Wisconsin Public Television University Place Wednesday Nite at the Lab  UW Engineering and Biological Microscopy  Kevin Eliceri and Steve Paddock  12/5/12 UP815 cc >> Welcome everyone to Wednesday Nite at the Lab. I'm Tom Zinnen. I work here at the UW-Madison Biotechnology Center. I also work for UW Extension, Cooperative Extension. On behalf of those folks and our other sponsors, Wisconsin Public Television, Wisconsin Alumni Association, the UW-Madison Science Alliance, thanks for coming to Wednesday Nite at the Lab. We do this every Wednesday night, 50 times a year. Tonight I have the pleasure of getting to introduce two people, both of whom have given Wednesday Nite at the Labs before. There's that old saying, one picture is worth 10,000 words. We're going to be several billion tonight. Because these are some of the greatest images around of the cellular and molecular level. 

Tonight, Steve Paddock will be giving part of the talk. He's a Howard Hughes Research Fellow in Sean Carroll's lab here at the University of Wisconsin-Madison's laboratory of molecular biology. Steve has an extensive background in the biological sciences and he has authored many publications on such topics as advanced applications for microscopy, digital and video imaging, photomicrography, and biological and medical research, and specialized techniques in confocal laser scanning microscopy. His work has appeared in numerous books and scientific journals, and many of his images have been featured on the covers those journals. Steve's images have received recognition on numerous occasions in Nikon Small World competitions. His major research interests include insect developmental biology, with specific emphasis on appendage formation in drosophila, of fruit flies, and in butterflies. He's also interested in the application of confocal microscopy to imaging biological structures, and the transfer of the technology to biomedical and clinical research applications. He'll be joined tonight by Kevin Eliceri who is the director of the Laboratory for Optical and Computational Instrumentation. Otherwise known as, LOCI. He is a permanent principle investigator in the laboratory for cell and molecular biology here at UW-Madison, and also in the graduate school. 

Kevin is also a member of the departments of biomedical engineering and medical physics, the UW Carbone Cancer Center and the McPherson Eye Research Institute. He's an affiliate investigator of the Morgridge Institute for Research, focusing on the development of medical devices. Kevin's research focuses on biophotonics, the use of light to investigate biological phenomena, and bioimaging informatics, the application of computational techniques to analyze and process bioimages. He collaborates with investigators around the world on the development and application on optical and computational methods to study a range of biological processes, including cancer progression and stem cell differentiation. A major emphasis of his current work is developing advanced imaging methods for the improved detection and characterization of cancer invasion and progression. It's always a great thing to be able to see what you're looking at and look at what you're seeing. I think this is one of the great things about the imagery that Kevin and Steve are able to develop here and with their colleagues around the world. It's a very impressive thing to me. I'm looking forward to seeing what you have to show us. Please join me in welcoming both Steve and Kevin to Wednesday Nite at the Lab. 

[applause]  >> I'm delighted to be here. I'm Kevin Eliceri. Steve Paddock is in the front row. You can see our pictures here. To start off, I am delighted to be here. I will warn you, I talk very fast. So if I'm talking too fast, if anybody audience wants to go like this, I'll slow down. The more excited I get, the faster I talk. We're delighted to be here. As Tom mentioned, this is not our first time here. 

In the past, both Steve and I have come here talked about our own research programs. I've come and talked about my work on cancer, very specific to what our group does. Steve has come and talked about his work in evolution and development. This is going to be different tonight. Steve has been a longtime friend and collaborator, and recently we found a lot overlap in our interests. He, in the lab, really studies evolution. It's an amazing lab, Sean Carroll's lab at the Howard Hughes Institute. They're interest is in evolution, what we can learn about imaging and how if can form our understanding of evolution and development. I'm in a lab that does some cell biology, but really focuses on the cell biology of cancer, stem cells. We're more of a disease oriented lab, but as you'll find out in tonight's talk, there's a lot of overlap. 

We use very similar imaging techniques, we're very interested in very similar imaging aspects. The major theme is that we want to look at cells and see what they do in real time, and that's what both of us do. To give you some idea of some of the data. This is one of my favorite movies, zebra fish development. Sometimes as microscopists we just want to watch biology happen. We just want to watch to see-- watch the process of cell division and development, and before your eyes, pretty soon, you'll start to see the shape of a fish. That's what we want to do, is to watch biology happen. As you heard tonight, a big part of our work is watching and interpreting. You'll see the fish inside the egg there. You'll hear tonight about that, and the theme is engineered image. 

What we mean by that is that imaging of any type, including MRI and CT and ultrasound, or we're talking tonight about light microscopy, really is built on the work of engineers. We want to talk about how engineers have contributed to this, from this campus and elsewhere, and really look at the history of this, how this field came to be and where we're going. It's very timely. There's a special exhibit in Wendt Library that we put together. The library is right next to Union South. If you walk in there-- It's open to the public. On the right we have an exhibit of scopes, old microscopes, including the same models that were on the Darwin and the Beagle, famous boats. You're welcome to come there and see that. See how engineers have played a role in microscopy. That's in part why we're giving this talk, but also want to get across just how amazingly the field has developed and where it's come from. 

What is the rational for the engineered image? This is something Steve and I wrote together, so we're both interested in the role that cells play in development, both normal and abnormal. My passion often is looking at what happens when things go wrong. For example, cancer is cell division that has been messed up. We want to understand the interaction between cells and their microenvironment. You guys are in my microenvironment. When you clap I feel good. When you fall asleep I know I'm boring. That's interaction. The same thing with cells. The cancer can hijack the microenvironment and have interactions. 

We want to understand what happens. For example, cells are progressing. What happens to other components and other systems nearby the cells? Then the role of cell behavior and communication. How do cells communicate? What do they do? When you have a wound due to a burn or due to a physical injury, how do cells communicate in that process? What happens in cardiac disease and neuro disease? These are things we're interested in. To best understand this, as I mentioned, the best way is to watch it. Imaging is really the only way to understand these spatial and temporal, over time, relationships. We want to watch them in their natural environment. By natural I meant we don't want to do artificial if we can. We want to see them intact, whether it's in an animal or whether it's in a dish with the right nutrients. We want to look at it with as close to natural as possible, doing their thing and not disturb them, but still get a realistic view. 

This requires imaging methods that can see cells map-able to genes. We want correlate to genomics. You often hear about the genotype, and that's actually the parts list. Then there's also the phenotype. That's what they do. We're after the phenotype, but we want to link it back to the genes. We're not satisfied just to watch thing. We want to know what the function is. We want to know how the genes came to be. Such methods require the work of engineers. 

I'm an engineer. I develop systems and I use them. I work with -- just like Steve, to try to see if we can't use these methods to get a higher understanding of what happens. This is one of my favorite movies. On the film strip on the right there, that's actually just watching C. elegans development. You'll see a movie in a second that illustrates that. Many of you have probably heard of the power of stem cells. This is an example of that. One thing is our talk-- We're going to keep it pretty light tonight. It's night time. 

We want to have-- I don't want to put anybody to sleep. I'm going to actually gloss over some of the technical details and really focus on what the power of the techniques can do. But if you have questions as the end, I can talk to you about them. We really want to show what the power of imaging can do. This is an example. This campus really is a major campus for stem cell research. One of the real powers of it, you have to understand how stem cells differentiate, how they become more specialized cells. We can use it to understand disease, but also even to treat disease. One of the really fascinating things is what happens to embryoid bodies, groupings of stem cells, when they become more specialized cardiac cells called cardiomyocytes. You will see here, this is a plate of cells that's beating. 

That's because they're heart cells. So you can actually watch this beating happen. That's something that you really only can do with video microscopy. The power of this is that if we can understand how these cells come to be, how these cardiomyocytes get formed, we actually could use this to treat heart disease. There are active efforts, professors on campus, trying to create grafts, ways of grafting or putting onto heart tissue, new cells that could regenerate the heart. Stem cells are very promising. As well, both Steve and I are very interested in development. Sometimes we just want to understand what happens normally. All of us are here because of development. We all started off as one cell embryos and we kept developing, becoming more specialized. 

We want to understand how that happens. In part because of disease, because of the importance of understanding cancer and other diseases. But also just to have a proven understanding of how we came to be. One of our favorite organisms is the C. elegans worm. You have heard of this before, but this campus is one of the leading research entities in C. elegans. This little worm, you can find it in the soil of Bascom Hill, or any place. This little worm has a lot of genes that are common with us. Even though it's this little, tiny worm, it has great gene homology similar to us. And it's clear. We can image it. 

It's very easy to image. So this is one of my favorite images. It shows sometimes-- Again, similar to the fish movie I showed, sometimes we just want to watch it develop so you can see the start of the two embryo developing, then it becomes a four cell embryo, and then more specialized. You can see the cells keep dividing. And then six cells-- I can help you a little here and show you that-- You can see the nuclei, more specialized. As the cells become more specialized, and more of them, you will start to see the shape of the worm form in a second. This was all done over a long period of time. We can watch 12, 14 hours, and just watch this occur. This is all done with high-contrast light microscopy using techniques kind of similar to this. I'm lit up here. 

We can light up the embryo and look for things that contrast. That's what we did. In a second you'll watch the worm shape. You'll start to see the worm kind of curve around. You can start seeing-- It's towards one end here. In a minute you'll start to see it looks like a worm. The power of being able to watch development is huge because we can also watch when things go wrong. We can look at mutants, changes in genes, and compare the normal to the mutant. Now you can start seeing the shape of the worm quite clearly. Now the little guy wants to get out of this shell. 

That's the power of what imaging can do for you. We also though-- So that's very powerful. But what if I want to correlate it to genes? Genes are almost like genetic paintball. I can take colors and I can tag it to genes, and those genes that Steve will talk about, fluoresce. Now they've been tagged with a special fluorophore, we can then watch the development and see what happens. For example, if I want to study a gene of interest that's involved in cancer, or involved in a failure in cell division, I can tell what happened because that color is there. In this case we actually want to see what happens in cell fusion. Cell fusion is really important. It's involved in many disorders, including muscular dystrophy. How cells fuse and form membranes is both important for development, but also important in disease. 

In this case, we labeled some important genes in this with color, with fluoresces, and now you can see-- Again, this is C. elegans, also with microscopy, but in this case, a different method. You can see, it's completely different. We're looking at the embryo again, but his time we're only looking at the membranes. So we're only seeing the junctions. That way you can use fancy 3-D techniques. Now you're seeing three dimensions pop out at you. This is an example of using advanced microscopy to look at a very basic organism, but then using 3-D techniques, 3-D visualization techniques, that allow us to look to it from perspectives. So modern biological investigation needs all sorts of ways of imaging across multiple time and size scales. We want to look at the structure, physical structure. This is my structure. 

Me being dynamic, me moving over time. We want to do that. We also, as I'll talk about at the end, are really pushing the envelop. And by we, I mean the field, of engineering of what we can do beyond a pretty image. Yes, we want to collect pretty images, but can we get quantitative? Can we go after what's in the microenvironment? I'll talk about that. And a big challenge in the field is you're dealing with multi-dimensional data. Your brain isn't really well-equipped to deal with data of this dimensionality. Another challenge is, how do we actually appreciate this kind of data? In part because it's big. One of our favorite images, collected with a collaborator, Brad Amos, is looking at really big data. Here you'll see a big field of view, but then this data is so high-res in the brain that we can blow it up and just get an outstanding view of what's going on in this neural environment. 

As well, sometimes we can collect big data because we tile it. I don't know if you can see back there, but this image is actually made up of 81 images. This is super-high-res, and similar to those of you who have done a panoramic view of the Grand Canyon, where you look at the Grand Canyon, take the camera and go, boom, boom, boom, boom, boom across and stitch it. That's what we did. We looked at, breast cancer, in this case. This is a mammary tumor in breast cancer. We want to create a giant view, but typically to do a giant view is you use a low resolution, big field-of-view detector. We don't want that. We want it high-res. So this image is incredibly high-res. 

You're actually seeing the individual fibers that are used-- I'll talk more about this in a little bit. They're used by cancer cells to invade the tumor. We did that by stitching together lots of these high-resolution images into one massive image. This is something that is an engineering feat, and also really important. When it starts getting that big, it means that we can start correlating high-resolution data to medical data. For example, this image is being over lapped with ultrasound data from a human patient. For the first time, you transcend micro with macro. So what is scale? Well, I thought to give you guys some perspective, many of you have probably heard of techniques like an MRI and CT and ultrasound. Steve and I do confocal, a different aspect of microscopy. But the key thing about these techniques is that every time you hear an imaging guy talk, he has his favorite method. 

There is no doubt when you hear Steve and I today that we love light microscopy. But don't leave this lecture hall thinking that we think it's the best technique. It's not. It's the best technique for what we're trying to do. So the big theme of any type of imaging is, if I want to look at an intact human, our work is not appropriate. But if I want to actually look at cells in an intact human, and how it's invading a tumor, it is appropriate. It's all based on the idea of scales. Each imaging method is appropriate for the scale you're doing. In our case, we're interested in the sub-micron, below the micrometer. We actually want to see what happens at that level, because that's where the cells are. 

And it's known that cells play a big role in disease. To help you a little more, you can get an idea of the scale we're interested in if you go all the way from a mouse down to a protein, or smaller. We really are in that sweet spot in our work, where we really want to go after cells. If you look at that chart, that's really why microscopy is king, and particularly light microscopy. That's because the two main things Steve and I want to do in our work is we want to look at cells, and we want them to be alive. If I want to look at cells, it really is microscopy that you need for this. It could be electromicroscopy that we won't have a chance to talk about tonight, or light microscopy. Thank you. My first, slow down, Kevin. So to do that we actually want to use techniques that would be alive. 

Electromicroscopy looks at fixed, dead things. The advantage of light microscopy is that it allows us to get that micron level resolution where we can get bacteria and cells, but we can do that live. And we can do it non-evasively without killing them, without squashing them. If you go down even further, this shows all the microscopy techniques. We're really in that light microscopy area. You can see, with our work, we can't get down to vesicles or even -- layers, but we can get really nice images of tissue and cell. So our work is really going to be about this range. Keep that in mind when you hear people talk. The appropriate image, whether it be optical, electron, radiation based, can be defined by the needs of the application. In this case, there's a favorite cartoon where we're looking at the mastodon, or the elephant. 

We need microscopes that allow us to see deep into that. That's what we're trying to develop as engineers. Again, to reiterate, the challenge we have is that-- It's all about resolution. It's temporal resolution. All what that means is that we want to be live versus fixed. The spatial scale, what view do you want? Do we want big or do we want small? And then resolution, as I mentioned, every method can be defined by resolution, and we're really after the cell resolution. That's because early changes in development, like Steve's work, and cancer, my work, can be at this scale. To give you some idea of the work that is in our lab, that we can LOCI, is we do work ranging everywhere from looking at the uterus, looking at uterine development. In this case, looking a multispectral data. You can see many different colors. 

It's like looking at the wavelengths of the sun and matching them up. Sometimes just watching long-term development. Again, this is the C. elegans example. Watching this embryo with these microtubulales here, watching it over time, in this case, tagged with a gene that's tagged with GFP. You may have heard of this. A very famous Green Fluorescent protein that was originally isolated from jellyfish. It glows green. It got the Nobel Prize in 2002, that we can use this for long-term imaging. To using new, exotic techniques that look at the chemical microenvironment. In this case, looking at our ras, an important simian protein thought to be important in cancer, and what happens. 

Or in this case, is the work of Lynn Allen-Hoffman on campus, trying to understand what we can do in treating burn victims. They're actually trying to create new cells that can used to graft people who have extensive burn damage. It was actually studied, a property of collagen that's in your skin, how that can actually help with burn victim treatment. There's new opportunities and challenges. There's the concept of all these different techniques. We have new kinds of lasers and scanning techniques, and new ways of acquiring data. A big, big theme of the work is that combining all these modalities is the goal of the engineer. we can yield more information if we think cleverly about how to use the computer, how to use the laser, how to use the microscope. A big theme of our work, to be honest, is that I borrow, or sometimes we don't give it back, so we steal, techniques from many other fields, from astronomy, telescope techniques. Adaptive optics from the Hubble Telescope we use in our work, but we won't have a chance to talk about that tonight. 

We use advanced techniques from geology, we've used for visualization and rendering. We really do borrow from many fields. Our goal is to yield more information, but not more frustration. It would be very easy to throw lots of techniques on and not get more information. This is a favorite image. This is actually work showing invading cancer cells in a live animal. So we have the ability that we can actually look inside an animal very non-evasively as well, look inside the animal and be able to peer though it and see what happens at the cell scale. I'll be showing some other data of that too. This slide is-- This overwhelms all of us. If you're overwhelmed looking at this, I'm overwhelmed too. 

This is basically just showing the shear number of techniques available to us as engineers, whether it's an imaging modality, a type of microscope, a light microscope. And then all the different ways of contrast and detection. So whether it's with your naked eye or using special detectors, or different types of filters. All sorts of ways of manipulating the sample, we have the ability to be more that just passive. We can not only image, but we can also manipulate the sample. We can use, almost like tractor beams where you can move things around like on Star Trek, we can actually poke holes in things. We can do things to actually manipulate the microenvironment with light. We also have the ability to do all sorts of fancy computer techniques as well. I'm going to leave that there. The next part of the talk, I'm going to talk about where we're going next. 

Where we're going next can really be best learned by where we came from. So my colleague, Steve Paddock, is going to talk about that. It's a good segue that these picture are these very famous microscopes, including the very famous van Leeuwenhoek microscope and this botanical microscope. They are on display over at Wendt Library. We're fortunate to have a collection of about 200 microscopes that range from the 1800s to now. So if you want to come look those, you're welcome to. These are picture of some of our collection. These are ones that belong to the campus. The one on the right is a more modern microscope. One of the themes we want you to learn about is how, going all the way from the past until now, that modern microscopes are built on past engineering. 

With that, I give you my colleague, Steve Paddock.  >> Okay. Thank you, Kevin. Well, I'm going to take you back some 350 years to start off with. When I started to curate the engineered image exhibit over at Wendt Library with Kevin I realized the idea of the exhibit was to celebrate the contribution of engineers to imaging. And I kind of realized how much I really don't know about the instruments that we use, the lasers, the scanners, the computers. Then again, I really don't know much about the car I drive. I get in and I drive it. I guess it was probably, maybe 100 or so years ago when it was possible to know everything about everything. There were these guys, these great polymaths that knew everything about everything. 

But now we just have so much information that is impossible to know everything about everything. Maybe if we go back 350 years to the first person I'm going to talk about, Robert Hooke. In 1662 he became the Curator of Experiments of the Royal Society of Great Britain. He was probably the very first paid scientist. He was probably paid because he was such a good mechanical engineer. People like Robert Boyle and Christopher Wren really depended on him for, kind of, coming through with apparatus and, kind of, coming through with his ideas, with their ideas. Robert Hooke was a very interesting guy, in that his main job-- the Royal Society had every week, he was supposed to produce an experiment for the members. It was kind of like the beginnings of Wednesday Nite at the Lab, if you like, in 1662. One of his major contributions is this book, Micrographia, which was published in 1664 by the Society. It contained many, many of his images that he took using, not only a microscope, but telescopes and various other 'glasses' as he called them. 

This is taken from the preface of Micrographia. "In the collection of most of which I made use of microscopes and some other glasses, including telescopes." There are pictures of craters on the moon there. "And instruments that improves the senses only to promote the use of the mechanical, helps for the senses, both in the surveying the already visible world, and for the discovery of many others hitherto unknown." Here's a picture of the microscope that he used. It's kind of basically designed on a telescope design. There we go. The big deal about Hooke was he discovered a way of making very small lenses. Van Leeuwenhoek made lenses by polishing the glass. Or there were methods of blowing glass. But Hooke came up with this ingenious way of using melting glass in a weak torch flame. If you take a very clear piece of broken, it had to be Venice glass, I guess. 

That must have been the very purest glass. Then in the lamp, draw it out into very small hairs, or threads. Then holding the ends of these threads in the flame until they melt and run into a small, round, globule or drop which will hang at the end of the thread. Then he figured out ways of polishing and mounting these into the microscope. This is a panel from one of the plates in Micrographia, of his microscope. He also came up with an ingenious illumination system. This is kind of a vessel full of oil on this, kind of, a flame, which goes through this vessel full of water. It produces a very nice defused light on the specimen. Using this microscope, remember there was no photography at the time. Hooke happened to be very good at geometry at high school. 

He was trained in art. So he was able to come up with very clear drawings. The key to this book was he not only looked at biological specimens, but he showed pictures of specimens familiar to people at the time, the tip of a needle, the edge of a razor blade, the warp and weft of some fabric. People could relate to that. But then those images did not compare to the beauty of nature. This is some mold growing on the edge of his book. This is a louse, a hair louse, hanging onto a piece of human hair. Notice that the book has these amazing fold-out figures. There's actually a copy in the special collection here in Memorial Library if anybody's interested. You can go see it. 

I'm not sure you can touch it, but-- So Hooke wrote, he had "a sincere hand and faithful eye." This is the eye of a fly, the first time anybody had ever seen the eye of a fly. But he ran into some problems because the way, even with a sincere hand and faithful eye, the way the light hit the om-matidia of the eye changed the structure in his microscope. It kind of played tricks on him. One of the most famous images is this image of cork. It reminded him of cells that monks live in. It was the very first time that the word cell was used in a biological context. And again, another common creature of the time was the flea, which was very common in 1660. This book was incredibly popular. It was a best-seller of the time. Samuel Pepys said that once he bought it, he couldn't put it down. 

He stayed up the whole night reading the book. It was because people had never seen such-- It was a whole new world to them of organisms. The power of imaging. So Robert Hooke was kind of a polymath. He invented many, many things. There's Hooke's lure, the sash window, the watch spring. Many, many improvements to barometers, telescopes, microscopes. All part of the Royal Society. Isaac Newton actually read Micrographia when he was in Cambridge at college. Hooke and Newton kind of fought over the years, mainly because Hooke accused Newton of stealing some of his ideas from Micrographia to put into his Principia. 

This is actually the present president of the Royal Society, Paul Nurse, and the portraits of Robert Boyle and Isaac Newton. I don't know which is which, but it doesn't really matter. But upon Hooke's death, Newton supposedly burned all of Hooke's portraits. There are no portraits of Hooke left. There was a stained glass window in a church in London. That was blown out by an IRA bomb in the '90s, I guess. So there are no faithful reproductions of Hooke. In a letter from Newton to Hooke he sarcastically says, "If I have seen further, it is by standing on the shoulders of giants." This was after Hooke had accused taking some of his data. Let's move on a couple of hundred years. Charles Darwin was also a pretty good microscopist, and he took a microscope on the Beagle with him. 

It was a very simple, aquatic microscope. This is portrait, one of several  portraits, of Charles Darwin. This is a young Charles Darwin about the age that he would have been when he went on the Beagle. He would dredge up samples from the ocean and look at micro-organisms in his aquatic microscope. But when he got back to England-- These are some of his original slides that were sent back from his trip to South America. They're sections of bones from various animals that he collected samples from. But when he got back to England, he spent a lot of time with a new compound microscope. He was really excited, "My new microscope has come home and I am delighted with it. It really is a splendid plaything." That was in 1847, when he was working on his famous barnacle work. He did a lot of microscopy. 

This microscope cost the princely sum of 34 pounds, which is about $50 now, or so. At that time, it was the top of the line and very expensive. This is one of his high magnification lenses. This is an eyepiece that he had designed with a little graticule in it that he would use for measuring the size of the barnacles. He was interested in doing scientific experiments with these. Here's some of his original barnacle slides that he made. You can still look at them, in a regular microscope. Here are some of the drawing of barnacles from his work. At that time, among microscopists, there was a debate raging as to whether you should use high-power in conjunction with low-power imaging. Most people wanted to just use low-power and not high-power. 

But Darwin had a strict sense about the use of the microscope. He thought that using high-powers without using low-powers was injurious to natural philosophy. Of course, as Kevin was saying, we move between many different scales now, and it's absolutely essential to go from high-power to low-power. This philosophy applies today. This is some work that I did maybe 15 years ago with a colleague, Jim Williams, in Sean Carroll's lab. This is a low-power image of a wing-imaginal disc. This is the tissue that's going to develop into a fruit fly, a fruit fly wing. If we look at it at 16X it looks to be a little, kind of, bright spot, down here at 16X. But if we look at it at a higher resolution, at 60X, then we can see cellular details. Indeed, notice that some of the cells are brighter than the others. 

I'm going to spend a little bit of time talking about the modern image as compared to the older images. Documenting the images, or collecting the images-- I obviously didn't draw this image. I didn't actually photograph the image. It's actually a digital image taken with a confocal microscope. It's a digital image. In fact, photography at the turn of the century, when photography was first introduced, microscopists were reluctant to actually use it. One of the reasons being that it was black and white. Then other being kind of more philosophical in that some of the early photographs people claimed to have seen spirits in the background of the photographs. So scientists would say, well, if you can spirits, how can our results be true. Most cells, well, all cells, are pretty much colorless. 

So we need a method of adding contrast. Here I'm using fluorescence. But in the early days people would use non-specific dyes. This is a typical section of, actually, as onion, stained with, I think, methylene blue. It show the chromosomes and dividing cells. Chromosomes are called chromosomes because they were first seen because they took up dye. Now we are able to use more specific labels. This is actually a double labeled sample. In red, it's a gene product called wing disc, which is telling these cells that they're going to be the actual margin of the fruit fly wing. Then the green cells are actually-- This fly has been genetically engineered to express wing disc in the wrong place. 

We use the green cells, which are tagged with a different dye, to figure out where the cells that are being expressed in the wrong place are. It's one was of figuring out the function of genes. This is 15 years ago. One of the problems with fluorescence is, if you look at fluorescence in a regular epifluorescence microscope at a structure that has any three-dimensionality, you cannot actually see structures. I'm going to turn to my third biologist which is John White, who around 1987 came up with the laser scanning confocal microscope. The design is kind of the basis of-- many of the microscopes of today are bases upon this design. This is John in 1987 at one of his first actual Bio-Rad MSC-500 laser scanning microscope. His favorite sample would be the C. elegans. This is from one of his patents of the scan head on top of the microscope. It's a good job that the box is actually closed because, I have no idea what goes on inside that box. 

This is from their original, their first, paper on the application of laser scanning confocal microscopy to biology. This paper actually took the world by storm. Everybody wanted a laser scanning confocal microscope at that time. I was working at the microscopy facility. It wasn't called LOCI at that time. We bought one of instruments and I was responsible for it. Everybody wanted to use it. It was so, so busy. With the microscope you could cut optical sections. You could collect optical sections. 

This is taken with a 60X lens of a mitotic spindle. You can move the actual plaque sections at submicron intervals. Then we were able to perform multiple label imaging, and label with more than one fluorophore. This is a more advanced instrument which had three detectors, which were able to detect three different wavelengths. Then you can put the image together. This is some work we did about 15 years ago now using that microscope. This is a more modern scan head. The electronics and mirrors are even more improved. This image is from Mark Ellisman's lab, but it just shows that beauty of what you can do with some of these multiple-labeled images. This is a butterfly embryo that we collected, a butterfly wing disc. 

These bright spots here are marking regions of the wing disc where the eyespots are going to form in the adult animal. Another triple-labeled image of a fruit fly wing nerve cells. The ultimate goal is to-- This image is actually fixed and stained. But the ultimate goal, as Kevin said, is look at living cells. Now if we were doing this experiment, we be using the green fluorescent protein that Kevin mentioned before. The advantage of it is that we can look at gene expression in living cells. This is an example of wing disc development in the fruit fly pupa. You might see the discs developing right at the end. These things are the legs developing, and there come the wing discs. So now we are able to see these gene expressions, patterns, in real time. 

John White also, along with Brad Amos, developed a technique called multiphoton microscopy which enables you to image living cells more easily, and cells more deeply into the animal. This is some work that was done in Evan's lab, or John's lab. This is using multiphoton imaging to look at embryonic development, and then the proof of the pudding is in the eating. This little hamster is called Laser. You have one, two, three, four, five-- You have seven images of Laser at different stages of development. Then Laser went on to have babies of her own. That's always a good test of an imaging experiment is if the cells survive. Just one more thing before I hand it back to Kevin. Remember I told you about Robert Hooke developing tiny lenses. Now as Brad Amos is now developing a giant lens, which enables you to view large things over great areas at high resolution. 

This lens is about the size of a coffee can, which is necessary to collect all the light. This is just a movie of-- there we go. Go on. This is a movie from Brad of a field of cells. You can collect, just with one shot, the whole field of cells, and then zoom in. The resolution is such that you can see exquisite resolution at any part of the field. The image file is massive. And there are lots of problems to work out, but this is one of the future ways of imaging. It's kind of neat. Brad took a image of Hooke's flea using his microscope on the left, and then probably it took Brad maybe 10 seconds to take image. 

Whereas I don't know how long it took Robert Hooke to draw that one, but-- Things have come a long way in 350 years. I'll hand it back to you.  >> All right, well, thank you Steve. I hope you got some idea of how engineering has really contributed through the years of microscopy. Now we're going to fast-forward to now. Where are we now? We at a very exciting time in the engineered image, that we really can take advantage, not only of the pretty powerful images you saw that Hooke and others did using their naked eye, but using the lens's magnification. We hope to go beyond magnification. We hope to go to another level. With the type of imaging that's being done in the field right now all across campus, at many, many facilities like the Keck Microscopy Facility, labs like the Waisman, and many labs across campus, we're using techniques allowing us to not only collect an image, that drawing you saw, but collect it over time. So instead of just drawing, you know, that mite or that bedbug or that louse, we want to watch it develop as it happens. 

We now have the ability to collect over time. But we also have the ability, which we won't have time to talk about, we can surprisingly also collect information about chemistry. We have new kinds of detectors that not only can see what you see with your eye, but can measure things like PH and changes that happen in the microenvironment. We have the ability to collect chemistry as well. If you're interested, come talk to me afterward. This is one example where we can actually map to things you can see, color, chemical changes. So things that happen in your microenvironment such as changes in PH. We can also collect, and this is a big, big frontier, the physics of the image. What I mean by that is way that light interacts with tissue isn't just passive. Things change, things go different directions, light bounces off of things. 

If start understanding that, we've found that, for example in cancer, we can understand how a tumor is different from normal tissue. There's a lot of power to that. Also, obviously, looking at the structure. which is what Hooke did, trying to get an image of the structure. But beyond just a flat image we want to see three dimensions. We can use light to actually go into the sample, without a knife, it's an optical section. We can actually peer in 3-D. So optical microscopy give us the ability to look at things over time, the dynamics, the chemistry, the physics and the structure. Supporting technology is what engineers make. It's hardware, it's using advanced processors, the same ones as in your cell phone, the ones in your graphics card, new processors, new types of software, new types of -- techniques including ones that were developed for other fields, including fly-through weather and other techniques. 

And then data management. The same thing that Google uses and other people use to manage data, we're also trying to push the field. It's all because of an image like this. We love pretty images, don't get me wrong, we still want a pretty picture. We're still very much swayed by that. But can this pretty picture of cell division be more than a pretty picture? Can it be a measurement? Can I start understanding what does this mean that this is green and these are red, that some are brighter and dimmer? What type of information can one collect? Really, what it's about is we need computer techniques, informatics. That's a big, big theme of the field, is that when I started my lab almost 12 years ago, the group had maybe, I don't know, 10%, 20% of the group was computer research. Now it's about 80. We can't do this work without software and advanced engineering approaches. They're software based. 

That can be for looking at organelles and cells, for drug discovery, the physiology of an animal or even in viva, in an intact sample. I'm biased of course, but my colleagues and I, we think we're in the Golden Age of optical microscopy. Now, we're biased, so keep that in mind. But basically the reason is that we had this tremendous revolution in the gene sequencing. We have the parts lists to most of the animals you know. For the human, the fly, the fish and so on, the worm. We are continuously sequencing more. In fact, we're now even sequencing individual humans to see the differences. But it's like knowing the parts list to you car, as Steve was saying. It's one thing if somebody gave me a list of all the parts. 

But if I don't know what they do-- I need to drive the car. If you drove your car with like the carburetor missing or the muffler missing, or the steering wheel, you pretty quickly figure out what's wrong. That's what we do as microscopist, we often remove things and see, hey, does it drive differently? That's the power on imaging. The reason that optical microscopy is so powerful is that we have this embarrassing richness of techniques. We have this ability to have genetic paintball of all different colors. Roger Tsien all a couple of other people have developed this amazing library of fluorophores. Scott Gilbert, is mentioned earlier, he's the next speaker. He is also an amazing microscopist as well. There's a lot of things you can do. We have all sorts of microscopes that allow us to separate out different colors. 

We have advanced detectors that can tell apart one color from another of many colors. We also have the ability to look at these new complex fluorescence phenomenon, like the chemistry, and so on. As well, practical things. We've made it easier to work with live cells. We can keep cells happy on a microscope. We figured out what temperature they need. Do they need gas? What type of nutrients they need to keep them happy. We can make an images for long periods of time. We also figured out, the same way that light damages your skin, we figured out the wavelengths that can kill cells. So we found ideal wavelengths of light, the right type of spectra of light. 

For example, room lights are not good for cells. We found the right types of wavelengths we can use. Then practical ways of applying these. And fewer trade-offs. We can be high-content. That means rich in information. High resolution, high through-put, being really fast over long periods of time. When I started in the field almost 20 year ago, or 15 years ago, we couldn't do that. We had to choose one verses the other. Or a couple of them. 

The idea of motorization was having students automate the microscope. Now we actually have motors. The field's come a long way even the short time I've been involved. What kind of information can you provide? Well, imaging is the only way to access spatial and structural information together. The other techniques you hear about really don't give you the ability to actually get to that localization of time and structure. Also we have the ability of multiplexing. That's just a fancy word for saying that we can label structures. We can actually use that giant paintball technique to have color and tell us where things go. If I'm looking for a gene of interest, if I want to see if a gene is involved in cancer or in cell division, if I'm able to color and see it express later, I know that gene was there. It's like the smoking gun. 

And the ability to do this over time. The opportunities are huge. More insight from fewer experiments. It means that we can use, by animals, rats and mice to worms. We can use less animals and have a better understanding. We can have a faster path to systems level understanding. What I mean by that is that we want to go from the cells in the dish to us. We want to understand how that's relevant to the whole system. And automation and discovery. The idea that you can look for drugs and new phenomenon, quickly. 

Companies in town and other places are testing new drugs on dishes of cells and trying to see what happens in an automated context.  This is PowerPoint gone crazy. But basically we want to understand that we want to look at structural measurements and how these structures relate. We want to look at the dynamics of structures. How did a structure come to be? If I see a membrane form, how did that happen, why did it happen? We want to see functional measurements. Be able to measure and put markers in for different genes, like a green color or a red color, tag different genes to see what they do. And then what are the dynamics between two different fluorofores when they're tagged to a gene? What happens to them? What do these two genes do? How do they interact? We can use this color the same way that if you put jerseys on different football players, you could tell them apart and see how they interact. We're trying to do the same thing. I use lots of analogies, so hopefully it makes sense. Then structure and function. 

How do structure and function relate? The structure, the physical structure, how does that relate to what it does. Then, as well, we want to see how that changes over time. How does structure and function relate to time, so development. Ultimately, the holy grail is something that Steve and I both are very passionate about. It's how this came to be. How it's evolved. How did these processes happen? Why is cell division the same in C. elegans, this little worm, as it is in me? Why? That's the thing we're pursuing. So, the needs and challenges, and this is why we need good engineers, computer engineers, electrical engineers, biomedical engineers, is the complexity of the data. It's visual and quantitative. It is a mingling of space and time to other dimensions you can't see with your eye. 

It's huge. It's big data, and ways of compressing it. Not only is it big on your hard drive, but it's big for your brain to understand, because it's multi-dimensions. So, you need ways of managing the data. You need good ways of sharing the data and backing it up, also ways of visualizing it. Also, so many different types of measurements you can take. There can be structure measurements, function measurements and dynamic. So, I thought toward the end here, I'd give one example of the future. As you can probably tell, Steve and I are excited about our work. We could keep you here all night, but we won't, unless you want us to. 

But we will give one example of where we're going. So far, you've seen pictures of fleas and lice and C. elegans, but you're like, how does this relate to me? What does that mean? Sure, we're using it as a basilar modelism, but where is the engineered image going? The exciting thing is that we're now starting to take the information that we're learning from cells and actually applying it to humans. In our lab, and in many other labs on campus, we're working on trying to understand how these stem cells differentiate, how these beating heart cells I showed, how they came to be. What are the cues that actually could coax the cell to be become the right type of cell that I could use for transplants or use for therapy? I'm going to give one example. I thought it'd be a fun one, about work on cancer. In particular, our work in trying to understand how cancer invades, breast cancer. We call this the engineered image, imaging breast cancer highways. So one of the really scary things about any type of cancer, and particularly breast cancer, is not the tumor, but it's the metastasis. It's how the cancer spreads. That's what kills you, how cells invade and they spread. 

If it's a localized tumor, we've gotten very good at either treating it with advanced techniques like Rock Mackie's Tomo Therapy. That was developed here in town. He's a great engineer we collaborate with. Or, surgery or other types of therapies, radiation therapy, they've gotten very good at getting rid of the tumor. But when it spreads, that unfortunately, is what makes the treatment very, very hard, and in some cases not treatable. So our interest is why these cells invade, what tells them to invade, why do some people have localized tumors and other people have tumors spread? What tells the cells it's time to invade, to leave this niche they made, this tumor niche, and invade they body? Why do they do it? If we could figure that out, we maybe could stop that. We could develop drugs and ways of stopping that, and doing it. So, we call this the highway, because interestingly enough, cancer hijacks normal things in our body, and in particular, a network that is based on collagen. I'll talk about this. But basically, as you see here, the same way. 

I was just in California and I got to experience gridlock for the first time in a long time, and it's really bad. I missed Madison. But basically, in gridlock where you're a car on the road, and you're interacting with the road and other cars, the same thing with cancer cells. Due to other traffic, they interact with other cancer cells and normal cells. They interact here. You can see the car on the road. These are the collagen fibrils, and these are the cells, but you understand what goes on. So to give you some context, this is our work on breast cancer. The classic breast cancer is to use something like ultrasound and MRI that would give you images where you can understand the density of a breast. So, it's known that one of the major risk factors for women is how dense the breast is. 

The density of the breast is known to be very important to survival and cancer risk, and yet, we don't have any clinical way to exploit it. We know that density is important, but we don't know what to do about it. There's not currently a clinically accepted method to go after it. In part because we don't understand what it means. Why does a dense breast have a higher chance of poor prognosis for cancer? That's what we're working on with many investigators, particularly Patty Keely, who is a breast cancer biologist and Lee Wilke, who's a breast cancer surgeon, and Rock Mackie, who's an engineer. So we're looking at the density of the breasts and trying to understand what happens. You can see in this higher dense breast, how it really looks quite a bit different on the right versus the left. This is the one we're worried about for cancer risk. Well, it turns out that it's understood that it's collagen that is behind this. So collagen is a structural protein that we want to go after. 

You may have heard of collagen. It's used for cosmetic purposes. It's in our body. It's the most abundant protein. It's actually Greek for glue producer. It is the glue or highway that connects our body. Without collagen, we wouldn't be the way that we are. We need collagen. It has this amazing structure to it. It's a very beautiful protein. 

It's this wavy quality of collagen that gives it both strength and the ability to stretch. So, you could not be here without collagen. You absolutely need it. But unfortunately, it's been shown by many, many people, and the UW is one of the leaders in this, that cancer has been very smart, and it can actually hijack this. It can take advantage of this mechanical property and use the collagen like a road to escape where the tumor is and go out. We're going to show what we're doing with that with microscopy. So, we want the Google Street View of cancer. My clinical collaborator came up with this, but I apologize. [laughter] So, we want to look at the traffic lights, who are the regulators of cell growth. You look at this image here of this time lapse. 

These are the regular cell growth. These are what tells cells to grow or not grow. This streets are the collagen, and the cars are the cells, including tumor cells, and this we want to go after. The reason we need the imaging method that we do, that Steve has talked about and I have talked about, is that we don't want to just take a snapshot in time and say that's cancer, that's invading. We want to have, not the traffic light camera that shows a speeding car go through, we want to have a movie camera that watches all the cars go through and records all of them. That's what we're doing. Our technique will allow us to watch the highways for a long period of time, but watch not just all the highways. We want to be from above in a helicopter. We don't want to be down low, so we can actually see the cars on the road. That's why we have to use our technique, because you want cell resolution over time, and that's why you need light microscopy. 

So, traditionally, this image on the left is what you get if you went to the doctor for a test. You can see some collagen here, but it's kind of hard to make out. What we need is a new imaging modality that doesn't require a knife, that doesn't require stains. The gold standard of pathology is staining, where you take a knife, like if you had a mole that they biopsied. They'd take a little piece off and stain it and look at it. We want to go beyond that. So for that, we have built-in some requirements. It's got to be compatible with clinical specimens. We have to see these highways in whatever sample we can get from the doctor. We also don't want to use dyes or stains. 

They've got to be high resolution, submicron, so we can see an individual cell. It's got to be capable of imaging deep in tissue. We've got to see 3-D, because these highways are not just flat. They go like this. They go different directions. And it's got to be able to tell cancer cells apart from normal cells. Most importantly, it's got to be able to tell us where the highways are, where there are roads of collagen. So, we're fortunate that we have a technique that can do that. But that technique was totally due to an engineering effort. This will give you an idea of the type of people involved. 

Engineers make this happen. There's engineers, such as Paul Campagnola, and Rock Mackie, and Dave Beebe, and our postdocs and students. Biologists like Patty Keely, and Ray Sullivan. To me, who just pays the bills, to people that visualize techniques and trying to use computer techniques to render things, to clinicians like Lee Wilke, who's a surgeon, and Andreas Friedl, who's a pathologist. So, when you think of the engineered image, we use that term very freely, but it means engineers of all different types, quantitative scientists who are coming together. It took a whole team to do this study. So what did we do? We found that we can actually use a new method that Steve briefly referred to, based on our work, and also John White contributed to this, being able to use multi-photon imaging. Just think of it as a fancy type of light microscopy that can image deep in to an intact environment without a knife. We can actually see into my arm, and see live cells, what they do, using benign light, light that doesn't kill, light that doesn't hurt. We can actually see cells as they go. 

That's what we're using. You can see here some idea of what we can see, the collagen and the tumors here. The benefits of this technique is it can directly visualize the collagen and the architecture. The same way that the road tonight really dictates how fast I get home, if it's slippery or if it's curved, we understand that. But the road analogy is not quite right, because what we've found that's real exciting is that tonight, if I want to get home quicker, I can't redirect the road to my house. I can't say the Beltline is now going to go from here to my home, no matter how much I want it to. Cancer can. It can actually tell the highway to re-lay down a more direct route to go somewhere else, usually to invade. That's the part that scares us, and also intrigues us. We want to understand why so we can block that. 

It's selective for cancer cells versus collagen, high resolution, and go deep. You can see some of the images. This is a cartoon to help you out a little bit, and this is the real data. We have found that there's these different stages, we call them signatures of where the cancer cells interact with the collagen. The only one to focus on is the bottom one. This is the one that scares us. This is where the collagen all of a sudden starts branching out like roads, leading away from the tumor. We have movies where the cells actually start climbing along and escaping. That's what we want to go after. This is a better cartoon showing that this TACS thing that we call a TACS-3 is what we're going after, showing cells escaping. 

The neat thing is we've done this in animal models. We looked at rats and mice. We've done it in humans. We did a very large study that was published, where we compared, this is classic pathology. These images got flipped, actually, so this should be here and that should be there. You see the shape of this? That's that. And this is that. We want to understand the interaction of the collagen with the micro environment. We published a paper with all these collaborators in pathology, that we were able to prove that by looking at over 200 women, so volunteers, people that were willing to help us, tissue that was donated or tissue that was gotten for other purposes. We actually show that this actually was a biomarker for survival, that just looking at these little changes in collagen on a little microscope slide, can tell us something about how that patient is going to do and survive. 

That is what motivates us. It's exciting to us. That's something that you can really do uniquely with light microscopy, this engineered approach, if we can quantitate these changes in collagen, we then can develop screening assays. By that I mean multiple dishes with all these cells doing their thing in these collagen networks, and try different drugs to see if we can block that, and then eventually use that in a human. We're also developing new microscopes, so we always welcome, by the way, like many people on campus, we're very open to visitors. If you want to visit my lab, we're full of lots of big microscopes. This is one of those we built. We love visitors. This is a more modern one we're building. We're now working with Rock and others, trying to build compact, portable setups. 

So, the advantage of these new ones is they're very small and portable. We're also trying now to look at endoscopes. Can we do this through a fiber optic? Can we have a little probe that look in an intact human? So, in the interest of time, I have one more slide. We also want to understand in vitro models. We're now trying to create in vitro environments, almost like Jell-O, that approximate the breast. Not for drug screening, we built a 3-D model. This is a collagen network that we actually can map based on real data from a breast. So, we're not limited to just looking at human data. We can take the human data, we now can build networks, first in silico, but then in a dish, and we can actually have an in vitro breast model where then we can do drug screening, and we can see the 3-D model of all the collagen highways. I'll end there, just some more pretty images, everything from looking at cancer cells, to 3-D cells from a lab here on campus, to images of collagen from Paul Campagnola. 

With that, I thank you. [applause]