エヴァ・ノガレス（カリフォルニア大学バークレー校）。電子顕微鏡入門 (Eva Nogales (UC Berkeley): Introduction to Electron Microscopy)

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Hi, my name is Eva Nogales, I'm a professor of molecular and cell biology at UC-Berkeley,
a Howard Hughes Medical Institute Investigator and a senior faculty scientist at the Lawrence Berkeley national lab.
And today, I would like to give you an introduction to what is my favorite visualization technique
to see cellular and molecular details in biology.
This is electron microscopy. In my lab we use this method to visualize processes
of cellular self-assembly and molecular machines that are involved in nucleic acid transactions.
And I will be using some of these as examples. I'm going to start by giving you
an introduction to the physics behind how electrons interact with matter,
how the electron microscope is able to generate
contrast in visualizing sample
and then give you examples of biological molecules and cells
and how the images are generated, how they look and
how we go into farther processing to learn more
about structure and function in cell biology.
So, the first thing that I would like to tell you is that electron microscopy comes in two very different flavors.
SEM, or scanning electron microscopy, is a method that uses
focused beams of low-energy electrons to raster along a bulky object
and give you a low resolution rendition of the surface
of the object. So this is an example of such an image.
It's a crab larvae and it looks very pretty because it has added false color,
but there's no color whatsoever in electron microscopy, so that's the first thing that you
have to remember. This is more like the real image
Let me give you another one, this is of dust mites,
these are nasty things that cause allergies certainly they do only.
And I want you to pay attention to the scale bar here,
which is two hundred microns, this is about the size of these organisms.
You could certainly crank up the magnification in this type of microscopy
and get to visualize individual cells.
So this is an image now of a mouse oviduct.
And these kind of tissue has lots of cells that have these cilia that they use to create fluid motion
and allow the sperm and the egg to encounter one another.
Notice that the scale bar now is 2 microns, so we're really seeing cellular details right now.
I would like to concentrate from now on on the other electron microscopy technique,
which is Transmission Electron Microscopy, or TEM.
This uses very different principles and what it gives you is a projection
images at much higher resolution of thin samples that are introduced into the microscope and there's possibility here
to get even to an atomic resolution,
as I will tell you in a second.
So this particular example comes from a section that was taken from the flagella of a sperm,
the one that could have been coming up the oviduct that I showed you before.
So, in this section, what we see is the axoneme,
a structure that goes all the way along the flagella,
it's made up by microtubules, which are organized into this beautiful structure.
Now, microtubules are made by self-assembly of the protein tubulin.
and you can actually purify tubulin, typically from mammalian brain, like cow brain,
and reconstitute the process of microtubule assembly in vitro, in the test tube.
And this is now a TEM image of such individual microtubules.
And this image now contains information at the atomic level.
The scale bar in the image that I showed you before
was not microns, it was nanometers.
And what you see here, the thickness of one of these microtubules is 250 angstroms, or 25 nanometers.
In fact, this methodology, has been used to obtain information about the structure of the tubulin protein itself.
And what I show you here is a density map in blue inside the protein molecule, where these yellow lines represent the polypeptide chain
going along it. And every one of these squares in blue corresponds now to one angstrom.
So the resolution here is much higher, is at the atomic level.
So, I want to give you more examples from microtubules, which are one of my favorite biological samples in a minute.
But before that, I want to go back to very basic principles of how electrons interact with matter.
In the transmission electron microscope, electrons have very high energies,
of the order of hundreds of kiloelectron volts.
That means that they are moving at close to relativistic speed,
They are moving so fast that sometimes they basically go through matter without even noticing.
So, in here, what you can see are electrons going past an atom and some of them just go through and simply don't interact.
They don't see anything. Some of them, and these are very important for generating the image,
are going to go through and bounce off the nucleus of the atom and be bent.
This is a process of elastic scattering, in which electrons don't change energy, don't change speed,
but change direction. And this is what we call the good scattering
and is going to be used to generate contrast in the image, in the TEM.
Unfortunately, there's another process of scattering,
the bad scattering, and these are electrons in your primary beam generated in the microscope
that go through the atom and interact with the electrons in your sample
and in doing so, they lose energy of their own and they pass it to your sample.
These inelastically scattered electrons
are going to only contribute to the noise in your image,
while at the same time, really damaging your sample.
Ok, so, the TEM is going to be able to visualize your sample
by using these elastically scattered electrons to generate contrast in the image.
And the way this is done is in two different manners.
The first type of contrast is called amplitude contrast and is the one that is used to visualize sections of cells.
Like this one, this is a section through the root of a maize plant
and you can see the variety of internal organelles in here.
Amplitude contrast works very much like an X-ray
that you get at the doctor's, where more X-rays are being absorbed by your bones
than by the rest of your soft tissue,
so the bones appear darker in the image.
Actually, what I'm showing you here is the positive of the image.
What the doctor shows you is the negative, which looks like this.
Ok, so in the microscope, in the TEM, electrons can be either absorbed by the sample or
otherwise they can be elastically scattered
and then we can remove the elastically scattered electrons by means of an aperture.
The aperture is placed after the objective lens
and what is does is it allows the unscattered electrons to go through, but it blocks the elastically scattered ones.
And that generates contrast in the image,
basically making regions where lots of scattering happens, because there's more density, appear dark
and regions where there was less scattering appear bright.
This type of contrast is great to visualize sections of cells,
but it falls really short when you're trying to get high resolution information
on proteins and other macromolecular complexes.
So, for that, we need phase contrast. This is the contrast
that is generated in these types of images, now, of purified protein and protein complexes.
In this case, the objective aperture of the microscope is utilized to make the scattered, elastically scattered electrons,
and the unscattered electrons interfere,
generating contrast in that manner.
This is based on the principle that relativistic electrons basically can be seen as waves
and that when they go through matter, the wave front will suffer a phase shift
and this is what will ultimately cause the interference, which will mix with the unscattered wave front.
I'm not going to into any more physics, rather, I will now show you how an electron microscope looks like.
Ok, this is what I would call a middle of the range electron microscope.
The whole story starts up here with the electron gun,
which is where the electrons are produced.
They shoot down the column, which is maintained at very high vacuum
so as to minimize the scattering of electrons by residual air.
At each stage you have electromagnetic lenses that are used to deflect the path of the electrons
Earlier on, there's two condenser lenses and these
control the illumination of the sample, how bright and how large is the area that's being illuminated
and then comes the most important lens in the scope,
which is right in the middle. It's the objective lens, this is the one that
will combine the scattered and non-scattered electrons to give you contrast in the image.
And the other thing that happens right here
is that's where the sample goes in.
In this case, this is a cryo sample that is being maintained at liquid nitrogen temperature
by being in contact with this dewer, with liquid nitrogen.
So, after the objective lens come a number of intermediate lenses
that are utilized to change the magnification from 50 times to something as high as 400,000 times.
The image can then be observed in a phospo screen, directly on a TV
and ultimately recorded for further data processing,
either on photographic film or on a CCD camera.
The one thing that I would like to show you is an electron microscope grid.
It's right there on my finger. This metal grid is coated by a thin layer of carbon
and then the sample goes in there.
And we need extremely little amount of sample.
We use, say for purified protein complexes, concentrations that are on the nanomolar,
sub-micromolar range and we use a very small drop, the size of small tear,
that goes right in there. And then gets blotted to a thin layer
before it's very quickly frozen.
The grid, all of this is done, under liquid nitrogen or nitrogen gas and then in the holder
and then it is introduced in the electron microscope.
But with very, very little sample, we can still get millions of occurrence of the complex
we are interested in and take many, many images and hopefully get the structure we need.
I get often asked what kind of resolution can the TEM reach.
And in fact, microscopes like the one that I showed you is capable of obtaining images
with atomic detail. This is such an example,
this corresponds to a thin, nanocrystal of silica,
where each one of these dots are actually atoms that have been visualized in this image.
In fact, a state of the art electron microscope can reach resolutions
beyond a single angstrom. So, very high resolutions are achievable,
as long as the sample is not radiation sensitive.
So, this sample was able to withstand thousands of electrons going through it in each square angstrom.
in the sample, without damage. Unfortunately, that is not the case for biological material,
which is extremely sensitive to radiation.
It was only a few years ago that people thought that high-resolution information
from biological materials would never be reached
because the sample will vaporize before images were finally collected.
If that had been the case, I would be very sad, would not have a job
and I would be not talking to you today.
But, fortunately, there is more than one way in which we can trick nature
and obtain high resolution information from our biological samples.
So, let me review with you what the problems are that are unique to biological, organic samples.
First of all, all biological material lives in aqueous solution
and by definition they hate the high vacuum in the column of the electron microscope.
The other thing is that the atoms that biological materials are made of, nitrogen, carbon, oxygen,
have basically the same scattering power as the water that is surrounding them.
So, they basically have very low intrinsic contrast.
And ultimately, and most importantly, they are very radiation sensitive.
When inelastic scattering occurs, the sample gets ionized,
generating radicals, that then move around the sample
and break all the bonds and basically make the whole thing explode.
Ok, so, how do we overcome these problems?
There's two solutions. The first one to occur historically was negative staining.
In this case, your sample is embedded in a low concentration of a salt solution
of a very heavy atom, typically uranium.
The sample is embedded in this solution.
The solution is then dried to a thin layer
and introduced into the electron microscope.
Because now there's no water, there's no problem with the vacuum.
The heavy atom, the uranium, generates very high contrast
so we can overcome the second problem
and because now what you're imaging is this cast generated
by the stain, rather than the protein
you also reduce the problem of radiation damage.
The protein may vaporize, but as long as the cast still reproduces its shape,
we are ok. So, the big pluses of this methodology are the high contrast in the image,
and the fact that it's fast and easy.
So, Berkeley undergraduate students can come to my lab and in a few weeks, they're ready and taking beautiful images
using this methodology. Now, there are minuses,
of course. The minus, the big minus, is that artifacts are readily possible.
This is due to the fact that in some cases, the stain cannot penetrate inside the protein
or cases where, as you dry the stain, the protein structure may collapse.
Even if you have very good preservation, in some cases, the resolution is always limited.
It's limited because as you dry the stain, it forms little grains,
and that's the ultimate size of anything that you're going to be able to see,
which is typically about 15 angstroms.
So, the solution, the second optimized solution is to look at unstained, frozen, hydrated samples.
This is what we call cryo-electron microscopy. In this case,
the sample is embedded in active solution where it is happy,
but then is very quickly frozen. It's frozen so fast that the water molecules
don't have time to reorganize into a crystal
into ice, and therefore remains amorphous. We call that vitrified water.
To achieve vitrification, the samples have to be frozen very fast,
typically a million degrees per second
and then kept at very low temperatures, the temperature of liquid nitrogen.
If you do that, this sample can go into the electron microscope without evaporation of the water.
So, we avoid the problem of vacuum altogether.
So, the sample is hydrated, but in a solid state that can withstand the high vacuum.
Now, because there's no stain, these samples do suffer from low contrast,
and we're going to have to overcome that by other means,
I'll tell you about that later.
Radiation sensitivity is limited because now the very low temperatures means that radicals that were generated
through the process of inelastic scattering are not able to move very fast.
So, that radiation damage is minimized.
Not eliminated, but reduced.
So, the pluses of this technique is that the preservation is extremely good
because basically you have preserved even the aqueous layer that surrounds your protein.
Because there's no stain and there's no graininess, high resolution is in principle achievable.
In fact, in some cases, if you have the right experimental set-up,
you can even obtain time resolution.
You can time a certain biological process to be triggered during the process of vitrification and trap intermediates.
Now, minuses. This is a much more technically demanding technique,
so, undergraduates in my lab rarely get to a point where they are feeling very comfortable about doing cryo-EM.
It takes many months, if not years, to really master.
The other problem is the contrast, as I told you.
There are ways of enhancing the contrast in the electron microscope,
but they always tend to come at a price.
So, we mostly we deal with that computationally.
The other problem is that although we have minimized radiation,
still the sample remains sensitive. So, we have to use
low doses, typically 10-20 electrons per angstrom squared.
And that means that the images are going to be very noisy.
So, let me give you an example how the same sample. the same biological material
looks like in negative stain versus cryo-EM.
So, what you see here on the top is an image of a microtubule that is surrounded by rings
that are made of a kinetochore protein.
The kinetochores are the structures by which microtubules interact with chromosomes
in a process called mitosis, by which genetic material is separated.
So, here is that sample in negative stain.
This is uranyl acetate that is used to generate this very high contrast.
Notice that the proteins appear white, while the stain around it appears black.
The image below is exactly the same sample, but now what you're looking at is just the contrast
of the protein on a background of water.
And the image appears a lot cleaner
because in here we can see every individual protein, even those here in the background
that have not self-assembled into these beautiful structures,
while this in here is basically invisible.
On the other hand, what we really present very beautifully in the cryo-EM image is the cylindrical shape of the microtubule
and the circular shape of the ring,
which allows us to obtain ultimately the structure in high detail and with high reliability.
Ok, so, let me now go back to the electron microscope
to show you what is a true state of the art TEM machine.
Alright, now, this beast is what I would call a state of the art transmission electron microscope.
You can see that the column is both longer and wider.
This is because the electrons that are being emitted by the electron gun
have higher energy; as they're moving faster, they need bigger electromagnetic lenses to deflect them.
This microscope has two special, very unique things.
One is the sample goes here, this is what we call the stage,
and this sample is being maintained at liquid helium temperature.
That's very much close to absolute zero, minus 270 degrees centigrade.
So, that reduces radiation damage
and also, the whole mechanical stage makes these samples very, very stable.
And it makes a difference if the sample really doesn't move when you are taking the picture.
Now, the other thing that is very important in this microscope and the reason why it is so tall
that I have to stand on a ladder is that it has an extra piece right here.
This is an in-column energy filter.
It works very much like a prism, but for electrons.
It spreads them out in a rainbow depending on their energy
and that allows us to filter out the inelastically scattered electrons
that are contributing only to the noise in the image.
This is particularly important when the samples that you're looking at
are thick sections of thick cells, where the signal is going to be very low
and the amount of inelastically scattered electrons is very large.
This will allow us to clean up the image and be able to visualize things that otherwise would be invisible.
Ok, this is a good time now to recap
and think of the basic principles of how to generate images of biological materials.
In most cases, we start with a purified sample of your biological material of interest.
This one is the deposited on a substrate in the EM grid that I showed you before,
typically covered with carbon, and it's either embedded in negative stain
or in a thin layer of vitrified water.
Then we pass electrons through it.
Some electrons go right through
and others are elastically scattered and it will be the interaction of the unscattered and scattered electrons that will give you an image
in the electron microscope. But remember,
although we start with a 3-dimensional object,
what the image in the TEM gives you is a 2-dimensional projection of the object.
Remember, this is not a surface like in SEM,
it is a projection of the whole structure, but now compacted into two dimensions.
Things are really worse than that because the radiation sensitivity of the sample
means that we put in very few electrons to generate the image and the image is really noisy.
So, this is the true data that we have to deal with.
From here, from this noisy, 2-dimensional images, we need to get back to 3-dimensional object
in great detail. So, how do we do it?
That is, the details are going to depend on the type of sample,
but typically involve a process by which many images of the object in the same orientation
are identified, aligned and averaged to recover the signal so that now we have things that look more like that.
If we can get these type of images now,
but of the object in different orientations,
then they can be combined as long as we find out the relative orientation between them
to move from 2D to 3D and recover a structure.
This process is what we call reconstruction
and how each one of these two steps are carried out depends
very much on what type of sample do you have.
So, one type of sample that is ideal, but comes very rarely,
is that of 2 dimensional crystals of proteins.
In this case, the protein is arranged in a single plan in an ordered lattice
that can extend for several microns.
with a thickness that is just a single protein.
This kind of sample always falls in the same orientation in the grid,
so you know that to get 3-dimensional information it is absolutely required
that you do what we call tilting.
This means tilting the sample with respect to the electron beam
so that we can generate different views of the object.
This tilting process is actually experimentally very complex and difficult,
but once the data is collected, the computational processing is very simple.
And it actually allows you to get to very high resolution fairly fast.
This is because the image of these ordered arrays
contains very high resolution information, as can be seen in this electron diffraction pattern,
from such two dimensional protein crystals which extend to about 3 angstrom resolution.
Another type of sample that is really very helpful and great for doing EM are helical arrangements.
These can be naturally occurring or they can be artificially produced.
Because in a helix, the molecule is in different orientations
as you move through the helix, you get different views that are related by the geometry of the helix.
So, no tilting is needed and you can actually obtain a full, 3 dimensional reconstruction from a single image
although initially, you may have low resolution.
Now, these type of methodology is able to get between medium to high resolution,
meaning between 10 and 3 angstrom resolution.
And, like for crystals, the order in these structures, means that in Fourier space,
if you want, in the diffraction pattern, we have reflections that are well-separated
and we're filtering, I'm not going to go into details,
but the filtering is equivalent of an averaging process.
So, the 2D classification and alignment and the 3D reconstruction are very trivial computationally
for both of these two samples.
However, the most general type of biological sample is not going to be a 2 dimensional crystal
and is not going to be organized into a helix.
In that case, the type of reconstruction that we do is called single particles.
Typically, these objects are going to be randomly oriented in your EM grid
and no tilt will generally be needed.
The type of resolution that you get is going to depend on the type of sample.
For objects that don't have any internal symmetry and that may have floppy regions,
the resolution may be very low, on the order of a few nanometers,
while for objects with internal symmetry, like is the case for viruses,
the resolution can be very high, all the way to 3 or 4 angstroms.
In these cases, where there's no supra-molecular arrangement,
the computation is really heavy, it takes a big toll of the data processing.
So, let me show you some examples, let's go back to microtubules.
Microtubules are an example of cytoskeletal self-assembly into helical structures.
As I told you, microtubules are made of alpha-beta tubulin,
which are represented here by these light and dark cubes.
They associate longitudinally, making what we call protofilaments
and these associate in parallel, making the wall of the microtubule.
From images like these, of this structure, using helical reconstruction procedures,
it is possible to obtain structures like this, where each one of these correspond to a tubulin molecule,
and you can see details on the secondary structure,
the architecture of the molecule, one at a time.
It so happened that in the case of tubulin, you can trick it to self-assemble
into something different where protofilaments still form, but they associate in an anti-parallel fashion
where the structure doesn't close into a tube
but rather it grows into what can be considered two dimensional crystals.
These are the ones that produced these beautiful diffraction patterns that I showed you,
due to the high order in this polymer.
And from here, it is possible to obtain atomic resolution information
and that's where ribbon diagrams like this that now describe the path of the tubulin chains
could be obtained. I just want you notice that this was obtained in the presence of Taxol,
which is here shown in yellow. This is an anti-cancer drug that is used to bind to tubulin
and stabilize microtubules, make microtubules very stable.
And that has stopped the process of cell division
and it stops in particular cells that are dividing very fast,
those being cancer cells.
Typically, microtubules are very highly dynamic
and microtubules have been the object of cryo-EM study to describe actually
how the process of assembly and disassembly take place.
So, what I'm going to show you now is a short animation
that describes in very graphic way
how we think microtubules undergo the process of assembly and disassembly
based on cryo-EM structure of the intermediates that are generated in the process.
So, this is a microtubule that has reached a critical state
where it's going to lose its stability and is going to start depolymerizing.
This is the tubulin structure that I showed you before
so that you have an idea of how it arranges into the microtubule.
Microtubules break down actually by peeling back and curling of individual protofilaments.
The peels are normally very short lived,
they break apart and they depolymerize into individual subunits.
But we were able to trap them biochemically
in order to obtain this structure of tubulin in that conformation.
And what we found was that tubulin subunits are normally interacting with a kink,
but they are kinked internally and that is what makes it impossible for them to remain stably in the microtubule.
As a molecule of GDP is exchanged for a molecule of GTP
that re-energizes the tubulin molecule, straightens it out
and allows it to now form both longitudinal and lateral contacts
in what is, we believe, are the structural intermediates in the process of assembly
that is open and outwardly curved.
We could again stabilize that polymer by means of low temperatures and a non-hydrolyzable GTP analogue.
And this is the structure of what we saw,
was that the protofilaments here are paired up and within one pair
the interaction is just like protofilaments in the microtubules but between pairs, these interactions have rotated
and as this thing grows, it eventually starts rotating around that special interface
so that is closes into a tube in a process that can be very highly cooperative,
by zipping up of the tube as the protofilaments straighten.
So, typically, you would have a microtubule that is growing by addition of tubulin subunits
into an open sheet that then closes into a tube.
And eventually, this microtubule will grow, will reach a critical step and then will start depolymerizing.
And assembly and disassembly will constantly occur, as in the cell.
Ok, so I showed you samples, using tubulin, of how helical reconstruction or 2-dimensional crystals
are used to obtain high resolution information on a sample.
But, in many cases, we have to rely on single particle techniques
because these highly ordered structures are not available.
So, let me very quickly go through the processing that will have to take place
in a single particle project in order to get to the final structure.
To start, remember that we have our sample embedded, again, purified sample,
molecules, embedded either in stain or vitreous water,
that the EM image gives you a two-dimensional projection that is actually very noisy
because of the low doses that we can use.
Now, from here, what we will do is we'll visualize each one of these occurrence of our, say, protein complex
and we'll pick them out and generate galleries,
like this, that show our different molecules.
These are showing the molecule in different in-plane orientations, but also different views.
So, what we do computationally is we go through a process of aligning these images to each other
and then classifying them.
So, eventually we put everything that shows the same view in different classes
and now these are ready for averaging
and the averaging will give us now enhanced views of each of these orientations of the molecule.
These now have to be related to one another
and this is a very tricky step that I'm completely going to forget about for now,
but ultimately this can be very computationally involved
but ultimately if the relative orientations of these different views are obtained,
we can go and reconstruct the object in 3 dimensions.
Let me now illustrate how do we go from the 2 dimensional images
that we know are related to one another by defined angles to obtaining the 3 dimensional reconstruction.
We do that by something that is called back projection.
So, imagine now, this is a very simple example, where your object, your molecule, is made up by these three circles.
So, when you pass electrons through it, you generate a 2 dimensional projection that
looks say like this. And of course, you're going to have this object in different orientations in your EM grid,
which means that when you take different images,
what you get is different projections that look distinct
and that by some means you're able to place
one in relation to each other by finding the relative angles.
This is tricky to do, but once you've done it, the way to obtain the reconstruction is to back-project.
What does that mean? You take each one of these projections
and you smear it and you see how all of them intersect,
reproducing the object.
So, I have another movie that is a little bit more fanciful
because St. Patrick's day is coming, the day that we are filming,
so this is our object and what I want to illustrate here is
how as we use more projections, that are equally distributed,
we get more and more accurate representation of the object.
So, this is a movie in which now projections are being added and the intersection is giving rise to this leaf now
in more and more detail.
Let me now illustrate all of these with a real project.
This is our study of the exosome,
which is a molecular machine that is involved in processing RNA
and in some cases degrading RNA.
And the exosome, in this case from yeast, from budding yeast,
was purified and each one of these lumps that you see correspond to one complex, one image of the complex.
And the complex is randomly oriented in here,
and this is actually, by the way, a negative stain image, so all that I showed you up to now was cryo-EM,
but this is an example of a negative stain study.
So, if you go and pick out individual particles, this is how they look like,
this is a gallery. They're pretty noisy,
but going through the process of alignment and classification, averaging,
you get now images like these, that look a lot more well-defined.
So, the tricky part, which I'm skipping, is how each one of these images are related to one another,
but ones that were sorted, we were able to obtain a 3-dimensional reconstruction.
Just to tell you, we obtained two reconstructions,
one of the full complex, that is shown here
and one of a core element in the complex,
whose structure had been obtained at atomic resolution by X-ray crystallography
of the human homologue.
When we subtract one from the other, we get the core in blue and this extra region in yellow,
which happened to be the one that has the biochemical activity,
the site that actually chops the RNA.
Now, what is shown here is now the crystal structure of the human homologue
of the core domain. And what you see here in yellow are pieces that were taken from homologues found via bioinformatics.
And what this allowed us to do was to create a pseudo-atomic model
of how the top and the bottom part of this structure interact.
Now, this is actually a very common type of methodology.
We refer to this as hybrid methods
and it involves the docking of crystal structures of components
into the low-resolution structure of the full, functional complex.
And this is something that not only tells you how good your structure is,
but also gives you new information on,
say, interfaces, how this bottom part, and the top and bottom part, interact,
which elements are involved in that interaction.
And in this particular case, it gave us the path of the RNA by aligning the cavity
in the top part with cavities that exist in the active region
that lead you all the way to the active site.
So, no matter whether the molecule that we were studying was in a 2-dimensional crystal,
in a helix, or was a single particle with many copies,
we're utilizing and combining to generate the structure,
we were always looking at things where there were many copies,
of, identical copies of an object.
But what happens when we're interested in something where no two are the same?
Like, when we're interested in organelles or cells. What do we do here?
In that case, what we utilize is the method of electron tomography.
In electron tomography, the basic principle is all the views that are required to obtain a reconstruction
have to be taken from a single object.
Not from identical copies, but from a single object.
So, in here, again, the idea is we have a very unique sample for which there's no identical one,
say, an organelle or a piece of a cell.
And what we're going to do is we're going to take many views of the object.
By taking this object and tilting it,
and always looking and shooting,
grabbing images from the same object.
The images will be obtained by tilting very gradually, typically about 1 degree,
although how fine that division is made depends on the size of the object.
In here, how these images are related to one another is very easy.
It's just determined by you; you were always looking at the same object
and you were the one telling the microscope to tilt by a certain degree.
So, computationally, experimentally and computationally, it's very easy to obtain a reconstruction,
which in this case is again done by back projection.
The difficulty here, as you will see, has to do with interpreting these images
which seem to be noisier and are of organelles that are really, really very complex.
So, we have utilized this kind of methodology in my lab
to study yet another self-assembly system
and that is the one of septins, which are proteins that self-assemble and make
filaments that actually line particular sites near the membrane in the cell
at the position where cell division is going to take place.
We study septins in the organism where it was first discovered, which is the budding yeast.
What we're interested in when we look at these cells is just the particular region here,
where a filament has formed and where we want to see how they're organized and how they interacting with the cell membrane.
So, the first thing that we do is collect a tomographic tilt series
where we place the object in the electron microscope, decide what it is we're going to shoot at
and then take images, once for every tilt of one degree.
And here, these images are showing just one right after the other,
so these don't correspond to a reconstruction yet, this just shows you one after the other the images of a very thick section
where it is very, very hard to determine what is in there.
So, after this tilt series are used in back projection, we can generate the reconstruction
and I'm going to show it to you as a series of slices
going in and out several times in the reconstructed section.
So, this is the section, we started at the edge of the section and now we're going through
and I hope that you can see now that we see in much detail as we're going
each one of these speckles corresponds to ribosomes
and there's many of them in the cell, what you see here is the double membrane of the nucleus.
There's a lot more endomembrane here and of course,
right by the edges is where we're going to see our object of interest,
which are the self-assembly of septins into filaments
around the membrane.
So, you can see the complexity of reconstructions like this,
there's so much going on. So, in order to be able to look at it at once
what we do is we simplified this image, but just utilizing simple surfaces and lines
to trace through the surfaces of the plasma membrane,
of the nuclear membrane, of the filaments
that we can trace from one section to the other.
And we get a rendition like this by what we call segmentation.
So, this is now a very simplified view where we eliminate the things that we were not interested in,
like all of the ribosomes. And what you see here in yellow is the plasma membrane,
it's very curved because that's site of the bottleneck where the septation,
the division of the mother and daughter cell, is going to take place.
This section included a nucleus that is also in the process of dividing
with microtubules shown here in red that are pulling chromosomes apart.
There is more membrane that is internal that is shown here in kind of orange.
Actually, the thing that we were interested in looking at are these filaments
that run in a number of directions, they run around the circle
if you want, in the bottleneck, but they also run between daughter and sister cells
so, they're the ones that we're showing here in green,
the ones that we're showing in blue
and interestingly, there are also small filaments that are shown in red
that are connecting the membrane to this filament system.
So, just as a final note, imagine all the information that is contained in the tomogram that I just showed you a minute ago
where we only concentrated on this small section.
It would be great if tomograms are made available, publically available,
just like crystal structures or electron maps of reconstructions
so that anybody, irrespective of what you work on,
can take, can make use of the image to follow and track
the object of their principle interest.
So, this is the introduction that I wanted to give you of this technique
and I hope that in this brief time I gave you an idea of the generality of how applicable this method can be,
all the way from individual molecules to visualization of the cell.
And what I haven't had any time to tell you that this method is far from being totally optimized
and that there is a lot of development and improvement in the pipeline
that is going to allow us to get not only higher resolution,
but study even more systems that right now remain really challenging.
So, by the time someone like you is ready to use this technique, things will have really moved beyond
what I showed you today. So, I really cannot wait for that moment myself.