(intense electronic music)
- So, you may ask, what's that title about?
Well, when you are asked for a title early,
sometimes you don't know what you're gonna say.
(audience laughing)
So, I figured I could say anything and
what I was thinking about was Ramon y Cajal
and what he would have thought beyond
his great gift of seeing things with the Golgi technique
that were actually hiding in a forest of complexity.
That lead him to speculate and make predictions that
we are still following in Neurobiology today
about how things actually connect.
If he were alive today, he would be in wonderment,
if you like, regarding all of the scales of details
that we can now describe with
different kinds of microscopies and labels.
He would probably be, as I think
this conference is considering, amazed at the gaps.
So, where are we limited with regard to filling
gaps across, either the spatial scales,
all the way from macromolecules to organs,
to the temporal scales?
So, today, I'm gonna tell you a little bit about
filling a few gaps all the way out to Life Spans.
Two projects about dendritic spines
and about lifelong memories.
But, I can't do this without giving you
a little background on techniques.
At The National Center that Jennifer mentioned,
we use really two techniques
to do electron microscopy across scales.
One is Serial Section Electron Tomography where we take
thick sections, map them to get the best
X, Y and Z resolution.
We look at systems that can be manipulated,
so here a vestibular hair cell is moving around,
that's what it's doing.
The top is rocking and it's changing the output.
Or we use a method that was pioneered by Winfried Denk
called Serial Block Face Imaging.
You'll see an alternative of this from Hal Hess shortly,
where you can put a microtome inside of a scanning EM
and just automatically record image after image after image.
Kinda like taking a look at a loaf of bread as you
keep slicing it, and get
a reconstruction with modern methods.
If you selectively stain in a cell.
As was done by these colleagues.
This was a sample we imaged when we first got this
going about ten years ago.
That's the endoplasmic reticulum in the mitotic spindle.
If the endoplasmic reticulum is stained, in this case,
with horseradish peroxidase, you can then pick out,
these are mitochondria.
Those are lysosomes.
Wait til you see the ER, and this cell's just in the
early stages of dividing.
So that's all the ER.
So how do you find that stuff hiding in plain sight?
First, unashamed pitch, we push this technology quite a bit.
While Harold has pushed the technology
he's gonna tell you about.
We've been pushing this to higher and higher resolution
and bringing stains in, as you see here, so that we can
genetically mark components in the context of this method.
We pushed it, so that you can look quite easily,
at structures like the golgi apparatus, mitochondria ER.
But we've done that through the benefit
of a long collaboration with Roger Tsien, from
about the time Roger came to UCSD.
Even before the fluorescent proteins, but then with
families of proteins, coming up with ways of
marking genetically for EM.
Then ultimately with Alice Ting,
APEX, which is a small peroxidase.
Now, that was preceded by activity trying
something called Photooxidation.
Using a reactive oxygen generating probe.
Something as simple as Eosin, to generate reactive oxygen
and capture diaminobenzidine, which then can be reacted
with osmium tetroxide or ruthenium tetroxide to give
you electron density in locations.
At the scale of molecules, we can see receptors marked
quite clearly with this method.
Here's an example, getting us into spines now.
Eric Bushong, who's here in the audience.
When he was a graduate student in the lab, now he's
a senior scientist in the group, tried out using
phalloidin, which binds to actin.
In this case with fluorescein, but also with eosin.
We had it specially conjugated, to give us a way
of doing actin by EM.
At that time, Francis Crick had postulated, 1982, that,
"Do spines twitch?"
You can look this up, it's a beautiful little
theoretical paper, which was Francis' best thing being
a theoretician.
So these are all dendritic spines marked by actin
in a confocal microscope.
The cell, that's a Purkinje cell was also injected,
just to see it with a red dye.
At that time, our tomography was best done with
massive microscopes.
Here's a person for size reference.
We could punch through with these
very high energy electrons, three million volts,
through samples as thick as ten microns.
Kind of a light microscopic sample,
but you can see inside.
This is from a Fragile X animal model, and you can see
how tortured, or variable, the spines are.
That's a hallmark of that disease, in animal models
or humans.
Then if you switch to the Eosin phalloidin, do more or less
the same thing.
That's the light microscopy.
Actin looks like it's all over.
It's not actually.
It's concentrated in the spines and if you punch
through it, this is not a tomogram, it's just a projection,
the spines are full with this
flocculent material that's actin.
It's not just filaments, it's like we know in cells now,
a gel.
Actually forms dodecahedral plates.
So, fast forward to today, we continue to develop these
techniques and the math, and Rick Lawrence
is a Mathematician, Sebastian Phan, who I believe is here,
is a Polymer Physicist, we developed software
and methods and automated these microscopes,
so that we take as many as
a thousand or two-thousand images of the same object.
By tilting the sample, rotating it, kind of like having
a thousand drones in this room simultaneously
taking pictures of you.
Then you have a super sampling, so this solves to some
extent, what Daniels said is the Z-Problem.
What you just saw play, was one of these volumes.
I'll show you another one, but if you extract the
dendritic spine from that volume,
that's what it looks like.
After you use some fancy tools to follow the actin.
So that's the post-synaptic density.
This is a little finger-like process.
Probably this guy was trying to extend.
But this is just a surfacing of the actin.
Here is a more recent one with something called the
Direct Detector, which we invented at the center.
Here's the spine, head, neck, the shaft of the dendrite.
These are actin polymers.
The little balls you see are actin monomers.
Here, you can even see, if you are close the to front,
membrane proteins in the membrane.
Then this is extracellular matrix.
Perhaps the perineuronal net, that I'll talk about in
a moment.
What you can see actually connects from the extracellular
space, through proteins in the membrane,
on into the cytoskeleton.
That's the second part of the talk.
If you look at this as a volume.
Just one slide, you can see how rich this is and
how we extracted with the right algorithms,
which you saw on the previous slide.
So this is what we do today, at even higher resolution
than this, to match up the molecular details that
are coming from structural biology.
Then to begin with different cadence of experiments
to look at what changes during sleep, wakefulness, time
scales that we can actually stop action quite easily.
So with colleagues in Munich and in Stockholm, we developed
methods to extract this kind of information in large scale.
This is just an example of how this is done,
slice by slice, and you can begin to study these
and consistency between spines in different regions,
or as was published in Science recently by a group
collaborating with us.
How this changes when you sleep or awake.
Spines shrink by 20% when you sleep.
More adventuresomely, we're saying okay, if we know
it's actin, or the majority of what's there is actin.
What does it look like if you substitute for the center
lines that we defined, for the actin that you saw in that
previous colorful spine spinning, actually actin?
Does that tell us anything about the charge
and the crowding?
So this is taking actin, replacing all the threads.
This is actin from the PDB.
Why do we do that?
Because the actin is highly charged, very acidic,
and this leads us to predict that the actin
creates an ion biding matrix, a gel, and it's actually
the sol-gel changes that may be driving a lot of the
physiology that's interesting.
That's a speculation.
Moving on, back to that extracellular matrix,
in a short amount of time, I thought I'd try and
squeeze in, what I think is one of the most exciting
projects, kind of a leave from Roger.
This is what he and I, and he was most excited
about when he died.
Projects now being led by Varda Lev-Ram, who is here.
Having to do with life-long memories, and Martin Hetzer,
who is also involved, because this techniques overlap.
Roger's hypothesis is this, you can look it up, it's in the
paper postulating that very long-term memories might
be stored in a pattern of holes
in the extracellular matrix.
The idea being, if the extracellular matrix holds
state and the more dynamic things, like Daniel talked about
and you'll hear more about.
Know about the state of that part of the brain, then those
things that turn over will come back or form those
parts of cells, guided by the extracellular matrix.
Kind of like the extracellular matrix is the stone
that's chiseled in, that gives a durable state
for the brain.
So that was Roger's idea, that this extracellular matrix
would be edited by MetalloProteinases, synapses formed,
synapses come to a shape by activity or size.
Predicted that the synaptic proteins,
pre- and post-synaptic would have short half-lives,
relative to the extracellular matrix.
So how do you test that?
How do you play with that?
Well, sorry, this is just a little bit more about the
Perineuronal Net, which had been described by Cajal
and others.
This is what it looks like in light microscopy
with wisteria floribunda as a fluorescent stain.
And this is some of the molecules that are known to
be associated with it.
So you can use proteomics, and look at that.
You can stain it, sorry, I got ahead of myself,
You can stain this, the same way that it was done
by light microscopy, by doing a peroxidase reaction
to mark that material in the extracellular space.
You can reconstruct it by the methods that I showed
you, to see what it looks like.
The synapses are in these holes.
And then the question is, "Does it stay around?"
What Varda did, following a protocol that Martin Hetzer
had first done, was create animals that are 100%
nitrogen 15.
You're otherwise nitrogen 14, so this is kind of the most
expensive and heroic pulse-chase experiment.
You can see the paradigm here.
What is it, eight hundred dollars a kilo, for the food,
something like that?
So these experiments, for the food, could be a hundred
thousand dollars for a colony of sufficient size.
Then at the right point, after let's say, a six month or
18-month chase, with the normal nitrogen.
You sacrifice animals from the colony, grind up there
brains, do proteomics.
Then you are able to ask, synaptic proteins have short
half lives.
Those molecules that I said are part of the extracellular
matrix at six-months, still 30% of them.
At 18 months, they're decreasing, but some of them
are quite significantly more persistent
than those constituents that everybody's excited about
in synaptic plasticity, which do turn over.
This is supportive of Roger's hypothesis.
Can we image N15, N14, so then we went after tricks
that are done more in geology, or in astrophysics,
looking at meteorites, or whatever.
Something that was taught to me by a colleague,
Victoria Orphan, at Cal Tech, working on some samples from
the ocean.
This is a machine that uses a cesium-beam, knocks out atoms
secondary ions.
Runs em down something like a mass spec column and then,
point-by-point, you get a collection of masses for
as many as seven different atoms.
You can make a map.
So, one of the things we tried, Nick's post-doctoral
advisor, Jack McMahan, so this goes back a way,
postulated and then proved, that agrin, a molecule that's
secreted into the extracellular matrix guides
synapse formation for the neuromuscular synapse.
We said, well, we have intercostal muscles from these
mice, what do the end plates look like?
Do we see a signal from this method that I just showed you.
Yes, so that would be predicted.
Here it shows you can do this.
We went from there, to ask, in these samples, from the
mice that Varda grew.
What about this stuff?
This extracellular matrix, is it old?
Here you see, doing the same sorta thing on those samples.
That in deed, it is. Okay?
And this by the way is myelin.
Myelin turns out like you saw maybe, if you were paying
attention the bottom.
Myelin basic protein, two other myelin proteins are old.
So this is telling you, if you look at the brain
after the majority of proteins have turned over.
Six months, 18 months later, what piece parts are left
behind.
And here, this is the stuff
that presumably is left behind.
Turns over very slowly, and these terminals.
These boutons come in, plug in, in between, so this is
how would you say, data that is headed in the direction
I think, of strongly supporting Roger's postulate.
All of this is unpublished, but I think it's exciting.
It's the product of, I think,
great thinking by many investigators,
great colleagues, great collaborators, generous support.
This is the cast of characters, some of whom are here,
and I think with that, maybe I might end it early.
(laughter and applause)