1 00:00:02,420 --> 00:00:03,643 I live in Utah, 2 00:00:03,667 --> 00:00:06,577 a place known for having some of the most awe-inspiring 3 00:00:06,601 --> 00:00:09,143 natural landscapes on this planet. 4 00:00:09,167 --> 00:00:12,624 It's easy to be overwhelmed by these amazing views, 5 00:00:12,648 --> 00:00:16,513 and to be really fascinated by these sometimes alien-looking formations. 6 00:00:16,537 --> 00:00:20,195 As a scientist, I love observing the natural world. 7 00:00:20,219 --> 00:00:21,973 But as a cell biologist, 8 00:00:21,997 --> 00:00:24,791 I'm much more interested in understanding the natural world 9 00:00:24,815 --> 00:00:27,077 at a much, much smaller scale. 10 00:00:27,934 --> 00:00:30,713 I'm a molecular animator, and I work with other researchers 11 00:00:30,737 --> 00:00:33,633 to create visualizations of molecules that are so small, 12 00:00:33,657 --> 00:00:35,252 they're essentially invisible. 13 00:00:35,276 --> 00:00:38,138 These molecules are smaller than the wavelength of light, 14 00:00:38,162 --> 00:00:40,407 which means that we can never see them directly, 15 00:00:40,431 --> 00:00:42,495 even with the best light microscopes. 16 00:00:42,519 --> 00:00:44,645 So do I create visualizations of things 17 00:00:44,669 --> 00:00:46,641 that are so small we can't see them? 18 00:00:46,665 --> 00:00:48,823 Scientists, like my collaborators, 19 00:00:48,847 --> 00:00:50,926 can spend their entire professional careers 20 00:00:50,950 --> 00:00:53,522 working to understand one molecular process. 21 00:00:53,546 --> 00:00:56,014 To do this, they carry out a series of experiments 22 00:00:56,038 --> 00:00:59,141 that each can tell us a small piece of the puzzle. 23 00:00:59,165 --> 00:01:01,953 One kind of experiment can tell us about the protein shape, 24 00:01:01,977 --> 00:01:03,188 while another can tell us 25 00:01:03,204 --> 00:01:05,505 about what other proteins it might interact with 26 00:01:05,529 --> 00:01:08,441 and another can tell us about where it can be found in a cell. 27 00:01:08,465 --> 00:01:12,474 And all of these bits of information can be used to come up with a hypothesis, 28 00:01:12,498 --> 00:01:15,595 a story, essentially, of how a molecule might work. 29 00:01:16,990 --> 00:01:20,948 My job is to take these ideas and turn them into an animation. 30 00:01:20,972 --> 00:01:22,155 This can be tricky, 31 00:01:22,179 --> 00:01:25,488 because it turns out that molecules can do some pretty crazy things. 32 00:01:25,512 --> 00:01:28,837 But these animations can be incredibly useful for researchers 33 00:01:28,861 --> 00:01:31,657 to communicate their ideas of how these molecules work. 34 00:01:32,020 --> 00:01:34,766 They can also allow us to see the molecular world 35 00:01:34,790 --> 00:01:36,057 through their eyes. 36 00:01:36,377 --> 00:01:38,297 I'd like to show you some animations, 37 00:01:38,321 --> 00:01:41,871 a brief tour of what I consider to be some of the natural wonders 38 00:01:41,895 --> 00:01:43,569 of the molecular world. 39 00:01:43,593 --> 00:01:45,561 First off, this is an immune cell. 40 00:01:45,585 --> 00:01:48,458 These kinds of cells need to go crawling around in our bodies 41 00:01:48,482 --> 00:01:51,537 in order to find invaders like pathogenic bacteria. 42 00:01:51,561 --> 00:01:54,649 This movement is powered by one of my favorite proteins 43 00:01:54,673 --> 00:01:55,839 called actin, 44 00:01:55,863 --> 00:01:58,426 which is part of what's known as the cytoskeleton. 45 00:01:58,450 --> 00:02:00,085 Unlike our skeletons, 46 00:02:00,109 --> 00:02:03,847 actin filaments are constantly being built and taken apart. 47 00:02:03,871 --> 00:02:07,268 The actin cytoskeleton plays incredibly important roles in our cells. 48 00:02:07,292 --> 00:02:09,054 They allow them to change shape, 49 00:02:09,078 --> 00:02:11,466 to move around, to adhere to surfaces, 50 00:02:11,490 --> 00:02:13,926 and also to gobble up bacteria. 51 00:02:13,950 --> 00:02:16,569 Actin is also involved in a different kind of movement. 52 00:02:16,593 --> 00:02:19,776 In our muscle cells, actin structures form these regular filaments 53 00:02:19,800 --> 00:02:21,323 that look kind of like fabric. 54 00:02:21,347 --> 00:02:24,257 When our muscles contract, these filaments are pulled together 55 00:02:24,281 --> 00:02:26,297 and they go back to their original position 56 00:02:26,321 --> 00:02:27,823 when our muscles relax. 57 00:02:27,847 --> 00:02:31,049 Other parts of the cytoskeleton, in this case microtubules, 58 00:02:31,073 --> 00:02:33,779 are responsible for long-range transportation. 59 00:02:33,803 --> 00:02:36,422 They can be thought of as basically cellular highways 60 00:02:36,446 --> 00:02:39,795 that are used to move things from one side of the cell to the other. 61 00:02:39,819 --> 00:02:42,607 Unlike our roads, microtubules grow and shrink, 62 00:02:42,631 --> 00:02:44,052 appearing when they're needed 63 00:02:44,076 --> 00:02:46,449 and disappearing when their job is done. 64 00:02:46,473 --> 00:02:48,893 The molecular version of semitrucks 65 00:02:48,917 --> 00:02:51,474 are proteins aptly named motor proteins, 66 00:02:51,498 --> 00:02:53,958 that can walk along microtubules, 67 00:02:53,982 --> 00:02:56,680 dragging sometimes huge cargoes, 68 00:02:56,704 --> 00:02:58,514 like organelles, behind them. 69 00:02:58,538 --> 00:03:01,410 This particular motor protein is known as dynein, 70 00:03:01,434 --> 00:03:03,836 and its known to be able to work together in groups 71 00:03:03,860 --> 00:03:07,315 that almost look, at least to me, like a chariot of horses. 72 00:03:07,339 --> 00:03:11,172 As you see, the cell is this incredibly changing, dynamic place, 73 00:03:11,196 --> 00:03:14,323 where things are constantly being built and disassembled. 74 00:03:14,680 --> 00:03:16,029 But some of these structures 75 00:03:16,053 --> 00:03:18,156 are harder to take apart than others, though. 76 00:03:18,180 --> 00:03:20,093 And special forces need to be brought in 77 00:03:20,117 --> 00:03:23,562 in order to make sure that structures are taken apart in a timely manner. 78 00:03:23,586 --> 00:03:26,305 That job is done in part by proteins like these. 79 00:03:26,329 --> 00:03:27,860 These donut-shaped proteins, 80 00:03:27,884 --> 00:03:29,892 of which there are many types in the cell, 81 00:03:29,916 --> 00:03:31,995 all seem to act to rip apart structures 82 00:03:32,019 --> 00:03:35,384 by basically pulling individual proteins through a central hole. 83 00:03:35,408 --> 00:03:37,965 When these kinds of proteins don't work properly, 84 00:03:37,989 --> 00:03:40,719 the types of proteins that are supposed to get taken apart 85 00:03:40,743 --> 00:03:43,180 can sometimes stick together and aggregate 86 00:03:43,204 --> 00:03:47,084 and that can give rise to terrible diseases, such as Alzheimer. 87 00:03:47,419 --> 00:03:49,426 And now let's take a look at the nucleus, 88 00:03:49,450 --> 00:03:52,403 which houses our genome in the form of DNA. 89 00:03:52,427 --> 00:03:53,847 In all of our cells, 90 00:03:53,871 --> 00:03:58,164 our DNA is cared for and maintained by a diverse set of proteins. 91 00:03:58,188 --> 00:04:01,006 DNA is wound around proteins called histones, 92 00:04:01,030 --> 00:04:05,338 which enable cells to pack large amounts of DNA into our nucleus. 93 00:04:05,362 --> 00:04:08,441 These machines are called chromatin remodelers 94 00:04:08,465 --> 00:04:11,203 and the way they work is that they basically scoot the DNA 95 00:04:11,227 --> 00:04:12,426 around these histones 96 00:04:12,450 --> 00:04:16,347 and they allow new pieces of DNA to become exposed. 97 00:04:16,371 --> 00:04:19,307 This DNA can then be recognized by other machinery. 98 00:04:19,331 --> 00:04:21,856 In this case, this large molecular machine 99 00:04:21,880 --> 00:04:23,570 is looking for a segment of DNA 100 00:04:23,594 --> 00:04:25,903 that tells it it's at the beginning of a gene. 101 00:04:25,927 --> 00:04:27,616 Once it finds a segment, 102 00:04:27,640 --> 00:04:30,402 it basically undergoes a series of shape changes 103 00:04:30,426 --> 00:04:32,528 which enables it to bring in other machinery 104 00:04:32,552 --> 00:04:36,242 that in turn allows a gene to get turned on or transcribed. 105 00:04:36,704 --> 00:04:39,791 This has to be a very tightly regulated process 106 00:04:39,815 --> 00:04:42,617 because turning on the wrong gene at the wrong time 107 00:04:42,641 --> 00:04:45,283 can have disastrous consequences. 108 00:04:45,307 --> 00:04:48,117 Scientists are now able to use protein machines 109 00:04:48,141 --> 00:04:49,545 to edit genomes. 110 00:04:49,569 --> 00:04:52,013 I'm sure all of you have heard of CRISPR. 111 00:04:52,037 --> 00:04:54,863 CRISPR takes advantage of a protein known as Cas9, 112 00:04:54,887 --> 00:04:57,823 which can be engineered to recognize and cut 113 00:04:57,847 --> 00:05:00,212 a very specific sequence of DNA. 114 00:05:00,236 --> 00:05:01,395 In this example, 115 00:05:01,419 --> 00:05:05,514 two Cas9 proteins are being used to excise a problematic piece of DNA. 116 00:05:05,538 --> 00:05:09,019 For example, a part of a gene that may give rise to a disease. 117 00:05:09,043 --> 00:05:10,530 Cellular machinery is then used 118 00:05:10,554 --> 00:05:14,067 to basically glue two ends of the DNA back together. 119 00:05:14,091 --> 00:05:15,337 As a molecular animator, 120 00:05:15,361 --> 00:05:18,383 one of my biggest challenges is visualizing uncertainty. 121 00:05:18,720 --> 00:05:22,029 All of the animations I've shown to you represent hypotheses, 122 00:05:22,053 --> 00:05:24,294 how my collaborators think a process works, 123 00:05:24,318 --> 00:05:26,680 based on the best information that they have. 124 00:05:26,704 --> 00:05:28,672 But for a lot of molecular processes, 125 00:05:28,696 --> 00:05:31,672 we're still really at the early stages of understanding things, 126 00:05:31,696 --> 00:05:33,038 and there's a lot to learn. 127 00:05:33,062 --> 00:05:34,212 The truth is, 128 00:05:34,236 --> 00:05:38,767 that these invisible molecular worlds are vast and largely unexplored. 129 00:05:39,474 --> 00:05:41,508 To me, these molecular landscapes 130 00:05:41,532 --> 00:05:44,926 are just as exciting to explore as a natural world 131 00:05:44,950 --> 00:05:46,883 that's visible all around us. 132 00:05:47,379 --> 00:05:48,530 Thank you. 133 00:05:48,554 --> 00:05:51,760 (Applause)