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