1 00:00:05,040 --> 00:00:10,080 IT'S MY PLEASURE TO HAVE HEMALI 2 00:00:10,080 --> 00:00:15,480 PHATNANI A LONG-TERM 3 00:00:15,480 --> 00:00:17,040 COLLABORATOR. 4 00:00:17,040 --> 00:00:20,080 THE DIRECTOR FOR THE CENTER OF 5 00:00:20,080 --> 00:00:24,000 NEURO GENERATIVE DISEASE KNOWN 6 00:00:24,000 --> 00:00:29,000 AT NYGC AND A POINT APPOINTMENT 7 00:00:29,000 --> 00:00:33,000 AT COLUMBIA UNIVERSITY. 8 00:00:33,000 --> 00:00:35,880 SHE HAILS FROM BOMBAY, INDIA AND 9 00:00:35,880 --> 00:00:37,080 LEARNED SHE HAD A 10 00:00:37,080 --> 00:00:40,400 NON-TRADITIONAL PATH TO WHERE 11 00:00:40,400 --> 00:00:41,760 SHE IS TODAY. 12 00:00:41,760 --> 00:00:49,040 SHE AMASSED EXPERTISE IN SEVEN 13 00:00:49,040 --> 00:00:50,120 LANGUAGES INCLUDING GERMAN AND 14 00:00:50,120 --> 00:00:51,920 HER FIRST JOB WAS ACTUALLY TO 15 00:00:51,920 --> 00:00:54,160 TEACH GERMAN TO STUDENTS. 16 00:00:54,160 --> 00:00:57,680 SHE FINALLY MADE HER WAY BACK TO 17 00:00:57,680 --> 00:00:59,720 SCIENCE AND DID HER Ph.D. AT 18 00:00:59,720 --> 00:01:04,040 DUKE UNIVERSITY WHERE SHE 19 00:01:04,040 --> 00:01:07,320 RECEIVED A Ph.D. IN BIOCHEMISTRY 20 00:01:07,320 --> 00:01:09,000 AND MOLECULAR BIOLOGY AND LOOKED 21 00:01:09,000 --> 00:01:10,920 AT TRANSCRIPTION PROCESSING. 22 00:01:10,920 --> 00:01:14,520 SHE THEN CARRIED OUT HER STUDIES 23 00:01:14,520 --> 00:01:16,680 IN HARVARD AND COLUMBIA 24 00:01:16,680 --> 00:01:19,040 UNIVERSITIES WHERE SHE STUDIES 25 00:01:19,040 --> 00:01:22,440 ALS DISEASE MECHANISMS USING 26 00:01:22,440 --> 00:01:28,720 GENOMIC PROFILING METHODS AND 27 00:01:28,720 --> 00:01:32,360 STUDIED INTRINSIC EFFECTS ON 28 00:01:32,360 --> 00:01:39,560 MOTOR NEURONS AND IN 2014 BECAME 29 00:01:39,560 --> 00:01:41,920 CO-DIRECTOR AT NYGC AND NOW THE 30 00:01:41,920 --> 00:01:42,280 DIRECTOR. 31 00:01:42,280 --> 00:01:44,120 THIS GROUP FORMED AN ALS 32 00:01:44,120 --> 00:01:45,000 CONSORTIUM INVOLVING ALLIANCES 33 00:01:45,000 --> 00:01:53,040 WITH CLINICIANS, SCIENCE TESTS 34 00:01:53,040 --> 00:01:55,720 AND PRIMARY PARTNER AND DISCOVER 35 00:01:55,720 --> 00:02:01,080 HOW THEY CAUSE ALS AND DISEASE 36 00:02:01,080 --> 00:02:05,720 AND THE CONSORTIUM LOOKS AT 37 00:02:05,720 --> 00:02:07,160 BIOINFORMATICS AND THE WORK SHE 38 00:02:07,160 --> 00:02:09,000 HAS LED WHILE BEING THE DIRECTOR 39 00:02:09,000 --> 00:02:11,080 THERE HAS BEEN TRANSFORMATIVE 40 00:02:11,080 --> 00:02:13,000 FOR THE FIELD OF ALS GENETICS 41 00:02:13,000 --> 00:02:15,480 AND GENOMICS AND MY GROUP AS 42 00:02:15,480 --> 00:02:17,000 WELL AS MANY OTHERS HAVE 43 00:02:17,000 --> 00:02:18,400 LEVERAGED THESE DISCOVERIES THAT 44 00:02:18,400 --> 00:02:19,800 WERE MADE THERE TO FURTHER 45 00:02:19,800 --> 00:02:21,000 SCIENCE MUCH BROADER THAN THE 46 00:02:21,000 --> 00:02:23,680 IMPACT OF HER OWN INDEPENDENT 47 00:02:23,680 --> 00:02:23,880 WORK. 48 00:02:23,880 --> 00:02:26,640 IN ADDITION TO LEADING THESE 49 00:02:26,640 --> 00:02:30,280 PROJECTS AT NYGC SHE RUNS A 50 00:02:30,280 --> 00:02:31,680 GROUP AS A TENURE TRACK 51 00:02:31,680 --> 00:02:33,200 INVESTIGATOR AT COLUMBIA AND 52 00:02:33,200 --> 00:02:35,360 FOCUSSING ON GENE REGULATORY 53 00:02:35,360 --> 00:02:37,040 MECHANISMS THAT UNDER LIE 54 00:02:37,040 --> 00:02:38,120 COMPLEX INTERACTIONS BETWEEN 55 00:02:38,120 --> 00:02:41,000 MOTOR NEURONS AND IN THE BRAIN 56 00:02:41,000 --> 00:02:43,960 AND SPINAL CORD OF ALS PATIENTS 57 00:02:43,960 --> 00:02:47,960 AND MOUSE MODELS AND APPLIES 58 00:02:47,960 --> 00:02:48,960 BIOINFORMATIC TO UNDERSTAND THE 59 00:02:48,960 --> 00:02:51,080 ROLE OF CELL TO CELL 60 00:02:51,080 --> 00:02:53,760 INTERACTIONS IN PATHOPHYSIOLOGY 61 00:02:53,760 --> 00:02:56,360 AND THERE'S A PAPER PUBLISHED IN 62 00:02:56,360 --> 00:03:01,680 SCIENCE USING A TRANSCRIPTOMICS 63 00:03:01,680 --> 00:03:04,320 METHOD TO CHARACTERIZED ALS 64 00:03:04,320 --> 00:03:08,080 MODELS IN HUMANS AND TISSUES AND 65 00:03:08,080 --> 00:03:10,720 USING SEQUENCERS TO REPURPOSE 66 00:03:10,720 --> 00:03:12,560 THEM TO HIGH THROUGHPUT IMAGING 67 00:03:12,560 --> 00:03:13,360 AND STAINING PLATFORM. 68 00:03:13,360 --> 00:03:15,240 WITH THEY CAN'T WAIT TO SEE WHAT 69 00:03:15,240 --> 00:03:17,000 HEMALI WILL TALK TO US TODAY 70 00:03:17,000 --> 00:03:20,120 ABOUT AND GIVE YOU A WARM 71 00:03:20,120 --> 00:03:28,400 WELCOME TO THE NIH. 72 00:03:28,400 --> 00:03:29,440 >>THANK YOU, MICHAEL. 73 00:03:29,440 --> 00:03:31,680 I'M PLEASED TO BE HERE AND 74 00:03:31,680 --> 00:03:33,680 HAVING A DELIGHTFUL VISIT SO 75 00:03:33,680 --> 00:03:33,840 FAR. 76 00:03:33,840 --> 00:03:36,000 TO RESET EXPECTATIONS IT'S ALL 77 00:03:36,000 --> 00:03:37,280 DOWN HILL FROM HERE. 78 00:03:37,280 --> 00:03:39,280 SO I'M GOING TO BE TELLING YOU 79 00:03:39,280 --> 00:03:43,880 HOW WE USE SPATIAL GENOMICS TO 80 00:03:43,880 --> 00:03:44,520 UNDERSTAND THE CNS IN HEALTH AND 81 00:03:44,520 --> 00:03:46,080 DISEASE AND THE QUESTIONS WE'RE 82 00:03:46,080 --> 00:03:50,120 TACKLING ARE HOW CAN WE USE THE 83 00:03:50,120 --> 00:03:51,160 POSTMORTEM HUMAN BRAIN TO STUDY 84 00:03:51,160 --> 00:03:53,920 SPATIAL DYNAMICS OF DISEASE 85 00:03:53,920 --> 00:03:55,800 PROGRESSION AND HOW 86 00:03:55,800 --> 00:03:56,400 DISEASE-ASSOCIATED MUTATIONS 87 00:03:56,400 --> 00:03:58,400 AFFECT THESE DYNAMICS. 88 00:03:58,400 --> 00:04:01,120 NEEDLESS TO SAY THIS IS 89 00:04:01,120 --> 00:04:04,440 COMPLICATED ESPECIALLY TO SAY OF 90 00:04:04,440 --> 00:04:06,920 LATE ONSET NEURODEGENERATIVE 91 00:04:06,920 --> 00:04:08,080 DISEASE. 92 00:04:08,080 --> 00:04:09,440 THE SAMPLES WE USE NEED TO BE OF 93 00:04:09,440 --> 00:04:11,200 GOOD QUALITY IN THE WAY THEY'RE 94 00:04:11,200 --> 00:04:14,600 BANKED TO ENABLE SOPHISTICATED 95 00:04:14,600 --> 00:04:16,480 MOLECULAR BIOLOGY APPROACH AND 96 00:04:16,480 --> 00:04:17,840 NEED TO BE CLINICALLY WELL 97 00:04:17,840 --> 00:04:19,760 PHENOTYPED TO STRATIFY COHORTS 98 00:04:19,760 --> 00:04:21,520 APPROPRIATELY AND I'LL GET TO 99 00:04:21,520 --> 00:04:25,000 THAT IN A BIT. 100 00:04:25,000 --> 00:04:26,520 AND ANEUROPATHOLOGICALLY WELL 101 00:04:26,520 --> 00:04:28,320 CHARACTERIZED TO SEPARATE THE 102 00:04:28,320 --> 00:04:29,600 INCLUSIONS AND CHARACTERISTICS 103 00:04:29,600 --> 00:04:33,000 OF THESE DISEASES AND IDEALLY 104 00:04:33,000 --> 00:04:35,640 NEED TO HAVE THEM WELL GENOTYPED 105 00:04:35,640 --> 00:04:36,280 AS WELL. 106 00:04:36,280 --> 00:04:38,080 ONCE YOU SORT THAT OUT HOW DO 107 00:04:38,080 --> 00:04:39,400 YOU DECIDE WHICH TECHNOLOGIES TO 108 00:04:39,400 --> 00:04:40,800 USE AND HOW DO YOU COLLECT THE 109 00:04:40,800 --> 00:04:43,040 DATA AND ONCE YOU HAVE IT, WHAT 110 00:04:43,040 --> 00:04:44,080 DO YOU DO WITH IT TO LEARN 111 00:04:44,080 --> 00:04:47,720 STUFF? 112 00:04:47,720 --> 00:04:49,800 I'LL TALK ABOUT THIS IN THE 113 00:04:49,800 --> 00:04:53,920 CONTEXT OF THE ALS FTD CLINICAL 114 00:04:53,920 --> 00:04:55,640 SPECTRUM USING A PHENOTYPE AT 115 00:04:55,640 --> 00:04:57,760 ONE END AND FRONTAL TEMPORAL 116 00:04:57,760 --> 00:04:59,160 DEMENTIA AT THE OTHER WITH LOTS 117 00:04:59,160 --> 00:04:59,760 OF PATIENTS BEING SOMEWHERE IN 118 00:04:59,760 --> 00:05:02,800 BETWEEN. 119 00:05:02,800 --> 00:05:08,080 THAT'S UNDER APPRECIATED BUT 120 00:05:08,080 --> 00:05:12,040 BECOMING MORE TRACTABLE NEW. 121 00:05:12,040 --> 00:05:12,760 -- NOW. 122 00:05:12,760 --> 00:05:14,640 WHEN WE TALK ABOUT THE 123 00:05:14,640 --> 00:05:16,240 CONSORTIUM A BIG CHALLENGE FOR A 124 00:05:16,240 --> 00:05:18,240 RARE DISEASE IS HOW DO YOU 125 00:05:18,240 --> 00:05:22,080 OBTAIN LARGE NUMBER OF PATIENT 126 00:05:22,080 --> 00:05:25,040 DNA AND RNA SAMPLES. 127 00:05:25,040 --> 00:05:27,160 EVEN ONE OF THE BUSIEST CLINICS 128 00:05:27,160 --> 00:05:30,360 IN THE OTHER EAST SEE S ABOUT 129 00:05:30,360 --> 00:05:31,760 400 PATIENTS A YEAR AND CAN'T 130 00:05:31,760 --> 00:05:34,200 RELY ON SAMPLES FROM ANY ONE 131 00:05:34,200 --> 00:05:37,360 CENTER AND THE SOLUTION WAS TO 132 00:05:37,360 --> 00:05:39,400 ESTABLISH A FEDERATED PROGRAM 133 00:05:39,400 --> 00:05:40,560 WITH CENTRALIZED GOVERNANCE. 134 00:05:40,560 --> 00:05:42,960 A FANCY WAY OF SAYING WE GOT 135 00:05:42,960 --> 00:05:45,040 SAMPLES FROM MULTIPLE DIFFERENT 136 00:05:45,040 --> 00:05:46,920 STUDIES THAT SPAN MULTIPLE SITES 137 00:05:46,920 --> 00:05:47,480 WORLDWIDE. 138 00:05:47,480 --> 00:05:51,280 THE COLOR CODING IN THE PINS IS 139 00:05:51,280 --> 00:05:52,760 THE DIFFERENT STUDIES SET UP 140 00:05:52,760 --> 00:05:56,960 WHEN WE STARTED THIS TO DO 141 00:05:56,960 --> 00:06:00,160 EITHER CROSS-SECTIONAL OR 142 00:06:00,160 --> 00:06:00,920 LONGITUDINAL BIO BANKING AND 143 00:06:00,920 --> 00:06:01,840 VARIOUS EFFORTS. 144 00:06:01,840 --> 00:06:03,160 ALL STUDIES DECIDED TO COME 145 00:06:03,160 --> 00:06:04,840 TOGETHER TO POOL THE SAMPLES SO 146 00:06:04,840 --> 00:06:08,680 WE COULD DO THE WHOLE GENOME 147 00:06:08,680 --> 00:06:09,000 SEQUENCING. 148 00:06:09,000 --> 00:06:11,680 WE HAD TO DO THE HARMONIZATION 149 00:06:11,680 --> 00:06:16,680 OF THE CLINICAL METADATA AND ALL 150 00:06:16,680 --> 00:06:18,000 THAT STUFF AND THEN EXPANDED TO 151 00:06:18,000 --> 00:06:19,560 SITES ALL OVER THE WORLD. 152 00:06:19,560 --> 00:06:20,200 THAT'S THE FEDERATED ASPECT OF 153 00:06:20,200 --> 00:06:29,040 THE PROGRAM. 154 00:06:29,040 --> 00:06:30,960 THERE'S STANDARDIZED PROCESSES 155 00:06:30,960 --> 00:06:34,080 TO ALLOW US TO WORK WITH WHAT IS 156 00:06:34,080 --> 00:06:36,960 NOW 45 SITES WORLDWIDE AND 157 00:06:36,960 --> 00:06:38,720 EXPANDING INDUSTRY AND ACADEMIA 158 00:06:38,720 --> 00:06:44,080 AND MANUALLY CURATING AND 159 00:06:44,080 --> 00:06:46,480 HARMONIZING THE METADATA AND 160 00:06:46,480 --> 00:06:47,440 COORDINATING HOW THE DATA COMES 161 00:06:47,440 --> 00:06:50,480 IN AND MERGING WITH THE CLINICAL 162 00:06:50,480 --> 00:06:52,040 DATA AND SHARING IT WITH EVERY 163 00:06:52,040 --> 00:06:54,680 PARTICIPATING SITE AND BEYOND IN 164 00:06:54,680 --> 00:06:55,280 THIS CONSORTIUM. 165 00:06:55,280 --> 00:06:58,880 SO DATA FROM THESE STUDIES ARE 166 00:06:58,880 --> 00:07:01,440 SHARED ALL OVER THE WORLD 167 00:07:01,440 --> 00:07:02,720 INCLUDING WITH INVESTIGATORS AT 168 00:07:02,720 --> 00:07:03,040 NINDS. 169 00:07:03,040 --> 00:07:04,160 SO IF YOU'RE INTERESTED IN 170 00:07:04,160 --> 00:07:05,120 ACCESSING THE RESOURCE, PLEASE 171 00:07:05,120 --> 00:07:14,920 JUST E-MAIL ME. 172 00:07:14,920 --> 00:07:21,000 WE HAVE OVER 5,000 WHOLE GENOMES 173 00:07:21,000 --> 00:07:23,280 AND SEQUENCES FROM THE PATIENTS. 174 00:07:23,280 --> 00:07:25,040 THEN ON THE LAB SIDE, HOW DO WE 175 00:07:25,040 --> 00:07:26,920 USE GENOMICS TO STUDY THE 176 00:07:26,920 --> 00:07:29,600 EFFECTS OF MUTATIONS ON CELLULAR 177 00:07:29,600 --> 00:07:29,960 FUNCTION? 178 00:07:29,960 --> 00:07:33,880 HERE'S WHERE OUR INNOVATIVE 179 00:07:33,880 --> 00:07:36,000 APPROACH TO ALS FTD COMES IN AND 180 00:07:36,000 --> 00:07:38,120 TALKED ABOUT THE CONSORTIUM 181 00:07:38,120 --> 00:07:41,680 EFFORTS AT NYGC AND WE HAVE 182 00:07:41,680 --> 00:07:44,760 ALMOST 500PM TISSUES WITH 183 00:07:44,760 --> 00:07:46,960 DIFFERENT REGIONS OF THE BRAIN 184 00:07:46,960 --> 00:07:52,360 AND SPINAL CORD WE GENERATED 185 00:07:52,360 --> 00:07:53,160 DATA ON. 186 00:07:53,160 --> 00:07:55,480 IN PARALLEL ON THE COLUMBIA SIDE 187 00:07:55,480 --> 00:07:57,600 WE USE AT MOUSE MODELS TO LOOK 188 00:07:57,600 --> 00:07:59,360 AT CELLS IN A DISH AND TISSUES 189 00:07:59,360 --> 00:08:01,800 FROM THE MOUSE AND HUMAN SAMPLES 190 00:08:01,800 --> 00:08:03,480 AND LOOK AT HOW GENE EXPRESSION 191 00:08:03,480 --> 00:08:04,120 PATTERNS CHANGE OVER SPACE AND 192 00:08:04,120 --> 00:08:10,920 TIME. 193 00:08:10,920 --> 00:08:13,880 WHY DO WE WANT TO SPATIALLY 194 00:08:13,880 --> 00:08:15,400 RESOLVE GENE EXPRESSION IN ALS? 195 00:08:15,400 --> 00:08:17,840 LIKE OTHER DISEASES IT INVOLVES 196 00:08:17,840 --> 00:08:18,800 PATHOLOGIES AND MULTIPLE CELL 197 00:08:18,800 --> 00:08:21,680 TYPES AND WE WANT TO UNDERSTAND 198 00:08:21,680 --> 00:08:23,080 HOW THESE DIFFERENT CELL TYPES 199 00:08:23,080 --> 00:08:23,960 INTERACT AS DISEASE PROGRESSES 200 00:08:23,960 --> 00:08:26,640 AND WHETHER WE CAN ACCESS THE 201 00:08:26,640 --> 00:08:28,040 DYNAMICS OF ALS PATHOLOGY ACROSS 202 00:08:28,040 --> 00:08:29,280 TIME AND SPACE. 203 00:08:29,280 --> 00:08:31,840 WHERE DOES IT STOP AND HOW DOES 204 00:08:31,840 --> 00:08:33,040 IT SPREAD. 205 00:08:33,040 --> 00:08:34,640 SO HOW CAN WE MEASURE GENE 206 00:08:34,640 --> 00:08:36,200 EXPRESSION IN MULTIPLE CELL 207 00:08:36,200 --> 00:08:39,840 TYPES AND LOCATIONS 208 00:08:39,840 --> 00:08:40,480 SIMULTANEOUSLY? 209 00:08:40,480 --> 00:08:42,240 THERE ARE MULTIPLE APPROACHES TO 210 00:08:42,240 --> 00:08:43,760 HOW TO DO SPATIAL 211 00:08:43,760 --> 00:08:44,120 TRANSCRIPTOMICS. 212 00:08:44,120 --> 00:08:46,160 THEY CAN BE DIVIDED INTO TWO 213 00:08:46,160 --> 00:08:46,920 BROAD CLASS. 214 00:08:46,920 --> 00:08:48,160 THE SPATIAL BAR CODING METHODS 215 00:08:48,160 --> 00:08:51,480 THAT DON'T RELY ON SELECTING 216 00:08:51,480 --> 00:08:53,640 TRANSCRIPTS UP FRONT AND THEN 217 00:08:53,640 --> 00:08:55,120 THE IMAGING BASED METHODS WHERE 218 00:08:55,120 --> 00:08:56,680 YOU START WITH A KNOWN SET OF 219 00:08:56,680 --> 00:08:59,080 TRANSCRIPTS AND BUILD PROBES 220 00:08:59,080 --> 00:09:01,080 AROUND THEM AND THESE METHODS 221 00:09:01,080 --> 00:09:04,800 CAN GIVE YOU CELLULAR AND SUB 222 00:09:04,800 --> 00:09:07,440 CELLULAR RESOLUTION WHICH THE 223 00:09:07,440 --> 00:09:08,680 BAR CODING BASED METHOD SO 224 00:09:08,680 --> 00:09:09,240 NECESSARILY DO. 225 00:09:09,240 --> 00:09:10,400 WHAT YOU LOSE IN RESOLUTION IN 226 00:09:10,400 --> 00:09:13,160 ONE METHOD YOU MAKE UP FOR IN 227 00:09:13,160 --> 00:09:14,520 THROUGHPUT AND SCALE ON THE 228 00:09:14,520 --> 00:09:15,760 OTHER. 229 00:09:15,760 --> 00:09:18,760 AN IDEAL COMBINATION WOULD BE TO 230 00:09:18,760 --> 00:09:19,800 ARTFULLY COMBINE THESE TWO AND 231 00:09:19,800 --> 00:09:20,320 THAT'S WHAT WE'RE WORKING 232 00:09:20,320 --> 00:09:26,960 TOWARDS. 233 00:09:26,960 --> 00:09:30,600 THE METHOD OF CHOICE IS NOT 234 00:09:30,600 --> 00:09:33,000 COMMERCIALIZED BY 10X GENOMICS 235 00:09:33,000 --> 00:09:36,640 AND THIS WAS DEVELOPED AT THE 236 00:09:36,640 --> 00:09:42,720 LAB IN WE'D -- SWEDEN AND 237 00:09:42,720 --> 00:09:44,320 DEVELOPED THE WORK FLOWS THAT 238 00:09:44,320 --> 00:09:48,400 WERE THEN TAUGHT IN SWEDEN. 239 00:09:48,400 --> 00:09:53,800 ESSENTIALLY ANYONE FAMILIAR WITH 240 00:09:53,800 --> 00:10:01,040 HOUSE VISSIUM WORKS? 241 00:10:01,040 --> 00:10:03,560 YOU HAVE AN ARRAY OF PROBES ON 242 00:10:03,560 --> 00:10:06,240 THE GLASS SLIDE AND THEY'RE 243 00:10:06,240 --> 00:10:08,200 SPOTTED IN 55 MICRON CIRCLES 244 00:10:08,200 --> 00:10:10,560 WITH THE CENTER TO CENTER 245 00:10:10,560 --> 00:10:11,760 DISTANCE OF 100 MICRON. 246 00:10:11,760 --> 00:10:14,080 YOU CAN SEE OFF THE BACK THEY 247 00:10:14,080 --> 00:10:15,320 WON'T GIVE YOU COVERAGE ACROSS 248 00:10:15,320 --> 00:10:20,080 THE TISSUE AND NOT GOING TO GIVE 249 00:10:20,080 --> 00:10:22,640 YOU SINGLE CELL RESOLUTION. 250 00:10:22,640 --> 00:10:24,720 SO EACH OF THESE PROBES HAS A 251 00:10:24,720 --> 00:10:26,120 UNIQUE MOLECULAR IDENTIFIER THAT 252 00:10:26,120 --> 00:10:29,000 GIVES YOU TWO PIECES OF 253 00:10:29,000 --> 00:10:29,480 INFORMATION. 254 00:10:29,480 --> 00:10:31,160 WHERE ON THE GLASS SLIDE IT CAME 255 00:10:31,160 --> 00:10:33,160 FROM AND HOW MANY UNIQUE SPECIES 256 00:10:33,160 --> 00:10:35,560 OF AN INDIVIDUAL MOLECULE YOU 257 00:10:35,560 --> 00:10:36,360 CAPTURE. 258 00:10:36,360 --> 00:10:41,760 SO THEN YOU'VE GOT YOUR TISSUE 259 00:10:41,760 --> 00:10:45,920 SECTION AND MICRON FRESH FROZEN 260 00:10:45,920 --> 00:10:49,000 AND TAKE A PICTURE AND IT WILL 261 00:10:49,000 --> 00:10:50,680 ALLOW TO RELATE WHICH MOLECULE, 262 00:10:50,680 --> 00:10:54,280 HOW MANY, WHERE ON THE SLIDE, 263 00:10:54,280 --> 00:10:55,480 WHERE ON THE TISSUE. 264 00:10:55,480 --> 00:10:58,480 I SHOULD DO THAT WITH MY LEFT 265 00:10:58,480 --> 00:11:01,120 HAND BECAUSE I CAN'T BEND THE 266 00:11:01,120 --> 00:11:01,520 PINKY WITH MY RIGHT. 267 00:11:01,520 --> 00:11:04,400 THEN YOU HAVE THE TISSUE 268 00:11:04,400 --> 00:11:04,960 SECTION. 269 00:11:04,960 --> 00:11:07,360 YOU PERMEABLIZE IT AND ALLOW THE 270 00:11:07,360 --> 00:11:12,160 RNA TO DIFFUSE AND BE COLLECTED 271 00:11:12,160 --> 00:11:14,120 BY THE PROBES AND WASH THE 272 00:11:14,120 --> 00:11:16,720 TISSUE FROM THE SLIDE AND DO 273 00:11:16,720 --> 00:11:19,120 YOUR LIBRARY PREP AND SEQUENCING 274 00:11:19,120 --> 00:11:23,680 LIKE FOR ANY NEXT GEN 275 00:11:23,680 --> 00:11:23,960 EXPERIMENT. 276 00:11:23,960 --> 00:11:26,200 SO THE VISIUM SLIDE HAS ON ONE 277 00:11:26,200 --> 00:11:32,720 SLIDE FOUR OF THESE ARRAYS EACH 278 00:11:32,720 --> 00:11:37,000 WITH THE 55 MICRON SPOT AND EACH 279 00:11:37,000 --> 00:11:42,880 ARRAY IS 6MM BY 6MM AND HERE'S A 280 00:11:42,880 --> 00:11:45,800 CLOSE UP OF THE STAIN SECTION 281 00:11:45,800 --> 00:11:47,120 OVERLAID ON THE SPOTS. 282 00:11:47,120 --> 00:11:54,120 YOU'VE GOT THE DNA OLIGOS WITH 283 00:11:54,120 --> 00:11:55,360 THE SPATIAL BAR CODE. 284 00:11:55,360 --> 00:11:57,800 WHAT WE LIKE ABOUT THIS AND THE 285 00:11:57,800 --> 00:12:02,120 REASON WE CHOSE IT, IT ALLOWS AN 286 00:12:02,120 --> 00:12:05,000 UNBIASSED WAY OF ACCESSING THE 287 00:12:05,000 --> 00:12:06,360 TRANSCRIPTOME AND DO THINGS AT 288 00:12:06,360 --> 00:12:07,720 THE THROUGHPUT AND SCALE YOU 289 00:12:07,720 --> 00:12:08,720 NEED IT. 290 00:12:08,720 --> 00:12:11,760 WE OVERCAME COMPUTATIONAL 291 00:12:11,760 --> 00:12:13,880 APPROACHES AND LACK OF COVERAGE 292 00:12:13,880 --> 00:12:16,000 AND LACK OF CELL TYPE SPECIFIC 293 00:12:16,000 --> 00:12:16,280 INFORMATION. 294 00:12:16,280 --> 00:12:18,000 I'LL TELL YOU ABOUT IN A SECOND. 295 00:12:18,000 --> 00:12:20,120 SO WHEN WE WERE SETTING THIS UP, 296 00:12:20,120 --> 00:12:22,520 WE DECIDED TO USE THE MOUSE 297 00:12:22,520 --> 00:12:24,640 MODEL OF ALS BECAUSE THERE WAS A 298 00:12:24,640 --> 00:12:27,040 WHOLE BANK OF DATA THAT WE COULD 299 00:12:27,040 --> 00:12:29,040 USE TO SEE IF THE THINGS THAT WE 300 00:12:29,040 --> 00:12:30,720 WERE FINDING DID THEY MAKE 301 00:12:30,720 --> 00:12:31,920 SENSE, COULD WE PLACE THEM IN 302 00:12:31,920 --> 00:12:33,520 THE CONTEXT OF WHAT WAS ALREADY 303 00:12:33,520 --> 00:12:33,720 KNOWN. 304 00:12:33,720 --> 00:12:35,440 SO THE POINT OF THE MOUSE MODEL 305 00:12:35,440 --> 00:12:42,960 WAS TO USE IT AS A TOOL TO BUILD 306 00:12:42,960 --> 00:12:46,360 THE LAB WORK FLOWS WE NEED TO 307 00:12:46,360 --> 00:12:51,600 APPLY THEM TO HUMAN TISSUE. 308 00:12:51,600 --> 00:12:53,920 WE PICKED AN AGGRESSIVE MODEL 309 00:12:53,920 --> 00:12:57,560 AND FOUR TIME POINTS THAT SPAN 310 00:12:57,560 --> 00:13:04,520 TO PRE AND POST SYMPTOMATIC 311 00:13:04,520 --> 00:13:08,040 DISEASE STAGES AND WHAT WE HAD 312 00:13:08,040 --> 00:13:10,720 TO OVERCOME IN ANALYZING THIS 313 00:13:10,720 --> 00:13:13,600 DATA IS THE HIGH DIMENSIONALITY 314 00:13:13,600 --> 00:13:15,920 OF THE DATA SET A SCRIPTOME 315 00:13:15,920 --> 00:13:17,560 SCALE AND HAS HUNDREDS I THINK 316 00:13:17,560 --> 00:13:20,080 THIS IS A LITTLE OUTDATED BUT 317 00:13:20,080 --> 00:13:23,760 ABOUT 1300 TISSUE SECTIONS FROM 318 00:13:23,760 --> 00:13:26,000 MOUSE ABOUT 80 HUMAN SECTIONS 319 00:13:26,000 --> 00:13:28,880 THAT WE DID WHEN WE DEVELOPED 320 00:13:28,880 --> 00:13:32,200 THIS ANALYTICAL FRAMEWORK. 321 00:13:32,200 --> 00:13:34,920 THE MOUSE SPECIMENS SPAN 322 00:13:34,920 --> 00:13:36,360 MULTIPLE ANIMALS AND MULTIPLE 323 00:13:36,360 --> 00:13:38,880 TIME POINTS AND GENOTYPES AND 324 00:13:38,880 --> 00:13:42,520 SPAN MULTIPLE REGIONS AND THE 325 00:13:42,520 --> 00:13:45,800 ENTIRE CROSS SECTION. 326 00:13:45,800 --> 00:13:48,880 AND THEN THERE ARE TECHNICAL 327 00:13:48,880 --> 00:13:49,120 ISSUES. 328 00:13:49,120 --> 00:13:51,160 EXTENSIVE AND HIGHLY VARIABLE 329 00:13:51,160 --> 00:13:56,120 ZERO INFLATION WHICH MEANS A 330 00:13:56,120 --> 00:13:57,840 MEASUREMENT OF ZERO DOESN'T 331 00:13:57,840 --> 00:13:59,000 NECESSARILY MEAN IT WASN'T 332 00:13:59,000 --> 00:13:59,280 THERE. 333 00:13:59,280 --> 00:14:00,400 IT COULD BE TECHNICAL REASONS 334 00:14:00,400 --> 00:14:05,040 YOU GET DROP OFF BECAUSE YOU GET 335 00:14:05,040 --> 00:14:08,120 THIN SECTIONS AND NOT EVERY SPOT 336 00:14:08,120 --> 00:14:09,920 WILL ACCESS EVERY MOLECULE IN 337 00:14:09,920 --> 00:14:11,800 THE TRANSCRIPTOME. 338 00:14:11,800 --> 00:14:13,000 SO THERE'S VARIABILITY BETWEEN 339 00:14:13,000 --> 00:14:23,440 SPOTS AND BETWEEN SAMPLES. 340 00:14:24,560 --> 00:14:26,560 SO WE CAME UP WITH A WAY TO 341 00:14:26,560 --> 00:14:32,120 DIVIDE UP THE SPINAL CORD TO 11 342 00:14:32,120 --> 00:14:35,120 DIFFERENT ANATOMICAL REGIONS 343 00:14:35,120 --> 00:14:38,120 WHETHER A SPOT FELL ON WHITE OR 344 00:14:38,120 --> 00:14:40,440 DARK OR MEDIAL OR CENTRAL OR 345 00:14:40,440 --> 00:14:44,160 DORSAL AND MANUALLY ASSIGNED 346 00:14:44,160 --> 00:14:47,400 ABOUT 130,000 SPOTS TO ONE OF 347 00:14:47,400 --> 00:14:50,120 THESE 11AARs. 348 00:14:50,120 --> 00:14:53,000 YOU SEE THE FOUR MOUSE SPINAL 349 00:14:53,000 --> 00:14:55,120 CORD CROSS SECTIONS ON THESE 350 00:14:55,120 --> 00:14:57,000 ARRAYS AND THIS IS HOW A 351 00:14:57,000 --> 00:14:58,160 CLOSE-UP VIEW LOOKS LIKE. 352 00:14:58,160 --> 00:15:01,080 A GIVEN SPOT CAN HAVE A VARYING 353 00:15:01,080 --> 00:15:02,880 NUMBER OF NUCLEI DEPENDING ON 354 00:15:02,880 --> 00:15:03,720 WHERE ON THE TISSUE SECTION IT 355 00:15:03,720 --> 00:15:06,240 FALLS. 356 00:15:06,240 --> 00:15:07,400 SO ONCE WE HAVE DONE THIS, ALL 357 00:15:07,400 --> 00:15:13,960 WE HAVE TO DO IS TO TAKE THE 358 00:15:13,960 --> 00:15:15,320 HORNS TO REGISTER THE TISSUE 359 00:15:15,320 --> 00:15:17,280 SECTIONS WITH RESPECT TO ONE 360 00:15:17,280 --> 00:15:20,840 ANOTHER. 361 00:15:20,840 --> 00:15:29,000 ALLOWED US TO GO FROM WHAT WAS 362 00:15:29,000 --> 00:15:31,760 COARSE AND UNEVEN TO WHAT IS 363 00:15:31,760 --> 00:15:33,680 DENSE AND EVEN SAMPLING ACROSS 364 00:15:33,680 --> 00:15:35,760 THE CROSS-SECTION OF TISSUE AND 365 00:15:35,760 --> 00:15:37,520 SAW THE EXPECTED PATTERN OF 366 00:15:37,520 --> 00:15:39,520 EXPRESSION OF EXPRESSION OF 367 00:15:39,520 --> 00:15:39,760 GENES. 368 00:15:39,760 --> 00:15:40,760 THINGS IN THE WHITE MATTER WERE 369 00:15:40,760 --> 00:15:42,040 IN THE WHITE AND THINGS IN THE 370 00:15:42,040 --> 00:15:44,120 GRAY WERE IN THE GRAY MATTER AND 371 00:15:44,120 --> 00:15:47,840 THINGS THAT WERE SUPPOSED TO BE 372 00:15:47,840 --> 00:15:49,920 IN THE VENTRAL HORN WAS THERE 373 00:15:49,920 --> 00:15:51,600 AND WE KNOW THAT REGISTRATION 374 00:15:51,600 --> 00:15:56,120 ALLOWED TO US GO TO DENSE AND 375 00:15:56,120 --> 00:15:56,720 EVEN COVERAGE. 376 00:15:56,720 --> 00:15:59,160 NOW THAT YOU HAVE IT, HOW DO YOU 377 00:15:59,160 --> 00:16:01,120 USE IT? 378 00:16:01,120 --> 00:16:05,360 WE USED WITH A GROUP TOGETHER 379 00:16:05,360 --> 00:16:14,160 AND CAME UP WITH A HIERARCHICAL 380 00:16:14,160 --> 00:16:16,200 PROBLEMISTIC MODEL THAT IS 381 00:16:16,200 --> 00:16:19,520 SPLOTCH AND IT DOESN'T STAND FOR 382 00:16:19,520 --> 00:16:21,040 ANYTHING AND WE MODEL THE 383 00:16:21,040 --> 00:16:22,320 EXPRESSION LEVEL OF A GENE IN 384 00:16:22,320 --> 00:16:23,720 ANY GIVEN SPOT AS A FUNCTION OF 385 00:16:23,720 --> 00:16:28,680 WHICH REGION IT CAME FROM. 386 00:16:28,680 --> 00:16:30,200 IT'S IMMEDIATE LOCAL ANTIBODY 387 00:16:30,200 --> 00:16:31,480 AND ALSO BUILT IN SPOT-LEVEL 388 00:16:31,480 --> 00:16:35,560 VARIATION. 389 00:16:35,560 --> 00:16:36,880 THE EXPRESSION PATTERNS IN A 390 00:16:36,880 --> 00:16:39,240 SPOT ARE LIKELY TO BE MORE 391 00:16:39,240 --> 00:16:40,600 SIMILAR TO IMMEDIATE NEIGHBORS 392 00:16:40,600 --> 00:16:42,720 THAN TO SPOTS FURTHER AWAY AND 393 00:16:42,720 --> 00:16:43,960 THE EXPRESSION PATTERNS IN LETS 394 00:16:43,960 --> 00:16:50,800 SAY THE AAR FOR THE VENTRAL HORN 395 00:16:50,800 --> 00:16:52,440 WOULD BE MORE SIMILAR TO EACH 396 00:16:52,440 --> 00:16:53,400 OTHER THAN SOMETHING MUCH 397 00:16:53,400 --> 00:16:55,400 FURTHER AWAY. 398 00:16:55,400 --> 00:16:57,240 AND THEN THERE'S THIS LINEAR 399 00:16:57,240 --> 00:16:59,680 MODEL THAT'S A COMPONENT OF 400 00:16:59,680 --> 00:17:01,600 SPLOTCH THAT ALLOWS YOU TO 401 00:17:01,600 --> 00:17:03,440 CONTRACT THE VARIABLES YOU BUILT 402 00:17:03,440 --> 00:17:06,120 INTO YOUR EXPERIMENTAL DESIGN. 403 00:17:06,120 --> 00:17:09,000 SO THIS CHANGES WITH EXPERIMENT 404 00:17:09,000 --> 00:17:11,440 TO EXPERIMENT FOR THE UNDERLYING 405 00:17:11,440 --> 00:17:13,040 MODEL FOR HIGHER MODELLING GENE 406 00:17:13,040 --> 00:17:16,440 EXPRESSION STAYS THE SAME. 407 00:17:16,440 --> 00:17:18,040 AND THIS ALLOWED US BECAUSE OF 408 00:17:18,040 --> 00:17:21,000 THIS MODELLING WE COULD BORROW 409 00:17:21,000 --> 00:17:21,960 INFORMATION FROM NEIGHBORING 410 00:17:21,960 --> 00:17:24,440 SPOTS AND EVEN THOUGH IN ANY 411 00:17:24,440 --> 00:17:26,480 GIVEN SPOT YOU CAN ONLY DIRECTLY 412 00:17:26,480 --> 00:17:29,320 MEASURE A FEW THOUSAND 413 00:17:29,320 --> 00:17:29,640 TRANSCRIPTS. 414 00:17:29,640 --> 00:17:31,080 WHEN YOU COMBINE ALL THIS 415 00:17:31,080 --> 00:17:33,760 INFORMATION YOU CAN INFER THE 416 00:17:33,760 --> 00:17:34,520 EXPRESSION ACROSS ALMOST THE 417 00:17:34,520 --> 00:17:36,720 ENTIRE TRANSCRIPTOME. 418 00:17:36,720 --> 00:17:39,720 AND THIS IS WHAT ALLOWS YOU TO 419 00:17:39,720 --> 00:17:44,160 DO REGION SPECIFIC DIFFERENTIAL 420 00:17:44,160 --> 00:17:46,640 EXPRESSION MEASUREMENTS AND SEE 421 00:17:46,640 --> 00:17:47,480 HOW MUCH STATISTICAL 422 00:17:47,480 --> 00:17:49,000 SIGNIFICANCE THEY HAVE. 423 00:17:49,000 --> 00:17:52,720 THIS IS AN EXAMPLE OF ONE TWO 424 00:17:52,720 --> 00:17:55,200 SUCH GENES AND HOW THEY VARY 425 00:17:55,200 --> 00:17:57,080 BETWEEN DIFFERENT PHENOTYPES, 426 00:17:57,080 --> 00:17:59,080 THOSE ARE THE DIFFERENT COLORS, 427 00:17:59,080 --> 00:18:04,040 DIFFERENT TIME POINTS, THE 428 00:18:04,040 --> 00:18:05,680 DIFFERENT ROWS DIFFERENT REGIONS 429 00:18:05,680 --> 00:18:08,080 OF THE CORE, THE BOXES. 430 00:18:08,080 --> 00:18:12,760 YOU CAN START TO SEE HERE THE 431 00:18:12,760 --> 00:18:16,760 GENE EXPRESSION STARTS TO DIFFER 432 00:18:16,760 --> 00:18:19,240 BETWEEN GENOTYPES AT P70 IN THE 433 00:18:19,240 --> 00:18:20,720 VENTRAL HORN BEFORE IT DIVERGES 434 00:18:20,720 --> 00:18:21,680 TO OTHER REGIONS. 435 00:18:21,680 --> 00:18:25,400 YOU CAN SEE WE HAVE MORE 436 00:18:25,400 --> 00:18:30,760 CONFIDENCE THE TIGHTNESS OF 437 00:18:30,760 --> 00:18:37,000 THESE THINGS IN THESE 438 00:18:37,000 --> 00:18:37,560 MEASUREMENTS THAN THESE FOR 439 00:18:37,560 --> 00:18:43,600 EXAMPLE. 440 00:18:43,600 --> 00:18:45,960 THIS IS THE CHANGE AS DESCRIBED 441 00:18:45,960 --> 00:18:53,440 AND THE VALIDATION THROUGH IF. 442 00:18:53,440 --> 00:19:03,040 WE CAN START TO SEE IT HAPPENS 443 00:19:03,040 --> 00:19:08,120 AS EARLY AS 930 AND HAPPENS IN A 444 00:19:08,120 --> 00:19:12,520 SUBSET OF CELLS AND THESE CELLS 445 00:19:12,520 --> 00:19:17,600 WE KNOW THESE ARE IBA POSITIVE 446 00:19:17,600 --> 00:19:20,120 MICROGLIAL CELLS HAPPEN TO BE 447 00:19:20,120 --> 00:19:22,160 CLOSELY ABUTTING THE AXONS OF 448 00:19:22,160 --> 00:19:24,800 THE MOTOR NEURONS AS THEY EXIT 449 00:19:24,800 --> 00:19:26,400 THROUGH THE VENTRAL HORN. 450 00:19:26,400 --> 00:19:27,360 THOSE ARE THE TYPES OF THINGS 451 00:19:27,360 --> 00:19:31,680 YOU CAN DO ON A GENE BY GENE 452 00:19:31,680 --> 00:19:33,000 BASIS AND GO THROUGH YOUR 453 00:19:33,000 --> 00:19:33,960 FAVORITE PATHWAYS. 454 00:19:33,960 --> 00:19:36,560 THEY ALSO HAPPEN TO BE THE 455 00:19:36,560 --> 00:19:39,400 EARLIEST CHANGES WE SAW AND SEE 456 00:19:39,400 --> 00:19:47,080 THEM IN THE SVENTRAL/LATERAL ARA 457 00:19:47,080 --> 00:19:48,440 AND WE GROUPED THEM DEPENDING ON 458 00:19:48,440 --> 00:19:49,720 HOW SIMILAR THEY WERE TO EACH 459 00:19:49,720 --> 00:19:53,000 OTHER AND DIVIDED THE 460 00:19:53,000 --> 00:19:55,360 TRANSCRIPTS THAT WERE CHANGED 461 00:19:55,360 --> 00:19:58,960 INTO SEVERAL MODULES BASED ON 462 00:19:58,960 --> 00:20:02,120 THE SIMILARITY OF THE EXPRESSION 463 00:20:02,120 --> 00:20:05,800 CHANGES AND MAPPED THOSE MODULES 464 00:20:05,800 --> 00:20:07,440 ON SPATIAL TEMPORAL COORDINATES. 465 00:20:07,440 --> 00:20:14,080 THIS IS MODULE 8 AND HOW MODULE 466 00:20:14,080 --> 00:20:17,760 8 GENES CHANGE THE WILD TYPE AND 467 00:20:17,760 --> 00:20:23,880 MUTANT AND THE GLIALS. 468 00:20:23,880 --> 00:20:28,680 MODULE 11 AND YOU CAN START TO 469 00:20:28,680 --> 00:20:33,600 LOSE THIS EXPRESSION OVER 470 00:20:33,600 --> 00:20:38,120 SYMPTOMATIC TIME POINTS AND YOU 471 00:20:38,120 --> 00:20:41,640 CAN SEPARATE OUT WITHOUT GETTING 472 00:20:41,640 --> 00:20:43,240 DROP OUT OF CELLS. 473 00:20:43,240 --> 00:20:45,760 WE THEN TREATED EACH SPOT AS A 474 00:20:45,760 --> 00:20:49,040 MINI BULK AND USED ORTHOGONAL 475 00:20:49,040 --> 00:20:52,680 AND SINGLE-CELL DATA SETS. 476 00:20:52,680 --> 00:20:54,000 THIS DATA SET WAS ONE OF THE 477 00:20:54,000 --> 00:20:58,160 FIRST WE USED TO DO THE 478 00:20:58,160 --> 00:21:00,280 DECONVOLUTION AND START TO NOW 479 00:21:00,280 --> 00:21:02,800 EXTRACT THE CONTRIBUTION OF 480 00:21:02,800 --> 00:21:04,440 SPECIFIC TYPES OF CELLS TO THE 481 00:21:04,440 --> 00:21:07,080 CHANGES IN EACH OF THESE 482 00:21:07,080 --> 00:21:07,320 MODULES. 483 00:21:07,320 --> 00:21:10,440 MODULE 8 YOU CAN SEE WHAT'S THE 484 00:21:10,440 --> 00:21:18,600 CONTRIBUTION OF MODULE CELLS AND 485 00:21:18,600 --> 00:21:20,120 ASTROCYTES AND HOW MANY CAN YOU 486 00:21:20,120 --> 00:21:22,200 DO IT INTO TURNS OUT THESE TWO. 487 00:21:22,200 --> 00:21:25,760 AND THEY'RE DEFINED ON 488 00:21:25,760 --> 00:21:30,280 SIMILARITIES OF SPATIAL, 489 00:21:30,280 --> 00:21:34,240 TEMPORAL TYPES AND SOME ON 490 00:21:34,240 --> 00:21:37,000 PATTERN TYPE AND THEN DIFFERENT 491 00:21:37,000 --> 00:21:43,320 CELL TYPES WITH SUBMODULES COULD 492 00:21:43,320 --> 00:21:46,800 REPRESENT SUBPOPULATIONS OF 493 00:21:46,800 --> 00:21:47,920 MICROGLIA. 494 00:21:47,920 --> 00:21:50,560 HERE'S IBA1 MICROGLIA AND PART 495 00:21:50,560 --> 00:21:53,040 OF TWO DIFFERENT MODULES. 496 00:21:53,040 --> 00:21:55,080 THEY HAVE VERY DIFFERENT 497 00:21:55,080 --> 00:21:56,120 PATTERNS OF EXPRESSION OVER THE 498 00:21:56,120 --> 00:22:03,240 TIME COURSE OF THE DISEASE. 499 00:22:03,240 --> 00:22:06,960 NOW YOU CAN START TO DO THIS 500 00:22:06,960 --> 00:22:08,760 WITH DIFFERENT CELL TYPES AND 501 00:22:08,760 --> 00:22:16,560 START TO BUILD ENSEMBLES 502 00:22:16,560 --> 00:22:18,000 DEPENDING ON WHERE THEY ARE IN 503 00:22:18,000 --> 00:22:19,760 THE PORT AND WHAT STAGE OF THE 504 00:22:19,760 --> 00:22:20,280 DISEASE YOU ARE IN. 505 00:22:20,280 --> 00:22:23,480 NOW THAT WE HAVE ALL THESE 506 00:22:23,480 --> 00:22:27,120 METHODS HOW CAN WE STUDY DISEASE 507 00:22:27,120 --> 00:22:28,480 PROGRESSION AND HOW DO YOU 508 00:22:28,480 --> 00:22:29,840 APPROXIMATE THE PROGRESSION YOU 509 00:22:29,840 --> 00:22:40,280 GET FROM THE MOUSE MODEL? 510 00:22:40,600 --> 00:22:43,920 BECAUSE WE SPREAD THROUGH C 511 00:22:43,920 --> 00:22:46,880 CONTIGUOUS REGION WE STUDIES 512 00:22:46,880 --> 00:22:48,560 REGIONS THAT WERE CLOSE TO OR 513 00:22:48,560 --> 00:22:53,240 FURTHER AWAY FROM THE SITE OF 514 00:22:53,240 --> 00:22:55,720 ONSET OF DISEASE AND WE HAVE 515 00:22:55,720 --> 00:22:56,320 PHENOTYPING ASSOCIATED WITH 516 00:22:56,320 --> 00:22:58,560 THESE CASES. 517 00:22:58,560 --> 00:23:00,240 WE CAN START TO BUILD COHORTS 518 00:23:00,240 --> 00:23:01,040 THIS WAY. 519 00:23:01,040 --> 00:23:06,280 SO THE FIRST PASS AT THIS WAS 520 00:23:06,280 --> 00:23:08,040 TAKING LUMBAR ONSET PATIENTS AND 521 00:23:08,040 --> 00:23:10,720 LOOKED AT CERVICAL AND LUMBAR 522 00:23:10,720 --> 00:23:13,000 CORD THAT'S WHAT THIS 523 00:23:13,000 --> 00:23:15,480 COMPLICATED DIAGRAM IS SUPPOSED 524 00:23:15,480 --> 00:23:16,560 TO REPRESENT. 525 00:23:16,560 --> 00:23:17,400 THE YELLOW THINGS ARE THINGS 526 00:23:17,400 --> 00:23:18,960 CLOSE TO OR FURTHER AWAY FROM 527 00:23:18,960 --> 00:23:23,200 THE SITE OF ONSET OF DISEASE. 528 00:23:23,200 --> 00:23:27,000 THE PURPLE THINGS ARE CLOSE TO 529 00:23:27,000 --> 00:23:31,720 OR FURTHER AWAY FROM LOWER LIMB 530 00:23:31,720 --> 00:23:33,000 ONSET OF DISEASE. 531 00:23:33,000 --> 00:23:35,800 WE DID THIS FOR SIX PATIENTS. 532 00:23:35,800 --> 00:23:37,680 WE LEARNED ONE SIX IS NOT ENOUGH 533 00:23:37,680 --> 00:23:38,840 BECAUSE THERE'S MORE INDIVIDUAL 534 00:23:38,840 --> 00:23:43,560 VARIABILITY IN HUMAN SAMPLES 535 00:23:43,560 --> 00:23:46,400 THAN FOR MICE AND WE NEED LARGER 536 00:23:46,400 --> 00:23:46,920 COHORT. 537 00:23:46,920 --> 00:23:49,320 THE MOUSE EXPERIMENTS ALLOWED US 538 00:23:49,320 --> 00:23:52,280 TO DO POWER CALCULATIONS. 539 00:23:52,280 --> 00:23:55,480 WE KNOW FOR ANIMALS FOUR ANIMALS 540 00:23:55,480 --> 00:23:58,200 PER CONDITION AND FOUR SECTIONS. 541 00:23:58,200 --> 00:24:00,600 TISSUE IS MORE THAN TO GET MORE 542 00:24:00,600 --> 00:24:02,120 DATA WITH HIGH CONFIDENCE. 543 00:24:02,120 --> 00:24:05,160 FOR HUMANS IT'S MORE LIKE 20 AT 544 00:24:05,160 --> 00:24:05,400 MINIMAL. 545 00:24:05,400 --> 00:24:07,040 THE SECOND THING WE LEARNED WAS 546 00:24:07,040 --> 00:24:10,080 THAT YES, THERE IS A DEPENDENCE 547 00:24:10,080 --> 00:24:12,320 ON HOW CLOSE TO OR FAR AWAY YOU 548 00:24:12,320 --> 00:24:15,920 ARE FROM THE SITE OF ONSET OF 549 00:24:15,920 --> 00:24:18,400 DISEASE AND COMPARING CERVICAL 550 00:24:18,400 --> 00:24:20,280 AND LUMBAR ISN'T THE WAY TO GO 551 00:24:20,280 --> 00:24:22,120 BECAUSE THERE'S DISEASE-DRIVEN 552 00:24:22,120 --> 00:24:22,440 DIFFERENCES. 553 00:24:22,440 --> 00:24:25,000 THE THIRD THING WE DID WAS TWEAK 554 00:24:25,000 --> 00:24:27,440 THE STUDY DESIGN TO LOOK AT 555 00:24:27,440 --> 00:24:29,040 MOTOR VORTEX AND LUMBAR CORD 556 00:24:29,040 --> 00:24:30,880 FROM PATIENTS WE STRATIFIED 557 00:24:30,880 --> 00:24:32,120 BASED ON SITE OF ONSET OF 558 00:24:32,120 --> 00:24:33,160 DISEASE AND THOSE ARE STUDIES 559 00:24:33,160 --> 00:24:40,760 THAT ARE ONGOING. 560 00:24:40,760 --> 00:24:44,120 WE PUT THIS INTO A DATA 561 00:24:44,120 --> 00:24:47,520 VISUALIZER BUT IT'S CASE 562 00:24:47,520 --> 00:24:50,040 SENSITIVE SO YOU HAVE TO ENTER 563 00:24:50,040 --> 00:24:51,600 THE GENES IN A PARTICULAR WAY 564 00:24:51,600 --> 00:24:53,200 AND IT WILL GUIDE YOU THROUGH 565 00:24:53,200 --> 00:24:53,400 THAT. 566 00:24:53,400 --> 00:24:55,560 YOU CAN EXPLORE THE ARRAY VIEW 567 00:24:55,560 --> 00:24:57,920 FOR MOUSE OR HUMAN. 568 00:24:57,920 --> 00:25:01,160 YOU CAN DO DIGITAL IN SITUS FOR 569 00:25:01,160 --> 00:25:02,600 YOUR FAVORITE GENE OR LOOK AT 570 00:25:02,600 --> 00:25:04,760 ONE OR MULTIPLE AT A TIME FOR 571 00:25:04,760 --> 00:25:06,840 MICE AND HUMANS. 572 00:25:06,840 --> 00:25:09,000 THE HUMAN DATA ARE SPARSE 573 00:25:09,000 --> 00:25:10,440 BECAUSE WE HAVEN'T HAD TIME TO 574 00:25:10,440 --> 00:25:13,160 POPULATE IT WITH THE NEW DATA 575 00:25:13,160 --> 00:25:15,160 COMING ONLINE BUT ACTIVELY 576 00:25:15,160 --> 00:25:16,360 WORKING ON THAT. 577 00:25:16,360 --> 00:25:18,960 YOU CAN EXPLORE THE DATA SET 578 00:25:18,960 --> 00:25:22,080 THROUGH THE COEFFICIENT VIEW FOR 579 00:25:22,080 --> 00:25:22,680 DIFFERENTIALLY EXPRESSED GENES 580 00:25:22,680 --> 00:25:23,520 AT A PARTICULAR PLACE AND TIME 581 00:25:23,520 --> 00:25:26,720 AND PARTICULAR REGION. 582 00:25:26,720 --> 00:25:28,880 OR YOU CAN LOOK AT EXPRESSION 583 00:25:28,880 --> 00:25:31,240 TRAJECTORIES AND GROUPS OF GENES 584 00:25:31,240 --> 00:25:34,360 THAT BEHAVE SIMILARLY WITH TIME. 585 00:25:34,360 --> 00:25:37,000 SO SO FAR I TOLD YOU ABOUT HOW 586 00:25:37,000 --> 00:25:39,600 WE USED THE MOUSE MODEL TO BUILD 587 00:25:39,600 --> 00:25:42,600 ROBUST WORK FLOWS TO APPLY IT AT 588 00:25:42,600 --> 00:25:44,120 SCALE AND HOW WE DEVELOPED THE 589 00:25:44,120 --> 00:25:50,120 COMPUTATIONAL APPROACHES TO MINE 590 00:25:50,120 --> 00:25:57,000 THE ST DATA AND IDENTIFY 591 00:25:57,000 --> 00:25:59,760 PATTERNS AND MAYBE IDENTIFIED 592 00:25:59,760 --> 00:26:00,520 SUBPOPULATIONS OF GLIAL CELLS 593 00:26:00,520 --> 00:26:02,920 AND BEGIN TO APPLY THIS TO THE 594 00:26:02,920 --> 00:26:05,000 MOTOR SYSTEM AND THE STUDY OF 595 00:26:05,000 --> 00:26:07,560 THE CORD AND MOTOR CORTEX AND 596 00:26:07,560 --> 00:26:11,400 GAVE YOU A FLAVOR FOR THIS 597 00:26:11,400 --> 00:26:13,000 INTERACTIVE DATA EXPLORATION 598 00:26:13,000 --> 00:26:13,200 WORK. 599 00:26:13,200 --> 00:26:19,200 THE APPROACH WE'RE TAKING TO THE 600 00:26:19,200 --> 00:26:23,920 COGNITIVE DEFICITS ARE SLIGHTLY 601 00:26:23,920 --> 00:26:24,400 DIFFERENT. 602 00:26:24,400 --> 00:26:31,920 I TOLD ALS IS A SPECTRUM AND 50% 603 00:26:31,920 --> 00:26:39,960 TO 80% WILL HAVE SOME COGNITIVE 604 00:26:39,960 --> 00:26:41,560 DEFICIT AND FTD. 605 00:26:41,560 --> 00:26:43,120 WHAT CAN WE DO WITH PATIENTS ON 606 00:26:43,120 --> 00:26:44,480 THIS CONTINUUM? 607 00:26:44,480 --> 00:26:47,920 YOU HAVE PATIENTS WITH A MOTOR 608 00:26:47,920 --> 00:26:49,320 PHENOTYPE THAT PRESENT WITH 609 00:26:49,320 --> 00:26:51,040 VARYING LEVELS OF COGNITIVE 610 00:26:51,040 --> 00:26:53,000 DEFICITS FROM NONE UP TO AND 611 00:26:53,000 --> 00:26:57,200 INCLUDING FTD. 612 00:26:57,200 --> 00:27:00,480 THE ISSUE IS THAT THE COGNITIVE 613 00:27:00,480 --> 00:27:05,280 PHENOTYPING IS A BIT HIT OR MISS 614 00:27:05,280 --> 00:27:09,680 IN NORTH AMERICAN TESTING AND 615 00:27:09,680 --> 00:27:12,560 NOT EVERY CLINIC WILL DO THIS 616 00:27:12,560 --> 00:27:13,960 AND DEPENDS WHERE THEY'RE SEEN 617 00:27:13,960 --> 00:27:17,680 AND IF WHEN THEY DO ADMINISTER 618 00:27:17,680 --> 00:27:19,600 COGNITIVE PHENOTYPING, THE TESTS 619 00:27:19,600 --> 00:27:24,800 THEY USE CAN VARY WIDELY. 620 00:27:24,800 --> 00:27:26,680 THERE'S ONLY FOUR CLINICS IN 621 00:27:26,680 --> 00:27:29,000 NORTH AMERICA SOON TO BE FIVE, I 622 00:27:29,000 --> 00:27:30,600 HOPE USING A TEST WIDELY USED IN 623 00:27:30,600 --> 00:27:33,000 THE ALS COMMUNITY IN EUROPE. 624 00:27:33,000 --> 00:27:39,520 SO WE'RE SO WE'RE A BIT LIMITED 625 00:27:39,520 --> 00:27:43,360 MOVED TO ANOTHER SITE THE 626 00:27:43,360 --> 00:27:50,120 UNIVERSITY OF EDINBURGH AND IT'S 627 00:27:50,120 --> 00:27:52,720 USED IN SOME CLINICS IN THE U.S. 628 00:27:52,720 --> 00:27:55,160 HERE THEY DESIGN A SCREEN FOR 629 00:27:55,160 --> 00:27:56,160 PATIENTS WITH PHYSICAL 630 00:27:56,160 --> 00:28:00,640 IMPAIRMENT THAT TESTS ALS 631 00:28:00,640 --> 00:28:03,080 SPECIFIC AND ALS NON-SPECIFIC 632 00:28:03,080 --> 00:28:13,000 COGNITIVE DOMAINS AND WE'LL 633 00:28:13,000 --> 00:28:18,160 LEVERAGE PATHOLOGY TO ASSESS 634 00:28:18,160 --> 00:28:19,760 THIS ALONG THE SPECTRUM AND WE 635 00:28:19,760 --> 00:28:22,160 KNOW THERE'S DIFFERENT PATTERNS. 636 00:28:22,160 --> 00:28:23,640 IT COMES IN MANY DIFFERENT 637 00:28:23,640 --> 00:28:24,160 FLAVORS. 638 00:28:24,160 --> 00:28:29,000 IT CAN ALSO BE IN DIFFERENT CELL 639 00:28:29,000 --> 00:28:30,680 TYPES PREDOMINANTLY NEURONAL AND 640 00:28:30,680 --> 00:28:33,920 MIXED AND GLIAL. 641 00:28:33,920 --> 00:28:40,080 THE RELATION BETWEEN TDP-43 642 00:28:40,080 --> 00:28:41,160 PATHOLOGY IS POORLY UNDERSTAND 643 00:28:41,160 --> 00:28:44,920 AND WE HAVE THIS COHORT IN 644 00:28:44,920 --> 00:28:45,840 EDINBURGH WITH MOTOR AND 645 00:28:45,840 --> 00:28:49,000 COGNITIVE ASSESSMENTS EVERY SIX 646 00:28:49,000 --> 00:28:56,120 MONTHS AND SEMI QUANTITATIVE 647 00:28:56,120 --> 00:28:57,760 STAINING. 648 00:28:57,760 --> 00:29:02,200 WE PICKED TWO REGIONS AND HAVE 649 00:29:02,200 --> 00:29:05,000 CORRELATES OF EXECUTIVE AND 650 00:29:05,000 --> 00:29:07,240 LANGUAGE FUNCTION AND SATISFIED 651 00:29:07,240 --> 00:29:10,480 THEM ON THE EXTENT OF COGNITIVE 652 00:29:10,480 --> 00:29:11,480 DYSFUNCTION ON THE SCORES. 653 00:29:11,480 --> 00:29:14,120 NOW WE WANT TO ASK WHAT ARE THE 654 00:29:14,120 --> 00:29:15,200 CHANGES IN CELL STATE AND 655 00:29:15,200 --> 00:29:17,920 FUNCTION THAT UNDER LIE THE 656 00:29:17,920 --> 00:29:19,880 DEVELOPMENT OF COGNITIVE 657 00:29:19,880 --> 00:29:24,160 IMPAIRMENT IN ALS FTD AND HOW DO 658 00:29:24,160 --> 00:29:25,000 AGGREGATES AFFECT SURROUNDING 659 00:29:25,000 --> 00:29:29,000 CELLS? 660 00:29:29,000 --> 00:29:31,080 WE WANT TO IDENTIFY FEATURES AND 661 00:29:31,080 --> 00:29:33,000 PROGRAMS THAT CORRELATE WITH 662 00:29:33,000 --> 00:29:35,600 THIS COGNITIVE IMPAIRMENT. 663 00:29:35,600 --> 00:29:37,920 WE NEED THE CLINICAL 664 00:29:37,920 --> 00:29:38,840 PATHOLOGICALLY STRATIFIED COHORT 665 00:29:38,840 --> 00:29:41,040 AND NEED WAYS TO MEASURE GENE 666 00:29:41,040 --> 00:29:44,160 EXPRESSION I DESCRIBED AND THEN 667 00:29:44,160 --> 00:29:49,560 YOU ALSO WANT WAY TO LINK THIS 668 00:29:49,560 --> 00:29:51,960 TO SPECIFIC CELL TYPES MEASURES 669 00:29:51,960 --> 00:29:55,360 OF PATHOMNEMONIC INCLUSIONS AND 670 00:29:55,360 --> 00:29:58,960 NEED WAYS TO DO MULTIPLE 671 00:29:58,960 --> 00:30:00,960 ANTIBODY STAINS AT THE SAME TIME 672 00:30:00,960 --> 00:30:01,240 ESSENTIALLY. 673 00:30:01,240 --> 00:30:02,120 I'LL TELL YOU ABOUT THE ANTIBODY 674 00:30:02,120 --> 00:30:06,080 STUFF FIRST. 675 00:30:06,080 --> 00:30:11,000 WE DEVELOPED A PROTOCOL FOR 676 00:30:11,000 --> 00:30:11,240 IMAGING. 677 00:30:11,240 --> 00:30:14,120 THEY DEVELOPED THIS FOR CELL 678 00:30:14,120 --> 00:30:18,080 CULTURE WHERE THEY STAINED, 679 00:30:18,080 --> 00:30:20,080 IMAGES MULTIPLE ANTIBODIES FROM 680 00:30:20,080 --> 00:30:22,480 THE SAME GROUPS OF CELLS AND 681 00:30:22,480 --> 00:30:30,920 HERE'S AN AG GR-- AGGREGATION O 682 00:30:30,920 --> 00:30:33,080 ALL THE DATA AND THEY REALIZED 683 00:30:33,080 --> 00:30:34,680 THERE'S CROSS LINKING OF THE 684 00:30:34,680 --> 00:30:35,920 ANTIBODY TO THE ANTIGEN WHEN YOU 685 00:30:35,920 --> 00:30:38,120 DO THE IMAGING. 686 00:30:38,120 --> 00:30:40,440 THEY DEVELOPED WAYS TO QUENCH 687 00:30:40,440 --> 00:30:45,320 THIS PHOTO CROSS LINKING BY 688 00:30:45,320 --> 00:30:50,600 DOING THESE EXPERIMENTS IN 689 00:30:50,600 --> 00:30:54,560 PUFFERS THAT HAVE MILD DNA 690 00:30:54,560 --> 00:30:56,120 CONDITIONS. 691 00:30:56,120 --> 00:30:57,760 THAT'S WHERE THE ITERATIVE 692 00:30:57,760 --> 00:30:59,520 MACHINE COMES IN. 693 00:30:59,520 --> 00:31:02,920 YOU DO THE STAIN, IMAGE AND DO 694 00:31:02,920 --> 00:31:05,000 THIS BEFORE YOU DO YOUR NEXT 695 00:31:05,000 --> 00:31:07,840 ROUND. 696 00:31:07,840 --> 00:31:11,040 WE OPTIMIZED THE PROTOCOL 697 00:31:11,040 --> 00:31:11,400 FOR--SECTION. 698 00:31:11,400 --> 00:31:14,680 WE HAD TO TWEAK THE ILLUSION 699 00:31:14,680 --> 00:31:15,320 BUFFER A LITTLE BIT. 700 00:31:15,320 --> 00:31:20,680 TWEAK THE TYPE OF SLIDES WE 701 00:31:20,680 --> 00:31:22,680 SECTIONS THE--ON TO WARMED THE 702 00:31:22,680 --> 00:31:25,760 SLIDE WITH THE FINGER A LITTLE 703 00:31:25,760 --> 00:31:29,480 BIT TO MAKE SURE IT STICKS AND 704 00:31:29,480 --> 00:31:32,080 ASSEMBLED BEFORE WE DO THE 705 00:31:32,080 --> 00:31:35,800 SECTIONING IB VISIUM AND AT OPT 706 00:31:35,800 --> 00:31:36,960 MISSING OF THIS PROTOCOL WHERE 707 00:31:36,960 --> 00:31:44,120 WE USED A REPURPOSED 708 00:31:44,120 --> 00:31:46,760 DECOMMISSIONED MACHINE MACHINE 709 00:31:46,760 --> 00:31:48,080 AND INCREASED THE THROUGHPUT OF 710 00:31:48,080 --> 00:31:52,240 MULTI DAY EXPERIMENTS AND SHOW 711 00:31:52,240 --> 00:31:55,320 REPRODUCIBILITY AND ACCURATE 712 00:31:55,320 --> 00:31:55,760 LOGGING. 713 00:31:55,760 --> 00:31:58,520 WE MADE USE OF THE INTEGRATED 714 00:31:58,520 --> 00:31:59,160 FLUID CAPABILITIES. 715 00:31:59,160 --> 00:32:03,920 THIS WAS IN COLLABORATION WITH 716 00:32:03,920 --> 00:32:06,200 THE TECHNOLOGY LAB AND AN 717 00:32:06,200 --> 00:32:08,120 TALENTED ENGINEER AT THE NEW 718 00:32:08,120 --> 00:32:14,560 YORK GENOME KRRT. 719 00:32:14,560 --> 00:32:17,000 A Ph.D. STUDENT WORKED WITH THEM 720 00:32:17,000 --> 00:32:20,120 TO DESIGN THE CUSTOM BUILT FLOAT 721 00:32:20,120 --> 00:32:23,160 CELL THE GLASS SLIDE WITH HOLES 722 00:32:23,160 --> 00:32:33,680 IN IT TO ALLOW TUBING AND THEY 723 00:32:35,680 --> 00:32:40,720 USE THE TAPE THEY PUT ON ROCKETS 724 00:32:40,720 --> 00:32:44,160 AND THERE'S A COVER GLASS THAT 725 00:32:44,160 --> 00:32:49,000 BUI 726 00:32:49,000 --> 00:32:52,480 BUILDS LAYERS FOR MULTIPLE 727 00:32:52,480 --> 00:32:56,120 LAYERS OF TISSUE AND THEY THEN 728 00:32:56,120 --> 00:32:58,840 OPTIMIZED THIS FOR THE HUMAN 729 00:32:58,840 --> 00:33:02,200 SPINAL CORD WITH THE DIFFERENT 730 00:33:02,200 --> 00:33:04,360 ANTIBODIES AND HERE'S THE 731 00:33:04,360 --> 00:33:06,280 EXAMPLE OF THE DATA YOU CAN GET 732 00:33:06,280 --> 00:33:12,880 ON THE ANTIBODIES ON THE HUMAN 733 00:33:12,880 --> 00:33:13,040 ONE. 734 00:33:13,040 --> 00:33:15,200 IN THE FLOW CELL WE KNOW TISSUES 735 00:33:15,200 --> 00:33:17,920 STAY TABLE UP TO TWO WEEKS AND 736 00:33:17,920 --> 00:33:18,960 YOU HAVE TO DO OPTIMIZATION OF 737 00:33:18,960 --> 00:33:20,120 THE ANTIBODIES TO MAKE SURE THEY 738 00:33:20,120 --> 00:33:22,440 CAN WORK IN DIFFERENT CYCLES. 739 00:33:22,440 --> 00:33:24,000 YOU CAN DO UP TO 10 CYCLES BUT 740 00:33:24,000 --> 00:33:25,760 YOU HAVE TO MAKE SURE THE 741 00:33:25,760 --> 00:33:27,840 ANTIBODY GIVES YOU THE SAME KIND 742 00:33:27,840 --> 00:33:29,040 OF SIGNAL IN THE FIRST AS IN THE 743 00:33:29,040 --> 00:33:33,560 10th CYCLE. 744 00:33:33,560 --> 00:33:35,600 THE CYCLE IN WHICH YOU PUT THEM 745 00:33:35,600 --> 00:33:36,880 IS IMPORTANT. 746 00:33:36,880 --> 00:33:38,120 THERE'S OPTIMIZATION INVOLVED UP 747 00:33:38,120 --> 00:33:39,120 FRONT. 748 00:33:39,120 --> 00:33:42,560 WHEN HAVE YOU THAT WORKED OUT 749 00:33:42,560 --> 00:33:44,120 YOU GET NICE DATA. 750 00:33:44,120 --> 00:33:47,000 THEN THE DESIGN OF THE 751 00:33:47,000 --> 00:33:47,680 MULTI-MODEL EXPERIMENTS IS YOU 752 00:33:47,680 --> 00:33:51,440 HAVE ONE SECTION OF TISSUE YOU 753 00:33:51,440 --> 00:33:54,640 USE AND TAKE THE SECTION AND 754 00:33:54,640 --> 00:33:57,560 ASSEMBLE THE FLOAT CELL AND CAN 755 00:33:57,560 --> 00:34:07,640 DO ALL THE MULTIPLEXED 756 00:34:07,640 --> 00:34:09,920 IMMUNOFLUORESCENCE AND YOU CAN 757 00:34:09,920 --> 00:34:13,480 USE THIS FOR WATCHING AN 758 00:34:13,480 --> 00:34:16,040 ILLUSION AND TAKING PICTURES AND 759 00:34:16,040 --> 00:34:20,120 TAKE A THIRD PICTURE FOR IN SITU 760 00:34:20,120 --> 00:34:21,200 BASED LOCATIONS AND GET YOUR 761 00:34:21,200 --> 00:34:22,360 FAVORITE TRANSCRIPT. 762 00:34:22,360 --> 00:34:28,400 THE IDEA IS TO COMBINE ALL OF 763 00:34:28,400 --> 00:34:31,960 THIS AND BUILD A SUITE OF TOOLS 764 00:34:31,960 --> 00:34:34,040 AND ANTIBODIES TO GIVE YOU THE 765 00:34:34,040 --> 00:34:34,840 MAXIMUM AMOUNT OF INFORMATION 766 00:34:34,840 --> 00:34:40,160 YOU NEED TO TELL YOU WHAT'S 767 00:34:40,160 --> 00:34:45,920 GOING ON WITH DISEASE. 768 00:34:45,920 --> 00:34:47,680 I HAVE A LITTLE BIT OF TIME SO I 769 00:34:47,680 --> 00:34:50,640 CAN TELL YOU NEW STUFF WHAT THE 770 00:34:50,640 --> 00:34:56,000 DATA FOR THE CORTEX BEGINS TO 771 00:34:56,000 --> 00:35:00,600 LOOK LIKE I TOLD YOU WE HAD TO 772 00:35:00,600 --> 00:35:06,200 DO THIS ANNOTATION STUFF. 773 00:35:06,200 --> 00:35:10,480 SO SHE DID ANNOTATION FOR DOWN 774 00:35:10,480 --> 00:35:11,160 STREAM ANALYSIS. 775 00:35:11,160 --> 00:35:13,440 THAT'S HOW WE'LL EXTRACT 776 00:35:13,440 --> 00:35:14,160 LAYER-SPECIFIC DIFFERENCES. 777 00:35:14,160 --> 00:35:17,040 SHE STARTED BY IDENTIFYING GRAY 778 00:35:17,040 --> 00:35:18,800 VERSUS WHITE MATTER BOUNDARIES 779 00:35:18,800 --> 00:35:20,840 BASED ON THE PRESENCE OF 780 00:35:20,840 --> 00:35:21,080 NEURONS. 781 00:35:21,080 --> 00:35:23,600 SHE THEN WORKED AWAY FROM THAT 782 00:35:23,600 --> 00:35:26,120 TO IDENTIFY THE LARGE PARAMETER 783 00:35:26,120 --> 00:35:32,200 CELLS THAT MARK LAYER 5. 784 00:35:32,200 --> 00:35:35,760 THE THEN IDENTIFIED LAYER 4 BY 785 00:35:35,760 --> 00:35:44,160 THE NEURONS ADJACENT TO LAYER 5 786 00:35:44,160 --> 00:35:46,680 AND YOU COULD I WHY DIDN'T YOU 787 00:35:46,680 --> 00:35:48,440 USE SPECIFIC MARKERS FOR THIS? 788 00:35:48,440 --> 00:35:50,880 WE WANTED AN INDEPENDENT WAY OF 789 00:35:50,880 --> 00:35:55,360 ASSIGNING SPOTS TO LAYERS 790 00:35:55,360 --> 00:35:57,720 BECAUSE WE WANTED TO EXTRACT 791 00:35:57,720 --> 00:36:01,320 CONTRIBUTION TO DIFFERENTIAL 792 00:36:01,320 --> 00:36:03,760 GENE EXPRESSION. 793 00:36:03,760 --> 00:36:08,160 IF WE IDENTIFIED THE LAYERS WE 794 00:36:08,160 --> 00:36:12,320 WOULD BE DOING IT A BIT 795 00:36:12,320 --> 00:36:12,840 CIRCULAR. 796 00:36:12,840 --> 00:36:14,000 WE WANTED TO RELY ON THE 797 00:36:14,000 --> 00:36:22,680 FEATURES TO DO THIS ANNOTATION. 798 00:36:22,680 --> 00:36:24,960 THE GREATEST VARIATION WERE 799 00:36:24,960 --> 00:36:28,480 EXPLAINED BY THE CORTICAL LAYER 800 00:36:28,480 --> 00:36:30,800 AND WANTED TO USE SYSTEM -- IT 801 00:36:30,800 --> 00:36:32,840 WASN'T WHETHER A SAMPLE WAS 802 00:36:32,840 --> 00:36:34,280 CONTROLLED OR ALS OR WHETHER IT 803 00:36:34,280 --> 00:36:36,680 HAD OR DID NOT HAVE COGNITIVE 804 00:36:36,680 --> 00:36:36,960 IMPAIRMENT. 805 00:36:36,960 --> 00:36:38,960 THE LARGEST VARIATION IS COMING 806 00:36:38,960 --> 00:36:40,200 FROM WHICH LAYER YOU'VE ASSIGNED 807 00:36:40,200 --> 00:36:44,760 A SPOT TO. 808 00:36:44,760 --> 00:36:48,000 THIS IS QUANTIFYING ALL OF THAT 809 00:36:48,000 --> 00:36:51,760 AND ALL THE SAMPLES THE CONTROL 810 00:36:51,760 --> 00:36:52,960 ALS WITH IMPAIRMENT AND THEY 811 00:36:52,960 --> 00:36:55,000 HAVE THE SAME DISTRIBUTION OF 812 00:36:55,000 --> 00:36:58,280 SPOTS ACROSS ALL THE LAYERS. 813 00:36:58,280 --> 00:37:02,800 NOW WE CAN TAKE THE 814 00:37:02,800 --> 00:37:04,280 TRANSCRIPTOME MEASUREMENTS AND 815 00:37:04,280 --> 00:37:08,160 SAY ARE WE RECAPITULATING THE 816 00:37:08,160 --> 00:37:15,560 LAYER EXPRESSION AND WE ARE. 817 00:37:15,560 --> 00:37:17,440 SO THEN WE CAN DO CO-EXPRESSION 818 00:37:17,440 --> 00:37:20,800 ANALYSIS LIKE WE DID FOR THE 819 00:37:20,800 --> 00:37:25,040 MOUSE COHORT TO IDENTIFY MODULES 820 00:37:25,040 --> 00:37:30,280 OF GENESES WHO IS EXPRESSION 821 00:37:30,280 --> 00:37:34,040 COVARIES AND LOOK AT THE CELL 822 00:37:34,040 --> 00:37:34,680 SPECIFIC CONTRIBUTION TO THE 823 00:37:34,680 --> 00:37:37,920 EXPRESSION MODULES AND BECAUSE 824 00:37:37,920 --> 00:37:43,200 OF THE LINEAR MODEL HOW WE BUILD 825 00:37:43,200 --> 00:37:47,080 IT WE CAN SAY HOW MUCH IS 826 00:37:47,080 --> 00:37:50,600 ASCRIBABLE TO WHETHER YOU HAVE 827 00:37:50,600 --> 00:37:54,000 TDP-43 INCLUSIONS AND WE'RE 828 00:37:54,000 --> 00:37:58,920 RELYING ON THE STAINING THE PATH 829 00:37:58,920 --> 00:38:01,040 LAB PROVIDED. 830 00:38:01,040 --> 00:38:03,840 SO MODULE 4 FOR EXAMPLE IS 831 00:38:03,840 --> 00:38:06,240 UPREGULATED IN THE UPPER 832 00:38:06,240 --> 00:38:08,240 CORTICAL LAYERS HERE OF ALS 833 00:38:08,240 --> 00:38:09,200 PATIENTS WHEN THEY HAVE 834 00:38:09,200 --> 00:38:10,600 COGNITIVE IMPAIRMENT. 835 00:38:10,600 --> 00:38:13,040 HERE'S A CONTROL GROUP AND ALS 836 00:38:13,040 --> 00:38:17,720 WITH MOTOR ONLY AND HERE'S ALS 837 00:38:17,720 --> 00:38:18,600 WITH COGNITIVE IMPAIRMENT. 838 00:38:18,600 --> 00:38:21,000 YOU CAN SEE THIS IN THE UPPER 839 00:38:21,000 --> 00:38:23,360 THREE LAYERS. 840 00:38:23,360 --> 00:38:29,000 WHAT IS MODULE 4 MADE UP OF? 841 00:38:29,000 --> 00:38:31,240 IT'S ESSENTIALLY INFLAMMATORY 842 00:38:31,240 --> 00:38:31,560 SIGNALLING. 843 00:38:31,560 --> 00:38:32,200 WHICH CELL TYPES CONTRIBUTE TO 844 00:38:32,200 --> 00:38:35,920 THIS? 845 00:38:35,920 --> 00:38:41,240 IT'S BETWEEN MICROGLIA, 846 00:38:41,240 --> 00:38:48,080 ASTROCYTES AND ENDOTHELIAL CELLS 847 00:38:48,080 --> 00:38:49,520 AND YOU HAVE A SIGNAL 848 00:38:49,520 --> 00:38:52,840 COORDINATED BETWEEN ASTROCYTES, 849 00:38:52,840 --> 00:38:57,800 MICROGLIA AND ENDOTHELIAL CELLS 850 00:38:57,800 --> 00:38:59,960 HIGHLY SPECIFICALLY CORRELATED 851 00:38:59,960 --> 00:39:01,120 WHETHER A POPULATION HAS 852 00:39:01,120 --> 00:39:04,280 COGNITIVE IMPAIRMENTS IN 853 00:39:04,280 --> 00:39:06,640 ADDITION TO PHENOTYPES AND DON'T 854 00:39:06,640 --> 00:39:10,320 AND WHEN YOU SEE HOW DOES TDP-43 855 00:39:10,320 --> 00:39:12,440 RELATES TO THIS, IF YOU JUST 856 00:39:12,440 --> 00:39:13,480 LOOK AT THE CONTRIBUTION YOU 857 00:39:13,480 --> 00:39:16,080 DON'T PICK THIS OUT. 858 00:39:16,080 --> 00:39:17,080 THIS APPEARS TO BE SOMETHING 859 00:39:17,080 --> 00:39:20,160 SPECIFIC TO THE COGNITIVE 860 00:39:20,160 --> 00:39:20,480 IMPAIRMENT. 861 00:39:20,480 --> 00:39:23,120 AND NOT NECESSARILY WHEN DRIVEN 862 00:39:23,120 --> 00:39:28,480 BY THE TDP-43 PATHOLOGY. 863 00:39:28,480 --> 00:39:30,960 SO NOW WE CAN SEE -- NOW WE CAN 864 00:39:30,960 --> 00:39:32,680 TAKE THE ADJACENT SECTIONS WE 865 00:39:32,680 --> 00:39:35,200 BANKED AND SAY HOW VALID IS 866 00:39:35,200 --> 00:39:35,440 THIS? 867 00:39:35,440 --> 00:39:37,040 WHAT IF YOU REALLY WENT IN AND 868 00:39:37,040 --> 00:39:40,120 LOOKED AT OTHER WAYS OF LOOKING 869 00:39:40,120 --> 00:39:42,440 AT TDP-43 CONFIRMATIONS? 870 00:39:42,440 --> 00:39:46,680 CAN YOU START TO TEASE THIS 871 00:39:46,680 --> 00:39:47,000 APART? 872 00:39:47,000 --> 00:39:48,800 DOES IT HAVE SOMETHING TO DO 873 00:39:48,800 --> 00:39:50,640 WITH WHERE AND WHICH CELL TYPES 874 00:39:50,640 --> 00:39:52,520 AND SO ON? 875 00:39:52,520 --> 00:39:56,160 SO, SPATIAL TRANSCRIPTOMICS CAN 876 00:39:56,160 --> 00:39:58,160 LOOK AT PATTERNS SHARED WITHIN 877 00:39:58,160 --> 00:40:00,560 CELLULAR NEIGHBORHOODS AND 878 00:40:00,560 --> 00:40:02,360 STRATIFYING SUBJECTS BASED ON 879 00:40:02,360 --> 00:40:04,720 COGNITIVE AND PATHOLOGICAL 880 00:40:04,720 --> 00:40:08,600 PHENOTYPING CAN REVEAL DISTINCT 881 00:40:08,600 --> 00:40:12,160 SETS OF GENE EXPRESSION 882 00:40:12,160 --> 00:40:12,480 PERTURBATIONS. 883 00:40:12,480 --> 00:40:13,920 I'M GOING TO GIVE YOU A FLAVOR 884 00:40:13,920 --> 00:40:19,880 OF HOW WE'RE APPROACHING THIS IN 885 00:40:19,880 --> 00:40:22,080 NON-DISEASED CNS SAMPLES THROUGH 886 00:40:22,080 --> 00:40:23,080 THE COLOMBIA UNIVERSITY 887 00:40:23,080 --> 00:40:25,040 SENESCENCE TISSUE SAMPLING 888 00:40:25,040 --> 00:40:35,520 CENTER ON WHICH I WORK WITH 889 00:40:35,760 --> 00:40:37,000 PATHOLOGISTS. 890 00:40:37,000 --> 00:40:42,400 OUR GOAL IS TO BUILD AN AN ATLAS 891 00:40:42,400 --> 00:40:43,920 OF SENESCENCE ACROSS THE BRAIN 892 00:40:43,920 --> 00:40:44,800 AND SPINAL CORD THROUGHOUT THE 893 00:40:44,800 --> 00:40:45,240 LIFE SPAN. 894 00:40:45,240 --> 00:40:47,920 THIS IS CHALLENGING BECAUSE WE 895 00:40:47,920 --> 00:40:50,240 DON'T REALLY KNOW WHAT 896 00:40:50,240 --> 00:40:52,120 SENESCENCE LOOKS LIKE IN THE 897 00:40:52,120 --> 00:40:53,600 CONTEXT OF TISSUE IN THESE CELLS 898 00:40:53,600 --> 00:40:55,560 AND THAT'S THE POINT OF THE 899 00:40:55,560 --> 00:40:58,080 SENESCENCE NETWORK THE COMMON 900 00:40:58,080 --> 00:41:02,920 FUND PUT TOGETHER IS TO MAP 901 00:41:02,920 --> 00:41:04,080 EXACTLY WHAT SENESCENCE LOOKS 902 00:41:04,080 --> 00:41:08,760 LIKE ACROSS THE LIFE SPAN AND 903 00:41:08,760 --> 00:41:11,600 WE'RE LOOKING AT THE SAME REGION 904 00:41:11,600 --> 00:41:14,800 OF THE CORTEX WE'RE LOOKING AT 905 00:41:14,800 --> 00:41:20,200 CASES AND THE LUMBAR CORD, THE 906 00:41:20,200 --> 00:41:23,280 REGION IN THE FTD CASES AND 907 00:41:23,280 --> 00:41:24,600 HIPPOCAMPUS WHERE WE ARE 908 00:41:24,600 --> 00:41:26,200 EXPECTING TO SEE CHANGES 909 00:41:26,200 --> 00:41:27,160 ASSOCIATED WITH AGE. 910 00:41:27,160 --> 00:41:34,640 WE ARE RELYING ON SAMPLES FROM 911 00:41:34,640 --> 00:41:35,720 THE UNIVERSITY OF EDINBURGH 912 00:41:35,720 --> 00:41:37,720 BRAIN BANK AND LOOKING AT 20 913 00:41:37,720 --> 00:41:40,640 MALES AND 20 FEMALES FROM EACH 914 00:41:40,640 --> 00:41:42,320 AGE BIN WE'RE GOING TO BE DOING 915 00:41:42,320 --> 00:41:51,680 A COMBINATION OF VISIUM LIKE I 916 00:41:51,680 --> 00:41:56,200 DESCRIBED AND RNA SYNC TO BUILD 917 00:41:56,200 --> 00:42:01,640 THEM BACK ON TO SPACE AND TIME. 918 00:42:01,640 --> 00:42:02,680 SO IT'S RIGHT AT 12:45. 919 00:42:02,680 --> 00:42:04,080 I'D LIKE TO THANK ALL THE 920 00:42:04,080 --> 00:42:07,720 PATIENTS WHO PARTICIPATED IN 921 00:42:07,720 --> 00:42:08,080 THESE STUDIES. 922 00:42:08,080 --> 00:42:13,560 THE PEOPLE I DID THE WORK ARE 923 00:42:13,560 --> 00:42:19,440 CYLUS WHO LED THE MOUSE ST AND 924 00:42:19,440 --> 00:42:22,400 JOANNA WHO WORKED ON THE 925 00:42:22,400 --> 00:42:29,160 AUTOMATION OF THE 4I AND WE 926 00:42:29,160 --> 00:42:31,280 PARTNERED AND CONTINUED TO HAVE 927 00:42:31,280 --> 00:42:36,320 A CLOSE PARTNERSHIP WITH 928 00:42:36,320 --> 00:42:38,200 PHYSICALLY SHARED SPACE AT THE 929 00:42:38,200 --> 00:42:44,200 NYU AND WORKED WITH A GROUP AND 930 00:42:44,200 --> 00:42:49,800 THEY'RE WORKING TO BAKE INTO 931 00:42:49,800 --> 00:42:53,000 SPLOTCH THESE SINGLE NUKE 932 00:42:53,000 --> 00:42:54,960 MEASUREMENTS TO GET DIFFERENTIAL 933 00:42:54,960 --> 00:42:59,400 EXPRESSION IN SPACE ALONG WITH 934 00:42:59,400 --> 00:43:02,240 THE CONTRIBUTION OF THE CELL 935 00:43:02,240 --> 00:43:04,080 TYPES AND AT UNIVERSITY OF 936 00:43:04,080 --> 00:43:05,880 EDINBURGH THE WOULD NOT HAVE 937 00:43:05,880 --> 00:43:08,520 HAPPENED WITHOUT THE SAMPLES 938 00:43:08,520 --> 00:43:14,480 COLIN SMITH ASSEMBLED THERE WAS 939 00:43:14,480 --> 00:43:17,000 A THANK YOU SLIDE FOUR GUYS THAT 940 00:43:17,000 --> 00:43:20,200 APPARENTLY IS HERE. 941 00:43:20,200 --> 00:43:30,720 THANK YOU FOR YOUR ATTENTION. 942 00:43:36,200 --> 00:43:40,520 >>REALLY GREAT TALK. 943 00:43:40,520 --> 00:43:44,000 I WAS CURIOUS IN YOUR ALS FTD 944 00:43:44,000 --> 00:43:45,400 STUDY DID YOU TRY TO STRATIFY 945 00:43:45,400 --> 00:43:48,560 BASED ON ANY OTHER PATHOLOGY 946 00:43:48,560 --> 00:43:51,840 LIKE FTP PIT OR A PARTICULAR 947 00:43:51,840 --> 00:43:54,960 COGNITIVE PHENOTYPE? 948 00:43:54,960 --> 00:43:56,080 >>NOT YET. 949 00:43:56,080 --> 00:43:59,200 >>THAT'S PARTLY WHAT ALL THE 950 00:43:59,200 --> 00:44:00,400 IMAGING STUFF IS MEANT TO BE 951 00:44:00,400 --> 00:44:10,880 ABLE TO ACCOMMODATE LATER. 952 00:44:11,680 --> 00:44:13,040 >>A BEAUTIFULLY CLEAR 953 00:44:13,040 --> 00:44:14,480 PRESENTATION. 954 00:44:14,480 --> 00:44:17,040 DO YOU HAVE ANY WAY OF 955 00:44:17,040 --> 00:44:22,120 ESTIMATING WHETHER THE CELLS ARE 956 00:44:22,120 --> 00:44:28,800 LOST 957 00:44:28,800 --> 00:44:32,200 >>WE CAN DO THAT FOR MICE BUT 958 00:44:32,200 --> 00:44:34,920 CAN'T REALLY DO THAT FOR HUMANS. 959 00:44:34,920 --> 00:44:42,320 THAT WAS WHY WE WENT TO THIS CAN 960 00:44:42,320 --> 00:44:45,280 WE USE THE CLINICAL STRATIFY TO 961 00:44:45,280 --> 00:44:47,000 LOOK AT EARLY VERSUS LATE IN 962 00:44:47,000 --> 00:44:49,840 DISEASE AND THAT'S THE CLOSEST 963 00:44:49,840 --> 00:44:50,880 WE CAN COME TO PATIENTS WHO HAVE 964 00:44:50,880 --> 00:45:00,520 DIED OF THE DISEASE. 965 00:45:00,520 --> 00:45:07,520 >>THREW -- THANK YOU FOR THE 966 00:45:07,520 --> 00:45:09,080 TALK AND FOR PIONEERING THE 967 00:45:09,080 --> 00:45:10,600 APPROACHES WE'LL GET TO USE. 968 00:45:10,600 --> 00:45:12,240 I'M WONDERING WITH THE MODULES 969 00:45:12,240 --> 00:45:13,840 WITH MULTIPLE CELLULAR 970 00:45:13,840 --> 00:45:16,160 COMPONENTS IN THEM IS IT BECAUSE 971 00:45:16,160 --> 00:45:18,040 YOU HAVE SIGNALLING THAT ARE 972 00:45:18,040 --> 00:45:19,480 COVARYING OR EXACTLY WHAT'S 973 00:45:19,480 --> 00:45:20,360 GOING ON THERE? 974 00:45:20,360 --> 00:45:25,320 CAN YOU TAKE A DEEPER LOOK? 975 00:45:25,320 --> 00:45:30,160 >>SO, THE WAY I INTERPRET IT IS 976 00:45:30,160 --> 00:45:34,720 IN THAT REGION THERE'S A 977 00:45:34,720 --> 00:45:36,560 CONCERTED RESPONSE BY THREE 978 00:45:36,560 --> 00:45:37,120 TYPES OF CELLS. 979 00:45:37,120 --> 00:45:39,640 NOW WE CAN GO BACK TO THE DISH 980 00:45:39,640 --> 00:45:42,560 AND SAY IF YOU IT'S THIS OUT HOW 981 00:45:42,560 --> 00:45:45,040 ARE THEY TALKING TO ONE ANOTHER? 982 00:45:45,040 --> 00:45:47,520 WHICH ONE IS DRIVING WHAT? 983 00:45:47,520 --> 00:45:50,040 WHICH ONE IS PRIMARY AND THEN 984 00:45:50,040 --> 00:45:51,520 WHAT ARE THE EFFECTS IT'S HAVING 985 00:45:51,520 --> 00:45:53,040 ON THE NEURONS AND THAT'S PARTLY 986 00:45:53,040 --> 00:45:53,800 WHY WE HAVE SO MUCH FUN WORKING 987 00:45:53,800 --> 00:46:04,040 WITH MICHAEL. 988 00:46:06,400 --> 00:46:09,000 >>GREAT TALK. 989 00:46:09,000 --> 00:46:14,440 YOU TALKED BY STRATIFYING BY 990 00:46:14,440 --> 00:46:16,200 DIFFERENT GENE EXPRESSION 991 00:46:16,200 --> 00:46:16,520 DIFFERENCES. 992 00:46:16,520 --> 00:46:19,760 HAVE YOU GONE THE OTHER 993 00:46:19,760 --> 00:46:23,800 DIRECTION SO LOOKED AT HOW 994 00:46:23,800 --> 00:46:25,360 VARIOUS PATTERNS OF EXPRESSION 995 00:46:25,360 --> 00:46:27,760 MIGHT ASSOCIATE WITH NOVEL 996 00:46:27,760 --> 00:46:29,200 CLUSTERING OF CLINICAL 997 00:46:29,200 --> 00:46:29,560 PHENOTYPES? 998 00:46:29,560 --> 00:46:31,320 >>NOT YET BUT WHEN WE BUILD 999 00:46:31,320 --> 00:46:32,360 THIS OUT MORE THAT'S THE KIND OF 1000 00:46:32,360 --> 00:46:35,240 STUFF WE WANT TO BE ABLE TO DO. 1001 00:46:35,240 --> 00:46:38,160 I TALKED ABOUT THE MOTOR SYSTEM 1002 00:46:38,160 --> 00:46:41,000 AND DLPC IN TWO SEPARATE STUDIES 1003 00:46:41,000 --> 00:46:44,200 BUT REALLY WHAT WE'RE DOING IS 1004 00:46:44,200 --> 00:46:46,000 USING THE SAME PATIENTS FROM 1005 00:46:46,000 --> 00:46:47,440 WHOM WE HAVE ALL THE OTHER DATA 1006 00:46:47,440 --> 00:46:49,800 TYPES AND STUDYING EACH REGIONS 1007 00:46:49,800 --> 00:46:52,440 FROM THE SAME PATIENTS TO START 1008 00:46:52,440 --> 00:46:54,400 TO ANSWER QUESTIONS LIKE THAT. 1009 00:46:54,400 --> 00:46:57,920 SO WHEN YOU GROUP ALS VERSUS NO 1010 00:46:57,920 --> 00:46:59,280 ALS DO YOU SEE ANYTHING THAT 1011 00:46:59,280 --> 00:47:02,200 CORRELATES IN THIS REGION VERSUS 1012 00:47:02,200 --> 00:47:05,720 THAT REGION WITH THIS A SPECIFIC 1013 00:47:05,720 --> 00:47:08,720 TYPE BUT TO GET THE NUMBERS TO 1014 00:47:08,720 --> 00:47:10,000 BE ABLE TO DO THAT RIGHT YOU 1015 00:47:10,000 --> 00:47:12,320 NEED TO GET TO AT LEAST 100 1016 00:47:12,320 --> 00:47:14,560 PATIENTS AND YOU DON'T WANT TO 1017 00:47:14,560 --> 00:47:16,360 MAKE YOUR GROUPS TOO SMALL 1018 00:47:16,360 --> 00:47:18,920 EITHER OTHERWISE YOU LOSE THE 1019 00:47:18,920 --> 00:47:19,360 POWER. 1020 00:47:19,360 --> 00:47:21,760 WE'RE ABOUT A THIRD OF THE WAY 1021 00:47:21,760 --> 00:47:23,200 TO WHERE I WANT US TO BE TO BE 1022 00:47:23,200 --> 00:47:25,040 ABLE TO ANSWER QUESTIONS LIKE 1023 00:47:25,040 --> 00:47:33,160 THAT. 1024 00:47:33,160 --> 00:47:35,560 >>HAVE YOU HAVE PLANS TO EXPAND 1025 00:47:35,560 --> 00:47:38,080 THE DISEASE SETS YOU INCLUDE IN 1026 00:47:38,080 --> 00:47:40,080 THIS BECAUSE THE GENE LIST IN 1027 00:47:40,080 --> 00:47:44,200 THE MODULES ARE REMINISCENT OF 1028 00:47:44,200 --> 00:47:45,640 OTHER DISEASES. 1029 00:47:45,640 --> 00:47:49,000 THERE'S SIMILAR FLAVORS OF 1030 00:47:49,000 --> 00:47:52,480 MICROYES -- MICROGLIA AND 1031 00:47:52,480 --> 00:47:53,200 ASTROCYTES THAT SHOW UP. 1032 00:47:53,200 --> 00:47:56,440 >>WE DO A LOT OF THAT THROUGH 1033 00:47:56,440 --> 00:47:56,960 COLLABORATION. 1034 00:47:56,960 --> 00:47:58,440 THERE'S AGE-RELATED COGNITIVE 1035 00:47:58,440 --> 00:48:01,240 DECLINE AND MCI ASSOCIATED WITH 1036 00:48:01,240 --> 00:48:04,480 AD PROGRESSION WE'RE LOOKING 1037 00:48:04,480 --> 00:48:07,320 INTO IN COLLABORATION WITH OTHER 1038 00:48:07,320 --> 00:48:11,480 GROUPS AT COLUMBIA. 1039 00:48:11,480 --> 00:48:15,160 THERE'S EFFORTS TO BANK ISSUES 1040 00:48:15,160 --> 00:48:18,320 THROUGH THE NEW IMMUNOLOGY GROUP 1041 00:48:18,320 --> 00:48:22,120 AT COLUMBIA AND IF YOU'RE 1042 00:48:22,120 --> 00:48:24,200 INTERESTED IN DOING THAT I'M 1043 00:48:24,200 --> 00:48:26,200 HAPPY TO TALK THROUGH HOW THAT 1044 00:48:26,200 --> 00:48:27,240 CAN WORK. 1045 00:48:27,240 --> 00:48:29,840 WE'LL BE HAPPY TO SHARE AND ANY 1046 00:48:29,840 --> 00:48:31,680 ALL PROTOCOLS THAT YOU NEED. 1047 00:48:31,680 --> 00:48:36,640 >>I'M CURIOUS TO GET YOUR 1048 00:48:36,640 --> 00:48:42,280 THOUGHTS ON USING DIFFERENT 1049 00:48:42,280 --> 00:48:44,160 REGIONS OF TISSUE FROM HUMAN 1050 00:48:44,160 --> 00:48:46,840 SAMPLES AND LEARNING PATHWAYS 1051 00:48:46,840 --> 00:48:48,960 THAT MAY BE IMPORTANT EARLY IN 1052 00:48:48,960 --> 00:48:50,240 THE DISEASE PROGRESSION AND TO 1053 00:48:50,240 --> 00:48:53,000 WHAT EXTENT YOU THINK ANIMAL 1054 00:48:53,000 --> 00:48:55,200 MODELS ARE USEFUL FOR THAT. 1055 00:48:55,200 --> 00:49:00,360 >>IT DEPENDS ON WHAT WE'RE 1056 00:49:00,360 --> 00:49:00,600 MODELLING. 1057 00:49:00,600 --> 00:49:02,200 FOR THE MOTOR SYSTEM WE DAN 1058 00:49:02,200 --> 00:49:07,840 DAN -- -- WE CAN -- FROM THE SOD 1059 00:49:07,840 --> 00:49:09,800 MODEL IT'S A VERY AGGRESSIVE 1060 00:49:09,800 --> 00:49:12,240 MODEL AND ANYTHING THAT CAN GO 1061 00:49:12,240 --> 00:49:13,680 WRONG DOES GO WRONG AND THE TIME 1062 00:49:13,680 --> 00:49:15,480 COURSE IS VERY VERY FAST. 1063 00:49:15,480 --> 00:49:17,000 THE FIRST MODEL, FOR EXAMPLE, IS 1064 00:49:17,000 --> 00:49:23,400 VERY DIFFERENT AND MUCH MORE 1065 00:49:23,400 --> 00:49:23,640 NUANCED. 1066 00:49:23,640 --> 00:49:26,800 WE DON'T KNOW WHICH PATHOLOGIES 1067 00:49:26,800 --> 00:49:29,000 CONVERGE WHEN OR IF THEY DO AT 1068 00:49:29,000 --> 00:49:29,160 ALL. 1069 00:49:29,160 --> 00:49:31,200 THEY MUST AT SOME POINT BECAUSE 1070 00:49:31,200 --> 00:49:35,000 THE SAME TYPES OF CELLS DIE. 1071 00:49:35,000 --> 00:49:36,400 THAT'S WHERE THE ANIMAL MODELS 1072 00:49:36,400 --> 00:49:37,680 BECOME MORE USEFUL AND THERE'S 1073 00:49:37,680 --> 00:49:42,440 AN ASO THAT REVERSE THE CLINICAL 1074 00:49:42,440 --> 00:49:44,200 PRESENTATION AND MODEL AND ONE 1075 00:49:44,200 --> 00:49:47,520 STUDENT IN THE LAB IS WORKING ON 1076 00:49:47,520 --> 00:49:50,480 THE TIME AND DOES IT CONVERGE 1077 00:49:50,480 --> 00:49:52,920 WITH ANYTHING IN THE SOD? 1078 00:49:52,920 --> 00:49:58,720 WHAT IS REVERSED BY THE ASO? 1079 00:49:58,720 --> 00:50:00,440 DID THEY LEAD TO THE FUNCTION IN 1080 00:50:00,440 --> 00:50:02,160 THE FIRST PLACE AND WHEN YOU GET 1081 00:50:02,160 --> 00:50:06,480 TO THAT HOW MANY ARE SEEN IN ALS 1082 00:50:06,480 --> 00:50:09,000 PATIENTS AND HOW MANY OF THOSE 1083 00:50:09,000 --> 00:50:12,040 SERVE TO SEPARATE PATIENTS INTO 1084 00:50:12,040 --> 00:50:12,960 DIFFERENT TYPES OF PROGRESSION? 1085 00:50:12,960 --> 00:50:14,440 SO THOSE ARE THE KINDS OF 1086 00:50:14,440 --> 00:50:17,040 APPROACHES THAT WE CAN TAKE WITH 1087 00:50:17,040 --> 00:50:23,440 THE ANIMAL MODELS. 1088 00:50:23,440 --> 00:50:25,000 >>I HAVE A QUESTION AS WELL. 1089 00:50:25,000 --> 00:50:33,000 I THOUGHT IT WAS COOL HOW 1090 00:50:33,000 --> 00:50:39,480 [INDISCERNIBLE] THIS IS 1091 00:50:39,480 --> 00:50:42,560 OBVIOUSLY A VERY GRAPHICALLY 1092 00:50:42,560 --> 00:50:44,840 ADVANCED TOOL TO MAKE SENSE WITH 1093 00:50:44,840 --> 00:50:45,920 DATA WITH A LOT OF MISSING 1094 00:50:45,920 --> 00:50:46,880 VALUES AND A LOT OF NOISE. 1095 00:50:46,880 --> 00:50:52,160 WHAT DO YOU THINK ARE BIG 1096 00:50:52,160 --> 00:50:54,000 QUESTIONS THE SPATIAL 1097 00:50:54,000 --> 00:50:54,880 TRANSCRIPTOMICS WILL BEGIN TO 1098 00:50:54,880 --> 00:50:57,840 RESOLVE IN OUR GENERATION WE 1099 00:50:57,840 --> 00:51:03,960 CAN'T CURRENTLY GET AT WITH 1100 00:51:03,960 --> 00:51:14,080 HIGHER DEPTH IN SEQ. 1101 00:51:14,080 --> 00:51:16,680 >>WE CAN LOOK AT PATHOLOGICAL 1102 00:51:16,680 --> 00:51:18,040 AGGREGATES OR OTHER SIGNALLING 1103 00:51:18,040 --> 00:51:19,360 PATHWAYS THAT ARE CHANGED AND 1104 00:51:19,360 --> 00:51:26,200 ALLOWS US TO ASK MORE NUANCED 1105 00:51:26,200 --> 00:51:29,520 QUESTIONS SINGLE NUC CAN GIVE 1106 00:51:29,520 --> 00:51:32,160 YOU A LOT OF DEPTH BUT WHEN YOU 1107 00:51:32,160 --> 00:51:34,080 MARRY IT WITH SPATIAL METHODS 1108 00:51:34,080 --> 00:51:36,280 CAN TAKE YOU FURTHER THAN EITHER 1109 00:51:36,280 --> 00:51:38,160 CAN GO BY THEMSELVES AND THAT'S 1110 00:51:38,160 --> 00:51:39,200 WHAT WE'RE HOPING TO DO. 1111 00:51:39,200 --> 00:51:42,800 AND NO ONE LAB CAN DO ALL THIS 1112 00:51:42,800 --> 00:51:43,400 BY THEMSELVES. 1113 00:51:43,400 --> 00:51:47,760 THAT'S THE OTHER LESSON WE 1114 00:51:47,760 --> 00:51:48,880 LEARNED SIT DOESN'T MAKE SENSE 1115 00:51:48,880 --> 00:51:51,120 TO HAVE SILOS BASED ON WHICH 1116 00:51:51,120 --> 00:51:51,760 DISEASE AND METHOD. 1117 00:51:51,760 --> 00:51:53,760 YOU NEED TO TALK TO PEOPLE AND 1118 00:51:53,760 --> 00:51:56,440 BE OPEN TO SHARING AND BORROWING 1119 00:51:56,440 --> 00:51:57,120 INFORMATION AND GETTING BY WITH 1120 00:51:57,120 --> 00:52:03,440 HELP FROM YOUR FRIENDS. 1121 00:52:03,440 --> 00:52:08,200 >>IF YOU HAD A CRYSTAL BALL DO 1122 00:52:08,200 --> 00:52:11,560 YOU THINK WE'LL ALL BE DOING 1123 00:52:11,560 --> 00:52:14,200 SPATIAL TRANSCRIPT OMICS OR 1124 00:52:14,200 --> 00:52:18,600 STILL PARALLEL TECHNOLOGIES? 1125 00:52:18,600 --> 00:52:20,920 >>I THINK WE'LL LEARN MORE ON 1126 00:52:20,920 --> 00:52:22,040 WHAT DRIVES THE VARIOUS 1127 00:52:22,040 --> 00:52:22,320 DISEASES. 1128 00:52:22,320 --> 00:52:26,200 THESE ARE VERY EXPENSIVE TOOLS. 1129 00:52:26,200 --> 00:52:27,200 EVERYBODY DOESN'T HAVE TO DO ALL 1130 00:52:27,200 --> 00:52:29,040 OF THEM. 1131 00:52:29,040 --> 00:52:32,080 WE'LL HAVE LEARNED ENOUGH ENOUGH 1132 00:52:32,080 --> 00:52:34,200 ABOUT THE COMMONALITIES AND 1133 00:52:34,200 --> 00:52:35,280 DISTINCTIONS AND HOW MUCH IS 1134 00:52:35,280 --> 00:52:38,560 EXPLAINED BY COMPARTMENTS AND 1135 00:52:38,560 --> 00:52:41,000 BARRIERS WHAT DETERMINES 1136 00:52:41,000 --> 00:52:42,320 SELECTIVE VULNERABILITY WHEN YOU 1137 00:52:42,320 --> 00:52:44,560 HAVE SO MANY PATHWAYS ALL IN 1138 00:52:44,560 --> 00:52:44,800 COMMON. 1139 00:52:44,800 --> 00:52:47,240 THAT'S WHERE THE CELL-BASED 1140 00:52:47,240 --> 00:52:49,920 MODELS WILL GOING TO BE VERY 1141 00:52:49,920 --> 00:52:50,200 INFORMATIVE. 1142 00:52:50,200 --> 00:52:51,560 SO IT'S GOING TO BE REALLY 1143 00:52:51,560 --> 00:52:56,480 EXCITING AND ALL THE IMAGING 1144 00:52:56,480 --> 00:52:58,160 METHODS AND THE M.L. BASED 1145 00:52:58,160 --> 00:53:00,240 APPROACHES TO DO THE 1146 00:53:00,240 --> 00:53:00,880 CLASSIFICATION AND LOOKING AT 1147 00:53:00,880 --> 00:53:02,800 HOW MUCH MORPHOLOGY CAN EXPLAIN 1148 00:53:02,800 --> 00:53:06,200 AND HOW MUCH YOU CAN EXTRACT 1149 00:53:06,200 --> 00:53:07,600 FROM MORPHOLOGICAL INFORMATION 1150 00:53:07,600 --> 00:53:08,880 WILL BE MUCH FURTHER ALONG. 1151 00:53:08,880 --> 00:53:11,080 YOU'LL HAVE MORE TARGETED TOOLS, 1152 00:53:11,080 --> 00:53:13,000 I THINK, TO BE ABLE TO PARS OUT 1153 00:53:13,000 --> 00:53:14,400 SOME OF THIS IN A MUCH FINER 1154 00:53:14,400 --> 00:53:27,000 GRAIN WAY. 1155 00:53:27,000 --> 00:53:28,000 >>ANY QUESTIONS? 1156 00:53:28,000 --> 00:53:38,320 THANK YOU, HEMALI.