transcript protein tagging technologies in cell …...molecular biology of the cell, and traffic....
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Protein Tagging Technologies in Cell Imaging and Analysis
[0:00:00] Sean Sanders: Hello and welcome to the Science/AAAS live webinar. My name is
Sean Sanders and I’m the commercial editor at Science. Slide 1 The subject of today’s webinar is, “Protein Tagging Technologies in
Cell Imaging and Analysis”. There currently exist a number of approaches to indirectly monitor the expression, localization, and degradation of cellular proteins in fixed cells and cell lysates. However, tools to study these events in living cells in real time are more limited. In this presentation, we will examine the current ‐‐ the application of current fluorescent protein tagging technologies as well as a variety of complementary cell imaging approaches including several chemical labeling techniques.
In the studio today, I’m joined by three exceptional scientists to
discuss this subject. Sitting next to me is Dr. Jennifer Lippincott‐Schwartz from the NIH, just up the road from us in Bethesda, Maryland. Next, we have Professor Kai Johnsson from the Swiss Federal Institute for Technology in Switzerland. And finally, we have Dr. Klaus Hahn from the University of North Carolina in Chapel Hill.
Welcome to all of you. Before we begin, I’d like to remind everyone watching: If you wish
to see an enlarged version of any of the slides, you can click on the enlarge slides button located just underneath the slide window of your web console. You can also download a PDF copy of all of the slides by using the download slides button. If you’re joining us live, you can submit a question to the panel at any time simply by typing it into the ask‐a‐question box on the bottom left of your viewing console below the video screen and clicking the submit button. I’ll do my best to get to as many of the questions as possible. Keeping them short and to the point will give you the best chance of them being put to the panel. We frequently receive over a hundred questions during these webinars so please do not take it personally if we don’t manage to answer your specific query.
Finally, I’d like to thank New England BioLabs for their sponsorship
of today’s webinar. Slide 2
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It now gives me great pleasure to introduce our first speaker today. Dr. Jennifer Lippincott‐Schwartz received her Master's in biology from Stanford University and her Ph.D. from Johns Hopkins University. After doing postdoctoral work in the laboratory of Richard Klausner at the National Institutes of Health in Bethesda, she established her own lab on the same campus. Dr. Lippincott‐Schwartz is currently Chief of the Section on Organelle Biology in the Cell Biology and Metabolism Branch at the NIH where she uses live cell imaging approaches to analyze the spatiotemporal behavior and dynamic interactions of molecules in cells. Dr. Lippincott‐Schwartz serves as editor for Current Protocols in Cell Biology and The Journal of Cell Science, and is on the editorial boards of Cell, Molecular Biology of the Cell, and Traffic. She was elected to the National Academy of Sciences in 2008.
Welcome, Dr. Lippincott‐Schwartz. Dr. J. Lippincott‐Schwartz: Thank you very much, Sean. Slide 3 So, today, I’m going to be talking about the development and use of
fluorescent proteins as imaging tools. And these fluorescent proteins including GFP have really revolutionized biomedical sciences since they can be expressed within cells or organisms like this mouse simply by adding small quantities of DNA, and they still are fluorescent under those conditions. This has revolutionized the biomedical sciences because it allows proteins to be tracked and imaged in various physiological contexts.
Slide 4 Now, this next slide shows the advantages of the fluorescent
proteins. Because the cDNA for these fluorescent proteins can be tagged to different proteins of interest, you can directly insert them into the cells or organisms. And this allows for non‐invasive imaging in the absence of photodynamic toxicity because the GFP really has minimal toxicity when it’s expressed in cells. And the GFP and its variants can be also used to monitor biological events and signals based on their interaction with each other.
Slide 5 Now, as you might imagine given the significance of these types of
probes, they’ve undergone significant development over the last 15 years as shown in this timeline for the development of fluorescent proteins. This includes the development of different color variants, brighter versions of these fluorescent proteins, as well as photoactivatable fluorescent proteins.
Slide 6
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Now, this is just a diagram showing the different color variants that are available now among these fluorescent proteins. And this allows researchers to be able to perform multicolor simultaneous imaging within their specimens, which allows for really characterization of different ‐‐ how different proteins behave under different contexts.
[0:05:02] Slide 7 This is a list of some of the brightest versions of these fluorescent
proteins in each spectral class, in case you’re interested in finding out what the latest and greatest for each of these proteins are. And that allows for specific double labeling as well as FRET based interactions.
Slide 8 Slide 9 What I want to focus now on for the rest of this little talk is these
photoactivatable green fluorescent proteins, which are invisible at the imaging wavelength, in this case 48 nanometer light, until they’ve been activated by a UV pulse of 400 nanometer light. After which, they become brightly fluorescent.
Now, this has allowed for many new applications by these
photoactivatable fluorescent proteins because you can switch them on. You can highlight them.
Slide 10 Now, there are many variants of these photoactivatable or
photoconvertible proteins and some of them are listed in this slide. Of these, the two most useful for double labeling are the photoactivatable GFP and the PAmCherry. And the reason is because these two different photoactivatable fluorescent proteins can be switched on simultaneously by UV activation as shown in this sequence here where both molecules have been expressed in the same cell. And with one pulse of 405 nanometer light, you can switch on these molecules. In this case, they’re being switched on in the nucleus. And you can see those molecules then diffuse out of the nucleus into the rest of the cell.
Slide 11 There are many applications that one can use for these
photoactivatable fluorescent proteins, including studies of dynamics where you switch on a population and watch how molecules move out of a particular area of the cell. You can look at protein turnover with these probes because after you photoactivate an image, the photoactivated molecules, any newly synthesized molecules will not be fluorescent unless you photoactivate them. So, you can look at
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protein turnover. You can also look at fate mapping, the temporal and developmental expression patterns in different organisms.
Slide 12 But perhaps the most exciting application of these photoactivatable
fluorescent proteins now is in super resolution imaging. Slide 13 Well, what is super resolution imaging? It’s imaging beyond the
diffraction limit, which is illustrated in this next slide here. Where if one’s looking at a single molecule of GFP, which is about 2.5 nanometers in size through a typical light microscope, you wouldn’t see the GFP, but you’d see a blurry spot about a hundred times the size of that GFP. And that’s due to the diffraction limit of light, which makes any fluorescent probe a blurry object if you’re looking at a single molecule.
Slide 14 It turns out that that point‐spread function or blurry spot can be fit
to a 2D Gaussian least squares fit to find the center or the centroid of this point‐spread‐function. And that then allows you to define with much more accuracy where the molecule is.
Slide 15 And that’s been the basis for a new super resolution imaging
technique that is we call Photoactivated Localization Microscopy or PALM. And in this technique, one takes a sample, in this case a fixed sample that’s expressing a photoactivatable fluorescent protein. And you expose it to very low photoactivated light so that you switch on only a small subset of the molecules in a dense population as shown in this top slide here.
Slide 16 Slide 17 And after highlighting just a few of the molecules in your dense
specimen by switching them on, you fit them. You can fit the point‐spread functions and then you can bleach those molecules and switch on another subset in this dense population. Capture the distribution of those molecules, fit them, and then do this over again and over again until you’ve essentially acquired the distribution of all the molecules in this dense population.
Slide 18 And by summing up the position probability Gaussian fits for each
of the individual photoactivation events, you can then get a super resolution image.
Slide 19 And this is just an resolution of that. This is an aggregate of 50‐
nanometer polystyrene beads coated with the photoactivatable
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fluorescent protein Kaede. To the left is the conventional TIRF image of this aggregate. To the right is the PALM image.
Slide 20 And if we zoom up, you can see we can identify the individual
distribution of these 50‐nanometer elements in this aggregate. Slide 21 Slide 22 Now, you can do PALM in living cells simply by fixing these cells,
putting them on a cover slip. We’re TIRF imaging the very bottom of this cell an when we do that ‐‐ in this case we’re looking at a focal adhesion tag that’s been labeled with vinculin tagged with this tandem‐dimer Eos ‐‐ you can see a really beautiful resolution.
[0:10:15] Slide 23 If we zoom up on one of those focal adhesions as shown in this
slide, you can see the distribution of the individual vinculin molecules.
Slide 24 Now, you can do two‐color PALM with the photoactivatable Cherry
in combination with a photoactivatable GFP. And an illustration of that is shown here where we’re looking to the left a transferrin receptor tagged with a PAmCherry, to the right with the Clathrin light chain, which labels Clathrin coded pits. We can see the super resolution co‐distribution of those molecules.
Slide 25 – Slide 28 Now, to look at intracellular components using PALM, one only has
to essentially thin section through your fixed specimen. Put that thin section, in this case a 70‐nanometer thin section, on a cover slip and then image.
Slide 29 And here is an example where we’re looking at an Eos tagged to a
mitochondrial targeting marker where you can see the distribution of the molecules within mitochondria.
Slide 30 Now, it turns out that you can do PALM in 3D using an
interferometric approach developed by Harald Hess recently at Janelia Farm. And in this approach, you can look at the Z distribution over a depth of about 250 nanometers.
Slide 31 Here, we’re looking in Z at the distribution of a plasma membrane
marker. And if you ‐‐ each of the molecules are color coded so that you can look at their Z dimension.
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If you rotate that plasma membrane image to the left, and look at it at the bottom, you can now see the top and the bottom of the cell membrane and the distribution of those molecules in them.
Slide 32 And this is just another example of an iPALM image of this ‐‐ a beta
integrin, which labels focal adhesions. And what’s exciting about this image is that we can see the distribution of this integrin throughout the whole secretory pathway. And how that pathway including its final distribution and focal adhesions are distributed in the three dimensions.
Slide 33 So, there are many exciting directions available to us now with
these photoactivatable fluorescent proteins. I mentioned the possibility of doing correlative EM analysis. I didn’t have time to talk about live cell analysis, but you can ‐‐ PALM is now live. You can use this technique in living cells. And this 3D approach, I think, is going to be very powerful.
Slide 34 And I just want to end by thanking the collaborative group that has
been involved in all of this technology. Eric Betzig and Harald Hess were the physicists that really came up with the idea for PALM. The biologists have helped implement it. And I want to thank my colleagues George Patterson and Suliana Manley at NIH as well as Mike Davidson and Vlad Verkhusha at Florida State and Einstein for their help in the development of these probes.
Sean Sanders: Great. Dr. J. Lippincott‐Schwartz: Thank you. Slide 35 Sean Sanders: Thank you so much, Dr. Lippincott‐Schwartz. It’s a great
introduction. I know there’s a lot more than you had time to cover so I appreciate it.
We do have a lot to get to today, but I’m going to throw out a
question to you very quickly that came in about GFP. Basically, it’s clear now the GFP molecules are fairly large. Could there possibly be steric hindrance issues? And what examples are you aware of where the size has interfered with the use of the tags, and what would you recommend be done in that case?
Dr. J. Lippincott‐Schwartz: Yeah, that’s a great question. So, the GFP is a 27 kD protein. But
because it folds up into a very compact beta‐barrel like structure, it
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has been remarkably useful for tagging to the N‐ or C‐terminus of proteins without really fundamentally interfering with the activity of many of these proteins. But, as you know, many proteins assemble into polymers and those polymers are tightly organized where the proteins are fitting very closely with each other. And under these conditions, we’ve found that if GFP has been inserted into the individual subunits of this polymer at too high a density, essentially the polymer it won’t assemble correctly.
And so, the way one can deal with this is to essentially just sprinkle
in at small levels the GFP tagged polymer subunits. So, that it’s not fully integrated into the polymer and thereby disruptive.
Sean Sanders: Great. Thank you very much. Slide 36 So, on to our second speaker today, Professor Kai Johnsson. Dr. Kai
Johnsson received his undergraduate diploma in chemistry and his Ph.D. from ETH in Zürich, Switzerland. Following his postdoctoral training at the University of California, Berkeley, Dr Johnsson worked as a research assistant at the Ruhr‐University‐Bochum in Germany before returning to Switzerland to take an assistant professorship position at the Institute of Chemical Sciences and Engineering with EPFL. He is currently an Associate Professor at EPFL, researching the development and application of tools to study protein function in vivo and in vitro, as well as the directed evolution of protein function. Dr Johnsson is associate editor of ACS Chemical Biology and a member of the Faculty of 1000.
[0:15:24] Welcome, Dr. Johnsson. Thank you. Slide 37 Dr. Kai Johnsson: Thank you very much. What I would like to talk about today is also an approach to study
protein function and lysates, but that is actually not based on autofluorescent proteins. And so, what we are interested on doing in my lab is using the following approach if we would like to study a protein of interest in a cell. We also express it as a fusion protein with a polypeptide. But now the role of this polypeptide is not to be fluorescent by itself, but rather to react with a synthetic probe in a way that this probe becomes covalently and irreversibly attached to your fusion protein, and thereby giving it a unique property such as fluorescence.
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And so, if you do something like this, what are the principal advantages of this approach? First of all, you can provide proteins with properties that cannot be genetically encoded, that is, unnatural properties. Second, you as a user, have temporal and spatial control over when you do the labeling. And thirdly, since these tags can be labeled with a lot of different synthetic probes, you can use a single construct for a lot of different applications.
Slide 38 Now on the next slide, I’ll show you two of the commonly most
popular approaches for protein labeling. The first one is the so‐called tetracysteine tag, which was developed by the lab of Roger Tsien ‐‐ which is a peptide that in the presence of simple dithiols chelates to biarsenical derivatives such as this fluorescein derivative called FlAsH forming a stable fluorescent complex. The unique features of this approach are the relatively smallest mass size of the peptide that you attach to your protein of interest.
And another tech that my laboratory developed for protein labeling
is the so called SNAP‐tag, which is a small protein that specifically reacts with benzylguanine derivatives carrying a synthetic probe or here described as a label. Thereby transferring the label to the fusion protein and covalently attaching it. The unique features of this approach are its explicit specificity and also the large varieties of labels or synthetic probes that you can attach to it. My laboratory alone has synthesized over 100 benzylguanine derivatives.
So, what I would like to do in the following is to give you an
overview about the things that you can do with this labeling approaches that complement more traditional approaches to study protein function.
If you’re interested in the field in general, I also at the end of my
presentation listed a couple of general reviews on this field. I should also disclose, at this point, that I’m co‐founder of a biotech
company that licensed these protein‐labeling technologies to New England BioLabs.
Slide 39 So, a few more words on the SNAP‐tag. The SNAP‐tag is a protein of
about 20 kD. It’s a small monomeric protein that, as I already said, reacts very rapidly with benzylguanine derivatives in a way that then the synthetic probes attach to your protein. The rate is very fast of this labeling, but what is most important for labeling applications is that independent of the sort of benzylguanine
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derivatives that you synthesize, the SNAP‐tag still can react with it. So, you can attach fluorophores, probes for affinity, purification, even beads for pull‐down assays.
Slide 40 So, how do you do such an experiment? Let’s assume you would
like to do a fluorescence labeling such as SNAP‐tag fusion protein. The first step, of course, is that you need to transfect the cells that they express the protein of interest. And then you just pipe it in a benzylguanine derivative into the cell medium that carries an appropriate fluorophore. And then after some incubation time, 10 minutes or so, you need to, through a washing step, remove excess molecule that hasn’t reacted. And then, on the third step, you go to the x‐ray imaging for example.
Slide 41 And here on this slide, I’ve shown two applications of such
fluorescence live cell imaging of SNAP‐tag fusions; to the left, the SNAP‐actin and to the right the SNAP‐β‐tubulin both labeled with tetramethylrhodamine.
What I would like to do now is not sort of show you examples
where in principle we imitate autofluorescent proteins. But I’d like to discuss some of the things that you can do where you really complement autofluorescent proteins and can do things that would not be possible otherwise.
So, for these applications, what is important again is that we can
label a single construct with multiple fluorophores that we, as the user, control when and where we label. And that you can use fluorophores that have properties that cannot be found in autofluorescent proteins.
Slide 42 So, the first application that is what we call pulse‐chase labeling. It’s
where you label a protein at different time points with different fluorophores. And this is important because it allows you to differentiate between different generations of this protein.
Slide 43 To make this more clear, I’d like to work you through an experiment
that came out of a collaboration with Nils Johnsson at the University of Ulm where we pulse‐chased a cell wall protein to the study the formation of a cell wall in budding yeasts. And so, the result of this experiment is already shown here on this slide. And so, the question is, how did we get this wonderful image.
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And so, the experiment is in the following where that if you have the yeast cell wall, which is a glucan with proteins covalently attached to it, that one of these proteins is attached and fluorescent labeled. Now, if after this labeling you let the yeast continue to grow, in part what will happen is that a new cell wall will be made and also new proteins attach to it and this growth will be localized to the tip of the bud.
Now, if you come with a second fluorophore and then do a labeling,
that you will only label in the second the step the fluorophore that was synthesized after the first labeling step. And so, just by the colors, you differentiate old from new protein and you follow the formation of the structure.
[0:20:32] Slide 44 You can continue this pulse‐chase labeling experiments as long as
you have fluorophores that can be differentiated in your fluorescence microscope, then again leading here to this nice image that you can see. And it captures in essence the essence of all these pulse‐chase experiments. Different colors for different generations of a fusion protein and then just looking at the pattern of the colors tells us something about the formation of this biological structure. This is an approach that is quite popular with SNAP‐tag fusion proteins.
Another work that I would like to mention was a really nice work by
Lars Jansen and the group of Don Cleveland in San Diego where they looked at when in the cell cycle of a mammalian centromere protein A is actually inserted into the centromere. Reference to this work as well as other pulse‐chase labeling applications you can find at the end of my presentation.
Slide 45 What I would like to do now is to also discuss an example, which is
important, that the fluorophores has properties that cannot be genetically encoded. And I would like to discuss a little bit with you work with that was done by the group of Jean‐Philippe Pin in Montpellier where they looked at the oligomerization of the of G‐protein coupled receptors. And they expressed G‐protein coupled receptors as SNAP‐tag fusions and labeled them with an europium cryptate coupled to benzylguanine.
Europium cryptates are particular fluorophores because they have
much longer lifetimes than normal fluorophore. So, if you excite such a fluorophore and then wait with coding of the emission some
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time, the fluorescence that come out from ‐‐ outer fluorescence of the cells has already decayed. And that significantly increases signal to noise. You can use these fluorophores then to build really nice FRET pairs, and, for example, look at protein‐protein interactions through FRET experiment. And this is what the group of Jean‐Philippe Pin did where they just looked at the oligomer extensions of a variety of different GPCRs.
Another interesting feature of this experiment actually is that in this
experiment, they only labeled the GPCRs that were functionally expressed on the cell’s surface. Whereas all those GPCRs that misfolded are stuck in the secretory pathway, they’re not visible in the experiment. And that’s also a feature that distinguishes this labeling approach from traditional approaches based on autofluorescent proteins.
Slide 46 And so, finally, you might ask what the future holds for us, what
kind of things can we do in the future. And one of the things that I think will become very important is that you cannot only label one protein, but then you can label multiple proteins at the same time.
And the first step in this direction was already taken by a very clever
post doc in my lab, Arnaud Gautier, who came up with the CLIP‐tag that can be labeled in the presence of a SNAP‐tag. And so, what you can do now is that you have two different proteins and simultaneously you can label them with different fluorophores. And that is very interesting for FRET experiments, but also simultaneous pulse‐chase experiments of different proteins at the same time.
Slide 47 And then, finally, one feature of these labeling approaches that I
would like to mention is that if you already have like a SNAP‐tag fusion protein and then in the future, someone comes up with a nice interesting probe. That you can profit from this future invention by simply using your old construct and label it with a new probe. For example, we try now, in my laboratory, to synthesize interesting fluorophores for caging of photoswitchable fluorophores. I mean, for obvious applications. And if this work is successful then you can also profit from this in the future.
So, what I was trying to tell you in the last minutes is that these
protein labeling approaches are a really nice complement to study protein function in live cells. And the main features are you have properties that cannot be found in genetically encoded tags as well as you can use one tag for a lot of different applications.
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Sean Sanders: Great. Thank you very much, Dr. Johnsson. Slide 48 ‐ Slide 51 And you have some additional slides here with some references ‐‐ Dr. Kai Johnsson: Yes. Sean Sanders: ‐‐ that people can download if they’re interested in looking ‐‐ Dr. Kai Johnsson: Yes, yes. Sean Sanders: ‐‐at some reviews. Slide 52 So, I’m going to throw a question over to you as well that has come
in both by email and online asking whether these technologies can be used to visualize fixed as well as live cells. And the other part of that question is can they be used in bacteria?
Dr. Kai Johnsson: Oh, okay, yes. So, I mean, the question first of fixed or live cells, and
that’s a very good question. The nice thing is if you label with a synthetic fluorophores, the emission or excitation properties of this fluorophore do not depend on the falling of the protein anymore. So, if you label a SNAP‐tag fusion protein and fix it, it remains fluorescent. And so, you can label ‐‐ you can image fixed cells and you can actually also ‐‐ since the SNAP‐tag is hard to kill, you can label after the fixation.
And that is interesting because then you can also look in [0:25:02]
by fluorescent scanning for like expression levels of proteins very conveniently.
[0:25:08] And the second question, can we label in bacteria? To keep it short,
the answer is yes. Sean Sanders: Okay. Great. Maybe I can throw it to Dr. Lippincott‐Schwartz, the techniques that
you’ve looked at that can be used in fixed and live cells? Dr. J. Lippincott‐Schwartz: Oh, absolutely. And in bacteria. Sean Sanders: And in bacteria. Excellent. Slide 53
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Great, well, our final speaker today is Dr. Klaus Hahn. Dr. Hahn earned his Ph.D. in chemistry from the University of Virginia, followed by postdoctoral work in the Center for Fluorescence Research at Carnegie Mellon University. He was an assistant professor and associate professor at the Scripps Research Institute before becoming a professor of pharmacology at the University of North Carolina, Chapel Hill in 2005. His work currently focuses on developing new tools to address the spatiotemporal regulation of signaling networks.
Welcome, Dr. Hahn. Thank you for being here. Dr. Klaus Hahn: Thanks a lot for the opportunity to show up here. Slide 54 I thought today it might be most helpful to give you a broad
overview of some of the elements of biosensor design assuming that you’re going to try to be making some of these yourself. And then at the end, highlight more recent applications and unusual applications in a number of areas.
Slide 55 So, let me leap right in with this sort of an early example that we
can use as a prototype. So, this is a sensor for a protein conformational change. It could also be for posttranslational modification. And you see here Rac, in gray, has two different conformations. But I’ve highlighted there in blue a very key portion of any biosensor of this type, that’s the recognition element.
So, you need to find out of a naturally occurring protein or some
other source, a molecule that binds specifically to the active conformation of your target. You can link it to the target via this dotted line here, the optional linker or not and we’ll discuss that. And then, you would employ a variety of different available readouts in by far the great majority of the case is FRET, but now there are a lot of other alternatives open to you.
Slide 56 So, here’s a more generic version. I’m going to hit each of these
elements and then talk a little bit the linker, the recognition element itself and not so much about these readouts primarily FRET and FLIM. But more recently now, bimolecular fluorescence complementation has become extremely useful.
Slide 57 So, if you look at the linker itself first, the single molecule
biosensors are by far the most popular now. But this slide highlights
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the fact that I believe that bimolecular versions are going to make a comeback.
And I’ve done a little contrast here between the two. So, if you look
at the single gene types, for example this Rho A sensor, they’re obviously going to be the easiest to use for animal studies. You want to have multiple genes that have to be expressed in the right relative proportions. They’re far easier to image because you don’t have differences in the distribution of the components that you have to correct for. But the main Achilles heel is that they’re far harder to make because of this all‐important linker.
You’ll find often that if you try to take an affinity reagent that
you’ve found, harness it to your target protein, that you have to do a great deal of engineering to move into the range of FRET changes that are useful to you. And that’s highlighted by this dynamic range column. Because in the single gene, you have your affinity reagents attached to the target so it’s never fully separated. And even in the off state, they’re a significant threat. So, you may have a bright signal, but the extent of change will never be as great as in the bottom case where the affinity reagent is separated from the target.
And you can see that in this particular example of the Rac sensor
that gives actually a much greater than 18:1 difference. These are much easier to make because you have flexibility in where you put the fluorescent proteins so you don’t have to deal with the linker. But again, they’re harder to image. It requires a more in‐depth knowledge of image processing and more caution in interpretation of your results.
Slide 58 What I wanted to highlight now are some of the aspects of this that
are involved in multiplexing. So, if you want to put multiple probes in the same cell. And it’s also true if you’re just trying to not look at protein activity, but look at simple markers and watch the movements of proteins.
On the left, you see the FRET type of sensor I’ve shown you before.
On the right is a recent one that we’ve been employing a lot, an example of another technology that is far less perturbing. Notice that the protein itself now is not tagged with any sort of fluorophore. Instead, you take the affinity reagent and you attach on to it a dye that’s very bright, long wavelength for cells, and is sensitive to environment. So, now, when that affinity reagent binds
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the endogenous protein target, you see a big color change, a shift in wavelength and intensity.
So, these types of probes are less perturbing not only because you
don’t tag the target, but because you’re directly exciting a dye instead of indirectly via FRET.
Slide 59 So, we’ve found and here are some specific examples. I really don’t
have that much time. But I just wanted to point out some of the challenges and interesting aspects. So, this is one of the examples of the dyes, which are bright for live cells; quantum yield 0.8, epsilon greater than 200,000. And there’s an interesting engineering challenge in each probe as you decide where to place this dye and how to orient it so that changes in exposure to water or interactions with the target protein affect its spectrum.
[0:30:08] Slide 60 Here are some of the new directions that, I think, will really widen
the number of biosensors that are available to people. There are a lot of molecules that people would like to study, but relatively few biosensors as is illustrated in the upper left‐hand corner. And that’s primarily because it’s very difficult often to find one of these recognition elements for your particular target. Even if you’ve found it, it may be difficult to engineer it such that it will reflect conformation ‐‐ you can put the fluorescent protein in the right place or attach the dye.
So, we and other groups are now working on an area that I hope
will soon have a lot of impact where you use artificial scaffolds, for example, peptides, where you can find the one that binds your target via peptide screening, or proteinaceous scaffolds that are designed to bind your targets where most of the scaffold remains constant. But there’s a small variable region shown here in red and blue. And you can do Phage display or other screening technologies to pull out the one scaffold version that binds your target. And then all the other steps are taken care of because the structure remains constant. You can immediately add your fluorescent proteins or dyes and turn it into a sensor.
Slide 61 Let me conclude then with an example of an application that’s dear
to our heart. We’re trying to understand these very rapid changes in these three Rho GTPases at the edges of moving cells. Those three work together to coordinate actin dynamics, each affecting actin.
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But moving in their position, in their site of localization with a timescale of seconds and a localization scale of microns.
So, if you try to do separate experiments investigating each GTPase
in a different study, there’s simply too much cell‐to‐cell variation. That’s a huge factor in live cell imaging of biosensors. And also, too little resolution in timescale to compare one experiment to another.
Slide 62 So now, there are fluorescent proteins that are available that allow
you to do FRET of two biosensors in the same cell. This and also technologies like I just showed you using dyes or the ones that Kai talked about where you can now label your probes in many different colors mean that, I think, soon we’ll all be looking at multiple activities simultaneously.
And I just wanted to point two things that I think are especially
important in that area. Number one is the sensitivity of the probe. Because as you add more and more probes to the cells the perturbation of the cells becomes a serious issue.
So, look then in the lower left‐hand corner and you’ll see an
example of one of our probes for Cdc42 when you have acceptable expression levels or an excess where the cells begin to round up and change morphology.
But there are much more subtle things that you might want to be
aware of. When we first used the RhoA biosensor for example, we thought it wasn’t working. There was no response. Until we noticed in the lower right‐hand panel there that this biosensor was all in the membrane. And that indicated to us that it was overwhelming the upstream regulators that maintain it in cytoplasm until it’s activated and moves in the membrane. So, by reducing the concentration in both these cases, we were able to find successful experiments.
On the left‐hand side, I’m basically trying to highlight what, I think,
is going to be a really important future direction. Those are the computational tools that are used to extract information from these images. I think that’s going to be absolutely essential to really understand biology here.
I mean including the beautiful image analysis that you just saw from
Dr. Lippincott‐Schwartz. That’s one aspect, which is understanding the image. The other is fitting it to biological models.
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So, the top example there shows multiplexing of two proteins, in the case macropinocytosis, where there are very clear localizations. If you compare the two proteins, you’ll have a flash of one as a vesicle closes, a flash of another as a ruffle forms, very easy to differentiate them.
But if you look in the bottom right‐hand corner at our studies of the
edge of a cell, you see extremely subtle, fine variations in activity moving throughout the cell in a seconds timescale. And only through new image analysis tools can we extract information. Definitely, not enough time in eight minutes to go into that. But I wanted to highlight it.
Slide 63 The last thing I wanted to say is the blurb about the webinar at least
stated that we should discuss other things you put on proteins. So, I wanted to mention that our group and others are working on, I think, an exciting area where you can not only visualize these proteins but manipulate their activity. So, with genetically encoded versions of proteins, you can irradiate your cells, turn your proteins, turn your proteins off in very precise locations and times. And that’s it.
Thanks. Sean Sanders: Great. Thank you Dr. Hahn, and to the other speakers for the
excellent presentations. So, I’m going to jump in with a question that we got in by email, to
you Dr. Hahn. How could tagging affect protein localization and behavior and what controls are used to determine this?
Slide 64 Dr. Klaus Hahn: You know, you’ve mentioned to me beforehand that that question
had come in and I had this slide so I put it up. Sean Sanders: Great. [0:34:57] Dr. Klaus Hahn: I think it’s an important question. In a nutshell, this is again
something that’ll be very different for each protein. I think you want to try to engineer your biosensor to be very careful with upstream signals because that’s what you’re trying to study; to not perturb the way your biosensor reflects upstream regulation. You can more easily damage, if you will, the downstream interactions if you have a sensitive sensor. So, you’re using just a tracer amount and not
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actually perturbing the bulk of your signaling protein and thereby altering downstream behavior. But you don’t want to alter the limited set of downstream interactions that actually produce localization.
Sean Sanders: Uh‐hum. Great. Thank you. Dr. Klaus Hahn: That’s it in a nutshell. Slide 65 Sean Sanders: Okay. Well, we’re going to essentially jump into the Q&A now. And I
appreciate everyone keeping to time so we have as much time as possible to get to some of the questions that have come in.
The first one I’m going to address to maybe you, Dr. Hahn, and Dr.
Lippincott‐Schwartz as well. Are there technologies that allow determination of the subcellular localization of activated GTPases or, I guess, any proteins in the cell? So, Dr. Hahn, maybe you can start off.
Dr. Klaus Hahn: Well, actually, you know, that’s been the focus of our lab from the
beginning, and we’ve tried to develop new sensors for each GTPase using a different technology. So, if you look at our papers, you’ll see several examples. This person is, I guess, particularly interested in that protein family.
There’s also the work of Dr. Matsuda in Japan who’s made some
really interesting sensors of different types and a person, Tim Gomez at the University of Wisconsin. So, just throwing out those three names there are a lot of interesting sensors for that family.
Sean Sanders: Okay. Dr. J. Lippincott‐Schwartz: So, my lab in collaboration with other people have looked at many
different GTPases tagged with GFP including, you know, Ras, Sar, Arf, and even dynamin. And what we’ve been able to do using live cell imaging approaches combined with photo bleaching is to look at the dynamics of these GTPases. For instance, their cycle of membrane binding and release, how rapid it is, what’s controlling it, how are affectors impacting that. And that’s something that you can easily do with these GFP chimeras. Because they’re being expressed in live cells and you can monitor their membrane and cytoplasmic associations and the timeframe of that.
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Dr. Klaus Hahn: I, perhaps, should add one thing. You know, if you’re talking about all these different versions of these sensors, there are sort of two broad classes. The ones that are based simply on localization where you take a downstream protein that binds to the active GTPase and watch it all accumulate in one place. And that’s very easy to do and useful when your target protein does that. These other more complex sensors are for gradients and things that are subtle where you don’t have this kind of an obvious localization.
Sean Sanders: Great. Okay, a question for Dr. Johnsson, specifically about the SNAP‐tags
and about SNAP‐tag specificity, and also diffusion of the SNAP‐tag and the CLIP‐tags. Can you talk a little bit about that?
Dr. Kai Johnsson: You mean the relative specificity of the two proteins to each other?
I mean… Sean Sanders: I think about the specificity of the tag for the protein that is ‐‐ Dr. Kai Johnsson: Oh, the substrate? Sean Sanders: The substrate. Dr. Kai Johnsson: Okay. So, yeah, I mean that’s an important question. The specificity
of the type of the substrate is very high. I mean, if you take these benzylguanine derivatives and incubate them with any other proteins, I mean, you can wait as long as you want. There will not be any other reaction. These molecules are essentially rocks and you’ll even need the active site of the SNAP‐tag too to activate and then convert and then to react to species and do the labeling. So, the specificity that’s ‐‐ as I tried to say in my presentation, this reaction is one of the key features or the unique features of this approach. And that makes it so useful, in my opinion.
Sean Sanders: Okay. And diffusion of the tags? Dr. Kai Johnsson: I guess, the question probably refers to diffusion of the substrate. Sean Sanders: Uh‐hum. Dr. Kai Johnsson: I mean, if you want to do a labeling experiment, you need to get the
substrate into the cell. And that then depends on ‐‐ in a way, it depends on the molecule that you attach to the benzylguanine.
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There are fluorophores, for example, that have very nice permeability and then other fluorophores that are impermeable. And this is actually an advantage also of the approach. That for example imagine you would like to label the subpopulation of a protein that’s only on the cell’s surface, but not already internalized or not yet secreted. If you take an impermeable dye, you only label what’s on the surface.
Sean Sanders: Uh‐hum. Dr. Kai Johnsson: And then you can also label coming in the second step and label
them, what’s still inside or already has been internalized. So, the permeability of the dye is something you have to think about, but you can also use it as an advantage depending on the question that you’re interested in.
Sean Sanders: Okay. Excellent. Next question, do you normally introduce linker sequences
between fluorescent protein and your protein of interest so that the large tag doesn’t interfere with protein function? This seems to be a common question. And what kind of length would be best for that and the question is also about the stability and the potential loss of the tags. So, who would like to start? Dr. Lippincott‐Schwartz?
Dr. J. Lippincott‐Schwartz: So, the way that you typically attach the GFP is to the N‐ or C‐
terminus of your protein of interest. And the beta‐barrel of the GFP, the two ‐‐ its N‐ and C‐terminus are really only sticking out a small amount from the beta‐barrel.
[0:40:10] Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: So, usually it makes a lot of sense if you’re going to make your
protein really function independently or keep its full function, is to put a linker. And typically, when we’re constructing our fusion proteins, put in a ten amino acid linker between typically, the C‐terminus of the protein of interest and GFP.
Sean Sanders: Okay. Dr. Klaus Hahn: I could add two notes to that. I mean, basically, we do the same
thing, try to keep the fluorescent protein away from your target.
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Dr. J. Lippincott‐Schwartz: Yeah. Dr. Klaus Hahn: There was one occasion where we made the linker long and it was a
problem because there was a nonspecific interaction between the fluorescent protein and the target. So, sometimes, you might want to try a shorter one if nothing is working.
Dr. J. Lippincott‐Schwartz: Yeah. Sean Sanders: Uh‐hum. Dr. Klaus Hahn: And the other cautionary note is I went to a meeting once with
biosensors and they showed a graph of linker space where they showed all the possible variations in the linker. And it was absolutely remarkable what a tiny little region actually worked. So, it’s probably the most critical element in biosensor design, I would say.
Sean Sanders: Okay. To come back to something you mentioned about fusing to
the N‐ or C‐terminus ‐‐ Dr. J. Lippincott‐Schwartz: Yes. Sean Sanders: Is there a preference? There are some questions that are coming,
which ones do I use, which one’s better? Dr. J. Lippincott‐Schwartz: Yeah. You pretty much have to look at individual proteins one by
one. If a protein has a key signaling element at the N‐ or C‐terminus or a key sorting element at the N‐ or C‐terminus, you definitely do not want to put the GFP at that end or else you’re likely to interfere with that.
So, just based on your protein, you put it on the N‐ or C‐terminus
where there’s least likely to be interference with a potential function. Now, if worst ‐‐ you know, worst case scenario, if you have a multi‐spanning transmembrane protein, you could put it into an intraloop region or in the case of a soluble protein, a region between specific domains, sometimes that works as well.
Again, it’s an area that you have to really just explore yourself. Sean Sanders: Okay.
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Dr. Kai Johnsson: Trial and error. Dr. J. Lippincott‐Schwartz: Yeah, trial and error. I mean, one thing is just that you could look in
the literature and see whether there’s been GFP constructs that have been made of comparable type proteins, and where have they successfully done it.
Sean Sanders: Okay. A question for you Dr. Johnsson, can SNAP tags be used to
differentiate monomeric protein from oligomeric protein? Dr. Kai Johnsson: Well, that depends on how you do the experiment. If you go back to
this work by Jean‐Philippe Pin, where they looked at the oligomerization of SNAP‐tag fusion proteins, what they did is they labeled the same proteins with a mixture of fluorophores so that they can do FRET experiments between sort of the same protein if you want. And thereby, you can actually assess the oligomeric status of the protein.
So, in principle, you can do this. And there advantage is again that if
you have such a self‐labeling protein tag that you can label multiple fluorophores that for example it can do FRET with itself. And so, in principle, yes, you can do that. Yeah.
Sean Sander: Okay. It’s ‐‐ sort of a related question has come in asking whether there is
a size limit to the target protein for any of ‐‐ that can be labeled by any of the techniques that you’ve described? Maybe, we’ll start at the end with Dr. Hahn.
Dr. Klaus Hahn: For the target protein? You know, we’ve used peptides as affinity
reagents with much larger fluorescent proteins on there. And, I think, you just have to think about the steric environment and the kD of the things that you’re trying to bring together.
In focal adhesions, for example, we’ve seen black holes in the
image, just dark spots where the biosensor can’t get in there. So, there a small affinity reagent maybe really useful. I think that’s a question that’s very protein specific and there’s no absolute limit.
Sean Sanders: Okay.
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Dr. J. Lippincott‐Schwartz: And we’ve tagged ubiquitin with GFP and gotten the GFP to then
target to the proteasome so… I mean, ubiquitin is a pretty small molecule and the consequence was targeting of the GFP to the proteasome and degradation. So, it was very useful.
Sean Sanders: Okay. Dr. Johnsson? Dr. Kai Johnsson: Well, yeah. No, I don’t ‐‐ I mean, in principle I think what we also
should pay attention to is not the only if we tag a protein with another protein that it affects the function. But we also have to keep the expression level into mind. I think that’s something that’s often not considered too much in these experiments.
Of course, when you express your protein interest as a fusion
protein, it will change the properties, but you also have to worry about the concentration at which you express this protein. In particular, if you’re looking at somewhat of a protein that is involved in signaling, there the concentration is very crucial. And so that’s maybe, as a note also, the user has to keep this in mind.
Sean Sanders: Okay. A question has come in for Dr. Lippincott‐Schwartz asking your
opinion on FlAsH. [0:45:03] Dr. J. Lippincott‐Schwartz: Oh… Sean Sanders: [Laughs] Dr. J. Lippincott‐Schwartz: So, we haven’t really used it extensively in my lab. But from what I
hear, you know, it’s been used in many different applications. Klaus, you may have some more ‐‐ a better?
Dr. Klaus Hahn: We haven’t used it ourselves either, but a lot of people I know have
used it successfully. And, you know, there are some good and bad things with all of these techniques and you hear rumors. I think, basically, you look at the literature. There are a lot of successful applications. To some extent, there was an initial issue with toxicity, I believe.
Dr. J. Lippincott‐Schwartz: With the arsenic.
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Dr. Klaus Hahn: But it certainly is being used. Sean Sanders: Uh‐hum. Talking about toxicity, I know you mentioned about GFP toxicity.
There have been some very specific questions that have come in saying, you know, I label my protein with GFP and then the cells die. You know, what’s going on? Is there known toxicity using this tag?
Dr. J. Lippincott‐Schwartz: Well, not I think ‐‐ at the expression levels that we’ve used, we
don’t see cell toxicity. And part of the reason is at least people are thinking is that the fluorophore is embedded within this beta‐barrel structure. And when it’s fluorescing, any free radicals that are generated as a consequence of the electrons being shuttled back in these different orbitals, is essentially quenched or shielded by the polypeptide of the protein itself. And that’s very different than, you know, fluorescein, you know, rhodamine where you don’t have that type of shielding and so you get free radicals that are spewed out all over the place.
Sean Sanders: Right. Dr. J. Lippincott‐Schwartz: And they’re much more damaging. Dr. Klaus Hahn: I mean, that gets back to the earlier question. When somebody
asked why the biosensor isn’t working, my first thought is it’s so over expressed that it’s either hurting the cells or altering the physiology.
Sean Sanders: Uh‐hum. Dr. Klaus Hahn: Or that the termini are affecting the physiological ‐‐ the behavior of
the protein. You can switch your fluorescent proteins to the other terminus as we said. A lot of times too, the biosensors are built so that you have the two fluorescent proteins on the outer ends to get the maximum distance change, and that’s often a problem. And there’s nothing wrong with putting them in the middle and looking at orientation changes because the orientation as well as the distance affects the fluorescence.
Sean Sanders: Okay. Dr. J. Lippincott‐Schwartz: But one point related to this. I think, there are different fluorescent
proteins that ‐‐ you know, that are different, they’re color shifted.
25
And so, originally, the blue fluorescent protein actually had a toxicity issue not necessarily related to anything about the fluorescent protein per se, but the fact that you had to image it with UV light.
Sean Sanders: Okay. Dr. J. Lippincott‐Schwartz: And it’s the UV exposure to these cells, which ultimately is making
them unhappy. And so, under those conditions, the recommendation would be to use the more red shifted fluorescent protein GFP, you know, YFP or RFP.
Sean Sanders: Okay. Dr. J. Lippincott‐Schwartz: Where you can ‐‐ you’re imaging with red shifted light, which is
much less damaging to the cell. Sean Sanders: Okay. Are you aware of any effects on protein folding? That the
application of the tag causes the protein not to fold properly or to fold at different kinetics?
Dr. J. Lippincott‐Schwartz: So, we, as well as Roger Tsien, made an observation with the
original EGFP and other green fluorescent protein variants where they can dimerize with very low affinity.
Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: And that, in fact, can have an effect in particular on the membrane
proteins causing them to become cross‐linked with each other. And you’ll get large aberrations in the way that the membranes are folding with these dimeric forms of these fluorescent proteins. And this is a particular problem with the red fluorescent proteins, which are tetramers.
Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: So, there’s been a big effort among the chemists who are modifying
these fluorescent proteins to monomerize them. And so, the monomeric variants have been gotten around this problem because they really have very little affinity performing dimmers.
Dr. Klaus Hahn: Another sort of ‐‐
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Dr. Kai Johnsson: I think ‐‐ Dr. Klaus Hahn: I’m sorry. Go ahead. Dr. Kai Johnsson: You can actually also ‐‐ I mean, that’s not in the mammalian cells.
But use this tag to solubilize proteins that by themselves often do not fold so well when you express them in E. coli. That’s actually also a nice application. Not necessarily GFP, but then there are also tags that keep your protein in solution and simplify, for example, the purification.
Sean Sanders: Great. Dr. Klaus Hahn: As long as ‐‐ there’s been an issue for years even before there was
GFP tagging is that certain probes for unknown reasons are autophagocytosed and you see a large accumulation of not tiny vesicles, which are trafficking vesicles but large ones that are fluorescent. And that is again very influenced by the linker.
So, a lot of times when we build probes, we’ll find that subtle
differences there will make that go away or appear. And that’s probably a function of protein degradation. A very important practical point that we run into all the time.
Sean Sanders: Uh‐hum. Right. Okay. There was a question that we received on drug discovery and
whether any of these technologies have been applied to drug discovery. Are you aware of that, any applications?
[0:50:06] Dr. Kai Johnsson: I guess, all experiments with GPCR very often are linked to drug
discovery. I mean, this is like the class of one of the drug targets. So, in principle, these tools are also related to drug discovery or assays based on them.
Dr. Klaus Hahn: High content screening is an important area. It’s been around for a
while now. Companies automating image analysis and even looking at signaling pathways where they trigger a signaling change you could never see to induce movement of a GFP tag material into the nucleus. And then, they read that out so…
Dr. J. Lippincott‐Schwartz: And will get ‐‐ certainly, affecting various drugs on that process.
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Dr. Klaus Hahn: That’s right. Dr. J. Lippincott‐Schwartz: Yeah. Dr. Klaus Hahn: As a drug screen. Yeah. Dr. J. Lippincott‐Schwartz: Yeah. There are many different large high throughput assays being
doing done with GFPs that have been put into various places within the cell. And then you look at how drugs impact that.
Sean Sanders: Okay. A question for Dr. Johnsson about the application of these
techniques for visualizing surface proteins, and I know you briefly mentioned that. Maybe you could ‐‐
Dr. Kai Johnsson: Yeah, I briefly mentioned it already. I mean, the point there is that if
you would like to visualize only a subpopulation of your protein, and that being like the protein that is expressed on the surface, what you can do is take in chemicals for the labeling that are not membrane permeable. And so, in the labeling step, you only can touch what’s present on the cell’s surface, but not what’s inside, either internalized or not yet secreted.
So, through taking advantage of the labeling step, you can actually
address only the subpopulation of a certain protein that’s just present on the cell surface.
Sean Sanders: Great. So, a couple of questions about the PALM technology for you Dr.
Lippincott‐Schwartz. PALM has its shortcomings according to the viewer, including the requirement of a sparse distribution of photoactivatable species for unambiguous imaging and difficulty in examining interactions deeper in cells. Could you talk a little bit about how these can be overcome?
Dr. J. Lippincott‐Schwartz: Sure. So, the first point about sparse distribution of molecules. In
fact, the whole goal of PALM is to get at the distribution of the individual molecules in a dense population. And perhaps the questioner doesn’t really understand the technology because you are taking a dense population of photoactivatable fluorescent proteins. But if you switch them on all at the same time, you could
28
not distinguish what molecule is what. Because the fluorescence would all overlap.
But because you have the ability with these photoactivatable
fluorescent proteins to use small amounts of photoactivatable light to switch on in a stochastic manner subgroups of a dense population, you then have the ability to spatially isolate into these individual molecules in a sequential photoactivation bleaching scheme that I mentioned. That can then be used to sort of stitch together the pattern of all of these molecules. And we’re talking, you know, hundreds of thousands of molecules that you can define at 20‐nanometer resolution how they’re positioned in your specimen.
Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: Now, the second part of that question, remind me again is…? Sean Sanders: How the ‐‐ examining the interactions deeper in cells. Dr. J. Lippincott‐Schwartz: Yeah. So, that ‐‐ we’re hoping that variations of this interferometric
PALM approach can be helpful. The other methods that other people have developed, in terms of using defocusing to get at deeper penetration. And it’s ‐‐ you know, we’re hoping that sometime down the road, that we could do something to photon to get deep into tissue to use this approach.
Sean Sanders: Uh‐hum. So, that actually brings me to another question about this.
It’s what type of equipment is needed to do this type of work? You know, can you do it with a regular confocal microscope?
Dr. J. Lippincott‐Schwartz: No, you can’t do it with a ‐‐ well you can’t, at this point, use a
confocal. But it’s a very, very simple setup. Essentially, you can use a brightfield microscope. We use a TIRF objective.
Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: And then you have lasers for activation and lasers for imaging that
then feed the fluorescent output into a very ‐‐ you know, an intensified EMCCD camera. And that’s really all you need. So, you can purchase these things for probably under $200,000 and put it together and you’ve got your PALM system.
Sean Sanders: Uh‐hum. Great.
29
Another question maybe to all of you about whether this has been
used or can be used in living animals. We’ve talked mostly about cells, bacteria.
Dr. J. Lippincott‐Schwartz: Yeah. Sean Sanders: Maybe, Dr. Hahn, we’ll start with you. Dr. Klaus Hahn: Well, you know, certainly you can look at GFP tagged proteins in
animals. There was a great picture of a mouse in your talk. I thought ‐‐ I liked that one.
[0:55:00] More recently, people have succeeded with FRET and that was
initially difficult. And with some of these biosensor studies, it was difficult because of the sensitivity, but improvement in the optics has helped a lot. And now, they’re doing a lot of work in animals like zebrafish that are transparent where you can do interesting work without autofluorescence background. So, certainly, for FPs and FRET it is possible to do it in animals.
Sean Sanders: Okay. Dr. Kai Johnsson: We have also tried to start with labeling experiments in mice in a
collaboration with another colleague. And then, there’s the group of TJ Turner. And the first results look really good, but I mean, that’s a battle. The more complex the sample becomes, the more complex the experiment.
Sean Sanders: Uh‐hum. Great. Dr. J. Lippincott‐Schwartz: The red fluorescent proteins, which have a deeper penetration
capability because of the longer wavelength for their imaging, really offer the best in terms of deep tissue imaging. And, I think, researchers are beginning to use these particular variants of GFP.
Dr. Kai Johnsson: It might be done also in the area where ‐‐ like the chemical layering
becomes important because then you can go to near infrared dyes. Dr. J. Lippincott‐Schwartz: Exactly, yes. Dr. Kai Johnsson: That have better tissue ‐‐
30
Dr. J. Lippincott‐Schwartz: Absolutely. Dr. Kai Johnsson: ‐‐ penetration and so… Dr. J. Lippincott‐Schwartz: Yeah, right. Dr. Klaus Hahn: And there are quantum dots and things that ‐‐ Dr. Kai Johnsson: Yeah, quantum dots. Dr. Klaus Hahn: ‐‐ have spectacular brightness. Dr. Klaus Hahn: Yeah. Dr. J. Lippincott‐Schwartz: Uh‐hum. Sean Sanders: Okay. So, we’re close to the end, but I’m going to try to squeeze in a
couple more questions. I’m going to give you one, Dr. Johnsson. Someone was asking about the type of applications that would benefit from the use of the blocking agents available for a SNAP‐tag approach.
Dr. Kai Johnsson: Oh, okay. This is in principle ‐‐ that’s in principle also a pulse‐chase
experiment where you come with a substrate that is not a fluorophores, and, sort of you block, turn to the dark state a certain population of your SNAP‐tag fusion proteins, and then at then at a later time point come as a fluorophore. And then to highlight in only this population. And that can be interesting also for looking at not only dynamic process or structure formation but also just the lifetime of single proteins, how fast they’re degraded as you see how the fluorescence then is disappearing for example.
Sean Sanders: Okay. Dr. Kai Johnsson: That will be an example. Sean Sanders: Dr. Lippincott‐Schwartz, a question about what are the most
commonly used fluors and the brightest versions. You did have a slide up, but they were asking about what ‐‐ are different versions used for different applications and are some better for particular applications?
Dr. J. Lippincott‐Schwartz: Yes. As I mentioned, if you’re doing ‐‐ if you are going to be going
into an organism or do deep tissue, the red shifted variants are
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definitely preferable. For doing double labeling, I think, the CFP and YFP are probably ‐‐ the variants are the most widely used because of their spectral separation.
Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: It’s very easy to ‐‐ they’re very easy to separate. The enhanced
version of these molecules, which have mutations that really shift the spectrum to a single absorption peak, has really made a big difference in terms of increasing the brightness of these molecules.
Sean Sanders: Uh‐hum. Dr. J. Lippincott‐Schwartz: That’s the S65T mutation that Roger Tsien discovered many years
ago. That variation and all of these molecules has made a big difference in terms of their usability.
Sean Sanders: Great. So, we’re almost out of time, but I’m going to throw out my favorite
final question and we’ll start with Dr. Hahn, which is, where you see the field going in the next say two to five years?
Dr. Klaus Hahn: Oh, you know, it depends. There are many fields we’ve discussed
here actually. One of the things, I think is most exciting is the spectacular work of following different populations of cells in animals where you can see that they behave as groups. But if you do a fixed immunofluorescence image of an animal, you don’t understand that many of their behaviors are coordinated almost as ‐‐ in each different type of cancer, there are specific differences in the way they move. I think also the extension to human diagnosis is going to be very exciting. That’s, I guess, enough excitement for one answer.
[Laughter] Sean Sanders: Dr. Johnsson? Dr. Kai Johnsson: Well, what I think is very exciting or can be exciting is ‐‐ that goes in
the direction of what Klaus Hahn is doing, that’ll certainly create sensors for small metabolites that we can actually quantify things in cells, are they gradients, what is the concentration of key metabolites. I mean, there’s so much more. And, I think, that’s an invitation for scientists too to look at this in detail.
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Sean Sanders: Great. Dr. J. Lippincott‐Schwartz: So, for us it’s the super‐resolution imaging capabilities that are now
possible using these photoactivatable and photoswitchable proteins. It’s really allowing us to get a nanoscopic outline of how various machines within cells are functioning. You know, you have tomographic images of these structures, but you really don’t know how proteins are associated with them. And these super‐resolution approaches, I think, for the first time are going to allow us to be able detail how different types of proteins are positioned in these nanoscopic machines.
[1:00:05] Sean Sanders: Excellent. Well, thank you all very much. Unfortunately, we’re out of times.
So, I would like to thank our wonderful speakers for being here today: Dr. Jennifer Lippincott‐Schwartz from NIH, Prof. Kai Johnsson from the Swiss Federal Institute for Technology, and Dr. Klaus Hahn from the University of North Carolina.
Thank you all for your fabulous questions. I’m sorry we didn’t get to
all of them. Please go to the URL at the bottom of your slide viewer now if you’d
like to learn a little bit more about the products related to this discussion. And look out for more webinars in the future from Science. Just go to www.sciencemag.org/webinar. We encourage you to share your thoughts as well with us. You can just use the email address up in your slide viewer right now, [email protected].
And thank you again to all our participants and to New England
BioLabs for their generous sponsorship of today’s educational seminar.
Thank you very much. [1:01:15] End of Audio