Data collection (imaging)
Now that we've talked about sample prep, let's talk about imaging.
In a single particle project, the images can either be collected manually or
automatically by a program written to do that.
For instance, the one I'm going to use as an example is Leginon, a program for
automatic data collection.
The Leginon imaging approach begins by recording
what is called an atlas of an entire grid, and that's shown here in the first panel.
And what you see is a bunch of green squares here in a lattice,
and each of these squares was an individual image
recorded by the microscope at a magnification of approximately 120 times,
where you can see multiple individual grid squares in this image.
And then lots of images like these are tiled together
to form the atlas of the complete grid.
So using the atlas one can inspect the whole grid and
detect regions where the ice is just right, or where the ice is too thin or
too thick, and then select regions of interest.
And so here if we consider this one of the regions of interest, in this image we can
then further select specific grid squares where it looks the ice is just right.
So this grid square looks promising, and this grid square is promising and
then so is this one and perhaps this one.
See these have some ice around them.
You can see because some of the grid square is covered by thicker ice.
For instance this is a grid square where the ice is very thin along the outside but
then there's something very dark in the middle, and so
this is not a promising grid square.
But these look just right for further imaging.
And so one of these particular grid squares can be chosen,
and then it is imaged at a higher magnification, say like 500 times.
And so here in the picture of a particular grid square you can now
see individual holes.
And here we have some region of the grid where the ice looks too thick for
high resolution imaging, so those aren't the best.
But over here these holes look just right.
And so one can choose several holes for
high resolution imaging, and in addition to the holes that will be imaged for
high resolution information on your particle structure, another hole can be
chosen to reset eucentric height during the imaging procedure.
Okay, once that is done then a higher
magnification image can be recorded of a single hole.
So here this hole has been imagined and
the blue square shows the picture that you see here in panel D.
And this image was recorded at more like 5,000 times magnification.
So here you see a single hole in the carbon film full of particles and
ice that nicely covers that hole,
there's a little bit of contamination here that you obviously want to miss, and
the computer can select target areas for final high resolution imaging.
So, for instance, one target area is chosen right here,
another target area is right here, and the third target area is right there.
In addition to that, one might choose a focus region next to those holes
shown here in purple, and the beam can be deflected to this focus region and
a very high dose image can be recorded.
If you look at the power spectrum of that high dose image here, that's what's being
shown here and inside the purple square in Panel E, and you can see
in the power spectrum of that image the various tawn rings in the power spectrum.
And that can be fit to theoretical CTF curves to determine the focus and
set it just right.
Once the focus is set just right at the focus spot,
then high resolution lotis images can be recorded on these targets.
And so for instance,
the image recorded here, shown in green, is now presented as panel F.
So this is a high magnification final image of the region being recorded at say,
50,000 times magnification, and this is the image
where individual particles will be picked and further processed.
Now you'll remember that the principle resolution limitation in cryo-EM
is radiation damage, meaning that the electrons break the sample, and so we have
to be very limited in the dose that we apply to a sample before the final image.
And so an important principle is to look at
how many times have we already imaged this hole?
Well, once in the 5,000 times mag image, again we imaged it
in the 500 times mag image, we also imaged it at 120 times mag.
And so you can ask how damaged are the particles here
before we ever get the final image?
Well, remember that the dose rate falls off as the square of the magnification.
So if you take a one second exposure at 50,000 times magnification,
and you take another one second exposure even at the same beam intensity,
but this time the image is only 5000 times magnification,
the dose delivered here is only one percent of the total dose delivered here.
And the dose delivered to record this image at 500 times magnification
is one ten thousandth of the total dose used for this final image.
And so because these are low magnification images
they can be captured without significant radiation damage to your sample.
And so in a typical single particle project
a grid will be inserted into the microscope, and then Leginon or
some other program for automatic data collection, will record an atlas, and
a user might select specific squares that they think are best for further imaging.
And then the computer can go ahead and pick holes by itself, and
record hundreds or thousands of high magnification images
at just the focus values that are desired of the sample automatically.
Now, of course, while this is happening, the investigator will want to
follow the process and ensure that the right things are happening along the way.
And for this, Leginon has what it calls the Leginon observer utility.
And this is just a web page where you can show up to six different
kinds of images that are being recorded during the procedure and
just follow how the process is moving forward.
A big advantage of using an automatic data collection software package is that your
images are, without any extra effort from you, then organized into a database.
And so in Leginon, Leginon has a database of all the images that it's ever
recorded and their relationship to each other and
other parameters about the data collection session along the way.
For instance, it can track grid drifting during the session and
predict where samples will be moving,
where targets will be moving during the data collection session.
And afterwards, all these images are stored in a database, and so
this is a web based viewing tool.
So here is a list of the various images that the Leginon database has for
a particular session, and you can click on different ones and see them.
And for instance see the relationship between a high magnification data image.
From the lower magnification images that show you where that was taken from and
all of this is organized for you and can be processed and managed more easily.
Now, sometimes in a single particle project instead of just recording single
images of a field of particles, sometimes focal pairs are recorded.
And you've seen this slide before,
but it just shows a focal pair of a field of viral particles.
So here's an icosahedral virus of this large round object.
Here's another icosahedral virus, one of them is circled here.
And this is another picture of the same field of viruses taken
much further from focus.
And below them you see the plot of the contrast transfer function.
And we've already gone over this slide before.
But it just illustrates that there's different information content in this
image taken at high d focus from this image which is taken closer to focus.
And so, as we'll see later, in order to build a high-resolution model,
sometimes investigators employ a strategy of recording
focal pairs of the same field of particles, likewise,
sometimes tilt pairs are recorded of the same field of particles.
And so, here is a field of hemocyanin particles that were imaged first untilted.
So the tilt angle is 0 degrees and
here you can see all the various particles and I drew your attention
to this image first because it's untilted unlike the others that we have discussed,
but it's actually the second image that is typically recorded.
The first image is typically recorded of a tilted sample,
tilted to say maybe 45 degrees.
And here is depicted the tilt axis and so what you can see,
comparing the 45 degree tilt image to the untitled image and
many of the particles have been circled.
The same particles circled over here are the same ones circled over here.
So you can see that in this tilted image, the particles have been compressed
towards the tilt axis and here they're spread out more.
And you can choose images of individual particles and show them, for
instance here, as a 0 degree image, and then pair
them to the 45 degree tilted image here and you can pick this out and
show what the particle looked at an orientation of 45 degrees tilted.
And this allows one to produce a reconstruction using what's
called the random conical tilt method that we'll discuss later.
Another variation on the same basic idea is to record the first image at, say,
-45 degrees, and then a second image at +45 degrees.
And another variation on that same basic idea is to record the first
image at -45 degrees and then record the second image at +45 degrees.
And as you might be able to guess, this tilt pair will have
the advantage of being exactly 90 degrees apart from one another.
And so, here's an enlarged version of the -45 degree image,
here's an enlarged version of part of the +45 degree image.
And as you can easily see, individual particles in this image can be
paired with individual particles in the other image,
giving us two different views of the same particle.
And so, in some variations of the basic single particle experiment,
focal pairs are recorded or tilt pairs are recorded.
Now, unfortunately, when one takes a picture of a thin film of ice,
the radiation causes changes in the specimen and
causes some beam-induced specimen movement.
In particular, vitreous ice within holes moves and
flows and bulges with exposure.
At one point my group was interested in the changes that happened to thin films
of ice when they are radiated.
And also when they're cooled either by liquid nitrogen or liquid helium.
And when they're warmed up and transitioned between these.
And what we observed, we had fiducial markers distributed throughout this ice.
And here's a picture of a particular hole and fiducial markers, and after
one of these temperature transitions, we noted which fiducial markers had risen
in the ice, and which ones marked in blue had actually lowered in the ice.
So what you can see is that the fiducials in the middle
bulged up with respect to the ones around the outside.
And if we reverse that temperature transition
we could get the opposite effect of the fiducials in the middle
falling with respect to the ones on the outside.
And these images are of a particular hole tilted to high angle, about 65 degrees.
And here the ice is relatively flat and
you see it from a high positive angle and a low angle.
And then, after imaging and a temperature transition we see that now the ice
has a dark bulge here right through the middle.
See how this side of the ice is much darker?
That's because it's bulging out away from that hole.
And the negative tilt angle shows that bulge on the opposite side.
So one of the major changes in the ice during imaging is that
the ice will bulge within the hole and also flow somewhat.
Now, this process is depicted in this figure from 2012.
Showing a carbon film with vitreous ice surrounding here icosahedral viruses and
the idea is that the electron beam, when it hits the sample,
can cause many changes.
One is that the diameter of the carbon hole can decrease.
The carbon can actually stretch inwards.
In addition, radiolosis and
charging within the hole can cause this material to want to expand and
as a result there's a doming effect of the sample within the hole.
Now, unfortunately, while the vitreous ice is bulging during the exposure,
particles within the ice change their orientation and they flow into different
positions as illustrated in this experiment imaging icosahedral viruses.
Here, they had a field of purified icosahedral viruses.
There's a virus.
Here's another virus.
Here's another virus.
And these are imbedded in vitreous ice across a hole in the carbon film.
And using a direct detector which can record images in rapid sequence,
40 times per second or more.
These investigators recorded a sequence of images
called subframes of a single long exposure.
And then, because each icosahedral virus,
it's a massive object with lots of intrinsic signal and also symmetry.
They could find the center of the virus
in each of the subframes of this exposure series.
In addition, they could also detect the relative orientation
of each virus because of it's high symmetry, you can do that.
And track how the orientation of the particle changed during
the single exposure.
And so, in panel A, what is shown are vectors showing the direction and
the magnitude of the orientation change of the virus,
how it rolled during that single long exposure.
And note that the scale bar here,
this depicts a one degree change in the orientation.
So you can see that some of the viruses, their orientation is pretty well fixed.
But other viruses are rolling up to a degree or
more, in an apparently random direction.
This one is very different than this one, say.
As that ice bulges, the translations that the virus
has exhibited during the exposure are depicted over here in panel B.
And so here, the scale bar is ten angstroms, and
the translations are shown here on the figure.
So obviously, the translation factors are not on the same scale as the image itself,
because the viruses more like 100 angstroms itself.
But this translation of that much is just ten angstroms.
But what you can see is that the viruses are moving within the ice.
Most of them here are moving in approximately the same direction, although
some are a little different, by ten or more angstroms during the exposure series.
And, unfortunately, the shifts and the rotations that
each particle will experience during the exposure is unpredictable.
Here on the left is a picture of mitoribsosmes recorded.
And each of these vectors is again,
showing the translation that each particle exhibited during an exposure series.
And if you just look at it, you see that the whole field of particles seem to flow
up and to the right during the exposure.
But this is very different than another case of the complex-I protein.
Here its vectors as you look at the vectors around the field,
you see some of them seem to be flowing out towards the edge, others are flowing
in a different direction, and these are doing something yet again different.
So the take home message is that during an exposure the ice bulges and
the particles can flow and roll.
Now over the years there's been a couple ideas emerge to help reduce
beam-induced specimen movement.
The first is that it was observed that including some carbon in each of
the exposures seemed to reduce beam-induced specimen movement.
The second idea is to use a more rigid grid material and so
there are efforts on going to explore different kinds of
grid materials that might strengthen the samples and reduce this movement.
And so this is why one typically chooses to take pictures on the edge
of a hole like this one and this one and
this one rather than right smack in the middle of the hole.
It's because it's been observed that if some of the carbon next to the hole is
also exposed during the image there's a last beam induced specimen movement,
and the reasons for that are still unclear.
Now, the good news is that if your camera can record images very quickly
in a so-called movie mode where it records many sub frames every second,
then images can be motion corrected computationally after the fact.
And this is illustrated in this figure.
Here is a picture of three viruses.
And in this image,
all of the subframes were simply averaged together without any motion correction.
And so you can see that particles are blurry and the details are missing.
However, if you use cross-correlation to
track how each particle moved during that exposure.
And then motion corrected so
that all the images are more coherently averaged together.
Then the particles are much crisper, with much higher resolution detail present.
So in summary, while data collection for single particle analysis might
seem pretty simple and straight forward to just record a projection image
of different fields of particles, in fact it could be more complicated.
Sometimes you'd like to record focal pairs,
at other times you record tilt pairs.
And at all times you need to minimize beam-induced specimen movement.
And if possible correct it through motion correction.
