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"Mapping molecules to cells” - Dr. Sarah Teichmann — Transcript

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0:00up next we have uh Dr Sarah tman uh who
0:04was a distinguished leader in cell Atlas
0:06Technologies and cellular genetics Dr
0:08tman established her research group at
0:10the MRC laboratory of molecular biology
0:13in 2001 and then moved to the welcome
0:15genome campus in 2013 becoming the first
0:18faculty member appointed across both the
0:21embo European bioinformatics Institute
0:23and the welcome Sanger Institute in
0:25April 2024 Dr tman joined the University
0:28of Cambridge as chair in stem cell
0:30medicine while also working with glos
0:32Smith Klein and her startup ocell
0:35Therapeutics she co-founded the
0:37international human cell Atlas
0:39Consortium which now spans over 3,000
0:42members aiming to map all human cell
0:44types Dr tman has received numerous
0:47prestigious Awards including the embo
0:50gold medal and the febs embo women in
0:52science award and is a fellow of both
0:54the Academy of Medical sciences and the
0:56Royal Society please join me in
0:58welcoming Dr Sarah tman
1:00[Applause]
1:06thank you for that kind introduction and
1:07thank you for having me it's a
1:09tremendous honor and a pleasure to speak
1:11today in this Symposium um for the Next
1:14Generation sequence in Canada Gardner
1:16award and I want to just give a little
1:18anecdote that makes it particularly
1:20special for me to be here which is that
1:22almost exactly 30 years ago Shankar uh
1:25taught me organic chemistry When I Was
1:27An undergraduate second year
1:28undergraduate so I don't think at the
1:30time either of us thought we'd be
1:32meeting here again um but great pleasure
1:35and uh and and delighted to be here and
1:38of course Shankar went on to discover
1:40Next Generation sequencing with um David
1:44kenman and and um Dr Meyer and I went
1:48off and uh had an exciting journey
1:51through theoretical and computational
1:53biology and that's what I'm going to
1:54tell you about today um about molecules
1:58and cells so mapping cells is an idea
2:01that has a long history and has sort of
2:03probably popped up in different places
2:05in the world again and again one of the
2:08um lectures that that that um kind of is
2:11is on the internet and is famous is the
2:13the Nobel lecture by Sydney brener where
2:15he sees he says we need a program of
2:17making maps of cells and maps of how
2:20cells talk to each other the cell map
2:23project for which we don't need a model
2:25organism because of course we can study
2:27ourselves the human body um will be one
2:30of the things to occupy us for the next
2:32few decades and what Sydney didn't know
2:35was that there was going to be a
2:36resolution revolution in genomics so I
2:38don't mean next Generation sequencing
2:41but what I mean is actually the ability
2:44of a processing cells and the library
2:48preparation step Upstream that allows us
2:52to sequence the nucleic acid content of
2:54individual cells and you already heard
2:56in the the the amazing previous talk on
2:59epigenetics how important it is to
3:01understand cell States and you can see
3:03that with this technology basically it's
3:06possible um you know from from the
3:09earliest days which were sort of
3:11pioneered by azim serani and others
3:13studying a handful of cells this this
3:16technology underwent a a scaling up
3:19where it's now possible to study
3:21hundreds of thousands or millions of
3:22cells in a single experiment and so what
3:25that means is that you can take a um a
3:27tissue sample like a human heart sample
3:30and then study the the the the the
3:32individual cells or or nuclei in terms
3:35of the the transcriptomic content of the
3:38cells in other words the RNA that's
3:40that's expressed the genes that are
3:42switched on in that single cell so we've
3:44heard a lot about the DNA sequence um of
3:48of individuals in health and disease
3:51we've heard a lot about the epig genome
3:53and of course all of that is encoding
3:55the the uh repertoire of genes that are
3:58active in single cells which are very
4:00different in uh a cardiomyo side versus
4:04a um an immune cell versus a virro blast
4:07versus a neural cell Etc and so
4:10sequencing um at the single cell or
4:12single nuclear level and suspension
4:14gives us that that huge amount of
4:16information about which genes are active
4:18in each cell which we can then analyze
4:20with with computational methods deep
4:22learning AIML and so on that we have
4:25available nowadays and hand inand with
4:28that resolution Revolution
4:30what we've had is technology development
4:32in spatial genomics and spatial
4:35genomics it sort of comes through the
4:37sequencing side and the Imaging side and
4:40and sequencing and microscopy s are sort
4:42of coming together again in this spatial
4:45biology field which is kind of uh also
4:48raced forwards in the last decade or so
4:51where we can then map in a tissue
4:53section so taking a salami slice of a
4:55human tissue sample the gene expression
4:58landscape of the cells in that section
5:00and then you can imagine combining that
5:02computationally with the deep deep
5:05knowledge of the cells in that sample
5:07with consecutive sections we can build
5:10up a picture of the tissue niche in that
5:12sample in that in that tissue and
5:15understand how the cells are oriented
5:17relative to each other and this spatial
5:19biology uh you know is really um
5:23becoming kind of uh you know widespread
5:25prevalent and popular and earlier this
5:27year in June we had a small Symposium in
5:31in Stockholm called spatial biology in
5:33the genomics era and that's really the
5:35era that we live in the era that we live
5:37in now is single cell genomics and
5:39spatial genomics and and Aviv and I uh
5:42Aviv rev both gave talks in in the last
5:45section of course she's the co-founder
5:47with me um of the human cell Atlas
5:50International um uh uh project that that
5:53Rob mentioned at the beginning of the
5:54talk and so why is this
5:57mapping important why is it important to
6:00know in in in Exquisite detail and at
6:03full molecular depth um that the fine
6:06cell States in a tissue sample and how
6:09they're located relative to each other
6:11it's important because it's not just a a
6:14kind of enumeration and mapping exercise
6:16but that information also tells us about
6:19the function of the individual cells and
6:21the cell States because it tells us how
6:23the cells are talking to each other and
6:26and the the molecular dialogue basically
6:29between the cells it tells us about the
6:32cell function and and therefore then
6:34also the function of the tissue within
6:37within our organs and to illustrate that
6:40I'm going to tell you three short
6:41stories about three different tissue
6:42niches the placenta the heart and the
6:45thymus if I if I get through them so why
6:48is the placenta so fascinating um you
6:51know it's a transient organ that forms
6:53at the beginning of
6:54pregnancy and um of course it's
6:57necessary for a delivery of o oen and
6:59nutrients to the embryo what fascinated
7:02me about it is uh that that um conundrum
7:06that that Kathleen presented earlier
7:08which is that our tea cells and our
7:10immune system is trained to distinguish
7:13self from nonself and of course in the
7:15placenta just like in a tumor the the
7:18maternal immune system is presented with
7:20a paternal antigens so they should be in
7:23theory the maternal immune system should
7:25be rejecting the paternal antigens but
7:28instead what happened is that there's a
7:30a remodeling of the tissue so that you
7:33have um these larger arteries that are
7:36formed to deliver the the the oxygen
7:38nutrients through the blood to the
7:39placenta and um essentially a harmonious
7:42coexistence of the fetal cells that are
7:45the the the invasive trophoblasts that
7:46are entering the uterus and the the
7:49maternal cells on the uterine side of
7:51the placenta and Janet knows this well
7:53because she's one of the discoverers of
7:54the trophoblast stem cells so so the
7:57conundrum is really how does the
7:59maternal immune system respond and what
8:01are the interactions that allow this
8:04coexistence this peaceful coexistence
8:06and to to address that question Roser
8:08vent toror who was a postto in the group
8:10set out on this um Brave quest to do to
8:13single cell sequence um the the the the
8:17cells both on the maternal and on the
8:18fetal side of the the first trimester
8:21placenta that we got from the human
8:22developmental biology resource in
8:24Newcastle um with with the support of M
8:27hanif's lab who is right next to the war
8:29Bo there and also Ashley morph's group
8:32and this allowed us for the first time
8:33to map out the the um the fetal
8:37genotypes with the uh because M had also
8:41gotten research ethics to get the the
8:43maternal blood so we're able to use the
8:45sequencing data to say what is maternal
8:47what is fetal and distinguish maccrage
8:51States for instance that were were fetal
8:53and maccrage states that were maternal
8:55so distinguishing which cells in this
8:57intermingling come from the mother which
8:59come from the the fetus and the the this
9:04this sort of dialogue between the cells
9:06that's absolutely crucial to get right
9:08at this interface in order for the the
9:11remodeling of the the the uterus to to
9:14um allow the blood supply to to form
9:17correctly um is is an an interaction
9:20that we deciphered uh by by mapping the
9:23molecules on the surface of the cells
9:26and then statistically inferring what
9:29are the molecular interactions what's
9:31the molecular communication between the
9:34the the fetal and the maternal cells and
9:36you can see here there are three natural
9:38killer cell states that we described in
9:40in molecular detail for the first time
9:43in this sort of um
9:45um um Continuum of activation of natural
9:48killer cells and these are obviously
9:49cells that normally kill non sself so
9:52how are they kept in check they're kept
9:54in check by by the the particular um
9:58receptor ligan inter re actions that
9:59they see on the fetal side with the
10:01extrav trophoblast and from the
10:04macrofagos and strumal cells um on the
10:06maternal side that are also kind of
10:08controlling these cells and keeping them
10:10calm as it were and where does the um
10:15you know what was the thinking here
10:17behind these receptor Li interactions
10:20basically in the cells so so combining
10:23the cells with their their their
10:25molecular um uh cell surfaceome and
10:28their interactions well that's from from
10:31basically the 15 years that I spent um
10:34at the MRC laboratory of molecular
10:35biology in the structural studies
10:37division where we were studying protein
10:40biophysics and and you can see a few
10:42years ago we had a Nobel Symposium with
10:44these uh a gentleman here again in
10:47Stockholm in 2022 Demis sabis who was of
10:49course um awarded the Nobel Prize for
10:52the alpha fold and what we had worked on
10:55was
10:56um uh modeling protein complex as graphs
11:00and understanding the the assembly
11:02Pathways of proteins in three dimensions
11:05and how they find each other inside
11:07cells and also of course then what we
11:09were asking here was how do they
11:11interact with each other on the on the
11:13extracellular surface in a stoom
11:15metrically Accurate Way um with all the
11:18subunits there at the right at the right
11:20concentration so we're not thinking of
11:22protein protein interactions as binary
11:24interactions we're thinking of them
11:26basically in terms of all the subunits
11:28that were that are needed that we know
11:30from uh protein structure and protein
11:32biophysics and so it's really bringing
11:34together this molecular kind of thinking
11:37about about proteins and the cellular
11:41interactions um that that led us to a
11:43deeper understanding of of the placenta
11:46of the cell types and and um and
11:49developmental
11:50trajectories um of the the the the cell
11:53cell interactions and how that immune
11:55tolerance is set
11:57up so that's really a a story about our
12:00our development um the human development
12:03during pregnancy which is by the way
12:05different from uh uh the early kind of
12:08Developmental stages in Mouse and the
12:10and the molecules in the mouse so
12:12there's a lot of evolutionary Divergence
12:14so this concept of that Sydney brener
12:16said of not studying a model organism
12:18but studying ourselves is really quite
12:20relevant when you want to really uh uh
12:24um get to the the molecular details in
12:26the tissues the so humans are very
12:29different both in terms of the immune
12:31system in particular which is obviously
12:32evolving very fast because of host
12:35pathogen arms race but also um
12:39speciation kind of in in these early uh
12:42in these early developmental tissues so
12:45next I'm going to go on to um a a
12:47different organ that's that's uh you
12:49know um incredibly important to life
12:52which is the heart obviously one of the
12:54The crucial organs um and and one of the
12:57most complex organs in our body besides
12:59the brain and I want to talk about again
13:01tissue nichas but also cell cell
13:04interactions both in a paracrine sense
13:06but also in an endocrine sense which
13:07means signaling endocrine is the hormone
13:09system and signaling uh between distant
13:12regions of our body and coordinating our
13:14physiology so we started studying um the
13:19the human heart with collaborators in
13:20Berlin and Boston um uh many years ago
13:25and um in initially using this
13:28suspension single cell genomics
13:30Technologies to define the the the the
13:32cell types in the the free walls of the
13:35four chambers of the heart so we've got
13:36two atria two ventricles and and
13:39defining the kind of muscular tissues in
13:41terms of um both the cardiomyocytes but
13:43also the immune cells and um fiber
13:46blasts and so on that that and and and
13:48the the the complexity that we
13:50discovered was quite shocking so instead
13:52of having let's say one cardium myosite
13:54subtype in in the ventricles we found
13:57you know um six or more and um and and
14:01then more recently what we moved on to
14:04was um wanting to understand not just
14:06the muscular tissues in the heart but
14:09also the sort of brain of the heart
14:11which is the cardiac conduction system
14:13and that electrical conduction system
14:16basically maintains the coordination
14:18between the contraction of the four
14:20chambers the muscular tissue and the
14:22four chambers and that that
14:25um um uh beating of the heart that
14:29Rhythm and that coordination is kicked
14:32off by so-called pacemaker cells so
14:34pacemaker cells are very special very
14:36rare cells in our body they're amongst
14:38the only spontaneously firing cells and
14:41they they start beating very very early
14:44in embryonic development and are kept
14:45beating through a sort of clock of
14:48calcium and potassium channels that goes
14:50on forever until of course we take our
14:52last breath and the heart stops so these
14:55are absolutely crucial cells to
14:56understand they're very hard to find
14:58because they're so rich rare and the
15:00surgeon who's doing the the dissection
15:02of the tissue FR us wasn't able to see
15:04them um be also because this the tissue
15:07that they sit in the sinoatrial node is
15:08located in different positions in
15:10different people and isn't obvious uh
15:13isn't always in a perfect stereotyp
15:15typical position so we worked with a
15:17cardiac pathologist uh Professor Yen ho
15:20um in London uh and and the the um the
15:24team James cranley and kazum maak
15:26kanamaru who are both clinician
15:28scientist Tres in the group uh were were
15:31absolutely brilliant in Catching these
15:33very rare cells that you can see here in
15:35blue at the top from these are from two
15:38donor hearts that we that we um were uh
15:41lucky to to have donated uh in during
15:44the pandemic when the transplant was
15:46down in the UK um so James and kazumasa
15:50traveled to different uh cities in the
15:52UK London New Castle so on to get these
15:54declined donor hearts and then do the
15:56dissections and then send the tissue to
15:58Yen the images for looking at and
16:00identifying these regions and you can
16:02see these this tiny uh cluster of cells
16:06uh has a different profile in terms of
16:08the the sodium Channel expression that's
16:11high in these working cardiomyocytes in
16:13the uh the right atrium and um uh but
16:18but they have very high expression of
16:19this calcium channel kagna 1D which has
16:21been described from from urine cells as
16:24typical of pacemaker cells and here what
16:27you can see is the the pro profile of
16:29all ion channels and and G protein
16:31coupled receptors in cardiomyocytes and
16:34and uh neural cells um neurons and glea
16:37in the heart and you can see that these
16:39cells have a special profile that's
16:41different from the the working
16:43cardiomyocytes and the neuros cells and
16:45that gave us confidence that we had
16:46actually caught those very special cells
16:49in the human uh sinoatrial node for the
16:52first time what we did then was combined
16:54that with the spatial genomics that I
16:56mentioned and and indeed they mapped to
16:58the node to the nodal region there that
17:00you can see and and that's at the center
17:03of this uh region where um uh we see the
17:09the uh um the inner noal region with the
17:12pacemaker cells and then we Define with
17:14the spatial genomics outer noal regions
17:17that has fi blasts uh adipocytes and
17:19macrofagos that are kind of electrically
17:21insulating these cells um and we what we
17:24were also able to decipher was the the
17:26niche of the Pacemakers with with
17:29special gleo cells that we're able to
17:30Define for the first time that are kind
17:32of hugging the Pacemakers and sort of
17:35nourishing them and connecting to the
17:37sympathetic nervous system which is the
17:39uh the the parasympathetic nervous
17:41system that that comes from our our
17:43brain stem bya the cardiac ganglin to
17:45kind of keep down the heart rate and the
17:47um sympathetic nervous system which says
17:50go faster when when we see a bear and so
17:52modulates the heart rate in that way and
17:55so then um because heart rate kind of as
17:58I've indicated is so important kind of
18:00in in modulating our physiology what
18:03what um the two uh clinician scientists
18:06who are working on this James and and
18:07kazamaza kind of wanted to know is which
18:10drugs can we predict to be acting on the
18:12pacemaker cells and so I said go next
18:15door to the European biomatics Institute
18:17where there's the kemell database this
18:19is an open-source database of drugs and
18:21targets and map those developed drug to
18:25sell which they did with with Christoff
18:27palansky and and others the group and
18:29map those drugs to all the the cardiac
18:32cells including the pacemaker cells and
18:35what was what was me know not surprising
18:37was that all the chronotropic drugs have
18:40their receptors in the pacemaker cells
18:42as expected but then there are other
18:44drugs that we found acting we predict to
18:47be acting on these cells because they
18:48are receptors in the cells and the most
18:50surprising was the glip one receptor to
18:52us which is the of course the target of
18:55glip one receptor Agonist lorag stide
18:58which the wovi and asmic and Monaro and
19:01so on uh drugs and indeed if you look at
19:04the clinical uh real world evidence
19:06there's a six beats per minute increase
19:08in heart rate initially when these drugs
19:11are given so there's clinical real world
19:13evidence that these holds and we also
19:15show in vitro in experiments in the dish
19:17with fetal uh uh cardiomyocytes that you
19:20get a change in the beating pattern when
19:22you add glip one receptor agonis and
19:24recently there's been a paper from a pig
19:27uh showing the same thing and so this
19:29this allowed us to hypothesize that
19:31basically the the six beats per minute
19:33change comes through a direct mechanism
19:36on the pacemaker cells rather than an
19:38indirect mechanism via the brain or the
19:40autonomic nervous system and so this
19:43this basically gives you an idea that
19:45the human cell Atlas which is what we're
19:47contributing to here where we're
19:48building the cell atlas of the human um
19:51tissues gives us new insights not only
19:54into into signaling in the tissue Niche
19:56parine signaling but also endocrine
19:59signaling these are hormones and how
20:00hormones are acting across the body in
20:03new and unexpected ways and so that's
20:05you know also incredibly exciting so to
20:08summarize here we see the new Niche for
20:10for the cardiac conduction system with
20:12the autonomic nervous system drug to
20:14sell kind of shows us that we can use
20:16this data for Toxicology repurposing and
20:19for reconstruction of both paracrine and
20:21endocrine signals so one last story in
20:24the last few minutes is the thymus and
20:26this is relevant because of course for
20:28this prize um this year of the the gner
20:32awards there's also the car tea cells
20:34are being awarded and and te- cells
20:36develop in our thymus the thymus is a
20:39little uh uh tiny organ next to the
20:41heart was discovered as an immunological
20:43organ in the 1960s you you may or may
20:46not have heard of it it's probably one
20:47of the most recently discovered organs
20:49in the human body and the hematopics
20:51cells come to the thymus the tea cells
20:54develop and are trained to distinguish
20:56self from non-self in the organ and they
20:58they then go around and colonize the
21:00body and of course those cells also have
21:02therapeutic potential so the question
21:04with this little tiny organ which is
21:06much smaller than the heart and it
21:08actually involutes with age and becomes
21:10even even more smaller uh uh during
21:13puberty is can we map can we Atlas an
21:17entire human organ and how can we do
21:21that by combining multiple modalities
21:23together from single cell genomics
21:25spatial genomics and uh um
21:29Multiplex protein Imaging and the way we
21:32we uh figured out that we can do this is
21:35to model the organ onto a quasi uh uh
21:39sort of Two and a Half dimensional
21:41framework using a linear model from uh
21:44from from the outside to the inside of
21:46the organ and so the the the concept
21:49here is very simple we form an axis and
21:51you can think of the the the loes of the
21:54thymus like an egg that has an egg white
21:56on the outside that's the medala and an
21:58egg yellow on the in sorry that's the
22:00cortex and the egg yellow in the middle
22:03that's the medala and what we're
22:04modeling is each lobe of the thymus as
22:06an egg white sort of from the outside to
22:09the inside with a um uh a landmarks and
22:13then a nonlinear modeling between each
22:15Landmark to give us an idea of where
22:17each data point is coming from from the
22:19spatial genomics the single cell
22:21genomics and the multiplex Imaging that
22:23we did with Ron germain's group and what
22:25this allowed us to do then is to build
22:27up a model of the organ in terms of all
22:30these different layers you can think of
22:32them like layers of an onion from
22:34capsular to subcapsular through the
22:35cortex through the cortical medular
22:38Junction and into the medala which is
22:39the center of the organ and what this
22:41allowed us to discover was new insights
22:44into precisely how this um cellular
22:48development is taking place from the
22:49hematopics cells or the early thymic
22:52progenitor um that actually
22:55enters uh in inside the the organ kind
22:58of unexpectedly and then we show that it
23:00travels basically around uh up to the
23:03outside of the organ and then the cells
23:06re-enter the Medela and are trained and
23:08sort of quantifying that in a in a
23:11precise way revealed new unexpected
23:14positionings of the cells as they go on
23:17this journey of maturation through the
23:19organ what it also allows us to do is to
23:21Define precisely what the cells are
23:24seeing in terms of the extrinsic signals
23:26as they go through this journey and um
23:29they are receiving basically cyto kind
23:31signals they're receiving growth factor
23:33signals and we can we can quantify this
23:36in in terms of the different layers of
23:38the onion and what the other the
23:40epithelial cells the fiop blast and so
23:41on are expressing the dendritic cells at
23:43each layer in terms of these factors and
23:46then also show how this differs in fetal
23:49stages of thymic development so during
23:51pregnancy versus pediatric stages of
23:54thymic development when when we have the
23:56the mature organ and that's important
23:59because the te- cell output is slightly
24:01different when the during organogenesis
24:04when the thymus is forming during
24:05pregnancy and the tea cells actually
24:07contribute to development of our tissues
24:09versus after birth when we have to fend
24:11off um infections and and and other
24:15challenges so the nature of the cells
24:16kind of changes what we what we were
24:19also able to do was to map the the the
24:22the Identity or the the cell state of
24:25the cells as they then travel to
24:27peripheral organs and this is using um
24:30tissues in in um from the fetus so just
24:33to to sort of summarize we're we're
24:35understanding and mapping the t- cells
24:37across scales so we have the molecular
24:39scale with the cyto receptor
24:41interactions TCR MHC interactions which
24:43Kathleen mentioned the cellular scale
24:46understanding the developmental
24:48trajectories Cell Activation
24:49differentiation and then the whole organ
24:52scale that I described with this organ
24:53axis model um where we're we're
24:56understanding the entire lobe of the th
24:58and of course then the whole body scale
25:01is relevant in terms of immunity and
25:03tolerance and and all the functions of
25:05the immune system that I mentioned so
25:07this is unpublished work and I want to
25:09again say this has been a a really
25:11International collaboration with nadav
25:14yayan who was a postto in the group and
25:17and and also shared with John Marion's
25:19lab and VY Olman and Veronica kedley and
25:22who was an amazing PhD student in the
25:24group and this was a collaboration with
25:25Ron Germaine at the NIH and Andrea vka
25:28who did the the Ibex multiscale protein
25:30Imaging and the nanelo lab at NIH and
25:33also Tom Tagan in um Belgium and of
25:37course we we we must never forget the
25:39donors of these tissues um the women the
25:43children their families uh these tissues
25:46come from from children's hospitals and
25:48from the human developmental biology
25:50resource and um looking towards the
25:52future you can see here that that
25:55mapping the the human body across scale
25:58you know from sort of zero Dimensions
26:00where we started through two dimensions
26:03in tissue sections and then going up to
26:05large volumetric morphological
26:07reconstructions like with hierarchical
26:09phase contrast
26:11tomography you know will will give us
26:13new new insights and valuable insights
26:17um for for for a better understanding of
26:19ourselves but also for drug development
26:22drug Discovery and this multiscale
26:24modeling and mapping is enabled by by
26:28the Canadian Institute for advanced
26:30research um and and in collaboration
26:32with Gary Bader who's a co-director of
26:34mine in that program multiscale mapping
26:37um and and of course he's based here in
26:39Toronto and also kotti Bader in Indiana
26:42these are my disclosures and I will stop
26:45there say thank you and take
26:48[Applause]
26:53questions uh excellent uh thank you
26:55Sarah really uh phenomenal talk I just
26:58remind people to get your questions in
27:00uh via slido um maybe I'll I'll start
27:03with with where you ended Sarah just um
27:06you know Eric started out this morning
27:07talking about the uh ambitious journey
27:09of the Human Genome Project and and
27:11starting out with uh you know sort of a
27:13project that was hard to see through its
27:15conception and then eventually sort of
27:16working through to the point where you
27:17were doing implementation it strikes me
27:19the human cell Atlas is uh is somewhat
27:21similar in terms of that scope and
27:22ambition and so on you've presented a
27:24few uh cases here of really really
27:26impressive work we also uh you know
27:28mentioned that there's collaborators
27:30working in other spaces around the world
27:31in the Consortium and so on can we just
27:33say a few words about kind of how the
27:35human cell Outlets is sort of look
27:36coming together more broadly in terms of
27:38international collaboration where it is
27:40on the journey and maybe what some of
27:41the hurdles remain to kind of see it to
27:43fruition absolutely no so thank you
27:45that's uh be delighted to do that so the
27:47human cell Atlas is this gr Grassroots
27:50International Consortium that you
27:51mentioned has over 3,000 members from
27:53over 100 countries around the globe and
27:56everyone is welcome to join it and there
27:58are a lot of members here in Canada that
28:00contributing I've already mentioned Gary
28:02but there are there are many others
28:03Sonia mcparland you know who have been
28:05atlasing the liver so this is really
28:07Grassroots and um there's more
28:09information at hum cals.org
28:12jooin HCA where you everybody can join
28:15and register who's interested in this
28:17quest of mapping the human body at the
28:19molecular and cellular level and the the
28:22project has is is sort of organized into
28:25working groups and and biological
28:26networks bi ological networks focus on
28:29the individual organs and systems in the
28:31body and we've generated over 100
28:33million suspension cell data points and
28:36increasing um spatial data is coming
28:40through and we're basically in the phase
28:43of now assembling data objects for
28:45suspension cell data sets for individual
28:47tissues and organs and we're releasing
28:50sort of gold standard uh data sets now
28:53on the human cell Atlas data. human cell
28:56at.org website so you can kind of think
28:58of that as like the golden path assembly
29:01of the chromosomes of the Human Genome
29:02Project at least in a first draft and
29:05that's focused on suspension not spatial
29:07data we are we are so so we're sort of
29:09developing these first drafts now
29:11there's going to be a big publication
29:13bundle at natur publishing group at the
29:15end of November and we are then looking
29:17forward to kind of the next phase of the
29:19project which will be a lot um I hope
29:22more comprehensive coverage of the body
29:24and and much more um uh High resolute
29:28spatial genomics data coverage of all
29:30the tissues so that's how I see it going
29:33yeah awesome yeah really exciting uh
29:36initiative uh I think we have time for
29:37one question here from the audience and
29:39so um this is uh asking you to comment
29:42on the implications of your work with
29:43placenta and immune tolerance and the
29:46potential for uh treatments of
29:48autoimmune
29:51diseases potential for treatments of
29:53autoimmune diseases
29:55um I mean I would say the mo and
29:58mechanistic level a lot of the
30:00tolerogenic interactions like pd1 pdl1
30:03and so on were were you know can be
30:05observed in the placenta so I showed
30:07with enk cells like entpd1 which is the
30:10enzyme that degrades ATP it breaks down
30:13ATP and so on a lot of those at the
30:15molecular level there are
30:17tolerogenic kind of mechanisms that that
30:20may be relevant in autoimmunity but
30:23they're probably sort of deployed in a
30:25you know they may be deployed in a
30:27different way in different cells and
30:29different sort of tissue niches in
30:31autoimmunity but yeah it's a um at the
30:33molecular level there are a lot of
30:35mechanisms that are that are repeated
30:37again and again in different parts of
30:38the body in different contexts excellent
30:41well thank you very much please join me
30:42in thanking Dr s tman for her wonderful
30:45CL

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