- Welcome everyone to Wednesday Nite @ the Lab.
I'm Tom Zinnen.
I work here at the University of Wisconsin-Madison
Biotechnology Center.
I also work for the Division of Extension, Wisconsin 4-H.
And on behalf of those folks
and our other co-organizers, PBS Wisconsin,
the Wisconsin Alumni Association,
and the UW-Madison Science Alliance,
thanks again for coming to Wednesday Nite @ the Lab.
Tonight, it's my pleasure to introduce to you Scott Coyle.
He's a relatively new professor from right across the street
in the Department of Biochemistry.
And he's gonna have what I think is an extraordinary talk
because he has extraordinary video of cells.
Cells that move and do things
and molecules that move and do things.
And it's very different
than the microscopic visions I had in college,
or at least the ones through the microscope.
Scott was born in Livermore, California
and then went to Granada High School there in Livermore.
He stayed right there in the East Bay to go
to the University of California, Berkeley,
where he majored in biochem as an undergrad.
Then he went across the Bay to get his PhD
at the University of California at San Francisco,
also in biochemistry.
And then he went down the road just a little bit
to Stanford to do a postdoc.
He came to the UW-Madison in late 2019.
He single-handedly timed the COVID pandemic.
- Scott: What can I say? - Tom: Perfectly.
I think this is an extraordinary thing.
Veit Bergendahl gave the first talk
for Wednesday Nite @ the Lab on February 22 of 2006
on human embryonic stem cells.
For me, it's great to have this extraordinary talk
also on cells to wrap up my time as the emcee here.
Would you please join me in welcoming Scott Coyle
to Wednesday Nite @ the Lab?
[audience applauding]
- Scott: Thank you.
Make sure my pointer's working.
Can you all hear me?
PBS, you can hear me?
Good, all right.
Well, it's my great pleasure to be here
and talk to you about kind of my thoughts
about biology and cells.
And really, I am a biochemist and a synthetic biologist
interested in understanding and engineering cells.
And that's kind of a daunting task
because everything I'm showing you
on this screen here is a cell, right?
And they look very different.
They're doing very many different things.
And what I'm hoping to tell you about
in today's talk is ways to think about the answer
to a simple question, which is, "What are cells?"
They're very complicated, obviously,
but I'm gonna share with you some ways
I like to think about cells
that make them easier to understand.
And through that lens, we will see also that
that approach to thinking about the cells
may give us an answer to another question, which is,
could cells be more than they already are?
Can we engineer them and change them
to do new things for us in the world?
And so with that in mind, I'm gonna try to tell you
about three different sort of arcs in this talk
as we think about these fascinating little creatures
that we call cells.
I'm gonna give you kind of a view
of the kind of classic biology of cells.
How do cells work and why are these kind of the basic unit
or the kind of the atom of all life on earth?
And I'm going to try to make it very simple
because every cell is very different,
and the biology of cells is very complicated.
But there's some useful abstractions in there
that will help us kind of generalize our thinking
about what a cell is and what the key things
that have gone into making this an important unit for biology.
And from that abstraction, I'm gonna challenge us
as an audience to think a little bit
about cells from different perspectives.
So instead of thinking about the cell
as a biological entity in and of itself,
we're gonna start to reimagine cells
as different kinds of things.
A manufacturing system, for example,
or a chemical computer, or even some sort
of self-driving machine or microscopic robot.
And then in the final stage,
I'm gonna tell you a little bit about
how those new perspectives of kind of projecting
cell biology onto these other concepts
can help us think about ways to engineer biology
and living systems through this lens
of other kinds of technologies,
really with an aim in the long term
of kind of paving a way forward to sort of a new,
more biologically-powered future, okay?
That's a little bit
of a synthetic biology futurism there,
but I hope you'll join me on this fun excursion, okay?
So let's start by just thinking a little bit about cells,
how do they work, and why have they become
kind of the unit of all life on earth?
And the first thing we need to recognize is that
cells are really the minimal system that's capable
of executing all the processes of a life form, okay?
So what I mean is if we have a cell here,
and real cells look a lot more interesting
than this little schematic there [laughs],
but these cells will have a few things
that are really important
to how they're able to function, okay?
The cell is gonna have a genome.
And what that means is that there
is chemical material inside the cell
that provides the information for this thing
to be able to make an exact replica of itself.
And so I'm sure many of you have seen
the beautiful structure
of the B-form double-helix DNA structure.
And it's a really remarkable chemical entity
for encoding information because it's actually
this beautiful helical structure here.
And the complementarity between the two strands,
the pairing of As with Ts and the pairing of Cs with Gs
through Watson-Crick-Franklin based pairing interactions
that make this molecule this perfect copyable entity
that can be replicated and passed down
from one to the next.
But this material, the genome,
is only part of the story, right?
And this genome encodes the things
that enables a cell to build materials, okay?
And cells are amazing builders.
They can create nanoscale machines called proteins
that perform specific biological functions.
And so for many of you,
proteins might be like the soy powder
that you would get at GNC, like my students over there,
bulking up and things like that.
But really, proteins are kind of,
each one of them is a very special entity
that can perform chemical reactions.
They can create structure.
They can do all sorts of amazing things.
And our genome contains the instructions for the cell
to build all kinds of different proteins
with different functions that let them execute the tasks
that they need to perform.
And finally, a key thing about cells is that
they can react to what's happening around them.
So they're not like a static thing
that just sits there doing nothing.
They can change what they make and do in response
to signals that they experience from the environment.
And that's because they have all sorts
of things on their surface.
They're like this little red thing, we zoom in.
There's all these things on the surface.
We call them receptors.
They're special proteins in the membrane of these cells
that combine to things in the environment.
And when they do, they transmit information
to the inside of the cell, where networks
of additional protein molecules work together
to interpret what those signals are, process the data,
and then communicate to our genomes
what types of new proteins they should make
or what kinds of changes to the biology should happen.
And so really, we can sort of abstract the cell
to kind of just a few key components
that are really critical to driving this function.
The genome, which is providing these chemical blueprints
with which we can make the molecular parts,
and then kind of the proteins
that are the actual molecular parts
that the cells are gonna use to do most of their work.
And if anyone out there works on lipids, I apologize.
I left out some critical molecules that exist.
But this is kind of like the key set for me
in terms of what's going on.
And then it is through this interaction
between our genome producing proteins,
and then proteins doing important work
and doing important tasks that feed back into our genome.
This sort of leads to this integrated loop
in which we end up with a cell.
And so we can then start to think of the cell
as this network of dynamically interacting molecules
that are working together to produce this functional,
self-replicating system that we call a cell.
And the things that cells,
the kinds of machinery that comes out,
the kinds of cells that we find in nature,
and the diversity of forms
that we can see is just truly astonishing.
So I'm showing you here two videos of two cells,
both of which, I think, you could spend your whole life
trying to understand how they work,
and think about their remarkable capabilities.
Over here on the left, we have a video of a T cell
interrogating a target cell in its environment.
So T cells are immune cells, they're in your body,
and one of their functions is to investigate
or talk basically to other cells in your body
and say, "What's going on in you?
"Do you have a viral infection?
"Do you have some sort of,
is there something inside you that shouldn't be there?"
And what you're seeing this cell doing
is it's actually searching around
on the surface of this target cell,
and it's looking for information about
what's going on in the inside to make an evaluation
as to whether it should let this blue cell live on
or if it should destroy it because it thinks it has a virus
or something else like that inside it.
And so here's a cell investigating another cell.
On the right-hand side,
we have an extraordinary single-celled animal.
So this is basically a single-celled organism
that's almost indistinguishable from the kind of
complex animal structures that we form.
And we found this cell, my students and I,
we just went out to the lake, fished it out.
You find these things.
If anyone wants to know where you can find them,
I can tell you where we get them.
But this cell is almost able to do the same thing,
but with a completely different kind of structural apparatus.
You see, it's built this unusual hunting trunk,
and it swings it around,
and it looks for food in its environment.
And when it recognizes something that it's evolved to eat,
it's able to detect it, paralyze it, and eat it.
And so both of these cells are basically
doing totally different things,
but they're sort of built into the same framework
of they all have genomes, they're all making proteins,
and yet we're getting so many different kinds
of results at the other end, okay?
And this is one of the elements of a cell
that's actually quite phenomenal
for building even more complex organisms.
It's really this flexibility
that it makes cells an exquisite building block
for multicellular life forms.
Because a single genome can contain the information needed
to make all the parts that you might need
to make any cell in your body.
So from this one little cell, you can potentially,
by regulating what portions of the genome
are actively used at different places and times,
you can start to create all kinds of different cells.
Cells like neurons, cells like epithelial cells,
intestinal cells, muscle cells, blood cells.
They're all producible just from one set
of parts inside this genome,
but using them in different ways.
Not so different from how my son,
who's now getting into playing with blocks and Legos.
You can make all kinds of things
from the different parts that are in his collection.
It's how you put them together.
You can get different results.
And just to give you a sense
for the kind of scale of how many cells
might go into a multicellular organism,
a very simple animal like a nematode,
which my colleague, Judith Kimble, studies,
they might have a thousand cells or so.
And a mouse might be made up of three billion cells,
but our human cells have upwards of 40 trillion
of those little things running around,
working together to build us up.
And within those trillions of cells, there's hundreds,
and people are discovering new ones all the time,
but hundreds of different cell types
that is specific machines that can be built
from that single genome, muscle, neuron, et cetera.
So it's quite remarkable
how much you can potentially get out
of this kind of framework for building materials.
So that's kind of just like
how I like to think about the cell, okay?
Try to abstract it a little bit and simplify it.
And now, I want you to think about those things
that I just told you about,
genomes that contain information, making things,
making decisions, evaluating them.
Let's take a moment now to see if we can start
to reimagine those activities of cells as other things.
That is, we can start to view the cell
as something that can serve as a manufacturing device
to make lots of something, or it can serve as a chemical device
that can perform computations for us,
not so different from the computer
I'm presenting to you around here from,
or even operate functionally,
not so different from the kinds of robots
that you might see running around campus delivering food.
I don't know if any of you have seen those,
but they're out there.
So what I wanna kinda do is project
onto this scheme I had for this
sort of oversimplification perhaps of the cell,
each of these concepts for a sort of
technological paradigm that we can kind of imagine.
And so we can think about the genome
and its information that it contains
and the proteins that it can make,
which are the sort of parts, as a step
in a sort of manufacturing process, right?
Because the genome allows us
to manufacture or create protein products.
And in fact, you'll find that there are many cells
in your own body whose primary functions often involve
the manufacturing of lots and lots of specific proteins.
So for example, myocytes that make up your muscles,
a large portion of their mass is one protein called myoglobin,
whose primary function is to bind oxygen
so that your muscles have enough fuel
to be able to power themselves, okay?
And so these cells will sit there,
and they're cranking out tons and tons
and making tons and tons of these myoglobin molecules
so that they can make sure that they are fueled up
and have enough oxygen ready to go.
And then just a little way down the,
I guess I don't know where it is on my body relative,
but elsewhere in your body, you'll find cells like B cells.
And these are the cells whose primary function
in their existence is to manufacture antibodies.
So each B cell, for example,
in your body can produce one unique antibody
that will bind potentially something, right?
Maybe it will never bind anything at all.
But the purpose of this B cell is that
perhaps one day, a foreign invader
will come into your body,
and the antibody that this B cell makes
will bind specifically to that invader.
And if it does, then you have basically tagged
that foreign material for destruction.
And when a B cell produces material
that detects a foreign agent, it will kick into overdrive
on a mass production scale of this antibody
and will undergo massive changes in its metabolism
and its architecture so that it can secrete
as much of this protein
into the environment as it possibly can
to try to basically tag all of those invaders,
whether they're bacteria or viruses or whatever
with this material so that they'll be destroyed.
But I wanna emphasize that cells
aren't really just limited to manufacturing,
say, a single protein molecule.
They can actually make things much, much, much larger
and much grander in scale.
And so we can also start
to think about the cell as a machine
that not only makes these nanoscale proteins,
but also makes microscopic devices and things.
And I'll give you one example
that one of my students has recently discovered.
She grows these very unusual cells
in the lab calledP. collini.
Their bark is much, well, I don't know.
They're cold-blooded killing machines,
as you'll see in a minute.
And the reason for that is that these cells
are able to manufacture a specialized structure
that we call the tentacle.
But in fact, the purpose of this structure
is to provide the physical support
and the chemical sensory necessary
to essentially puncture foods in the environment
and suck up their goodies.
And if you don't believe me, this is what it looks like.
When these cells, for example,
encounter something they wanna eat,
they puncture their targets and they use these arms,
these straws, essentially, they've built,
dozens of microns in length, to suck out all the goodies.
And then when they're done,
you'll notice they eat for a while, like you see here.
And then when they've had their fill, at some point,
they just throw a little leftover wrapper away, okay?
I think it's really funny because they're very,
actually, they litter everywhere.
So like when my student, Maggie, grows these, we watch these.
You come back the next day and there's just wrappers
of these carcasses everywhere, okay?
But what's remarkable, I mean,
it's fun to look at these obviously,
but these cells are essentially manufacturing
microscopic straws that can detect targets,
and upon contact, puncture and begin feeding them, okay?
So these structures are much longer
than any individual protein.
And other cells that you might encounter in the environment
can build extraordinary physical structures,
physical objects like this.
So that earlier cell that I showed you swinging
its sort of proboscis around to look for food.
Underneath that hood, there is an interwoven web
of protein structures that sort of form
this deformable mesh that allows these cells
to stretch and bend this structure
all through in their environment.
And these are structures
that you can actually even see with your naked eye.
I mean, they're over a millimeter long.
They are very large and they're just made out of proteins.
So these are the kinds
of microscopic manufacturing capabilities
that essentially defy any sort of skills
that we have in the laboratory to make ourselves.
So that's making stuff, and making stuff is great.
I was told not to walk around.
Okay, making stuff is great.
But another thing that cells can do that's quite remarkable
is that they can actually compute for us.
And what I mean is just in the same way
that you're listening to me and you're like,
you might be thinking, "Ugh,
when is this talk gonna be over?" or whatever,
your brain is making computations
based on the inputs that you're receiving from me
and the things that you're hearing,
and it's making evaluations
and choices and things like that.
And individual cells are able to do this as well,
but they're able to do it without having a brain
or anything like that, right?
So it's just a chemical system that's able
to perform these kinds of computations.
So how do these work?
How can you compute using chemical substances
instead of wires and transistors?
Well, I'll briefly introduce you to a very classic example
from history for how this kind of computation is performed
because I think it actually illustrates so nicely
how many biochemical decision-making systems
have almost direct parallels
to the kinds of decision-making systems
that you might use in an electronic system
and the type of computational structures
you would use there.
And so perhaps some of you have heard
about this bacterium called E. coliorEscherichia coli.
These bugs are actually quite remarkable
in terms of their computational capabilities.
And one of the decisions they make
that I think people in Wisconsin will find a little distressing
is these bugs love glucose as their food.
These bugs would like to eat glucose
all day if they could.
It's their favorite food.
You wanna know what they don't like?
Lactose, the thing we use to make dairy products.
They would prefer never to eat this
unless they were, like, absolutely starving, okay?
I don't understand why.
Somebody should give these bugs a curd, but...
[audience laughing]
But this is how their worldview is, okay?
And so how is this bacterium able
to have this sort of picky preferences, okay?
'Cause it doesn't have a brain;
it's just a little sack full of molecules, right?
And so we've actually known for almost 60 years now
how these bacteria are able to make this decision.
And it's quite remarkable.
To me, it's even more remarkable
that these two gentlemen were able to work this out
almost 60 years ago, in a time period
where it was perfectly acceptable to smoke in the lab
and the lab looked like a kitchen and things like this.
But they're very committed to answering this question
about why they don't like milk.
And what they discovered is actually perfectly analogous
to a Boolean logic gate.
And I'll kind of take you through how this works.
What they found is that the bacteria in its genome
has this region where it's gonna have all the genes
it would need to eat lactose, okay?
If it doesn't make these genes, it can't eat lactose.
It's not gonna waste any time making lactose.
And right in front of those genes,
there's two sets of DNA sequences
which are called regulatory sequences.
These are sequences that don't specify
how to make any protein,
but they're gonna influence whether or not
these proteins are gonna get made, okay?
And there's two kinds of regulatory sequences in here.
One of them binds a protein
that's called an activator, okay?
And this activator is required to be bound to the DNA in order
for these genes ever to be transcribed.
And so if this protein is not bound,
the genes will not be made into protein.
And in order for this protein to bind DNA,
it has to have bound to it
various by-products of starvation.
I'm not gonna tell you what they are
'cause they're not really important.
But the bottom line is,
is that if the cell is not starving,
this activator protein is not gonna bind
to this piece of DNA.
And as a result, you're not gonna make any
of these genes, okay?
So that's the first kind of input
to this control scheme that the cell has, okay?
The other one is what we call a repressor protein.
And this is a protein that if this protein
is bound to this piece of DNA, it will prevent these genes
from being made into protein.
And it doesn't matter whether the activator
is bound or not, in this case.
The binding of this repressor protein there
completely stops the ability of these genes to be made.
And this repressor protein has evolved
to sense the molecule lactose.
So if lactose is present in the cell,
then this protein falls off
and that frees up the possibility
that these genes can be expressed.
And so we can think about this kind of
for this cell's reasoning as saying,
"There better be some lactose around
if I'm gonna make these genes," okay?
And so what we have here are two regulatory sequences
in front of this lactose metabolism gene.
And we're gonna think of 'em as taking two inputs.
One says, "Am I starving, yes, no?"
The other says, "Is there lactose around, yes, no?"
And the output to those two inputs is a decision,
"Do I make these genes?
"Do I make the proteins that I need
to eat this lactose," okay?
And for those of you who might be electrical engineers
or anything like that in the audience,
you might recognize that the conditions for making lactose,
which are that both you must be starving
and there must be lactose in the media, are exactly the same
as the fundamental electronic logic AND gate
that essentially a foundational component
of all of our sort of computing devices, okay?
And essentially, you can then start to abstract
this gene regulation that this bacteria is doing
as a simple equivalent to an electronic circuit,
a very simple AND gate
where you need both lactose to be present
and glucose to be absent.
And only if both are true, then do you make these genes.
And so this is pretty cool
because this is basically Boolean logic
like you might find in a transistor made out of silicone,
and then we had to manufacture with various kinds of tech.
But it's built entirely out of those
protein components that I told you about.
And instead of it being electricity that's being used
to make this computation, it's biochemistry.
It's the binding of proteins to and from pieces of DNA
and the ways in which they interact.
So that's pretty cool.
But an AND gate will only get you so far in life, right?
And this is where what becomes more interesting
is that you can establish much,
much more complicated control logic by stacking,
just like you might in a computer,
multiple kinds of logic gates together,
connected in different ways.
And so if we go back
to that little video I showed you before
of that T cell that's interrogating the target cell,
and it's trying to figure out, "What's going on inside?
"Should I kill this cell?
What should I do to it?"
You might notice that there's this very dynamic interface
between the two, where it's sort of groping
and grappling and shaking it around.
At that interface, there are hundreds
of interactions between different molecules
on the surfaces of these two cells, which are being used
to inform the internal computational process
about what sorts of decisions it should make.
And it's actually quite remarkable
the number of choices that can be made.
You don't need to know any of those names, trust me.
They're all different possible inputs
that provide different kinds of signals
to the cell about what's going on.
"Should I kill this, should I not?
"Is this a cell that has a viral infection,
"or is there bacteria in there?
"What types of things should I secrete
depending on what I sense," okay?
And so by stacking hundreds of these on top of one another,
you can build a system that can create much,
much more complex decisions than a simple AND gate.
And in fact, many folks are beginning
to start to model these kinds of networks
as being almost like a biochemical version
of the neural nets that computer scientists are using
to process massive quantities of inputs
and make different outputs.
And I will say, as biochemists and cell biologists,
we still don't understand actually all the ways
in which the computations are being performed
by these kinds of networks as we go.
But it does suggest
that it's being built up from these more simple things.
So everything I kind of said so far
was about things where there's an analogy directly
to a computing strategy we have in electronics,
like logic gates and various kinds of neural nets.
But something that's very interesting
that cells can do as well is they can also use
very novel computational strategies
that are almost unique to chemistry itself
to do other kinds of computations,
like, for example, solve a geometry problem.
And one of my students in my lab works on a system
of proteins that can be found in bacteria
whose function is to help this bacteria know
where the middle of the cell is, okay?
They essentially need to be able to figure out
where their midpoint is so that when they divide,
they divide evenly into two cells.
They don't divide into a tiny little mini cell
and a big cell over there.
And so the cell has to solve this geometry problem.
"Where is my midpoint," right?
And I think if we were humans, we'd pull out the ruler
and we'd measure the two lengths,
and then we'd say, divide by two or whatever.
So how do these bugs do it?
Well, they actually use a strategy
that takes advantage of the chemical properties
and the things that are sort of unique
to a biochemical system, which is that these bugs
will essentially create a wave of proteins
that goes back and forth and back and forth
inside the cell.
And what they're doing is not trying
to make you get excited about waves,
although we, in my lab, are very excited about waves.
What they're actually doing is setting up
a wave structure that has a node in it.
And that node based on the geometry of the cell
will always occur at the midpoint of the cell.
So they set up a wave,
and the sort of spatial constraints
on how this wave propagates necessitates that a node
will materialize in the middle of the cell.
And that is how they actually choose
where their midpoint is.
So this is an example of a cell choosing a kind of method
for computation that's not really a way we do,
but is extremely efficient for them.
So briefly, we've now seen that cells
can make stuff using their genomes,
and those making proteins and making structures.
And we've seen how they can use proteins
to do different kinds of computations.
So let's think a little bit about
how you can put the two together to create a dynamic machine
that can do more than just make and compute,
but can kind of interact dynamically
with this world like a tiny little robot.
And I'll give you two examples real briefly here.
One is a very classic one where I'm gonna show you this video.
It's from the '50s 'cause I like
to pay my respects to the scientists of before.
The very famous video,
I've seen it dozens of times in my life.
This is a neutrophil here chasing after a bacteria, okay?
So neutrophils are immune cells in your body.
Their purpose is to find things like bacteria and eat them.
And this movie is, again,
almost 70 years old at this point,
but I think it nicely shows very well
how a cell is able to, you know,
it's not just a bag of genomes and things like that.
This is something where it's sensing the location
of where the bacteria is,
and then it's modifying its structure
so that it can grow towards it.
And it's going to keep doing this
and modifying its structure and sensing
and modifying until it catches up, okay?
And what this means is that this behavior
that we're seeing here is actually sort of powered
by this self-driving control loop, okay?
We have a process in which the location
of that foreign bacterium is somehow detected,
and the response is to try to change
and build its structure so that it reorients
towards where that bacteria is.
And it's gonna keep doing this, sensing, responding,
sensing, responding sort of in this loop
until it finally makes contact, right, with that bacteria.
And when it does,
that's gonna trigger this engulfment response.
And if all goes well,
you eliminate these bacteria, okay?
Now, I wanna emphasize, because I'm about to show you
something else on the next slide.
This video is sped up about a 120 times.
So if you were looking under the scope,
it would not look this cool, I'm afraid.
But if you speed it up, it looks really cool.
However, this same principle of self-driving control loops
and sensing and responding can happen
at exactly the same kind of timescales
that our own lives are going on.
And they happen with that organism I showed you before
where we have a simple, single-cell pond organism,
and this is real-time.
So this is what it looks like if you look under the scope.
You'll see this little single cell
is whipping this structure around.
And what is it doing?
It's looking for something to eat.
And right here, you'll see in a moment
that when it finds it,
it actually paralyzes those objects,
and then you will see, it opens its mouth
and it starts to eat them, okay?
But the point here is that, once again,
the behavior of the cell is actually governed
by the self-driving control loop.
And essentially, this cell has an algorithm
that's implemented in it, which enables it
to perform a random search of its local environment.
And at the tip of this structure where it finds these preys,
it has all kinds of proteins loaded up in there
that can sense what it's evolved to eat, okay?
So a repertoire of things that it likes to eat.
And when it contacts them, it will release toxins.
That takes about a couple milliseconds.
And then once the prey has been sort of paralyzed,
then it can take its time to enjoy its meal, okay?
And so this is just kind of another example
of how combining those together
can yield these sort of robo-like systems, okay?
So now, we've sort of projected the idea of cells
onto various kinds of paradigms
that we don't often think of as being biological, right?
Maybe some of you do
if you're biologists, so whatever.
But many of us don't think about the computer and think,
"Oh, the cell is computing and things like that."
And so what I wanna do now is show that
that sort of abstraction and thinking about cells
from the vantage point of different kinds of technologies
can give us clues for how we might actually engineer cells
to do new things for us.
And not only to build cells that do different things,
but actually to potentially embed cells
as a part of a technology in our everyday lives,
where we're essentially harnessing the abilities
that cells have to do new things that we could not before, okay?
And to start with this,
we can just see that we just imagined cells
as these kind of familiar analogs
or analogs of these very familiar things.
So we thought about them as molecular factories
that could manufacture huge quantities of substances.
We thought about them as chemical computing devices.
Here, I, again, pay my respects to the years of old
in terms of what computer is.
And here are those very small robots
that I was telling you about
that deliver food to kids all around campus.
Quite impressive, right?
So we've seen that we can imagine cells
as being similar to these kinds of things,
but is that abstraction useful?
Can we actually repurpose living systems
to build out these kinds of technologies in new ways?
And the analogy that I'd like you to think about
is that if we could do this,
it wouldn't really be the first time
that we had done something like this as a human species.
Because many of the electronics
that's powering our computers and everything like that,
they never existed in the form that we have them today.
And they came from us looking at things
like lightning strikes and other kinds
of natural phenomena that inspired us and dazzled us.
And then we found ways to domesticate those kinds
of forces of nature and make them bend to our will
so that we could have new kinds of technologies available to us.
And so in the same way,
we've domesticated these other forces of nature,
can we potentially do the same to cells?
And why might you wanna do this?
I mean, don't we have factories?
My colleague, Vatsan, who's also a synthetic biologist
is like, "Oh, people are always trying too hard
in terms of selling these things."
But I would say that cells are completely unmatched
in certain abilities they have.
And in particular, it is their ability to organize
and manipulate energy and matter
at the microscopic or nanoscopic length scales
that really, there is no parallel
on our planet to their capabilities.
And certainly, we have ways of manufacturing
very tiny objects and making very tiny things.
I mean, we just talked about computer chips
and things like that.
But to make those objects requires
enormous investments in energy.
We have to use huge amounts of fuels or heat things
to extraordinarily high temperatures, okay?
A cell does all of these things at room temperature, right?
My students, they grow 'em in the lab,
it's like 30 degrees.
That's, like, what it takes.
They can also do all those things
using simple chemical fuel sources as their supply, right?
So they can do it using glucose
like we just talked about with theE. coli,
or things like plants can harvest light
and harvest energy from light to build their machines, okay?
And what I think is perhaps the most useful thing is that
if you've ever fabricated, like, a PCB chip or whatever,
you go to all these great lengths to do it,
but you can only make one thing from all that effort, right?
The thing that you make, the wafer that you have,
the chip that you use for that lithography,
you can print many chips with it.
But if you wanna make a new chip,
you're gonna have to make a new mold.
And so this kind of manufacturing,
it's kind of scaled towards building one
or two things from all this effort.
A cell, as I told you,
is essentially infinitely reconfigurable.
From one genome, we make all the cells in our body, right?
And that means that you can start to imagine
that cells are almost like some sort of living 3D printer
where thousands and thousands of different designs
can be installed into this living system.
The system can be shared with other people
because you can grow it,
and then hand it off to your friends.
I mean, my students have sent DNAs and cell lines
and things like that they've made to other people.
It's an infinitely shareable medium.
And it can be loaded,
preloaded with all kinds of extraordinary designs.
And all you need is, like, some sugar to get it going.
And I think that's pretty incredible
to think about what you might be able to achieve
if you could really find the best way to exploit that.
So let's kind of then think about some ways
in which cells can be the different technologies
that we thought about them in useful ways.
And I'll tell you some that are already used
in our everyday lives.
And then we'll talk a little bit
about some more futuristic ideas as well.
So the first thing we gotta think about
is getting cells to make stuff for us, okay?
And this, again, gets back to this idea
that the genome contains the instructions to make parts
and the proteins are the things that they're gonna make.
So in this arm, we have this
sort of manufacturing process going on here.
And the key thing that's really nice about cells
is that because the information
to make the proteins comes from here,
in order to make cells make different things for us,
we can simply modify their genomes
because by modifying the genome of a cell,
we can control what proteins it makes.
And those proteins might be its own proteins
if we wanna maybe make the cell behave in a different way.
But we can also make them make proteins
that are completely new.
Maybe they come from different organisms,
maybe they're ones we designed on the computer,
but the rules just say that the cell
will make whatever we tell it to.
And so this is a tremendous capability
to manipulate these organisms to make stuff for us.
And let's think about some things
that they actually are already making for us to this day.
So I don't know if anyone has diabetes; my grandma did.
May she rest in peace.
But what used to be the case
when she was a young woman was that
when she would need her insulin,
that insulin would come from a pig.
That is, they would take the pig
and they would get the insulin out of the pig,
so it's pig insulin,
and she would take that insulin for her diabetes, okay?
And that's because there wasn't a good source
of human insulin unless you're gonna try to,
I don't think the ethical rules are appropriate
to drain the blood of a human
and take their insulin and use that instead.
So this was the best choice that they had, right?
And of course, this doesn't really work that well
because even though it's kind of a substitute
for our insulin, it's not the same protein as our own.
And as a result, you can have an immune response to it
or it doesn't work as well.
It's really suboptimal.
So what happens in today's world
is that most of the insulin that someone
who's diabetic will take comes actually
from what's called a recombinant source.
And what that means is that an organism,
in fact, oftentimes theE. colicell
that I told you about with the lactose disdain
for our good lactose,
the genomes of those organisms are modified
to basically include this human insulin gene.
And not just like any insulin gene, our insulin gene,
the exact one that we would have for our proteins, okay?
So we can put those genes inside the cell,
and then cause that cell then to manufacture
huge quantities of human insulin for us, okay?
And the key thing is that by programming
the bacteria to make human insulin,
even though it was made in a bacteria,
for all intents and purposes, if you give it to us,
it is exactly the same as human insulin.
They made it exactly the same way.
It's the exact same sequence of amino acids.
It's the exact same protein, okay?
But we can make it at scale.
So imagine if you go to any of those breweries
and you see those huge vats of yeast
making delicious beer for us or whatever,
there's another place somewhere
where people are making huge vats
of insulin from these bacteria, okay?
So instead of having to sap those poor pigs
to get crummy insulin, we can tell cells
to manufacture our own insulin for us.
That's pretty cool.
Now, of course, that's taking someone else's cells
and getting them to make useful things for us.
But in the last few years,
we've actually seen a different kind of paradigm
in which our own cells become the factories
to make a foreign material.
And so many of you
may have taken an mRNA vaccine for COVID-19.
And what that vaccine was
was it was a nanoparticle containing an RNA molecule,
which contained the instructions
for making large quantities of a COVID viral protein.
And this nanoparticle was taken up by your own cells,
and your own cells then served as the factories
to manufacture large quantities of this foreign material,
in this case, the spike protein here
that would serve as the antigens
for your own immune system to have a response, okay?
So we don't have to make it that the manufacturing
happens in the lab outside there.
The manufacturing can be performed directly inside you.
Okay, now that's a little scary sometimes too
because maybe you gotta think about
what you're manufacturing in your own body.
But it does create a new paradigm
where instead of tedious manufacturing,
purification of these protein products in the lab,
separation, all those things,
you can send the DNA materials into your body
and get your own cells
to do the work for you; pretty amazing.
Now, we don't have to stop,
of course, at the single protein level.
There's active research going on all the time
to use cells to build larger structures for us
with unusual things.
So there's an interesting example
where there's a lot of nanomaterials work done
in which people actually use bacteria
to make magnetic particles inside them,
like these structures here, which are called magnetosomes.
And the regular magnetosomes aren't necessarily
that interesting on their own,
but these are perfect, defectless crystals
because they're made by a cell using proteins
to help structure and template this thing.
And scientists are finding ways to dope them
with interesting rare metals and things like that
to create essentially remarkable sort of
electronic magnetic systems
that can be then isolated from the cells
and used for different other kinds of things.
And in just one other example, you could even get cells
to make pure biochemical machines for you
similar to the structure,
similar to those sort of single-celled dynamic structures
that I showed you before.
Here, you can actually get cells
to make chemical machines for you.
These are little flagella
that have been isolated from living cells.
You can actually take them out of the cells,
strip away all the membrane, all the cell, all the stuff.
You feed these a chemical fuel source,
and they'll start swimming around
and moving through in their environment
and binding things and interacting.
And scientists are working to modify these
with different kinds of detectors and things like that
to really make these tiny little robots
and things like that.
So you don't have to stop really at the single protein level.
You're really just limited by your imagination,
I feel, in terms of how complex
the structures that you create can be.
Now, in this last little part,
I'm gonna tell you a little bit about
how we can get cells to perform new computations
and build towards getting cells to behave
in new ways sort of as robots.
And so this time, we're gonna be thinking
about this other arm in our kind of model of the cell
where we have proteins doing work to then communicate
some sort of computational result
back to the cell to perform.
And since we've been sort of thematically building
around this T cell interacting with the target,
I wanted to tell you about some work
that I've previously been involved with
that I think really gets at the power of trying
to project these computations onto other cells.
So what I showed you
in the original video was a native T cell
interrogating a regular cell in the body,
but there's a great interest in engineering T cells
to be able to recognize cancer cells
that they encounter in the environment.
And why might you wanna do this?
Well, the regular way in which a T cell
will recognize a foreign target is based
on an interaction between its T cell receptor
and antigens that are presented
as MHC-peptide complexes.
Doesn't really matter for this audience what that is,
but these are the interactions that tell the cell
whether foreign material is present in this cell.
And of course, the challenge sometimes with cancer
is that we have a cell in our body
that we would like to eliminate,
but oftentimes, the majority of that cell isn't foreign, right?
It's our own bodies that have become messed up
in some way, okay?
And so that makes it hard for our immune system,
which has evolved not to destroy itself
to recognize these targets often.
And so scientists, myself included,
have done work on the design of synthetic proteins
called chimeric antigen receptors,
whose purpose is to recognize new proteins,
specific proteins that we choose,
that are overrepresented on cancer cells, okay?
And the idea is that this synthetic receptor
will emulate the behavior of this native receptor,
such that when this recognition
of some sort of cancer-specific marker
on the surface here is recognized,
it will trigger that same sort
of downstream cascade of killing, and yeah,
releasing toxins and killing the target cell, okay?
And this is a paradigm which has actually
been used clinically, not my products,
but it has been clinically used
to treat various kinds of B-cell lymphomas
that were previously thought to be untreatable.
And people have been, basically, their T cells are removed.
They are made to express this new kind of receptor,
and then they're put back in the body.
And then those cells go out and they seek
B-cell lymphoma cancer cells, and they destroy them.
And this has actually been the case
where many people that basically were on the brink of death
are now alive to this day; pretty amazing.
Now, you don't have to stop at a single input recognition.
So you can take that same idea
that I told you about with the lactose, right,
where you have a bacteria that's making a sort of
Boolean logic decision about what's going on,
and you can expand this kind of decision-making
to your engineered cell products.
And so when I was in industry
before starting my professorship,
I worked on this strategy for expanding
that kind of target cell recognition
between an engineered T cell and a cancer cell
to basically display more complex logic.
And what this was useful for,
and I won't go into the details of how these receptors work,
but a challenge for that paradigm I just told you
is that cancer cells, as we discussed,
are essentially our own cells, but with some problems, right?
And so a single thing that tells you,
that you try to use to identify a cancer cell
is often not sufficient to be able
to not destroy other tissues in your body, right?
And in fact, many failures
when people try these technologies clinically
for the first time was they would kill the cancer,
but then they would also go off
and destroy other tissues in the patient.
So it looks like it's working,
but then your heart gets vaporized by these cells.
And so by building these kind of
more complex combinatorial logic gates,
we can make a stricter requirement
for what kinds of signals are required for a kill.
That is, you might need to, kind of like the old game
ofGuess Who, "Are you wearing a hat?
"Do you have glasses?
What color is your hair?"
If you can build up a profile for your cancer cell,
then you can encode that target for your thing
and achieve more selectivity.
It's pretty cool.
Okay, so with the last five minutes,
I wanna tell you a little bit about
how we can integrate those two parts of manufacturing
and computing together in one last arc
to kind of think about creating cells that can act
and do things for us that are more like robots.
And my students are here,
so they might be mad about this next part
because one thing that we're trying to do in my group
is program cells to actually be able
to be the scientist for us.
That is, to make measurements about themselves
and report back to us, okay?
You can imagine this cell being like,
"I'm gonna do this thing to myself
and have your results back for you quickly."
And so, my joke is now you have to pull it back.
But it was my plan
to replace my graduate students with cells.
No, of course not, because they're the engine
that is creating all of this results.
But that's one idea we have is,
can we turn the cells into the scientists for us?
And an area that we focused on quite a lot
is actually this little text bubble here
'cause how do you get a cell to tell you
what the results of its computations are in real time?
How do you get it to communicate to you
what's going on or what exciting result it has?
Sometimes I have a hard time getting my students
to tell me what exciting results they have.
So how do you get a cell to do it?
Well, this is where we can start to connect back
to some of those earlier slides I showed you.
'Cause remember how I told you that those bacteria
perform that geometric computation
by creating this kind of wave structure
like I showed you here?
Well, it turns out that we can make cells, human cells,
manufacture this wave generation system for us.
And when we put those into human cells,
they create these stunningly powerful
and beautiful oscillations.
So these are human cells, where you're seeing
protein oscillations traveling through them.
It's some beautiful psychedelia, for sure.
My dad is a child of the '60s, so he loves seeing these videos.
But I wanna emphasize
that it's not just about creating cool visuals
because it turns out that the oscillations
that we can produce are extremely powerful
as a communications media for us to go back and forth
between what the cell is measuring
and what's going on.
And that's because these oscillations
actually enable us to turn cells into the objects
that are almost like radio stations,
where each cell will produce some sort
of oscillating data structure, which we can encode
all of its calculations and computations in.
And the idea is quite simple.
We have a beautiful image of these cells
and you could stare at it all day.
And my dad just says,
"Keep 'em coming, keep 'em coming."
And I'll put my Grateful Dead records on.
But the power of this structure is that
if you actually analyze the intensity
of these oscillations over time, they'll produce
this astonishingly regular oscillation
inside a human cell.
These are the kind of oscillations
that never exist inside these cells on their own.
And that means that what we have
is a unique sort of high frequency signal running
inside these cells just like a radio station.
And so we can use techniques from electrical engineering.
Those would be things that would be pretty much
undergraduate level electrical engineering tools,
where we use things like Fourier transforms, et cetera,
to isolate the specific cellular radio signal of interest
and project it back onto the cell, okay?
And what this enables us to do
is start with data like these, where it's great for my dad,
but it's not necessarily scientifically useful
on its own.
And then begin with these analysis tools
to pull out quantitative, where here,
I've color-coded them by different kinds of data
that we're collecting, the information
that's going on inside here, okay?
And because each cell is sending this data to us
on this very unique high frequency structure,
it actually provides us an incredibly straightforward way
to access this kind of hidden information
going on inside the cells.
So it's actually been super useful for us in the group
because we can then extrapolate these circuits
to do really interesting kinds of computations.
So if the cell has received some kind of signal
from its environment that turns something on.
In this case, it's a molecule called PKA.
It doesn't really matter for the purposes of this talk.
We can make it so that when the PKA activity is on,
we can see data appearing
in some sort of oscillation, okay?
And we can then get cells to encode the results
of their computation for us on this little radio.
And it really does look like a radio signal
because when we analyze it, we have a carrier signal
that's always being broadcast to us
from inside the cell.
And then the data that we're interested in,
like whether that kinase was on
or whether some protein is active or whatever,
they appear to us as modulation
of the waves that are produced, okay?
And although it seems crazy,
it really is just taking the same concepts that are used
to process radio data or telecommunications data,
and then reencoding them
in a sort of biochemical fashion, okay?
And using this approach,
we're actually kind of essentially creating
these little cellular scientists that can report out
on all kinds of interesting stuff.
You, again, don't need to know what PKA or ERK is or mTOR.
They're things that we care about as scientists,
and then we send them into, these cells
into different environments,
and we can start to learn about what's going on
in these individuals as they form different layers
or as they develop into organoids
or even as they potentially develop into a large animal.
So every cell is gonna tell us what's going on.
They're gonna do the experiments for us.
And then my students are gonna put their feet up
on their desks and be like, "Ah, perfect."
And it'll be worth it because they did all the work
to make the machines do that.
Okay, so with one last thing,
I just wanna emphasize that we don't only use
these kinds of tools to create data structures.
We can also take advantage of their properties
to manipulate the spatial organization
of cells in new ways.
And the key thing that enables us to do that is that
that pair of proteins that I just talked about,
they form what is sort of an old-timey chemical structure
called a reaction diffusion system.
And again, you don't need to know
what the partial differential equations mean.
All you need to know is that the systems
under certain conditions are actually
what gives rise to beautiful, beautiful patterns
in animals that we see in nature.
So for example, this beautiful fish pattern over here
is the result of this combination
of molecules reacting and diffusion together.
And they call these Turing patterns.
I should have capitalized the T
because this concept was developed
by famous mathematician, Alan Turing.
And so a student in my group,
Eden, has taken these kinds of components
that we've been working with,
and he's started manipulating them in new ways
to get human cells to actually produce beautiful,
stunning patterns inside themselves
that are essentially identical to those kinds of patterns
that we can create...
That were predicted to be created in animal scales.
So this is like a single human cell
that now has all these beautiful spots.
And while it's, of course, beautiful,
one of the things we're using these kinds of patterns to do
is to organize components in the cell in new ways.
So for example, getting them to template
the location of receptors for other molecules
and things like that.
But it does bring me to one last thing
that I believe that we should be able
to project onto cells as something they can be,
and that's works of art.
Because I really think
that these are truly beautiful things
that my students have created that are a product
of their understanding of how the cell works
and the plasticity and manipulability of those systems.
Okay, and so cells don't have to only be a technology.
They can also be a canvas where our understanding
of biochemical principles and cell biology
could be manipulated to create sort of astonishing displays.
So long term, of course, our goal is to,
of course, build new kinds of technologies
and products out of cells, where the idea
is to emulate those key features of cell biology
to enable them to then perform new kinds of tasks.
These might be therapeutic tasks
like I talked about with the T cells,
but these could also be manufacturing
or computational tasks
where perhaps cells might be more well-suited
for performing certain kinds of computations for us
than the traditional computing paradigms
we have to this day.
So to just sort of sum up where we're at,
I told you about how I like to think
about cells in the simplest way.
And of course, I don't want to imply
that the cell isn't extremely complex.
It's extremely complex.
But by abstracting a little bit,
we can see that there's some key design principles
underlying their form and function.
And those design principles can be really understood
in terms of things that are familiar to us,
like making things or computing or building machines.
And that thinking helps us see ways
to repurpose those living technologies
or those living cells as technologies
where potentially, we can start to reimagine
how we might create nanoscopic devices or machines,
and ultimately have a future that's not so reliant
on burning all this energy
and operating in high temperatures,
but a world in which our technology
is sort of at the same temperature
and length scales as ourselves.
And so with that, I just wanna say thank you very much
for the opportunity to kind of give you
my philosophical worldview on cell biology.
If you're interested in learning more,
you can visit our website
and read the different things that we've been up to.
I wanna thank the funders who gave us the money
to be able to do all those kinds of fun experiments in the lab.
And I, of course, really wanna emphasize,
and maybe they'll stand up.
My students, can you stand up?
My students are here and they're embarrassed.
But I really wanna say...
[audience applauding]
It is my students....
[audience applauding]
It is my students who generated everything you saw today.
So they sat in my office and I said,
"You gotta do this, and you gotta do that."
And then they went out there
and they produced all of this extraordinary science.
And so they are the real heroes, I think.
And when I think about this sort of biologically-powered future,
they really inspire me
and give me tremendous hope for that vision.
And with that, I'm happy to take questions
from you guys about anything that you might have.
[audience applauding]