1 00:00:02,417 --> 00:00:03,684 I live in Utah, 2 00:00:03,708 --> 00:00:06,559 a place known for having some of the most awe-inspiring 3 00:00:06,583 --> 00:00:09,143 natural landscapes on this planet. 4 00:00:09,167 --> 00:00:12,643 It's easy to be overwhelmed by these amazing views, 5 00:00:12,667 --> 00:00:16,518 and to be really fascinated by these sometimes alien-looking formations. 6 00:00:16,542 --> 00:00:20,184 As a scientist, I love observing the natural world. 7 00:00:20,208 --> 00:00:21,976 But as a cell biologist, 8 00:00:22,000 --> 00:00:24,809 I'm much more interested in understanding the natural world 9 00:00:24,833 --> 00:00:27,042 at a much, much smaller scale. 10 00:00:27,917 --> 00:00:30,726 I'm a molecular animator, and I work with other researchers 11 00:00:30,750 --> 00:00:33,643 to create visualizations of molecules that are so small, 12 00:00:33,667 --> 00:00:35,268 they're essentially invisible. 13 00:00:35,292 --> 00:00:38,143 These molecules are smaller than the wavelength of light, 14 00:00:38,167 --> 00:00:40,406 which means that we can never see them directly, 15 00:00:40,430 --> 00:00:42,476 even with the best light microscopes. 16 00:00:42,500 --> 00:00:44,643 So how do I create visualizations of things 17 00:00:44,667 --> 00:00:46,643 that are so small we can't see them? 18 00:00:46,667 --> 00:00:48,809 Scientists, like my collaborators, 19 00:00:48,833 --> 00:00:50,934 can spend their entire professional careers 20 00:00:50,958 --> 00:00:53,518 working to understand one molecular process. 21 00:00:53,542 --> 00:00:56,018 To do this, they carry out a series of experiments 22 00:00:56,042 --> 00:00:59,143 that each can tell us a small piece of the puzzle. 23 00:00:59,167 --> 00:01:01,934 One kind of experiment can tell us about the protein shape, 24 00:01:01,958 --> 00:01:03,226 while another can tell us 25 00:01:03,250 --> 00:01:05,536 about what other proteins it might interact with, 26 00:01:05,560 --> 00:01:08,465 and another can tell us about where it can be found in a cell. 27 00:01:08,489 --> 00:01:12,476 And all of these bits of information can be used to come up with a hypothesis, 28 00:01:12,500 --> 00:01:15,583 a story, essentially, of how a molecule might work. 29 00:01:17,000 --> 00:01:20,934 My job is to take these ideas and turn them into an animation. 30 00:01:20,958 --> 00:01:22,226 This can be tricky, 31 00:01:22,250 --> 00:01:25,476 because it turns out that molecules can do some pretty crazy things. 32 00:01:25,500 --> 00:01:28,851 But these animations can be incredibly useful for researchers 33 00:01:28,875 --> 00:01:31,976 to communicate their ideas of how these molecules work. 34 00:01:32,000 --> 00:01:34,768 They can also allow us to see the molecular world 35 00:01:34,792 --> 00:01:36,351 through their eyes. 36 00:01:36,375 --> 00:01:38,309 I'd like to show you some animations, 37 00:01:38,333 --> 00:01:41,851 a brief tour of what I consider to be some of the natural wonders 38 00:01:41,875 --> 00:01:43,559 of the molecular world. 39 00:01:43,583 --> 00:01:45,559 First off, this is an immune cell. 40 00:01:45,583 --> 00:01:48,476 These kinds of cells need to go crawling around in our bodies 41 00:01:48,500 --> 00:01:51,518 in order to find invaders like pathogenic bacteria. 42 00:01:51,542 --> 00:01:54,643 This movement is powered by one of my favorite proteins 43 00:01:54,667 --> 00:01:55,934 called actin, 44 00:01:55,958 --> 00:01:58,434 which is part of what's known as the cytoskeleton. 45 00:01:58,458 --> 00:02:00,101 Unlike our skeletons, 46 00:02:00,125 --> 00:02:03,851 actin filaments are constantly being built and taken apart. 47 00:02:03,875 --> 00:02:07,268 The actin cytoskeleton plays incredibly important roles in our cells. 48 00:02:07,292 --> 00:02:09,059 They allow them to change shape, 49 00:02:09,083 --> 00:02:11,476 to move around, to adhere to surfaces 50 00:02:11,500 --> 00:02:13,934 and also to gobble up bacteria. 51 00:02:13,958 --> 00:02:16,559 Actin is also involved in a different kind of movement. 52 00:02:16,583 --> 00:02:19,768 In our muscle cells, actin structures form these regular filaments 53 00:02:19,792 --> 00:02:21,309 that look kind of like fabric. 54 00:02:21,333 --> 00:02:24,268 When our muscles contract, these filaments are pulled together 55 00:02:24,292 --> 00:02:26,309 and they go back to their original position 56 00:02:26,333 --> 00:02:27,809 when our muscles relax. 57 00:02:27,833 --> 00:02:31,059 Other parts of the cytoskeleton, in this case microtubules, 58 00:02:31,083 --> 00:02:33,768 are responsible for long-range transportation. 59 00:02:33,792 --> 00:02:36,434 They can be thought of as basically cellular highways 60 00:02:36,458 --> 00:02:39,809 that are used to move things from one side of the cell to the other. 61 00:02:39,833 --> 00:02:42,601 Unlike our roads, microtubules grow and shrink, 62 00:02:42,625 --> 00:02:44,059 appearing when they're needed 63 00:02:44,083 --> 00:02:46,434 and disappearing when their job is done. 64 00:02:46,458 --> 00:02:48,893 The molecular version of semitrucks 65 00:02:48,917 --> 00:02:51,476 are proteins aptly named motor proteins, 66 00:02:51,500 --> 00:02:53,976 that can walk along microtubules, 67 00:02:54,000 --> 00:02:56,684 dragging sometimes huge cargoes, 68 00:02:56,708 --> 00:02:58,518 like organelles, behind them. 69 00:02:58,542 --> 00:03:01,393 This particular motor protein is known as dynein, 70 00:03:01,417 --> 00:03:03,851 and its known to be able to work together in groups 71 00:03:03,875 --> 00:03:07,309 that almost look, at least to me, like a chariot of horses. 72 00:03:07,333 --> 00:03:11,184 As you see, the cell is this incredibly changing, dynamic place, 73 00:03:11,208 --> 00:03:14,643 where things are constantly being built and disassembled. 74 00:03:14,667 --> 00:03:16,018 But some of these structures 75 00:03:16,042 --> 00:03:18,143 are harder to take apart than others, though. 76 00:03:18,167 --> 00:03:20,101 And special forces need to be brought in 77 00:03:20,125 --> 00:03:23,559 in order to make sure that structures are taken apart in a timely manner. 78 00:03:23,583 --> 00:03:26,309 That job is done in part by proteins like these. 79 00:03:26,333 --> 00:03:27,851 These donut-shaped proteins, 80 00:03:27,875 --> 00:03:29,893 of which there are many types in the cell, 81 00:03:29,917 --> 00:03:31,976 all seem to act to rip apart structures 82 00:03:32,000 --> 00:03:35,393 by basically pulling individual proteins through a central hole. 83 00:03:35,417 --> 00:03:37,976 When these kinds of proteins don't work properly, 84 00:03:38,000 --> 00:03:40,726 the types of proteins that are supposed to get taken apart 85 00:03:40,750 --> 00:03:43,184 can sometimes stick together and aggregate 86 00:03:43,208 --> 00:03:47,393 and that can give rise to terrible diseases, such as Alzheimer's. 87 00:03:47,417 --> 00:03:49,434 And now let's take a look at the nucleus, 88 00:03:49,458 --> 00:03:52,393 which houses our genome in the form of DNA. 89 00:03:52,417 --> 00:03:53,851 In all of our cells, 90 00:03:53,875 --> 00:03:58,184 our DNA is cared for and maintained by a diverse set of proteins. 91 00:03:58,208 --> 00:04:01,018 DNA is wound around proteins called histones, 92 00:04:01,042 --> 00:04:05,351 which enable cells to pack large amounts of DNA into our nucleus. 93 00:04:05,375 --> 00:04:08,434 These machines are called chromatin remodelers, 94 00:04:08,458 --> 00:04:11,184 and the way they work is that they basically scoot the DNA 95 00:04:11,208 --> 00:04:12,476 around these histones 96 00:04:12,500 --> 00:04:16,351 and they allow new pieces of DNA to become exposed. 97 00:04:16,375 --> 00:04:19,309 This DNA can then be recognized by other machinery. 98 00:04:19,333 --> 00:04:21,851 In this case, this large molecular machine 99 00:04:21,875 --> 00:04:23,559 is looking for a segment of DNA 100 00:04:23,583 --> 00:04:25,893 that tells it it's at the beginning of a gene. 101 00:04:25,917 --> 00:04:27,601 Once it finds a segment, 102 00:04:27,625 --> 00:04:30,393 it basically undergoes a series of shape changes 103 00:04:30,417 --> 00:04:32,518 which enables it to bring in other machinery 104 00:04:32,542 --> 00:04:36,684 that in turn allows a gene to get turned on or transcribed. 105 00:04:36,708 --> 00:04:39,809 This has to be a very tightly regulated process, 106 00:04:39,833 --> 00:04:42,601 because turning on the wrong gene at the wrong time 107 00:04:42,625 --> 00:04:45,268 can have disastrous consequences. 108 00:04:45,292 --> 00:04:48,101 Scientists are now able to use protein machines 109 00:04:48,125 --> 00:04:49,559 to edit genomes. 110 00:04:49,583 --> 00:04:52,018 I'm sure all of you have heard of CRISPR. 111 00:04:52,042 --> 00:04:54,851 CRISPR takes advantage of a protein known as Cas9, 112 00:04:54,875 --> 00:04:57,809 which can be engineered to recognize and cut 113 00:04:57,833 --> 00:05:00,226 a very specific sequence of DNA. 114 00:05:00,250 --> 00:05:01,518 In this example, 115 00:05:01,542 --> 00:05:05,518 two Cas9 proteins are being used to excise a problematic piece of DNA. 116 00:05:05,542 --> 00:05:09,018 For example, a part of a gene that may give rise to a disease. 117 00:05:09,042 --> 00:05:10,519 Cellular machinery is then used 118 00:05:10,543 --> 00:05:14,059 to basically glue two ends of the DNA back together. 119 00:05:14,083 --> 00:05:15,351 As a molecular animator, 120 00:05:15,375 --> 00:05:18,684 one of my biggest challenges is visualizing uncertainty. 121 00:05:18,708 --> 00:05:22,018 All of the animations I've shown to you represent hypotheses, 122 00:05:22,042 --> 00:05:24,309 how my collaborators think a process works, 123 00:05:24,333 --> 00:05:26,684 based on the best information that they have. 124 00:05:26,708 --> 00:05:28,684 But for a lot of molecular processes, 125 00:05:28,708 --> 00:05:31,684 we're still really at the early stages of understanding things, 126 00:05:31,708 --> 00:05:33,018 and there's a lot to learn. 127 00:05:33,042 --> 00:05:34,309 The truth is 128 00:05:34,333 --> 00:05:38,292 that these invisible molecular worlds are vast and largely unexplored. 129 00:05:39,458 --> 00:05:41,518 To me, these molecular landscapes 130 00:05:41,542 --> 00:05:44,934 are just as exciting to explore as a natural world 131 00:05:44,958 --> 00:05:47,351 that's visible all around us. 132 00:05:47,375 --> 00:05:48,643 Thank you. 133 00:05:48,667 --> 00:05:51,792 (Applause)