Transcriber: Robert Tucker Reviewer: Ariana Bleau Lugo
I'm a biophysicist, and in my lab at the Institute of Photonic Sciences,
we develop and use tools that are inspired by physics to study biology.
And the tool that I will talk about today, that we use the most, is microscopy.
In fact, I will talk about a particular type of microscopy
which is based on fluorescence.
Why microscopy, you might ask.
Well, because we like to see things to understand how they work.
Seeing is believing.
And, in this case, we want to understand biology.
So, we want to look at cells that make you up,
and we want to look at molecules that make those cells work.
And these things are really small.
So, in order to see them, and study them, and understand them,
we need powerful tools, tools like microscopy.
Of course, microscopy is not a new concept.
We have been building
and playing around with microscopes for a long time now.
And perhaps this may be the first example of the use of a microscope.
And the next one after that dates all the way back to late 1600's.
And during this time, two really great men were using lenses
to build microscopes and they used these microscopes to study nature.
And this a drawing of a flee
that Robert Hooke made in his famous book "Micrographia".
If you look at this drawing, you will see that it's really detailed,
very beautiful.
So, if we want to claim that we have made progress
in the field of microscopy,
this is really the kind of picture that we're competing with.
We really need to do better than that.
And, today, I hope to convince you that indeed we can do better than that.
We can zoom up into this flee, go past, beyond the organs,
and look at individual cells.
And we can look at molecules and proteins that make those cells work.
In order to do that, we take advantage of a lot of technological breakthroughs
in the fields of biology, physics and chemistry.
The first thing that we need are labels.
These are things that we can attach to the protein or the cell
that we want to study,
so that we can see it in our microscope.
And fluorescent labels work best for these.
These are labels that, when you excite them with light,
for example, laser light,
then, they give out light of their own,
and you can capture that light with a sophisticated camera.
So, if you attach these labels to a cell,
and you make a picture of the light coming from these labels,
essentially you are making a picture of that cell.
We can synthesize these fluorescent labels in the lab,
but, of course, as always, nature has given us
some of the best fluorescent labels.
These are fluorescent proteins that we can extract
from something like jellyfish in the ocean.
And the picture that you see on the top
are green jellyfish that are found in the ocean.
They're green because they contain this fluorescent protein.
And we can extract that fluorescent protein,
and we can then use it to genetically engineer
an animal or a cell to become fluorescent.
So, this is really great, because we can use these fluorescent proteins
to label whatever that we want inside an animal or inside a cell.
And so, for example, we can genetically engineer mice
to be fluorescent.
These mice that you see are green
because they contain these fluorescent proteins.
And we genetically engineered them
with these fluorescent proteins to be green,
so they glow green under light.
If we target these fluorescent proteins to the right place,
then we can zoom up into these animals,
and we can look at collections of cells that make up a tissue,
for example, brain tissue.
We can look at even individual cells, like neurons in the brain,
and we can zoom up into those cells,
then we can look at organelles like mitochondria,
or proteins that are found on these organelles.
So, all we need are some actors,
and we turn the lights on, and we let the camera roll,
and we can capture biology on our camera.
So, I want to give you one specific example
in which the actor that we chose to study while I was back at Harvard
was influenza virus.
I'm sure that you're all familiar with this virus,
it's very common and most of the time it's just a nuisance,
but, of course, it can also be deadly,
and we always have to deal with new emerging strains of flu.
So, if we understand how the virus enters and invades a cell
at the molecular level,
then, perhaps, we can devise better ways to treat viral infection.
But, of course, the virus is really tiny, we cannot really see it by eye,
so, we need these fluorescent labels to tag the virus,
and we need our powerful fluorescent microscopes
that we can build in the lab using laser lights and cameras,
in order to study the viral infection.
The viral infection is a really long, complex, dynamic process,
and if you just have a few snapshots to look at that process,
then you cannot really understand how it happens,
because you don't know what happened before the snapshot,
and you don't know what will happen after the snapshot.
So, if you ever watched a football game, I think you will understand what I mean.
Trying to understand what happens during a viral infection
from just a few snapshots,
is just like trying to understand what happens in a football match
from by just looking at a frame.
Because the game is really fast and really dynamic,
you don't know who passed the ball to whom and who scored the goal,
if you just have one snapshot, right?
So, what you really have to do is, you have to sit down
and watch the game from the very beginning to the very end,
without missing even a second of it.
And this is exactly what we need to do with the viral infection,
we have to watch the entire process as it's happening.
And the great thing about using light to study biology
is the fact that light is non-invasive,
so we don't have to kill the cells that we're studying to study them.
We can have the live cells, and we can throw the virus in there,
and let the virus infect the cell,
and we can watch this whole process as it's happening.
And this is exactly what we did, we made movies of influenza virus,
as the virus is infecting cells.
And we make movies of many viruses, as they're infecting a cell.
And we then wanted to study these viruses one at a time.
Because much like football players, different viruses may behave differently,
and you want to capture all that heterogeneity,
all that complexity.
So, you want to study each virus, one at a time.
And so we devised a scheme called single virus tracking,
and this is how it works.
Charlie Chaplin, in this case, is the virus
that's about to infect a cell,
and the wine bottle is the fluorescent label
that we placed on the virus,
So, by just looking at the light that is coming from the fluorescent label,
we can follow the motion of the virus inside the cell, and we can track it.
The cell may be really crowded, but we are blind to everything else,
we only see the light coming from the virus.
and we can follow it around.
If we really want, we can use a different fluorescent label,
and we can tag something else.
For example, we can tag a protein in the cell.
The virus may interact with that protein,
and if we label both of them, then we can watch those interactions.
Those interactions may be brief,
but because we're making these really fast movies,
then we can capture all of this.
And so this is the actual movies that we made
of influenza virus infecting cells.
And these bright spots that you see moving around
is the light coming from these fluorescent labels
that are attached to the virus.
So, we are actually following the motion of the virus inside the cell.
And sometimes we have the virus on its own,
and sometimes we tag the virus in red, and a protein in green,
and we can watch them interact.
And then we can make really detailed, really, highly quantitative plots
of the virus's motion and its interaction with other proteins.
So, we have a lot of information to work with,
and I don't I have time to go into details,
but by doing this, we're able to learn
information that you couldn't with any other technique,
because we were able to watch the process, as it's happening, in real time,
from the beginning to the end.
And this is great, and it's not just applicable to viral infections,
you can actually use this concept to study many other cellular processes.
So, fluorescence microscopy is a super powerful technique
for understanding what happens in biology
at the cellular, subcellular and molecular level.
But, of course, like any other great thing,
there's a problem with fluorescence microscopy,
and I've ignored this problem so far.
But now I want to speak about this problem.
And to do that, I'm showing you a picture taken with a fluorescence microscope,
and this picture shows you highways in the cell.
These are just like the highways that we have in our cities.
They're used for transport.
So, when you see the virus moving around in the cell,
it's actually most likely moving on one of these highways.
Now, if I zoom up to this picture,
then you see that it starts getting pixely and blurry.
And this is because light is a wave, it has a certain wavelength.
And if we are looking at something that is smaller than the wavelength of light,
then its image becomes blurred out by the wavelength of light,
so we lose information, it becomes blurry and pixelated.
Of course, a lot of things inside the cell are smaller than the wavelength of light.
So, even though we can still do quite a lot
and learn a lot of information from these blurry, pixelated pictures,
we would like to study this in as much detail as possible.
So, this is the big problem.
And many people have been thinking about ways to overcome this problem,
and I was lucky enough, while I was at Harvard,
to work with Professor Xiaowei Zhuang.
And she, and two other talented graduate students at the time in the lab,
Mark Bates and Mike Rust,
they developed a technique
to overcome this limit of resolution in fluorescence microscopy.
They called this technique
stochastic optical reconstruction microscopy.
That's really, really long, but there's a reason for that,
because it spells out the word "storm".
So, you can call this technique STORM, in short.
And so I'm going to try to explain to you
how STORM overcomes this limitation of resolution.
In fact, we have other techniques that achieve the same thing,
but I want to just talk about STORM,
because this is really the technique that I'm now using in my lab in Barcelona,
to study biology.
So, let me attempt to explain this to you.
Imagine that you make a picture of a fluorescent label,
in this case a single fluorescent label,
these labels are much smaller than the wavelength of light,
so their picture, their image, becomes blurry,
and you see this one big blob.
And the graph that you see, which is really the only graph in my talk,
is a mathematical representation of that image.
It looks like a mountain with a peak.
So, this is a big, blurry image,
but what you can do is, you can find the center position of that image,
or the peak of that mountain.
And what that tells you, is the position on the fluorescent label.
So, the fluorescent label is at the center of this image,
or at the peak of that mountain,
so, you essentially reduce this blobby, big image to a small cross.
And that cross tells you where the fluorescent label is.
So now, if you can find the positions of many fluorescent labels,
then, you can, by putting those crosses together, recreate an image.
And this is exactly how STORM works.
Imagine that you write the word "STORM" with many fluorescent labels
and, if the word "STORM" is smaller than the wavelength of light,
and you make a picture of it with your fluorescence microscope,
then the signals from these labels blend together.
You see this big smear, you cannot tell that this says "STORM".
So, you get a blurry image.
But if you are able to find the position of all the fluorescent labels,
and put those positions together, then you can recreate the word "STORM".
It's easy to do that when you just have one fluorescent label;
it's not so easy to do when you have many fluorescent labels.
So, in fact, we work with very special fluorescent labels
that we can, by exciting them with light,
switch them off so they become dark.
And then we can bring back only a few at a time.
So, now you have few blobs,
and you can find the centers of those blobs,
and you can put crosses there.
And then you can do this process over and over and over again,
and if you have done it enough times,
then you will find all the positions of the fluorescent labels,
and you put them together,
and you get a much more detailed higher resolution image.
You can say that this spells out the word "STORM".
So, STORM, essentially, is like pointillistic painting.
This was popular in the 1800's,
and really talented painters could paint these complicated scenes
by putting together dots.
And this is exactly what we are doing, we are putting together dots.
In this case, these dots are the positions of fluorescent labels,
and we are making an image from that.
So, I'm going back to the picture that I showed you
of the highways in the cell.
Now, we can repaint this with our STORM microscope,
and then if we zoom up to this, now we don't get pixelation anymore,
like we do with the normal microscope.
We can see where these highways are with much more detail,
how they cross each other,
and we have improved the resolution of our microscope ten times
compared to a normal fluorescence.
So, what we did in Barcelona then, was to go back to making movies.
So, now we're making movies of again things moving inside the cell
but this time, these are not viruses, these are organelles.
And, on top of this movie,
we overlaid this high resolution image of the highways.
And now if we zoom up to this,
for the first time, we can map the track of this organelle
with very high detail and high precision to exactly which tracks it's moving on.
And this is important, because by doing this
we can learn about, again, the biophysical and the molecular mechanisms
of how things move around in the cell,
and this is what makes your cells work.
So, we are learning about the fundamental mechanisms
of biology.
OK, so, before I finish, I want to show you
an animation, this is a computer animation,
which was made at Harvard University.
And it shows how organelles move in the cell
along these tracks, along these highways.
This was made based on scientific data,
and our interpretation of that data,
and you can see that it's quite spectacular, right?
It looks like a futuristic movie.
And it has a lot of detail,
but, of course, it's just a computer animation,
and this is what we think is going on.
And our dream is, one day to capture these processes in as much detail
as you can see in this computer animation.
And I hope I was able to show you
that we are getting closer and closer to that dream.
And so we managed in the last decade
to improve the resolution of the fluorescence microscope
by an order of magnitude.
And now we can really, for the first time, map the trajectories of these organelles
to the tracks in which they're moving on.
So, we're getting very close to this animation.
We are not quite there yet,
but with physicists, chemists and biologists working together
to develop the next generation of fluorescent labels,
the next generation of lasers and cameras,
then I really believe that we will be able to get data like this
from our fluorescent microscope
and we will not need to make computer animations anymore.
Thank you.
(Applause)