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How Mitochondria Control Your Metabolism | Dr. Jared Rutter

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How Mitochondria Control Your Metabolism | Dr. Jared Rutter

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0:00

There's a widely accepted hypothesis

0:03

that mitochondria with excess energy

0:07

leads to problems. Many people that that

0:09

are listening have probably heard of

0:10

reactive oxygen species. This is forms

0:13

of oxygen that become reactive and end

0:14

up spinning out and damaging proteins

0:18

and nucleic acids. And I think it is

0:21

widely accepted that one of the

0:23

contributors to that is mitochondria

0:26

that have too much energy. Basically,

0:28

the form that energy takes when it's

0:30

extracted from the food we eat and

0:32

before it's converted to ATP is powering

0:35

the mitochondria. And when that

0:37

mitochondria is overpowered, that leads

0:40

to a state that is very susceptible to

0:42

generation of these reactive species

0:44

that end up damaging our genome,

0:45

creating mutations and damaging proteins

0:48

and creating many of the problems that

0:50

we see. Welcome to the Hubberman Lab

0:52

podcast, where we discuss science and

0:55

science-based [music] tools for everyday

0:56

life.

1:00

I'm Andrew Huberman and I'm a professor

1:02

of neurobiology and opthalmology at

1:05

Stanford School of Medicine. My guest

1:07

today is Dr. Jared Ruer. Dr. Jared Ruer

1:10

is a professor of biochemistry at

1:12

University of Utah and an investigator

1:14

with the Howard Hughes Medical

1:16

Institute. He is one of the world's top

1:18

experts in the biology of mitochondria

1:20

and metabolism. Mitochondria are known

1:22

as the powerhouse of the cell. But as

1:25

you'll learn today, they do far more

1:27

than just power our cells. They also

1:29

determine how much energy goes into

1:31

making new cells, to making sure that

1:33

cells stay healthy, and to fighting off

1:35

disease. Today's conversation explains

1:37

how mitochondria do that, and clarifies

1:40

what your metabolism really is. And in

1:43

doing so, you will learn that you don't

1:44

have one metabolism. Your metabolism as

1:48

it's called is actually a reflection of

1:49

the constellation of all the metabolisms

1:52

of all the cells in your body. So

1:54

today's conversation will teach you the

1:55

real biology of mitochondria and it will

1:58

provide a framework for you to make

2:00

better decisions on the behalf of your

2:02

health. So what follows is a

2:03

conversation about mitochondria and

2:05

metabolism unlike any that you've heard

2:07

from one of the world's premier experts

2:09

in this topic. Before we begin, I'd like

2:11

to emphasize that this podcast is

2:12

separate from my teaching and research

2:14

roles at Stanford. It is however part of

2:16

my desire and effort to bring zero cost

2:18

to consumer information about science

2:20

and science related tools to the general

2:22

public. In keeping with that theme,

2:23

today's episode does include sponsors.

2:26

And now for my discussion with Dr. Jared

2:28

Ruer. Dr. Jared Ruer, welcome.

2:31

>> Thank you. Thanks for having me on.

2:32

>> I have many questions about metabolism,

2:35

mitochondria, and I know many people do

2:37

as well. Most people hear the word

2:40

metabolism and they think calories in,

2:42

calories out. They hear the word

2:44

mitochondria and they probably think the

2:46

powerhouse of the cell and that's all

2:48

great. People are becoming more educated

2:51

about cells and their bits and pieces

2:53

and what they do. You have a very

2:55

different perspective that is very

2:57

important I believe for people to

2:58

understand. Maybe we could start off by

3:00

talking about how the metabolism of any

3:04

one cell in our body relates to what we

3:08

call our metabolism, the collective

3:09

metabolism of all those cells. And as

3:12

you go, if you could take any liberties

3:14

you want to tell us what we probably

3:16

don't know about the quote unquote

3:18

powerhouses of the cell.

3:19

>> Yeah. You know, when we think about

3:20

metabolism, as you say, I think all of

3:22

us think about metabolism in terms of

3:24

our body's metabolism, our metabolic

3:27

rate, as you say, calories in, calories

3:29

out. What that is really our body's

3:31

metabolism is basically

3:34

the the sum total of what we ingest, you

3:37

know, what we eat, what we drink, what

3:39

we breathe,

3:40

that enters our body and gets processed.

3:44

And the results of that processing are

3:47

individual molecules, amino acids and

3:49

sugars and so forth that then distribute

3:52

throughout the body go into individual

3:55

cells and enter this process that we

3:58

call metabolism and we call cellular

4:00

metabolism.

4:01

And I think it's reasonable to think of

4:04

cellular metabolism as almost like a

4:07

map. There's an entry point. A molecule

4:09

of glucose or sugar comes into a cell

4:12

and that sugar can be chemically

4:14

modified in a variety of ways to fulfill

4:17

the needs of that cell. And then that

4:19

cell does whatever it needs to do with

4:21

the molecules it takes in to fulfill its

4:25

particular functions. And then that

4:27

leads to the um release of waste

4:29

products that we eliminate from our

4:31

body. And that is sort of the organismal

4:34

metabolism, the metabolism of our body.

4:37

And as you allude to, I think something

4:41

that maybe many people don't understand

4:44

is that cellular piece of it. The

4:47

metabolism of our body is really the sum

4:50

total of the metabolism of each one of

4:54

our 30 trillion cells or so. That's

4:56

really where my passions lie are those

4:59

individual cells and how they choose to

5:02

take up certain nutrients, how they

5:05

choose how to process them, turn them

5:07

into other things, how they use them to

5:10

fulfill their particular functions, and

5:12

how that's regulated. the masterful

5:15

coordination of each of those cells

5:19

working together to allow us to be

5:22

sitting here talking to one another and

5:25

go out and run or whatever we do. It's a

5:27

beautiful orchestration, but that

5:30

happens at the level of of individual

5:32

cells. And I think that's one of the

5:33

fascinating things that is maybe a

5:35

little bit less understood. if we were

5:37

to just take the single cell view for a

5:41

moment and I know that aging isn't a

5:43

like your specific area of interest but

5:45

one thing that's always intrigued me

5:47

because my postto adviser once came down

5:49

the hall and said why do I have so much

5:51

less energy than I used to and he had a

5:52

ton of energy so that I like I wonder

5:54

what he used to be like but it's a great

5:56

question he used to do this every once

5:58

in a while like just ask these very

5:59

basic questions that no one else on our

6:01

halls at Stanford could really answer

6:03

why does a kid have so much energy and

6:06

when we're older We don't what people

6:07

say well people are moving less the

6:09

tissues are wearing out but at the level

6:12

of energy production are we aware as

6:15

biologists at this point in history as

6:17

to why a young cell could be muscle cell

6:20

it could be neuron whatever versus an

6:23

older version of that cell why it it

6:27

either produces less energy I don't know

6:29

if it does I'm guessing it might but why

6:31

the whole body just seems to have less

6:33

get up and go do we have an answer for

6:35

Yeah, I think we have a partial answer

6:38

for that. I think that's a that's

6:40

definitely a frontier of science is

6:42

trying to understand exactly what goes

6:44

wrong during aging. There's many aspects

6:46

to it. As you alluded to, one of my

6:48

passions also is the mitochondria. And I

6:51

think it's almost universally the case

6:54

that mitochondria become less energized,

6:57

less effective, let's say, as we age.

7:00

And the reasons for for that are to some

7:03

extent clear but I think largely unclear

7:06

but that is definitely a feature of the

7:09

aging process. You know there there is

7:12

this sort of aspect of accumulation of

7:15

damage. You know living in the world we

7:17

live in as I alluded to before this

7:19

orchestration of metabolism that happens

7:22

throughout the body. That's hard. It's

7:24

expensive. And it's expensive not only

7:26

in terms of what we need to eat to fuel

7:28

it, but it's expensive in terms of the

7:30

damage that can come as a side effect of

7:32

that. And the accumulation of that

7:35

damage over time is certainly correlated

7:38

strongly with aging. And I think there's

7:40

some really nice evidence in models

7:43

where we can do genetics, you know, in

7:45

in animal models that suggests that that

7:47

accumulation of damage is a big part of

7:50

the aging process. And it's a huge area

7:53

of interest in the field is trying to

7:55

understand how you can decrease the

7:58

onset of damage, how you can reverse

8:00

damage that comes. One thing that I like

8:02

about how you ask that question is

8:04

thinking about that in the context of

8:06

the cell, which again I don't think we t

8:08

tend to think of aging as a cellular

8:11

phenomenon, but I think fundamentally it

8:13

almost has to be. We are made up of

8:14

cells and the processes that lead to

8:17

aging are the accumulation of processes

8:19

that happen at the level of individual

8:21

cells. And I think in a way we're at the

8:23

precipice of understanding a lot of this

8:25

because of the tools that we are um

8:27

starting to have access to that will

8:29

help us better understand cause and

8:31

effect and the specific molecular

8:34

features of of the aging process. Let's

8:37

talk about mitochondria. Perhaps

8:38

surprisingly, I'm going to ask you why

8:40

you study them with the caveat that they

8:44

are incredibly interesting. They are

8:46

involved in energy production and

8:47

metabolism. But what what specifically

8:49

drew you to mitochondria versus all the

8:52

other pieces of cells or parts of the

8:55

body or organs that you could have

8:56

worked on? Why the mitochondria? What

8:58

what's so sticky about those as a place

9:00

to I mean you devote a significant

9:02

fraction of your life to them? Yeah,

9:04

it's an area of cell biology, an area of

9:07

sort of the details of how life works.

9:10

One of these things that is, in my view,

9:13

just a brilliant example of taking in

9:18

chemistry of incredible complexity and

9:21

making it work effectively

9:24

inside of a a living cell. Mitochondria

9:27

are believed to have been the result of

9:30

an endo symbiotic event where a

9:32

bacterium a free-living bacterium

9:35

was engulfed by another cell and in a

9:39

way kind of domesticated.

9:42

So wild to think about totally wild. I'm

9:44

sure people are following, but in case

9:45

there's somebody who's not,

9:47

>> what Jared is saying is that our cells

9:50

basically were invaded by a bacterium

9:54

and then that bacterium became part of

9:56

our stable genome going forward. It went

10:00

into the what we call the germ line and

10:01

therefore was propagated from parents to

10:04

kids. And so now mitochondria live in

10:06

us, but they didn't start off living in

10:09

us.

10:09

>> That's right. And I and we hear that

10:11

about the gut microbiome like we have

10:12

these trillions of bacteria that live in

10:14

us and we colonize and we can recolonize

10:15

take antibiotics and then you need to

10:17

replenish eat your yogurt and so on. But

10:19

but the fact that the mitochondria made

10:21

it stably into our genome and are

10:23

transmitted from one generation to the

10:25

next. We think of them as us but you're

10:28

saying there is solid evidence that they

10:30

came from outside of humans.

10:32

>> I think that's the only model that I

10:34

think any of us as scientists have any

10:37

good reason to believe. And you know

10:40

that's fascinating history, right? That

10:43

there was a bacteria and another cell

10:45

that got together and and together that

10:47

combination could do things that that

10:49

any one of either of them on their own

10:52

could not do and that they work together

10:55

in in some way to enable the evolution

10:59

of complex life. you know ukarotes which

11:02

are the the type of cell that resulted

11:04

from that combined situation that we

11:07

were just talking about. These are all

11:09

the organisms that we see around us.

11:12

Plants, animals, fungi even are all the

11:15

result of these two cells getting

11:17

together and making peace so to speak

11:21

and uh teaming up to make this

11:23

synergistic cell.

11:24

>> Is it synergistic? for forgive me for

11:26

interrupting, but when I think about

11:28

viruses, I think viruses have their own

11:30

sort of intelligence. They kind of they

11:32

hijack the genomes of cells and they

11:33

either kill those cells or if they're

11:35

really smart, they keep them those cells

11:37

alive and use those cells to continue to

11:39

live and then propagate through like the

11:41

behavior of an animal like the rabies

11:43

virus like, oh, let's get this animal

11:44

aggressive so that it bites and then I

11:46

mean viruses don't think, but they have

11:48

an intelligence. Do we know that the

11:50

mitochondria were benefiting the cells

11:52

and the cells were benefiting the

11:54

mitochondria or could have this been a

11:56

takeover by the by the mitochondria?

11:58

>> I mean, this is a a bit of a

11:59

philosophical question. Of course, we

12:02

don't have a record of of what exactly

12:04

happened when and who benefited in real

12:06

time, but one thing we do know is all of

12:09

complex life resulted

12:12

from cells that underwent that event.

12:14

One time or multiple times, but all of

12:16

complex life evolved from that. And I

12:19

think that tells us that more than

12:20

likely complex life could not result

12:24

from a bacteria on its own or the archa

12:29

the the the cell that became the host

12:31

for that bacteria. So I think you can

12:35

make a compelling argument that this was

12:37

beneficial. And one reason it was

12:39

beneficial because it enabled a form of

12:41

metabolism that wasn't possible before

12:44

and enabled now a more complex cell to

12:47

be able to do things metabolically to be

12:49

more metabolically efficient and and and

12:52

diversified that it could enable you

12:54

know again complex life to evolve and

12:57

totally fascinating history but I think

13:00

as you alluded to also has very

13:03

interesting implications for life today.

13:06

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13:08

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15:16

Could we explore a little bit of how

15:19

mitochondria getting into these cells

15:20

were able to make it stably into their

15:22

genome and propagate? This isn't going

15:24

to be a conversation about genetics per

15:26

se, but I maybe as a just two points of

15:29

background for people like if any of our

15:31

cells have something put into them, but

15:33

let's say a physical object like a

15:35

splinter, little tiny piece of splinter

15:37

stays in the cell and then you procreate

15:39

with somebody, you don't expect that

15:40

child will have that little bits of

15:42

splinter in their cells. But if the germ

15:45

line, right, so the the eggs or the

15:47

sperm have something incorporated into

15:49

them, then potentially it could

15:51

propagate is why they call germline as

15:53

opposed to sematic cells. I think most

15:54

people aren't aware of that. It makes

15:55

perfect sense once you hear it, but

15:57

you're talking about many, many, many

15:58

years ago

16:00

>> a cell having this bacterium go into it

16:03

and then it was somehow able to stably

16:06

represent itself in the genome. So that

16:07

that propagated forward and eventually

16:10

>> it has to be in the germ line of

16:11

whatever you know primordial homo

16:15

sapiens were there otherwise

16:18

>> your kids I you wouldn't have

16:19

mitochondria in us how do we think that

16:22

might have happened

16:23

>> the main genome of the cell the cellular

16:26

genome DNA contained typically in the

16:29

nucleus of the cell mitochondria exists

16:32

in the cytool outside the nucleus one of

16:35

the interesting things about

16:36

mitochondria which I think is totally

16:38

fascinating and has really interesting

16:40

disease implications and worthy of

16:43

talking about. We may or may not come

16:44

back to it is that mitochondria have

16:47

their own separate genome that is sort

16:49

of a relic of the bacterium that they

16:53

are the descendants of. It's in a circle

16:55

like the bacterial genomes. Whereas the

16:58

nuclear genome of a ukareotic cell is

17:01

linear chromosomes. And that genome

17:04

performs very essential functions and

17:06

codes very important proteins that

17:09

enable our mitochondria to function as

17:12

the powerhouse of the cell which we uh

17:15

know them to be to enable the extraction

17:17

of usable energy from the food that we

17:19

eat. So, as you alluded to, those

17:22

cytoplasmic mitochondria

17:25

somehow make it from generation to

17:27

generation. And one of the interesting

17:28

features of them being cytoplasmic

17:31

is they're completely inherited from the

17:35

mom, from the egg, cuz as you know, when

17:38

the sperm invades the egg, the the

17:40

genome from the sperm gets into the the

17:42

egg, fertilizes it. The cytoplasm of the

17:45

sperm does not. So the mitochondrial

17:48

genome of you came completely from your

17:51

mother. Mine came completely from my

17:53

mother. And again that has interesting

17:55

implications for the inheritance of uh

17:58

diseases that are mitochondrial on

18:00

origin. But that's sort of how we think

18:03

it works. It basically propagates from

18:05

the egg upon fertilization. Then it gets

18:09

distributed to all the cells including

18:10

the the germ line that that fertilized

18:13

embryo will have and then gets passed on

18:16

to the next generation in [snorts] the

18:18

same way

18:18

>> ratcheting toward the actual functioning

18:21

of mitochondria. Maybe um you give a

18:24

beautiful picture of the mitochondria

18:26

not uh in the nucleus of the cell but in

18:29

the cytoplasm. So still inside the cell

18:31

and most people probably remember from

18:33

their high school biology a picture of a

18:34

cell always looks round. Mhm.

18:36

>> I'm guessing you're going to tell us

18:37

that the mitochondria can be distributed

18:40

lots of places in a cell cuz a lot of

18:42

cells aren't round. A lot of them look

18:43

hairy or they have long extensions like

18:45

neurons.

18:47

Is it fair to say that you can find

18:48

mitochondria everywhere in a cell? So no

18:51

matter what shape it is, it's got

18:52

mitochondria everywhere. And if so, what

18:53

is the importance of having mitochondria

18:56

distributed spatially through the cell?

18:58

So maybe we go so people know where

18:59

we're going. We we'll talk about the

19:00

spatial distribution because it turns

19:02

out that's very important. We'll talk

19:03

about the functioning and then I want to

19:05

talk about time as a factor and that can

19:07

be a little bit abstract for people. So

19:09

we'll come to that.

19:10

>> Yeah. Spatially,

19:12

you know, I I one of my scientist

19:14

colleagues might call me on this but to

19:16

my know I can't think of a place that

19:18

exists in cells where there aren't

19:20

mitochondria.

19:21

And I think as you alluded to I it's a

19:23

little bit dangerous for me to talk

19:25

about neurons with a neuroscientist. I

19:27

am not a neuroscientist but one of the

19:30

brilliant bodies of work that's been

19:32

done on mitochondria has been done in

19:34

neurons. It's fascinating these these

19:37

neurons that have one meter long

19:38

projections and mitochondria

19:42

transit from the cell body down those

19:44

projections and as best we can tell

19:48

those mitochondria play essential roles

19:50

at the ends of those projections

19:52

typically being able to generate again

19:54

usable energy. They're extracting the

19:57

energy from the food that we eat and

20:00

powering the neurotransmission the the

20:03

functions of those nerve nerve

20:04

terminals. And I think that's true of

20:06

virtually every cell in our body. The

20:08

extraction of energy and turning it into

20:10

use a usable form typically in the form

20:12

of ATP adenosine triphosphate. Obviously

20:15

that is the energy currency that's used

20:18

by almost every cell in our body and

20:20

that is a key function of mitochondria.

20:22

We'll probably come to functions of

20:24

mitochondria that are outside of just

20:27

extracting energy, but that is a

20:29

critical function of mitochondria and

20:31

that ATP is needed in virtually every

20:35

place of every cell and by having local

20:39

production that makes it more efficient.

20:41

So I think spatial distribution is a key

20:42

part of that. It's fascinating. There's

20:45

been beautiful work that's shown that

20:48

when a cell is crawling as cells

20:49

sometimes do you know like an immune

20:51

cell that sees something it's chasing

20:55

there will be a distribution of

20:56

mitochondria towards that leading edge

20:59

of the cell which is very energetically

21:02

expensive to crawl for a cell requires a

21:05

lot of ATP and mitochondria will

21:08

congregate at that leading edge where

21:09

that ATP is being consumed to make ATP

21:12

right there so it can be used I think

21:14

it's fascinating example of that local

21:17

uh demand for energy.

21:19

>> I'm asking some highle questions I

21:21

realize, but is there any reason to

21:24

believe that a a given mitochondria

21:26

knows what cell it belongs to?

21:28

>> Like the like are they different? Is is

21:31

are the mitochondria in one cell type so

21:33

very different than the mitochondria in

21:34

another cell type? or the mitochondria

21:36

between like let's say a neuron of the

21:38

eye versus let's get out and since

21:41

you're saying you don't want to talk

21:42

neurons as a per se like is two adjacent

21:45

skin cells they're both skin cells they

21:46

have mitochondria in them but do they

21:48

know which cell they belong to

21:51

>> and do your mitochondria I'm guessing

21:53

because they came from your mom's genome

21:55

they know that they're different than my

21:56

mitochondria but how much identity do

21:59

they have

22:00

>> yeah I would say this is a topic that is

22:02

at the frontier of what we No, you're

22:05

you're asking some questions that are

22:07

right at the edge of our current

22:09

knowledge. Yeah, mitochondria are

22:11

different. To a first approximation, you

22:13

could say that virtually every cell in

22:15

our body has slightly different

22:17

mitochondria

22:18

that are particularly suited to the

22:20

demands of that cell. a heart muscle

22:23

cell, a cardiammyioite, that cell

22:27

kind of has one job and that's to

22:30

contract

22:32

every second of every minute of every

22:34

hour of every day for our entire life.

22:36

And when it coordinates that contraction

22:38

with the other cells in the heart, that

22:40

enables our heart to beat. That's what

22:42

its job is.

22:43

>> Is there any turnover of those cells? We

22:45

know neurons don't tend to turn over.

22:46

>> Very little. Very little.

22:48

>> Well, that's reassuring.

22:48

>> Very very little. I'm glad you

22:51

>> you can imagine that it would be hard to

22:53

replace that in real time, right? That's

22:55

a I'm a hockey fan and that's a change

22:57

on the fly scenario of biblical

23:00

proportions. So that those

23:01

cardiammyioytes,

23:03

>> their mitochondria is wired

23:06

>> to consume whatever it has available and

23:08

make ATP because that ATP is is going to

23:11

be incredibly important to enable that

23:13

contraction of that cell and the beating

23:15

of the heart. mitochondria and other

23:17

cells. For example, like cells that line

23:20

that that are the stem cells that that

23:23

enable our intestinal lining to be

23:27

turned over every 5 to seven days, which

23:30

is amazing. By the way,

23:31

>> your whole gut

23:32

>> your whole gut is turning over every 5

23:34

to seven days. The the lining of that of

23:36

your gut, it is it is amazing. Those

23:39

stem cells, ATP

23:42

is not the major demand of those of

23:44

those cells. They need to completely

23:47

duplicate themselves constantly every

23:51

day or less. So their metabolic program

23:56

is very different from a cardiammyasite

23:58

which just needs to make ATP to a first

24:01

approximation. They need to make a whole

24:03

new cell. So we talked about you know

24:06

the metabolism of of the organism. The

24:08

metabolism of those cells is very

24:11

complex because it needs to replicate

24:13

all the DNA, duplicate it to go into a

24:16

new cell, duplicate all the proteins,

24:18

duplicate all the membranes, the lipids,

24:21

and that needs to happen rapidly. And so

24:24

that metabolic wiring is is completely

24:27

different. And again, the mitochondria

24:29

are fundamental to that. So those

24:31

mitochondria

24:33

are wired in a way that enable them to

24:36

produce

24:38

the biomass that's required to make a

24:40

new cell quite different from the

24:42

mitochondria of a cardiammyioite. And

24:44

that diff distinction plays out in

24:46

virtually all cells in our body, right?

24:48

Every one of our cells has some

24:50

particular purpose, some particular

24:52

function that it serves uh for the body

24:55

and the demands of the mitochondria

24:57

therefore of that cell are different

25:00

depending on the unique functions and

25:03

demands of that cell. And so it's a

25:05

fascinating topic, this diversification

25:07

of mitochondria. I think again that's

25:09

something that we're learning about. One

25:11

of the developments that's really been

25:13

happening over the last few years, very

25:16

much a frontier field, is you might

25:18

imagine a cell that has a complex set of

25:22

demands. There's actually evidence most

25:24

prominently published recently by Craig

25:26

Thompson at at Sloan Ketering that

25:28

showed that in one cell you can have two

25:31

different kinds of mitochondria that

25:33

have two different functions and they're

25:35

distinct in one cell.

25:37

>> What what's each of them doing?

25:39

>> Yeah. One of them tends to be more

25:40

biosynthetic, maybe producing biomass,

25:43

and one of them tends to be more energy

25:44

extracting and producing ATP. That's a

25:47

an overly simplified but generally

25:49

accurate way of thinking about it. It

25:51

really emphasizes this unique function

25:55

of of mitochondria that can be adapted

25:58

again for the needs of the cell.

25:59

>> Okay. So, I eat some food and uh that

26:02

food's absorbed and I get glucose

26:04

circulating in my bloodstream. I've got

26:05

some stored energy in the form of

26:06

glycogen etc. And I'm curious how greedy

26:10

are the different mitochondria? Is the

26:12

name of the game that every cell is

26:13

trying to get as much energy as it can

26:16

to produce as much ATP as possible or

26:18

are they communicating and is it energy

26:20

being allocated in some way that's a

26:23

little bit more um democratic that's one

26:26

question then framed within that um I

26:28

could imagine two scenarios one non

26:31

mutually exclusive where like the

26:32

vasculature just distributes the glucose

26:34

very well to everything so everybody

26:36

every cell gets gets access to some of

26:38

this glucose and and then is just greed

26:41

needy trying to make as much ATP as

26:43

possible and the whole system works

26:44

beautifully. I could also imagine a

26:46

situation where there's some shuttling

26:48

to important structures like the brain,

26:51

you know, like keeping you alive like

26:52

breathing, heart that there's a

26:54

prioritization of of organs. I'm talking

26:56

about under non-stressful conditions.

26:58

>> So, yes. So, how is energy allocated to

27:00

cells and then how are cells divvying up

27:02

the the goods? Yeah, it's a brilliant

27:05

question and a fascinating area of

27:07

physiology. As you allude to, when we

27:10

eat, our digestive system starts

27:12

extracting the constituents of what we

27:15

eat. Again, sugars, amino acids, fats

27:19

from that food that then triggers

27:21

signals of different kinds, GLP-1 being

27:24

one, insulin being another. Those

27:28

signals then are hormones. They get

27:30

secreted and they go to many cells

27:32

throughout the body and that tells each

27:34

individual cell we just ate. And the

27:38

implications of that are different from

27:40

each cell. Some cells don't care. Some

27:42

cells don't pay attention to that and

27:43

they just keep on doing what they were

27:45

doing. Some cells care a lot. Aipocites

27:48

for example, these are the fat cells,

27:50

the cells that make up our fat tissue.

27:53

They care a great deal about that. And

27:55

when they see insulin, what they do is

27:59

they turn on a protein. They start

28:01

making a protein that will cause glucose

28:04

to be taken up into that adiposite, that

28:08

fat cell. And that glucose will then be

28:11

converted through a series of chemical

28:12

reactions into a fat molecule. And then

28:15

that fat molecule will be stored away in

28:18

a way that is very safe and enabled to

28:21

be stored for potentially a very long

28:23

time.

28:25

And again, it's a beautiful way for the

28:27

organism to coordinate.

28:30

I just ate our energy status as an

28:34

organism, as a body is great. It's very

28:37

good. So let's squirrel away some of

28:40

that energy in the form of fat that can

28:45

be stored in our adiposytes again very

28:47

safely and can be then used when we go

28:50

through a period of prolonged fasting

28:52

which doesn't happen for us all that

28:55

frequently but happened for our

28:56

ancestors probably much more frequently

28:58

and those atyposites full of fat from

29:01

when we ate probably kept our ancestors

29:04

alive when they went through the periods

29:06

of prolonged fasting.

29:08

Insulin has other effects on muscle and

29:10

and other cells throughout the body that

29:12

again this is the brilliance of this

29:15

coordination. The response of different

29:18

cells to the fed state is different

29:20

depending on the the the needs and and

29:23

functions of that cell. Again, some

29:25

cells don't care at all. They're going

29:26

to just go about and do their business.

29:28

And some cells completely rewire their

29:31

function depending on the the metabolic

29:35

state the fed fasted state of the

29:37

organism. So the picture you just

29:39

described leads me to conclude that

29:43

basically every cell obviously knows its

29:46

job and is not greedily but is um

29:49

diligently fulfilling that role.

29:51

>> Yeah. And somehow the whole thing is

29:54

orchestrated so that like we work which

29:57

I know I think for some people it might

29:58

be like duh but like just like think

30:01

about that crazy

30:02

>> like a liver cell isn't really talking

30:03

to the brain cell in any kind of direct

30:05

way about how much glucose it has access

30:07

to. What you describe makes me really

30:10

understand for the first time the

30:11

brilliance of having this hormone signal

30:13

insulin not just as a shuttle because I

30:15

think most people we think like insulin

30:17

sensit most people listen to this

30:18

podcast or just existed in the world

30:20

today they're like oh you want to be

30:21

insulin sensitive you want your cells to

30:23

recognize this signal but we've never

30:25

actually talked on this podcast about

30:26

what exactly that signal is we think

30:28

about insulin as a shuttle

30:30

>> but the size of that signal is saying

30:33

what's likely to be there and I realize

30:36

has all sorts of cool implications that

30:38

can prepare the cell to like oh I'm

30:39

going to go to work hard now to be the

30:41

little squirrel that I am of a fat cell

30:43

and like squirrel away as much as I can

30:44

or be a brain cells like let's go

30:46

>> I'm ready to fire action potentials if I

30:49

need to and some cells like the photo

30:50

receptors in the eye are just doing that

30:52

>> eyes closed they're firing eyes open

30:54

well it's tricky but they're more or

30:56

less firing it's a not worth going into

30:58

obviously but in every one of these

31:00

cells mitochondria are the ones that are

31:02

essentially going to drive this ATP

31:04

>> thing right and that seems extremely

31:08

efficient, too, to just have essentially

31:10

one major cellular energy source. So, if

31:13

you could walk us through what happens

31:15

as glucose gets into the cell and and

31:17

and really what we've not done ever on

31:19

this podcast and I I don't think I've

31:21

heard elsewhere on any podcasts,

31:23

>> maybe it's out there, but is how you go

31:27

from ATP to actually the cell being able

31:29

to perform its roles. Yeah.

31:31

>> And I realize there's a lot of

31:32

biochemistry there, but you've worked on

31:34

some really lynchpin molecules in that

31:37

pathway that perform very specific

31:40

roles. And so like maybe we could really

31:41

talk about basically gets us from ATP to

31:44

pyuvate, which might scare some people

31:46

away, but you'll you'll educate us as to

31:48

why it's not scary. It's just super cool

31:50

and why it's so important to have these

31:52

signals that that aren't just like

31:53

chemicals. They actually mean something

31:55

for the cell. Cuz for me, forgive me for

31:57

going a little long here, but then I'll

31:58

shut up. I think if people can really

32:00

internalize this idea that yeah, like

32:02

hormones go up, hormones go down.

32:03

Cortisol goes up with stress, it goes

32:04

down. You wake up, cortisol goes up.

32:06

Melatonin when you're sleepy. It's not

32:09

just that it's there, but that the size

32:11

of the signal says a lot more than just

32:16

be sleepy. It's saying what once

32:18

happened is different than what's

32:19

happening now. It sets a stage for what

32:21

happens next. And this is really like

32:23

the verbs of biology that are harder to

32:26

communicate even in video. Yeah.

32:28

>> So, take us from glucose to ATP and ATP

32:32

to this thing that we call energy.

32:34

>> Yeah, there's a obviously a lot to

32:36

unpack there. Glucose is the dominant,

32:40

let's say, carbohydrate, the dominant

32:42

sugar that most our cells are consuming.

32:45

And when glucose is brought into a cell,

32:47

it goes through again a series of

32:48

chemical reactions that we call

32:50

glycolysis.

32:52

And I I'm going to simplify because

32:54

there's obviously this is the subway map

32:56

of New York. There's a lot of branches

32:58

going all over the place that we're

32:59

going to

33:01

>> go north or south.

33:02

>> North and south,

33:03

>> which is pretty much the only direction

33:04

you can go on the cell. I'm I'm not a

33:05

New Yorker. I'm kidding. I realize you

33:06

can go across across the aisle.

33:08

>> Yeah. Don't insult the New Yorkers

33:09

anymore. Yeah.

33:10

>> So glucose

33:12

comes into a cell, goes through a series

33:14

of chemical reactions, and you mentioned

33:16

it gets to pyrovate. That's the end

33:18

point of glycolysis, this set of

33:20

chemical reactions. And then pyrovate

33:23

there's a decision that has to be made

33:24

by that cell. It can either

33:29

take that pyrovate into the mitochondria

33:31

and burn it essentially

33:34

oxidize it which is essentially burning

33:36

it combining it with oxygen and that is

33:38

a very effective way to extract all the

33:41

energy that can be extracted from that

33:44

glucose via pyrovate.

33:46

>> Tell us a little bit about pyrovate.

33:48

Yeah. What's the best way to like

33:50

conceptualize pyuvate for for somebody

33:52

like me?

33:53

>> It's an intermediate. It's a midpoint

33:56

let's say from glucose. Glucose is a

33:58

sixcarbon molecule complex chemical

34:01

sixcarbon chemical that gets again

34:04

chemically modified down to this

34:06

pyrovate which is as I alluded to in a

34:09

way kind of a pivot point

34:12

>> in the metabolism of that glucose. And

34:15

the reason why we became really

34:17

fascinated with pyrovate

34:19

is because of that bifurcation that

34:22

happens. Pyrovate can either be again

34:25

taken into mitochondria and burned and

34:27

that's very effective for generating ATP

34:29

for extracting all the energy that can

34:31

be extracted and that's what

34:33

cardiammyioytes for example really love

34:35

to do take that everything they can from

34:39

the circulation burn it make ATP keep

34:42

our heart pumping and again other cells

34:45

on the other hand don't do that they

34:47

don't need as much ATP so those

34:49

intestinal stem cells that I talked

34:51

about that are the factory in a Okay,

34:53

that's enabling the repopulation of our

34:55

gut lining every week. They do something

34:59

different with that pyrovate. They

35:01

instead of burning it turn that pyrovate

35:04

and other molecules intermediates in

35:06

glycolysis into biomass into the stuff

35:10

that will enable that one cell to

35:11

duplicate itself. And I've become

35:14

totally fascinated with this

35:17

bifurcation.

35:19

Food can either be converted to energy

35:23

or it can be converted to biomass. I

35:26

think that's maybe a bit overly

35:27

simplistic, but I think a good baseline

35:30

way to think about the what we get out

35:34

of the food that we eat.

35:36

Energy or building blocks that can be

35:40

used to make a new cell to repair a cell

35:43

that's been damaged for a B cell and

35:45

immune cell that are the ones that make

35:47

antibodies. making a bunch of

35:49

antibodies, which an activated B cell

35:51

needs to do. That's a lot of stuff that

35:53

needs to be made. That requires that B

35:55

cell to have a lot of amino acids that

35:57

can be turned into proteins, which are

35:59

antibodies are proteins. And and and

36:02

that again, that's a very important part

36:04

of our immune system that keeps us

36:05

protected from invaders that might

36:07

otherwise kill us. And so that that

36:10

distinction that lands at the point of

36:12

pyrovate I think is a is a super

36:14

fascinating pivot point in metabolism

36:17

that I think many of us are fascinated

36:19

by exactly how the cell

36:22

>> organizes itself to make the right

36:25

resource allocation decisions. You know

36:27

every one of our cells is all every

36:30

second of every day is making resource

36:32

allocation decisions. What does it do

36:35

with the stuff that it has? And and this

36:38

is one that I think is really

36:40

fascinating.

36:41

>> So we are probably like seven I'm

36:43

insulting the cell biologists but

36:45

probably seven steps away from sandwich.

36:47

So sandwich goes in the mouth into the

36:50

gut gets absorbed right we get glucose.

36:52

Glucose gets into the cell. We got some

36:55

important biochemistry that you know is

36:57

in this uh ATP generation pathway and we

36:59

get to this like key node that you're

37:01

describing as pyuvate and pyuvate is

37:04

either going to say let's make more you

37:06

called it biomass but stuff of cells.

37:08

>> Yeah.

37:09

>> So we're like you have lumber arriving

37:11

maybe might be a decent enough analogy.

37:13

You're either going to use it to build

37:14

more house or you're going to burn it

37:16

>> for heat energy.

37:18

>> Great analogy. Um, and let's look make a

37:21

add a condition where you need to burn

37:23

some of that lumber for heat energy to

37:25

keep the construction project going.

37:26

>> Exactly.

37:27

>> Okay. So, we're at this key bifurcation,

37:29

this key split point. Is it just as

37:31

metabolically demanding for a cell to

37:36

use pyuvate to keep itself going like a

37:39

cardomyioite versus making biomass or is

37:41

one more costly? I'm thinking again as

37:44

you beautifully pointed out at the

37:45

beginning about thinking about that our

37:47

metabolism as a whole body as a person

37:50

is is the sum total of all these these

37:52

things is it equivalent in terms of like

37:56

>> how much sandwich relatively speaking is

37:58

going into maintaining us and rebuilding

38:00

us what you call biomass what I'm

38:02

calling building you know allocating

38:04

lumber for the for the house itself

38:06

>> versus to uh fuel the fire so to speak

38:09

>> that's hard math to do there's a lot of

38:11

nuance rough percentages. I won't hold

38:13

you to it.

38:14

>> Yeah. No, I mean one way to think about

38:16

that, many of us are probably

38:17

unfortunately aware of PET imaging,

38:20

right? This is this is something that

38:21

happens that's often used to diagnose

38:23

cancer

38:25

emission tomography.

38:26

>> An FDG PET, which is the most common

38:28

form of PET, is basically you're giving

38:31

cells a form of glucose that can then be

38:33

visualized with this PET scan that many

38:37

people are aware of. And the reason we

38:39

do that is because tumors

38:43

take up a lot of glucose and FDG PET is

38:46

fluoroxy glucose. This is a a labeled

38:48

version of glucose. So the reason we do

38:51

FDG PET is to see the cells where in the

38:54

body is taking up a lot of glucose and

38:57

tumors take up a lot of glucose. So FDG

39:01

PET is used to diagnose cancer

39:05

frequently very effectively. So that is

39:07

one metric for this. A cancer cell is

39:10

again a cell that is making a resource

39:13

allocation decision all the time. But in

39:15

the context of of that cell when it

39:18

transforms into a cancer cell that

39:20

resource allocation becomes very much

39:22

about building more cells. That's why a

39:25

tumor is a tumor is because that one

39:28

cell that was the first bad actor

39:31

decided instead of doing the thing it

39:33

was supposed to be doing decided to

39:34

duplicate itself and duplicate itself

39:37

again and build a cluster of cells that

39:40

then become a tumor.

39:41

>> Okay. I have a pseudo philosophical

39:44

question but it's really a scientific

39:46

medical question about tumors. Bacteria

39:49

have the opportunity to hijack genomes

39:51

of cells. viruses certainly probably the

39:54

the easiest example for people to

39:55

understand is like a herpes virus like

39:58

HSV1 or something which lives on neurons

40:01

>> doesn't kill the neuron which is

40:03

convenient for the virus

40:04

>> right because if it killed the neuron it

40:06

too would die because if the neuron is

40:08

expressing that virus it's hijacked the

40:11

genome

40:11

>> so this earlier I was saying like

40:13

viruses have their own quote unquote

40:15

intelligence

40:16

>> like stay alive but keep the host alive

40:18

too and transmit and in the case of

40:21

rabies it's the most easiest one to

40:23

conceptualize like impact areas of the

40:25

brain that trigger aggression would that

40:27

trigger

40:27

>> right

40:28

>> biting and and people have speculated

40:30

like does the virus know that it's doing

40:31

this like probably not right doesn't

40:33

they're not brains but pretty impressive

40:35

level of quote unquote

40:37

>> uh adaptive behavior and intelligence

40:41

>> I think of cancer as just a bad thing

40:43

all around right that these cells are

40:45

greedy they're taking glucose they're

40:47

making more of themselves it's cell

40:49

turnover gone arry tumor gets big, it

40:52

starts to encroach on other tissues,

40:54

metastasize, boom, you kill the host.

40:56

>> That's not a great strategy from the

40:58

perspective of the tumor. So, it

41:00

obviously isn't thinking about its

41:01

long-term outcome in any kind of

41:03

adaptive way.

41:04

>> But has anyone ever looked at tumors in

41:06

the same way that we think about

41:07

viruses? Like the logic there is the

41:09

same.

41:10

>> Yeah.

41:10

>> Except it it seems that their goal is to

41:12

kill the organism. I'm not trying to

41:14

anthropomorphize about cells and

41:17

cellular processes, but I think

41:20

is there a a potential set of answers

41:22

about how to deal with tumors and and

41:25

think about cancer that could be

41:26

borrowed from any of those other

41:27

examples or am I or am I going down the

41:29

wrong path?

41:30

>> Yeah, it's an it's an interesting

41:31

question. You know, viruses and

41:32

bacteria, similar to how you were

41:35

describing viruses, some of the same

41:37

principles apply to bacteria in you

41:39

know, parasitic bacteria. Viruses, as

41:42

you allude to, their goal that, you

41:45

know, if you do want to anthropomorphize

41:47

them, their goal is to propagate, right?

41:51

They are under evolutionary pressure.

41:53

The way that that virus survives is to

41:55

make more of itself, go infect another

41:58

organism and have that other organism

42:00

make a bunch of additional viruses that

42:02

will then go and infect another

42:03

organism, right? That is the

42:04

evolutionary game

42:06

>> and that's what viruses do. And they're

42:08

very good at it. And you described some

42:09

really interesting biology where viruses

42:11

will actually affect the behavior of the

42:14

host to make them better at getting into

42:16

the next host. It's amazing.

42:19

>> I wish we had a better language for this

42:20

thing because intelligence is not really

42:22

it because it's not of brains,

42:24

>> but it's this adaptive logic.

42:26

>> Yeah, that's a good uh phrase for it,

42:28

adaptive logic that enables the survival

42:31

and propagation of that virus. And and

42:33

this is how evolution works, of course.

42:36

If that virus had a mutation that made

42:40

it better able to do that, that virus

42:42

then would infect better

42:45

>> and it would get into hosts better,

42:47

propagate better, and it would

42:49

eventually take over the population of

42:51

that virus. That is the process of

42:53

evolution. And I think again it makes

42:55

intuitive sense. You know, you asked

42:57

about cancer. Cancer is obviously

42:59

fundamentally different in one key way.

43:02

If I get a virus and I come in here and

43:04

we're sitting across the table and I'm

43:05

hacking and whatever and I spew across

43:08

the table at you, you might get the

43:10

virus,

43:11

>> get sick, build a bunch of additional

43:13

virus, and then you give it to

43:14

co-workers and that's viral propagation,

43:17

which we all sadly know about. There's

43:20

very little evidence that cancer is

43:22

infectious.

43:23

>> What about Tasmanian devils?

43:25

>> You know about this, right?

43:26

>> No, I don't know about this.

43:27

>> Okay, I don't know if this held up, but

43:28

there was this idea for a while. Someone

43:29

will tell us in the comments. This is

43:31

what's fun about doing this on the

43:32

internet.

43:32

>> That Tasmanian devils fight and that

43:35

there's wound induced propagation of

43:37

cancers. These very disturbing as an

43:40

animal lover, you know, very disturbing

43:41

images of these cute little animals with

43:44

these little teeth. They're they have a

43:46

viciousness to them and they have these

43:47

like tumors growing at the at wound

43:49

sites and it turns out those are cancer.

43:51

So there's somehow like

43:54

>> fighting and wounds and viral, it might

43:57

it might be bacterial. I don't know.

43:59

That's outside my expertise,

44:00

>> but there was this idea that you that

44:02

they could transmit cancers to one

44:03

another through fighting.

44:05

>> Interesting.

44:05

>> Which I thought was sad but fascinating

44:08

nonetheless. And Australia is a weird

44:10

place, you know.

44:11

>> A lot of stuff happens.

44:13

>> I mean, the world's upside down there,

44:14

so after all. No. Um but but right,

44:16

you're right. In general, yeah, we don't

44:18

actually think that um people are

44:20

catching cancers from one another.

44:22

>> So when you think about the evolution of

44:23

a cancer, the scope of that evolution is

44:26

different, right? The scope of that

44:28

evolution of a a cell in me

44:31

>> is limited to me.

44:33

>> Cancer cells undergo evolution in the

44:36

exact same way. You know, if one cell in

44:38

my body starts propagating, it acquires

44:40

a mutation that enables it to divide and

44:43

divide faster and maybe it, you know,

44:47

get out from underneath the limits that

44:49

are being placed upon it by the immune

44:51

system and by other systems that control

44:54

propagation of cells in the body. It can

44:56

then divide and divide again. And that's

44:59

basically the continuous process of

45:01

cancer development is the acquisition of

45:03

mutations that make that cell better

45:06

able to evade the immune system, to

45:09

duplicate itself, evade um the the

45:13

problems that would come with DNA

45:14

damage, which many cancers have, and to

45:17

continue to make it make cells that

45:19

survive. And that is in a way an

45:21

evolutionary process playing out at the

45:23

level of individual cells. But how that

45:27

interacts with the host is obviously

45:29

different because again a virus has this

45:34

sort of evolutionary drive to get from

45:36

one organism to to another to another to

45:39

enable its propagation.

45:42

Cancer you isn't fueled by the same

45:45

motivations let's say because again as

45:48

far as we're aware that very rarely if

45:50

almost never happens to get from one

45:52

organism to another. And so the

45:55

motivations are different, but the

45:56

evolutionary process underlying it, it's

45:59

the same principles at play in both.

46:02

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to save up to $350. I'll take us down

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48:38

going to talk about mitochondria and

48:40

pyuvate again and your contributions to

48:42

this critical node of where pyuvate puts

48:46

its efforts building more stuff of the

48:48

cell or using energy. Anytime I have a

48:50

serious cell biologist, which isn't that

48:52

often on this podcast, or somebody who

48:54

thinks about the pieces that make up us,

48:58

I try and ask this. I'm bothered by this

49:01

one thing I heard once, which is that

49:04

like it's so easy to think about

49:05

evolution. It's like, okay, we're all

49:07

adaptively trying to make more of

49:08

ourselves, care for our young, and go

49:10

forward. That's like what every spe

49:11

every you know, mamalian species does.

49:14

That all makes sense until I learned

49:16

about the gut microbiome from my

49:18

colleague Justin Sonnenberg and he said

49:21

you know every time you shake hands like

49:22

we exchange microbiome today

49:24

>> and we're sharing in the air and skin we

49:26

shook hands you see and like there is

49:29

this one model of like all of this

49:32

that's very purely biological that we

49:35

are just shuttles for the microbiota

49:37

>> and everything that we're doing like

49:40

building electric cars and uh holding uh

49:43

debates and protests and um sending kids

49:46

to school and all of that we think is

49:48

about us but the microbiota are just

49:50

like they've hijacked this process and

49:53

like they're not sitting there going

49:55

these [laughter] humans they think this

49:56

is all about them and we're just trying

49:58

to spread and make sure that we continue

50:00

and maybe long after they're gone we're

50:01

just going to keep going and I can't

50:03

poke any holes in this it's like too

50:05

good a theory but I keep hoping

50:06

somebody's going to tell me at least

50:08

from a purely biological perspective

50:10

that like that's not true but it kind of

50:12

scares me every once in a while I think

50:14

Maybe I'm just a bunch of micro biota

50:17

shuttle just the vehicle.

50:18

>> We're just a shuttle. But we got this

50:20

brain which is very convenient for them,

50:22

right? Because it makes me want to go

50:23

out and do things and I think about

50:25

failures and successes and how I want to

50:27

do better and what I want to do at

50:28

different stages and like maybe it's

50:29

just all about them getting as far and

50:31

wide as they can.

50:33

>> Well, unfortunately, Andrew, I'm not

50:34

sure I'm going to be able to provide you

50:36

the concrete proof that that's not true.

50:37

It's a it's a fascinating

50:39

>> kind of eerie, right?

50:40

>> Yeah, very eerie. We definitely don't

50:43

like to see think of ourselves as

50:44

anything other than the pinnacle of

50:46

evolution and the reason for everything,

50:47

>> right?

50:48

>> But there's no question to to your

50:50

point, the microbiome are the bacteria

50:53

that live in our gut and on our skin,

50:56

they're being driven by the same

50:58

evolutionary pressures that we've been

51:00

talking about for viruses and for us.

51:03

They're trying to propagate themselves

51:06

and fill the niche that they live in,

51:08

fill the little chunk of of the universe

51:11

that they live in and do it better than

51:14

their com their competing neighbors. And

51:17

if they can do that, then their genome

51:19

is going to get passed on and again and

51:22

again. And it's fascinating to think

51:23

about the role that we play for them and

51:26

they play for us. This is a phenomenon

51:28

that's been known for a long time, but I

51:30

think the implications of the microbiome

51:31

is something that really has only been,

51:35

I think, experimentally dealt with in a

51:37

really serious way in the recent decade

51:39

or so. And I think we're still learning

51:41

about the implications, but there's no

51:42

question that they're big. Tell us about

51:45

MPC 1 and 2. I'm asking about

51:47

biochemical steps and a key process of

51:50

energy production and and allocation.

51:52

And normally when people hear acronyms,

51:54

they don't understand. and they kind oh

51:55

my goodness like what are we doing here?

51:57

But like

51:59

I think it's so important that people

52:00

understand like this business of us this

52:03

metabolism having energy whether we're

52:05

young or old have a lot of it or less of

52:07

it healthy or dealing with cancer like

52:10

this is a key node and what I want to

52:12

know truly is how do you actually

52:15

discover something like this because and

52:17

this is where I think we we can really

52:19

illustrate the scientific process in a

52:21

way that like most people just don't

52:23

understand. You need cells first of all.

52:25

You need to be able to find the mic

52:27

mitochondria. You need to be able to

52:29

know what's ATP and what's pyuvate. And

52:31

then you know they're going to two

52:33

different pathways cuz someone else said

52:34

that and you can observe it down a

52:35

microscope.

52:36

>> Yeah.

52:37

>> But then how do you find this thing and

52:39

then tell us what it's doing perhaps or

52:41

tell us what it's doing. But I think it

52:43

would be very useful for people to get a

52:44

picture of how this is done because we

52:46

hear this stuff like oh this molecule MC

52:49

and people go oh is there a peptide for

52:50

that? It's like hold off. Let's think

52:53

about how we come to understand these

52:55

these essential aspects of oursel I

52:57

think would be so useful.

52:58

>> I appreciate you asking about that. It

53:00

allows me to reminisce a little bit

53:02

about the process of discovering that

53:04

which was you know a fun time in my

53:06

career and was fueled by the brilliant

53:08

people in the lab that did it. So MPC

53:11

this is a case where the acronym

53:13

actually makes sense. It's the

53:14

mitochondrial pyrovate carrier. So you

53:17

don't have to be a scientist.

53:19

>> Uh we did not name it. that was it was

53:20

named before. I'll I'll tell you that

53:22

one story cuz I don't like acronyms that

53:24

aren't informative.

53:25

>> MPC,

53:27

>> aptly named

53:28

>> is the carrier

53:30

>> that enables pyrovate to get into the

53:32

mitochondria. Mitochondrial pyrovate

53:34

carrier. That's what it does. Sits in

53:36

the mitochondria and basically provides

53:38

a very specific hole in the membrane to

53:41

enable pyrovate to get in so that it can

53:44

then be burned by the mitochondria to

53:46

again extract all the energy to make

53:48

ATP. That's that's basically what it

53:50

does. The history of this is really

53:52

interesting. It's been known for

53:55

60 or 70 years that mitochondria must

53:58

have a carrier to enable pyrovate to get

54:01

in. But it was not identified what that

54:05

protein was, how it worked.

54:08

And

54:09

fast forward to 2008 or nine or so, and

54:13

our laboratory had just recently become

54:15

again fascinated with mitochondria. I

54:18

would say the motivating piece of of

54:21

information that convinced us to start

54:23

working on mitochondria was the

54:26

realization that many of the proteins

54:30

that make up mitochondria that do the

54:33

stuff that mitochondria do we don't know

54:35

what their functions are and that

54:37

suggested that this organel powerhouse

54:40

of the cell we kind of I at least felt

54:43

like we knew a lot about what

54:44

mitochondria do there's mysteries there

54:47

that we don't have answers for. And so

54:50

we started just taking some of these

54:52

proteins that we know are in

54:54

mitochondria, we don't know what they

54:55

do, and trying to figure out what they

54:57

do. And two of those turned out to be

55:00

MPC1 and MPC2. Way back when I I

55:04

observed and was taught, I didn't do a

55:06

ton of this, that like if you want to

55:07

figure out what proteins are in a cell,

55:09

you get a bunch of those cells, which

55:11

you can do

55:12

>> and then you

55:13

>> you kind of grind them up and then you

55:15

run them through a bunch of columns and

55:17

like literally tubes.

55:18

>> Yeah.

55:19

>> And those tubes have filters that either

55:21

let big, less big, small, or very small

55:24

things through, what we call

55:25

fractionation, right? And then you kind

55:27

of test the the different stuff that

55:30

comes through for its ability to do

55:32

something in some sort of cell. It's

55:33

like how did you actually find MPC2? Was

55:36

it done by like

55:38

>> sort of hardcore what we call hardcore

55:39

biochemical purification? That was kind

55:41

of the old way of doing it. Or well, let

55:44

me ask this. Do we know the total number

55:47

>> of proteins in the in a given human

55:50

heart cell?

55:52

>> I think we know. Yeah, I think

55:53

>> we know everything that's in a heart

55:55

cell. I think we know all the proteins

55:56

in a heart cell. Again, you can get into

55:59

the nuances of slightly modified

56:00

versions, but we know the proteins

56:02

because they are encoded by our genome,

56:04

right? We know the human genome that's

56:06

been sequenced. We know what that is,

56:08

>> but we don't know that everything that's

56:10

expressed in a given cell. That's right.

56:11

>> That that's true. And there there are

56:13

some very interesting features there.

56:14

>> Can I sorry, I'm interrupting on

56:16

purpose. 20 years ago, could you say

56:18

what you just said

56:19

>> with much less confidence that I than I

56:21

can now? say heart cell, but we don't

56:23

actually know all the all the bits in

56:25

it. But now we do.

56:26

>> Now I think we we know

56:29

>> essentially everything. Again, there's

56:30

going to be subtle nuances that we don't

56:32

know, but I think we know almost

56:33

everything.

56:34

>> That's good.

56:35

>> Doesn't mean we know what all those

56:36

things do. And that's maybe the frontier

56:38

for the biochemistry frontier for the

56:41

next generation of scientists to to

56:43

figure out. We don't know what they all

56:45

do, but we know more or less what they

56:47

all are. knowing what they are but not

56:50

knowing what they do motivated us to go

56:53

take these two proteins that were in the

56:55

mitochondria.

56:57

We could make a very strong hypothesis

56:59

that they were important because they

57:02

were in every cell that has mitochondria

57:05

down to a yeast that's a single-sellled

57:07

organism and plants and animals.

57:12

Everything that has a mitochondria has

57:14

these two NPC1 and NPC2 proteins. And it

57:18

would probably uh take too long to

57:21

explain on this podcast this the

57:23

processes that we went through to try to

57:26

identify the function of this MPC 1 and

57:29

2, but this was a a brilliant

57:31

collaboration and I think one of the the

57:34

highlights of my career.

57:36

different people in my lab and in the

57:38

lab of my colleague Carl Thumbl that

57:40

worked together. Carl was a fly

57:43

geneticist or is a fly geneticist that

57:46

used his unique skills and and resources

57:49

and we were using yeast as a model

57:51

system as well as human cells and

57:54

triangulating all that data. We came up

57:56

with data that suggested that this might

57:59

be the mitochondrial pyrovate carrier.

58:01

these two unknown proteins that happened

58:03

to be sitting in the mitochondria and

58:05

that was now been validated many times

58:08

over that these are the proteins that do

58:10

this transport of pyrovate into the

58:12

mitochondria. It was a really fun time

58:15

for me as a scientist to to see that

58:18

happen. And you know, you kind of

58:21

alluded to this when you asked the

58:22

question, what was maybe even more

58:25

exciting than the discovery of the

58:27

mitochondrial pyrovate carrier, which

58:29

Carl and I did, and we published a paper

58:31

and the lab of JeanClaude Martin and

58:33

Geneva published a paper at the same

58:35

time showing the same discovery. What's

58:38

been really fun since then is to see the

58:41

implications of that and starting again

58:43

to understand what role this protein

58:46

plays in the allocation of that pyrovate

58:49

that we've been talking about because

58:51

now the MPC

58:54

is the first step towards one

58:59

destination of that pyrovate. So it kind

59:02

of pulls it into the mitochondria so to

59:04

speak and once that pyrovate is in the

59:06

mitochondria it's going to be used for

59:08

something in the mitochondria instead of

59:10

maybe being used for something else in

59:12

the cytool. And so that's been work that

59:15

that we've done a lot of since is what

59:17

are the implications of that. And I

59:19

think it's been exciting to see in

59:22

different cell types what that means.

59:25

And so cardiamyiotes for example again

59:27

these are cells that want to make ATP to

59:30

to allow cardiumes to continue to

59:33

contract. They need to extract every bit

59:35

of energy they can make as much ATP as

59:38

they can. They use this MPC extensively.

59:42

How do they ensure that that these

59:44

cardiammyioites make sure that they make

59:47

just enough to maintain themselves so

59:49

they they're not so busy burning up all

59:51

the lumber that they end up going, "Oh

59:53

my goodness," and the house fell apart.

59:55

>> Yeah.

59:55

>> Do they consistently devote 90% of of

59:57

their ATP to energy utilization and that

60:00

they just know 10%. Like how

60:02

quantitative are these these these

60:04

pathways?

60:05

>> Because you can't you can't have the

60:06

walls fall down. It doesn't matter how

60:08

much energy you produce, right? It's a

60:09

brilliant question and and it's

60:12

definitely not programmed like like

60:14

there's a a spigot with a diverter valve

60:16

that 90% goes this way and 10% goes that

60:19

way. What actually happens and this

60:21

doesn't just happen in cardiammyioytes

60:23

it happens in every cell is that

60:26

basically the cell is measuring the

60:29

outputs again to anthropomorphize and I

60:31

have to say there are some scientists

60:33

that hate us when we anthropomorphize

60:36

having an intelligence or an adaptive

60:38

logic. So it's okay.

60:39

>> I think you've provided cover for me to

60:41

do it on for cells. Then

60:42

>> cells basically are measuring

60:47

their resources all the time.

60:50

>> I think you could make a compelling

60:52

argument that every cell almost all

60:54

cells know how much usable energy ATP

60:58

they have all the time. And when it gets

61:01

low,

61:03

they will initiate a series of reactions

61:06

to that, responses to that to bring it

61:08

back up. They'll turn off processes that

61:11

use ATP. They'll start pulling glucose

61:14

out of the circulation to make more ATP.

61:17

There's this really profound response to

61:20

ATP depletion. And I think that's true

61:22

for many of the endroducts of our

61:25

metabolic map. Again, these are the the

61:28

the products of the metabolic map are

61:30

the amino acids that make proteins. And

61:33

the nucleotides that are required to

61:35

make DNA and RNA, our genome,

61:38

>> there's a greediness to all these cells.

61:40

If the fat cells are greedy, you could

61:42

really see a problem like if we're not

61:43

ingesting enough glucose. Let's let's

61:45

hold off on ketosis for a second and

61:47

alternate metabolic pathways. But we

61:49

will touch on it. But if the fat cells

61:51

are also very self- serving then you

61:55

know at some point are they just forced

61:56

to liberate this stuff. But like

61:58

ultimately fat cells just want to get

62:00

bigger and bigger and that but if this

62:01

cardomyite it doesn't have enough

62:03

glucose eventually it's like it could

62:05

shut down any number of things like you

62:07

can remodel the house down to you know

62:09

just the fireplace and a little bit of

62:11

structure around it but eventually

62:13

>> you need the resource. So then what

62:15

happens that atyposite liberates the

62:17

energy. Yeah.

62:18

>> And and cells everybody gets a little

62:21

bit and you just hang on. So it's a

62:23

famine type situation.

62:24

>> Exactly. I mean just as insulin tells

62:27

the body I just ate.

62:29

>> We're good. Take that energy that's

62:32

available in the form of glucose.

62:33

Squirrel it away. Use it. There are

62:37

hormones that do the opposite. Glucagon

62:39

is one of them. And glucagon again has

62:41

become a little bit more popular

62:43

recently because it's now being combined

62:45

in some of the GLP-1 uh more newer GLP-1

62:50

drugs. Glucagon is called a fasting

62:52

hormone. So glucagon in many ways does

62:55

the opposite of insulin. It will go to

62:57

the fat cell, bind to the vat fat cell,

63:00

tell the fat cell to take the fat that

63:03

it has squirreled away and release it.

63:06

And now that can go to other cells in

63:08

the body, the heart. Heart is very good

63:10

at consuming fatty acids that come from

63:13

atapost tissue. And so so that's good.

63:17

>> I'm actually relieved to hear that.

63:18

>> Yeah.

63:18

>> Right. Because if if god forbid there's

63:21

a shortage of food that lasts long

63:23

enough, like that's definitely an organ

63:25

I don't want shutting down.

63:27

>> Exactly. And and most of us have fat in

63:30

our fat cells. And and you could make an

63:32

argument that the key destination of

63:34

that fat is the heart to keep it alive.

63:37

And you know in a normal human I think

63:40

it's estimated 70 to 80% of the energy

63:43

extraction that happens in

63:45

cardiammyioytes and heart muscle cells

63:48

is happening from fat. You said under

63:50

fasted conditions is that

63:51

>> especially under fasted conditions but

63:53

even in fed conditions fat is is uh is

63:56

available for the heart to use and and

63:58

>> dietary fat or fat from adapocytes

64:00

>> both whatever fat is in the circulation

64:03

the cardiammyioite is pretty good at

64:04

taking it up and burning it making ATP

64:06

from it

64:07

>> yeah the brain likes glucose but it can

64:09

use maybe now we I'm not super versed in

64:12

in the ketogenic pathways but I know

64:14

that our brain can thrive on ketones

64:17

>> so carbohydrates are not quote unquote

64:19

essential. You know, all the ketogenic

64:21

folks love to say that there's no such

64:22

thing as an essential carbohydrate. That

64:24

doesn't change the fact that like the

64:25

preferred fuel source for most every

64:26

cell is glucose. But anyway, that's a

64:28

separate issue.

64:29

>> You don't want the brain to shut down

64:31

either.

64:32

>> Yeah.

64:32

>> So, if the form of energy changes, is it

64:37

still once you get to mitochondria,

64:40

pyuvate, MCP, and downstream, is it all

64:43

the same? is essentially like energy is

64:45

energy at that point or is or is there

64:47

are there multiple pathways depending on

64:49

the fuel source?

64:50

>> Yeah, the ability of neurons to consume

64:54

fatty acids is limited. I I think it's

64:57

traditionally been thought that it's

64:58

very close to zero. I think that's being

65:00

questioned now, but it's limited. As you

65:03

allude to neurons are particularly fond

65:06

of consuming glucose and use that

65:08

glucose to make their ATP. And you know

65:11

that obviously puts a very

65:15

stringent demand on the body to always

65:18

have glucose available. Glucose is one

65:22

of these things that's fascinating the

65:23

the systems that we have in our body to

65:25

maintain glucose. You know diabetes is

65:28

defined as high blood sugar. That is the

65:31

definition the clinical definition of

65:32

diabetes when basically our body does

65:35

not adequately limit the circulating

65:38

glucose and that is destructive damaging

65:42

but it's damaging on the in the course

65:45

of years right a person can live with

65:47

diabetes for years before succumbing to

65:49

it if glucose is too low you die within

65:53

minutes if not seconds and that I think

65:56

for a few different reasons but probably

65:58

the most important one is the brain

66:01

requires some amount of uh glucose to

66:04

keep it functioning. So you know again I

66:07

I alluded to this before this very

66:09

elaborate dance that is happening by

66:11

these individual cells taking up

66:14

different nutrients out of the

66:16

circulation

66:17

using them for their own unique purposes

66:20

and and neurons again are are very adept

66:22

at taking in glucose and burning it and

66:25

making ATP from it. I think again the

66:27

heart I I feel like is really

66:29

fascinating because it'll it'll eat

66:31

anything. It's an omnivore. Fats,

66:33

glucose, lactate,

66:36

ketones, amino acids. It will make ATP

66:41

out of just about anything that ATP can

66:43

be made out of. And again, that's

66:46

important for us to enable us to live no

66:48

matter whether we just ate or not. Heart

66:50

is very good at that. So I think this

66:53

elaborate dance that we have going on in

66:55

our body all the time between different

66:56

cells cells doing it different way

66:58

taking in different fuels and uh using

67:01

them for their unique purposes.

67:03

>> What is the consequence of eliminating

67:06

the M MCP a shuttle like you get like if

67:08

you take a mouse you're at the

67:10

University of Utah let's give a shout

67:11

out to Mario Kapi whose life story is

67:14

amazing who won a Nobel Prize for

67:16

essentially developing what are called

67:18

knockout mice among other things. um you

67:20

can eliminate genes to test the role of

67:22

a particular protein downstream of that

67:24

gene. If you make a mouse that lacks

67:26

these proteins, do you get a dead mouse?

67:28

So

67:29

>> they do not survive to birth. Yeah,

67:31

>> you can get sperm egg and a and that

67:33

somehow the

67:34

>> it can become a a mouse.

67:36

>> Yeah, it'll start to develop and then I

67:38

think if I remember right, it's about 12

67:40

or 13 days of development, which is

67:42

>> you know 2/ird of the way from

67:44

fertilization [clears throat] to birth

67:46

of the mouse, it will die and and you

67:48

won't get a live mouse. But what has

67:49

been done and and obviously you were

67:51

probably getting there is because of the

67:53

technologies that Mario developed and

67:55

then others following after him, we can

67:57

now make mice that lack the MPC only in

68:01

the liver or only in the heart or only

68:04

in the muscle or only in the brain and

68:06

many of these things have been done.

68:08

>> Sorry, I should have been given credit.

68:09

He developed a technology that would

68:10

allow for organ and cell type specific

68:13

deletions or additions of genes. forgive

68:15

me but you reminded me like in all much

68:17

to so

68:18

>> yeah and many people have been

68:19

contributing that technology and

68:21

different ways to use it for decades now

68:23

and as you might imagine given the

68:26

unique demands of

68:29

different cells the effects are

68:30

different the heart is again very

68:34

focused its metabolic program is focused

68:36

on generating ATP so what if we

68:39

eliminate the MPC in the heart so we

68:42

have now made ATP P generation from

68:45

glucose less efficient. We've we've now

68:48

cut off the ability to use mitochondria

68:50

at least in the conventional way. So I

68:52

actually think the results of that

68:53

experiment are fascinating and this is

68:55

work that has been done by a few

68:58

different labs. Akmed Clinton who's a

69:00

postoc now running his own lab at

69:01

Rutgers was the one who started this and

69:04

uh other people have contributed. What

69:06

essentially happens to that heart is

69:09

that it lives and the animal lives for

69:13

weeks after that. But eventually the

69:16

animals die. And when you look at what

69:18

they die of, they have a massive heart.

69:20

They die of heart failure. And what has

69:24

become clear as we've gone and done more

69:26

sophisticated analyses of this heart and

69:28

why they die. It's pretty clear that

69:32

they don't die from an inability to make

69:35

ATP

69:37

because they can burn other things to

69:38

make ATP. We talked about this. They can

69:40

burn fats. They burn fats just fine.

69:43

What they appear to die from, and I

69:45

would say I'm speculating a bit here, we

69:47

don't have all the answers to all the

69:49

questions, is they have made a resource

69:52

allocation decision that turns out to be

69:54

pathological for them. And instead of

69:57

using the glucose that they take in to

69:59

burn it and make ATP, they start making

70:02

biomass. That that again we talked about

70:04

that that bifurcation. We've eliminated

70:07

their ability to make ATP from it at

70:09

least as effectively and instead they

70:12

make biomass. They grow. And when

70:14

cardiamyioytes grow that creates

70:17

structural problems for the heart.

70:20

Almost every human that succumbs to

70:22

heart failure will end up with a big

70:25

dilated heart that's less effective at

70:27

pumping. And that's what we see in in

70:29

the mouse really. And that maybe tells

70:32

us something about the fundamental

70:33

importance of this resource allocation

70:36

decision. And this is obviously just in

70:38

the context of cardiammyioytes. But

70:40

again, that resource allocation decision

70:42

is happening in every cell in our body

70:44

all the time. And that's one reason why

70:47

I'm fascinated with this field is we're

70:49

just starting to understand how those

70:51

resource allocation decisions are made.

70:54

What are the implications of making them

70:56

correctly and incorrectly? And maybe

70:58

even more excitingly, can we go and fix

71:03

that? When a cardiamyioite or when a

71:07

heart more aptly is making a resource

71:10

allocation decision that is

71:12

pathological,

71:14

can we fix it? Can we find a a

71:16

therapeutic that will go and correct

71:19

that and rewire it in the appropriate

71:21

and healthy way and can that then

71:24

restore the proper function of the

71:25

heart? Again, I think we're at the at

71:27

the frontier of this field, but it's a

71:29

really exciting place that that our

71:32

field exists now where we're starting to

71:33

understand the problems and we're

71:36

starting, I would say, early in

71:38

developing the right agents to act and

71:41

to manipulate this metabolic map that

71:44

might be able to fix things. I'd like to

71:46

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73:24

So, is it fair to say that the

73:25

allocation of energy, which is made

73:27

pathologic in this mutant mouse, but

73:30

also in people who have these uh cardiac

73:34

conditions and die of heart attack

73:35

essentially. It's almost like the the

73:38

identity of the cells is screwed up.

73:40

They're still a cardommyioite,

73:42

>> but they're devoting too much energy to

73:43

making more of themselves and not enough

73:45

to to doing what they're supposed to do.

73:47

I have like two analogies that I want to

73:49

throw out there and maybe they they're

73:50

too much of a reach, but I love dogs. I

73:52

have a now a medium-sized dog. I used to

73:54

have a large dog. The larger breeds of

73:57

dogs live much shorter lives than the

73:59

smaller ones. And and we actually know

74:01

>> that's because of dosing of IGF-1, which

74:03

is a growth pathway thing. So there is

74:06

this like story about larger animals

74:09

within a given species tend to live much

74:12

shorter lives than the smaller variety

74:13

of that same species. There's some

74:15

exceptions to this, but there does seem

74:17

to be a sort of rule that like you can

74:20

either be big and live a short life or

74:22

you can be small and live a longer life

74:24

within certain species.

74:26

>> But there's also this thing about

74:27

heartbeats, right? Like this theory that

74:29

you only get so many heartbeats in your

74:30

life. The reason I I like these higher

74:33

level perhaps appropriate comparisons, a

74:36

lot of caveats there, is that like

74:39

ultimately when I think about life and

74:41

evolution and a propagation of species

74:43

and health versus pathology, it's all

74:46

about energy, right? It's like how are

74:48

you devoting energy? It can get into the

74:50

kind of mystical spiritual piece. That's

74:52

not our purpose. There's not my purpose

74:54

in in bringing this up now, but

74:56

>> it seems like at the cellular level and

74:59

at the subcellular level, which is what

75:00

you're describing,

75:02

>> the allocation of energy in this case is

75:05

the difference between life and death,

75:06

but but this this decision, you're not

75:09

telling us like, oh, you know, these

75:10

pathways I discovered along with others

75:13

are really like there's a a fan out of

75:15

like 50 different options. You're saying

75:17

make more

75:18

>> biomass, more of self, [snorts]

75:20

or use energy to be self. Mh.

75:23

>> And there seems to be like a critical

75:25

balance there. And I have another story

75:26

I could tell about how like if you look

75:28

at the data on longevity in different

75:30

athletes like the gymnasts, the

75:31

sprinters seem to live 3 to six years

75:33

longer on average than than others. And

75:35

the endurance runners are somewhere in

75:36

the middle. You look at very large

75:38

athletes like the powerlters and the um

75:40

moving aside all things of like use of

75:42

drugs in sports, you go like

75:44

>> the the sports where there's just a lot

75:46

more of somebody that's not good for

75:48

longevity and it really isn't. So there

75:51

does seem to be this balance between

75:53

size and the use of fuel to to build

75:57

more of oneself and the use of fuel to

76:00

just be oneself. And that self could be

76:02

a cell.

76:03

>> Yeah.

76:03

>> That self could be an organ.

76:05

>> That self could be a whole organism. And

76:08

I find that like not incidental, but

76:11

maybe I'm taking too many liberties

76:13

here.

76:13

>> Yeah. I mean that's a that's a complex

76:15

analogy. and and but I think one thing

76:18

that is very clear about about what

76:20

you're talking about is this sense of of

76:22

of identity in a cell. I that's a

76:25

fundamentally important phenomenon that

76:28

again we've known about for a long time

76:30

and there's been under an understanding

76:32

in some cell types in some ways about

76:34

how that identity is established and

76:36

maintained. But I think your question is

76:38

a really interesting one. To what extent

76:41

is disease associated

76:44

with loss of that cell identity? And and

76:47

cell identity is a bit of a squishy

76:50

parameter. You know, how do you measure

76:52

what a cell thinks it is? You know,

76:53

there's no function, right? So, yeah,

76:56

like when we had Max Crumbl on the

76:57

podcast, he was like, you know, every

76:58

one of your cells by the time you reach

77:00

our age, roughly, you know, in our 30s,

77:02

no, I'm kidding. in our 50s, early 50s,

77:04

is we're a mosaic of like our original

77:07

genetic makeup plus all these mutations

77:10

that have accumulated. Nobody likes that

77:12

picture. That's true. We're a patchwork

77:14

of like our former self and our newer

77:16

self.

77:17

>> That's one form of cell identity. What I

77:19

like here is that you're talking about

77:20

within an organ, within a cell type,

77:23

>> you sort of have a choice of a make more

77:25

of oneself or b just be you.

77:28

>> Yeah. So there's something like kind of

77:30

like to me conceptually sticky about

77:32

this notion of size versus use.

77:35

>> Yeah. I think I as you say I I think

77:38

that in a way we're talking again about

77:40

resource allocation allocating to energy

77:44

versus making more stuff that could mean

77:46

another cell or a bigger cell.

77:49

>> There's many examples of where making

77:52

more stuff instead of making more energy

77:56

is pathological. We talked about cancer.

77:58

We talked about the heart getting

77:59

pathologically bigger. Immune cells

78:02

becoming hyperactivated can lead to

78:03

inflammatory diseases. You know, there's

78:05

many examples of that.

78:07

>> So, I think this is all playing out at

78:10

the level of individual cells and what

78:11

you're talking about is obviously a

78:13

bigger uh conceptual framework in which

78:15

to think about it. But I think there is

78:17

that uh connection and I don't know this

78:20

is a bit non-scientific but I I do think

78:23

it's fascinating to understand the

78:27

historical philosophical ways that our

78:30

ancestors thought about the world

78:33

>> and we [snorts] find relics of that in

78:36

our science right that we can see

78:38

reflected in the discoveries that are

78:40

made today. I don't want to take us off

78:42

the biology, but if we can go down this

78:44

pathway a little bit more, you know, I

78:45

sometimes think about energy in terms of

78:47

human interactions and and I think most

78:49

of us can think of the extremes of

78:50

benevolent versus malevolent energy

78:52

exchange like like let's say somebody

78:55

like money is just

78:56

>> a tool, right? Like people say money is

78:58

energy. That sounds very like, you know,

79:00

like internety, but really it it can be

79:03

exchanged for something, right? We've

79:04

decided that. And if somebody steals

79:06

from us or they they promise something

79:09

and it turns out they overcharge us or

79:10

something like that like we

79:12

fundamentally understand the math there.

79:14

You said it was going to cost us this

79:16

much cost. You said it was going to be

79:17

this and instead I got that and this

79:19

isn't what I paid for. Right? But if you

79:20

look at human interaction and behavior,

79:23

the stuff that we consider malevolent is

79:26

usually when something when someone

79:27

perceives the energy has been stolen

79:29

from them. Usually in the form of time,

79:31

>> but often in the form of physical energy

79:33

because time is physical energy, right?

79:36

>> And then benevolent acts are generally

79:38

ones in which there's a either an even

79:40

or a kind of a um like a

79:44

>> net positive exchange of energy. And

79:46

this is like a lot of what structures

79:48

human interactions. Like I don't want to

79:50

take us too far. This is not a

79:51

psychology podcast, but think about this

79:53

all the time and like why I like zooming

79:54

down at the level of the cell is we can

79:56

find there there isn't going to be a

79:58

perfect relationship between the cell

80:00

and human interactions at large. But

80:02

this notion of no cell if it wants what

80:07

best for itself and therefore the organ

80:10

it resides in and therefore the

80:11

organism.

80:12

>> Yeah.

80:13

>> Can afford to really cheat itself.

80:16

>> That's right. like bring it down to like

80:18

the individual cell. You can't like the

80:19

cell can't afford to cheat itself,

80:22

>> right?

80:22

>> And if too many cells do that, you end

80:24

up with a big heart that doesn't pump.

80:26

>> Exactly.

80:27

>> So, it cheated itself.

80:28

>> Yeah.

80:28

>> For me, that's very useful. I don't know

80:30

if it is for anyone else. So, when I

80:32

think about like really critical

80:33

biology,

80:36

all these proteins, like which ones are

80:37

you going to study? Like, it's clear to

80:38

me now why this set of proteins is very

80:41

important. Yeah.

80:42

>> Very, very important. What I didn't get

80:44

was how you actually found it. So was it

80:46

that you knew there was a gene there

80:48

that coded for this thing of a certain

80:49

size? So you started making some what we

80:51

call recominant version of that and like

80:53

throwing it on cells seeing what

80:54

happened. Is that kind of the the steps

80:55

that went through?

80:56

>> We knew the protein was there. What we

80:58

didn't know is what it did.

80:59

>> Mhm.

81:00

>> And I would say the key discoveries of

81:03

that came from genetics. Basically

81:06

Carl's lab made flies that lacked the

81:09

MPC and we could then

81:12

>> they were actually alive. There's an

81:13

interesting story there that's probably

81:14

too in the weeds, but they live,

81:16

[snorts]

81:17

>> but they had specific manifestations

81:19

that we could analyze using

81:22

>> chemistry. [snorts]

81:23

And I'll tell you about the results of

81:24

that. We were studying it in other in

81:26

other cell types in yeast cells and in

81:28

human cells and studying the results of

81:34

losing these genes. You know, again,

81:36

this is what's enabled by doing

81:39

genetics. You know, Mario Capeki figured

81:41

out how to do this in mice and his

81:43

colleagues that gave us the ability to

81:45

do knockout mice. Other people have

81:47

enabled it in other species. And by

81:50

doing that and studying the results, we

81:54

could then deduce, oh, what's happening

81:57

in these yeast cells, these fruit flies,

82:00

and these human cells grown on a dish is

82:03

they aren't able to take their pyrovate

82:05

into the mitochondria. You know by

82:07

analyzing them using sophisticated

82:09

chemical tools we could see that they

82:12

were basically their metabolic pathway

82:15

from glucose to pyrovate to pyrovate in

82:19

the mitochondria to ATP that was being

82:21

blocked and it was being blocked

82:23

specifically at that level of the

82:25

pyrovate. So that then gave us the

82:28

initial hypothesis maybe that's what

82:30

these proteins are doing and we could

82:31

then go and validate that hypothesis in

82:34

multiple experiments and that like I

82:36

said been validated by many other people

82:38

over the ensuing decade or so. So those

82:41

were the experiments that enabled us to

82:43

to figure it out. It was really um

82:45

genetics that enabled us to do it.

82:47

>> Very satisfying when a discovery comes

82:49

about in yeast flies and mamalon

82:52

including human cells. What year span

82:56

was all of that happening if you had to

82:57

really tighten it?

82:58

>> Yeah, we published the paper in 2012. It

83:00

probably was going on from 2008 or 9 to

83:03

2012, something something like that.

83:06

>> This is actually an important moment, I

83:07

think, for people to understand like

83:09

when they hear about yeast or flies.

83:11

They're probably like like why why are

83:12

we doing this stuff? And I'm not here to

83:13

like plug federal funding for research.

83:15

I think that just happens naturally as a

83:17

consequence of the podcast. Or at least

83:18

I hope so. But my graduate adviser told

83:21

me that yeast like they have a very

83:23

quick turnover. So that's why they're

83:24

good to use. And and she said that um

83:26

she was a wine drinker. She said and

83:28

they were much smarter than us because

83:29

they know how to make their own alcohol.

83:30

[laughter] So now we know why biologists

83:32

use yeast.

83:33

>> Fruit flies. It's because of the short

83:36

generation time. You can get a lot of

83:37

experiments

83:37

>> done. And they they have many of the the

83:40

same structures that a human does. You

83:42

know, not exactly obviously, but they

83:44

have many structures that human does.

83:45

And there's some things that they're

83:46

particularly good at. You can look at

83:47

the whole thing in the microscope and

83:49

see different cells and different

83:51

features. And I would say again, not to

83:53

plug our specific experiments, but we

83:55

could not have made that discovery with

83:57

any one type of organism. If we just had

84:00

the yeast data, we wouldn't have figured

84:02

it out. If we just had the flight data,

84:03

we wouldn't have figured it out.

84:06

>> Same with the the human cell data. But

84:08

putting it all together, we could

84:09

triangulate what we were seeing in one

84:11

to what we were seeing in the other, and

84:13

it became obvious that this is the

84:15

hypothesis we should pursue. And I I

84:17

think that's been obviously an effective

84:19

strategy that's been employed by

84:21

scientists for a long time is to take

84:24

multiple different approaches, multiple

84:25

different model systems to answer a

84:28

complicated question.

84:29

>> Let's talk about lactate.

84:31

>> Every time lactate's come up on this

84:32

podcast before, it's been the in the

84:34

context of exercise physiology. We had

84:36

the the great Andy Galpin, whose name I

84:38

don't expect you to recognize, but he's

84:39

he's really one of the like pre-minent

84:41

public educator. He's a professor of

84:42

physiology and exercise physiology. And

84:45

he told us and he told the world like

84:47

everyone talks about lactic acid. We

84:49

don't actually make lactic acid. We make

84:50

this thing called lactate. But within

84:52

the cell lactate plays a very crucial

84:55

role in this metabolic pathway. I know

84:57

you spent some time with lactate. So

84:59

when you think about lactate what do you

85:02

think about?

85:02

>> I mean so pyrovate we talked about

85:04

pyrovate extensively

85:07

>> to a first approximation. Again it's a

85:09

little more complicated than this but I

85:10

think this is a good way to think about

85:12

it. When pyrovate is made simplistically

85:15

has two fates. It can go into the

85:16

mitochondria we talked about. What we

85:18

didn't talk about is the other major

85:20

fate is to be converted to lactate and

85:22

exported. And that decision burn it make

85:25

lactate. I think you could make a very

85:28

strong argument is one of the most

85:30

important metabolic decisions that cells

85:32

are making all the time.

85:32

>> Why would it not burn it or make more of

85:34

itself because it's just got it in

85:36

excess?

85:36

>> Yeah. There's something about that

85:37

production of lactate that enables

85:40

ongoing production of biomass. So again,

85:42

a little more complicated than this. If

85:44

you burn the pyrovate, that turns into

85:47

carbon dioxide. We breathe it out. That

85:49

the stuff is gone. We breathe it out.

85:53

There's no stuff. There's just the

85:55

energy.

85:57

If you don't burn it, that stuff doesn't

86:01

get eliminated as carbon dioxide and can

86:03

turn into a protein. can contribute to

86:06

protein production or carbohydrate

86:08

production or you know fatty acids that

86:11

can be used to make make new cells. And

86:13

so that really is the that resource

86:16

allocation decision as we talked about

86:18

many times building or burning.

86:22

And lactate is one of the mediators in a

86:25

way of that building decision. And so

86:28

lactate I think historically has been

86:30

thought of as a waste product when our

86:32

cells can't burn

86:35

typically because of lack of oxygen. We

86:37

haven't talked so much about the role of

86:39

oxygen and all this. When I talk about

86:40

burning, what I really mean is taking

86:43

that pyrovate or fatty acids or other

86:46

things and oxidizing them using oxygen

86:50

and ex by so doing extracting the energy

86:54

and doing this unbelievably amazing

86:56

chemistry that the mitochondria do to

86:58

basically very effectively capture all

87:01

that energy and make it usable in the

87:03

form of ATP. When oxygen isn't

87:05

available, that pyrovate cannot be

87:07

burned and then it essentially has to be

87:10

converted to lactate. That's why when we

87:12

exercise and our muscle becomes hypoxic

87:15

or doesn't have adequate oxygen, we make

87:17

lactate and that lactate is what causes

87:20

the burn that we feel. And we've thought

87:21

about it traditionally as a waste

87:23

product. There's been beautiful

87:25

experiments done in the last 5 or 10

87:27

years. Joshua Benowitz, a friend of

87:29

mine, a professor at Princeton, has done

87:30

some of these that have demonstrated

87:32

that lactate is a very important fuel on

87:35

its own. The heart, for example, is

87:37

quite good at consuming lactate and

87:40

burning it.

87:40

>> The heart can it seems like it's kind of

87:42

like a it's got it's consuming a sort of

87:45

like dog's breakfast of fuels. It likes

87:47

lipids. It'll take glucose. It likes

87:49

lactate. anything that's good for us cuz

87:51

that that keeps it beating no matter

87:53

what the metabolic status of you know as

87:56

long as we're alive we have something

87:57

that it can burn and lactate is just an

87:59

important mediator of carrying th that

88:02

energy around

88:03

>> it can be a fuel it can be a shuttle

88:06

>> in the context of exercise in brain and

88:08

I know this is we're not talking about

88:10

actionables here but like I've mentioned

88:12

before on this podcast like if we do

88:14

like an intense typically it's aerobic

88:17

exercise we get like enough lactate

88:19

generated that does seem to be a signal

88:21

to the brain for this brain derived

88:23

neutrophic factor which now kind of

88:24

makes sense in this context because the

88:27

whole purpose of BDNF is to build more

88:30

stuff more connections typically rather

88:33

than break connections so it's amazing

88:34

that we think of these things like a

88:36

waste product just like we used to talk

88:37

about like junk DNA nobody does that

88:39

[clears throat] anymore we have to be

88:40

very careful with language in biology

88:42

I'm realizing

88:43

>> like the moment we we label something

88:45

conceptually

88:46

>> you like shut down a field like line of

88:49

discovery that almost always ends up

88:51

being like super important.

88:52

>> Yeah, we joke all the time in the

88:54

mitochondria field about the powerhouse

88:56

of the cell, right? Which it really is.

88:58

I mean, the cell the mitochondria are

88:59

very good at being a powerhouse and

89:01

making ATP, but they do so much more.

89:03

And again, just to illustrate the point

89:05

that when we categorize something into

89:07

one thing, this is what it does. We're

89:09

almost always proven wrong and it turns

89:11

out to be a bit more complicated.

89:12

There's something I can't wrap my head

89:14

around because if I have an excess of

89:15

energy and therefore I'm making lactate,

89:18

am I going to now prioritize lactate? Is

89:20

that going to now get burned off the top

89:21

of the energy uh priority scale?

89:24

>> That's a good question. And and you

89:26

know, I I don't think we have strict

89:28

answers to this, but there's definitely

89:30

prioritization of energy. One of the

89:32

most important things to burn is fatty

89:34

acids. And and the reason for that is

89:36

that when fatty acids are in excess,

89:39

they can be toxic. and they can be toxic

89:41

in an acute way quickly. Glucose again

89:45

is toxic in excess but chronically maybe

89:48

it's a little bit less dangerous if we

89:50

have high glucose for for some time.

89:52

High free fatty acids is dangerous now

89:55

>> and not just because it clogs arteries

89:56

>> that of course. Yeah, exactly.

89:58

>> Yeah,

89:59

>> it Yeah, in reason in ways that we

90:02

probably don't need to get into, but can

90:03

be disruptive to cell structures and so

90:06

forth. And so, you know, most cells when

90:10

they have fatty acids will burn the

90:12

fatty acids first probably as a response

90:15

to, hey, this could kill us. Let's let's

90:17

take care of this first.

90:19

>> Is also true the fatty acids we ingest.

90:21

>> This is also true. The fatty acids we

90:23

ingest if they get into cells, of

90:24

course, you know, um you could imagine,

90:27

again, it's a little more complicated

90:28

than this, but the fatty acids we ingest

90:30

and the fatty acids we make end up in

90:32

the same pathways, right? They they both

90:35

get into other cells. uh throughout the

90:37

body and when they do they need to be

90:40

handled appropriately. Lactate is maybe

90:42

a little bit more on that on that side.

90:45

It has some important effects to the

90:48

chemistry of cells that are important to

90:50

deal with. And so lactate if it if it

90:53

gets too high in the body it can be

90:55

toxic. you know, uh, lactic acidosis,

90:58

which is essentially the the the

91:00

phenomenon where we have too much lactic

91:03

acid, lactate in our in our circulation.

91:06

That's bad and can be lethal. And so,

91:08

dealing with that lactate is important.

91:11

And so, yeah, I think there is a

91:12

prioritization that probably comes as a

91:14

result of evolutionary pressure. You

91:16

know, we had ancestors that maybe didn't

91:18

deal with fatty acids so well and maybe

91:22

didn't survive, but we had one

91:24

individual that figured out how to deal

91:25

with them more effectively and that

91:27

individual survived better and and that

91:29

trait was selected for and we're now

91:31

pretty good at it. We had a colleague of

91:33

yours on the podcast who studies hypoxia

91:36

and spleen function and and we're

91:38

talking about how everyone hears the

91:39

word mutation

91:40

>> and they think like oh mutations are

91:42

just always damaging but you know these

91:44

mutations that afford more life that are

91:46

adaptive essentially people can't hear

91:48

that enough mutations are the reason

91:51

we're here.

91:52

>> That's right.

91:52

>> Yeah. So the X-Men had it right. Like

91:54

that's a that's a good series to watch.

91:55

on the other side of the coin, the

91:57

maladaptive um situation. Could you tell

91:59

us about the Warberg effect and its role

92:02

in cancer? And and I do want to frame

92:03

this properly because nowadays we're

92:06

living in a weird time around this topic

92:09

of cancer. There are these corners of

92:11

the internet that like don't actually

92:13

believe in cancer or germ theory. They

92:16

they just like don't believe it. And

92:17

some of that is actually kind of

92:18

catching on. I believe cancer exists and

92:21

I believe that cancers can come about

92:23

through a variety of mechanisms. So only

92:26

if you believe that to be true that it

92:28

can come about through a variety of

92:30

mechanisms. Would I ask you to like

92:32

>> agree uh if you disagree please disagree

92:34

but

92:35

>> it's true right that there are a lot of

92:37

paths to cancer.

92:38

>> Yeah there's no question that there are

92:40

some fundamental features of cancer. All

92:42

cancers to my knowledge have mutations

92:45

in the genome and those mutations are

92:48

many but tend to cause again work

92:52

together to cause that cell to divide to

92:56

replicate itself more rapidly

92:59

to evade the immune system which is

93:02

patrolling looking for misbehaving cells

93:04

to eliminate them and somehow cancer

93:06

cells can avoid that. critically

93:08

important and you know one of the most

93:12

um exciting developments in cancer

93:13

therapy over the last 10 or 15 years has

93:15

been these checkpoint inhibitors PD1

93:17

PDL1 that uh inhibitors that basically

93:21

reverse that you know cancer cells are

93:23

very good at cloaking themselves let's

93:25

say from the immune system and those

93:26

therapies eliminate that cloak and and

93:29

allow them to be seen by the immune

93:30

system and eliminated and there's just

93:32

been amazing responses to those new

93:35

therapies again they don't

93:38

treat every cancer to the same degree,

93:40

but there's been wonderful examples

93:42

where they've been effective. So yeah,

93:44

cancers can arise through many different

93:45

pathways. They all are associated with

93:47

mutations. One of the common features of

93:50

cancer is changes in metabolism. And

93:52

this is when you talk about the Warberg

93:55

effect, this is really fundamentally

93:57

what you're talking about. So the

93:58

Warberg effect is a phenomenon that was

94:02

named after Otto Warberg, a scientist, a

94:05

German scientist back in the 1920s that

94:08

observed that cancer cells

94:12

consumed less oxygen

94:14

than would be expected from the cells

94:17

around them. And that has been named the

94:20

Warberg effect.

94:22

What Otto Warberg thought was that

94:26

that's because the mitochondria are

94:28

broken and then concluded that broken

94:31

mitochondria are probably the cause of

94:33

cancer. That was the thinking that

94:36

permeated from the time of Otto Warberg

94:38

in the 1920s for for many years.

94:41

>> Broken meaning they're not making ATP or

94:43

or they're they're doing something

94:45

wacky.

94:45

>> Yeah, they're well they're not consuming

94:47

oxygen. That was the observation. the

94:49

oxygen consumption was low and that is

94:52

again mitochondria as the powerhouse of

94:54

the cell are consuming oxygen that's how

94:57

they're doing their powerhouse function

94:59

making ATP so that was the observation

95:02

the interpretation of that observation

95:04

was that mitochondria are probably

95:06

broken we now know we've talked about

95:09

this that mitochondria do more than just

95:11

make ATP

95:13

and it turns out that mitochondria and

95:14

cancer cells are not broken in fact

95:17

they're very very good not necessarily

95:19

at making ATP but at making stuff and

95:22

again the stuff is what's so important

95:24

for a cancer cell because it needs to

95:26

divide itself it needs to duplicate

95:28

itself to eventually make a tumor so the

95:31

Warberg effect is a phenomenon again in

95:33

simple terms that is absolutely the case

95:36

that mo many cancer cells most tumors

95:39

consume less oxygen than you would

95:40

imagine because they're instead of

95:43

burning their fuel again we talked about

95:45

this bifurcation cancer cells tend to

95:48

not be burning. And by burning, that's

95:51

consuming oxygen,

95:53

but they're using their resource

95:56

allocation to build stuff, to build a

95:58

new cell. And so, I think this dubtales

96:01

very nicely with what we've been talking

96:03

about before. The oxygen consumption,

96:05

the Warberg effect, is basically just a

96:08

surrogate for that resource allocation

96:11

question. And cancer cells are are very

96:14

adept at using their resources to

96:16

duplicate themselves.

96:18

>> Of the uh modern treatments for cancer,

96:21

radiation, chemotherapy and

96:23

amunotherapies and what's of happening

96:26

now had someone on talking about you

96:28

know cart cells and um things of that

96:30

sort. But is there anything that um you

96:34

kind of sense on the horizon? it might

96:36

be 5 10 years out or two years out that

96:38

like if if we could just solve that

96:42

that we would be in a position to treat

96:44

and cure many more cancers like like

96:46

what's the

96:47

>> what's the kind of lynchpin thing here?

96:49

Is it being able to reallocate the use

96:52

of pyuvate like if we could do that if

96:55

that was a druggable thing or you could

96:57

do a gene therapy but or you could use

97:00

non-invasive tools like ultrasound or

97:02

light these are all just forces right

97:04

chemical or I would I would like to

97:05

simplify things like for people if

97:07

possible like there two ways to change

97:08

things in the body healthy or unhealthy

97:10

you have mechanical choices and chemical

97:11

choices right you can feel more full by

97:14

having your gut distend you can feel

97:15

more full because your hypothalamus says

97:16

you're full and there's a bunch of other

97:18

stuff involved But like that's all we've

97:19

got is mechanical and chemical forces.

97:21

>> So let's assume you had the tool.

97:24

>> Is there some place where like you feel

97:26

like if we could just

97:28

>> turn that bolt?

97:29

>> Yeah.

97:30

>> We would be in a much better position to

97:31

treat a lot of cancers or cure them.

97:33

>> Let's maybe take a step back from that

97:35

and then get to that question in a

97:36

second and talk about cancer. You know

97:38

what it is and why it's so difficult. If

97:41

a bacteria invades us,

97:44

it's very easy for our immune system to

97:47

say, "Hey, that's not us. Let's go kill

97:50

that thing."

97:52

>> If a cancer cell starts hyperp

97:54

proliferating, it's us, right? It's our

97:57

cells. It doesn't have antigens, which

98:01

are the technical term for the

98:03

molecules, the features that are

98:04

recognized by the immune system. it

98:06

doesn't necessarily have antigens that

98:08

are recognized as not us nonself. So

98:12

that's one of the big challenges of

98:14

cancer. The challenge for us is to

98:17

figure out a way to kill those cells

98:20

which again are our cells. They are us

98:23

to kill those cells without killing the

98:25

rest of our cells. Because if we kill

98:27

the rest of our cells, we kill us,

98:29

right? That's the challenge of cancer

98:31

therapy in my view. Again, I'm

98:33

oversimplifying, but that's that's a big

98:35

challenge. And many of the features of

98:39

cancer cells are not completely new

98:43

things that that cancer just invented.

98:46

It's using the functions that our normal

98:48

cells have. For example, one of the

98:51

things that's common, not universal, but

98:53

common in cancer cells is to become more

98:56

like a stem cell. Has many features of

98:59

stem cells. So, okay, we can find a way

99:01

to target a specific stem cell pathway

99:05

and kill all the cells that have that.

99:08

Well, then we're killing many of our

99:09

stem cells, too. And now the lining of

99:11

our gut doesn't regenerate, which we

99:13

talked about. That's driven by hair.

99:16

Exactly. This is obviously one reason

99:18

why many of the the side effects of

99:21

chemotherapy is to target those

99:23

proliferating cells which share many

99:26

features with cancer cells. So that's

99:29

the problem of cancer therapy. And

99:31

there's a second problem that's worth

99:33

talking about too.

99:35

We've talked about evolution a lot here

99:37

which I think is it's a great rubric by

99:39

which to think about biology.

99:42

Cancer cells a a tumor is under

99:45

evolutionary pressure. Right? So we know

99:47

let's take an example where we have a

99:49

tumor and we get a drug. We have a great

99:52

drug that kills 99.9%

99:55

of the cells in that tumor.

99:58

But.1% of the cells either through a

100:00

mutation or some sort of an adaptation

100:02

are not killed by it.

100:05

But that.1%

100:07

can now repopulate, make a new tumor.

100:09

And this is what happens in cancer

100:11

therapy. We all know of tragic examples

100:14

where we loved ones had a tumor,

100:18

got a treatment and they went into

100:20

remission. you know, the tumor maybe

100:23

shrinks, it goes away, maybe even

100:24

becomes invisible by the imaging tools

100:27

that we have to image uh cancers, but

100:30

then it comes back. And that's because

100:32

these cells are under evolutionary

100:34

pressure. If if one cell, theoretically,

100:37

one cell acquires a mutation that makes

100:40

it resistant to that drug, doesn't get

100:43

killed by that drug, that one cell can

100:45

now repopulate, make a new tumor, and be

100:47

just as damaging. And now it's resistant

100:49

to the drug. Now the drug doesn't work

100:51

anymore. And this is the second big

100:53

problem with cancer therapy. You know I

100:56

this is not my field of expertise per se

100:59

but I feel like given that situation

101:03

this is not dissimilar to what happens

101:05

with viruses. HIV now can be managed and

101:09

frequently is managed by a triple

101:12

combination therapy. And the reason for

101:15

that is you now give three drugs that

101:18

are going to kill that virus or prevent

101:20

the propagation of that virus. It's now

101:23

very difficult to acquire resistance to

101:25

all three simultaneously.

101:28

I think the analogy applies to cancer

101:30

too. I think the future of cancer

101:32

therapy

101:34

again in my in my worldview is going to

101:37

be we have many safe and effective drugs

101:42

that hit different features of the

101:45

cancer cells biochemistry and by virtue

101:48

of understanding the specifics of the

101:51

tumor that I might have the astute

101:54

oncologist can say given that unique

101:57

biochemistry of that tumor this drug

101:59

this drug and this drug are going to

102:01

work together to kill that tumor. And

102:03

it's going to be very hard for that

102:06

tumor to become resistant to all of

102:07

those drugs simultaneously

102:10

and as a result of that that might

102:12

result in something approximating a

102:14

cure. I think that's the world that we

102:16

need to get to. So there's been amazing

102:20

therapies that have come out. You know,

102:21

one of the most exciting recently are

102:24

drugs that target specific encogenic

102:26

mutations, specific mutations that cause

102:28

cancer. Krass mutations are one that

102:30

that are really exciting that target

102:33

specific proteins that are contributing

102:35

to the cancer in a completely specific

102:37

way. Don't do anything else in the body

102:39

to normal cells. Only hit those

102:42

mutations that are onenic. But again,

102:45

eventually there can be resistance

102:46

that's acquired to that. So if we can

102:49

now make multiple examples of that kind

102:52

of specific safe kind of [snorts] drug

102:55

and use them in combinations, our

102:57

ability to treat cancer is going to be

102:59

dramatically improved.

103:00

>> That's very encouraging. We had a guy on

103:02

the podcast named David Fagenbomb. He's

103:04

a medical doctor. Are you familiar with

103:05

his work? He's at University of

103:07

Pennsylvania. He had Castleman's disease

103:08

and he was able to cure his own

103:10

Castleman's disease because he was

103:12

basically on his deathbed. and he

103:14

basically just started taking different

103:15

combinations of already approved drugs

103:17

in a kind of desperate attempt to save

103:20

his life. And he he found things that

103:21

would extend his life. And he's been

103:23

alive 11 years now. and he runs a lab,

103:25

serious scientist as we say, but he also

103:28

has this uh not for profofit called

103:29

Every Cure, which has been successfully

103:32

using AI and cell assays and things to

103:35

take biopsies and try and figure out

103:38

like, okay, in this tragedy of a kid

103:40

who's dying of a particular cancer, like

103:42

let's just throw a bunch of not random

103:45

drugs, but already approved drugs at

103:47

this tumor in a dish, and if some of

103:48

them work, like if the parents agree and

103:51

there's no other hope, do it. and like

103:53

in some cases they're curing and in many

103:55

cases they're extending life. It matches

103:58

up well with what you're describing. It

103:59

requires this AI piece to run iterations

104:01

cuz there's a huge catalog of drugs that

104:03

even oncologists might not be aware of.

104:06

One particular highlight of his work is

104:08

that we know now that in breast cancers

104:11

where they use lidocaine during the

104:13

surgery the incidences of recurrence are

104:16

significantly lower.

104:18

>> And it turns out that lidocaine has some

104:19

effect on the local environment. I'm

104:21

not, this isn't my area, but you know,

104:22

David talks about this and I'm

104:24

encouraged by things like that and what

104:26

you're describing that we're not

104:27

necessarily going to have like the

104:28

miracle drug, but then the miracle

104:31

cocktail for that individual, that

104:33

cancer.

104:34

>> That's the key thing is that, you know,

104:37

>> David's situation is very specific to

104:40

David and and every tumor is a little

104:42

bit different.

104:43

>> Yeah. And one of I think the unhelpful

104:48

results of historically how we talk

104:50

about tumors is we talk about breast

104:52

cancer or liver cancer or

104:56

you know colon cancer.

104:59

There are some breast cancers that are

105:02

more similar to some liver cancers than

105:05

they are to other breast cancers. Right?

105:06

This is our historical classification of

105:09

cancer has just been by where it is. was

105:11

defined by the surgeons that would take

105:13

it out. But the specific mutations that

105:17

cause that cancer and keep that cancer

105:20

again evading the immune system,

105:22

propagating, avoiding cell death and so

105:25

forth are unique to that cancer. So if

105:28

we understand the unique mutational

105:31

landscape of that cancer that gives us

105:34

then

105:36

an ability to say again in a in a world

105:39

that isn't today's world but hopefully

105:42

not too long uh far from now where we

105:44

have the ability to say this combination

105:46

of drugs is going to be effective at

105:49

killing the cells in that tumor. You're

105:52

highlighting something really important

105:53

that is both about the sociology of

105:55

medicine and science that it's just the

105:57

it's not disparaging of it's just it is

105:59

the way it is because of history. So

106:01

much of the way things are in medicine

106:04

and science can be answered by the a

106:06

phrase that everyone should hate, which

106:09

is, well, we've always done it that way,

106:10

which is the worst reason to do anything

106:12

unless it's working spectacularly well,

106:15

right? But is it a stretch to say that

106:18

there are some liver cancers that are

106:20

called liver cancer but that are

106:23

actually much closer in terms of their

106:25

cellular phenotype to cancer of a

106:28

cardiammyioite because of the way that

106:30

say MPC one is changed in other words

106:34

like should we be classifying cancers as

106:37

oh this is a cancer of the sort that the

106:39

cells are making too much of themselves.

106:41

>> Yeah.

106:41

>> As opposed to they're overusing energy.

106:44

There's too much pyuvate. I'm making

106:45

this up, right? I'm not obviously not my

106:47

field. But rather than think only about

106:50

address in the body.

106:51

>> Yeah, no question that we should be

106:53

thinking about the specific features of

106:55

cancer. I've been talking about it in

106:57

terms of the mutation,

107:00

>> the specific mutations that define a

107:01

cancer. And I think that's a useful way

107:03

to do it

107:04

>> because those mutations in a way are the

107:08

instructions for making a new cell.

107:10

Right? the genome of a cell are the

107:12

instructions for how to make a new cell,

107:14

the the constituents that would make up

107:16

a new cell. But I think a very important

107:19

feature that you're touching on that I

107:21

appreciate you bringing up is on top of

107:24

that, layered on top of that is the

107:26

unique metabolism

107:29

that makes up that cell, right? That

107:32

enables those instructions to be

107:34

executed. You know, a cell can have all

107:36

the right instructions to make a new

107:38

cell, but if it doesn't have the

107:41

building blocks, the lumber and the

107:43

bricks and the mortar to make a new

107:45

cell, it can't make a new cell. And so,

107:48

I think that's a really important

107:50

feature of this that we need to talk

107:52

about. And there's been a lot of energy

107:53

in the in the field over the last 10 or

107:55

15 years and maybe even 10 years or less

107:58

at trying to specifically block the

108:01

resource allocation of cancer cells

108:03

toward

108:05

building new new cells. The challenge

108:07

there again is that it's fairly easy to

108:10

develop resistance to that. A cancer

108:11

cell can just make a mutation and and

108:13

rewire its metabolism to build that same

108:16

thing a different way. But that is a

108:18

very important feature of the cancer

108:20

tube. Beyond just the mutations are the

108:23

are the the metabolic processes that

108:25

enable those mutations to be manifest in

108:28

in in what turns into a tumor. How far

108:31

are we from a a world where um I drink a

108:35

fluid and it's a safe fluid because we

108:37

do this for like other types of imaging.

108:39

I step into a tube and I do it when I'm

108:41

like five

108:42

>> and I do it when I'm 50.

108:44

>> Mhm. And I get a picture of red and

108:46

green in every cell, right? So you get

108:48

like an image of like the proportion of

108:51

my metabolism in different organs and

108:53

you could zoom in to a single cell. This

108:55

is not like science fiction at the level

108:57

like it couldn't be done

108:59

>> where you say okay this is a healthy

109:01

cardommyioite and it's using 65% of its

109:05

energy to just keep pumping and then it

109:08

like puts aside a little bit to make

109:10

sure it can make more of its stuff so it

109:11

stays around and a little bit. it's like

109:13

going to this other pathway and like

109:15

that's a healthy cardio. We know this

109:17

from the population of of age match data

109:20

and then when I'm you know 40 50 you go

109:23

yeah I don't know like the your heart's

109:24

looking a little more green than red or

109:27

something like that. we can kind of turn

109:29

the dial back like like we have

109:31

druggable, you know, targets inside of

109:33

cells and we can like kind of like

109:34

adjust the the energy allocation like is

109:37

what I'm describing like so crazy

109:39

because I can imagine a mouse experiment

109:41

or paper will probably come out on that

109:43

next week if it hasn't already

109:44

>> and like that's kind of what you want.

109:46

You want subcellular resolution cuz I

109:48

feel like we've gone from this place

109:50

where like

109:51

>> I was around when the first MR like

109:53

functional magnetic resonance imaging

109:54

stuff was kind of like here's a person

109:56

looking at a banana here's a person

109:57

hearing a joke and like now you can see

110:00

dynamics and you can see acts on

110:02

pathways but if we get down to the cells

110:04

cool

110:05

>> it's a lot of salt and pepper

110:07

>> then you get down to the inner workings

110:08

of the cells you can't see everything if

110:10

you look at everything it's going to

110:11

look like chaos

110:12

>> someone put on X this morning actually a

110:15

AI I rendering of all the proteins in a

110:17

cell in one tiny patch of cell and it's

110:19

just like overwhelming. You're just

110:21

like, "Oh my god." Like there's so much

110:22

here. But if you just say like, "Let's

110:24

just look at metabolism at this key node

110:26

and we know what healthy should be.

110:28

Here's where you're at."

110:29

>> And you're just trying to tilt that

110:31

balance. I mean, that to me feels like a

110:33

>> that could be done.

110:34

>> Yeah.

110:35

>> Like we've got smart people working on

110:36

this. We need more money

110:38

>> to for scientists to work this stuff out

110:40

and more scientists to do that work. But

110:43

I feel like that's doable

110:44

>> conceptually. Pieces of that are doable.

110:46

I think you know when you talk about can

110:49

we basically image metabolism with

110:53

cellular resolution

110:56

I [clears throat] should be clear that's

110:57

a very difficult problem. The spatial

111:00

resolution the ability to see fine

111:02

enough detail to make out individual

111:04

cells or even uh smaller than that.

111:07

That's a challenge. That's definitely a

111:09

challenge inside a human body. And it's

111:11

also a challenge to be able to have a

111:14

surrogate of metabolism that we can

111:16

actually see. Of course, our metabolism,

111:20

there's nothing visual that we can see

111:21

with the naked eye, right? That there's

111:23

nothing I can see in the metabolism of a

111:26

cell. So, what could we make that would

111:28

enable us to visualize that? There's

111:30

really exciting tools being developed of

111:32

many different kinds to be able to image

111:35

various features of metabolism in a

111:38

cell.

111:38

>> Well, we would in neuroscience. I mean,

111:40

again, I was fortunate to be part of

111:41

this wave of technology. Didn't

111:43

contribute to building any of it, but it

111:45

was like, how do you know which brain

111:46

areas are active? Well, you could drop

111:48

electrodes in or you could remove a

111:50

piece and go, well, it probably did that

111:52

when it was there cuz you lost that

111:53

function. But, you know, a lot of it was

111:55

just blood flow. It was like oxygenated

111:58

to deoxxygenated blood

111:59

>> reflects light differently. And like

112:01

you'd get these beautiful maps, but you

112:03

were just looking at blood flow. Now,

112:04

then you got

112:05

>> 2D deoxy glucose. You can look at

112:07

glucose uptake, but it was spatially

112:09

very crude or it was the the time

112:11

resolution wasn't very good. But I feel

112:13

like we've come some way. You can look

112:14

at voltage. You can look at calcium. I

112:16

feel like

112:17

>> the moment that chemists, bioengineers,

112:20

and physicists

112:21

and computers came into biology,

112:25

>> things got a lot better.

112:26

>> Yeah.

112:26

>> I mean, some people say it got a lot

112:28

worse,

112:29

>> but they retired now. So, like, it got a

112:31

lot better because you could see what's

112:33

really happening.

112:34

>> Maybe I'm overly optimistic. No, I I

112:36

think that we need to be able to figure

112:38

out what to measure. I mean, that's

112:40

obviously a key thing. What would be the

112:42

metabolic parameter? What would be the

112:44

one metabolic parameter you'd really

112:47

want to measure to assess is this cell

112:50

healthy or not healthy? And it's hard to

112:52

know exactly what that one would be or

112:54

collection of things and then figure out

112:56

a way to measure that

112:58

>> non-invasively, so to speak. You know,

113:00

it's one thing if if I'm going to

113:03

measure that, do I have to cut off my

113:04

arm,

113:05

>> shave it into slices, and you know,

113:07

measure it? Nobody wants that.

113:09

>> So, how can I measure it without,

113:12

>> you know, doing damage to me while I'm

113:14

measuring it? These are hard problems,

113:16

but as you say, the technology just

113:18

keeps getting better in all versions of

113:20

this. And the experimental tools, the

113:22

tools that we can use in mice or in

113:25

cells and culture are definitely getting

113:27

better. And that that's that's an aspect

113:29

of this field of of studying metabolism

113:32

that's really exciting is our ability to

113:34

now be able to measure what's happening

113:36

at individual places in individual cells

113:39

and looking at specific individual

113:41

molecules you know intermediates and

113:43

products and substrates of these this

113:45

metabolic map and that I think is

113:48

teaching us a lot about how metabolism

113:51

works in individual cells and that is

113:53

then going to be informative when we

113:55

think about how it's working in a

113:57

I'm intrigued by this really wild thing

114:00

that you see in the news every once in a

114:01

while which I believe to be true but no

114:03

one can explain which is that there are

114:05

dogs and there are occasionally people

114:08

who can detect the scent of cancer

114:11

beyond chance like this is like no one

114:14

really knows the basis of this and

114:16

recently there's an example my

114:18

understanding is it's validated of a

114:20

woman who was able to smell Parkinson's

114:22

as a musty scent that a musky excuse me

114:25

and now spouses of people that had

114:27

Parkinson's in particular the female um

114:30

the wives of these men like oh yeah I

114:32

remember this now of course there's a

114:33

whole lot of like placebo correlation

114:35

just so story that can emerge from that

114:37

but as you're telling me some of this

114:39

like obviously you wouldn't want this to

114:41

be the one and only frontline detection

114:43

system but it kind of makes sense that

114:44

if if cellar metabolism is at the heart

114:46

of certain cancers or neurodeenerative

114:49

conditions makes sense that we're

114:51

breathing out yeah

114:52

>> the byproducts obviously these sense are

114:54

just correlative right and the shifts in

114:56

when we with infants, parents are

114:59

remarkably good at being like

115:00

something's off because they can't

115:02

communicate verbally with us yet, right?

115:04

Like something's off in their stool or

115:06

something's off in their skin power

115:08

that's not extreme and and become

115:10

remarkably astute detecting real

115:12

underlying issues. Yeah. So, do you

115:14

think that there could be useful

115:16

information coming from the air we expel

115:20

in terms of revealing at a systemic

115:22

level or maybe even at a cellular level

115:24

um how well or poorly we're regulating

115:26

>> energy? Yeah. I mean, obviously, as you

115:29

said in your in in alluding to this,

115:31

this is again at the frontier of science

115:33

and I don't think we understand much of

115:35

the specifics, but I think you could

115:38

imagine that because again, smells,

115:40

scents are chemistry, right? These are

115:43

chemical compounds that are coming from

115:45

the person. And when a person's doing

115:49

different metabolism, they're going to

115:50

be producing different chemicals in

115:52

different proportions. And I think it is

115:54

possible that those can be detected in

115:56

specific ways. That's not so dissimilar

115:59

from some of the diagnostics that we do

116:01

use where we actually measure the blood

116:03

chemistry. You know, the blood chemistry

116:05

is different between people that have

116:06

different diseases and don't. And so,

116:08

you know, and obviously the breath is

116:12

some

116:13

measure of the chemistry that's going on

116:16

in the person. It's obviously um

116:18

different from the blood, but it's a

116:20

fascinating topic and and as that gets

116:22

to chemical specificity, it'll become

116:24

probably more clear what's going on

116:26

there and why why is Parkinson

116:28

specifically susceptible to that

116:30

different chemistry in a way that can be

116:32

detected by scent. We were talking a few

116:35

moments ago about excess energy

116:37

toxicity. This is something that Dr.

116:39

Lane Norton brought up on this podcast.

116:41

He's a serious biochemist, nutrition,

116:43

exercise science guy, public educator,

116:46

loves random ice control trials and

116:48

metaanalysis. That's like his if it's

116:50

not there, he's not interested or he's

116:53

perfectly interested in in tossing away

116:54

everything else. So that's kind of his

116:56

hallmark. So that should feel good to

116:57

you just knowing that. But he talks

116:59

about this energy toxicity. You know,

117:01

like excess calories leads to problems.

117:04

Not just because of the presence of

117:06

excess body fat, but because of just too

117:09

much energy at the front end creates

117:11

downstream biochemical issues across the

117:14

body. How does this relate to some of

117:16

what we've been discussing?

117:18

>> There's a a widely accepted hypothesis

117:21

that mitochondria with excess energy

117:25

leads to problems. You know, many people

117:28

that that are listening have probably

117:30

heard of reactive oxygen species. This

117:32

is, you know, forms of oxygen that

117:34

become reactive and end up spinning out

117:37

and damaging proteins and nucleic acids.

117:40

And

117:42

I think it is uh again widely accepted,

117:46

not universally, but widely accepted

117:48

that one of the contributors to that is

117:50

mitochondria that have too much energy.

117:53

Basically, the form that energy takes

117:55

when it's extracted from the food we eat

117:57

and before it's converted to ATP is

118:00

powering the mitochondria. And when that

118:02

mitochondria is overpowered, that leads

118:05

to a state that is very susceptible to

118:07

generation of these reactive species

118:09

that end up damaging our genome,

118:11

creating mutations and damaging proteins

118:13

and creating many of the problems that

118:16

we see. And I think there's been a

118:18

number of studies that have suggested

118:19

they might contribute to various

118:21

pathologies including aging. So I think

118:24

that idea of excess energy is one that

118:27

is really important to consider from the

118:30

level of the organism down to the level

118:33

of individual cells and even the

118:34

mitochondria within those cells. Once

118:37

again, it I'm thinking about the this

118:39

notion like no individual or collection

118:43

of individuals or cell or collection of

118:46

cells can really get away with or what's

118:48

the saying like you pay the piper

118:49

somehow. Like cells really get punished

118:52

for cheating themselves by taking too

118:55

much energy or not allocating it

118:57

correctly. Like you can level up

119:00

>> from this like single cell analysis all

119:01

the way to to societies. I actually

119:03

think

119:04

>> this is fascinating. I for a variety of

119:07

reasons. First of all, again, we've

119:08

never had a serious discussion about

119:10

what mitochondria actually do besides

119:12

just create help create energy. So,

119:15

first of all, thank you so much for

119:16

telling us how they actually allocate

119:18

their resources towards things other

119:20

than just making more energy for usage

119:23

to build more of oneself. also for

119:25

framing that in the context of of

119:27

disease and health and also for shining

119:30

a light on the fact that like while we

119:33

might be right here now that I do think

119:36

I'll just say what maybe you were trying

119:37

to say but are too humble to say that I

119:40

think as long as we're looking at things

119:41

just like oh this is a cancer of this

119:43

tissue and not actually asking what

119:46

specifically is happening to the cells

119:48

there that might be common to other

119:50

cancers elsewhere and like changing our

119:52

nomenclature and boundaries of how we

119:54

classify things opening up our minds to

119:56

it

119:56

>> as well as really thinking about the

119:58

whole body as a like a constellation of

120:01

these little microactories that is us. I

120:04

am certain that people hearing this will

120:06

no longer think about like metabolism

120:08

just as them my metabolism but this um

120:12

constellation of metabolisms and and the

120:14

health status of of all the different

120:16

cells. So, it goes without saying that

120:18

it's a really unique opportunity for the

120:19

general public to hear from like like a

120:21

worldclass biologist working on these

120:24

specific issues and related issues for

120:27

decades now, right? And so, and you're a

120:29

very busy person. So, I'm very grateful

120:30

to to you to the University of Utah for

120:34

allowing uh and encouraging public

120:35

education to Howard Hughes. No, they

120:37

didn't tell me to say this, but I think

120:39

people really need to understand what an

120:41

amazing opportunity is to learn from the

120:42

people and there are others in the

120:44

field. you're so good at attribution who

120:46

are who are really trying to figure out

120:48

these really hard problems in biology

120:50

that are crucial to health and to

120:52

disease and therefore to curing disease

120:54

and really trying to move things forward

120:56

in your workshop that you call a

120:58

laboratory. So you don't have to do this

121:00

sort of thing but I greatly appreciate

121:01

it and I speak on behalf of many many

121:03

people really appreciate it. There's

121:05

information and then there's superb

121:06

information. So thank you so much.

121:08

>> Thanks Andrew. It's been a lot of fun.

121:09

>> Uh we'll do it again

121:10

>> anytime.

121:11

>> Cheers.

121:11

>> Thank you. Thank you for joining me for

121:13

today's discussion with Dr. Jared Ruer.

121:15

To learn more about his work, please see

121:17

the links in the show notes caption. If

121:19

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121:20

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121:53

read all the comments. For those of you

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that haven't heard, I have a new book

121:56

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121:58

It's entitled Protocols, an operating

122:00

manual for the human body. This is a

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122:12

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122:14

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122:23

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122:25

There you can find links to various

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122:30

Protocols, an operating manual for the

122:32

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123:10

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123:12

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123:20

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123:29

Thank you once again for joining me for

123:31

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123:33

And last, but certainly not least, thank

123:35

you [music] for your interest in

123:37

science.

Interactive Summary

This episode of the Huberman Lab podcast features Dr. Jared Ruer, a leading expert in biochemistry and mitochondria. They discuss the biological complexity of mitochondria, which act as more than just energy powerhouses, and explore how cellular metabolism is the collective sum of the body's 30 trillion cells. The conversation covers the origin of mitochondria as endosymbiotic bacteria, their unique role in resource allocation between energy production and biomass creation, and the importance of this balance in diseases like cancer and heart failure. Additionally, they touch upon the role of lactate as a signaling molecule and fuel source, and the future potential of personalized, metabolically targeted cancer therapies.

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