Hello everyone!
Welcome to the microscopy lecture series.
My name is Xiaowei Zhuang.
And I am a professor at Harvard University
and an investigator of
Howard Hughes Medical Institute.
And today what I am going to tell you about
is a brief introduction of
super-resolution fluorescence microscopy,
which breaks the diffraction limit.
And such imaging methods allow us
to look at cells with much better clarity.
For example, here we see a conventional
image of mitochondria.
And here is a three dimensional
super-resolution image of mitochondria.
So I'll tell you a few methods
that allow us to get there.
But first let me tell you why we like
fluorescence microscopy so much.
As we all know, this is one of the
most widely used imaging modality
for biological research.
And two of the advantages
of fluorescence microscopy
is really very well recapitulated  by this movie that
I downloaded from the book
.
by Bruce Alberts et al.
So first right away jumping into the scene
even without even knowing what it is
is things that are moving, changing,
highly dynamic all the time.
And what you actually see here are
actually diving embryonic cells.
The blue is the staining for DNA
and the green is microtubule.
So because light is really quite non-invasive,
it actually allows us to monitor living samples,
even not only living cells, but also living organisms,
with relatively little perturbation.
And because of that,
and because of light microscopy
have reasonably fast time resolution,
so we can actually catch dynamics
as is happening in cell in real time,
as one important advantage.
The other advantage is aslo
quite obvious from this movie,
and that is you see different color objects.
Because light is really wonderfully colorful,
and also there are so many different
colorful fluorescent probes these days,
such as fluorescent proteins, fluorescent dyes,
quantum dots, you name it.
And also because they are
chemically or biochemically very specific approach
that allow us to specifically attach these probes
to the molecule of interest,
so when you combine these three aspects together,
what we have is a tool that allows us to look at
different gene products inside the cell
simultaneously with high molecular specificity
that when combined with live cell imaging
allow us to study molecular processes in real time.
And hence we can learn a lot about
what's going on inside the cell
from fluorescence microscopy.
That said, light microscopy also has
a quite significant downside.
And that is its resolution.
Traditionally resolution of light microscopy
is limited to a few hundred nanometers.
While that might sound small,
things inside the cell are much smaller.
For example, protein molecules are often
just several nanometers in size.
And not only that,
cellular environment is
a very crowded environment,
with molecules packed in high density.
So ideally if we want to see the
interactions between molecules
we would need a resolution
that is up to the molecular scale.
So before I tell you
how we try to approach that kind of scale,
in other words, to recapitulate this introduction,
we would like to keep the advantages
of light microscopy,
the live cell imaging capability,
the multicolor molecular specific imaging capability,
but push the resolution towards the molecular scale.
What's preventing us previously is
this so-called diffraction limited resolution.
Now since Jeff Lichtman is going to
give another iMicroscopy lecture
that will tell us what exactly
is diffraction limited resolution,
so let me just go through that very briefly.
Because light is a wave,
all waves are subjective to diffraction.
That means if we try to use a lens to focus light
no matter how an objective we can find
the focal spot nonetheless will have a finite size.
Even with the best high numerical
aperture objective in the world,
the focal spot size in the lateral dimension
is about 200 nm,
and along the axial direction
where light propagates down
is even approaching 1 um.
Now if we use such a spot to scan our sample,
and then each of these small features
will be broaden by the spot.
That's why the spot is also called
the point spread function.
If the features,
let's say two of these features are widely separated
despite each one of them is broadened,
none the less we can resolve them.
And if the features get closer,
closer, and closer together
eventually the two images of these two features
will overlap so substantially
so that you just see a single blob,
and that's when you no longer
are able to resolve them.
That means the resolution is basically
comparable to the spot size,
which is about 200 nm in the x, y direction
and about 500 nm in the z direction.
And this was first recognized
in the 1870s by Ernst Abbe,
hence diffraction limit is also called the
Abbe resolution limit.
Now with this principle of resolution limit in mind,
there are currently a couple of
different classes of methods
that allow us to break the diffraction limit.
The first is to take advantage of pattern illumination
to effectively shrink the size
of the point spread function.
And this class include methods like
Stimulated emission depletion microscopy,
or known as STED microscopy,
or its generalized form of RESOLFT microscopy.
And as well as the
structured illumination microscopy,
and particularly the saturated form of the
structured illumination microscopy,
as S(SIM) also allow us to get resolution
that is substantially beyond the diffraction limit.
The second class of method
take advantage of single molecule imaging
and stochastic switching of single molecules,
and representative examples include
the Stochastic optical reconstruction microscopy,
the short name is STORM,
Photo-activated Localization Microscopy [PALM],
and Fluorescence Photo-activation
Localization Microscopy,
the in short name of, that is, FPALM.
So I'm going to in this lecture briefly
elaborate both classes of approaches.
There are also these other
single molecule based methods
that take advantage of other ways to
change the single molecule signaling time
for example, through molecular bindings,
through fluctuation of fluorescence signal,
and through bleaching and so on.
These approaches include methods like
PAINT, SOFI, BALM and generalized SHRIMP,
and 3B analysis, as well as other methods.
But due to the limited time that we have in
this short introduction lecture,
I don't have time to elaborate on these methods,
but would refer interested audience
to these references
and other references so that you could find.
So first let me give you a brief
introduction of STED and RESOLFT.
Back in the 90s,
Stefan has already the foresight to realize that
it is actually possible to
break the diffraction limit in the far field.
And in his elegant STED design,
he uses two beams to accomplish that goal.
One of the beam excites fluorescence
to give this excitation spot,
and the other is a doughnut-shaped beam
that induces stimulated emission.
And that deplete fluorescence
at the edge of this excitation spot,
and effectively shrink the point spread function
to a much smaller size.
So one could imaging that if you use such
a small sized spot to scan your sample,
you'll get a resolution that is much
beyond the diffraction limit.
Later on, he, Stefan,
also generalize this approach
to the RESOLFT form,
which actually take advantage of
a general fluorescence transition,
reversible fluorescence transition,
that just limited to stimulated emission
to shrink the point spread function
and then give us the sub-diffraction limit image.
And this can be extend to the 3D form
by using a STED beam that also
deplete fluorescence at the edge of the
excitation spot in the z direction,
give you almost isotropically small sized
fluorescence spot that is much much
smaller than the diffraction limit.
And then here are some beautiful 3D STED images
of mitochondria, and you can compare the
conventional confocal fluorescence image
of mitochondria, and the 3D STED images,
and see a much improved resolution.
And STED can not only be applied to
living cells, but is also applicable to living animals.
Here is a remarkable movie of, STED movie of
neurons in the brain of a living mouse.
Since Stefan Hell himself will also give a lecture in
this iMicroscopy series, so
I won't further elaborate this approach.
Now let's go to this other approach, which also use
pattern illumination to effectively
shrink the point spread function.
And this is the structured illumination microscopy
developed by Mats Gustafsson,
Dave Agard, Rainer Heintzman and co-workers.
Now in this approach,
a sinusoidal excitation pattern is applied to the sample.
This excitation pattern
beats with the sample information
and brings those high spatial frequency information
that is otherwise not resolvable
by a conventional microscopy
into a range that is resolvable by light microscope.
So for example, what you see here
is the sample pattern that is superimposed with these
vertical stripes of excitation pattern.
And that generate these small fringes
that has a much lower spatial frequency
that can be detected by the microscope.
And with this, we can also have a
better resolution and diffraction limit.
Now in the linear form,
it can improve the resolution by two fold,
and in the saturated form or nonlinear form,
we can actually get the resolution much
beyond the diffraction limit.
For example,
what you see here is a 50 nm resolution
image of fluorescence beads,
compared to conventional images
again you see a much higher resolution.
SIM and also in principle, saturated SIM,
can also be extended
to the third dimension to allow us
to take a 3D supper-resolution image.
And here what you see is a 3D linear SIM image of
nuclear pore complexes,
and in comparison to the conventional image
you can see these pore complexes
much better resolved.
Dave Agard will also give
a lecture in this iMicroscopy series
to talk about SIM, so I also won't
elaborate on this method further.
So another class of supper-resolution
fluorescence imaging method
takes advantage of single molecule imaging.
So as we know in the single molecule field that
even though the image of a single molecule is still
diffraction limited,
meaning that the width of the image
is still a couple hundred nanometers wide,
nonetheless we can localize
the center of the image with
a much higher precision,
and this precision is roughly equal to
the width of the image
divided by the numbers of photons
that we direct take a square root.
So for example, if we detect 10,000 photons
from this images, square root of 10,000
would be a 100, so if we do 200 divided by 100
that gives us 2 nm.
So in other words,
despite the diffraction limit image
we can localize the centroid position of this image
with a few nanometer
or even higher localization precision.
This is a very powerful approach
that has already been used
to study a variety of biological systems.
For example
Paul Salvin and co-workers have applied to
directly visualize hand-over-hand
movement of kinesin molecules.
However, powerful as it is,
this high precision localization
of single molecules does not directly
translate into sub-diffraction limit resolution.
and that is because it requires well
isolated images of individual molecules.
One could argue that
if you already have two molecules
the images are well isolated from each other
then they are already resolved by
conventional imaging approaches.
So the question of resolution then comes in
as how do we then separate overlapping images
of single molecules.
In particular, you know
many biological samples are very heavily stained
with fluorescent probes so that
their individual images of
single molecules are heavily
overlapped with each other.
So in this scenario, how do we separate the
images of single molecules and
localize their centroid position.
Several years ago,
we and others had come up with the idea
of taking advantage of photoswiching of fluorophores
to break the diffraction limit
and separate these single molecules images.
Many fluorescent probes or fluorophores
are photoswitchable,
means that they have an ineffective dark state
and a fluorescent state
and they can be switched from dark state
to the fluorescent state by light.
In that case,
if we use a weak enough activation light
and what we can accomplish
is then activate only a small subset of the molecules
in the field of view,
such a small subset so that they are
isolated from each other,
and that will allow us to pinpoint the center position
of these images and determine the molecular positions
for those activated fluorophores in this particular frame.
And then we can iterate this process
over time, and then accumulate
a sufficient number of
localizations of individual molecules
to build up this superresolution image.
So you can see that in this case,
the image resolution is
no longer limited by the diffraction,
but instead limited by how precise
we can localize each individual molecule
and the localization density.
Now because we use a wide field illumination
to activate the individual molecules
in the field of view,
and there is no patterned illumination
so the activation process is stochastic,
you know we can say we activate
0.1 % of the molecules, but we don't know which
0.1%, so we termed this method
stochastic optical reconstruction microscopy,
and hence this acronym STORM.
I should also mention that
in the mean time, two other teams have
independently developed similar approach
and published their work almost simultaneously,
and that's, one of them is the team lead by Eric Betzig
and Jeniffer Lippincott-Schwartz,
and they termed their approach PALM,
and the other team is lead by Samuel Hess,
and he called his approach FPALM.
I should also note that
many other labs have contributed
to the development of different photoswitchable probes,
and different photoswitchable mechanisms
that have made this approach very versatile
that can be applied to many biological systems.
However again, due to the limit of time,
I won't have time to elaborate these different
switching mechanisms and different switchable probes.
I'll just give you one example of
the application of STORM
to image microtubules.
As you can see that in this case, this is
a wide field image of a microtubules
so where all the fluorophores are turned on,
so it give you a smeared poorly resolved image.
Now if we activate a small subset of molecules at a time,
and then because they are well isolated,
we can pinpoint their positions,
we plot their positions at the right hand side.
And then after enough accumulation,
we can see this type of STORM images of microtubules.
And you can see in comparison with the conventional
image of the same field of view,
there is a drastic boost of resolution.
And we also expand this approach
into the third dimension by taking advantage
of the sheet of individual molecule images
to determine their z position.
Now one of the simplest approach to do that
is to use the Astigmatism imaging.
In this case, a cylindrical lens is inserted into
the detection path, and because cylindrical lens
only bend light in one direction,
and not the orthogonal direction
and therefore individual molecules images are
in general electrical, and from the electricity
we can determine the z position of
individual molecules.
And then again from the centroid position we
can determine their x, y position.
So hence we can determine x, y and z, all 3D
dimensional coordinates simultaneously,
and using this approach we first demonstrated
3D superresolution imaging.
And this is a 3D STORM image of microtubules
taken that way.
And since then there are actually
quite a number of three dimensional localization
approaches that have been used for
3D superresolution imaging.
For example, the Biplane approach
the engineering of point spread function,
in particular, the double=helical point spread function,
using interferometry to determine z position,
and the using of micromirror to sort of flip
the z dimensional information into the x y plane
and other methods.
Again, because the limit of time, I won't have
time to elaborate these methods,
but to refer interested audience to these references
and other interesting papers
that have come out recently.
So here is an example of
using a Astigmatism imaging
to do 3D STORM imaging of actin in the cell
and actin is, because it's very small dimension,
it's high packing density,
one of the actually more difficult objects to be resolved
by light microscopy, and here you can see that
even though in the conventional image we don't see any
individual actin filament resolved,
but these filaments are resolved very well
in those 3D superresolution, 3D STORM image.
And the localization precision we accomplished
in this particular work is about 4 nm in x,y position,
and 8 nm in z position.
And that translate into a resolution measure,
meaning how far the two molecules need to be
in order for them to be unambiguously resolved,
in a resolution to be about 10 nm in x y,
and 20 nm in z.
STORM can not only be used for
imaging fixed samples,
but can also be used for live cell imaging.
Here I show you two examples,
and the first is actually a three dimensional, two color
STORM image of Clathrin coated pits,
and its cargo transferrin in living cells.
Here you can see the transferrin cargo inside the pit
and here you can see the transferrin
actually moving towards the pit.
And in the second example,
is a STORM movie showing you
fission and fusion of mitochondria.
What's quite remarkable about this movie
is that it is actually taken with the sample
just simply labeled with MitoTracker,
which is one of the very easy to use,
and commonly used probes that people use to
label mitochondria in living cells.
And then here you can clearly see
the fission and fusion intermediate,
the tubular type of structure.
So typically we can accomplish
a spatial resolution about 20 to 40 nm,
and a temporal resolution on the order of 1 sec,
and these images are taken typically
with 1 kHz type of frame rate.
So 1000 images to give you one movie.
STORM can not only be applied to image cultured cells,
it can also be applied to image tissue samples.
For example, what I'm showing here is a
collaborative work between Catherine Dulac's lab
at Harvard and my lab, where we
imaged synapses in brain tissue slices.
And what you see here is a conventional
wide field image of synapses labeled with
Bassoon, a presynaptic scaffolding protein,
and Homer1, a postsynaptic scaffolding protein.
And here's the STORM image of the same field of view.
Since this is a three dimensional image,
we can sort of take one of these synapses and
show you a three dimensional perspective
showing the movie
where you can clearly see the pancake shape
like structure for the presynaptic active bassoon
and the post synaptic density
and also the clear separation of these two structures
by the synaptic cleft.
You will hear more about this single molecule based
superresolution fluorescent microscopy approach
from Jeniffer Lippincott-Schwartz, and Bo Huang
who both will speak in this iMicroscopy lecture series.
So I'll also not dwell in the technicality
of this approach any further.
But I will end this lecture with one recent
biological application where we
applied STORM to study
actin cytoskeleton structure in neurons.
So as we all know
actin play a variety of very important roles in cells,
and also in particular in neurons.
It is important for the polarization of neurons.
It is important for the stabilization of axons.
It is important for the stabilization
and plasticity of synapses.
And it is also important for intracellular transport
and other functions.
So because of these important functional role
it will be really nice if we know how actin filaments
are organized, how actin filaments are organized in
neurons, but very little is known about that.
In particular, very little is known
about what actin filament
is organized like in axonal shaft,
and in dendritic shaft.
And that again is because what I said earlier
that actin filaments are so skinny,
and they are packed in high density,
they are packed in high density together
with other filamentous structures,
in particular in axons,
they are packed together with
neurofilaments and microtubules.
So because of that, to resolve actin structure
actually requires both ultra high spatial resolution
and extremely high molecular specificity.
And therefore superresolution fluorescent microscopy
provides ideal approach to solve this problem.
So here what you see is a three dimensional
STORM image of actin in the dendritic compartment.
We know it's the dendritic compartment
because the red label here, actually the MAP2,
is dendrite specific.
And these Phalloidin labeled actin filament,
you can see that they run along
the longer axis of the dendritic shaft.
This is a type of organization
that is not so hard to imagine.
And what is very surprising to us
is when we look at
what actin look like in axonal shafts,
and we see this drastically different picture.
Instead of running along the long axis of axons,
which we do see a few filaments like that,
but the most prominent feature or aspect is
this stripes, these stripes that are perpendicular
to the long axis of the axons.
And they are arranged in this very regular pattern.
And it is very hard to see by other means,
for example,
this is a conventional fluorescence image
of the same field of view.
Now because this is a 3D image,
we can also look at what these stripes are by
turning the thing aside,
and you can see they are
actually ring-like structures
that wrap around the circumference of the axons.
As I said, they are highly regular.
You can take any segment of axons,
and then project the localization,
the actin localization
into one dimension,
and then you can subject this one dimensional
localization distribution to Fourier analysis,
and then see this clearly peaky structures.
You can see the primary peak,
and the secondary and tertiary hormonic and so on.
And then for this particular segment,
these Fourier analysis, the peak
corresponds to about 190 nm periodicity.
And then if we look at many filaments,
this is the distribution,
many axons, this is the distribution of periodicity
which is about 182 nm +- 16 nm.
So how do the actin filament manage to organize
into such a periodic structure,
in other words,
what are the factors that are spacing the actin rings.
So the spacing periodicity of 182-190 nm
actually offered us some clue.
Because that reminded us of this molecular complex
called spectrin tetramers.
And spectrin tetramer,
the only place where the organization of spectrin
is known is actually in red blood cells.
And there, spectrin tetramers form these triangular
shaped network, or polygonal shaped network,
where the spectrin tetramer forms the edge,
and at the nodes are actually short actin filaments.
So in other words, you can see that spectrin
can connect neighboring short actin filaments.
And spectrin is ubiquitously expressed in
many metazoan cells.
And therefore, it is also in the brain.
And actually brain spectrin purified
has a length of about 195 nm.
So you put these together, then spectrin becomes
a very good candidate to be the one that's spacing
actin filaments, because it can connect actin
and it's about 190 nm long.
So that led us to this hypothesis,
that the ring we see are
actually short actin filaments
and we think they are short because
in analogy to red blood cell.
And we think they are capped by adducin,
again in a analogy to the red blood cell structure.
And these structure of actin filament line up into
this kind of ring structure wrap around
the circumference of the axon.
And neighboring actin rings are actually
spaced and connected by spectrin tetramers.
Now to test that,
then we can image spectrin and adducin
together with actin.
For example, if we image the middle portion of
the spectrin tetramer, for example,
we can immunostain the C-terminal domain
of beta two spectrin, which is in the middle part
of the spectrin tetramer,
then we should see that stain to alternate with
the actin stain,
forming these alternating stripe pattern,
which is indeed what we see in the two color
STORM image of actin and the spectrin
C terminal domains.
And adducin we expected to line up with actin,
which is indeed also what we see.
And as a corollary,
you can see that the spectrin C terminal domain
and adducin form those alternating patterns.
This is a quite prevalent structure,
here is an entire field of view we have taken
for hippocampal cultured neuron,
and then you can see that except for this
big, fat dendrite in the middle,
all the other axonal structures show this
periodic, ladder-like pattern.
And this sample is stained for Beta-II spectrin.
And we can not only see this in cultured neurons,
we can also see it in brain tissue slices.
And here is the spectrin stain in brain
tissue slices where you can clearly see
the periodic-like pattern.
So put it all together,
we found that in axons, there is this novel
submembrane cytoskeletal structure that
was previously unknown.
And this structure is formed by
periodically arranged actin rings.
And these actin rings are
short filaments of actin alined around the
circumferential direction of the axons,
and these neighboring actin rings are
connected by spectrin tetramers.
So we have also results, and reasons to
believe that this periodic remarkably
long range ordered structure
plays some important roles for neurons.
For example, because spectrin is flexible,
so this cytoskeletal structure is
both robust and flexible,
and it can provide the kind of elastic and
durable mechanical support that
a thin and long axon filament needs.
And also, because this is a submembrane
lattice structure, it actually can
anchor membrane proteins
also in a periodic pattern.
And for example, we know
some of the very important
functional membrane proteins
in axons, like sodium channels,
we also found that it also forms a periodic
pattern in accordance with the underlying
cytoskeletal structure.
So this new structure could potentially
be important, novel structure for neurons.
But again, because of the time limit of this
short intro lecture, I won't elaborate
further on the structure, the development
function of this cytoskeleton structure.
But hopefully, through these brief introductions
of the variety of superresolution fluorescence
microscopy methods, and through this
one interesting recent biological application,
I hope I have conveyed you this message
that these new fluorescent imaging methods
are indeed powerful, and they can indeed
lead to new biological discoveries.
And this a very rapidly developing field
with many new things, new methods,
and discoveries that keep coming out.
For those interested audience,
you can also find exciting lectures
given by Stefan Hell, Jeniffer Lippincott-Schwartz,
Dave Agard and Bo Huang
about superresolution fluorescence microscopy
and in this same microscopy lecture series.
So with that, let me thank
the people in my lab
who both former group members and
current group members who have contributed
to this work, in particular,
to the studies I discussed in this lecture.
And the early development of STORM
is largely due to three former group members
Bo Huang, Mark Bates, and Mike Rust.
And some of the more recent development of
the STORM I have talked here,
for example, the live cell STORM imaging
is due to Sang-Hee Shim,
and Sara Jones, and the improvement
of resolution by the dual objective geometry
is due to Ke Xu and Hazen Babcock.
And the biological application of studying
actin and spectrin dependent cytoskeletal structure
in neurons is done by Ke Xu and Guisheng Zhong.
And I would also like to thank
Howard Huge Medical Institute and
the National Institutes of Health
for their generous support.
And also very importantly, thank you
the captivating audience for being interested in
advanced microscopy approaches.
Thank you!
