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EDWARD BRIGNOLE: My name's Ed.
I'm a postdoc in
Cathy Drennan's lab,
and previously, I had worked at
the Scripps Research Institute
with Francisco Asturias.
So some of the work
that I did there
is what Liz and Joanne like,
and we'll talk about that.
So I thought I'd start with
just finding out, has anybody
here done electron microscopy.
You've done some EM.
OK, on--
AUDIENCE: Gold nanoparticles
with a [INAUDIBLE]
spirit thing.
EDWARD BRIGNOLE: OK.
Over here?
AUDIENCE: No.
In St. Louis.
EDWARD BRIGNOLE:
In St. Louis, OK.
So you sat at the microscope
and worked on obs and--
AUDIENCE: That was my
favorite [INAUDIBLE]
EDWARD BRIGNOLE: Yeah.
Anybody else?
So how about a light microscope?
You guys used?
High school biology, maybe?
OK.
Everybody's used a
light microscope.
All right.
So that's good.
And then I guess at
this point, you guys
have had two lectures
on fatty acid synthesis,
so you sort of have some
feel for the enzymes
and who's involved
and what they do.
All right, so I thought
we'd spend the first 20
minutes talking about electron
microscopy and what it can do
and how it could be used.
And there is
actually quite a bit
that's changed since
this paper in 2009.
There's a lot that's happened
in the last few years.
And we can talk
briefly about that.
And then we can move into
fatty acid biosynthesis
and tie that into what you
guys have learned already.
And then there was a
bonus paper at the end.
If you are really
excited about this,
there's some polyketide
synthase structures
that have come out in
the last year or two.
And those are
pretty interesting.
So if you've got the handout
handy, there's some questions.
These are what I thought we'd
focus the conversation around.
The first part's about
fatty acid synthase in EM,
and then there's these
bonus ones at the end.
So when you guys were looking
in the light microscope,
you're probably looking
at biological samples,
I would guess.
So you were probably
looking at, say, a cell.
But all the bits and
pieces of the cell
that perform all these
interesting functions,
we want to understand these.
And so being able to actually
see them and see them in action
allows us to understand
how they work.
So for instance, if you pick out
this piece of machinery here--
and you can see that
it's got an active site
where it binds substrate
and maybe moves it around
or acts on it in some way.
And you might have
allosteric subunits,
and you can find that it's
got four subunits that
are round like wheels.
And it can move from
one place to the other.
This is just an
analogy, but same thing
would go for, say, motor
proteins transporting cargo,
or in this case,
fatty acid synthase.
So if you've used
a light microscope,
the electron microscope is
conceptually very similar.
You've got the light source
at the top versus an electron
source.
Condenser lens will focus
that on the specimen.
The objective lens
forms the image.
It's magnified by the projector
lens, and what you get out
is this enlarged image.
So you can see things that
you couldn't see by eye.
Light microscope, you can
get up to about 1,000x.
And in an electron microscope,
you can go up to 500,000x
or even beyond that.
So maybe an interesting
place to start here
is why can electron
microscopes do this
but light microscopes that.
Why can you get only
this magnification
with a light microscope?
Guesses?
If you look back up at the
top, what are the sources?
You're using light
versus electrons.
Why would you be able to get
a higher magnification image
using electrons than light?
AUDIENCE: Diffraction limit.
EDWARD BRIGNOLE: Yeah.
Do you know why?
Why would light have
a diffraction limit
that's in the micron
range or nanometer
range versus electrons in the
actually like picometer range?
AUDIENCE: Since your
wavelength could be--
EDWARD BRIGNOLE: Exactly.
That's what I was looking for.
Yeah, wavelength is
what I was looking for.
So either visible or even if
you go to a UV light source,
you're talking about
nanometer-sized waves
versus electrons, at the
typical electron acceleration
voltages that are
used, are in the tens
of picometer wavelength.
And so that's the main reason.
You can magnify
these images further.
But you're not going to
get any higher resolution
versus an electron microscope.
But you don't often
hear about tens
of picometer resolution
images by EM.
So I guess maybe I'll
flip back to this slide.
So this is differences
in the source.
But you could
actually theoretically
go 100 times or more beyond
these magnifications by EM.
Why do you not typically
hear about that?
What else could be
limiting resolution
as you go down through
this path here?
A number of you wear glasses.
Do they perfectly
correct your vision?
They don't for me.
Yeah, so same thing
with these lenses.
No lens is perfect, and you've
got different aberrations.
So the way light or
electrons that are coming in
are bent is never perfect.
They're not going to achieve--
and there's correctors that you
can use to compensate for this.
Also the wavelength
of the light,
having it perfectly tuned
to a particular energy
of either photons
or electrons, there
is going to be
some distribution.
And so you're going
to have some that
are a little more
redshifted or blueshifted,
higher energy or lower energy.
And those are going to also not
come to complete focus there.
And so this is for the
lenses in the source, why
you would typically be limited
to about an angstrom resolution
unless you buy some fancy
correctors for your microscope
to correct for spherical
aberration or energy filters
to correct for
chromatic aberration.
So what kinds of
things in the cell
could we look at by
electron microscopy?
Maybe you guys have
seen images in papers,
probably in your
textbooks, EM images of--
what?
Help me out.
You see in sections about,
say, muscle where there's
a section of some muscle
fiber where you can actually
see some of the proteins that
are involved, the filaments.
So you've seen things like that.
Tissue sections.
You could look at
tissue sections by EM.
You could look at
individual cells.
Could you look at an elephant
by electron microscopy?
Have you ever seen that?
No.
So why would you not
image an elephant
in an electron microscope?
AUDIENCE: Simply because
they're too [INAUDIBLE]..
EDWARD BRIGNOLE: OK, yeah.
Exactly.
You'd have a really hard
time preparing that elephant
even if you had a microscope
that was big enough.
But you could, say, take
an x-ray of an elephant.
Right?
But what is it about
electrons, maybe,
that you wouldn't have
to deal with with x-rays?
AUDIENCE: Killing the elephant?
EDWARD BRIGNOLE: I mean--
[LAUGHTER] Right.
So why would the elephant
have to be dead to image it
in an electron microscope?
AUDIENCE: When
you're shooting it
with electrons, even just for
the cell, it'll kill the cell.
[INAUDIBLE] you do it to a--
Oh, wait.
Don't you have to [INAUDIBLE]?
EDWARD BRIGNOLE: Yeah.
So in some cases, you
might negatively stain.
Typically, you would stain a
sample in some way or another.
But what I was getting
at is the vacuum.
So the microscope is
under high vacuum.
So electrons have
mass, and they're
going to interact
strongly with the matter
that they're going through.
You actually couldn't get an
electron through an elephant.
You could get x-rays
through an elephant though.
So thickness is one issue.
You'd have to cut really thin
sections of your elephant,
so about 200 nanometers thick.
You can go thicker than
that, but then there
are some other issues with
resolution that occur.
So this is about the high
end of what you would want
to be for a good EM specimen.
And then if we're looking at,
say, individual macromolecules,
the size of those
macromolecules,
to be able to look at the
image and pick them out,
would have to be-- if there
are single particles floating
around like a virus
particle or something,
you can usually do that.
Because they're much bigger
than 100 kilodaltons.
Probably in your textbook,
you've seen EM images.
Or even in newspapers, you
pick up the New York Times,
and there's an article on
Zika virus or something,
and there's an EM image of it.
So those are much bigger
than 100 kilodaltons.
But this is about the lower
end for individual particles.
So I thought I'd
just throw this up
so you could look at
the different bits
and pieces of an ant
in a light microscope.
An electron microscope
largely overlaps
with the high end of the
light microscope, where
you could look at cells
or sections of cells
if the cell is a
micron or more thick.
Bacteria, bacteria-like viruses,
bacteriophage in this case.
Electron microscopy has
resolution down to this range.
But in order to visualize
things like this,
you'd have to be able to
pick them out of your image.
So you could assemble 10
kilodalton particles into,
say if it's actin or something,
into a large polymer.
Then you can pick
out the polymer,
and in the process
of reconstructing it,
identify, say, 10
kilodalton-sized subunits.
But to look through an image and
pick out a 10 kilodalton piece,
that would be impossible.
And then x-ray
crystallography and NMR
are typically imaging
structures of about this size
down to resolutions
in the angstrom range.
All right.
So we've sort of gone
through the different kinds
of things you can see.
And then the one last
thing I wanted to say
is, there's lots of different
kinds of cellular structures
you can look at in an
electron microscope.
And I hinted at, say,
if you can assemble
smaller pieces into
larger structures,
then you can image them.
So if you can coax, say, a
G protein-coupled receptor
that you're interested in
into a two-dimensional array,
then you could visualize these
small very interesting proteins
as part of this 2D
crystalline array.
Or in the case of actin,
polymerized into a filament.
And so there are different
ways to reconstruct molecules
that arrange themselves into
arrays by, say, electron
diffraction or in filaments
because each unit is related
to the unit that's before
and after it in the filament.
But the brand of
electron microscopy
I'm largely going to
be talking about today
is what we call
single particle EM,
where you've got these
freestanding proteins or virus
particles in solution.
And you're going to try to pick
individual ones out and figure
out what their 3D structure is.
And each molecule is independent
and not necessarily related
to the other ones
that are around it.
All right.
So we talked a little bit
about why an elephant wouldn't
survive in the microscope.
And that had to do with
specimen preparation.
So electrons, because
they scatter strongly off
of the matter that
it's traveling through,
if you have gas in your column.
Then the electrons are going to
scatter off of that before they
get to your protein.
So the really good microscopes
have really high vacuums,
and the specimen has
to be preserved somehow
to survive that.
So you probably wouldn't want to
just put your protein in buffer
and stick it into the
microscope because basically,
all the buffer would
evaporate, and you'd just
have a dried out protein.
So you need some way
to either, if you're
going to dehydrate
it, to stain it,
which is what we're going
to talk about in this paper.
Or you can cryogenically
preserve it and then
keep it at liquid
nitrogen temperatures
while you're imaging it.
And then I think
one of you guys also
mentioned radiation damage, that
the elephant wouldn't survive
being bombarded by radiation.
And so at the specimen level,
these radiation damage doses
are equivalent to an atomic bomb
going off if you scale it up.
And so basically, this is what
you're doing to your specimen
while you're imaging it.
And so in your case, you're
looking at gold nanoparticles,
you had said.
And so you can hit a hefty
dose on a gold nanoparticle.
But on biological
specimen, you'd
be breaking carbon-carbon
bonds, and your protein
is rupturing as
you're imaging it.
So typically in
electron microscopy,
we'll only expose
the area that we're
going to-- and for
biological specimens,
just as we'll focus adjacent
where we're actually
going to expose and
then expose the area.
So the first time that area
sees a decent dose of electrons
is when you're actually
acquiring an image of it.
And I guess one last
thing I could point out
about this 30 electrons
per angstrom squared
is, even by 30 electrons
per angstrom squared dose
on your specimen, a large amount
of the high resolution signal
is already lost.
So the first five electrons
per angstrom squared
has most of the high
resolution information.
But it doesn't have
enough information in it
to actually visualize
your whole structure.
So you want to
give it enough dose
that you can see the whole
thing but not so much dose
that you've destroyed
the whole thing.
And I guess one other
thing that limits
what we can see
in the microscope
is, if you want to image
something at atomic resolution
and the stage that's
holding the specimen
is moving by a few
angstroms at the same time,
then it's going to be blurry.
The features you're looking
for are blurred out.
I mentioned at the beginning
that this paper was in 2009
that we're going to talk about.
So in the last two
to three years,
there's some new detectors
that have come online.
And these are
revolutionizing the field.
So if you look at structures
by single particle EM that
are at less than five
angstroms resolution,
it went from, around
the time of this paper,
there were one or two to now
there are tens to even 100
a year in the
last-- like in 2015.
So there's a whole
mess of developments
that are responsible
for this, but the one
that's the most
important of these
is these direct
electron detectors.
So did you guys have
a chance to look at,
say, the figures of the
paper we're going to talk
about today?
Did you have a chance to look
through the methods at all?
Did anybody notice how
the images were acquired?
So this predates direct
electron detectors.
So what sort of
detectors were used?
Anybody notice?
Going once.
OK, so some of the images
were collected on CCD cameras.
And some were collected on film.
So can you think of an advantage
of one versus the other?
Anybody here into photography?
Friends who are
into photography?
Does anybody still shoot
their images on film?
Maybe some purists of
image quality, something?
Anyway, but why do most people
use digital cameras these days?
You don't have to go and
develop your film, for one.
Right?
You probably don't even know
about having to go and develop,
though.
So that's a distinct
disadvantage,
is the throughput.
You can snap 100
pictures on your camera.
You don't have to wait a couple
of days to see the results.
So the same thing would
be an electron microscope.
So if you're imaging
your specimen on film
and then you have to take
the film cassette out and go
into the darkroom
and develop your film
and then realize that
there was some parameter
wrong or somebody didn't
change the developer recently,
the whole batch would be gone.
So throughput with film is low,
but the signal-to-noise ratio
and the point spread function
of detecting the electrons where
they strike the film is good.
So the image quality
is better with film.
And also, the area that you
would expose is bigger on film
too.
So typical CCD cameras
are, say, 4K by 4K pixels.
Film would be like 10K by 6K.
So you'd have a much
bigger area, which
means more particles per image.
So that would be the
advantage of film.
CCD cameras, I mentioned, are
a little worse performing.
So what they have is
a scintillator layer.
So it's like a phosphor layer.
So the electrons would
come down, and some of them
hit the scintillator
and bounce off.
Some of them will hit
the scintillator layer
and go through.
Some of them will hit
the scintillator layer
and zig around for a little bit
and then give off some photons.
So you can see what
the disadvantages are
if you're limited to,
say, a 30 electrons
per angstrom squared dose.
If a decent number of your
electrons are being lost
or not detected
accurately-- in this case,
you have a point
spread about the area
where that electron
struck, where
you're actually picking it up.
So this is going
to cause a blurring
of your high resolution signal.
And then this is just to convert
the electrons to photons.
Then you would
typically have some sort
of fiber optic coupling, where
you would also lose some signal
and also has a point spread.
And then this is connected
to the actual detector,
like what's in your
phone, basically.
So this is how
some of the images
were collected in the paper.
Basically, the nice thing
about the CCD camera
is its high throughput.
You can get lots of
images really fast.
But for the data that was
used to generate the 3D
reconstructions, that
was collected on film.
And then I guess I'll
just say one more
word about then, these
direct electron detectors.
Basically, they cut out
all this extra business.
You basically detect
the electrons directly.
So they come in, and actually,
each pixel has the ability--
on some of these, the newest
top-of-the-line detectors,
can actually figure out
which quadrant in the pixel
the electron struck and can
actually count each electron
event on each pixel
as it's happening.
So you have some
electronic noise in here,
so there's little bits of noise.
And on a typical CCD
camera, you would
integrate this whole signal
over time to come up with--
this is down here.
So you'd integrate the charge
that's accumulated over time.
But in these counting
detectors, you
could say, here's my threshold
for an electron event.
And you can filter
out all this noise.
So you can say an
electron struck here,
an electron struck over here,
an electron struck over here.
And so you've got
better signal-to-noise,
much tighter point spread than
you would have in a CCD camera.
And this is what's
allowing, say, in the last--
there was a really nice
structure in Science
a few weeks ago of p97, which
is a AAA-ATPase with the end
domain.
So this sort of ties
back in, I think,
to maybe some of
the proteasome stuff
that you were doing before.
P97's not a protein degradation
machine, but it's a AAA-ATPase.
And that was at 2.3
angstroms resolution.
And basically, what's
making this possible
is these developments.
AUDIENCE: Can you explain what
the fiber optic [INAUDIBLE]??
EDWARD BRIGNOLE: Sorry, I
didn't label anything up here.
So this is your phosphor layer.
It's like a scintillator.
Phosphor scintillator.
And then down here,
you've got your detector.
And then the fiber optics is
basically coupling the photons
that you see here,
channeling them down
to pixels in the detector.
Some detectors just don't
have the fiber optics.
They'll have a lens
of some sort here.
All right.
So any other questions
about EM before we will dive
into fatty acid biosynthesis?
OK.
So if I show up this cartoon
with lots of different two-
or three-letter colored short
versions for these enzymes,
do these names, I guess they
look familiar to you now
probably.
OK.
So this is the scheme for the
eukaryotic cytosolic fatty acid
synthesis.
There's some differences
in the bacterial system
and the yeast system is a
little bit different also.
But basically, to sort of--
I don't know-- to
help me remember
what all these enzymes
do, I like to group
them into the enzymes that
are responsible for chain
elongation and the enzymes
that are responsible for chain
processing.
So basically, the malonyl
acetyl transferase-- so
in our fatty acid synthesis, we
have this bifunctional enzyme
that can transfer both
malonate from malonyl-CoA
onto the carrier protein
or acetate onto the carrier
protein.
In different systems,
so in bacteria,
they've got a
malonyltransferase,
and then they have a
specialized ketoacyl synthase
that picks up the starter unit.
So there's some
differences like that.
But basically, these
are the enzymes
that are responsible
for collecting
the starter unit and
the elongating unit
and joining them together.
And then you've got
these three enzymes here,
the ketoacyl reductase,
the dehydratase
and the enoyl reductase that
are responsible for processing
this beta carbon.
So you've got the
hydroxyl, the alkene,
and then the saturated chain.
And then it goes around again.
All right.
So I mentioned that
the different organisms
have different systems.
So in our mitochondria and in
plants, chloroplasts and most
bacteria have a
system like this,
where the individual enzymes
are the dissociated players.
In fungi, some of
these enzymes are
joined into one of two
different polypeptides.
And some of the names here
might look unfamiliar.
So like this malonyl
palmitoyltransferase.
So in this case, it's
got an acetyltransferase
to select the starter unit
and a malonyltransferase
to select the elongating unit.
And then the
palmitoyltransferase,
which transfers the
product back onto CoA.
And this is a
bifunctional in this case.
And then in our cytosol, we've
got this giant monster enzyme
that's got all of the
catalytic domains fused
into one humongous polypeptide.
This is what attracted
me to this project
in the first place,
just how bizarre it
is to have all of these
enzymes all tied together.
And then we had this one
section of the protein.
It has homology to
methyltransferases,
and we called it the
structural domain in the paper.
So there is a bonus question
in the handout, which is, where
did this domain come from?
Why do we have
this non-functional
methyltransferase domain
in our fatty acid synthase?
So think about it.
If we have time, we'll
come back to it at the end.
Then the other cool
thing about this enzyme
is it has to dimerize
to be active.
And so you end up with a 550
kilodalton monster protein.
So I mentioned that the enzyme's
responsible for elongation
and for processing.
And the cool thing
is when you look
at the sequence of
the protein, you've
got the elongation enzymes
clustered at the N-terminus,
processing enzymes clustered
together in the middle,
the carrier protein's
way out here at the end,
and the thioesterase is there.
So there was some
decades of controversy
about how the acyl carrier
protein, which is way out here,
would be interacting
with the enzymes, which
are way over here at this end.
And so a model was proposed
where the enzymes sort of
come together in a
head-to-tail fashion.
So you would have one going
this way and the other one
going the other way.
But then, that
didn't jive with some
of the biochemical
results, which
said that this acyl carrier
protein could interact
with the enzymes
on its own chain.
And so there was
this controversy
in the field, which was
resolved in part by this crystal
structure.
So now we could see how
the two subunits associate
with each other.
So one of the chains is
just colored in white.
The other one's got the
catalytic domains all colored
in.
And so you can see
the cool thing here
is the elongation enzymes are
all clustered together down
here like in the legs.
And up here, in
the torso and arms,
you've got the
processing enzymes.
And the other cool thing
about this structure
is if we cartoon in--
we know the acyl
carrier protein has
to be tethered to the C-terminus
of the ketoacyl reductase
by a 10 amino acid linker.
So that puts the acyl
carrier protein right here,
and it would be
completely surrounded
by all of the catalytic domains
that it would need to contact.
So that's kind of cool.
Oh, yeah and then
the thioesterase
has a 25 residue linker.
And so it would be
somewhere around here.
And so basically,
all of these enzymes
are just sitting
there in a chamber,
and the acyl
carrier protein just
has to bounce around to
the different things.
So if I make a cartoon version
of the acyl carrier protein
with its phosphopantetheine
arm docked
into each of the
catalytic sites,
you can see where the acyl
carrier protein would have
to go on this reaction chamber.
And then the same
thing would have
to happen on the other side.
So now I've got a
question for you.
What happens if we make
a mutant heterodimer.
So this is actually an
experiment that was done,
but if we make a mutant
heterodimer where we knock out
the ACP on this
subunit but leave
this other subunit intact.
So if the wild type
has 100% activity,
how much activity
would this mutant have?
Any guesses?
What would you think?
It's firing on one
of its two cylinders.
AUDIENCE: 50%.
EDWARD BRIGNOLE: 50%, exactly.
So that's all good.
That makes sense.
What if we do another
experiment where
we knock out the elongation
enzymes in the other reaction
chamber?
Now what do you think?
AUDIENCE: Expect it
wouldn't be active.
EDWARD BRIGNOLE: You'd expect
it wouldn't be active at all.
But the experimental results
show that it had about 25%
activity.
So the only way
that could happen
is if this acyl carrier protein
can elongate with the enzymes
from the opposite chain.
Right?
So that looks like
a pretty long reach,
but let's figure out
how far that would be.
So a 10 residue linker to
the acyl carrier protein
would be about 35 angstroms.
The acyl carrier protein
itself is about 23.
Then you have the
phosphopantetheine arm,
which would be these
black things coming off
of our acyl carrier protein.
So if we draw that to scale
from the C-terminus of the keto
reductase to the end
of the red sphere,
it would be about 60 angstroms.
So if we draw how
big that would be,
that's this gray
sphere right here.
So this is how far the acyl
carrier protein can reach,
and you can see these
are clearly out of range.
And actually, even
the elongation enzymes
in its own side are also
sort of at the limit
of what the acyl carrier
protein can reach to.
So it's hard to imagine
what would happen,
but you would need to have some
sort of conformational change
to make these things happen.
And I'll point out one
other difficulty, which
is the access to
the enoyl reductase
and the dehydratase are
sandwiched in the space
between them there.
And so you'd need to have
some other separation
of these domains, possibly,
to get the acyl carrier
protein in there.
So we wanted to look at this EM.
Do you know why that would
seem like a good idea
based on what we talked
about with EM so far?
Does fatty acid
synthase seem like it
would be a good target for EM?
I mean, there was already
a crystal structure of it.
So should we have tried
crystallography, say,
to answer questions about
conformational changes?
AUDIENCE: You might not
be able to crystallize it
in the conformation you wanted?
EDWARD BRIGNOLE:
Yeah, as it was,
that was difficult
molecule to crystallize.
There were crystals of
it from back in the maybe
'70s, '80s, but it wasn't
until mid-2000s that they had
actually gotten--
they solved it initially at, I
think, six or seven angstroms.
And then this structure
was, I think, also not
the highest resolution,
somewhere in the three to four
range.
So yeah, you would have to find
ways to trap the conformations
that you want, lock it
in, and cross your fingers
to get crystals.
Why look at it by
electron microscopy?
Is it big enough?
It's 550 kilodaltons that you
can see individual molecules.
Possibly we could even see
them in different states,
and we might even be able to
perturb those states if we
threw in some substrates.
Then we had a whole
panel of mutants
that our collaborator had meant.
The experiments that I had
described about knocking out
the ACP in one chain
versus the elongation
enzymes in the other, there
was a whole battery of mutants
that we had available to us.
All right.
So to do the
electron microscopy,
we need to put our protein
on something that we
can stick into the microscope.
And typically,
that's a metal mesh
with a cart that's supporting
a thin carbon film.
And then we stick the protein
onto the thin carbon film.
So this is about
three millimeters
across, this little grid.
You can put about five
microliters on it.
And then to get a good
dispersion of particles
on the grid, you need about
15 nanograms per microliter.
If you go too much above that,
you get protein everywhere,
and you can't pick one
particle from another.
And if you go much
below that, then you
have to collect lots and lots of
images to get a few particles.
So this is sort of the
sweet spot, in the 15 to 20
nanogram per microliter range.
This is one limitation for EM,
the concentration dependence.
So if you have a molecule that
falls apart, it has a high Kd
and it falls apart at
these concentrations,
that could be difficult to
work with, for instance.
All right.
So there's a couple of different
ways to prepare specimens.
I think we already talked
about staining the specimens
or cryogenically
preserving them.
So the way that would look
like for a stain experiment is,
you've got your
thin carbon film,
you put your drop with your
protein molecules on it,
you blot off the
excess solution,
replace it with a heavy
metal salt solution--
typically a uranium salt--
and then you let it air dry.
And the specimen is then
embedded in this heavy metal.
And that's why we
call it negative
stain because what
we're imaging is,
you've got your
protein molecule,
and it's embedded in
this dense stain layer.
What's scattering the
electrons most strongly
is the material
around your specimen.
And so you're imaging where
your protein isn't, basically.
Or the stain excluded area
is what you're imaging.
So what you have, in this
case, is a dark background,
and your particles look light.
The other way to
prepare specimens
is to cryogenically
preserve them.
So the first part
starts out the same.
You would put your
proteins on the grid.
And sometimes, you
could have a grid that's
got little perforations
in the carbon,
so you actually would have
your protein suspended
in these perforations
when you blot it.
And then you plunge
it into liquid ethane
that's cooled to just about to
liquid nitrogen temperatures.
Here is a picture of the dewar
with the liquid nitrogen.
And then there's a
little cup in the middle
with the liquid ethane.
So why not just
plunge it directly
into the liquid nitrogen?
Does anybody know?
Does anybody do
rapid freeze quench
for any of your experiments
or anything like that?
So have you ever messed
around with liquid nitrogen
that any splashed onto you?
Did you get burnt?
No.
So the reason is liquid nitrogen
has a lower heat capacity,
so if it touches you,
basically, there's
a layer of gas between
the liquid and your hand
or whatever it spilled on.
But with liquid ethane,
the heat transfer--
basically, this grid
will go in there,
and it'll freeze so fast that
ice doesn't have a chance
to form crystalline ice.
So basically, everything is,
on a microsecond scale, frozen.
So now you've got
this amorphous ice
with your protein
embedded in it.
Can you think of some
advantages or disadvantages?
If this gives you
something preserved
and it's happy in
its buffer, why
wouldn't you always use that?
Why would you use stain?
Can you think of
some advantages?
Maybe the obvious
thing, why don't I
ask you for some disadvantages.
Why would you not
want to use stain?
AUDIENCE: The stain used could
possibly disrupt your specimen.
EDWARD BRIGNOLE: Yeah,
and that does happen.
Sometimes people have to play
around with different stains.
The uranium salt stains, the
uranyl acetate, for instance,
is a low pH.
And if you try to pH
it, it crashes out.
So if your protein isn't
happy in that low pH stain,
that could be a problem.
Also the stain layer is
dried, and so your specimen
is dehydrated and
dried out here.
And typically, that--
I drew my specimen like this.
But when it dries out, it
flattens out like this.
So that's a disadvantage.
What about contrast?
So if this is my amorphous ice,
my water layer with my protein,
do you know what the difference
in the density of protein
versus an aqueous buffer is?
They're pretty closely
matched, actually.
Protein's like 1.2 or
something like that.
So basically, you have
pretty weak contrast
in a frozen hydrated
specimen because here, you're
looking at the
difference in density
of your protein versus
the buffer around it
whereas here, you're
imaging the difference
between the density of, say,
your protein and uranium.
So you get a lot
better signal here.
But you've got some
specimen distortions.
And so we basically
just went through these.
There's one other
advantage I'll mention
to sticking your protein onto
a carbon surface as opposed
to freezing your
protein in a hole.
And that is that
most proteins tend
to have a preferred orientation.
Many do, and in the case
of fatty acid synthase,
it's sort of this.
It looks like a headless person
that's got arms and legs.
It'll very rarely hit the
grid and stand straight up.
It usually falls
back onto its back.
And so in some
circumstances, that
could be an advantage,
and other circumstances
you would actually want to have
many different views to make
a 3D structure.
So I listed that both as an
advantage and a disadvantage,
the preferred orientation.
Depends.
You could use it
to your advantage.
In other cases it would
be a disadvantage.
All right.
So you said you used
an FEI microscope.
It might have looked
like this one.
AUDIENCE: Yeah.
[INTERPOSING VOICES]
EDWARD BRIGNOLE: OK.
Yeah, this is an F20.
This is the microscope that
all the images in the paper
were collected on.
So there is a specimen
port on the side.
The electron source
is up here at the top.
The column with the lenses
and apertures in it is here.
There's a phosphorus
screen here that you
can look at through
the binoculars
to see what's going on.
There's the knobs that you can
use to control the microscope,
focus, move the stage around.
And then the camera is
right here below the column,
right where you can
knock your knees into it
when you look in here.
Yeah, I mean, you put a half
a million dollar detector
on there.
And you can knock
your knees into it.
Actually, the newer
microscopes these days
actually look more like
giant refrigerators.
And basically, all
of this is housed
in this environmental chamber,
and you operate the microscope
from the room next door.
So we put the grid
in the microscope.
At low mag, you can
get an image like this.
Little higher, just zooming in
on one of these squares here,
you can get an image like this.
This is negative stain
specimen so there's
little chunks of stain around.
If you ever happened to do some
negative stain experiments,
I usually like to
look for areas that
have this smudgy appearance.
It looks like little
pencil lead shavings
that somebody wiped
their hand across.
That's usually a good sign.
And then if you zoom
in another tenfold,
you can get an image like this.
And if you look
carefully at it, there's
all the individual 550
kilodalton fatty acid synthase
molecules.
So how do you get any
information out of that?
Any ideas?
You can pick out the
individual molecules here.
If you squint at
it, can you maybe
make out the legs and arms,
the processing portion,
and the elongation portion?
Maybe?
OK, it's tough.
Does anybody here
do spectroscopy?
AUDIENCE: No.
EDWARD BRIGNOLE: No.
So based on what you know,
electron microscope images
can have potentially high
resolution information in them.
But you're limited in dose
you can apply to the specimen
before radiation damage
becomes a problem.
So what we have is a
signal-to-noise problem here.
You've got high resolution
signal buried in lots of noise.
It's like having a low
exposure image of something.
What could you do to
boost your signal?
If you're going to take
a picture at night,
what would you do?
You need a really,
really long exposure.
Right?
But you can't take a really,
really long exposure.
So what would be a
different way to do it?
Say like, in the
case of spectroscopy,
if you had a sample
that's damaged every time
you stuck the
cuvette in the area,
but you could say, take a
cuvette and take a spectra,
take another one, take a
spectra, take another one,
take a spectra, and you can
average lots of them together,
that would boost
your signal-to-noise.
So that's what we
have to do here.
We have to extract all these
particles out and find a way
to average them together.
So if we put soccer
players on a EM grid--
if any of you are soccer fans--
and you collect
an image of them.
You get this noisy
image like this.
In the computer, you can go
through and pick the particles
out.
And the computer can do its
best to line them up for you.
And if it does a
good job, and you
get lots and lots of particles,
when you average them together,
you get your high
resolution signal out.
So that's all fine and
good, but not every protein
is going to land in exactly
the same orientation.
And in the case
of soccer players,
you probably would have a hard
time finding soccer players
that are in exactly
the same conformation
every time you image them.
So in this case, a
soccer player might
prefer to kick with his
right foot or left foot
or might have his right
arm or left arm up or down.
These are just a couple
of different conformations
maybe that you would observe.
So now what do you do?
You've got these averaged
together, and you're like,
I got an insect.
Does anybody here-- have
you looked at, say--
you could do this
by spectroscopy.
But it sounds like nobody
here does spectroscopy.
So you've got different
sorts of things
that you want to
categorize, basically.
So say, sequence
alignments, that
would be analogous to
this, where you've got
sequences that you've lined up.
Here we've got images
that we've lined up.
And then what would you do?
You'd look through columns
of residues or the computer
would do this for you and say,
this cluster of sequences all
have these particular residues.
So I'm going to put
them into one bin.
And these have a
different sequence,
and I'm going to put those
into a different bin.
The computer can do the same
thing in this cage, basically.
It'll look at these images
and say, some of them
have a density here, and some
of them have a density there
and split them up based on
differences in the intensities
of these pixels.
If this is a dataset of 100
images, then you split it.
Now you've got 50 and 50.
You might have 25, 25, 25,
25 if everything's evenly
distributed.
And the one thing you'll
notice as you split things down
further, you're averaging fewer
and fewer particles together.
And so your signal-to-noise
is getting worse and worse.
So you can split these down.
And the way I typically do
this is a little bit empirical,
but I'll split it and
then split it some more
and split it some more and
look till I get to a point
where I'm not
seeing anything new.
Because if you split
this image more,
it's basically going to be
split on the basis of noise
because there's no other
conformational change.
The same thing would
go for orientation.
If you put this
on the grid and it
landed in three
different orientations,
you would want to
separate things
out using the same strategy.
All right, so this gets
us to the averages,
like the averages that you
see in the fatty acid synthase
paper.
There are also 3D
structures in the paper.
So how do you go
from information
like this to a 3D structure?
So I mentioned one
way is if you've
got lots of different
orientations of the molecule
on the grid and you've got
each one of these averages
is a different view,
you can use the computer
to try to put those
different views together
to come up with a 3D structure.
And there's lots of
ways to get that wrong.
In this case, we've got
a preferred orientation
where they're all
lying on their backs.
We don't have lots
of different views.
So what would you do instead?
Yeah?
AUDIENCE: Get it from the sides?
EDWARD BRIGNOLE: Yeah, exactly.
So that's the thing to do.
So now you've got this
stereo view of your molecule
where you've got a tilted
view and an untilted view.
An extreme example
of this would be
if every particle-- let's say
if you're looking at cells,
no two cells are the same.
You couldn't do these
averaging methods,
but to get a 3D reconstruction
of a cell, what you would have
to do is take the stage
and tilt it by a degree,
tilt it by a degree,
tilt it by a degree,
go up as far as you can one
way, and then do it again
the other way.
So you'd have up to maybe
plus or minus 70 degrees.
And that would be equivalent to
the way a CAT scan or something
might be done, where you've
got images of your broken leg
or something like that
from all the way around.
And then you can have the
3D reconstruction of it.
Right.
So we've got these two
images of our specimen.
They're related to each other
by some tilt that you know.
If you take out these
particles from this image
and you line them
up, that tells you
what view you've
got of them in this.
So take, for instance,
this molecule here.
If you have to rotate
this 90 degrees clockwise,
that tells you
you're looking at him
in the tilted view with
his feet up in the air.
And this one here had to go
90 degrees counterclockwise.
That means that
you're looking down
on him in this tilted
view with his head up.
And so you can take the
alignment information
from this image and apply
that as a projection
parameter for these images.
And so you could take now these
tilted views of these soccer
players, and you know
which view they are.
And you can come up with the
3D reconstruction that way.
So this is actually
a fairly old method.
I think it's still widely
used and very elegant
because it's basically just
two images of the same thing.
And then you can
get a reconstruction
that's pretty easy to get out.
There is one disadvantage
to this approach, one
major disadvantage, which
is that you can only
tilt the stage so far.
So if you could tilt the
stage up to 90 degrees,
then you would have views
exactly all the way around.
And you could have
a reconstruction
that's fully complete.
In this case, you can
only tilt to 70 degrees,
and so you've got a
missing cone of information
in the reconstruction.
And so basically
what that means is
you've got better resolution
in x and y than you do in z.
Yeah, sure?
AUDIENCE: Is there some graphene
packet thing that came out
of the [INAUDIBLE] lab where
it's this packet filled with
solution that you
shoot your EM at the--
EDWARD BRIGNOLE: Yeah, to
keep your protein hydrated,
basically.
So you encapsulate
it in some sort
of graphene tube or something.
AUDIENCE: [INAUDIBLE]
exactly [INAUDIBLE]
EDWARD BRIGNOLE:
I vaguely remember
seeing something like that.
I think there are groups
working on things like that,
but it's not widely
adopted or used yet.
But yeah, there are some
pretty exciting things
like that that might allow
you to directly image
your molecule while it's
tumbling in solution, isolated
from the vacuum
on the microscope.
AUDIENCE: But then there's
some limit with what
your computer can reconstruct.
I mean, it's just
infinitely many
tumbling orientations
or something.
EDWARD BRIGNOLE: Yeah, it's
a tough experiment to do.
The other issue is
compressing all your dose
into a pretty short
amount of time
so that you basically obliterate
the molecule in this field
of view but you
capture the image of it
faster than it's tumbling,
say, or something like that.
So I don't know.
Maybe it depends on
its tumbling rate.
Yeah, something like that.
But yeah, I think it's
an exciting time for EM
right now because now
there's new detectors.
There's actually some
other examples of advances
that I put on that
slide that allow
us to look at smaller things,
potentially specimens that
are still hydrated.
Yeah.
I don't know if my email
address is on this,
but if you come
across that paper
or see anything like that,
feel free to bounce it to me.
All right.
So through the
methods that I just
described to you, basically from
the fatty acid synthase image
that we looked at a moment ago,
we can sort out some images.
And if you look
at this image, it
looks a lot like that crystal
structure I showed you earlier.
There's the legs
you can clearly see
in the average and
the processing enzymes
in the upper proportion.
Then we could sort
out a whole bunch
of other different classes.
And these puzzled us at first.
They're kind of fun to look
at because we thought maybe
it's winking at you.
It's got one eye
open and one eye
closed or like the other one.
And we described these
as different views.
This looked like it had a
pirate's hat on or something.
But one of the other things
that puzzled us at first too is,
this lower portion
of the structure
here, it looks like
maybe we were getting
some sort of proteolysis
and these malonyl acetyl
transferases at the
legs, we thought maybe
they were getting cut off.
So we were relieved
when we generated the 3D
reconstructions then,
that these actually
weren't getting cleaved off.
They're just rotated
90 degrees on the grid
and coming out towards us.
I'll say a quick
word now about--
have you read any
crystallography papers yet
for class when they
talk about resolution
of the structure,
what kinds of things
you can see in the structures?
So in crystallography, you
have a defined resolution limit
based on the highest angle of
scattering data you collect.
So it's defined
in the experiment.
In EM, we don't have that.
We just have images.
So the way we calculate
resolution in EM
is we would take our dataset--
so the data that went
into this reconstruction
here if there is 1,000
particles-- we'd split it
into two subdatasets,
one with randomly
selected 500 particles
and the other
with another randomly
selected 500.
And we'd generate a
reconstruction from both,
from each of those.
And we'd compare those,
the reconstruction
of this half of the data
to the reconstruction
from this half of the
data and see how similar
they are to each other.
And that's how we would
figure out resolution by EM.
So there's some
problems with that.
Can anybody think of one
way this would be biased
or any way that this would
be biased if you just
take your data, split
it into two halves,
reconstruct it, compare the two?
For one, it's sort of like
if you have one person
do the experiment
and they do it again,
but nobody else can do it.
There is a bias in--
you're taking the
exact same approach
to initialize both
of these experiments.
They're both going to converge
to the same local minima.
So you could be
precisely wrong and have
a false high resolution.
So typically, what
you'll see in EM
papers is a curve like
this, where you basically
are comparing the two half
reconstructions to each other,
one from first half
of the dataset,
the other from the other
half of the dataset.
You compare them, and
then you look at, say,
at low resolution,
how similar are they.
Add a little bit
higher resolution,
how similar are they?
If you go to, in this case,
20 angstrom resolution,
how similar are they?
And in this case,
they've got a correlation
of about 10% or 15%.
So in the case of
this paper, the way
we reported the
resolution was when
the correlation between
the two halves of the data
fell to about 50%.
So we reported a resolution
of about 30 angstroms
for these structures,
but like I said,
that doesn't necessarily
mean they're right.
And in our case, the
advantage we have
was that there was
a crystal structure.
So if we just dropped the
crystal structure right
into the EM reconstruction, that
looks like a pretty good match.
And one thing that we
didn't do for this paper,
but people sometimes
do is, instead
of comparing half of our data
to the other half of our data,
we could have compared our data
versus the crystal structure
and come up with a
similar curve to compare
our data to this
high resolution data
and see where things fall off.
So in these
reconstructions, there's
lots of different conformations.
You can see the lower portion
swinging back and forth,
the upper portion twisting
relative to the lower portion.
And then, you see this
other conformational change.
So we take the
arms off of the end
and look at what's happening
in the middle here.
The enoyl reductase
and dehydratase
are rotating like this
relative to each other.
So one side opens up while
the other side closes.
They sort of cross over
each other like that.
And so when one side
rotates, they sort of rotate,
but then one side tightens
up while the other side
comes loose.
So we wanted to know how
these related to catalysis.
So I guess if you've
looked at the paper--
I'm going to try to speed
up here a little bit--
what we did was we
looked at some mutants
in the presence and
absence of substrates
to look at how this--
we've got all these
different conformations--
how the frequency that we
see different conformations
changes.
And I'll sort of
cut to the chase.
I think in the paper,
there is histograms,
but I think the pie charts
are a little more telling.
But basically, what happens
is if you add substrates,
the conformation that
becomes most prevalent
is the one that's
represented in blue here.
So if I go back, you've
got these, basically,
four different categories
where the lower portion is
perpendicular or
parallel and then
whether the upper portion has
this asymmetric appearance
or not.
And the one thing that
jumps out right away
is that add
substrates and you get
lots of asymmetry
in the upper portion
and the lower
portion in parallel
with the bottom portion.
All right.
So why would that be?
So if we look at one
of these conformations
where the lower portion's
parallel to the upper portion,
the upper portion has this
asymmetric appearance.
What might this reaction
chamber be good at doing?
So these enzymes in the lower
portion, the ketoacyl synthase
and the
malonyltransferase, they've
come up close to where the
acyl carrier protein would be.
And at the same time,
this side is closed off,
so it would have a harder time
doing processing on this side.
So at the same time over
here, this side's opened up.
The acyl carrier
protein can easily
get in here to do
the processing,
but these enzymes
over here are out
of reach of the
elongation enzymes.
So what this means
is one side could
be elongating while the
other side's processing.
And then the structures
are symmetric.
So if you flip it
around, then this side,
once it's done
elongating, could process.
And then this side
could elongate.
So it's kind of cool because
it can sort of balance out
what it's doing from
one side to the next.
And then we have these
confirmations where the lower
portion is perpendicular.
And remember, at
the beginning I had
said that we know
that this acyl carrier
protein can elongate
with the enzymes
in the opposite portion.
So because of the
symmetry in the system
and also the resolution
of the structures,
we can't tell the difference
between whether the lower
portion is flipped 180
degrees relative to the top
or not because it
would look the same.
But the fact that we can
see these go 90 degrees
is suggestive that it could
probably unravel and go
the rest of the way around.
So in the crystal structure,
the way it had them
is, they were coiled like this.
And so it's pretty
easy to imagine
that they would just uncoil.
One other line of
evidence that I think
is telling-- so our
collaborators made
a mutant that has all
of the active sites
and the acyl carrier protein
knocked out of one subunit.
So there is one subunit totally
wild type and the other subunit
that's totally dead.
So the interesting
thing about this mutant
is it has to do the condensation
reaction, the elongation,
in this conformation,
sort of crossed over.
But to pick up its starter
unit or elongating unit,
it has to coil back
around for this.
And we know based on
the rate of this enzyme,
that this probably happens
about 100 times per minute.
There's a functional catalytic
event that happens 100 times
a minute.
So it probably is sampling
these much more rapidly.
Sure.
AUDIENCE: So this
isn't compensating
for when you knock out one half
that's naturally [INAUDIBLE]
EDWARD BRIGNOLE: Yeah,
that's what we think.
It's sort of naturally
sampling both sides.
It's interesting to think
about because let's say
this side picks up acetate and--
well, let me think
about this for a second.
But if one side is
ready to elongate
and the other one's
got a starter unit,
and this side over here
is already loaded with--
so basically, this will
pick up an acetyl group
and transfer it to
the ketoacyl synthase.
And then it comes back,
and then it picks up
an acetylic group again.
So then it would
be stuck because it
would be trying to extend
an acetyl with an acetyl.
But it needs a malonyl.
So what it could
do is flip around,
sample the other side, which
might have a malonyl group,
to continue on on that side
and then come back around.
And it could transfer
the acetyl group on.
So it'd allow maybe
one way that it
doesn't have to
necessarily go backwards,
though the malonyl
acetyl transferase can
function in reverse.
So that's another thing, is it
won't get stuck if everything's
all loaded up with acetate
because the malonyltransferase
will run backwards to
cut the acetates off.
But this would be
one way to maybe not.
It wouldn't have
to necessarily rely
on going backwards
to get unstuck.
It could just twist around.
All right.
So I think we'll just finish up
with a quick movie that shows
these different conformations.
So the bottom parts
picks up a substrate,
elongates it, goes up
here to do the processing.
Meanwhile down here,
it's elongating.
You can see how up here in the
upper portion, the separation
of where the dehydratase
and enoyl reductase is
so the acyl carrier
protein can fit in.
Here we go.
So then there was that bonus
question at the beginning.
I know you guys
probably have to run.
So the bonus question
at the beginning is,
what is that structural domain
that's-- the methyltransferase,
where did that come from.
Any ideas?
You guys have talked a little
bit about polyketide synthases
yet?
A lot of them have
domain architectures
identical to our
fatty acid synthase
with functional
methyltransferases.
So it seems like we probably
picked up our fatty acid
synthase from something
like a lovastatin synthase
or something like that.
So it's interesting
to think about.
And then we didn't need it,
so it's now not functional.
All right.
Cool.
Thanks guys.
