Optical Sectioning using Light Sheet Microscopy:
In Vivo Imaging with Astounding Resolution
Webinar
14 June 2012
[0:00:23] Slide 1 Sean Sanders: Hello everyone and welcome to this Science/AAAS webinar. I’m Sean Sanders, editor for custom publishing at Science. In this webinar, we’re taking a detailed look at a relatively new and exciting imaging modality known as light sheet microscopy or selective plane illumination microscopy also known as SPIM. This technique is an extremely powerful alternative to established fluorescence imaging techniques especially when it comes to 3D imaging deep within tissue or within whole live organisms. It is also fast, high resolution, and suitable for fragile samples since photo bleaching is minimal.
We are fortunate to have an extremely knowledgeable panel of experts with us today who will provide us with both interesting and beautiful data captured using this exciting new technology. It is my pleasure to introduce my studio guests, all of whom have travelled all the way from Germany to be with us today. First, we have Dr. Ernst Stelzer from Goethe University in Frankfurt. Next, we have Dr. Pavel Tomancak from the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden and finally we have Dr. Lars Hufnagel from the European Molecular Biology Laboratory in Heidelberg. A warm welcome to all of you. Thanks for being here. Dr. Ernst Stelzer: Thanks for having us. Dr. Pavel Tomancak: Thanks. Dr. Lars Hufnagel: Thanks.
Sean Sanders: Before we get started, we’re going to give you some important information for the audience. Note that you can resize or hide any of the windows in your viewing console. The widgets at the bottom of the console control what you see. Click on these to see the speaker
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Slide 2
Now, I'd like to introduce our first speaker, Dr. Ernst Stelzer. Dr. Stelzer studied physics as an undergraduate at the Goethe University in Frankfurt and completed his Ph.D. at the University of Heidelberg. He held various positions at the European Molecular Biology Laboratory for over 28 years before becoming a professor for Physical Biology at Goethe University. Dr. Stelzer’s interdisciplinary work has bridged the gaps between optical physics, instrumentation development, molecular cell biology, physical biology, and mathematics. His work has been integral in the development of light sheet fluorescence microscopy as well as a number of other microscopy devices, resulting in over 220 publications and about 20 patent applications. Dr. Stelzer’s research goal is to develop and apply instruments as well as specimen preparation techniques that allow for the efficient and high‐resolution observation and analysis of biological specimens. Welcome, Dr. Stelzer, and good to have you.
Slide 3
Dr. Ernst Stelzer: Thank you very much for the kind introduction, Sean. So what I will talk about is briefly you an introduction to light sheet based fluorescence microscopy and in particular, I want to make sure that you really understand why photo bleaching and phototoxicity are reduced and why this is really useful for three‐dimensional imaging.
Slide 4
Before I start, I really want to give credit to a number of people who have contributed to this talk so particularly Francesco Pampaloni, Daniel von Wangenheim, Christian Mattheyer from the current group of people in my lab and from the alumni in particular Philip Keller, Uros Krzic, Emanuel Reynaud, Klaus Greger, Jim Swoger, and also Jan Huisken.
Slide 5
Now we’ve been working on light sheet‐based fluorescence microscopy or light sheet microscopy for probably almost 20 years essentially directly. We worked on the physics; we built the instrumentation, hardware, and software. We applied the instruments in developmental biology, in cell biology, and also in biophysics.
Slide 6
The motivation has always been to make sure that we work with three‐dimensional specimens, that we are able to look at life, multiple processes as a function of time, and that we maintain the specimens on the conditions that are relevant. Then of course, we use fluorescence microscopy because it provides us spatially and temporally resolved information and we monitor several of those signals with a certain precision or resolution over a certain period of time. [0:05:17] Slide 7 Now the basis somehow for light sheet microscopy is that you don’t use a single lens as you do for epi or diode fluorescence microscopy, but you rather split it up and you use one lens for the illumination of the specimen and a second lens for the detection of the light. Slide 8 That is what we call an azimuthal or a kind of theta arrangement. Slide 9
The big advantage is that the light does not – let’s see, the illumination light actually passes of course through the entire specimen, but we are really restricting ourselves in the way that we collect the light and I’ll come back to that a little bit later.
So when we started with this, we called this a theta microscope and this is briefly sketched here. So at that time, we had a high NA illumination and a high NA detection system.
Slide 11 to Slide 13
That had the advantage that you only illuminated certain volume elements that you did not observe and on the other hand, you observed for all the elements that you never illuminated and essentially you take the product of the two points spread functions and that gives you a kind of isotropic resolution. Slide 14 We could demonstrate this. So at the bottom for example, you see images of small latex beads on the left‐hand side recorded with the confocal and then the right‐hand side with one of those confocal theta microscopes. You see quite nicely that that axial resolution has dramatically improved here in these cases and that could also be shown with biological specimens. Slide 15 to Slide 18 Now for the light sheet microscopy, we moved this whole concept a little bit further and we don’t use high NA illumination but rather low NA illumination. We not only illuminated a single point but rather an entire light sheet and that allows us actually to record millions of pixels in parallel.
Slide 19
This is just sketched again here in this simple drawing. So we just illuminated a small block within the specimen and as you can see, we only illuminated that part that we actually observe. So neither in front nor behind this light sheet do we excite any fluorophores. So we do not bleach those fluorophores and they do not contribute of course to the blurring of the whole system and of course, we do not introduce any phototoxicity in those areas.
The advantage of the light sheet can be seen quite easily. In a conventional microscope, you would illuminate the entire specimen and here we only illuminate that part that we actually observe and therefore you have an improvement or a reduction in phototoxicity or photo bleaching, which can be easily a factor of 300 or even more for optic specimens. Slide 20 to Slide 21
Then of course you can move the specimen through the light sheet or the light sheet through the specimen and then you can record stacks of images such as these. These are all recordings that were done by Daniel von Wangenheim in my group. You have a copepod in the upper left or a polycystic mouse kidney in the upper right. There’s a part of a zebrafish in the lower left and Arabidopsis in the lower right. You see that the images are really crisp. You really get the optical section that you want and I should also add that the recording is really fast. You can easily record these data sets with much, much less than a minute probably even just 10, 20 seconds. But the dynamic range is very, very high and you have a really good signal.
Slide 22 to Slide 23
Now the other thing, as I said, we really tried to maintain the specimens under conditions that resemble close to natural conditions so we keep them in these chambers. We try to also keep the temperature in these chambers.
Slide 24 to Slide 28
What we can also do due the way that the system is arranged and we may come back to that a little bit later is we can rotate the specimen. So we can not only record stack a long a single direction, but we can record it along multiple directions. That gives us kind of complementary views and you can fuse the data. Slide 29 This collection just shows you a number of those datasets where you see pictures from yeast in the upper panel down to pictures of medaka fish here recorded by Philip Keller, zebrafish. Also the drosophila dataset, the two nice datasets you see on the lower right side where a drosophila has been recorded a single direction and along multiple direction that was done by Jim Swoger.
Slide 30 to Slide 32
Now, we are currently using the system in cell biology, though really very briefly where we’re using it mainly for three‐dimensional cell biology for example to look at cellular spheroids, which you can look at very nicely with light sheet microscopes and you can really get the full view of those relatively large objects. [0:10:02] Slide 33
We’ve worked a lot on developmental biology. That’s something you will hear much more about by my colleagues here in a few minutes.
Slide 34
What we’re trying to push now is plant biology because that’s just really an area where not so much microscopy has been done.
Slide 35
These are datasets that were recorded by Daniel von Wangenheim in my group and you really see quite nicely the lateral root growth in Arabidopsis. You may also notice that this is a very long recording, it’s about 75 hours, but we can keep the microscope stable over that period.
Slide 36
We also illuminate the specimen I should say so we’re really try to keep 16 over hours day‐night cycle here in this case and you can really see with very, very great precision how the lateral root actually grows. Here in this case, you really see minute changes here in the positioning of for example the different cells. Slide 37 Okay. What do these instruments look like? There have been many different implementations. Slide 38 to Slide 39
This is one that we call the digital scanning light sheet microscope because we create the light sheet not with a simple cylindrical lens but rather by scanning the system. Here’s one where you really see the basic ideas. You see the camera at the back and then the chamber here on the front, front right side. You also see that it’s completely open and that is why we can actually illuminate the specimen for example here with the plants or we can also introduce micromanipulation technology. Slide 40 The chambers can be made of different sizes. You can use different lenses and so on. You may notice there’s nothing to adjust in these systems. Really, in a certain sense, they are adjustment free, which of course really facilitates biological research. Slide 41 to Slide 44 Then of course, you can think about other designs, illuminating from two sides or observing and illuminating along multiple directions.
That is also something that we always had on our mind and it doesn’t have to be symmetric. Depending on the kind of questions, you can also think about completely asymmetric systems for that. Slide 47 With this, I want to thank you and I’d like to hand over to the next person. Sean Sanders: Great. Thank you very much, Dr. Stelzer. Slide 48 to Slide 49 Our second speaker for today is Dr. Pavel Tomancak. Dr. Tomancak did his undergraduate studies in the Czech Republic before completing his Ph.D. in developmental biology at the European Molecular Biology Laboratory in Heidelberg, Germany. He conducted his postdoctoral work at the University of California, Berkeley and he is currently a research group leader at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, Germany. Dr. Tomancak's laboratory is using genomics approaches to investigate the role of tissue specific gene expression regulation in development and evolution of Drosophila embryos. His laboratory has developed molecular, imaging, and image analysis approaches to describe the dynamic patterns of gene expression during development with high resolution in space and time, making use of SPIM technology as a cornerstone of their research. Welcome, Dr. Tomancak.
Dr. Pavel Tomancak: Thank you very much, Sean. So what I would like to discuss here is the impact that SPIM technology might have on developmental biology.
Slide 50
As a development biologist, what I’m interested in how the information, which is contained in the genome, is transformed into the spectacular cellular behavior, which constitutes animal development. In this case, we are looking Drosophila development and we can make a very convincing argument that the most direct manifestation of the program, which is written in the genome, is the tissue‐specific regulation of gene expression.
Slide 51
So by describing when and where genes are active in development, we come a long way towards understanding this information transfer.
Slide 52
We have a very nice technique, which allows us to universally just having the genome sequence available make a probe for any particular gene in the genome, mix the probe with the specimen, and visualize where and when a gene expressed.
Slide 53 to Slide 54
We document this by collecting a lot of images, which describe various aspects of the pattern and we put those images in databases, which describe also how does a pattern develop across time as you look left to right. We corroborate these measurements by independent techniques such as micro arrays and we describe what we see in the imaging using a controlled vocabulary annotation making statements about the patterns, which can be used for computational analysis.
Slide 55
Now this in Drosophila has been done on a quite large scale. Of the 14,000 genes in the genome, we have expression patterns for about half of them in the embryo and we also have a lot of data about other developmental active tissues such as imaginal disc or the ovaries. What all these datasets have in common is that they are looking at fixed dead specimen, which are inherently three‐ dimensional.
Slide 56
So, what we would really like to do in the future is to be able to describe them in their three‐dimensional, let’s say, beauty and also to be able to look at the dynamics, how they develop. And to be able to combine these various ways of describing the pattern into a better understanding of what impact the tissue specific regulation of gene expression has on development. [0:15:15] Slide 57 We think that SPIM technology is an ideal method to visualize large specimen in a live setting. The principle has been described before. What I will be showing to you are examples of specimen, which have been imaged using the size prototype of SPIM. What is very important to note here that for imaging of large specimen, in SPIM the specimen is mounted in a rigid medium such agarose. It is placed in front of the lens and it can be rotated so that one can acquire the specimen from different angles and cover even the largest of samples.
Slide 58
I’ll show you some examples of what can be imaged with SPIM. So on top, you see the imaging of the entire larva of Drosophila. In the middle part, there is ovario [0:16:03] [Phonetic] which is the process how the oocyte is being formed and on the bottom part you have the entire C. elegans worm where we zoom in a four‐cell stage C elegans embryo.
Slide 59
But one can image in very much large specimens such as the entire mouse embryo or as Ernst has shown us spectacularly SPIM is very good for live imaging of zebrafish development.
Slide 60
The imaging is not limited only to a model organism. A postdoc in my lab is using the technology to study the morphogenesis of the various appendages on a crustacean body plan and he is using live imaging to follow the fate and the movements of the cells to explain how it comes that the different appendages arrive at a different shape and specialization.
Slide 61
Now in order to get this kind of full three‐dimensional reconstruction of the specimen, in SPIM it is important to solve a problem that we are imaging the same specimen from different angles. We are collecting large three‐dimensional image data. The signal is degrading along both illumination and detection axis and in order to put this data together, these large image segs have to be registered. Importantly, the specimen is also changing. Slide 62 So we have some elegant solution to this problem using the fact that the specimen is embedded in the rigid medium, we add subresolution of fluorescent beads around the specimen and we use them as the fiduciary markers to achieve the registration. It goes very simply. We find the beads in the different views. We establish which of the beads between the different views are the same and then we minimize the displacement of the beads, which are the same.
Slide 63
This can be visualized on the following video. What you are looking at here is a Drosophila embryo, which has been imaged from 18
different angles. The beads are colored according to how much they are displaced. At the beginning, they were maximally displaced. The displaced, they were completely red. Now, the optimization is bringing the corresponding beads together and importantly this will work regardless of what the specimen is inside. In this case, it is Drosophila, but it will work on any kind of specimen.
Slide 64
Now very important thing is that we have brought this solution to an open source, a platform, which is called Fiji. But this program can be used by the biology community even now for reconstructing multi‐ angle data such as SPIM and it’s also open to further improvement when new algorithms will become available. Slide 65 Now, in terms of imaging, what SPIM gives us for Drosophila is the ability to really cover the entire specimen with isotropic resolution. If you image the Drosophila embryo from a single angle, you will see that your latero and axio resolutions are quite different. But if you construct appropriately five different views, what you will see on the right side is that the latero and the axio resolution are quite similar so you are really isotropically covering almost the entire specimen.
Slide 66
What is also nice is that you can do that on a living specimen. You can do it relatively fast. On this movie, we are looking at a single embryo where every single cell is expressing a histone 5 P marker and we are imaging this embryo continuously from five different angles every about five minutes. This is not as fast as what you will see in the next presentation, but even this gives us a very good overview of all the spectacular morphogenetic movements, which are happening during the development of Drosophila.
Now for developmental biologists, this kind of data is extremely exciting and it opens up new ways of asking questions. What I found very striking is that the SPIM technology is actually also relatively simple to realize physically.
[0:20:06] Slide 67
So that’s why we have started the so‐called Open SPIM project, which is a simple SPIM‐like microscope, which can be assembled for less than 20,000 Euros.
Slide 68
We call this Open SPIM because our intention is to release on the internet in form of a wiki page all the detailed instructions of what one has to buy to build such a scope and all the step‐by‐step procedures to build it. So, it should be actually as easy to assemble it as if you are assembling a piece of Ikea furniture.
Slide 69
Most importantly, we will also provide you with open source software, which is based on Fiji, which will be actually able to drive this microscope. So there will be truly a synergy between the open software and hardware, which will allow us to further develop this technology in a kind of collaborative manner.
Slide 70
This scope actually exists. It is very small and it can be put into a suitcase. The idea here is to be able to bring such a scope with us to a meeting. However, one has to say that it is very difficult to pass this kind of suitcase through airport security.
Slide 71
Finally, I would like to say what is the motivation, which we have to actually do this kind of Open SPIM development. What we intend to do is to image tens, hundreds, and eventually thousands of expression patterns during the development of Drosophila. This process takes inherently 24 hours and so one scope will be occupied for one day.
Slide 72
In order to achieve any kind of throughput in this kind of imaging, what we have to do is to parallelize. Open SPIM allows us to build many such setups and feed the data directly into the Fiji platform where we have developed ways how to register them, how to put them together, and how to analyze them further on. Slide 73 So I will end here by saying that from my point of view, I believe that every developmental biologist should have such a microscope. Slide 74 to Slide 75
There are many questions, which can be solved with the high end setups, which allow you to image entire development with unprecedented resolution eventually being able to follow each cell. But there are many other samples, which can be imaged with this
technology and therefore it is also important that there is a broad range of solution, which can be adapted to various developmental circumstances.
Slide 76
Now finally, we also would like to be able to parallelize the acquisition with the SPIM scope and for that we believe that one way how to do that is to open source the whole setup.
Slide 77
So at the end, I would like to thank the people who participated in this particularly the co‐PI on the Open SPIM project is Jan Huisken and the work on the Open SPIM has been done by Pete Pitrone and Johannes Schindelin who wrote the software. The software development I described to you has been performed by Stephan on the left. Thank you.
Sean Sanders: Wonderful. Thank you so much, Dr. Tomancak. Fantastic slides. It’s really interesting stuff. Slide 78 I’m very much looking forward to our final presentation and that is by Dr. Lars Hufnagel. Slide 79
Dr. Hufnagel completed his Ph.D. at the Max Planck Institute for Dynamics and Self‐Organization in Göttingen, Germany and went on to do postdoctoral research training at the Kavli Institute of Theoretical Physics in Santa Barbara, California. He has been a group leader in the Cell Biology and Biophysics Unit at the EMBL in Heidelberg, Germany since 2007, and in 2010 became a joint group leader at the Center for Modeling and Simulation in the Biosciences. Dr. Hufnagel’s research interests include biophysics, microscopy, optics, developmental and cell biology, and biophysical modeling. Welcome, Dr. Hufnagel.
Dr. Lars Hufnagel: Thanks for having me. So I hope your talks stimulate you a little bit to go more into light sheet microscopy. What I want to tell you about is basically two stories. As Pavel already said, we’re trying to squeeze out the maximum end speed and resolution from the light microscopy techniques and then the other part I’m going to tell you about is how one can also use these light sheet microscopy techniques to get information about protein concentration and protein diffusion within single cells.
[0:25:09] Slide 80
So to gain a deeper understanding of fundamental biological processes, it’s always important or it’s necessary integrate from the subcellular scale to the full organismal scale and this poses tremendous challenges for microscopy techniques. For example, if you want to image a Drosophila embryo, you will need around 400 million points in order to evenly cover the full embryo. So if you do this on standard confocal microscope, it will take about 400 seconds to image the entire embryo. In addition, that it’s very slow, it will also have a very high phototoxicity and bleaching and the background will also be very high. So this clearly called for new novel and in particular very fast imaging techniques that can bridge the scales from the subcellular resolution to the full organismal scale.
Slide 81
So, we have developed a microscope as you can see here that is capable of for example imaging a Drosophila embryo within just a few seconds. We named this microscope MuVi‐SPIM for MultiView Selective Plane Illumination Microscopy and you can think of it as basically four SPIMs in one. So it’s based around two illumination and two detection objectives, has two high speed and high sensitivity cameras attached to it, and it can operate at speed of something around 100 to 200 frames a second. So this microscope not only allows you to image with very high speeds, but it also makes the data processing much, much easier which I’m just going to present to you in a little bit in the next slide.
Slide 82
So as Pavel already said in the imaging specimen that also gets light illuminated, it’s important to image it from multiple sides so that one can image the entire specimen. So as said MuVi‐SPIM images illuminates from two directions and has two detection directions so it gives you four views of the sample and without any rotation. This makes the data processing much, much easier. So the four views that the MuVi‐SPIM takes to register all these texts and transform them into a common coordinate system, the transformation is solely given by the optical setup. This transformation can be calculated or measured before the actual experiment and then the transformation can be online in real time is the image is acquired. So MuVi‐SPIM basically generates you in real time a high quality 3D, single 3D data spec of your specimen.
Slide 83
So now let’s put MuVi‐SPIM to the task. So we imaged the entire development of a Drosophila embryo. So here, you see a Drosophila embryo that expresses a histone marker with and M cherry so it’s a red fluorophore attached to it. On the left‐hand side, you see the future head of the fly. On the right‐hand side, it’s the posterior pole and we’re looking at the ventral part. This movie basically shows with very high temporal and spatial resolution all hallmarks of Drosophila development from ventral furrow formation, convergent extension, germ band retraction, dorsal closure and we’re even fast enough to image true muscle activities, which we will see in a few seconds. More importantly, it is to note that this embryo after imaging hatched and was a perfectly viable larvae after all this imagine procedure.
So the pure imaging time for four stacks was almost a little bit smaller than 10 seconds for the full four views and the maximum imaging, the total imaging time was 24 hours.
So also one thing one obviously gets if one asks for speed is that also one gets a lot of data. So this movie has a total of 8 terabytes of data and then one needs also to think about how to handle this data in particular if one wants to scan through many different embryo’s genetic types.
Slide 84
So this slide shows you our IT infrastructure around the microscope and so the MuVi‐SPIM in the middle we control by real‐time computer that does all the time critical controls for the microscope and then we use high end SCMOS sensors, which can generate high data rates of between 1 and 2 gigabytes per second. So this data is then collected by individual or specific computers, which are attached to the camera and we use fiberoptic cables to then store the data, bring the data to long‐term storage or to clusters that analyze the data further.
Slide 85
So we’ll show you another movie that now with this high speed we achieve imaging of a full Drosophila embryo just in five seconds. It is actually quite easy to now track nuclei as these nuclei now move very little from one time point to the next time point. This way, we can track nuclei through many divisions as you see here in one view of the Drosophila embryo, which is in the blastoderm stage where we track nuclei from cycle 9 to 14.
[0:30:16] Slide 86 Obviously, MuVi‐SPIM cannot just be used for imaging nuclei, but it can also be used to image for example membranes or other cellular components. So here, we image the Drosophila embryo expressing a membrane marker and this embryo was actually imaged now with eight views so we rotate it once by 90 degree. I hope you can appreciate that you see in the insert in the blow‐up region that there’s no displacement with the membranes. So actually even with 90‐degree rotation, we’re fast enough to really get an instantaneous view of the embryo. Slide 87 So before closing our presentation, I just want to also show you that you can push this light sheet microscopy also to gain information and very quantitative information over protein dynamics within single cells or even organs and this was a collaboration with Malte Wachsmuth and Michael Knop at EMBL. So what we did there, we illuminated with a very high angle, a very high end A objective so to generate a very thin light sheet. This light sheet is well below half a micrometer thin so it gives a very, very good optic sectioning, however, it’s very short, but it’s still long enough to image an entire mammalian cell for example or a tissue.
So on the right‐hand side, you see a comparison between light sheet microscopy optical sectioning and a confocal and we basically get the same volume, 3D volume as a confocal microscope with this light sheet microscope.
Slide 88
So now, this light pad as we call this very thin sheet of light can now be imaged on a high speed EMCCD camera as you see on the left‐ hand side and every pixel corresponds basically to a confocal volume in the specimen. Now when proteins move in and out of this volume, they give little fluctuations of their intensity signal and these fluctuations can then be analyzed and from this one can calculate what the diffusion constant is, what the concentrations are. This we have done for mammalian cells and for various systems, but what I present here on the bottom part is Drosophila wing imaginal disc where we expressed the nuclear marker, which can freely diffuse inside the nucleus but not outside the nucleus. On the right‐hand side, you can see first of all the intensity profile, the measured concentration we’re getting, and the diffusion constant and this is in
very good agreement with confocal FCS measurements, but here it really is an imaging method which gives you a two‐dimensional landscape instead on the confocal FCS system you would just get a single point.
Slide 89
Let me just thank the people involved in this project. So first of all my lab and there Uros Krzic is the main person developing the microscope and then Stefan Gunther, Timothy Saunders, and Sebastian Streichan basically complete the light sheet microscopy team. Then I’ll obviously thank the the core facilities for building the microscope and in particular I would also like to thank Malte Wachsmuth, Michael Knop, and Jeremie Capoulade for the project on the SPIM‐FCS. Thank you very much.
Sean Sanders: Fantastic. Thank you very much, Dr. Hufnagel. Really fantastic talks from all of our speakers so I want to thank them very much for their exciting presentations. Slide 90 We’re going to move right on to questions submitted by our viewers, but a quick reminder to those watching us live, you can still submit your questions by typing them into the textbox and clicking the submit button. If you don’t see the box on your screen, click the red Q&A icon and it should appear. Also just a note to our viewers, I know some of you had some trouble viewing some of the videos, they are quite large files, but this webinar will be made available within approximately 24 to 48 hours so you can watch it again and view those videos. You can also download the slides in the resources widget.
So the first question I’m going to put to all of you and I think I’ll start with Dr. Tomancak because they do mention embryos, and this viewer asks what are the biggest challenges for sample preparation in light sheet microscopy especially for embryos?
Dr. Pavel Tomancak: Okay. So I think it’s actually relatively simple to mount embryos. In fact, one just has to kind of abandon the idea of using slides and change the whole attitude. But at the end of the day, all you have to do is to essentially put your specimen into a rigid medium such as agarose and that essentially can be done by mixing the specimen with adaptively a hot agarose and sucking into a glass copula. So this is something, which can be done in a matter of seconds and this works beautifully for the embryos like the Drosophila. For some
specimens, which are maybe a little bit larger or they need some space to grow; one might need to do a little bit more elaborate micromanipulation to get the specimen into the microscope. But I think developmental biologists have all the necessary skills to do so and one can really adapt the sample mounting strategy to almost all specimens one is actually interested in looking at. [0:35:17] Sean Sanders: Dr. Stelzer? Dr. Ernst Stelzer: Well I think the first thing you should do is relax. Sean Sanders: [Laughs] Dr. Ernst Stelzer: It has been clear that the sample mounting is totally different than in a regular microscope and I really think that should be seen as an opportunity.
Sean Sanders: Uh‐hum.
Dr. Ernst Stelzer: Yeah. So you can really now try to mount whatever specimen you have in such a way that it really resembles the natural conditions to really work on the conditions that are very close to natural conditions. That’s really I think the goal that we should have anyway for the next few years. So I always try to point out that cells simply do not grow on coverslips. They grow on coverslips because we require the coverslips to look at them in a regular microscope but in fact, when we look at real tissues, cells grow on top of other cells. They are enabled by other cells. They generate their own microenvironment and that is really what we want to maintain and that is the kind of biology that we want to push well in the next 50 years or so. Sean Sanders: Dr. Hufnagel, anything to add? Dr. Lars Hufnagel: Yeah. I agree with what Pavel said. So I think one just needs to step out of his comfort zone a little bit from using standard Petri dishes and then find mounting techniques for the organism. So far, we have been always able to mount organisms for light sheet microscope into images for a long time so that it survives and gives good data quality. Sean Sanders: Uh‐hum. Great. So I’ll stay with you, Dr. Hufnagel. So you did show one slide where you did both confocal and the SPIM and this viewer asks about whether the resolution is the same as the confocal and
can we monitor for example signaling molecular, molecule 3D distribution within one cell?
Dr. Lars Hufnagel: So I mean that depends very much on the setup of your light sheet microscope. So one can obviously go for high NA detection objectives, which are then from the optical resolution very comparable to a confocal system. Also from the light detection efficiency, they are very comparable so one can also see very few molecules. On the last parts which I showed, the light PET microscope, there actually we illuminate with an extremely thin sheet of light, and this one allows us to actually get better objective sectioning as on the confocal microscope. So there are also people working on super resolution techniques to marry this with light sheet microscopy or what it can also show initially and Pavel I think also talked about the rotation is one can also use the inherent rotation capability of the light microscopy setup to then use afterwards computer power to increase the resolution. Sean Sanders: Uh‐hum. So the volume of the light sheet can be adjusted? Dr. Lars Hufnagel: Yes. So the volume of the light sheet is basically given by the NA of the illumination objectives. Sean Sanders: Okay. Dr. Lars Hufnagel: And this can be relatively freely adjusted, yes. Sean Sanders: Great. Any other comments? Dr. Ernst Stelzer: Well actually, you have to take into account that you have a certain field of view. Sean Sanders: Uh‐hum.
Dr. Ernst Stelzer: Yeah. So if you want to cover your field of view in a reasonable manner then of course you sacrifice your resolution a little bit. But the real nice feature is that you can adjust it. In principle by over or under illuminating the illumination lens appropriately, you can really find the right conditions. Yeah.
Sean Sanders: Uh‐hum. So that follows on nicely to another question about the constraints of sample size that you can illuminate. In other words, what’s the largest sample that can be used given the working distances?
Dr. Ernst Stelzer: Well the constraints are really essentially given by the lens that you use and by the camera. So the field of view or the pixel size or the number of pixels on the pixel picture essentially determine the chip size. Sean Sanders: Uh‐hum.
Dr. Ernst Stelzer: And that together with the detection lens actually determines the field of view that you can look at. But the other thing that we have done, which I didn’t show today, is what you can also do is you can look at certain subsections of the area and then you can stitch it together. So for example what you saw all the time today was essentially recording pixels along different directions and fusing those images. But in principle, you can also stitch them together very much like most cameras can do it and in this way you can artificially increase the field of view and that is done probably by a lot of people around a regular basis nowadays. Sean Sanders: Uh‐hum. Uh‐hum. So Dr. Tomancak, do you have any comments on that and maybe if you can also talk about some of the samples that you’ve illuminated and had challenges with. Dr. Pavel Tomancak: So I mean I have shown during the presentation that we went up to say the size of a mouse embryo. Sean Sanders: Uh‐hum. Dr. Pavel Tomancak: I mean I think the issue a little bit is also what exactly one is imaging. If one wants to image some specimen live, they’re not always like Drosophila stay in a confined space, they actually grow and one might need to actually adjust the imaging strategy for the different stages of their development. So one can probably start by imaging the embryos with a different, I would say, settings than when one has to then go to a later stage animal and, you know, do tricks like Ernst was describing to stitch together multiple fields of view. So, yeah, I think this will always depend on the type of sample one is imaging, right? [0:40:45] Sean Sanders: Uh‐hum. Dr. Hufnagel, anything to add? Dr. Lars Hufnagel: Yeah. So most of the applications we do is for live imaging and at the moment I think the biggest sample we looked at are in the order of a
millimeter. Then if one goes beyond a millimeter then one also gets a problem with the penetration of the light sheet inside the sample. But a millimeter to a little bit more of a millimeter is usually easily doable. Sean Sanders: Excellent. So another question for, how fast can SPIM image? What’s the maximum that you’ve reached? Dr. Lars Hufnagel: Yes. So at the moment ‐‐ I mean first of all maybe I have to add so I think during the last two or three years these exciting new cameras came out, these SCMOS cameras which really I think boosted the field of light sheet microscopy because they can show their full potential with their high frame rate. So we’re using regularly cameras, which have four to five megapixels and can run in full field up to 100 frames a second.
Sean Sanders: Uh‐hum.
Dr. Lars Hufnagel: So if we down sample it, it will get proportionately faster so these cameras can also run much, much faster. So on our microscope, we can run easily at 100 slices per second, maybe 200 slices per second that’s something we can easily do. With more tricks, one can probably even get – I don’t think it’s the top yet. I think one can probably get easily factor 2 to 5 faster if one really wants to push it. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: And it’s probably also important for the FCS. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: Because they are – I mean when we worked on that, I think we never got beyond 600 frames per second because the cameras were simply not faster. But what you really want to get at is I assume something in the range of maybe 2000, 3000, 4000, 5000 frames per second and I don’t think that’s unrealistic. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: So and that’s important because otherwise you really don’t get the temporo resolution that you require. Sean Sanders: Uh‐hum. Right. Dr. Tomancak?
Dr. Pavel Tomancak: I think it’s really actually impressive what kind of speeds one can achieve with these type of scopes. Even with the scopes which involve rotation, one can actually image the entire embryo in less than let’s say 15 seconds and that’s actually more than enough to sample the temporo dimension in a way that none of the relevant entities, which in this case will be cells, would actually move.
Sean Sanders: Uh‐hum.
Dr. Pavel Tomancak: And so then that allows, you know, really efficient tracking of these entities across time. But what we will probably discuss in the next part of this is that it generates tremendous amounts of data. Sean Sanders: Uh‐hum. Dr. Pavel Tomancak: And that’s actually a big issue here.
Sean Sanders: Uh‐hum. So that’s actually perfect because the next question I was going to ask was about data. It was actually directed at Dr. Hufnagel saying if the Drosophila development video was 8 terabytes, will there be a need for an external service for data processing? I know we spoke before the webinar about your processing systems.
Dr. Lars Hufnagel: Yeah. So obviously, if you ask for speed then also you get a lot of data storage.
Sean Sanders: Uh‐hum.
Dr. Lars Hufnagel: So this basically goes hand in hand. I mean just to put sort of the data amount we generate with MuVi‐SPIM at the moment and perspective it so eight terabyte is a normal overnight movie for us. Sean Sanders: Uh‐hum. Dr. Lars Hufnagel: And if Pavel wants to do his screen with his speed on a microscope, it will be more data than Google Earth at the moment has. So this just shows you where the challenges in the future will be. It will be much more on the computational part, what to do with the data afterwards.
Sean Sanders: Right.
Dr. Lars Hufnagel: And I think at the moment, we are dealing with 8 terabytes, 10 terabytes of data is still doable with the current technology, it’s no
problem. So one can basically send it to parallel computers. Individual type runs can be in parallel analyzed and this can speed it up. But, yeah, I think it calls for efficient algorithms and obviously storage is a main issue, storing data.
Sean Sanders: Dr. Tomancak, anything to add?
Dr. Pavel Tomancak: Well, I mean I think it’s also a question, you know, how much data actually do we need to answer our questions. That’s in this range, you know, where we are really as we were discussing before the broadcast, we are actually entering the realm of particle physics, right, and as biologists we are not necessarily equipped to be dealing with these volumes of image data. So I think one has to make some kind of reasonable decisions in terms of the resolution and especially the time resolution and the resources one has to actually analyze it because recording these datasets is only one step but extracting some information out of it is the next one and the challenge really becomes very much informatics. [0:45:26] Sean Sanders: Right. Dr. Ernst Stelzer: But one should not forget, I mean the amount of data that you start off with is maybe huge. I mean when Philip Keller actually showed quite nicely a few years ago, I mean at that time we created much less data, I have to say about 3 to 4 megabytes, terabytes not much less but less. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: But the real trick is actually to do the segmentation, yeah, and once you’ve really found all the nuclei then you’re talking about data, which is still handleable. So when you’re talking about gigabytes, maybe a list of a few thousand nuclei or some other feature in the cell which is described by a certain terminology and that’s really the data you’re interested in and that’s probably also the data you really would like to store. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: Yeah. That – Sean Sanders: So, Dr. Tomancak, a question for you. Is it possible to do images in chamber with live cells and control the temperature and CO2?
Dr. Pavel Tomancak: I don’t have any experience with that. I think some of the people here – Dr. Ernst Stelzer: We do it all the time. Sean Sanders: All the time?
Dr. Ernst Stelzer: Yeah. We really control the temperature and we also control the CO2 level and also the oxygen level.
Sean Sanders: Uh‐hum.
Dr. Ernst Stelzer: We really mix the gasses which is really, really, really important particularly in the 3D cytology stuff that I mentioned. Because if you think about it one of the weird things is that a lot of people work with cells and they’re cultivated on coverslips and they actually are exposed to 20% oxygen, but actually if you look at tissue in our bodies, it’s less than 8% on average. So you really have to push this. It’s a very important issue, yeah, very good question. Sean Sanders: Right. So a couple of questions about dyes. Are there any particular dyes that you would recommend for SPIM? Dr. Hufnagel, you want to – Dr. Lars Hufnagel: Yeah, I mean – Sean Sanders: ‐‐ try that? Dr. Lars Hufnagel: ‐‐ obviously SPIM is an excellent tool for getting deep into a tissue. Sean Sanders: Uh‐hum. Dr. Lars Hufnagel: And in order to penetrate maybe a little bit deeper into the tissue, one is obviously one needs a bright dye so that one can image quickly so one needs a good signal. The dye should also not overlap with the autofluorescence spectrum one has in most of the animals so that’s important. Then certain fluorophores can have better penetration depth for the light so this might be one needs to consider. So it will depend on the specimen one looks at, but in general I would say obviously bright fluorophores help a lot and then if one stays away from autofluorescent and the tendency is go to the red is probably a good way.
Sean Sanders: Uh‐hum. Dr. Tomancak?
Dr. Pavel Tomancak: Well I would say that important feature of the fluorophores is that the fluorescence appears fast. I mean for our let’s say application, we want to monitor the activity of the gene and if there is a delay between when the protein is made and before we can actually detect it, you know, then that’s a problem.
Sean Sanders: Uh‐hum.
Dr. Pavel Tomancak: So we are using a variance of the GFP, which fold very, very fast. I would also say that SPIM is in fact, you know, extremely useful also for imaging fixed specimen because you can really achieve amazing resolution by combining many different views and then of course, you know, the range of the fluorophores is massive, right?
Sean Sanders: Uh‐hum.
Dr. Pavel Tomancak: And it’s really one really needs then a setup, which is able to excite them or as many that is actually possible so that one can do a multicolored imaging.
Sean Sanders: Uh‐hum. Dr. Stelzer?
Dr. Ernst Stelzer: I think there’s no real limit to the – I mean basically it’s not like in some of the high resolution methods where you’re really restricted to some dyes, but whatever can be excited. Most of the stuff that you say or basically everything that you saw today was actually single photon excitation and whatever can be excited can be observed.
Sean Sanders: Uh‐hum. I’ll give you another question, is there any reason to use single versus multi‐photon lasers to generate light sheets?
Dr. Ernst Stelzer: Yeah, good question. I’m not absolutely sure so you would assume that in the two‐photon system you can probably penetrate a specimen a little bit better, which is probably true. But I think that’s where the niche is. Maybe the deeper you want to penetrate a specimen, the more likely it is that you will consider two‐photon microscopy.
Sean Sanders: Uh‐hum.
Sean Sanders: Uh‐hum. Any other comments, Dr. Hufnagel?
Dr. Lars Hufnagel: Yes. So there’s some nice work being done where people use two‐ photon lasers by Scott Frazer’s lab or the Betzig lab with bessel beams and I think these are all very promising applications. In particular, as Ernst said, if one wants to get a well‐defined light sheet in a specimen then obviously going for a longer wavelength is sort of a standard way to do it. Maybe one has to sacrifice a little bit on speed because the illumination efficiency with two‐photon is not as high as ‐‐ [0:50:13] Dr. Ernst Stelzer: Yes. Dr. Lars Hufnagel: ‐‐ a single photon. Dr. Ernst Stelzer: That’s a major problem…
Dr. Lars Hufnagel: But otherwise, I think it’s very good for probably thicker specimen where one doesn’t need the full maximum speed.
Sean Sanders: Uh‐hum. Excellent. This next question is what is the difference in depth resolution in optical slicing versus light sheet methods? I’m not sure if that makes sense to you. Dr. Stelzer, you want to…?
Dr. Ernst Stelzer: So I mean there’s a certain property that we’re really interested in and that’s optical sectioning.
Sean Sanders: Uh‐hum.
Dr. Ernst Stelzer: So that’s a well‐defined term in microscopy and optical physics. Confocal microscopy has this capability, conventional microscopy does not even if you do deconvolution you don’t have that. Two‐ photon microscopy has this and also light sheet microscopy. That’s what I briefly mentioned when I said you take the product of the two point spread functions.
Sean Sanders: Uh‐hum.
Dr. Ernst Stelzer: And in general, I would say the thickness of the light sheet in confocal microscopy with high NA lenses is probably a little bit smaller.
Sean Sanders: Okay.
Dr. Ernst Stelzer: But for the high NA systems, it’s different. For high NA systems, you will always have a much thinner light sheet ‐‐ sorry with the light sheet, with the SPIM than with the confocal microscope.
Sean Sanders: Dr. Tomancak?
Dr. Pavel Tomancak: One should probably take into account the kind of topology of this microscope that the light sheet comes from outside and so if your specimen is actually covered with something which is impenetrable to light then it will never get inside, right?
Sean Sanders: Uh‐hum.
Dr. Pavel Tomancak: And we are often here showing examples where we imaged the most challenging of samples that every single is labeled and every single cell actually deserves the illumination light. You know, if the specimen is labeled very sparsely, you can actually get much, much deeper in my experiences. So, yeah, it depends a little bit also on what you are imaging, right?
Sean Sanders: Uh‐hum. Another resolution question that came in asking whether it’s possible to look at subcellular organelles using SPIM? Have any of you ever tried that? Dr. Ernst Stelzer: Absolutely. Sean Sanders: Yeah. Dr. Ernst Stelzer: I mean it has been tried many times, it works very well. I’ve showed pictures of the yeast ‐‐ Sean Sanders: Okay. Yeah. Dr. Ernst Stelzer: ‐‐ works perfectly, absolutely. I think there’s no doubt and you also showed that. Dr. Lars Hufnagel: Well, yeah. We actually measured protein concentration, which is a very, very small molecule, yeah.
Sean Sanders: Right. Yeah and there was a question earlier about looking at protein‐protein interaction and I think I believe did you show a slide, yeah, on the protein…?
Dr. Lars Hufnagel: Well protein‐protein interaction could also be measured, yes. Sean Sanders: Uh‐hum. Dr. Lars Hufnagel: This will require to have both proteins labeled and then one would need to see how they basically correlate, the signal would correlate. Dr. Ernst Stelzer: I think you could also answer this in a more general term. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: For example, don’t forget, I mean if you look at the light sheet based microscope, basically the detection system is a regular fluorescence microscope. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: So whatever you can do with the fluorescence microscope, you can also do with the light sheet. The only thing that you really change is the way you illuminate the specimen and therefore you can do FCS, you can do FRET, you can FLIM, yeah, and if these technologies can be used in a regular microscope to measure protein‐protein interactions then of course you can also do it with a light sheet microscope, yeah. I think that is the most relaxed way to see it, regard it as a regular fluorescence microscope. Sean Sanders: Right. Dr. Ernst Stelzer: Yeah. Sean Sanders: Right. Dr. Hufnagel, anything to add? Dr. Lars Hufnagel: Yeah, perfectly put, yeah.
Sean Sanders: Excellent. So next question is can these techniques be used in organotypic cultures and over days? So I’m not sure if any of you have any experience with this, Dr. Stelzer? Dr. Ernst Stelzer: That’s what we do all the time. Sean Sanders: Okay. Dr. Ernst Stelzer: I can only say yes, yes, yes.
Sean Sanders: [Laughs] So is there anything this can’t do? Dr. Ernst Stelzer: Well of course. Sean Sanders: What will be the limitations? Where would you put those boundaries right now? Dr. Ernst Stelzer: The boundaries for a light sheet microscope? Sean Sanders: Yeah. Dr. Ernst Stelzer: Well I think it’s still targeted more for relatively large objects where you really want to work on the interaction let’s say of multiple cells or so on. So that’s where I would really go for it. Sean Sanders: Uh‐hum. Dr. Ernst Stelzer: Yeah. And I mean if you have a completely flat specimen, I mean for whatever reason let’s say you want to look at, I don’t know, single molecules on microtubules or so then you have them on coverslips then I think it has no reason to use a light sheet based microscope. You should just stick to the system that you currently have. There are a lot of reasonable biological questions that you want to address with TIRF or whatever. Sean Sanders: Uh‐hum. So maybe this is a good follow‐on question that asks about the fields of application that you think would most benefit from this and you each obviously have your own fields. But maybe we’ll start with you, Dr. Hufnagel, if you can just talk a little bit about how you see this being applied and where you’d like to apply it? [0:55:03] Dr. Lars Hufnagel: Well what I’ve witnessed sort of in my daily research is that I see that of the classical cell biologist and the developmental biologist sort of come together. The cell biologist will basically want to develop cell biology and developing backgrounds in the organism in the embryo and the developmental biology want to look closer at ultra‐cellular processes. Sean Sanders: Uh‐hum. Dr. Lars Hufnagel: I think the fundamental concept of SPIM the high speed it gives and then the low phototoxicity just make it a very good tool to basically
