Pathology Grand Rounds, January 11, 2024 - Diane Krause, MD, PhD

January 12, 2024

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Pathology Grand Rounds, January 11, 2024. Diane Krause, MD, PhD, presents on, "Mechanisms of Hematopoietic Fate Specification to Megakaryocytes."

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00:00Hey, good afternoon, everyone.
00:02So it's a great pleasure to introduce
00:06today's Grand Round speaker,
00:07a speaker that many of us know
00:09extremely well, Doctor Diane Krause,
00:11the Anthony N Brady Professor of
00:13Laboratory Medicine, Pathology
00:15and Cell Biology here at Yale. Diane
00:17did her MD PhD training at 10 at
00:20Penn and she also followed this
00:22by clinical pathology training
00:24at Penn as well. She
00:26moved on to postdoctoral training at Johns
00:29Hopkins and joined the Yale faculty in 1997,
00:32and since then she's developed an
00:34internationally recognized research
00:36program focusing on leukemiogenesis
00:38and hematopoietic differentiation.
00:40Some major research areas in Diane's
00:44group have included functionally
00:46characterizing gene products involved
00:49in acute megakaryoblastic leukemias,
00:51defining transcriptional mechanisms
00:53that regulate megacaryocyte maturation,
00:56and elucidating factors that regulate
00:58how the erythroid megacaryocyte
00:59precursor cell in the bone marrow
01:02differentiates down the erythroid versus
01:04the platelet lineage.
01:05Diane wears many hats at Yale.
01:07As many of you know,
01:08she's director of the Wine HH Stem
01:11Cell Processing Laboratory, associate
01:12director of the Blood Bank, Associate
01:14Director of the Yale Stem Cell Center Co,
01:17Director of Yale's Immunohematology
01:19T32 training Grant.
01:21And she's also the director of an
01:24NIHU 54 grant that has established the
01:26Yale Cooperative Center of
01:27Excellence in Hematology,
01:28one of five centers nationwide
01:31funded to increase to provide
01:33resources for investigators in the
01:35field of hematology and to provide
01:37training to promote, you know,
01:39a field of growing investigators
01:41in non legit heme. Diana
01:43is a recipient of numerous awards and
01:45just to name a few, the Klaus Meyer
01:46Award from Morial Sloan Kettering,
01:49the Tibor Greenwald Award from the American
01:50Association of Blood Banks,
01:52and she's been also inducted into
01:54the National Blood Foundation
01:55Hall of Fame. There's one local
01:58award that I'd really like to mention.
01:59In 2018, she received the Yale
02:02Postdoctoral Mentoring Award,
02:03and I think this award really
02:05speaks to her complete dedication
02:07to advance the success of women
02:10and those from underrepresented
02:11groups in science and medicine.
02:13She's extremely generous with her time,
02:16and despite her many responsibilities,
02:19she always finds time to serve as a
02:21truly dedicated mentor to a large number
02:23of trainees and many junior faculty,
02:25including Pallavi and myself.
02:27So we are really delighted
02:28that she's taken the time today
02:30to accept her invitation
02:31and present her work to you. Welcome, Dan.
02:39Thanks so much, Karen, for that really
02:41nice introduction I should have.
02:43I do have a recording of it.
02:44I can. That's me. Name my CD.
02:47I really wanted to start
02:47with the title slide.
02:48Because of this beautiful picture.
02:50I'm going to give too much in this talk.
02:52More than one should put into a one
02:54hour talk because I'm talking to
02:56pathology and I just couldn't not
02:57present some of the stuff in our lab
02:59that is just so visually beautiful
03:01and really maybe even attract some
03:03pathology trainees and faculty to
03:05collaborate on some of the the work.
03:08But I'll tell you mostly what's
03:10going on in lab.
03:11This picture is a mega karyocyte,
03:13a primary human mega karyocyte.
03:14And what you can see is that
03:16there's a lot of detail.
03:18You can even see the Golgi,
03:20the the Golgi and the endoplasmic reticulum.
03:23And what this is, is expansion microscopy.
03:25So this was taken with the confocal,
03:27but you really have a lot of
03:29the kind of detail that you can
03:30get with electron microscopy.
03:32So it's a pretty picture,
03:33but what I'll be telling you about
03:35today is hematopoiesis For those
03:36of you who don't think about this,
03:37it in our bone marrow there's a
03:39hematopoietic stem cell Like other
03:40stem cells it self renews for the
03:42life of the Organism and it can
03:44differentiate the hematopoietic
03:45stem cell differentiates into all
03:46of the cells in our peripheral blood
03:49leukocytes as well as the red,
03:50red blood cells and platelets.
03:53And my lab really focuses on this
03:55bright orange cell which we have here as MEP.
03:58I'm going to try not to talk in
04:00too many abbreviations,
04:02but the name of the MEP is a
04:05megacarycytic erythroid precursor cell,
04:06and it's kind of a mouthful,
04:08so I'll only sometimes say the whole thing.
04:10So this is the bipotent precursor of
04:12megacarycytes that make platelets and
04:14the erythroid lineage that ends up
04:16making enucleated red blood cells.
04:20And just to remind you,
04:21we make about 2,000,000 platelets and
04:232 million red blood cells every second.
04:25So this cell is very busy making its
04:27progenitors and trying to decide.
04:29I I don't really love using the word decide,
04:31but it really helps you ask the
04:34question which lineage to go down.
04:35So what is determining the fate
04:38specification of this bipotent progenitor?
04:41Just because I wouldn't be
04:42complete without saying this,
04:44there is evidence in the literature that
04:45megacary sites can also be derived directly
04:48from a hematopoietic stem cell population.
04:50So if that is the case,
04:52then I'm not talking about that lineage
04:54to megacarycytes, I'm talking about
04:56this bipotent lineage to megacarycytes.
04:58Why did we pick MEP?
04:59Well, first of all,
05:00it's a model of bipotent fate specification
05:02which is important in all of the
05:04stem and progenitor cell biology,
05:06tissue repair and response to injury.
05:10Secondly,
05:10it's important in regenerative medicine.
05:12As most of you are aware,
05:14the place that we get our red cells
05:16and platelets that we transfuse into
05:17patients is from healthy donors and
05:19there really aren't enough of them.
05:20And there's a huge amount of work
05:22in finding and collecting cells from
05:24healthy donors in order to maintain an
05:27adequate supply for the recipients.
05:29And sometimes we really run low
05:31on platelets in red blood cells,
05:32particularly in the last year or so.
05:35We've had several times when we're
05:36near crisis situation.
05:37So if we could figure out a way to
05:39make them in vitro, that would be great.
05:41And finally,
05:41just as potential therapeutics
05:43might be identified in erythroid
05:46and megacary acidic diseases,
05:48so how does one distinguish
05:50whether you have a bipotent MEP?
05:52What you have to do is a colony
05:54forming assay.
05:55Just if you think about a bacterium,
05:57it's going to form a colony.
05:58When we do him out of aquatic assays,
06:00we take a stemmer progenitor cell,
06:02we put it into a semi solid medium
06:03in a very dilute fashion and if that
06:06cell divides and differentiates,
06:07it's going to form a colony of cells.
06:10And what we do is we over the course
06:12of the two weeks that cell makes 2
06:14cell types with one of them being
06:15megakaryocytes and other cells of
06:17the erythroid lineage.
06:18Then the cell that started that
06:20process is the MEP,
06:21the bipotent progenitor that is
06:24the assay we used.
06:25We identified in in this paper
06:28from 2016 a really good sorting
06:31strategy for primary human MEP.
06:33What we did is we worked out the
06:36assay and then tested different flow
06:39sorting approaches to come up with
06:41the best possible way of isolating the cells.
06:43What happens is after the course of two
06:45weeks a single cell forms a colony.
06:47This is a colony of cells.
06:48It's been stained with anti glycoporin
06:50A which is a surface marker for
06:52red blood cell lineage.
06:53This and this colony is entirely
06:55made-up of cells that are committed
06:57to the erythroid lineage.
06:58Here's a colony that's stained
07:00with anti CD 41 only
07:02CD 41 is on the mega carry site lineage.
07:04So this is a colony of cells that are
07:06mega carry site only and then we often
07:08get colonies that have cells of both the
07:11megakaryocyte and the erythroid lineage.
07:13And just to be more complete,
07:14my lab has now switched to an assay and
07:16rather than using immunohistochemistry for
07:17glia in 41 we now do immunofluorescence.
07:23Based on the data obtained we now
07:25can get a population of primary human
07:27mega karyocyte erythroid progenitor
07:29cells where if you played 100 cells
07:31in a plate you get about 70 colonies
07:34and of those colonies about 50%
07:36shown here in blue are cells are
07:39comprised of cells with both of cells
07:41of both the mega karyocyte and the
07:43erythroid lineage with the remainder
07:45being erythroid only and mega only.
07:46We also came up with sorting strategies
07:48for the mega karyocyte progenitor,
07:50with most of the colonies are mega only
07:52and the erythroid progenitis under your
07:54similarly where they're mostly erythroid.
07:55One of the questions you may ask you
07:57may be asking yourself and will kind
07:59of be answered throughout the course
08:00of the talk is do we really have a
08:02good sorting strategy for the MEP?
08:04Because it looks like half of the
08:05colonies are E only and MK only.
08:07And what I'm going to tell you is
08:09that the data very strongly suggest
08:11that what we have is quite a pure
08:13population and that there is a
08:15probability that a bipotent cell,
08:17when put into the culture will,
08:19with the First Division,
08:21come up with two cells that then
08:23subsequently all decide Erythroid
08:24or subsequently all decide Meg.
08:26And it doesn't mean that the starting
08:28cell didn't have the potential
08:29to go down both lineages,
08:30and I'll try to convince you of that.
08:33So this enrichment of these populations
08:35has allowed us to study the fate
08:37transitions from the bipotent
08:38progenitor to the Meg progenitor
08:40and from the bipotent progenitor
08:41to the erythroid progenitor.
08:45I'm going to tell you four stories today,
08:47hopefully not too quickly,
08:48but quickly enough that I'm
08:49done by the end of the hour.
08:51The 1st is some really novel data
08:53that came out of our single cell RNA
08:56sequencing of these populations that
08:58revealed that the cell cycle speed
09:00of the MEP actually seems to predict
09:03whether that's going to be megacaryocyte
09:05output or erythroid output and that we
09:08can actually toggle the fate of the
09:10MEP by toggling its cell cycle speed.
09:13Then I'll tell you about the role of
09:14the Runks 1 transcription factor and
09:16how it's post translational modification
09:18effects MEP fate and then we'll talk about,
09:20we'll show show you some really cool
09:22data watching MEP fate specification that
09:24really gave us those probabilities that
09:26I told you about that a bipotent cell
09:28can form an E only or an MK only colony.
09:31And finally expansion microscopy
09:32that I already introduced
09:37what we did once we had fact sort facts,
09:39gating strategies for enriching MEP,
09:42Meg progenitors and erythroid progenitors.
09:44We also sorted the upstream common
09:46myeloid progenitors and we sent these
09:48for single cell RNA SEC analysis.
09:50And this was work done by Yi Shan
09:51Liu in the lab, an amazing post doc
09:53who published this work in 2018.
09:56What you can see when you look
09:57at the single cell RNA SEC and if
09:59you're not used to looking at this,
10:00the data from the individual cells has
10:04now been categorized into four groups.
10:07The CMP, the common myeloid progenitor group,
10:10the MEP or the Meg erythroid
10:12progenitor group,
10:12the Meg progenitors or the Meg
10:14committed and the erythroid
10:15progenitors or Erythroid committed.
10:17And what you can see is when
10:19we fact sort out these MEP,
10:20it's really a distinct population.
10:22There's a bit of a graduation to it,
10:24but it's a distinct population.
10:25It looks very different from CMPMKP or ERP,
10:28but it looks like it had still has
10:30some genes that are still on from
10:32the CMP that are going to be turned
10:34off and some genes that are on in
10:36erythroid and mega caries like Destin
10:39cells that are just coming on.
10:41So it really is a transitional state.
10:44When we looked at the gene expression
10:47analysis and compared MEP to the
10:49other populations,
10:50what we found that the pathways
10:52that were over represented in the
10:54differentially expressed genes
10:56were almost always the cell cycle.
10:58And so you can see it's here from
11:00the MEP to the Meg progenitor cell
11:02cycle shows up,
11:02from the MEP to the erythroid shows up
11:04and the other things were were less specific.
11:07We weren't entirely surprised by
11:09this because we had preliminary
11:10data that were consistent with this.
11:12What we had done prior to getting
11:14the single cell RNA C data is we had
11:16tried a candidate approach where
11:17we would add various drugs and
11:19cytokines to the MEP to see if it
11:22affected their hematopoietic output.
11:23We already knew that in response to
11:25all trans retinoic acid which goes
11:27to the nucleus and binds directly as
11:29a transcription factor on the DNA,
11:30that we had a dose dependent increase
11:33in megacaryocyte only colonies when
11:35we added ATRA.
11:36We also knew that when we added
11:38rapamycin which is an mtor inhibitor,
11:40it's affecting metabolism.
11:41We had a a similarly A dose dependent
11:44increase in megacaryocyte biased and
11:46what we realized is that both ATRA
11:49and rapamycin can slow the cell cycle.
11:51So we tested that.
11:53What we've done here is a dilution assay,
11:57CFSE, dilution assay,
11:58for those of you who are not
12:00familiar with this,
12:00you stain all your cells at time
12:02zero with a fluorescent dye.
12:04Each time the cells divide,
12:05they have less of the fluorescent dye.
12:07So the further to the left they are,
12:09the more division there's been.
12:11And what you can see is the
12:12controls here are shown in blue.
12:14When you treat with ATRA,
12:15there's less division. Similarly,
12:16when you treat with rapamycin,
12:18there's been less division proving that
12:20they're both slowing the cell cycle.
12:22Now I'm not necessarily talking
12:23about the speed of the cell cycle,
12:24we haven't tested that, but there's
12:26they're dividing less frequently.
12:30What we did next then is just
12:31add a cell cycle inhibitor.
12:33We used CDK 46 inhibitor.
12:34These cells completely stopped dividing.
12:37We then washed that out and put them
12:39into the colony assays and again saw
12:42this dose dependent increase in the
12:45mega carrier site lineage specification
12:47of the MEP that proved this long.
12:49The cell cycle gave us a Meg bias.
12:51But what happens if you speed
12:52up the cell cycle?
12:53Well how do you speed up the cell cycle?
12:54One thing is that you can
12:57knock down CDK inhibitors.
12:58The CDK is that was pretty much toxic
13:01to the cells and didn't turn out.
13:03What we ended up getting to work
13:05is when we over expressed cyclins.
13:07So we got two different vectors from
13:09Claudia Vaskal's group in Germany,
13:11one that expresses CDK 2 and cycling
13:14E So this is the cycling dependent
13:16kinase 2 and the cyclin here the cyclin
13:19E that activates it and separately
13:21the CDK four and it's cyclin CDK
13:23Cyclin D We call this guy 2E and
13:26this one 4D for obvious reasons.
13:28And what we found is both 2E and
13:314D accelerated the cycling of MEP
13:33getting more more cycling in vitro.
13:36And when we looked at the output of
13:38those MEP you can see that whether we
13:41gave them 2E or 4D on a cell by cell
13:43basis now we had an erythroid bias.
13:45So the opposite with more cell cycle,
13:48more E fate specification and we
13:50did not see this effect if we took
13:53cells that were already MK committed
13:55or already Erythroid committed.
13:57So part one is when we slow the
13:59cell cycle we get more MKP.
14:00When we speed up the cell cycle we
14:02get more Erythroid. Why, how there?
14:04We have a lot of ideas.
14:06I'm going to show you that where
14:07we are in terms of answering that
14:09which is the runks one story
14:13and we I'm not showing you the data but
14:15we've shown that MEP actually cycle more
14:17slowly than both Meg or Erythroid cells.
14:19So that's kind of an interesting
14:20concept that they have to speed up
14:22whether they're going Meg or Erythroid,
14:23it's just the degree to which they speed up.
14:27So I want to tell you about Runx 1.
14:28Runx one also was revealed in our
14:31single cell RNA seq data and then
14:33subsequently in bulk RNA seq data.
14:35When we looked at the single cell
14:37RNA seq data and said what's what
14:39is likely regulating the genes,
14:41the change from MEP to MKP and
14:43from MEP to ERP,
14:45from Meg to erythroid and Meg to,
14:47I'm sorry, from the bipotent to the Meg
14:49and from the bipotent to the erythroid.
14:51Ronx One was the predicted transcription
14:53factor that would be regulating this.
14:56Of the genes that are down regulated
14:58from CMP to MEP and down regulated from
15:00the MEP to the erythroid progenitor,
15:02it was the number one ranked
15:05transcription factor that was able
15:06to regulate the target genes that
15:09were differentially expressed.
15:10It was also the number three potential
15:13regulator of genes that are up
15:14regulated in the megacaryocyte fate
15:16specification and amongst those
15:18is Mipple which is thrombopotin
15:19receptor and FLEA one which is a
15:22known transcription factor that's
15:24critical for megacaryois what we oops,
15:29this is supposed to come next.
15:30What we did then was we over
15:32expressed Runks 1 and when we do
15:34that you can see that we actually
15:37caused those bipotent cells to go
15:39towards the megacaryocyte lineage.
15:41And then when we inhibited Bronx 1,
15:44Runks 2 and Runks 3 with a drug,
15:46we could see the opposite effect where we
15:48see an increased in E fate specification
15:51which really proved that the Runcs one
15:54activity is promoting the MK fate in the MEP.
15:58However,
15:58when we looked at Runcs One RNA and
16:01protein levels in these three lineages,
16:03the Meg erythroid progenitor and then the
16:04Meg and the erythroid committed cells,
16:06there was no difference in either
16:08protein or RNA expression between
16:10the Meg committed cells and
16:12the erythroid committed cells.
16:13Which told us it's not happening
16:15at the transcriptional level
16:16or the translational level.
16:18It's probably post translational.
16:19So we started looking at post
16:22translational modifications of Runx one.
16:24And one that has been heavily studied
16:26before is serine and threonine.
16:28Phosphorylation of Runx one is known
16:30to be necessary for its activation for
16:33its ability to activate transgenes.
16:36So activate transcription.
16:38I'm sorry.
16:39What we did is we got antibodies
16:41that are specific for different
16:43phosphoserines on Ronks.
16:44One from our collaborator,
16:46Alan Friedman,
16:47he'd published this and pulled them out of
16:49the freezer for us and they work beautifully.
16:51And what you can see,
16:52and this is work that was done by two
16:54very talented people in the laboratory.
16:56I already introduced you to Yi
16:58Shen and Nayeong Kwan is a grad
17:01student in the lab and she's really
17:03been the mastermind between all of
17:05all the work I'm about to show you.
17:08What she did is she did intracellular
17:11flow cytometry for total runks
17:13one and phosphoserine runks 1.
17:15And I'm going to show you data
17:16for several of the phosphoserines.
17:17This is phosphoserine 76.
17:18I just bother to show you.
17:20The 276 is here and phosphoserine 303
17:23which is here in the Runks one protein.
17:26And what she showed and this is just
17:28representative data on the left and
17:29then graphed here on the right for
17:31multiple replicates is that either
17:33with commitment to erythroid or
17:35megacarocyte fate specification,
17:36you see an increase in the phosphosurine
17:41levels of Bronx One and there's a
17:44significantly higher increase when
17:46you go to the Meg Fate specification.
17:48Similarly with the Erythroid, Similarly,
17:51I'm sorry, with phosphosurine 303,
17:53you see this increase and then a further
17:56significant increase between erythroid
17:58progenitors and Meg progenitors.
18:00So that's just shown schematically here.
18:02The phosphoserine runcs 1 levels go up
18:04from MEP to MKP and go down or don't
18:08go up with when you go to Erythroid.
18:11So this is where we are.
18:12Is there a link now with the cell
18:14cycle data that I showed you?
18:16I'll just show you one example
18:18to for this link.
18:19The link is basically that the slowing
18:21of the cell cycle requires Runcs 1.
18:25You if you slow the cell cycle and
18:26there's no Runx One activity then you
18:28don't get the Meg Fate specification.
18:30They still go down the erythroid lineage.
18:32But let me show that to you slowly.
18:33So here's your control with the bipotent,
18:35the erythroid only and the Meg only.
18:37This is the effect of the Runx 1 inhibitor
18:40that gives us more erythroid only.
18:41This is the effect I showed you
18:43previously of ATRA or rapamycin
18:44where they slow the cell cycle and
18:46you get more Meg Fate specification.
18:48And here I'm showing you the combination.
18:50You do not see this increase in
18:53Meg phase specification with ATRA
18:55or with rapamycin in the presence
18:56of the inhibitor of the Ronx one.
18:59Really suggesting that we have a link
19:01now between slowing the cell cycle and
19:04getting increased Ronx 1 phosphorylation
19:05and increased MK phase specification.
19:12Oh, so I did include this,
19:13I wasn't sure if I'd show this.
19:14So then we actually did prove that
19:15if you slow the cell cycle like
19:17with the Pelvicyclib that actually
19:19slowed the cell cycle and then
19:20you wash it out and then you show
19:22the cells are Meg fate specified,
19:24you actually get increased levels of
19:27phosphosurine runks one at both 276 and 303.
19:30It ends up you also get increased
19:32levels of total runks one,
19:33but the ratios suggest that we probably
19:35have a higher percentage of the
19:38total runks that is phosphorylated.
19:40So that's our link for now with fate
19:43specification and the cell cycle.
19:45We then wanted to test the effects
19:47on primary cells if we get rid of
19:50the serines and threonines that
19:51are phosphorylated in the Runx 1,
19:54So I'd shown you previously,
19:55when we overexpressed Runx one,
19:56we get more MK fate specification.
19:58What if we mutate these four residues,
20:013 serines and one threonine
20:04to alanine in that case?
20:06We didn't get quite no effect.
20:08We got some effect,
20:09but it was a less strong effect
20:10than in the wild type.
20:11And in contrast when we changed the
20:14serines and threonines to aspartic
20:15acid which mimics the phospho serine,
20:18so all of the overexpressed brunx one
20:20is pre in a pre phosphorylated state.
20:23We got a far stronger effect with
20:25almost no erythroid fate specification
20:27and a lot of MK only suggesting
20:30that this is really playing a
20:32role in MK fate specification.
20:34In order to study this we
20:35then used a cell line model.
20:37So human erythro leukemia
20:39cells are an OK model.
20:41When you add TPA they
20:42go down the Meg lineage,
20:44when you add hemen they kind of sort
20:46of go down the erythroid lineage.
20:48Anyway it's the best system we have
20:49for looking at this and what we wanted
20:51to do is over express the wild type,
20:53the 4A mutant that has the alanine mutations,
20:56the 4D mutant with the aspartic acid
20:58mutations and so that we can do some
21:00molecular studies like cut and run
21:02and and gene expression changes.
21:04And first thing you can see is even
21:06without inducing these cells to
21:08differentiate with TPA we just we
21:10get them to go down the Meg lineage.
21:12CD 42 comes on in more mature megakaryocytes.
21:15You can see that they already start
21:17to mature down the Meg lineage
21:19just by over expressing this pre
21:21phosphorylated Bronx one compared
21:23to the 4A or the wild type.
21:26We then looked at gene expression changes
21:28and cut and run in these health cells.
21:30I'm just showing you gene expression changes.
21:32First glycoprotein 1B beta is a
21:33gene that's very important in Meg
21:35maturation and what you can see
21:37and this is just two duplicates of
21:38each for the empty vector cells.
21:40For the cells that we're expressing
21:424A that cannot be phosphorylated
21:44on this four residues,
21:45the wild type and the 4D that's
21:48pre phosphorylated.
21:48And what you can see is
21:50this gradual increase in
21:51the glycoprotein 1B beta consistent with
21:53the increased CD 42 that we had seen when
21:56we looked at where is that Runx one bound.
21:58So the over expressed 4A4D and wild
22:00tape are all HA tagged and when we
22:02did anti HA cut and run what we
22:05found is there's no difference,
22:06they all bind just fine.
22:08This isn't a complete surprise because
22:11the DNA binding domain of Runx One
22:13is not near those phosphocytes.
22:15But what it strongly suggests is
22:17that Runx one can bind but the post
22:20translational modification is what's
22:22affecting its effect on transcription.
22:24And keep that in mind because I think
22:26we we start to have clues now as
22:29to where that might be taking us.
22:31This is just showing you that when
22:32we combine the cut and run and the
22:34RNA seek data that we have this group
22:36of genes that are activated by both
22:38wild type and 4D in the health cells
22:41but not as much by the 4A mutant.
22:43But yeah,
22:44the 4A mutant and those genes tend
22:46to be genes that we know are very
22:48important in Meg maturation.
22:49So just consistent with what I
22:51already showed you on the other two,
22:53I'm not going to show you a whole
22:54lot of data and a whole lot of
22:56work on the cut and run data,
22:57except to say that there really was no
23:00significant difference in binding of
23:02the four a the wild type in the 4D.
23:04So the next question is what phosphorylates
23:06the runks one and this has been,
23:08this is very recent data,
23:09it's not yet published.
23:10A lot of this isn't published,
23:12but this is like we got it in
23:13the last few months.
23:15Multiple kinases were published
23:17that phosphorylate runks one,
23:19and problem is whether when
23:20we knock down any of them,
23:22we had no loss of phosphorylation on Runx 1.
23:27So what's going on?
23:28We decided what has to be another kinase,
23:31so I'm going to take you through
23:32that a little bit.
23:33The predicted kinases for Runx
23:36one include CD,
23:38all of the cycling dependent kinases,
23:40and CDKS 1-2 and six had all been
23:42proven to phosphorylate it in vitro.
23:44Similarly with the SIP,
23:46K2 and the URC.
23:47But all of their activity was shown
23:48in reporter assays and it didn't end
23:50up being relevant for our primary
23:51cells where the phospho levels
23:52didn't change when we knocked down
23:54these genes or inhibited them with
23:56with with very small molecules.
24:00In fact,
24:00if you what we found
24:02is if if you
24:04inhibit CDK 9,
24:06which is completely different CDK,
24:08that's when you lose it.
24:09So I'm going to show you first,
24:10this is what happens when
24:11we inhibit CDK four or six.
24:13So they were predicted.
24:14CDK six was predicted to
24:16be a kinase for Runx One.
24:18I previously showed you these
24:19data in a different context.
24:21When you inhibit CDK four and six,
24:22you actually get more
24:24phosphorylation of Runx One.
24:25Remember that was consistent with slowing
24:27the cell cycle more Runx 1 phosphorylation.
24:29So CDK 6 is not the thing that's
24:32phosphorylating Runx One in our cells.
24:34But when we inhibited CDK 9,
24:37which was another predicted kinase
24:38that would phosphorylate these cells,
24:40then we saw something really interesting.
24:42Then the total level of Bronx
24:44One didn't change,
24:45but the levels of both phosphoserine
24:473O3 and phosphoserine 276 did change.
24:49Now this is one of several flavopyridol
24:52is one of several CDK 9 inhibitors,
24:54but none of them is absolutely
24:57specific for CDK 9:00.
24:58So we ended up getting a different
25:00CDK 9 inhibitor that is more specific.
25:02It's called phallus NSO 3 two,
25:04and it induces degradation of CDK 9,
25:07which I'm not showing you, but it does.
25:09And when we added the Thou,
25:11we also got the loss of the
25:14phosphoserine 3O3 and phosphoserine 276.
25:16And when we added the Thou to the cells,
25:19just as we had expected,
25:20we got an erythroid bias to our MEP.
25:23Really.
25:24Now connecting CDK 9 activity to Ronx 1
25:29phosphorylation to MEP Fate specification.
25:33Now for those of you who know what CDK 9 is,
25:35this is just like,
25:36Oh my God, what's it doing?
25:37And I the answer is I don't know.
25:38But for those of you who
25:40don't know what CDK 9 is,
25:41the reason this is exciting is
25:43CDK 9 is part of just the general
25:46transcriptional control apparatus.
25:49It's part of activating RNA polymerase too,
25:52but in published data from years
25:54ago that has never been explained.
25:57Knock down the CDK 9 causes you to lose
26:00megacary sites and people never knew why.
26:02So I think we now have a link between CDK 9,
26:05Runx One and Meg Fate specification
26:07that we have a grant to look at.
26:10So the summary of Part 2 is that
26:13phosphosurine RUNX 1 promotes Meg
26:16Fate specification that's through
26:18phosphorylation by CDK 9 which is part of
26:21the transcriptional regulatory complex.
26:22And the work that we're in the process
26:25of doing that I I don't know the
26:27answer to it yet is what is their
26:30differential binding as phosphosirring
26:31runks 1 to different target proteins.
26:33And we really want to do RNA seek and
26:35cut and run on these various different
26:37runks mutants in primary cells because
26:39everything I showed you for that
26:41so far was done in health cells.
26:43And then really,
26:44how does the CDK 9 Pol 2 Runks 1
26:47regulate transcriptional elongation
26:49to promote Meg BAKED specification.
26:52OK Act 3.
26:52So act three is I showed you
26:55that we get colonies and what we do is we
26:58read those colonies out after two weeks.
27:01So you put cells in two weeks later
27:02you say what colony types do we have,
27:04but we really then are not not,
27:07don't know for sure what's happening
27:08with all the cells in between.
27:10For example, is there more rapid
27:12proliferation in the cells before they
27:14pick the erythroid fate and slower
27:17proliferation before they pick the Meg fate?
27:19How are we going to look at that?
27:20We have to actually watch them
27:23undergoing this fate specification.
27:25So what Vanessa Scanlon lab and did in
27:28my lab and Vanessa has now moved on.
27:30She was an amazing post doc and
27:32she's now an assistant professor at
27:34University of Connecticut and what
27:36she did is she developed a time lapse
27:38microscopy to watch individual human MEP
27:41undergo fate specification in vitro.
27:47So here's what she did.
27:48She took her facts, sorted MEP.
27:50She put very few of them in a
27:52very small volume in a in a plate
27:54covered that and that in the same
27:55semi solid medium that we use
27:57for our colony forming essays.
27:58But it has it's very flat.
28:00She puts a cover slip on top of
28:02that puts it into the Viva view.
28:03This is an Olympus apparatus
28:05we still have in the lab.
28:07It works beautifully.
28:08They don't make it anymore.
28:09So for now we have it and then she
28:11can watch these cells undergoing
28:13fate specification and add the
28:15antibodies towards the end of making
28:16the movie so that the erythroid cells
28:18under are showing in red and the
28:20megacuria sites are showing in green.
28:22So here you have a bipotent colony,
28:25a mega only colony and an erythroid colony.
28:26But they're all very flat because
28:28we're looking at this and we're going
28:30to want to look at this over time.
28:32Here's an example of an MEP colony
28:34of an MEP ending up making a mega
28:37carry site in erythroid colony.
28:39The little dots that color them,
28:41we put those in, that's part of our analysis.
28:43So I don't have that pre dotted.
28:46But anyway, so that's a single cell.
28:47We're starting with a single MEP
28:49and then what you're going to
28:51see is that that cell over time,
28:53and this is over the course
28:54of about seven days,
28:56undergoes state specification.
28:57If it's blue,
28:58it means that downstream of that cell
29:00there are both Meg and Erythroid cells.
29:02If it's red,
29:03it means everything downstream of
29:04that is Erythroid and if it's green,
29:06it means everything downstream
29:07of that is going to be Meg.
29:10And there are a lot of things
29:11that you can see here.
29:12One of them maybe you saw
29:14those streaky green lines,
29:15the Meg progenitors move a whole lot
29:17more than the erythroid progenitors.
29:19We're not sure yet what that means
29:21and whether it's relevant for
29:22what's going on in the bone marrow.
29:23But what we do know is in the bone marrow,
29:25people have looked at it,
29:26Erythroid maturation tends to hurt
29:29occur in bundles, whereas megs,
29:31they tend to be all over the place.
29:33So we think that this might have
29:34something to do with the fact
29:36that the Meg destined cell is
29:37still quite motile and there are
29:38other things that you can see.
29:39I'll just let's go take show you
29:42quickly where you can see that there
29:44are blue cells that are still present
29:46after multiple rounds of division,
29:48but fewer and fewer of them.
29:50Some of the blue cells are still
29:52here even pretty late when
29:53the other ones still haven't
29:55undergone fate specification.
29:57When we analyze these,
29:58one of the first things we saw is.
30:00So this is now a tree where the
30:01blue cells are bipotent,
30:02the red cells are erythroid committed
30:04and the green cells are Meg committed.
30:06When I say committed,
30:07I should probably say destined.
30:08We don't really know when they committed.
30:10We just know what the
30:11cells became at the end.
30:12One thing you can see though
30:13is that MEP self renewal,
30:15this is not something anybody had
30:17ever known before and it was kind
30:19of questionable when you look at
30:20the single cell RNA seek data.
30:22If you remember we had this graduation,
30:24I didn't know how long that graduation took.
30:26Maybe cells just become an MEP and then
30:28the next day they're mega erythroid.
30:30But here you can see that the
30:31bipotent cells can self renew
30:33and make more bipotent cells.
30:35Sometimes where one bipotent cell
30:36makes 2 bipotent cells and times where
30:38sometimes where it makes 1 bipotent cell
30:41and one fate Destin cell unique fate.
30:43And when we and this is just looking
30:45at the the sometimes when we played
30:47at MEP we got MK only colonies,
30:49sometimes when we got we played
30:51at MEP we got E only colonies.
30:53So this was another opportunity
30:54for us to say, well,
30:55is this different from when we plate
30:57an erythroid progenitor that we already
30:59know is E committed or a Meg progenitor?
31:02And the answer is yes.
31:05This is a sample tree from an
31:07MEP that's going to undergo fate
31:09specification down both lineages.
31:11Here's one where it's going to
31:13undergo Meg only or Erythroid only.
31:15If you compare that when we
31:18plate the Meg progenitors,
31:19there aren't very many divisions.
31:21They make teeny tiny colonies and
31:23when we play erythroid progenitors,
31:24what we see is that they reach
31:27this faster proliferation sooner.
31:29So they really are downstream of this
31:31cell that we're seeing here that is
31:34making a much larger colony with,
31:36and it doesn't speed up its
31:37cell division quite so early.
31:41This is another way of looking at
31:43the data where what you can see is we
31:45were able to follow these cells for
31:47up to 13 generations, a single cell,
31:49what happens over 13 generations in
31:51vitro and what you can see is expansion.
31:53When one MEP makes 2 ME PS tends to
31:56occur but one is that's where we started.
31:58We only looked at colonies that
32:00were going to make both here.
32:01But what you can see is that you
32:03really get MEP self renewal where
32:05you're going to get two expansion from
32:08MET one MEP to two MEP for the 1st 3
32:11divisions and then that gradually goes
32:13away and by the 6th division you're
32:16not getting one MEP making two MEP.
32:18In contrast this maintenance division
32:20where one daughter cells going to be a Meg,
32:22an MEP and one is going to be fate
32:24destined that starts to occur at
32:26approximately the 4th generation and
32:27that's what we have until the end.
32:29And with each time you have one
32:31of these yellow divisions,
32:32that's when one MEP makes 1 Erythroid
32:34fate committed and one MK fate committed.
32:36That's going to be the end of the
32:38line because we're not going to
32:39keep following MEP.
32:40So it really gives us a nice way of looking
32:42at the changes that occur over time,
32:44which ends up being highly relevant
32:46for our predictive models.
32:48What we wanted to do is come up with
32:50a mathematical model that gave us the
32:52outcome that we saw so that we could
32:55understand the probability that a cell
32:57would undergo a specific fate decision.
33:00And this is work done by Everett Thompson
33:01in my lab who's an amazing graduate student.
33:04And what he realized is if he used a
33:07Markov model of these cells that are
33:09MEP that are expanding to make two
33:11MEP exhaustion where the MEP makes
33:131 erythroid and 1 Meg fate specified
33:16versus these two maintenance divisions.
33:18He could model the data that we got
33:20as long as he had that model change
33:23over time,
33:24which is consistent with what I just
33:25showed you.
33:25It does change over time the the
33:28probability that the MEP will self
33:30renew and expand.
33:31So when he did that he got the data
33:33that are plotted here.
33:34So what you're seeing here is the
33:37the broadbands shown here in blue,
33:39purple, Aqua and yellow.
33:41That is the data predicted by the model.
33:44And then in the dotted line is the.
33:48I want to make sure I say the right thing.
33:50Yeah.
33:50And the dotted line is the in blue
33:52is the observed data.
33:54So what you can see is we really
33:56are very closely modeling what the
33:58actual data are for the exhaustion,
34:01expansion, maintenance and maintenance.
34:03The way to look at this is,
34:05for example,
34:05if you just look at Generation 4,
34:08if you have an MEP,
34:09their chances are 46% chance of
34:12expansion or one MEP makes 2 MEP,
34:1528% chance that you're
34:16going to get maintenance
34:18plus E, 9% chance of maintenance plus
34:20MK and a 17% chance of exhaustion.
34:22Well, that kind of models our
34:24outcome in our CFU where we get about
34:2650% of the colonies have Mega and
34:28Erythroid and the other ones are
34:30Unilineage MK only and Erythroid only.
34:32And then similarly you can look at another
34:35generation and get additional data.
34:39She Vanessa got a huge amount of
34:41data out of this and I just want to
34:43show you one other part of that.
34:45And what she did is she analyzed the
34:48length of the cell cycle and whether
34:50that predicted output and it wasn't
34:53as simple as we had hoped, but we did
34:56get some statistically significant data.
34:57The data that we got is that MEP
35:00that are cycling slower are going
35:04to be the MK destined.
35:07Remember MEP cycling?
35:08I have to remember exactly.
35:10So there was no difference.
35:11And this is where this was disappointing.
35:13There was no difference in the cell cycle
35:16interval between MEP and E destined cells.
35:20I thought that we would have seen that the E
35:22destined cells had a faster proliferation,
35:24but that's not what we saw.
35:26But we did.
35:27What we did see is that once we and with
35:30MK destined it was a little slower.
35:32That's the point I wanted to make.
35:34So there was a slowing,
35:35as if the cell was dividing more
35:37slowly there was a very good chance
35:39that it was going to be MK destined.
35:41And then if you looked at the MKP themselves,
35:43they are,
35:43they're known to have a slower cell cycle.
35:44I already told you that.
35:45But this was really the the new
35:47data was this MK Destined having
35:48a slightly slower cell cycle.
35:50So not quite as clear as we would have liked,
35:52but that's what the data show
35:56this. So just this is this time
35:58lapse imaging is now a tool in the
36:00laboratory that we are enjoying using.
36:01If anybody wants to collaborate and
36:03use this tool just let us know.
36:05It's one of the tools that's offered by the
36:08Yale Center of Excellence in Hematology.
36:12So last story, plenty of time I
36:14wanted to tell you about expansion
36:16microscopy to probe hematopoietic cells.
36:18So what is expansion microscopy?
36:20This is a way of doing super
36:23resolution microscopy using a confocal
36:25microscope and that really opens
36:27up the door to all of those of us
36:30who don't do electron microscopy.
36:31And even if you do do electron microscopy,
36:33you know it's very difficult to do any
36:36kind of immuno analysis because you're
36:38really limited to the size of the gold
36:40balls that are attached to your antibody.
36:42So you maybe can look at two things at the
36:44same time and maybe can see where they are.
36:47Here you have a confocal you can do
36:49immunofluorescence from for some antigens,
36:51not for every antigen with the expansion.
36:55So this is just to get you guys interested,
36:57if you're not a pathologist
36:59in looking at mega karyocytes,
37:00they happen to be the most beautiful
37:02cell in the body according to me.
37:04And what you can see is they're very,
37:06very large, hence the name mega karyocyte.
37:09What we're looking at here
37:10is a bunch of blood cells.
37:12These are your normal neutrophils.
37:14You can see the size of their nucleus,
37:15it's about 8 microns and
37:17this is a mega karyocyte.
37:19It's a single cell.
37:21It's got this gigantic nucleus and a
37:24gigantic cell and what this nucleus is,
37:27is it's polyploid.
37:28It's got the cell has divide,
37:29the DNA has divided and the cell
37:31has gotten bigger and bigger,
37:33but the cell has not divided.
37:34So you have many.
37:35You can get four and eight and 1632,
37:37whatever, up to 128 clearly.
37:41And then this part of this cell,
37:43which is super interesting
37:44and hard to describe,
37:45but you're about to see what it is.
37:47It's not a single cell membrane
37:50surrounding a cytopus.
37:52Well, it is,
37:53but the cell membrane is invaginated
37:55all throughout that cytoplasm.
37:58And way you can see that is from this movie.
38:00So this is a movie.
38:01It was published in 1999 by Joe Italiano,
38:04who's an amazing mega karyocyte
38:05scientist up at Harvard.
38:07This is a single mega karyocyte.
38:09Here's its nucleus.
38:10It's starting to make pro platelets.
38:12And the thing that's amazing about
38:13this movie is you can see that
38:15the cytoplasm is basically going
38:17to unravel to release the pro
38:19platelets that then become platelets.
38:26So all that membrane system was inside,
38:28it was all packaged and then it just
38:30had to be induced to to unravel itself
38:33and release these pro platelets.
38:35So yeah, it's a very cool movie.
38:38When people then look at megacary sites, they
38:41want to see that demarcation membrane system,
38:43that invagination of the plasma membrane.
38:46And we're doing this using
38:48expansion microscopy.
38:48So what is it, expansion microscopy?
38:50It's been developed in multiple laboratories.
38:54Neither of these labs,
38:55York Broersdorf or Yong Shinzhao's,
38:57was the first to do it.
38:58But these are the two people
38:59that we're collaborating with.
39:00Many of you may know York.
39:01He's here at Yale.
39:02He does beautiful work with Pan XM
39:04that I'll show you the I And Yong
39:06Shinzhao is at Carnegie Mellon.
39:08He has a different approach called magnify.
39:12And what you can see is that you take
39:15your cell and here we're just looking
39:17at different the mitochondria and
39:19the Golgi here in the cell and you
39:22polymerize polyacrylamide gel into the cell,
39:25hit it and it cross links with it.
39:27You then expand that because there's
39:30acrylamide in there and sodium acrylate.
39:32Sodium acrylate is what's in babies diapers.
39:35It's very,
39:36very absorptive.
39:36So if you have sodium acrylate and then
39:39you add water everything expands so
39:41you get this huge expansion then what
39:43they do in the boomers Dorf's lab is
39:47they stop that get rid of the cross
39:50linking re embedded and do it again.
39:52So they can get up to 16 to 20
39:54fold expansion of a single cell.
39:57With Magnify you get about a 10 fold
39:59expansion and I'll tell you about the
40:00differences but we we do both in the lab.
40:02I mean the idea is you type take
40:05one thing that was really little
40:07and now it's really big.
40:09This is data from your Goersdorf's lab using
40:12the Pan XM his two fold expansion approach.
40:16What you can see in these cells is
40:18an NHS Ester just stains proteins.
40:21So it gives you something that's very
40:23similar to what you might see on EM.
40:25And you see this beautiful
40:27Golgi apparatus in a cell.
40:28This is just he LA cells.
40:31They can actually get antibodies to
40:34work that allow them to localize whether
40:36a protein is on the outside or the
40:39inside of this of the mitochondria.
40:41And So what you can see here is
40:44when they stain with anti Cox four,
40:46it's on the inside of the mitochondria.
40:48When they stain with anti Tom 20
40:50which is known to be on the outside
40:51of the mitochondria,
40:52you can see this different
40:53pattern and it's really,
40:54really beautiful how you
40:56can clearly see the Cox,
40:57the Tom 20 is on the outside and
40:59the Cox 9 is on the inside Cox four,
41:02sorry.
41:02So just beautiful imaging that we
41:05want to be able to use in now in
41:07mega carry sites and platelets.
41:09This is a comparison of Magnify which
41:12is from Yong Shin Zhao's lab and the
41:15Pan XM that is in your Boomer source lab.
41:17And we really takes the best of both in some
41:21of our assays York Boomersdorf's approach.
41:23The Pan XM gives you much better resolution.
41:26No doubt you're getting 16X expansion and
41:29you're really preserving morphology better.
41:31However, it takes a lot of time and effort.
41:35In contrast,
41:37Yongshin's approach called Magnify,
41:38just takes one to three days.
41:39It's less than an hour of hands on time per
41:42day and there's no special equipment needed.
41:44You don't need this nitrogen
41:45tank and you get less expansion,
41:47but it's still quite beautiful.
41:48So I'll show you some data
41:49that we have for each.
41:50And this is not an expensive thing to do.
41:54This is just a beautiful image
41:56that comes from the that we did in
41:59collaboration with your Brewers.
42:00Dorf's lab and your runs the imaging core
42:02for the Center of Excellence in Hematology.
42:04And what you see here is a pan XM image.
42:07So that's the 16 fold increase,
42:1020 fold increase.
42:10And they pan stained it with the NHS Ester,
42:13which stains all proteins and with M cling.
42:17The nice thing about M cling is it bind,
42:18you stain the cells before you expand them.
42:20It binds to membranes,
42:22it binds to lipids.
42:23And this is allowing us to start to see this
42:26invaginated membrane throughout the cell.
42:29And we're getting better and better
42:31images of this invagination that
42:33tells that shows us the demarcation
42:35membrane system of the megakaryocytes.
42:39So here's another way of looking at
42:41this demarcation membrane system.
42:42Now not with the M cling but just with
42:44the pan stain of all the proteins.
42:46This is an electron microscopy image and
42:48this is from our expanded whole bone marrow.
42:52This is Mina Shu gave us this slide.
42:54So this is expanded bone
42:55marrow from human FFPE tissue.
42:57And what you can see is that this PAN
43:00XM really shows you the demarcation
43:02membrane system similarly to what you
43:05can see with the electron microscopy.
43:07Here's another expanded thing.
43:09This is now from magnify,
43:11showing that we have some antigens
43:12that we can identify.
43:13We can identify CD 61 shown
43:15in green and thrombospondin.
43:16So these are megacaryocytes and
43:19these green and red vesicles are
43:22actually the granules that are going
43:23to become the platelet granules,
43:25the alpha granules that have
43:26within them the thrombus bonded.
43:30And this is an image.
43:31I just can't get it out of my mind.
43:32But we haven't seen this again,
43:34we haven't done this.
43:35Again, this is again the formal
43:37and fixed paraffin embedded tissue
43:38from Mina shoe where we just
43:41did a pan stain after expansion.
43:44And I can't get over this little
43:45hole in the megacaryocyte.
43:47I really think that this might be
43:49where the invagination is happening,
43:50but we have to see it more.
43:52But I'm showing it to you
43:53because this is a pathology,
43:54grand rounds and it's so beautiful.
43:56These are autofluorescent red blood cells.
43:57On the on the outside it's
44:00just your gigantic nucleus.
44:01What what we've been quite
44:04successful at is using this to
44:06look at platelets and this is
44:07work that was done by Max Carlino.
44:09Some of you may know he's a first
44:11year graduate student of pathology,
44:12but he worked in my lab before
44:14that and he worked on this
44:16expansion microscopy on platelets.
44:17This is just an ultra an electromic
44:20graph view of a platelet and you can
44:22see that there are dense granules
44:24and there are alpha granules.
44:25So I didn't mean to go to the next
44:27one so quite so quickly at but you
44:29need electron microscopy to see the details.
44:31So what Max was able to do was expand
44:34primary human platelets and then just
44:36this was just the pan staining with
44:39the protein stain you can see granules.
44:41Then he used antibody against thrombospondin.
44:45Oops,
44:45it's supposed to be playing Oh well then
44:47he used antibiotic and there you go.
44:49So sorry.
44:51This is the thrombospondin
44:53which is in alpha granules.
44:55This is staining for tubulin which
44:57is on the outside of platelets.
45:00So and just the way you expect,
45:01we can see this tubulin ring and
45:03this is showing you both the tubulin
45:05ring and the thrombus bonded.
45:07Beautiful. What can we use this for?
45:09Well,
45:09one of the things we can use it
45:11for is to try to quantitate alpha
45:13granules within the platelets.
45:14And what I'm showing you here on the
45:16left is some of the classic work
45:19where they were quantifying alpha
45:20granules in platelets using electron
45:22microscopy and they got about 50 such
45:25granules per platelet on average.
45:28This is our data,
45:30not counting them using electron
45:31microscopy where you it's a huge
45:33amount of time and effort to try to
45:35get this three-dimensional microscopy.
45:37Here he can look at 151 platelets
45:39in that stained slide that in the
45:41slide I just showed you and he can
45:43say how many total granules are
45:44there and how many granules are there
45:46that have thromaspondon in them.
45:48And he could see that there were a
45:49little bit more than 50 granules
45:50on average per platelet looking
45:51very similar to this.
45:52And then he could even look at
45:54what percentage of those platelets
45:55have thromaspondon.
45:56So again something that I think
45:57can be useful clinically,
45:58certainly it's interesting scientifically.
46:02So finally,
46:03this is what I've told you today that
46:05single cell RNA seek reveals MEP
46:07as a unique transitional state in
46:10hematopoietic fate specification.
46:12That cell cycle differences really
46:13seem to regulate MEP fate and
46:15we're trying to figure out how.
46:17One of the ways that seems to be working
46:20is through in a slower cycling cell
46:23there's more phosphoserine Ronx one,
46:25and that phosphoserine Ronx
46:261 activates Meg genes,
46:28so you get Meg fate specification.
46:30I showed you time lapse imaging
46:32that really showed at least that
46:34statistically significant slowing
46:36of the cell cycle speed predicts
46:39MK fade specification and that
46:41we can predict the probability
46:43of MEP fade specification over
46:45time with this Markov model.
46:47And finally that we're very excited about
46:50the power of using expansion microscopy.
46:53I wanted to take a minute to tell
46:54you about the cooperative centers
46:55of excellence in hematology,
46:57which Karen already mentioned,
46:58but who listens to the intro.
46:59So YCCEH is funded by the NIDDK.
47:04Yale is one of five such centers
47:07nationwide and we all provide
47:09cores that can help people who
47:11do non malignant hematology.
47:13And some of what I showed you
47:15today is available in our core
47:17including the expansion microscopy,
47:18the time lapse microscopy,
47:21CDC's colony forming assays.
47:22We can help you with hematopoietic
47:25assays and other across the country.
47:27There's a metabolomics core for
47:28any non malignant heme work
47:30that you're doing in at Utah.
47:32There's an imaging core that
47:34does codecs in Indiana.
47:35You can get as many CD34 cells as
47:38you would ever need from multiple
47:40types of donors in Seattle,
47:43so do contact me if you want to be part
47:45of that or look it up at cceh dot IO.
47:48Finally, there are grants available
47:50through ICCEH Money,
47:51Money, Money, money.
47:52They have Type A grants and Type B grants.
47:54The Type A grants give you $12,000 worth
47:58of services at any one of the five cores,
48:01and those are it's a rolling submission.
48:04Anytime you have one of these just
48:06submit it and we'll we review
48:08the monthly and then the Type
48:09B grants are up to 70,000.
48:11They take an 8% overhead out of that
48:14$70,000 for you for your research
48:16for non malignant hematology.
48:18And those Type B grants are due
48:21February 15th I think don't quote me
48:23on that go to I go to CCH dot IO.
48:26But really it's it's they're good grants.
48:28So finally thank you to the lab,
48:33everybody's pictured here and hopefully
48:34I gave them credit as we went along.
48:36Thanks so much.
48:46This is open for questions.
48:50Yeah,
48:53expansion by class is 34.
48:56I'm wondering do you know if
48:59that expansion material disrupt
49:01like protein public interaction,
49:03did you try to see that colonization
49:05of sort of things? Yeah. So
49:11the answer is that proteins stay
49:12intact and protein interactions they
49:15they're they say look Co localized,
49:17but I don't know if they stay
49:18negative if it's not prevailed.
49:20What you what you can do though with
49:23extended microscopy is Co localized
49:252 proteins that you cannot clearly
49:28visualize if you don't have extension.
49:30So if you stain them after you've extended,
49:33you'll really be able to see
49:34that they were right next to each
49:36other and all of the epitopes will
49:38still be there because they're not
49:40blocking one another by being bad.
49:42So people have done Co localization
49:44studies with expansion that weren't
49:46feasible prior to having expansion.
49:48But if you're asking other things when we
49:51don't know what happens to DNA and RNA,
49:53some people have gotten fish to work,
49:55but I don't really know what the
49:57stretching does and what exactly gets
49:59stretched at that tiny molecular level.
50:01I've asked the same questions to the answer,
50:04but I'm not sure you know,
50:07with your increase in drugs on
50:10causing the increase in accuracy.
50:13Do you know that this later gets rise
50:17to functional increase in platelets?
50:21No. But what we do know,
50:23so our work was unique in
50:25starting with the bipodent progenitor
50:27and what we were always looking
50:29for is just which fake did it pick.
50:31And so you're right, we're only
50:32looking like the first part of it,
50:35but we didn't come up with
50:36rocks all by ourselves.
50:38Bronx One is known in a mouse.
50:40If you knock down Bronx One,
50:41you have lower meds, lower platelets.
50:43If you over fresh rocks,
50:45you have more meds and more platelets.
50:46What wasn't known is where was
50:48that acting and that it might
50:50be acting literally at the Fate
50:52specification level of an MEP.
50:53So I think they would,
50:55but I can't tell you for sure.
50:56I ask this because of our patients
50:58with rocks one journal on mutation
51:02and they in the bone marrow have the
51:04creation of abnormal and carrying sites,
51:07but then they have Bronx therapy.
51:10Those patients actually are
51:13hemisitis for inactivating mutation.
51:16They have decreased Bronx activity.
51:20So their mutant Bronx is either hypo
51:23functioning or not functioning at all.
51:25I wasn't aware then more plate, more megs.
51:28I know they have lower ploying megs because
51:30they have a defect in Meg maturation
51:32and they have lower platelets. Yeah,
51:37yes, yes, it's really beautiful.
51:40I was wondering that the the
51:42the common progenitor and in vitro,
51:44the lineage commitment from the Detroit
51:47and and Medicare is obviously driven by
51:49the cell cycle towards that it's right.
51:52Could you understand your situation in
51:55vivo where those things are altered in
51:58a way that the the ratio you know the
52:01cell has to decide it's going to make?
52:02How many RPCS and how many pavements?
52:05In which situation does it go awry
52:07and is it truly lineage commitment
52:12between or is it just stochastic? Well,
52:15we think it's truly lineage commitment
52:17on a stochastic low because
52:19there's always probability.
52:20We don't see that if we overspress rocks,
52:23everything goes in it.
52:24It's just some ability to go overthrow it.
52:25In fact you need rocks one
52:28for erythroid maturation.
52:29So I think it's stochastic but biased
52:32that you know you have one ratio.
52:34In the absence of over expressing
52:36wrongs you get a ratio that's very
52:37Meg biased when you over express
52:39wrongs and more Meg bias if you have
52:41normal. But in a normal progenitor
52:43what is the ratio of commitment
52:45towards something like a carrier
52:46site and the unit for itself?
52:48You're asking in vivo and I can
52:49only tell you in vitro, yeah,
52:51or even in vitro. In vitro,
52:53it seems that they're about equal and
52:56there's a there's a good reason for that.
52:59What happens downstream is the
53:01erythroid progenitor proliferates
53:03log fold multiple times very quickly
53:05to make a lot of erythroid cells.
53:08The Meg progenitor doesn't
53:10proliferate very many times,
53:12but each mega carry site makes
53:1410 to the three platelets.
53:16So you have a three log production
53:20per mega Carrison.
53:21So it kind of works mathematically.
53:24If you say you make one play
53:25then one or it's all about you
53:27know 1 to 1 ratios that
53:28that's how it would go. And
53:29we know if in older adults where
53:32there is minority buys that
53:34that there is a a differential
53:36response to this commitment between
53:38megataryocytes and heart disease. I
53:39don't know, I'd love to actually get access
53:42to marrow from patients with different
53:44diseases and that's been problematic.
53:46We have looked at MPNS and in MPNS if they
53:50have essential thrombocytosis then they
53:52do tend to have a Meg bias to their MEP
53:55and the opposite for polysychemia Vera.
53:57But it's very subtle.
53:58I think a lot of that is downstream of
54:01the MEP and the FATE certification.
54:04Jack 2:00 and from and Teepo, they're there.
54:07They're acted the whole time.
54:09So it's not going to just toggle
54:10it. Yeah. So
54:12along those lines that you looked or
54:14what do you know about CHIP and actually
54:18mutations in Ronczuan,
54:18a lot of things in terms of their
54:21cell cycling and their biases,
54:23nothing but. But patients with Ronczuan
54:26familial mutations in Ronczuan
54:28do have an increased risk of Chip
54:33that might just be because they
54:34have abnormal Hemato policies.
54:35And so the few, the better cells
54:37are the ones that are taking over.
54:39But I I don't know for sure.
54:40It's a good question,
54:42really good question.
54:43It'll be fun to look at that.
54:45We have a lot of such patients
54:46that we can get access to cells.
54:53That question
54:56hypothetically speaking, eventually
54:57the red blood cells will be Euclided.
55:01Is there part of the process that they
55:03don't have to have a nucleus in the end
55:05that allows them to proliferate so fast?
55:07Is the ability of proliferation is is
55:10reduced because they don't have to
55:12maintain the full sort of nucleus.
55:14They can just go faster by being
55:16more efficient in that way.
55:17They keep
55:17it absolutely as well they're.
55:20But content is the content the same?
55:21Do you know what the size
55:23as they as they go forward?
55:24It's a good question for PAD Gallup.
55:26Here we go. What we do know is that
55:31as these erythroid cells are matured,
55:33they're proliferating.
55:34Again, matured that with the maturation,
55:37the nucleus shuts down and the histones
55:40get spit out. But prior to that,
55:42when they're so proliferating,
55:44I'm not aware of what's changing at
55:46the chromatin level, but correct.
55:48But that's been published.
55:49I should know.
55:50It's because Pat's published,
55:53I think what they,
55:54I think if I remember correctly,
55:55they express fewer and fewer genes
55:57and higher and higher levels of
55:59the erythroid genes and you know,
56:00like globins because it's going
56:02to need all that globin for
56:03when it doesn't have a nucleus
56:04if they give them a timing advantage, if
56:06they're going to that moment. So they can. I
56:08don't know why it sounds like
56:09being so fast. It's part of their
56:12own. Yeah, throughout that. So you can see,
56:18so can you see any advantage to
56:19cycling faster or that you can cycle
56:21faster because you don't need so much
56:23activity going on in your nucleus,
56:29which is like slow down. Yeah,
56:35sticking outside. Oh, I like it,
56:36I like it. Let me know when you
56:38have to go to that conference.
56:40So in addition to intrinsic
56:42things that would be
56:46differentiate, you can see downstream
56:48what about contribution from other
56:50cell types either from other chromatic
56:52cells and signals or thrombo cells.
56:56We have looked really hard for other parts
56:58of the micro environment that might affect
57:01MEP fate and I did not include those data,
57:04but we've done a lot of work and and
57:06Vanessa's published quite a bit on it.
57:07One thing we know is there are two growth
57:10factors that may many of you may be
57:12aware of erythropodent and thrombopodent.
57:14Thrombopodin sounds like it's making
57:16platelets, right, Thrombopodin,
57:17erythropodin making erythroid but
57:19they actually act super differently
57:22on different cells.
57:23Thrombopodin is the thrombopodin
57:25receptor is is on hematopoietic stem
57:28cell and all of those progenitors.
57:30So they all need thrombopodin
57:31and they're it's binding in the
57:33middle of the thrombopod receptor.
57:35When you get to the anti P level though,
57:37the erythroid progenitor loses its erythroid,
57:42its thrombopodin receptor,
57:44so it does not have ****** on it,
57:47and the MEP progenitor has increased ******.
57:51What we thought then is if we add
57:52****** or remove ****** we're going
57:54to affect faith specification.
57:56No, what happened is when you
57:58remove thrombocodin,
57:59I'm sorry saying that one.
58:00When you remove thrombocodin you get
58:02exactly the same ratio of colony types,
58:05but way fewer colonies and the
58:08colonies are teeny tiny.
58:09And when we look at the time
58:11lapse microscopy of that,
58:12what we see is that the cells are dying.
58:14So they're trying to,
58:15they're doing everything right
58:16at the beginning and then you
58:18can just see apoptosis.
58:19I don't know,
58:20I didn't prove it was after you see
58:21the cells dying with erythropoietin,
58:23again no difference in fate specification,
58:27but a lack of erythroid maturation,
58:30absolutely no difference
58:31in the ratio of output.
58:33We have seen an effect in this and
58:35this is part of Vanessa Scanlon's
58:37work now in the lab that when she Co
58:40cultures the cells with endothelial
58:42cells then she also sees an an
58:45erythroid phase specification.
58:46It's it's subtle but she can
58:48see a statistically significant
58:50increase in E phase specification.
58:52What she wants to do now is very
58:54methodically add different cell types
58:56that are in the bone marrow micro
58:58environment and determine how they affect
59:01NDP phase specification individually
59:03and together and then determine how.
59:05But that's as much as we know,
59:06but it's definitely not TECO and ECO.
59:09Has she tried macrophages
59:10since there's the, you know,
59:16I think she did once but
59:18she didn't have really good
59:19macrophages to use.
59:21We're much better in my lab at
59:23making urine macrophages than human.
59:24So I'd say we haven't done that adequately.
59:28I am here,
59:30very nice talk. So I think this
59:31is just a
59:37using the IPS cell, it's with the
59:41fringe and all kind of other cells,
59:42but they cannot differentiate
59:44that character. Is that true?
59:47They can make mix.
59:48They can make mix and in fact there's
59:50even one really good scientist who
59:53has made IPS derived megacarius like
59:56progenitor cell line that is a it's a
59:59really beautiful model for studying.
01:00:01You know you can get different mutations
01:00:03from the patients make IPSC make this
01:00:06Meg cell line and basically it doesn't
01:00:09look renty until you then induce
01:00:13the movie show. When you see that, terrified,
01:00:19do you see that? The size,
01:00:22you know, every size
01:00:23comes in the same size. Yeah,
01:00:25yeah, the arithmetics are always small
01:00:26and round and the bags get bigger and bigger
01:00:28and bigger and bigger. But when when
01:00:29do you see the immersion? Just like
01:00:32self started right
01:00:33about the same time that they
01:00:34express the C41. So by the time
01:00:37they're they're they're 41,
01:00:38they're they're kind of bigger now.
01:00:42We haven't looked at that carefully.
01:00:44If we really looked at nuclear size
01:00:46carefully, I would bet we would see
01:00:48something different because they're
01:00:49undergoing different nuclear changes.
01:00:50But we haven't looked that
01:00:51carefully. Thank you.
01:00:55One last question, the
01:00:58cell regulatory volume is it's super, super
01:01:04tightly regulated and that carrier sets
01:01:06something very unique in that regard.
01:01:08So I was wondering can you stall
01:01:10that process and or carrier sets
01:01:14that they do not and you know
01:01:18how long can can
01:01:19that be done or if that
01:01:21happens in any pathologies
01:01:25it hasn't been done but many people
01:01:27have tried not specifically with cell
01:01:29volume because many period sites can
01:01:32make platelets as a 2N cell as 4,
01:01:33N cell as 8, N as 16 and 32.
01:01:36So the question is,
01:01:37what tells the men stop undergoing this
01:01:40end of mitosis and start making platelets?
01:01:44All we know so far is that if you
01:01:47take the inside of a magnet making
01:01:49platelets set up and Joe Battalion
01:01:52and you inject it into a 2NA,
01:01:54it'll make platelets.
01:01:56So there's something that says go.
01:01:59And once you have it,
01:02:00you can transplant it into
01:02:01another bag and it'll tell
01:02:03it to go. So you can give a hypertonic
01:02:05shock to a melancharyocyte.
01:02:06Would it make platelets? I don't know.
01:02:11I don't know if that would
01:02:12be done. I don't know. Thank
01:02:17you. Next.