has available and [23:08] make ATP because that ATP is is going to [23:11] be incredibly important to enable that [23:13] contraction of that cell and the beating [23:15] of the heart. mitochondria and other [23:17] cells. For example, like cells that line [23:20] that that are the stem cells that that [23:23] enable our intestinal lining to be [23:27] turned over every 5 to seven days, which [23:30] is amazing. By the way, [23:31] >> your whole gut [23:32] >> your whole gut is turning over every 5 [23:34] to seven days. The the lining of that of [23:36] your gut, it is it is amazing. Those [23:39] stem cells, ATP [23:42] is not the major demand of those of [23:44] those cells. They need to completely [23:47] duplicate themselves constantly every [23:51] day or less. So their metabolic program [23:56] is very different from a cardiammyasite [23:58] which just needs to make ATP to a first [24:01] approximation. They need to make a whole [24:03] new cell. So we talked about you know [24:06] the metabolism of of the organism. The [24:08] metabolism of those cells is very [24:11] complex because it needs to replicate [24:13] all the DNA, duplicate it to go into a [24:16] new cell, duplicate all the proteins, [24:18] duplicate all the membranes, the lipids, [24:21] and that needs to happen rapidly. And so [24:24] that metabolic wiring is is completely [24:27] different. And again, the mitochondria [24:29] are fundamental to that. So those [24:31] mitochondria [24:33] are wired in a way that enable them to [24:36] produce [24:38] the biomass that's required to make a [24:40] new cell quite different from the [24:42] mitochondria of a cardiammyioite. And [24:44] that diff distinction plays out in [24:46] virtually all cells in our body, right? [24:48] Every one of our cells has some [24:50] particular purpose, some particular [24:52] function that it serves uh for the body [24:55] and the demands of the mitochondria [24:57] therefore of that cell are different [25:00] depending on the unique functions and [25:03] demands of that cell. And so it's a [25:05] fascinating topic, this diversification [25:07] of mitochondria. I think again that's [25:09] something that we're learning about. One [25:11] of the developments that's really been [25:13] happening over the last few years, very [25:16] much a frontier field, is you might [25:18] imagine a cell that has a complex set of [25:22] demands. There's actually evidence most [25:24] prominently published recently by Craig [25:26] Thompson at at Sloan Ketering that [25:28] showed that in one cell you can have two [25:31] different kinds of mitochondria that [25:33] have two different functions and they're [25:35] distinct in one cell. [25:37] >> What what's each of them doing? [25:39] >> Yeah. One of them tends to be more [25:40] biosynthetic, maybe producing biomass, [25:43] and one of them tends to be more energy [25:44] extracting and producing ATP. That's a [25:47] an overly simplified but generally [25:49] accurate way of thinking about it. It [25:51] really emphasizes this unique function [25:55] of of mitochondria that can be adapted [25:58] again for the needs of the cell. [25:59] >> Okay. So, I eat some food and uh that [26:02] food's absorbed and I get glucose [26:04] circulating in my bloodstream. I've got [26:05] some stored energy in the form of [26:06] glycogen etc. And I'm curious how greedy [26:10] are the different mitochondria? Is the [26:12] name of the game that every cell is [26:13] trying to get as much energy as it can [26:16] to produce as much ATP as possible or [26:18] are they communicating and is it energy [26:20] being allocated in some way that's a [26:23] little bit more um democratic that's one [26:26] question then framed within that um I [26:28] could imagine two scenarios one non [26:31] mutually exclusive where like the [26:32] vasculature just distributes the glucose [26:34] very well to everything so everybody [26:36] every cell gets gets access to some of [26:38] this glucose and and then is just greed [26:41] needy trying to make as much ATP as [26:43] possible and the whole system works [26:44] beautifully. I could also imagine a [26:46] situation where there's some shuttling [26:48] to important structures like the brain, [26:51] you know, like keeping you alive like [26:52] breathing, heart that there's a [26:54] prioritization of of organs. I'm talking [26:56] about under non-stressful conditions. [26:58] >> So, yes. So, how is energy allocated to [27:00] cells and then how are cells divvying up [27:02] the the goods? Yeah, it's a brilliant [27:05] question and a fascinating area of [27:07] physiology. As you allude to, when we [27:10] eat, our digestive system starts [27:12] extracting the constituents of what we [27:15] eat. Again, sugars, amino acids, fats [27:19] from that food that then triggers [27:21] signals of different kinds, GLP-1 being [27:24] one, insulin being another. Those [27:28] signals then are hormones. They get [27:30] secreted and they go to many cells [27:32] throughout the body and that tells each [27:34] individual cell we just ate. And the [27:38] implications of that are different from [27:40] each cell. Some cells don't care. Some [27:42] cells don't pay attention to that and [27:43] they just keep on doing what they were [27:45] doing. Some cells care a lot. Aipocites [27:48] for example, these are the fat cells, [27:50] the cells that make up our fat tissue. [27:53] They care a great deal about that. And [27:55] when they see insulin, what they do is [27:59] they turn on a protein. They start [28:01] making a protein that will cause glucose [28:04] to be taken up into that adiposite, that [28:08] fat cell. And that glucose will then be [28:11] converted through a series of chemical [28:12] reactions into a fat molecule. And then [28:15] that fat molecule will be stored away in [28:18] a way that is very safe and enabled to [28:21] be stored for potentially a very long [28:23] time. [28:25] And again, it's a beautiful way for the [28:27] organism to coordinate. [28:30] I just ate our energy status as an [28:34] organism, as a body is great. It's very [28:37] good. So let's squirrel away some of [28:40] that energy in the form of fat that can [28:45] be stored in our adiposytes again very [28:47] safely and can be then used when we go [28:50] through a period of prolonged fasting [28:52] which doesn't happen for us all that [28:55] frequently but happened for our [28:56] ancestors probably much more frequently [28:58] and those atyposites full of fat from [29:01] when we ate probably kept our ancestors [29:04] alive when they went through the periods [29:06] of prolonged fasting. [29:08] Insulin has other effects on muscle and [29:10] and other cells throughout the body that [29:12] again this is the brilliance of this [29:15] coordination. The response of different [29:18] cells to the fed state is different [29:20] depending on the the the needs and and [29:23] functions of that cell. Again, some [29:25] cells don't care at all. They're going [29:26] to just go about and do their business. [29:28] And some cells completely rewire their [29:31] function depending on the the metabolic [29:35] state the fed fasted state of the [29:37] organism. So the picture you just [29:39] described leads me to conclude that [29:43] basically every cell obviously knows its [29:46] job and is not greedily but is um [29:49] diligently fulfilling that role. [29:51] >> Yeah. And somehow the whole thing is [29:54] orchestrated so that like we work which [29:57] I know I think for some people it might [29:58] be like duh but like just like think [30:01] about that crazy [30:02] >> like a liver cell isn't really talking [30:03] to the brain cell in any kind of direct [30:05] way about how much glucose it has access [30:07] to. What you describe makes me really [30:10] understand for the first time the [30:11] brilliance of having this hormone signal [30:13] insulin not just as a shuttle because I [30:15] think most people we think like insulin [30:17] sensit most people listen to this [30:18] podcast or just existed in the world [30:20] today they're like oh you want to be [30:21] insulin sensitive you want your cells to [30:23] recognize this signal but we've never [30:25] actually talked on this podcast about [30:26] what exactly that signal is we think [30:28] about insulin as a shuttle [30:30] >> but the size of that signal is saying [30:33] what's likely to be there and I realize [30:36] has all sorts of cool implications that [30:38] can prepare the cell to like oh I'm [30:39] going to go to work hard now to be the [30:41] little squirrel that I am of a fat cell [30:43] and like squirrel away as much as I can [30:44] or be a brain cells like let's go [30:46] >> I'm ready to fire action potentials if I [30:49] need to and some cells like the photo [30:50] receptors in the eye are just doing that [30:52] >> eyes closed they're firing eyes open [30:54] well it's tricky but they're more or [30:56] less firing it's a not worth going into [30:58] obviously but in every one of these [31:00] cells mitochondria are the ones that are [31:02] essentially going to drive this ATP [31:04] >> thing right and that seems extremely [31:08] efficient, too, to just have essentially [31:10] one major cellular energy source. So, if [31:13] you could walk us through what happens [31:15] as glucose gets into the cell and and [31:17] and really what we've not done ever on [31:19] this podcast and I I don't think I've [31:21] heard elsewhere on any podcasts, [31:23] >> maybe it's out there, but is how you go [31:27] from ATP to actually the cell being able [31:29] to perform its roles. Yeah. [31:31] >> And I realize there's a lot of [31:32] biochemistry there, but you've worked on [31:34] some really lynchpin molecules in that [31:37] pathway that perform very specific [31:40] roles. And so like maybe we could really [31:41] talk about basically gets us from ATP to [31:44] pyuvate, which might scare some people [31:46] away, but you'll you'll educate us as to [31:48] why it's not scary. It's just super cool [31:50] and why it's so important to have these [31:52] signals that that aren't just like [31:53] chemicals. They actually mean something [31:55] for the cell. Cuz for me, forgive me for [31:57] going a little long here, but then I'll [31:58] shut up. I think if people can really [32:00] internalize this idea that yeah, like [32:02] hormones go up, hormones go down. [32:03] Cortisol goes up with stress, it goes [32:04] down. You wake up, cortisol goes up. [32:06] Melatonin when you're sleepy. It's not [32:09] just that it's there, but that the size [32:11] of the signal says a lot more than just [32:16] be sleepy. It's saying what once [32:18] happened is different than what's [32:19] happening now. It sets a stage for what [32:21] happens next. And this is really like [32:23] the verbs of biology that are harder to [32:26] communicate even in video. Yeah. [32:28] >> So, take us from glucose to ATP and ATP [32:32] to this thing that we call energy. [32:34] >> Yeah, there's a obviously a lot to [32:36] unpack there. Glucose is the dominant, [32:40] let's say, carbohydrate, the dominant [32:42] sugar that most our cells are consuming. [32:45] And when glucose is brought into a cell, [32:47] it goes through again a series of [32:48] chemical reactions that we call [32:50] glycolysis. [32:52] And I I'm going to simplify because [32:54] there's obviously this is the subway map [32:56] of New York. There's a lot of branches [32:58] going all over the place that we're [32:59] going to [33:01] >> go north or south. [33:02] >> North and south, [33:03] >> which is pretty much the only direction [33:04] you can go on the cell. I'm I'm not a [33:05] New Yorker. I'm kidding. I realize you [33:06] can go across across the aisle. [33:08] >> Yeah. Don't insult the New Yorkers [33:09] anymore. Yeah. [33:10] >> So glucose [33:12] comes into a cell, goes through a series [33:14] of chemical reactions, and you mentioned [33:16] it gets to pyrovate. That's the end [33:18] point of glycolysis, this set of [33:20] chemical reactions. And then pyrovate [33:23] there's a decision that has to be made [33:24] by that cell. It can either [33:29] take that pyrovate into the mitochondria [33:31] and burn it essentially [33:34] oxidize it which is essentially burning [33:36] it combining it with oxygen and that is [33:38] a very effective way to extract all the [33:41] energy that can be extracted from that [33:44] glucose via pyrovate. [33:46] >> Tell us a little bit about pyrovate. [33:48] Yeah. What's the best way to like [33:50] conceptualize pyuvate for for somebody [33:52] like me? [33:53] >> It's an intermediate. It's a midpoint [33:56] let's say from glucose. Glucose is a [33:58] sixcarbon molecule complex chemical [34:01] sixcarbon chemical that gets again [34:04] chemically modified down to this [34:06] pyrovate which is as I alluded to in a [34:09] way kind of a pivot point [34:12] >> in the metabolism of that glucose. And [34:15] the reason why we became really [34:17] fascinated with pyrovate [34:19] is because of that bifurcation that [34:22] happens. Pyrovate can either be again [34:25] taken into mitochondria and burned and [34:27] that's very effective for generating ATP [34:29] for extracting all the energy that can [34:31] be extracted and that's what [34:33] cardiammyioytes for example really love [34:35] to do take that everything they can from [34:39] the circulation burn it make ATP keep [34:42] our heart pumping and again other cells [34:45] on the other hand don't do that they [34:47] don't need as much ATP so those [34:49] intestinal stem cells that I talked [34:51] about that are the factory in a Okay, [34:53] that's enabling the repopulation of our [34:55] gut lining every week. They do something [34:59] different with that pyrovate. They [35:01] instead of burning it turn that pyrovate [35:04] and other molecules intermediates in [35:06] glycolysis into biomass into the stuff [35:10] that will enable that one cell to [35:11] duplicate itself. And I've become [35:14] totally fascinated with this [35:17] bifurcation. [35:19] Food can either be converted to energy [35:23] or it can be converted to biomass. I [35:26] think that's maybe a bit overly [35:27] simplistic, but I think a good baseline [35:30] way to think about the what we get out [35:34] of the food that we eat. [35:36] Energy or building blocks that can be [35:40] used to make a new cell to repair a cell [35:43] that's been damaged for a B cell and [35:45] immune cell that are the ones that make [35:47] antibodies. making a bunch of [35:49] antibodies, which an activated B cell [35:51] needs to do. That's a lot of stuff that [35:53] needs to be made. That requires that B [35:55] cell to have a lot of amino acids that [35:57] can be turned into proteins, which are [35:59] antibodies are proteins. And and and [36:02] that again, that's a very important part [36:04] of our immune system that keeps us [36:05] protected from invaders that might [36:07] otherwise kill us. And so that that [36:10] distinction that lands at the point of [36:12] pyrovate I think is a is a super [36:14] fascinating pivot point in metabolism [36:17] that I think many of us are fascinated [36:19] by exactly how the cell [36:22] >> organizes itself to make the right [36:25] resource allocation decisions. You know [36:27] every one of our cells is all every [36:30] second of every day is making resource [36:32] allocation decisions. What does it do [36:35] with the stuff that it has? And and this [36:38] is one that I think is really [36:40] fascinating. [36:41] >> So we are probably like seven I'm [36:43] insulting the cell biologists but [36:45] probably seven steps away from sandwich. [36:47] So sandwich goes in the mouth into the [36:50] gut gets absorbed right we get glucose. [36:52] Glucose gets into the cell. We got some [36:55] important biochemistry that you know is [36:57] in this uh ATP generation pathway and we [36:59] get to this like key node that you're [37:01] describing as pyuvate and pyuvate is [37:04] either going to say let's make more you [37:06] called it biomass but stuff of cells. [37:08] >> Yeah. [37:09] >> So we're like you have lumber arriving [37:11] maybe might be a decent enough analogy. [37:13] You're either going to use it to build [37:14] more house or you're going to burn it [37:16] >> for heat energy. [37:18] >> Great analogy. Um, and let's look make a [37:21] add a condition where you need to burn [37:23] some of that lumber for heat energy to [37:25] keep the construction project going. [37:26] >> Exactly. [37:27] >> Okay. So, we're at this key bifurcation, [37:29] this key split point. Is it just as [37:31] metabolically demanding for a cell to [37:36] use pyuvate to keep itself going like a [37:39] cardomyioite versus making biomass or is [37:41] one more costly? I'm thinking again as [37:44] you beautifully pointed out at the [37:45] beginning about thinking about that our [37:47] metabolism as a whole body as a person [37:50] is is the sum total of all these these [37:52] things is it equivalent in terms of like [37:56] >> how much sandwich relatively speaking is [37:58] going into maintaining us and rebuilding [38:00] us what you call biomass what I'm [38:02] calling building you know allocating [38:04] lumber for the for the house itself [38:06] >> versus to uh fuel the fire so to speak [38:09] >> that's hard math to do there's a lot of [38:11] nuance rough percentages. I won't hold [38:13] you to it. [38:14] >> Yeah. No, I mean one way to think about [38:16] that, many of us are probably [38:17] unfortunately aware of PET imaging, [38:20] right? This is this is something that [38:21] happens that's often used to diagnose [38:23] cancer [38:25] emission tomography. [38:26] >> An FDG PET, which is the most common [38:28] form of PET, is basically you're giving [38:31] cells a form of glucose that can then be [38:33] visualized with this PET scan that many [38:37] people are aware of. And the reason we [38:39] do that is because tumors [38:43] take up a lot of glucose and FDG PET is [38:46] fluoroxy glucose. This is a a labeled [38:48] version of glucose. So the reason we do [38:51] FDG PET is to see the cells where in the [38:54] body is taking up a lot of glucose and [38:57] tumors take up a lot of glucose. So FDG [39:01] PET is used to diagnose cancer [39:05] frequently very effectively. So that is [39:07] one metric for this. A cancer cell is [39:10] again a cell that is making a resource [39:13] allocation decision all the time. But in [39:15] the context of of that cell when it [39:18] transforms into a cancer cell that [39:20] resource allocation becomes very much [39:22] about building more cells. That's why a [39:25] tumor is a tumor is because that one [39:28] cell that was the first bad actor [39:31] decided instead of doing the thing it [39:33] was supposed to be doing decided to [39:34] duplicate itself and duplicate itself [39:37] again and build a cluster of cells that [39:40] then become a tumor. [39:41] >> Okay. I have a pseudo philosophical [39:44] question but it's really a scientific [39:46] medical question about tumors. Bacteria [39:49] have the opportunity to hijack genomes [39:51] of cells. viruses certainly probably the [39:54] the easiest example for people to [39:55] understand is like a herpes virus like [39:58] HSV1 or something which lives on neurons [40:01] >> doesn't kill the neuron which is [40:03] convenient for the virus [40:04] >> right because if it killed the neuron it [40:06] too would die because if the neuron is [40:08] expressing that virus it's hijacked the [40:11] genome [40:11] >> so this earlier I was saying like [40:13] viruses have their own quote unquote [40:15] intelligence [40:16] >> like stay alive but keep the host alive [40:18] too and transmit and in the case of [40:21] rabies it's the most easiest one to [40:23] conceptualize like impact areas of the [40:25] brain that trigger aggression would that [40:27] trigger [40:27] >> right [40:28] >> biting and and people have speculated [40:30] like does the virus know that it's doing [40:31] this like probably not right doesn't [40:33] they're not brains but pretty impressive [40:35] level of quote unquote [40:37] >> uh adaptive behavior and intelligence [40:41] >> I think of cancer as just a bad thing [40:43] all around right that these cells are [40:45] greedy they're taking glucose they're [40:47] making more of themselves it's cell [40:49] turnover gone arry tumor gets big, it [40:52] starts to encroach on other tissues, [40:54] metastasize, boom, you kill the host. [40:56] >> That's not a great strategy from the [40:58] perspective of the tumor. So, it [41:00] obviously isn't thinking about its [41:01] long-term outcome in any kind of [41:03] adaptive way. [41:04] >> But has anyone ever looked at tumors in [41:06] the same way that we think about [41:07] viruses? Like the logic there is the [41:09] same. [41:10] >> Yeah. [41:10] >> Except it it seems that their goal is to [41:12] kill the organism. I'm not trying to [41:14] anthropomorphize about cells and [41:17] cellular processes, but I think [41:20] is there a a potential set of answers [41:22] about how to deal with tumors and and [41:25] think about cancer that could be [41:26] borrowed from any of those other [41:27] examples or am I or am I going down the [41:29] wrong path? [41:30] >> Yeah, it's an it's an interesting [41:31] question. You know, viruses and [41:32] bacteria, similar to how you were [41:35] describing viruses, some of the same [41:37] principles apply to bacteria in you [41:39] know, parasitic bacteria. Viruses, as [41:42] you allude to, their goal that, you [41:45] know, if you do want to anthropomorphize [41:47] them, their goal is to propagate, right? [41:51] They are under evolutionary pressure. [41:53] The way that that virus survives is to [41:55] make more of itself, go infect another [41:58] organism and have that other organism [42:00] make a bunch of additional viruses that [42:02] will then go and infect another [42:03] organism, right? That is the [42:04] evolutionary game [42:06] >> and that's what viruses do. And they're [42:08] very good at it. And you described some [42:09] really interesting biology where viruses [42:11] will actually affect the behavior of the [42:14] host to make them better at getting into [42:16] the next host. It's amazing. [42:19] >> I wish we had a better language for this [42:20] thing because intelligence is not really [42:22] it because it's not of brains, [42:24] >> but it's this adaptive logic. [42:26] >> Yeah, that's a good uh phrase for it, [42:28] adaptive logic that enables the survival [42:31] and propagation of that virus. And and [42:33] this is how evolution works, of course. [42:36] If that virus had a mutation that made [42:40] it better able to do that, that virus [42:42] then would infect better [42:45] >> and it would get into hosts better, [42:47] propagate better, and it would [42:49] eventually take over the population of [42:51] that virus. That is the process of [42:53] evolution. And I think again it makes [42:55] intuitive sense. You know, you asked [42:57] about cancer. Cancer is obviously [42:59] fundamentally different in one key way. [43:02] If I get a virus and I come in here and [43:04] we're sitting across the table and I'm [43:05] hacking and whatever and I spew across [43:08] the table at you, you might get the [43:10] virus, [43:11] >> get sick, build a bunch of additional [43:13] virus, and then you give it to [43:14] co-workers and that's viral propagation, [43:17] which we all sadly know about. There's [43:20] very little evidence that cancer is [43:22] infectious. [43:23] >> What about Tasmanian devils? [43:25] >> You know about this, right? [43:26] >> No, I don't know about this. [43:27] >> Okay, I don't know if this held up, but [43:28] there was this idea for a while. Someone [43:29] will tell us in the comments. This is [43:31] what's fun about doing this on the [43:32] internet. [43:32] >> That Tasmanian devils fight and that [43:35] there's wound induced propagation of [43:37] cancers. These very disturbing as an [43:40] animal lover, you know, very disturbing [43:41] images of these cute little animals with [43:44] these little teeth. They're they have a [43:46] viciousness to them and they have these [43:47] like tumors growing at the at wound [43:49] sites and it turns out those are cancer. [43:51] So there's somehow like [43:54] >> fighting and wounds and viral, it might [43:57] it might be bacterial. I don't know. [43:59] That's outside my expertise, [44:00] >> but there was this idea that you that [44:02] they could transmit cancers to one [44:03] another through fighting. [44:05] >> Interesting. [44:05] >> Which I thought was sad but fascinating [44:08] nonetheless. And Australia is a weird [44:10] place, you know. [44:11] >> A lot of stuff happens. [44:13] >> I mean, the world's upside down there, [44:14] so after all. No. Um but but right, [44:16] you're right. In general, yeah, we don't [44:18] actually think that um people are [44:20] catching cancers from one another. [44:22] >> So when you think about the evolution of [44:23] a cancer, the scope of that evolution is [44:26] different, right? The scope of that [44:28] evolution of a a cell in me [44:31] >> is limited to me. [44:33] >> Cancer cells undergo evolution in the [44:36] exact same way. You know, if one cell in [44:38] my body starts propagating, it acquires [44:40] a mutation that enables it to divide and [44:43] divide faster and maybe it, you know, [44:47] get out from underneath the limits that [44:49] are being placed upon it by the immune [44:51] system and by other systems that control [44:54] propagation of cells in the body. It can [44:56] then divide and divide again. And that's [44:59] basically the continuous process of [45:01] cancer development is the acquisition of [45:03] mutations that make that cell better [45:06] able to evade the immune system, to [45:09] duplicate itself, evade um the the [45:13] problems that would come with DNA [45:14] damage, which many cancers have, and to [45:17] continue to make it make cells that [45:19] survive. And that is in a way an [45:21] evolutionary process playing out at the [45:23] level of individual cells. But how that [45:27] interacts with the host is obviously [45:29] different because again a virus has this [45:34] sort of evolutionary drive to get from [45:36] one organism to to another to another to [45:39] enable its propagation. [45:42] Cancer you isn't fueled by the same [45:45] motivations let's say because again as [45:48] far as we're aware that very rarely if [45:50] almost never happens to get from one [45:52] organism to another. And so the [45:55] motivations are different, but the [45:56] evolutionary process underlying it, it's [45:59] the same principles at play in both. [46:02] >> I'd like to take a quick break and [46:03] acknowledge our sponsor, AG1. AG1 just [46:06] launched their newest formulation called [46:08] AG1 Pro. And right now, you can get an [46:11] extra 20% off your first subscription. [46:13] AG1 takes the clinically backed AG1 [46:16] formula, which is a blend of vitamins, [46:18] minerals, probiotics, and adaptogens, [46:20] and adds three important new [46:21] ingredients. Creatine monohydrate, [46:23] calcium HMBB, and zinc carnosine. It has [46:26] 5 g of creatine monohydrate to support [46:28] muscle strength and performance along [46:30] with brain health, calcium HMBB to [46:32] support muscle recovery and reduce [46:34] muscle breakdown, and zinc carnosine to [46:36] support and improve the lining of your [46:38] gut. 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[48:04] It has so many incredible features. For [48:06] instance, the Pod 5 has a feature called [48:08] autopilot, which is an AI engine that [48:10] learns your sleep patterns and then [48:12] adjusts the temperature of your sleeping [48:13] environment across different sleep [48:15] stages. It'll even elevate your head if [48:17] you're snoring, and it makes other [48:18] shifts to optimize your sleep. If you'd [48:20] like to try eight, go to [48:22] eight.com/huberman [48:24] to get up to $350 off the new Pod 5. [48:27] Eightlee ships to many countries [48:28] worldwide including Mexico and the UAE. [48:31] Again, that's eight.com/huberman [48:34] to save up to $350. I'll take us down [48:37] one more estuary, then we are actually [48:38] going to talk about mitochondria and [48:40] pyuvate again and your contributions to [48:42] this critical node of where pyuvate puts [48:46] its efforts building more stuff of the [48:48] cell or using energy. Anytime I have a [48:50] serious cell biologist, which isn't that [48:52] often on this podcast, or somebody who [48:54] thinks about the pieces that make up us, [48:58] I try and ask this. I'm bothered by this [49:01] one thing I heard once, which is that [49:04] like it's so easy to think about [49:05] evolution. It's like, okay, we're all [49:07] adaptively trying to make more of [49:08] ourselves, care for our young, and go [49:10] forward. That's like what every spe [49:11] every you know, mamalian species does. [49:14] That all makes sense until I learned [49:16] about the gut microbiome from my [49:18] colleague Justin Sonnenberg and he said [49:21] you know every time you shake hands like [49:22] we exchange microbiome today [49:24] >> and we're sharing in the air and skin we [49:26] shook hands you see and like there is [49:29] this one model of like all of this [49:32] that's very purely biological that we [49:35] are just shuttles for the microbiota [49:37] >> and everything that we're doing like [49:40] building electric cars and uh holding uh [49:43] debates and protests and um sending kids [49:46] to school and all of that we think is [49:48] about us but the microbiota are just [49:50] like they've hijacked this process and [49:53] like they're not sitting there going [49:55] these [laughter] humans they think this [49:56] is all about them and we're just trying [49:58] to spread and make sure that we continue [50:00] and maybe long after they're gone we're [50:01] just going to keep going and I can't [50:03] poke any holes in this it's like too [50:05] good a theory but I keep hoping [50:06] somebody's going to tell me at least [50:08] from a purely biological perspective [50:10] that like that's not true but it kind of [50:12] scares me every once in a while I think [50:14] Maybe I'm just a bunch of micro biota [50:17] shuttle just the vehicle. [50:18] >> We're just a shuttle. But we got this [50:20] brain which is very convenient for them, [50:22] right? Because it makes me want to go [50:23] out and do things and I think about [50:25] failures and successes and how I want to [50:27] do better and what I want to do at [50:28] different stages and like maybe it's [50:29] just all about them getting as far and [50:31] wide as they can. [50:33] >> Well, unfortunately, Andrew, I'm not [50:34] sure I'm going to be able to provide you [50:36] the concrete proof that that's not true. [50:37] It's a it's a fascinating [50:39] >> kind of eerie, right? [50:40] >> Yeah, very eerie. We definitely don't [50:43] like to see think of ourselves as [50:44] anything other than the pinnacle of [50:46] evolution and the reason for everything, [50:47] >> right? [50:48] >> But there's no question to to your [50:50] point, the microbiome are the bacteria [50:53] that live in our gut and on our skin, [50:56] they're being driven by the same [50:58] evolutionary pressures that we've been [51:00] talking about for viruses and for us. [51:03] They're trying to propagate themselves [51:06] and fill the niche that they live in, [51:08] fill the little chunk of of the universe [51:11] that they live in and do it better than [51:14] their com their competing neighbors. And [51:17] if they can do that, then their genome [51:19] is going to get passed on and again and [51:22] again. And it's fascinating to think [51:23] about the role that we play for them and [51:26] they play for us. This is a phenomenon [51:28] that's been known for a long time, but I [51:30] think the implications of the microbiome [51:31] is something that really has only been, [51:35] I think, experimentally dealt with in a [51:37] really serious way in the recent decade [51:39] or so. And I think we're still learning [51:41] about the implications, but there's no [51:42] question that they're big. Tell us about [51:45] MPC 1 and 2. I'm asking about [51:47] biochemical steps and a key process of [51:50] energy production and and allocation. [51:52] And normally when people hear acronyms, [51:54] they don't understand. and they kind oh [51:55] my goodness like what are we doing here? [51:57] But like [51:59] I think it's so important that people [52:00] understand like this business of us this [52:03] metabolism having energy whether we're [52:05] young or old have a lot of it or less of [52:07] it healthy or dealing with cancer like [52:10] this is a key node and what I want to [52:12] know truly is how do you actually [52:15] discover something like this because and [52:17] this is where I think we we can really [52:19] illustrate the scientific process in a [52:21] way that like most people just don't [52:23] understand. You need cells first of all. [52:25] You need to be able to find the mic [52:27] mitochondria. You need to be able to [52:29] know what's ATP and what's pyuvate. And [52:31] then you know they're going to two [52:33] different pathways cuz someone else said [52:34] that and you can observe it down a [52:35] microscope. [52:36] >> Yeah. [52:37] >> But then how do you find this thing and [52:39] then tell us what it's doing perhaps or [52:41] tell us what it's doing. But I think it [52:43] would be very useful for people to get a [52:44] picture of how this is done because we [52:46] hear this stuff like oh this molecule MC [52:49] and people go oh is there a peptide for [52:50] that? It's like hold off. Let's think [52:53] about how we come to understand these [52:55] these essential aspects of oursel I [52:57] think would be so useful. [52:58] >> I appreciate you asking about that. It [53:00] allows me to reminisce a little bit [53:02] about the process of discovering that [53:04] which was you know a fun time in my [53:06] career and was fueled by the brilliant [53:08] people in the lab that did it. So MPC [53:11] this is a case where the acronym [53:13] actually makes sense. It's the [53:14] mitochondrial pyrovate carrier. So you [53:17] don't have to be a scientist. [53:19] >> Uh we did not name it. that was it was [53:20] named before. I'll I'll tell you that [53:22] one story cuz I don't like acronyms that [53:24] aren't informative. [53:25] >> MPC, [53:27] >> aptly named [53:28] >> is the carrier [53:30] >> that enables pyrovate to get into the [53:32] mitochondria. Mitochondrial pyrovate [53:34] carrier. That's what it does. Sits in [53:36] the mitochondria and basically provides [53:38] a very specific hole in the membrane to [53:41] enable pyrovate to get in so that it can [53:44] then be burned by the mitochondria to [53:46] again extract all the energy to make [53:48] ATP. That's that's basically what it [53:50] does. The history of this is really [53:52] interesting. It's been known for [53:55] 60 or 70 years that mitochondria must [53:58] have a carrier to enable pyrovate to get [54:01] in. But it was not identified what that [54:05] protein was, how it worked. [54:08] And [54:09] fast forward to 2008 or nine or so, and [54:13] our laboratory had just recently become [54:15] again fascinated with mitochondria. I [54:18] would say the motivating piece of of [54:21] information that convinced us to start [54:23] working on mitochondria was the [54:26] realization that many of the proteins [54:30] that make up mitochondria that do the [54:33] stuff that mitochondria do we don't know [54:35] what their functions are and that [54:37] suggested that this organel powerhouse [54:40] of the cell we kind of I at least felt [54:43] like we knew a lot about what [54:44] mitochondria do there's mysteries there [54:47] that we don't have answers for. And so [54:50] we started just taking some of these [54:52] proteins that we know are in [54:54] mitochondria, we don't know what they [54:55] do, and trying to figure out what they [54:57] do. And two of those turned out to be [55:00] MPC1 and MPC2. Way back when I I [55:04] observed and was taught, I didn't do a [55:06] ton of this, that like if you want to [55:07] figure out what proteins are in a cell, [55:09] you get a bunch of those cells, which [55:11] you can do [55:12] >> and then you [55:13] >> you kind of grind them up and then you [55:15] run them through a bunch of columns and [55:17] like literally tubes. [55:18] >> Yeah. [55:19] >> And those tubes have filters that either [55:21] let big, less big, small, or very small [55:24] things through, what we call [55:25] fractionation, right? And then you kind [55:27] of test the the different stuff that [55:30] comes through for its ability to do [55:32] something in some sort of cell. It's [55:33] like how did you actually find MPC2? Was [55:36] it done by like [55:38] >> sort of hardcore what we call hardcore [55:39] biochemical purification? That was kind [55:41] of the old way of doing it. Or well, let [55:44] me ask this. Do we know the total number [55:47] >> of proteins in the in a given human [55:50] heart cell? [55:52] >> I think we know. Yeah, I think [55:53] >> we know everything that's in a heart [55:55] cell. I think we know all the proteins [55:56] in a heart cell. Again, you can get into [55:59] the nuances of slightly modified [56:00] versions, but we know the proteins [56:02] because they are encoded by our genome, [56:04] right? We know the human genome that's [56:06] been sequenced. We know what that is, [56:08] >> but we don't know that everything that's [56:10] expressed in a given cell. That's right. [56:11] >> That that's true. And there there are [56:13] some very interesting features there. [56:14] >> Can I sorry, I'm interrupting on [56:16] purpose. 20 years ago, could you say [56:18] what you just said [56:19] >> with much less confidence that I than I [56:21] can now? say heart cell, but we don't [56:23] actually know all the all the bits in [56:25] it. But now we do. [56:26] >> Now I think we we know [56:29] >> essentially everything. Again, there's [56:30] going to be subtle nuances that we don't [56:32] know, but I think we know almost [56:33] everything. [56:34] >> That's good. [56:35] >> Doesn't mean we know what all those [56:36] things do. And that's maybe the frontier [56:38] for the biochemistry frontier for the [56:41] next generation of scientists to to [56:43] figure out. We don't know what they all [56:45] do, but we know more or less what they [56:47] all are. knowing what they are but not [56:50] knowing what they do motivated us to go [56:53] take these two proteins that were in the [56:55] mitochondria. [56:57] We could make a very strong hypothesis [56:59] that they were important because they [57:02] were in every cell that has mitochondria [57:05] down to a yeast that's a single-sellled [57:07] organism and plants and animals. [57:12] Everything that has a mitochondria has [57:14] these two NPC1 and NPC2 proteins. And it [57:18] would probably uh take too long to [57:21] explain on this podcast this the [57:23] processes that we went through to try to [57:26] identify the function of this MPC 1 and [57:29] 2, but this was a a brilliant [57:31] collaboration and I think one of the the [57:34] highlights of my career. [57:36] different people in my lab and in the [57:38] lab of my colleague Carl Thumbl that [57:40] worked together. Carl was a fly [57:43] geneticist or is a fly geneticist that [57:46] used his unique skills and and resources [57:49] and we were using yeast as a model [57:51] system as well as human cells and [57:54] triangulating all that data. We came up [57:56] with data that suggested that this might [57:59] be the mitochondrial pyrovate carrier. [58:01] these two unknown proteins that happened [58:03] to be sitting in the mitochondria and [58:05] that was now been validated many times [58:08] over that these are the proteins that do [58:10] this transport of pyrovate into the [58:12] mitochondria. It was a really fun time [58:15] for me as a scientist to to see that [58:18] happen. And you know, you kind of [58:21] alluded to this when you asked the [58:22] question, what was maybe even more [58:25] exciting than the discovery of the [58:27] mitochondrial pyrovate carrier, which [58:29] Carl and I did, and we published a paper [58:31] and the lab of JeanClaude Martin and [58:33] Geneva published a paper at the same [58:35] time showing the same discovery. What's [58:38] been really fun since then is to see the [58:41] implications of that and starting again [58:43] to understand what role this protein [58:46] plays in the allocation of that pyrovate [58:49] that we've been talking about because [58:51] now the MPC [58:54] is the first step towards one [58:59] destination of that pyrovate. So it kind [59:02] of pulls it into the mitochondria so to [59:04] speak and once that pyrovate is in the [59:06] mitochondria it's going to be used for [59:08] something in the mitochondria instead of [59:10] maybe being used for something else in [59:12] the cytool. And so that's been work that [59:15] that we've done a lot of since is what [59:17] are the implications of that. And I [59:19] think it's been exciting to see in [59:22] different cell types what that means. [59:25] And so cardiamyiotes for example again [59:27] these are cells that want to make ATP to [59:30] to allow cardiumes to continue to [59:33] contract. They need to extract every bit [59:35] of energy they can make as much ATP as [59:38] they can. They use this MPC extensively. [59:42] How do they ensure that that these [59:44] cardiammyioites make sure that they make [59:47] just enough to maintain themselves so [59:49] they they're not so busy burning up all [59:51] the lumber that they end up going, "Oh [59:53] my goodness," and the house fell apart. [59:55] >> Yeah. [59:55] >> Do they consistently devote 90% of of [59:57] their ATP to energy utilization and that [60:00] they just know 10%. Like how [60:02] quantitative are these these these [60:04] pathways? [60:05] >> Because you can't you can't have the [60:06] walls fall down. It doesn't matter how [60:08] much energy you produce, right? It's a [60:09] brilliant question and and it's [60:12] definitely not programmed like like [60:14] there's a a spigot with a diverter valve [60:16] that 90% goes this way and 10% goes that [60:19] way. What actually happens and this [60:21] doesn't just happen in cardiammyioytes [60:23] it happens in every cell is that [60:26] basically the cell is measuring the [60:29] outputs again to anthropomorphize and I [60:31] have to say there are some scientists [60:33] that hate us when we anthropomorphize [60:36] having an intelligence or an adaptive [60:38] logic. So it's okay. [60:39] >> I think you've provided cover for me to [60:41] do it on for cells. Then [60:42] >> cells basically are measuring [60:47] their resources all the time. [60:50] >> I think you could make a compelling [60:52] argument that every cell almost all [60:54] cells know how much usable energy ATP [60:58] they have all the time. And when it gets [61:01] low, [61:03] they will initiate a series of reactions [61:06] to that, responses to that to bring it [61:08] back up. They'll turn off processes that [61:11] use ATP. They'll start pulling glucose [61:14] out of the circulation to make more ATP. [61:17] There's this really profound response to [61:20] ATP depletion. And I think that's true [61:22] for many of the endroducts of our [61:25] metabolic map. Again, these are the the [61:28] the products of the metabolic map are [61:30] the amino acids that make proteins. And [61:33] the nucleotides that are required to [61:35] make DNA and RNA, our genome, [61:38] >> there's a greediness to all these cells. [61:40] If the fat cells are greedy, you could [61:42] really see a problem like if we're not [61:43] ingesting enough glucose. Let's let's [61:45] hold off on ketosis for a second and [61:47] alternate metabolic pathways. But we [61:49] will touch on it. But if the fat cells [61:51] are also very self- serving then you [61:55] know at some point are they just forced [61:56] to liberate this stuff. But like [61:58] ultimately fat cells just want to get [62:00] bigger and bigger and that but if this [62:01] cardomyite it doesn't have enough [62:03] glucose eventually it's like it could [62:05] shut down any number of things like you [62:07] can remodel the house down to you know [62:09] just the fireplace and a little bit of [62:11] structure around it but eventually [62:13] >> you need the resource. So then what [62:15] happens that atyposite liberates the [62:17] energy. Yeah. [62:18] >> And and cells everybody gets a little [62:21] bit and you just hang on. So it's a [62:23] famine type situation. [62:24] >> Exactly. I mean just as insulin tells [62:27] the body I just ate. [62:29] >> We're good. Take that energy that's [62:32] available in the form of glucose. [62:33] Squirrel it away. Use it. There are [62:37] hormones that do the opposite. Glucagon [62:39] is one of them. And glucagon again has [62:41] become a little bit more popular [62:43] recently because it's now being combined [62:45] in some of the GLP-1 uh more newer GLP-1 [62:50] drugs. Glucagon is called a fasting [62:52] hormone. So glucagon in many ways does [62:55] the opposite of insulin. It will go to [62:57] the fat cell, bind to the vat fat cell, [63:00] tell the fat cell to take the fat that [63:03] it has squirreled away and release it. [63:06] And now that can go to other cells in [63:08] the body, the heart. Heart is very good [63:10] at consuming fatty acids that come from [63:13] atapost tissue. And so so that's good. [63:17] >> I'm actually relieved to hear that. [63:18] >> Yeah. [63:18] >> Right. Because if if god forbid there's [63:21] a shortage of food that lasts long [63:23] enough, like that's definitely an organ [63:25] I don't want shutting down. [63:27] >> Exactly. And and most of us have fat in [63:30] our fat cells. And and you could make an [63:32] argument that the key destination of [63:34] that fat is the heart to keep it alive. [63:37] And you know in a normal human I think [63:40] it's estimated 70 to 80% of the energy [63:43] extraction that happens in [63:45] cardiammyioytes and heart muscle cells [63:48] is happening from fat. You said under [63:50] fasted conditions is that [63:51] >> especially under fasted conditions but [63:53] even in fed conditions fat is is uh is [63:56] available for the heart to use and and [63:58] >> dietary fat or fat from adapocytes [64:00] >> both whatever fat is in the circulation [64:03] the cardiammyioite is pretty good at [64:04] taking it up and burning it making ATP [64:06] from it [64:07] >> yeah the brain likes glucose but it can [64:09] use maybe now we I'm not super versed in [64:12] in the ketogenic pathways but I know [64:14] that our brain can thrive on ketones [64:17] >> so carbohydrates are not quote unquote [64:19] essential. You know, all the ketogenic [64:21] folks love to say that there's no such [64:22] thing as an essential carbohydrate. That [64:24] doesn't change the fact that like the [64:25] preferred fuel source for most every [64:26] cell is glucose. But anyway, that's a [64:28] separate issue. [64:29] >> You don't want the brain to shut down [64:31] either. [64:32] >> Yeah. [64:32] >> So, if the form of energy changes, is it [64:37] still once you get to mitochondria, [64:40] pyuvate, MCP, and downstream, is it all [64:43] the same? is essentially like energy is [64:45] energy at that point or is or is there [64:47] are there multiple pathways depending on [64:49] the fuel source? [64:50] >> Yeah, the ability of neurons to consume [64:54] fatty acids is limited. I I think it's [64:57] traditionally been thought that it's [64:58] very close to zero. I think that's being [65:00] questioned now, but it's limited. As you [65:03] allude to neurons are particularly fond [65:06] of consuming glucose and use that [65:08] glucose to make their ATP. And you know [65:11] that obviously puts a very [65:15] stringent demand on the body to always [65:18] have glucose available. Glucose is one [65:22] of these things that's fascinating the [65:23] the systems that we have in our body to [65:25] maintain glucose. You know diabetes is [65:28] defined as high blood sugar. That is the [65:31] definition the clinical definition of [65:32] diabetes when basically our body does [65:35] not adequately limit the circulating [65:38] glucose and that is destructive damaging [65:42] but it's damaging on the in the course [65:45] of years right a person can live with [65:47] diabetes for years before succumbing to [65:49] it if glucose is too low you die within [65:53] minutes if not seconds and that I think [65:56] for a few different reasons but probably [65:58] the most important one is the brain [66:01] requires some amount of uh glucose to [66:04] keep it functioning. So you know again I [66:07] I alluded to this before this very [66:09] elaborate dance that is happening by [66:11] these individual cells taking up [66:14] different nutrients out of the [66:16] circulation [66:17] using them for their own unique purposes [66:20] and and neurons again are are very adept [66:22] at taking in glucose and burning it and [66:25] making ATP from it. I think again the [66:27] heart I I feel like is really [66:29] fascinating because it'll it'll eat [66:31] anything. It's an omnivore. Fats, [66:33] glucose, lactate, [66:36] ketones, amino acids. It will make ATP [66:41] out of just about anything that ATP can [66:43] be made out of. And again, that's [66:46] important for us to enable us to live no [66:48] matter whether we just ate or not. Heart [66:50] is very good at that. So I think this [66:53] elaborate dance that we have going on in [66:55] our body all the time between different [66:56] cells cells doing it different way [66:58] taking in different fuels and uh using [67:01] them for their unique purposes. [67:03] >> What is the consequence of eliminating [67:06] the M MCP a shuttle like you get like if [67:08] you take a mouse you're at the [67:10] University of Utah let's give a shout [67:11] out to Mario Kapi whose life story is [67:14] amazing who won a Nobel Prize for [67:16] essentially developing what are called [67:18] knockout mice among other things. um you [67:20] can eliminate genes to test the role of [67:22] a particular protein downstream of that [67:24] gene. If you make a mouse that lacks [67:26] these proteins, do you get a dead mouse? [67:28] So [67:29] >> they do not survive to birth. Yeah, [67:31] >> you can get sperm egg and a and that [67:33] somehow the [67:34] >> it can become a a mouse. [67:36] >> Yeah, it'll start to develop and then I [67:38] think if I remember right, it's about 12 [67:40] or 13 days of development, which is [67:42] >> you know 2/ird of the way from [67:44] fertilization [clears throat] to birth [67:46] of the mouse, it will die and and you [67:48] won't get a live mouse. But what has [67:49] been done and and obviously you were [67:51] probably getting there is because of the [67:53] technologies that Mario developed and [67:55] then others following after him, we can [67:57] now make mice that lack the MPC only in [68:01] the liver or only in the heart or only [68:04] in the muscle or only in the brain and [68:06] many of these things have been done. [68:08] >> Sorry, I should have been given credit. [68:09] He developed a technology that would [68:10] allow for organ and cell type specific [68:13] deletions or additions of genes. forgive [68:15] me but you reminded me like in all much [68:17] to so [68:18] >> yeah and many people have been [68:19] contributing that technology and [68:21] different ways to use it for decades now [68:23] and as you might imagine given the [68:26] unique demands of [68:29] different cells the effects are [68:30] different the heart is again very [68:34] focused its metabolic program is focused [68:36] on generating ATP so what if we [68:39] eliminate the MPC in the heart so we [68:42] have now made ATP P generation from [68:45] glucose less efficient. We've we've now [68:48] cut off the ability to use mitochondria [68:50] at least in the conventional way. So I [68:52] actually think the results of that [68:53] experiment are fascinating and this is [68:55] work that has been done by a few [68:58] different labs. Akmed Clinton who's a [69:00] postoc now running his own lab at [69:01] Rutgers was the one who started this and [69:04] uh other people have contributed. What [69:06] essentially happens to that heart is [69:09] that it lives and the animal lives for [69:13] weeks after that. But eventually the [69:16] animals die. And when you look at what [69:18] they die of, they have a massive heart. [69:20] They die of heart failure. And what has [69:24] become clear as we've gone and done more [69:26] sophisticated analyses of this heart and [69:28] why they die. It's pretty clear that [69:32] they don't die from an inability to make [69:35] ATP [69:37] because they can burn other things to [69:38] make ATP. We talked about this. They can [69:40] burn fats. They burn fats just fine. [69:43] What they appear to die from, and I [69:45] would say I'm speculating a bit here, we [69:47] don't have all the answers to all the [69:49] questions, is they have made a resource [69:52] allocation decision that turns out to be [69:54] pathological for them. And instead of [69:57] using the glucose that they take in to [69:59] burn it and make ATP, they start making [70:02] biomass. That that again we talked about [70:04] that that bifurcation. We've eliminated [70:07] their ability to make ATP from it at [70:09] least as effectively and instead they [70:12] make biomass. They grow. And when [70:14] cardiamyioytes grow that creates [70:17] structural problems for the heart. [70:20] Almost every human that succumbs to [70:22] heart failure will end up with a big [70:25] dilated heart that's less effective at [70:27] pumping. And that's what we see in in [70:29] the mouse really. And that maybe tells [70:32] us something about the fundamental [70:33] importance of this resource allocation [70:36] decision. And this is obviously just in [70:38] the context of cardiammyioytes. But [70:40] again, that resource allocation decision [70:42] is happening in every cell in our body [70:44] all the time. And that's one reason why [70:47] I'm fascinated with this field is we're [70:49] just starting to understand how those [70:51] resource allocation decisions are made. [70:54] What are the implications of making them [70:56] correctly and incorrectly? And maybe [70:58] even more excitingly, can we go and fix [71:03] that? When a cardiamyioite or when a [71:07] heart more aptly is making a resource [71:10] allocation decision that is [71:12] pathological, [71:14] can we fix it? Can we find a a [71:16] therapeutic that will go and correct [71:19] that and rewire it in the appropriate [71:21] and healthy way and can that then [71:24] restore the proper function of the [71:25] heart? Again, I think we're at the at [71:27] the frontier of this field, but it's a [71:29] really exciting place that that our [71:32] field exists now where we're starting to [71:33] understand the problems and we're [71:36] starting, I would say, early in [71:38] developing the right agents to act and [71:41] to manipulate this metabolic map that [71:44] might be able to fix things. I'd like to [71:46] take a quick break and acknowledge our [71:48] sponsor, Function. Function provides [71:51] over 160 advanced lab tests to give you [71:53] a clear snapshot of your bodily health. [71:56] This snapshot gives you insights into [71:58] your heart health, your hormone health, [71:59] autoimmune function, nutrient levels, [72:02] and much more. 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[73:24] So, is it fair to say that the [73:25] allocation of energy, which is made [73:27] pathologic in this mutant mouse, but [73:30] also in people who have these uh cardiac [73:34] conditions and die of heart attack [73:35] essentially. It's almost like the the [73:38] identity of the cells is screwed up. [73:40] They're still a cardommyioite, [73:42] >> but they're devoting too much energy to [73:43] making more of themselves and not enough [73:45] to to doing what they're supposed to do. [73:47] I have like two analogies that I want to [73:49] throw out there and maybe they they're [73:50] too much of a reach, but I love dogs. I [73:52] have a now a medium-sized dog. I used to [73:54] have a large dog. The larger breeds of [73:57] dogs live much shorter lives than the [73:59] smaller ones. And and we actually know [74:01] >> that's because of dosing of IGF-1, which [74:03] is a growth pathway thing. So there is [74:06] this like story about larger animals [74:09] within a given species tend to live much [74:12] shorter lives than the smaller variety [74:13] of that same species. There's some [74:15] exceptions to this, but there does seem [74:17] to be a sort of rule that like you can [74:20] either be big and live a short life or [74:22] you can be small and live a longer life [74:24] within certain species. [74:26] >> But there's also this thing about [74:27] heartbeats, right? Like this theory that [74:29] you only get so many heartbeats in your [74:30] life. The reason I I like these higher [74:33] level perhaps appropriate comparisons, a [74:36] lot of caveats there, is that like [74:39] ultimately when I think about life and [74:41] evolution and a propagation of species [74:43] and health versus pathology, it's all [74:46] about energy, right? It's like how are [74:48] you devoting energy? It can get into the [74:50] kind of mystical spiritual piece. That's [74:52] not our purpose. There's not my purpose [74:54] in in bringing this up now, but [74:56] >> it seems like at the cellular level and [74:59] at the subcellular level, which is what [75:00] you're describing, [75:02] >> the allocation of energy in this case is [75:05] the difference between life and death, [75:06] but but this this decision, you're not [75:09] telling us like, oh, you know, these [75:10] pathways I discovered along with others [75:13] are really like there's a a fan out of [75:15] like 50 different options. You're saying [75:17] make more [75:18] >> biomass, more of self, [snorts] [75:20] or use energy to be self. Mh. [75:23] >> And there seems to be like a critical [75:25] balance there. And I have another story [75:26] I could tell about how like if you look [75:28] at the data on longevity in different [75:30] athletes like the gymnasts, the [75:31] sprinters seem to live 3 to six years [75:33] longer on average than than others. And [75:35] the endurance runners are somewhere in [75:36] the middle. You look at very large [75:38] athletes like the powerlters and the um [75:40] moving aside all things of like use of [75:42] drugs in sports, you go like [75:44] >> the the sports where there's just a lot [75:46] more of somebody that's not good for [75:48] longevity and it really isn't. So there [75:51] does seem to be this balance between [75:53] size and the use of fuel to to build [75:57] more of oneself and the use of fuel to [76:00] just be oneself. And that self could be [76:02] a cell. [76:03] >> Yeah. [76:03] >> That self could be an organ. [76:05] >> That self could be a whole organism. And [76:08] I find that like not incidental, but [76:11] maybe I'm taking too many liberties [76:13] here. [76:13] >> Yeah. I mean that's a that's a complex [76:15] analogy. and and but I think one thing [76:18] that is very clear about about what [76:20] you're talking about is this sense of of [76:22] of identity in a cell. I that's a [76:25] fundamentally important phenomenon that [76:28] again we've known about for a long time [76:30] and there's been under an understanding [76:32] in some cell types in some ways about [76:34] how that identity is established and [76:36] maintained. But I think your question is [76:38] a really interesting one. To what extent [76:41] is disease associated [76:44] with loss of that cell identity? And and [76:47] cell identity is a bit of a squishy [76:50] parameter. You know, how do you measure [76:52] what a cell thinks it is? You know, [76:53] there's no function, right? So, yeah, [76:56] like when we had Max Crumbl on the [76:57] podcast, he was like, you know, every [76:58] one of your cells by the time you reach [77:00] our age, roughly, you know, in our 30s, [77:02] no, I'm kidding. in our 50s, early 50s, [77:04] is we're a mosaic of like our original [77:07] genetic makeup plus all these mutations [77:10] that have accumulated. Nobody likes that [77:12] picture. That's true. We're a patchwork [77:14] of like our former self and our newer [77:16] self. [77:17] >> That's one form of cell identity. What I [77:19] like here is that you're talking about [77:20] within an organ, within a cell type, [77:23] >> you sort of have a choice of a make more [77:25] of oneself or b just be you. [77:28] >> Yeah. So there's something like kind of [77:30] like to me conceptually sticky about [77:32] this notion of size versus use. [77:35] >> Yeah. I think I as you say I I think [77:38] that in a way we're talking again about [77:40] resource allocation allocating to energy [77:44] versus making more stuff that could mean [77:46] another cell or a bigger cell. [77:49] >> There's many examples of where making [77:52] more stuff instead of making more energy [77:56] is pathological. We talked about cancer. [77:58] We talked about the heart getting [77:59] pathologically bigger. Immune cells [78:02] becoming hyperactivated can lead to [78:03] inflammatory diseases. You know, there's [78:05] many examples of that. [78:07] >> So, I think this is all playing out at [78:10] the level of individual cells and what [78:11] you're talking about is obviously a [78:13] bigger uh conceptual framework in which [78:15] to think about it. But I think there is [78:17] that uh connection and I don't know this [78:20] is a bit non-scientific but I I do think [78:23] it's fascinating to understand the [78:27] historical philosophical ways that our [78:30] ancestors thought about the world [78:33] >> and we [snorts] find relics of that in [78:36] our science right that we can see [78:38] reflected in the discoveries that are [78:40] made today. I don't want to take us off [78:42] the biology, but if we can go down this [78:44] pathway a little bit more, you know, I [78:45] sometimes think about energy in terms of [78:47] human interactions and and I think most [78:49] of us can think of the extremes of [78:50] benevolent versus malevolent energy [78:52] exchange like like let's say somebody [78:55] like money is just [78:56] >> a tool, right? Like people say money is [78:58] energy. That sounds very like, you know, [79:00] like internety, but really it it can be [79:03] exchanged for something, right? We've [79:04] decided that. And if somebody steals [79:06] from us or they they promise something [79:09] and it turns out they overcharge us or [79:10] something like that like we [79:12] fundamentally understand the math there. [79:14] You said it was going to cost us this [79:16] much cost. You said it was going to be [79:17] this and instead I got that and this [79:19] isn't what I paid for. Right? But if you [79:20] look at human interaction and behavior, [79:23] the stuff that we consider malevolent is [79:26] usually when something when someone [79:27] perceives the energy has been stolen [79:29] from them. Usually in the form of time, [79:31] >> but often in the form of physical energy [79:33] because time is physical energy, right? [79:36] >> And then benevolent acts are generally [79:38] ones in which there's a either an even [79:40] or a kind of a um like a [79:44] >> net positive exchange of energy. And [79:46] this is like a lot of what structures [79:48] human interactions. Like I don't want to [79:50] take us too far. This is not a [79:51] psychology podcast, but think about this [79:53] all the time and like why I like zooming [79:54] down at the level of the cell is we can [79:56] find there there isn't going to be a [79:58] perfect relationship between the cell [80:00] and human interactions at large. But [80:02] this notion of no cell if it wants what [80:07] best for itself and therefore the organ [80:10] it resides in and therefore the [80:11] organism. [80:12] >> Yeah. [80:13] >> Can afford to really cheat itself. [80:16] >> That's right. like bring it down to like [80:18] the individual cell. You can't like the [80:19] cell can't afford to cheat itself, [80:22] >> right? [80:22] >> And if too many cells do that, you end [80:24] up with a big heart that doesn't pump. [80:26] >> Exactly. [80:27] >> So, it cheated itself. [80:28] >> Yeah. [80:28] >> For me, that's very useful. I don't know [80:30] if it is for anyone else. So, when I [80:32] think about like really critical [80:33] biology, [80:36] all these proteins, like which ones are [80:37] you going to study? Like, it's clear to [80:38] me now why this set of proteins is very [80:41] important. Yeah. [80:42] >> Very, very important. What I didn't get [80:44] was how you actually found it. So was it [80:46] that you knew there was a gene there [80:48] that coded for this thing of a certain [80:49] size? So you started making some what we [80:51] call recominant version of that and like [80:53] throwing it on cells seeing what [80:54] happened. Is that kind of the the steps [80:55] that went through? [80:56] >> We knew the protein was there. What we [80:58] didn't know is what it did. [80:59] >> Mhm. [81:00] >> And I would say the key discoveries of [81:03] that came from genetics. Basically [81:06] Carl's lab made flies that lacked the [81:09] MPC and we could then [81:12] >> they were actually alive. There's an [81:13] interesting story there that's probably [81:14] too in the weeds, but they live, [81:16] [snorts] [81:17] >> but they had specific manifestations [81:19] that we could analyze using [81:22] >> chemistry. [snorts] [81:23] And I'll tell you about the results of [81:24] that. We were studying it in other in [81:26] other cell types in yeast cells and in [81:28] human cells and studying the results of [81:34] losing these genes. You know, again, [81:36] this is what's enabled by doing [81:39] genetics. You know, Mario Capeki figured [81:41] out how to do this in mice and his [81:43] colleagues that gave us the ability to [81:45] do knockout mice. Other people have [81:47] enabled it in other species. And by [81:50] doing that and studying the results, we [81:54] could then deduce, oh, what's happening [81:57] in these yeast cells, these fruit flies, [82:00] and these human cells grown on a dish is [82:03] they aren't able to take their pyrovate [82:05] into the mitochondria. You know by [82:07] analyzing them using sophisticated [82:09] chemical tools we could see that they [82:12] were basically their metabolic pathway [82:15] from glucose to pyrovate to pyrovate in [82:19] the mitochondria to ATP that was being [82:21] blocked and it was being blocked [82:23] specifically at that level of the [82:25] pyrovate. So that then gave us the [82:28] initial hypothesis maybe that's what [82:30] these proteins are doing and we could [82:31] then go and validate that hypothesis in [82:34] multiple experiments and that like I [82:36] said been validated by many other people [82:38] over the ensuing decade or so. So those [82:41] were the experiments that enabled us to [82:43] to figure it out. It was really um [82:45] genetics that enabled us to do it. [82:47] >> Very satisfying when a discovery comes [82:49] about in yeast flies and mamalon [82:52] including human cells. What year span [82:56] was all of that happening if you had to [82:57] really tighten it? [82:58] >> Yeah, we published the paper in 2012. It [83:00] probably was going on from 2008 or 9 to [83:03] 2012, something something like that. [83:06] >> This is actually an important moment, I [83:07] think, for people to understand like [83:09] when they hear about yeast or flies. [83:11] They're probably like like why why are [83:12] we doing this stuff? And I'm not here to [83:13] like plug federal funding for research. [83:15] I think that just happens naturally as a [83:17] consequence of the podcast. Or at least [83:18] I hope so. But my graduate adviser told [83:21] me that yeast like they have a very [83:23] quick turnover. So that's why they're [83:24] good to use. And and she said that um [83:26] she was a wine drinker. She said and [83:28] they were much smarter than us because [83:29] they know how to make their own alcohol. [83:30] [laughter] So now we know why biologists [83:32] use yeast. [83:33] >> Fruit flies. It's because of the short [83:36] generation time. You can get a lot of [83:37] experiments [83:37] >> done. And they they have many of the the [83:40] same structures that a human does. You [83:42] know, not exactly obviously, but they [83:44] have many structures that human does. [83:45] And there's some things that they're [83:46] particularly good at. You can look at [83:47] the whole thing in the microscope and [83:49] see different cells and different [83:51] features. And I would say again, not to [83:53] plug our specific experiments, but we [83:55] could not have made that discovery with [83:57] any one type of organism. If we just had [84:00] the yeast data, we wouldn't have figured [84:02] it out. If we just had the flight data, [84:03] we wouldn't have figured it out. [84:06] >> Same with the the human cell data. But [84:08] putting it all together, we could [84:09] triangulate what we were seeing in one [84:11] to what we were seeing in the other, and [84:13] it became obvious that this is the [84:15] hypothesis we should pursue. And I I [84:17] think that's been obviously an effective [84:19] strategy that's been employed by [84:21] scientists for a long time is to take [84:24] multiple different approaches, multiple [84:25] different model systems to answer a [84:28] complicated question. [84:29] >> Let's talk about lactate. [84:31] >> Every time lactate's come up on this [84:32] podcast before, it's been the in the [84:34] context of exercise physiology. We had [84:36] the the great Andy Galpin, whose name I [84:38] don't expect you to recognize, but he's [84:39] he's really one of the like pre-minent [84:41] public educator. He's a professor of [84:42] physiology and exercise physiology. And [84:45] he told us and he told the world like [84:47] everyone talks about lactic acid. We [84:49] don't actually make lactic acid. We make [84:50] this thing called lactate. But within [84:52] the cell lactate plays a very crucial [84:55] role in this metabolic pathway. I know [84:57] you spent some time with lactate. So [84:59] when you think about lactate what do you [85:02] think about? [85:02] >> I mean so pyrovate we talked about [85:04] pyrovate extensively [85:07] >> to a first approximation. Again it's a [85:09] little more complicated than this but I [85:10] think this is a good way to think about [85:12] it. When pyrovate is made simplistically [85:15] has two fates. It can go into the [85:16] mitochondria we talked about. What we [85:18] didn't talk about is the other major [85:20] fate is to be converted to lactate and [85:22] exported. And that decision burn it make [85:25] lactate. I think you could make a very [85:28] strong argument is one of the most [85:30] important metabolic decisions that cells [85:32] are making all the time. [85:32] >> Why would it not burn it or make more of [85:34] itself because it's just got it in [85:36] excess? [85:36] >> Yeah. There's something about that [85:37] production of lactate that enables [85:40] ongoing production of biomass. So again, [85:42] a little more complicated than this. If [85:44] you burn the pyrovate, that turns into [85:47] carbon dioxide. We breathe it out. That [85:49] the stuff is gone. We breathe it out. [85:53] There's no stuff. There's just the [85:55] energy. [85:57] If you don't burn it, that stuff doesn't [86:01] get eliminated as carbon dioxide and can [86:03] turn into a protein. can contribute to [86:06] protein production or carbohydrate [86:08] production or you know fatty acids that [86:11] can be used to make make new cells. And [86:13] so that really is the that resource [86:16] allocation decision as we talked about [86:18] many times building or burning. [86:22] And lactate is one of the mediators in a [86:25] way of that building decision. And so [86:28] lactate I think historically has been [86:30] thought of as a waste product when our [86:32] cells can't burn [86:35] typically because of lack of oxygen. We [86:37] haven't talked so much about the role of [86:39] oxygen and all this. When I talk about [86:40] burning, what I really mean is taking [86:43] that pyrovate or fatty acids or other [86:46] things and oxidizing them using oxygen [86:50] and ex by so doing extracting the energy [86:54] and doing this unbelievably amazing [86:56] chemistry that the mitochondria do to [86:58] basically very effectively capture all [87:01] that energy and make it usable in the [87:03] form of ATP. When oxygen isn't [87:05] available, that pyrovate cannot be [87:07] burned and then it essentially has to be [87:10] converted to lactate. That's why when we [87:12] exercise and our muscle becomes hypoxic [87:15] or doesn't have adequate oxygen, we make [87:17] lactate and that lactate is what causes [87:20] the burn that we feel. And we've thought [87:21] about it traditionally as a waste [87:23] product. There's been beautiful [87:25] experiments done in the last 5 or 10 [87:27] years. Joshua Benowitz, a friend of [87:29] mine, a professor at Princeton, has done [87:30] some of these that have demonstrated [87:32] that lactate is a very important fuel on [87:35] its own. The heart, for example, is [87:37] quite good at consuming lactate and [87:40] burning it. [87:40] >> The heart can it seems like it's kind of [87:42] like a it's got it's consuming a sort of [87:45] like dog's breakfast of fuels. It likes [87:47] lipids. It'll take glucose. It likes [87:49] lactate. anything that's good for us cuz [87:51] that that keeps it beating no matter [87:53] what the metabolic status of you know as [87:56] long as we're alive we have something [87:57] that it can burn and lactate is just an [87:59] important mediator of carrying th that [88:02] energy around [88:03] >> it can be a fuel it can be a shuttle [88:06] >> in the context of exercise in brain and [88:08] I know this is we're not talking about [88:10] actionables here but like I've mentioned [88:12] before on this podcast like if we do [88:14] like an intense typically it's aerobic [88:17] exercise we get like enough lactate [88:19] generated that does seem to be a signal [88:21] to the brain for this brain derived [88:23] neutrophic factor which now kind of [88:24] makes sense in this context because the [88:27] whole purpose of BDNF is to build more [88:30] stuff more connections typically rather [88:33] than break connections so it's amazing [88:34] that we think of these things like a [88:36] waste product just like we used to talk [88:37] about like junk DNA nobody does that [88:39] [clears throat] anymore we have to be [88:40] very careful with language in biology [88:42] I'm realizing [88:43] >> like the moment we we label something [88:45] conceptually [88:46] >> you like shut down a field like line of [88:49] discovery that almost always ends up [88:51] being like super important. [88:52] >> Yeah, we joke all the time in the [88:54] mitochondria field about the powerhouse [88:56] of the cell, right? Which it really is. [88:58] I mean, the cell the mitochondria are [88:59] very good at being a powerhouse and [89:01] making ATP, but they do so much more. [89:03] And again, just to illustrate the point [89:05] that when we categorize something into [89:07] one thing, this is what it does. We're [89:09] almost always proven wrong and it turns [89:11] out to be a bit more complicated. [89:12] There's something I can't wrap my head [89:14] around because if I have an excess of [89:15] energy and therefore I'm making lactate, [89:18] am I going to now prioritize lactate? Is [89:20] that going to now get burned off the top [89:21] of the energy uh priority scale? [89:24] >> That's a good question. And and you [89:26] know, I I don't think we have strict [89:28] answers to this, but there's definitely [89:30] prioritization of energy. One of the [89:32] most important things to burn is fatty [89:34] acids. And and the reason for that is [89:36] that when fatty acids are in excess, [89:39] they can be toxic. and they can be toxic [89:41] in an acute way quickly. Glucose again [89:45] is toxic in excess but chronically maybe [89:48] it's a little bit less dangerous if we [89:50] have high glucose for for some time. [89:52] High free fatty acids is dangerous now [89:55] >> and not just because it clogs arteries [89:56] >> that of course. Yeah, exactly. [89:58] >> Yeah, [89:59] >> it Yeah, in reason in ways that we [90:02] probably don't need to get into, but can [90:03] be disruptive to cell structures and so [90:06] forth. And so, you know, most cells when [90:10] they have fatty acids will burn the [90:12] fatty acids first probably as a response [90:15] to, hey, this could kill us. Let's let's [90:17] take care of this first. [90:19] >> Is also true the fatty acids we ingest. [90:21] >> This is also true. The fatty acids we [90:23] ingest if they get into cells, of [90:24] course, you know, um you could imagine, [90:27] again, it's a little more complicated [90:28] than this, but the fatty acids we ingest [90:30] and the fatty acids we make end up in [90:32] the same pathways, right? They they both [90:35] get into other cells. uh throughout the [90:37] body and when they do they need to be [90:40] handled appropriately. Lactate is maybe [90:42] a little bit more on that on that side. [90:45] It has some important effects to the [90:48] chemistry of cells that are important to [90:50] deal with. And so lactate if it if it [90:53] gets too high in the body it can be [90:55] toxic. you know, uh, lactic acidosis, [90:58] which is essentially the the the [91:00] phenomenon where we have too much lactic [91:03] acid, lactate in our in our circulation. [91:06] That's bad and can be lethal. And so, [91:08] dealing with that lactate is important. [91:11] And so, yeah, I think there is a [91:12] prioritization that probably comes as a [91:14] result of evolutionary pressure. You [91:16] know, we had ancestors that maybe didn't [91:18] deal with fatty acids so well and maybe [91:22] didn't survive, but we had one [91:24] individual that figured out how to deal [91:25] with them more effectively and that [91:27] individual survived better and and that [91:29] trait was selected for and we're now [91:31] pretty good at it. We had a colleague of [91:33] yours on the podcast who studies hypoxia [91:36] and spleen function and and we're [91:38] talking about how everyone hears the [91:39] word mutation [91:40] >> and they think like oh mutations are [91:42] just always damaging but you know these [91:44] mutations that afford more life that are [91:46] adaptive essentially people can't hear [91:48] that enough mutations are the reason [91:51] we're here. [91:52] >> That's right. [91:52] >> Yeah. So the X-Men had it right. Like [91:54] that's a that's a good series to watch. [91:55] on the other side of the coin, the [91:57] maladaptive um situation. Could you tell [91:59] us about the Warberg effect and its role [92:02] in cancer? And and I do want to frame [92:03] this properly because nowadays we're [92:06] living in a weird time around this topic [92:09] of cancer. There are these corners of [92:11] the internet that like don't actually [92:13] believe in cancer or germ theory. They [92:16] they just like don't believe it. And [92:17] some of that is actually kind of [92:18] catching on. I believe cancer exists and [92:21] I believe that cancers can come about [92:23] through a variety of mechanisms. So only [92:26] if you believe that to be true that it [92:28] can come about through a variety of [92:30] mechanisms. Would I ask you to like [92:32] >> agree uh if you disagree please disagree [92:34] but [92:35] >> it's true right that there are a lot of [92:37] paths to cancer. [92:38] >> Yeah there's no question that there are [92:40] some fundamental features of cancer. All [92:42] cancers to my knowledge have mutations [92:45] in the genome and those mutations are [92:48] many but tend to cause again work [92:52] together to cause that cell to divide to [92:56] replicate itself more rapidly [92:59] to evade the immune system which is [93:02] patrolling looking for misbehaving cells [93:04] to eliminate them and somehow cancer [93:06] cells can avoid that. critically [93:08] important and you know one of the most [93:12] um exciting developments in cancer [93:13] therapy over the last 10 or 15 years has [93:15] been these checkpoint inhibitors PD1 [93:17] PDL1 that uh inhibitors that basically [93:21] reverse that you know cancer cells are [93:23] very good at cloaking themselves let's [93:25] say from the immune system and those [93:26] therapies eliminate that cloak and and [93:29] allow them to be seen by the immune [93:30] system and eliminated and there's just [93:32] been amazing responses to those new [93:35] therapies again they don't [93:38] treat every cancer to the same degree, [93:40] but there's been wonderful examples [93:42] where they've been effective. So yeah, [93:44] cancers can arise through many different [93:45] pathways. They all are associated with [93:47] mutations. One of the common features of [93:50] cancer is changes in metabolism. And [93:52] this is when you talk about the Warberg [93:55] effect, this is really fundamentally [93:57] what you're talking about. So the [93:58] Warberg effect is a phenomenon that was [94:02] named after Otto Warberg, a scientist, a [94:05] German scientist back in the 1920s that [94:08] observed that cancer cells [94:12] consumed less oxygen [94:14] than would be expected from the cells [94:17] around them. And that has been named the [94:20] Warberg effect. [94:22] What Otto Warberg thought was that [94:26] that's because the mitochondria are [94:28] broken and then concluded that broken [94:31] mitochondria are probably the cause of [94:33] cancer. That was the thinking that [94:36] permeated from the time of Otto Warberg [94:38] in the 1920s for for many years. [94:41] >> Broken meaning they're not making ATP or [94:43] or they're they're doing something [94:45] wacky. [94:45] >> Yeah, they're well they're not consuming [94:47] oxygen. That was the observation. the [94:49] oxygen consumption was low and that is [94:52] again mitochondria as the powerhouse of [94:54] the cell are consuming oxygen that's how [94:57] they're doing their powerhouse function [94:59] making ATP so that was the observation [95:02] the interpretation of that observation [95:04] was that mitochondria are probably [95:06] broken we now know we've talked about [95:09] this that mitochondria do more than just [95:11] make ATP [95:13] and it turns out that mitochondria and [95:14] cancer cells are not broken in fact [95:17] they're very very good not necessarily [95:19] at making ATP but at making stuff and [95:22] again the stuff is what's so important [95:24] for a cancer cell because it needs to [95:26] divide itself it needs to duplicate [95:28] itself to eventually make a tumor so the [95:31] Warberg effect is a phenomenon again in [95:33] simple terms that is absolutely the case [95:36] that mo many cancer cells most tumors [95:39] consume less oxygen than you would [95:40] imagine because they're instead of [95:43] burning their fuel again we talked about [95:45] this bifurcation cancer cells tend to [95:48] not be burning. And by burning, that's [95:51] consuming oxygen, [95:53] but they're using their resource [95:56] allocation to build stuff, to build a [95:58] new cell. And so, I think this dubtales [96:01] very nicely with what we've been talking [96:03] about before. The oxygen consumption, [96:05] the Warberg effect, is basically just a [96:08] surrogate for that resource allocation [96:11] question. And cancer cells are are very [96:14] adept at using their resources to [96:16] duplicate themselves. [96:18] >> Of the uh modern treatments for cancer, [96:21] radiation, chemotherapy and [96:23] amunotherapies and what's of happening [96:26] now had someone on talking about you [96:28] know cart cells and um things of that [96:30] sort. But is there anything that um you [96:34] kind of sense on the horizon? it might [96:36] be 5 10 years out or two years out that [96:38] like if if we could just solve that [96:42] that we would be in a position to treat [96:44] and cure many more cancers like like [96:46] what's the [96:47] >> what's the kind of lynchpin thing here? [96:49] Is it being able to reallocate the use [96:52] of pyuvate like if we could do that if [96:55] that was a druggable thing or you could [96:57] do a gene therapy but or you could use [97:00] non-invasive tools like ultrasound or [97:02] light these are all just forces right [97:04] chemical or I would I would like to [97:05] simplify things like for people if [97:07] possible like there two ways to change [97:08] things in the body healthy or unhealthy [97:10] you have mechanical choices and chemical [97:11] choices right you can feel more full by [97:14] having your gut distend you can feel [97:15] more full because your hypothalamus says [97:16] you're full and there's a bunch of other [97:18] stuff involved But like that's all we've [97:19] got is mechanical and chemical forces. [97:21] >> So let's assume you had the tool. [97:24] >> Is there some place where like you feel [97:26] like if we could just [97:28] >> turn that bolt? [97:29] >> Yeah. [97:30] >> We would be in a much better position to [97:31] treat a lot of cancers or cure them. [97:33] >> Let's maybe take a step back from that [97:35] and then get to that question in a [97:36] second and talk about cancer. You know [97:38] what it is and why it's so difficult. If [97:41] a bacteria invades us, [97:44] it's very easy for our immune system to [97:47] say, "Hey, that's not us. Let's go kill [97:50] that thing." [97:52] >> If a cancer cell starts hyperp [97:54] proliferating, it's us, right? It's our [97:57] cells. It doesn't have antigens, which [98:01] are the technical term for the [98:03] molecules, the features that are [98:04] recognized by the immune system. it [98:06] doesn't necessarily have antigens that [98:08] are recognized as not us nonself. So [98:12] that's one of the big challenges of [98:14] cancer. The challenge for us is to [98:17] figure out a way to kill those cells [98:20] which again are our cells. They are us [98:23] to kill those cells without killing the [98:25] rest of our cells. Because if we kill [98:27] the rest of our cells, we kill us, [98:29] right? That's the challenge of cancer [98:31] therapy in my view. Again, I'm [98:33] oversimplifying, but that's that's a big [98:35] challenge. And many of the features of [98:39] cancer cells are not completely new [98:43] things that that cancer just invented. [98:46] It's using the functions that our normal [98:48] cells have. For example, one of the [98:51] things that's common, not universal, but [98:53] common in cancer cells is to become more [98:56] like a stem cell. Has many features of [98:59] stem cells. So, okay, we can find a way [99:01] to target a specific stem cell pathway [99:05] and kill all the cells that have that. [99:08] Well, then we're killing many of our [99:09] stem cells, too. And now the lining of [99:11] our gut doesn't regenerate, which we [99:13] talked about. That's driven by hair. [99:16] Exactly. This is obviously one reason [99:18] why many of the the side effects of [99:21] chemotherapy is to target those [99:23] proliferating cells which share many [99:26] features with cancer cells. So that's [99:29] the problem of cancer therapy. And [99:31] there's a second problem that's worth [99:33] talking about too. [99:35] We've talked about evolution a lot here [99:37] which I think is it's a great rubric by [99:39] which to think about biology. [99:42] Cancer cells a a tumor is under [99:45] evolutionary pressure. Right? So we know [99:47] let's take an example where we have a [99:49] tumor and we get a drug. We have a great [99:52] drug that kills 99.9% [99:55] of the cells in that tumor. [99:58] But.1% of the cells either through a [100:00] mutation or some sort of an adaptation [100:02] are not killed by it. [100:05] But that.1% [100:07] can now repopulate, make a new tumor. [100:09] And this is what happens in cancer [100:11] therapy. We all know of tragic examples [100:14] where we loved ones had a tumor, [100:18] got a treatment and they went into [100:20] remission. you know, the tumor maybe [100:23] shrinks, it goes away, maybe even [100:24] becomes invisible by the imaging tools [100:27] that we have to image uh cancers, but [100:30] then it comes back. And that's because [100:32] these cells are under evolutionary [100:34] pressure. If if one cell, theoretically, [100:37] one cell acquires a mutation that makes [100:40] it resistant to that drug, doesn't get [100:43] killed by that drug, that one cell can [100:45] now repopulate, make a new tumor, and be [100:47] just as damaging. And now it's resistant [100:49] to the drug. Now the drug doesn't work [100:51] anymore. And this is the second big [100:53] problem with cancer therapy. You know I [100:56] this is not my field of expertise per se [100:59] but I feel like given that situation [101:03] this is not dissimilar to what happens [101:05] with viruses. HIV now can be managed and [101:09] frequently is managed by a triple [101:12] combination therapy. And the reason for [101:15] that is you now give three drugs that [101:18] are going to kill that virus or prevent [101:20] the propagation of that virus. It's now [101:23] very difficult to acquire resistance to [101:25] all three simultaneously. [101:28] I think the analogy applies to cancer [101:30] too. I think the future of cancer [101:32] therapy [101:34] again in my in my worldview is going to [101:37] be we have many safe and effective drugs [101:42] that hit different features of the [101:45] cancer cells biochemistry and by virtue [101:48] of understanding the specifics of the [101:51] tumor that I might have the astute [101:54] oncologist can say given that unique [101:57] biochemistry of that tumor this drug [101:59] this drug and this drug are going to [102:01] work together to kill that tumor. And [102:03] it's going to be very hard for that [102:06] tumor to become resistant to all of [102:07] those drugs simultaneously [102:10] and as a result of that that might [102:12] result in something approximating a [102:14] cure. I think that's the world that we [102:16] need to get to. So there's been amazing [102:20] therapies that have come out. You know, [102:21] one of the most exciting recently are [102:24] drugs that target specific encogenic [102:26] mutations, specific mutations that cause [102:28] cancer. Krass mutations are one that [102:30] that are really exciting that target [102:33] specific proteins that are contributing [102:35] to the cancer in a completely specific [102:37] way. Don't do anything else in the body [102:39] to normal cells. Only hit those [102:42] mutations that are onenic. But again, [102:45] eventually there can be resistance [102:46] that's acquired to that. So if we can [102:49] now make multiple examples of that kind [102:52] of specific safe kind of [snorts] drug [102:55] and use them in combinations, our [102:57] ability to treat cancer is going to be [102:59] dramatically improved. [103:00] >> That's very encouraging. We had a guy on [103:02] the podcast named David Fagenbomb. He's [103:04] a medical doctor. Are you familiar with [103:05] his work? He's at University of [103:07] Pennsylvania. He had Castleman's disease [103:08] and he was able to cure his own [103:10] Castleman's disease because he was [103:12] basically on his deathbed. and he [103:14] basically just started taking different [103:15] combinations of already approved drugs [103:17] in a kind of desperate attempt to save [103:20] his life. And he he found things that [103:21] would extend his life. And he's been [103:23] alive 11 years now. and he runs a lab, [103:25] serious scientist as we say, but he also [103:28] has this uh not for profofit called [103:29] Every Cure, which has been successfully [103:32] using AI and cell assays and things to [103:35] take biopsies and try and figure out [103:38] like, okay, in this tragedy of a kid [103:40] who's dying of a particular cancer, like [103:42] let's just throw a bunch of not random [103:45] drugs, but already approved drugs at [103:47] this tumor in a dish, and if some of [103:48] them work, like if the parents agree and [103:51] there's no other hope, do it. and like [103:53] in some cases they're curing and in many [103:55] cases they're extending life. It matches [103:58] up well with what you're describing. It [103:59] requires this AI piece to run iterations [104:01] cuz there's a huge catalog of drugs that [104:03] even oncologists might not be aware of. [104:06] One particular highlight of his work is [104:08] that we know now that in breast cancers [104:11] where they use lidocaine during the [104:13] surgery the incidences of recurrence are [104:16] significantly lower. [104:18] >> And it turns out that lidocaine has some [104:19] effect on the local environment. I'm [104:21] not, this isn't my area, but you know, [104:22] David talks about this and I'm [104:24] encouraged by things like that and what [104:26] you're describing that we're not [104:27] necessarily going to have like the [104:28] miracle drug, but then the miracle [104:31] cocktail for that individual, that [104:33] cancer. [104:34] >> That's the key thing is that, you know, [104:37] >> David's situation is very specific to [104:40] David and and every tumor is a little [104:42] bit different. [104:43] >> Yeah. And one of I think the unhelpful [104:48] results of historically how we talk [104:50] about tumors is we talk about breast [104:52] cancer or liver cancer or [104:56] you know colon cancer. [104:59] There are some breast cancers that are [105:02] more similar to some liver cancers than [105:05] they are to other breast cancers. Right? [105:06] This is our historical classification of [105:09] cancer has just been by where it is. was [105:11] defined by the surgeons that would take [105:13] it out. But the specific mutations that [105:17] cause that cancer and keep that cancer [105:20] again evading the immune system, [105:22] propagating, avoiding cell death and so [105:25] forth are unique to that cancer. So if [105:28] we understand the unique mutational [105:31] landscape of that cancer that gives us [105:34] then [105:36] an ability to say again in a in a world [105:39] that isn't today's world but hopefully [105:42] not too long uh far from now where we [105:44] have the ability to say this combination [105:46] of drugs is going to be effective at [105:49] killing the cells in that tumor. You're [105:52] highlighting something really important [105:53] that is both about the sociology of [105:55] medicine and science that it's just the [105:57] it's not disparaging of it's just it is [105:59] the way it is because of history. So [106:01] much of the way things are in medicine [106:04] and science can be answered by the a [106:06] phrase that everyone should hate, which [106:09] is, well, we've always done it that way, [106:10] which is the worst reason to do anything [106:12] unless it's working spectacularly well, [106:15] right? But is it a stretch to say that [106:18] there are some liver cancers that are [106:20] called liver cancer but that are [106:23] actually much closer in terms of their [106:25] cellular phenotype to cancer of a [106:28] cardiammyioite because of the way that [106:30] say MPC one is changed in other words [106:34] like should we be classifying cancers as [106:37] oh this is a cancer of the sort that the [106:39] cells are making too much of themselves. [106:41] >> Yeah. [106:41] >> As opposed to they're overusing energy. [106:44] There's too much pyuvate. I'm making [106:45] this up, right? I'm not obviously not my [106:47] field. But rather than think only about [106:50] address in the body. [106:51] >> Yeah, no question that we should be [106:53] thinking about the specific features of [106:55] cancer. I've been talking about it in [106:57] terms of the mutation, [107:00] >> the specific mutations that define a [107:01] cancer. And I think that's a useful way [107:03] to do it [107:04] >> because those mutations in a way are the [107:08] instructions for making a new cell. [107:10] Right? the genome of a cell are the [107:12] instructions for how to make a new cell, [107:14] the the constituents that would make up [107:16] a new cell. But I think a very important [107:19] feature that you're touching on that I [107:21] appreciate you bringing up is on top of [107:24] that, layered on top of that is the [107:26] unique metabolism [107:29] that makes up that cell, right? That [107:32] enables those instructions to be [107:34] executed. You know, a cell can have all [107:36] the right instructions to make a new [107:38] cell, but if it doesn't have the [107:41] building blocks, the lumber and the [107:43] bricks and the mortar to make a new [107:45] cell, it can't make a new cell. And so, [107:48] I think that's a really important [107:50] feature of this that we need to talk [107:52] about. And there's been a lot of energy [107:53] in the in the field over the last 10 or [107:55] 15 years and maybe even 10 years or less [107:58] at trying to specifically block the [108:01] resource allocation of cancer cells [108:03] toward [108:05] building new new cells. The challenge [108:07] there again is that it's fairly easy to [108:10] develop resistance to that. A cancer [108:11] cell can just make a mutation and and [108:13] rewire its metabolism to build that same [108:16] thing a different way. But that is a [108:18] very important feature of the cancer [108:20] tube. Beyond just the mutations are the [108:23] are the the metabolic processes that [108:25] enable those mutations to be manifest in [108:28] in in what turns into a tumor. How far [108:31] are we from a a world where um I drink a [108:35] fluid and it's a safe fluid because we [108:37] do this for like other types of imaging. [108:39] I step into a tube and I do it when I'm [108:41] like five [108:42] >> and I do it when I'm 50. [108:44] >> Mhm. And I get a picture of red and [108:46] green in every cell, right? So you get [108:48] like an image of like the proportion of [108:51] my metabolism in different organs and [108:53] you could zoom in to a single cell. This [108:55] is not like science fiction at the level [108:57] like it couldn't be done [108:59] >> where you say okay this is a healthy [109:01] cardommyioite and it's using 65% of its [109:05] energy to just keep pumping and then it [109:08] like puts aside a little bit to make [109:10] sure it can make more of its stuff so it [109:11] stays around and a little bit. it's like [109:13] going to this other pathway and like [109:15] that's a healthy cardio. We know this [109:17] from the population of of age match data [109:20] and then when I'm you know 40 50 you go [109:23] yeah I don't know like the your heart's [109:24] looking a little more green than red or [109:27] something like that. we can kind of turn [109:29] the dial back like like we have [109:31] druggable, you know, targets inside of [109:33] cells and we can like kind of like [109:34] adjust the the energy allocation like is [109:37] what I'm describing like so crazy [109:39] because I can imagine a mouse experiment [109:41] or paper will probably come out on that [109:43] next week if it hasn't already [109:44] >> and like that's kind of what you want. [109:46] You want subcellular resolution cuz I [109:48] feel like we've gone from this place [109:50] where like [109:51] >> I was around when the first MR like [109:53] functional magnetic resonance imaging [109:54] stuff was kind of like here's a person [109:56] looking at a banana here's a person [109:57] hearing a joke and like now you can see [110:00] dynamics and you can see acts on [110:02] pathways but if we get down to the cells [110:04] cool [110:05] >> it's a lot of salt and pepper [110:07] >> then you get down to the inner workings [110:08] of the cells you can't see everything if [110:10] you look at everything it's going to [110:11] look like chaos [110:12] >> someone put on X this morning actually a [110:15] AI I rendering of all the proteins in a [110:17] cell in one tiny patch of cell and it's [110:19] just like overwhelming. You're just [110:21] like, "Oh my god." Like there's so much [110:22] here. But if you just say like, "Let's [110:24] just look at metabolism at this key node [110:26] and we know what healthy should be. [110:28] Here's where you're at." [110:29] >> And you're just trying to tilt that [110:31] balance. I mean, that to me feels like a [110:33] >> that could be done. [110:34] >> Yeah. [110:35] >> Like we've got smart people working on [110:36] this. We need more money [110:38] >> to for scientists to work this stuff out [110:40] and more scientists to do that work. But [110:43] I feel like that's doable [110:44] >> conceptually. Pieces of that are doable. [110:46] I think you know when you talk about can [110:49] we basically image metabolism with [110:53] cellular resolution [110:56] I [clears throat] should be clear that's [110:57] a very difficult problem. The spatial [111:00] resolution the ability to see fine [111:02] enough detail to make out individual [111:04] cells or even uh smaller than that. [111:07] That's a challenge. That's definitely a [111:09] challenge inside a human body. And it's [111:11] also a challenge to be able to have a [111:14] surrogate of metabolism that we can [111:16] actually see. Of course, our metabolism, [111:20] there's nothing visual that we can see [111:21] with the naked eye, right? That there's [111:23] nothing I can see in the metabolism of a [111:26] cell. So, what could we make that would [111:28] enable us to visualize that? There's [111:30] really exciting tools being developed of [111:32] many different kinds to be able to image [111:35] various features of metabolism in a [111:38] cell. [111:38] >> Well, we would in neuroscience. I mean, [111:40] again, I was fortunate to be part of [111:41] this wave of technology. Didn't [111:43] contribute to building any of it, but it [111:45] was like, how do you know which brain [111:46] areas are active? Well, you could drop [111:48] electrodes in or you could remove a [111:50] piece and go, well, it probably did that [111:52] when it was there cuz you lost that [111:53] function. But, you know, a lot of it was [111:55] just blood flow. It was like oxygenated [111:58] to deoxxygenated blood [111:59] >> reflects light differently. And like [112:01] you'd get these beautiful maps, but you [112:03] were just looking at blood flow. Now, [112:04] then you got [112:05] >> 2D deoxy glucose. You can look at [112:07] glucose uptake, but it was spatially [112:09] very crude or it was the the time [112:11] resolution wasn't very good. But I feel [112:13] like we've come some way. You can look [112:14] at voltage. You can look at calcium. I [112:16] feel like [112:17] >> the moment that chemists, bioengineers, [112:20] and physicists [112:21] and computers came into biology, [112:25] >> things got a lot better. [112:26] >> Yeah. [112:26] >> I mean, some people say it got a lot [112:28] worse, [112:29] >> but they retired now. So, like, it got a [112:31] lot better because you could see what's [112:33] really happening. [112:34] >> Maybe I'm overly optimistic. No, I I [112:36] think that we need to be able to figure [112:38] out what to measure. I mean, that's [112:40] obviously a key thing. What would be the [112:42] metabolic parameter? What would be the [112:44] one metabolic parameter you'd really [112:47] want to measure to assess is this cell [112:50] healthy or not healthy? And it's hard to [112:52] know exactly what that one would be or [112:54] collection of things and then figure out [112:56] a way to measure that [112:58] >> non-invasively, so to speak. You know, [113:00] it's one thing if if I'm going to [113:03] measure that, do I have to cut off my [113:04] arm, [113:05] >> shave it into slices, and you know, [113:07] measure it? Nobody wants that. [113:09] >> So, how can I measure it without, [113:12] >> you know, doing damage to me while I'm [113:14] measuring it? These are hard problems, [113:16] but as you say, the technology just [113:18] keeps getting better in all versions of [113:20] this. And the experimental tools, the [113:22] tools that we can use in mice or in [113:25] cells and culture are definitely getting [113:27] better. And that that's that's an aspect [113:29] of this field of of studying metabolism [113:32] that's really exciting is our ability to [113:34] now be able to measure what's happening [113:36] at individual places in individual cells [113:39] and looking at specific individual [113:41] molecules you know intermediates and [113:43] products and substrates of these this [113:45] metabolic map and that I think is [113:48] teaching us a lot about how metabolism [113:51] works in individual cells and that is [113:53] then going to be informative when we [113:55] think about how it's working in a [113:57] I'm intrigued by this really wild thing [114:00] that you see in the news every once in a [114:01] while which I believe to be true but no [114:03] one can explain which is that there are [114:05] dogs and there are occasionally people [114:08] who can detect the scent of cancer [114:11] beyond chance like this is like no one [114:14] really knows the basis of this and [114:16] recently there's an example my [114:18] understanding is it's validated of a [114:20] woman who was able to smell Parkinson's [114:22] as a musty scent that a musky excuse me [114:25] and now spouses of people that had [114:27] Parkinson's in particular the female um [114:30] the wives of these men like oh yeah I [114:32] remember this now of course there's a [114:33] whole lot of like placebo correlation [114:35] just so story that can emerge from that [114:37] but as you're telling me some of this [114:39] like obviously you wouldn't want this to [114:41] be the one and only frontline detection [114:43] system but it kind of makes sense that [114:44] if if cellar metabolism is at the heart [114:46] of certain cancers or neurodeenerative [114:49] conditions makes sense that we're [114:51] breathing out yeah [114:52] >> the byproducts obviously these sense are [114:54] just correlative right and the shifts in [114:56] when we with infants, parents are [114:59] remarkably good at being like [115:00] something's off because they can't [115:02] communicate verbally with us yet, right? [115:04] Like something's off in their stool or [115:06] something's off in their skin power [115:08] that's not extreme and and become [115:10] remarkably astute detecting real [115:12] underlying issues. Yeah. So, do you [115:14] think that there could be useful [115:16] information coming from the air we expel [115:20] in terms of revealing at a systemic [115:22] level or maybe even at a cellular level [115:24] um how well or poorly we're regulating [115:26] >> energy? Yeah. I mean, obviously, as you [115:29] said in your in in alluding to this, [115:31] this is again at the frontier of science [115:33] and I don't think we understand much of [115:35] the specifics, but I think you could [115:38] imagine that because again, smells, [115:40] scents are chemistry, right? These are [115:43] chemical compounds that are coming from [115:45] the person. And when a person's doing [115:49] different metabolism, they're going to [115:50] be producing different chemicals in [115:52] different proportions. And I think it is [115:54] possible that those can be detected in [115:56] specific ways. That's not so dissimilar [115:59] from some of the diagnostics that we do [116:01] use where we actually measure the blood [116:03] chemistry. You know, the blood chemistry [116:05] is different between people that have [116:06] different diseases and don't. And so, [116:08] you know, and obviously the breath is [116:12] some [116:13] measure of the chemistry that's going on [116:16] in the person. It's obviously um [116:18] different from the blood, but it's a [116:20] fascinating topic and and as that gets [116:22] to chemical specificity, it'll become [116:24] probably more clear what's going on [116:26] there and why why is Parkinson [116:28] specifically susceptible to that [116:30] different chemistry in a way that can be [116:32] detected by scent. We were talking a few [116:35] moments ago about excess energy [116:37] toxicity. This is something that Dr. [116:39] Lane Norton brought up on this podcast. [116:41] He's a serious biochemist, nutrition, [116:43] exercise science guy, public educator, [116:46] loves random ice control trials and [116:48] metaanalysis. That's like his if it's [116:50] not there, he's not interested or he's [116:53] perfectly interested in in tossing away [116:54] everything else. So that's kind of his [116:56] hallmark. So that should feel good to [116:57] you just knowing that. But he talks [116:59] about this energy toxicity. You know, [117:01] like excess calories leads to problems. [117:04] Not just because of the presence of [117:06] excess body fat, but because of just too [117:09] much energy at the front end creates [117:11] downstream biochemical issues across the [117:14] body. How does this relate to some of [117:16] what we've been discussing? [117:18] >> There's a a widely accepted hypothesis [117:21] that mitochondria with excess energy [117:25] leads to problems. You know, many people [117:28] that that are listening have probably [117:30] heard of reactive oxygen species. This [117:32] is, you know, forms of oxygen that [117:34] become reactive and end up spinning out [117:37] and damaging proteins and nucleic acids. [117:40] And [117:42] I think it is uh again widely accepted, [117:46] not universally, but widely accepted [117:48] that one of the contributors to that is [117:50] mitochondria that have too much energy. [117:53] Basically, the form that energy takes [117:55] when it's extracted from the food we eat [117:57] and before it's converted to ATP is [118:00] powering the mitochondria. And when that [118:02] mitochondria is overpowered, that leads [118:05] to a state that is very susceptible to [118:07] generation of these reactive species [118:09] that end up damaging our genome, [118:11] creating mutations and damaging proteins [118:13] and creating many of the problems that [118:16] we see. And I think there's been a [118:18] number of studies that have suggested [118:19] they might contribute to various [118:21] pathologies including aging. So I think [118:24] that idea of excess energy is one that [118:27] is really important to consider from the [118:30] level of the organism down to the level [118:33] of individual cells and even the [118:34] mitochondria within those cells. Once [118:37] again, it I'm thinking about the this [118:39] notion like no individual or collection [118:43] of individuals or cell or collection of [118:46] cells can really get away with or what's [118:48] the saying like you pay the piper [118:49] somehow. Like cells really get punished [118:52] for cheating themselves by taking too [118:55] much energy or not allocating it [118:57] correctly. Like you can level up [119:00] >> from this like single cell analysis all [119:01] the way to to societies. I actually [119:03] think [119:04] >> this is fascinating. I for a variety of [119:07] reasons. First of all, again, we've [119:08] never had a serious discussion about [119:10] what mitochondria actually do besides [119:12] just create help create energy. So, [119:15] first of all, thank you so much for [119:16] telling us how they actually allocate [119:18] their resources towards things other [119:20] than just making more energy for usage [119:23] to build more of oneself. also for [119:25] framing that in the context of of [119:27] disease and health and also for shining [119:30] a light on the fact that like while we [119:33] might be right here now that I do think [119:36] I'll just say what maybe you were trying [119:37] to say but are too humble to say that I [119:40] think as long as we're looking at things [119:41] just like oh this is a cancer of this [119:43] tissue and not actually asking what [119:46] specifically is happening to the cells [119:48] there that might be common to other [119:50] cancers elsewhere and like changing our [119:52] nomenclature and boundaries of how we [119:54] classify things opening up our minds to [119:56] it [119:56] >> as well as really thinking about the [119:58] whole body as a like a constellation of [120:01] these little microactories that is us. I [120:04] am certain that people hearing this will [120:06] no longer think about like metabolism [120:08] just as them my metabolism but this um [120:12] constellation of metabolisms and and the [120:14] health status of of all the different [120:16] cells. So, it goes without saying that [120:18] it's a really unique opportunity for the [120:19] general public to hear from like like a [120:21] worldclass biologist working on these [120:24] specific issues and related issues for [120:27] decades now, right? And so, and you're a [120:29] very busy person. So, I'm very grateful [120:30] to to you to the University of Utah for [120:34] allowing uh and encouraging public [120:35] education to Howard Hughes. No, they [120:37] didn't tell me to say this, but I think [120:39] people really need to understand what an [120:41] amazing opportunity is to learn from the [120:42] people and there are others in the [120:44] field. you're so good at attribution who [120:46] are who are really trying to figure out [120:48] these really hard problems in biology [120:50] that are crucial to health and to [120:52] disease and therefore to curing disease [120:54] and really trying to move things forward [120:56] in your workshop that you call a [120:58] laboratory. So you don't have to do this [121:00] sort of thing but I greatly appreciate [121:01] it and I speak on behalf of many many [121:03] people really appreciate it. There's [121:05] information and then there's superb [121:06] information. So thank you so much. [121:08] >> Thanks Andrew. It's been a lot of fun. [121:09] >> Uh we'll do it again [121:10] >> anytime. [121:11] >> Cheers. [121:11] >> Thank you. 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