The Shifting Shape and Functional Specializations of the Cell Cycle During Lineage Development

Transcript

• 00:00Everyone Jeannie Hendrickson I'm one
• 00:02of the Co directors of the enrichment
• 00:05program of the Yale Cooperative
• 00:07Center of Excellence in Hematology.
• 00:09Very excited to have our first virtual
• 00:11speaker sponsored by the Yale Cooperative
• 00:14Center of Excellence in Hematology,
• 00:16but hopefully broadcast to a lot of
• 00:18the other cooperative centers of
• 00:20excellence in hematology across the US.
• 00:23Whether you're looking at us Live
• 00:25Today or virtually on the video that
• 00:28we will eventually post of Mirage.
• 00:31Talk, we're happy that you could join
• 00:33us today and we're extremely grateful
• 00:35to Doctor Moore of Sokolovsky for
• 00:37being our kind of inaugural speaker,
• 00:40virtually for the YCCEH she's a
• 00:41professor at the University of
• 00:43Massachusetts Medical Center,
• 00:45she has had quite a distinguished career,
• 00:47really discovering fundamental insights
• 00:48into Areth row poesis in the process thereof.
• 00:51So again, we're very grateful.
• 00:53But she's our inaugural speaker this year.
• 00:56The way the web and R is going to work.
• 00:59She's going to give her talk.
• 01:01Then at the end of her talk,
• 01:04if you have questions.
• 01:05The questions in the chat or in
• 01:07the question and answer box.
• 01:09I also think I have the option
• 01:10to allow you to talk,
• 01:12so if you put in the chat you
• 01:14would like to talk in person.
• 01:15I can unmute your microphone
• 01:17and you can talk.
• 01:18So without further ado we will turn
• 01:19it over to Rob and thanks again Rob.
• 01:22We're excited to have you.
• 01:25Great, thank you so much.
• 01:27I'm truly honored to be invited to this
• 01:31forum and excited to tell you about
• 01:35the work that we've been doing so.
• 01:39I will attempt to start straightaway.
• 01:42Here we go so.
• 01:44When we think about the cell cycle,
• 01:48we think about a generic program
• 01:50whose purpose is to generate more
• 01:53cells to increase cell number.
• 01:56But when we look at a tissue,
• 01:59the cells that are cycling
• 02:02I usually transient cell.
• 02:04So long term teacher residents
• 02:07like terminally differentiated
• 02:09cells or stem cells.
• 02:11Do not cycle.
• 02:13So what does it mean that only transient
• 02:17cell states are undergoing cell cycle?
• 02:21These cells are continuously
• 02:23changing the genes that they express
• 02:26and our work suggests that they
• 02:28are also continuously changing
• 02:30the kind of cell cycle program
• 02:33that is expressed by these cells.
• 02:36It's likely that linear development.
• 02:39Had really coevolved with
• 02:41modifications in the cell cycle,
• 02:44so cell cycle programs probably
• 02:47adapted to specific tissue and cell
• 02:50cycles and developmental stage,
• 02:53and it is possible that in order
• 02:56to truly understand how a
• 02:59developmental process is regulated,
• 03:02we need to understand the
• 03:05specifics of its cell cycle.
• 03:08So here we're looking at
• 03:11the erythroid linear edge.
• 03:13The erythroid developmental trajectory
• 03:15has two phases earlier through
• 03:18pieces and terminal differentiation.
• 03:21What I'll show you today is that
• 03:24the cell cycle throughout this
• 03:26process varies in logs lockstep
• 03:30with differentiation stage both in
• 03:32terms of the cell cycle length,
• 03:35which here is represented vertically.
• 03:39And in terms of the ratio of
• 03:42S phase to the gap phases.
• 03:44So how did we set out on this question?
• 03:49We started out by asking.
• 03:54One question and that was how is a recruit
• 03:57terminal differentiation activated?
• 03:59We know that in earlier it releases
• 04:02we have progenitors that are already
• 04:04committed to their way through drainage,
• 04:07but that are not expressing any of the
• 04:10jeans that are present in red cells.
• 04:13At some point these progenitors undergo
• 04:16a selfhacked decision that switches on
• 04:19this specific program of red cell genes,
• 04:21and so the question is how does that happen?
• 04:26Of course, many labs are addressing
• 04:28this question, and the angle that
• 04:32we had was to ask.
• 04:35Can we identify the cell in
• 04:38which this activation happens?
• 04:40Our model system is the mouse fetal liver.
• 04:45And and that was,
• 04:46we also have experiments that show you
• 04:49later on in the mouse adult bone marrow.
• 04:52The fetal liver is a great system for
• 04:55working in original places because over 90%
• 04:57of the cells of the erythroid Lenny Edge.
• 05:01So we have two cells of his markers cities.
• 05:04Have anyone until 119 with just
• 05:07these two markers we can divide the
• 05:10fetal liver into a number of subsets
• 05:13that form a developmental sequence.
• 05:15So we find that in the S node
• 05:19subset and S1 subset,
• 05:21that's where we see colony
• 05:23forming progenitors.
• 05:24So this is where we see earlier with
• 05:28paresis and then in subsets as 22S5,
• 05:31we see progressively more
• 05:34differentiated erythroid precursors.
• 05:36And you can see this also here.
• 05:38The colonies that are formed by the S note
• 05:41cells and S1 cells are pretty similar.
• 05:43We wouldn't be able to tell them apart.
• 05:47But two important findings
• 05:48suggested to us over 10 years ago.
• 05:51Now that the S not see if you,
• 05:55we are really quite different
• 05:57to the those in S1.
• 05:59So the first finding was when
• 06:01we examined the fetal livers
• 06:03of a preceptor knockout cells.
• 06:05So here we're looking at two litter mates.
• 06:09This was published.
• 06:10The knockout was first published by Home
• 06:14Grow in the Lodish lab back in 1995 and.
• 06:17When we did flow cytometry on the
• 06:20fetal livers of embryos from a.
• 06:23Some this knockout we found that whilst
• 06:26in the wild type number we already see
• 06:30cells populating most of these subsets.
• 06:32This is Embedded Day 12.5.
• 06:35In the perception knockout,
• 06:37we see an absolute block at the
• 06:40transition from S No 2 S one,
• 06:42so that tells us that the transition
• 06:44is dependent on a preceptor signaling.
• 06:47These few cells that you see over here
• 06:50that tagline positive in the IP receptor
• 06:53knockout belong to the yolk SAC limit,
• 06:56and they're not part of
• 06:58definitive erythropoiesis.
• 06:58Now the second kind of experiment
• 07:01that we did that told us there's
• 07:03something different about S1 and S
• 07:06Note was a cell cycle experiment,
• 07:08and here we have a cartoon that illustrates
• 07:11typical cell cycle experiment that I'll
• 07:13show you a number of times during my talk,
• 07:17so.
• 07:17We take a mouse.
• 07:19In this case it's a pregnant female and
• 07:24injected with beyond you and then harvest
• 07:28hematopoietic tissue 30 minutes later.
• 07:31What we find is 2 things.
• 07:33First, we find which cells are positive.
• 07:36For Bru, these cells have
• 07:38incorporated be audio,
• 07:39which is a finding analog into their DNA.
• 07:43So these cells are in S phase
• 07:46during the 30 minutes of the pulse.
• 07:50A second finding. Is.
• 07:52Allows us to determine the speed of
• 07:55aspects and so we can compare the
• 07:58level of the audio incorporation in
• 08:02the cells of different populations.
• 08:05Cells that have incorporated less beardi.
• 08:08You must be synthesizing.
• 08:10DNA slower and have a longer
• 08:13essays than cells that incorporate
• 08:15the audio at a faster pace,
• 08:19and we've confirmed that with
• 08:21direct experiments that look that
• 08:24use a double family impulse to
• 08:27Measure S phase duration directly.
• 08:30And so when we did this experiment
• 08:32in the mouse fetal liver here we're
• 08:34looking at cells from each of the
• 08:37subsets and at the cell cycle status.
• 08:40We found 2 interesting things first.
• 08:44Whilst about 60% of the cells
• 08:47in S nought so these cells are.
• 08:52In S phase, at any one time.
• 08:53So this is a highly replicative tissue.
• 08:56When we look at S1 over here,
• 08:58nearly all of the cells, 90% in this case.
• 09:03Are in S phase of the cycle.
• 09:05So that's interesting finding number one.
• 09:09And the second finding was that
• 09:11the speed of S phase is about
• 09:1450% faster in S phase.
• 09:17Cells that are in S1 compared with S phase
• 09:21cells in the preceding as node subset.
• 09:25And so a number of.
• 09:27We've done a lot of work on this
• 09:30and I'll give you the summary.
• 09:33The way that we've interpreted our data.
• 09:37Is that the transition from S note to S1
• 09:40can only happen in S phase of the cycle.
• 09:44And this is based on a number of
• 09:47experiments where we have arrested as space,
• 09:50either genetically or using drugs
• 09:52that inhibit DNA polymerases.
• 09:53And when we do that,
• 09:55we totally prevent the transition
• 09:58from S note to S1.
• 10:00And.
• 10:00What we prevent isn't simply the
• 10:02upregulating I population of city 71,
• 10:04which is the marker of this transition,
• 10:06but all of the events that
• 10:08are associated with it,
• 10:10which is the induction activation of
• 10:13the array through transcriptional.
• 10:15Program their research differentiation
• 10:17program.
• 10:20The second thing that we found and I
• 10:23will talk about that a bit more later,
• 10:25running the talk is that S phase at the
• 10:29time of this transition is much shorter
• 10:32than S phase of preceding cycles.
• 10:35OK. And that the actual length of S
• 10:40phase is really only about four hours,
• 10:43which is pretty short for MA million S phase.
• 10:50Now what else is happening at the
• 10:52time of this suite at the time
• 10:55of transition from S note to S1,
• 10:58it turns out that there is a time
• 11:00when we see reconfiguration of
• 11:02chromating at the beta globin locus.
• 11:05We see a change in the timing of replication
• 11:07of the locals histone tail modifications.
• 11:10We see a loss in DNA methylation beginning
• 11:13at the time of this switch and more
• 11:16recent work from Dark Hexes Lab done by.
• 11:19Rob Bakery and others have shown
• 11:22that eight acsec and using tiled see,
• 11:26we see either changes in chromatin
• 11:29Accessibility promoter enhancer Contacts
• 11:31that begin with this transition,
• 11:33so this is clearly a key
• 11:36developmental switch.
• 11:40I haven't explained a color scheme here.
• 11:44What we think is happening is
• 11:47that CF uer undergoing expansion
• 11:50whilst in the S North subset.
• 11:54And then the very last generation of CFUE
• 11:58starts its life in the S note subset in G1.
• 12:02When it enters this specialized short space,
• 12:06it is at it up. Regulates city 71.
• 12:09And it is at that point that
• 12:12it undergoes commitment.
• 12:14The progeny of DCF.
• 12:15UE will no longer be safe UE.
• 12:17They will be priority through
• 12:19blast in the race for blast that
• 12:22undergo terminal differentiation.
• 12:24So when we asked next is is this
• 12:27CFU E2E TD transition true sweet?
• 12:30So it's all very well and good if
• 12:33we take all of us not cells and all
• 12:37of this one sells and compare them,
• 12:40large differences suggest to switch but
• 12:43is not is a heterogeneous population
• 12:45of cells and by taking all of them
• 12:49together we could be masking incremental
• 12:52changes within this population.
• 12:54The problem with addressing this
• 12:57question was that we really had no
• 13:02reliable way of taking apart this subset.
• 13:05And in fact,
• 13:07the entire trajectory starting
• 13:10with hematopoietic stem cells
• 13:12and ending at this point where
• 13:16terminal differentiation starts,
• 13:18this trajectory was really
• 13:21only partially understood,
• 13:23and so about four years ago the
• 13:27technology of single cell RNA SEQ had
• 13:32advanced massively by microfluidic.
• 13:35Approaches were introduced by
• 13:36a number of labs,
• 13:37including the lab of a long climb.
• 13:40And we were very fortunate in
• 13:42that he agreed to collaborate with
• 13:45us on this question.
• 13:47And so we took kit positive cells
• 13:49from the bone marrow or from fetal
• 13:52liver and we also took kid positive
• 13:54cells from the bone marrow of mice
• 13:57that were injected with Ipoh.
• 13:59Although I will not discuss that here.
• 14:02And we've undertaken single cell RNA
• 14:05sequencing on these projectors and
• 14:08what you're looking at here are two
• 14:11D projections of K nearest neighbor
• 14:14graphs of gene expression in the
• 14:17fetal liver and in the bone marrow.
• 14:21Topologically, these graphs are very similar.
• 14:24Each dot is a single cell,
• 14:27and the proximity of dots suggests
• 14:30a proximity in terms of their
• 14:33transcriptome similarity transcriptomes.
• 14:35And what you can see is that
• 14:38these transcriptomes are form
• 14:40one continuous structure.
• 14:41It's a branching structure.
• 14:43And in the fetal liver and bone marrow,
• 14:46the branches are pretty similar.
• 14:49Except that here we see a very
• 14:52large bulge compared with a much
• 14:54smaller bulge in the marrow.
• 14:55This bulge in fact contains the CFUE,
• 14:58as I will show you.
• 15:02I won't dwell on it today, but.
• 15:06We've used GNU algorithm that was
• 15:09developed by the client laboratory,
• 15:12especially Caleb Weinreb and some
• 15:15Wallach in the client lab called
• 15:18Population Balance analysis.
• 15:20And this algorithm allowed us
• 15:22to assign each cell within this
• 15:25structure with a fate probability.
• 15:28In fact, with a set of seven
• 15:31self check probabilities,
• 15:33which told us what is the probability
• 15:36of each cell to ultimately attain a cell
• 15:40fate in one of these seven branches and that?
• 15:46Really can be the result of our analysis
• 15:48can be collapsed into this structure,
• 15:51which is a hierarchical structure,
• 15:53not unlike the classical
• 15:55structure of hematopoiesis.
• 15:56The main difference is that
• 15:58we don't see discrete stages.
• 16:00We see a continuum which is meant to
• 16:03be represented by this kind of cloud.
• 16:09And one more point that I'd like to
• 16:12make is subsequent subsequent work
• 16:14of the client lab together with Luca
• 16:18Biosca Slab looking at single cell RNA
• 16:20seq of human marrow showed that the
• 16:24structure and topology is obtained
• 16:26from human bone marrow is actually very
• 16:29similar to that of the mouse and in
• 16:32terms of gene expression for each gene.
• 16:36Steam is aro.
• 16:38We see a very similar pattern
• 16:40in the mouse and in the human,
• 16:42which are represented here as mirror images.
• 16:46And so we can conclude that the
• 16:48mouse is a pretty good model for
• 16:51human hematopoiesis in general.
• 16:53Of course, that we know of some
• 16:56very clear differences as well.
• 16:58So now we were in a position to
• 17:01look at the erythroid trajectory,
• 17:03starting with multipotential progenitors
• 17:05in black and continuing along the
• 17:08array thread branch with the color
• 17:10representing every thread fate probability.
• 17:12We can use this probability to align
• 17:16the cells along a linear axis starting
• 17:19with MPP and ending with the end of ETD.
• 17:23And just to see that things look good.
• 17:29You can look at cells that we know our
• 17:32President Multipotential progenitor's
• 17:33like cities 34 gotta one which is
• 17:37expressed by the entire array thread
• 17:40branch and Alpha globin which is induced.
• 17:43Only with the activation of
• 17:47Arethra terminal differentiation.
• 17:49In order to be able to do experiments
• 17:53with transcriptome information we
• 17:55needed a way of learning how to
• 17:58isolate cells from specific regions
• 18:00of our single cell RNA SEQ graph.
• 18:03And so we've developed a fax approach
• 18:06that gives us five populations and then
• 18:09we sorted each of these five populations,
• 18:13repeated the single cell RNA SEQ work,
• 18:16and then projected them onto our.
• 18:19Original map and what you can see
• 18:22and what's relevant to today's talk
• 18:25is that the P1 and P2 subpopulations
• 18:28project pretty cleanly into this
• 18:30very narrow neck at the beginning
• 18:33of the urethra branch and then into
• 18:37this sort of bulge that follows up.
• 18:41And so we now have a way of isolating
• 18:44cells that correspond to these
• 18:46two regions of the graph.
• 18:48And the P5 population is also pretty
• 18:51good at giving us the multipotential
• 18:54progenitor cells right at the
• 18:57beginning of the erythroid branch.
• 18:59So with these three subpopulations,
• 19:02we can isolate cells from the entire.
• 19:06If we throw brunch and so now we're ready to
• 19:12do some assays and we find that P1 and P2.
• 19:18Almost my stroke of luck.
• 19:20Kivas populations at the highly enriched
• 19:25for CFUE. In fact, P1 contains.
• 19:29Almost all of the CFO is some
• 19:32small number also present in P2.
• 19:36And P2 is the only subpopulation that
• 19:40contains BFUE, so P2 is from the neck.
• 19:44Here represents cells with be
• 19:47a few potential.
• 19:48BF uer colonies that are multifocal either.
• 19:53Small bunches of small foci.
• 19:54Deezer called late be a few E and
• 19:57we see them around day four of.
• 20:00Culture or like might contain much
• 20:03larger column they might have might
• 20:06give rise to much larger colonies
• 20:09after about
• 20:10a week or even 10 days.
• 20:12See if you eat, give rise to 1.
• 20:15Focus of colonies that contain
• 20:17around 30 differentiated red cells,
• 20:20about two to three days after plating.
• 20:24OK, so we now have.
• 20:28Pretty complete set of tools
• 20:31to do our investigation.
• 20:33We can look at multipotential
• 20:36progenitors BFUS&CFUS at the
• 20:38transcriptome levels and we've given
• 20:41them transcriptome related names.
• 20:43You can correlate them with faith
• 20:46assays and isolate them by fax.
• 20:48And so we are in a position to ask,
• 20:52are we looking at a true switch when
• 20:56we transition from S Note 2 S one?
• 20:59Is this a few ITA ET transition
• 21:02at truth Switch?
• 21:03And so here we are looking at
• 21:05genes that are differentially
• 21:06expressed during the linear access.
• 21:09The linear suit I'm going from MPP
• 21:12to terminal differentiation and
• 21:14they arrange arrange story in terms
• 21:16of the peak expression along this.
• 21:19Access and without any really
• 21:21fancy analysis you could see that
• 21:24they form kind of three cohorts.
• 21:26There is a cohort of gene expression
• 21:29that happens during a very rapid change.
• 21:32Many streams are being switched on or off.
• 21:36Then we enter a period of relative
• 21:39stability of the ceep progenitors of
• 21:42correspond functionality to see a few E.
• 21:46Jeans and not many genes of
• 21:49turning on or off.
• 21:51Although you can see that there
• 21:53is a progressive slow change
• 21:55and this probably represents an
• 21:57amplification stage where there
• 21:59is little transcriptome change.
• 22:01And then we see.
• 22:05Rapid change or in fact I should say
• 22:07about sharp change from the CFD program
• 22:11to terminal differentiation program.
• 22:13Very few cells expressed genes
• 22:15of both terminal differentiation
• 22:17and sea Fury program.
• 22:18So that tells us that we're looking
• 22:21at a sharp transcriptional switch.
• 22:23So the answer is yes,
• 22:26the transition from this Cepheus
• 22:28Stage 2 terminal differentiation
• 22:29is a sharp transcriptional switch.
• 22:32So what is the context of that switch?
• 22:36And we're in the position to
• 22:38look at that as well.
• 22:40This is a busy slide,
• 22:41but let me take you through it slowly.
• 22:44So if we look at the medial
• 22:46medium panel first in red,
• 22:48we're looking at the expression of CD 71.
• 22:51This is the market we used by
• 22:53fax and we can see that there is
• 22:55a gradual increase in cities of
• 22:5771 throughout the trajectory.
• 22:59But at the time of the switch
• 23:02to terminal differentiation,
• 23:03this becomes a very rapid up regulation,
• 23:05and so the upregulation of CD 71.
• 23:08Which we previously took as a
• 23:10marker of activation of the switch.
• 23:13Acts as a marker of that,
• 23:15also at the single cell RNA level.
• 23:18When we look at either cells of
• 23:21his markers here we're looking at
• 23:24Ipoh receptor expression in blue.
• 23:26EPO receptor is expressed pretty
• 23:29early on in the trajectory in
• 23:31increases gradually subsequently.
• 23:33We can now look at transcription
• 23:36factors and we see in Grey gotta one
• 23:39is high initially and then is downregulated.
• 23:43Gotta sorry got it too in grey.
• 23:47Gotta one is low initially in
• 23:50multipotential parameters and then is
• 23:52expressed induced early in the trajectory.
• 23:55I'm sorry Ann is maintained at pretty
• 23:58high levels throughout the trajectory.
• 24:00Maybe going up a little bit
• 24:03at the time of the switch.
• 24:06Generally speaking,
• 24:07none of the key transcriptional
• 24:10regulators that we know of.
• 24:13Reporters of the timing of
• 24:16the switch from CFUE to ETD.
• 24:19When we look at the cell cycle,
• 24:21however, we see something that
• 24:23does seem to correlate very well
• 24:25with the timing of the switch.
• 24:27So what we're looking at here each
• 24:30each color denotes the average
• 24:32expression of genes in each that are
• 24:36characteristic of each cell cycle phase,
• 24:39either S Phase G,
• 24:412MG1S and so on,
• 24:43and there is very little difference there.
• 24:46Sensually, flat or uninteresting
• 24:48for most of the trajectory.
• 24:50And this really tells us that
• 24:53cells are cycling asynchronously
• 24:55through most of the trajectory.
• 24:58But as we approach the time of the switch,
• 25:01which is this dashed line,
• 25:03you can see the formation of a
• 25:06number of peaks starting with G1,
• 25:08S and then S in red and orange
• 25:11and then G2NG2M.
• 25:13So what we have here in fact
• 25:16is the cell cycle.
• 25:18And the first peak that is formed is S phase.
• 25:23And so it appears that the earliest event
• 25:27at the Switch from Seaview to ET D is
• 25:31marked by cells in S phase of the cycle.
• 25:35So this confirms our earlier functional data.
• 25:38That activation of the TD happens
• 25:42during S phase of the cycle.
• 25:45And So what we asked next is OK.
• 25:49Transcription factors are not good.
• 25:52Taught don't really report
• 25:53the timing of this switch.
• 25:55At least their expression doesn't.
• 25:57It's quite possible that post
• 26:00transcriptional post translational
• 26:01modifications of these do correlate
• 26:03with the timing of this switch,
• 26:05and that's an open question.
• 26:07Um?
• 26:09Can we find something else
• 26:12that might tell us?
• 26:14Something about the timing of the switch.
• 26:17So to do that we went back to the
• 26:20jeans that are expressed during this.
• 26:23See if you E program and we asked
• 26:26whether there are the slow progressive
• 26:29change that happens during this time,
• 26:32which streams are changing during that time?
• 26:35Which teams change their expression
• 26:37in a way that is correlated with
• 26:40progression along suit of time?
• 26:43And when we did that, the top five go.
• 26:48Terms that we got were essentially
• 26:51all to do with DNA replication.
• 26:54The cell cycle, S phase, and so on.
• 26:58And here are some examples.
• 27:01We're looking at cycling
• 27:038 two cycling E1 R&R.
• 27:06Units.
• 27:07Proteins that are associated
• 27:09with the origin of replication.
• 27:11All of these are ramping up their
• 27:15expression throughout the trajectory
• 27:16right through the BFUE&CFU stage
• 27:19and reach a peak at the time of the
• 27:22transcription of switch from CF UE2ET D.
• 27:27Now what does that mean functionally?
• 27:31So to understand the significance of
• 27:34this really quite impressive ramping
• 27:36up in cell cycle X gene expression,
• 27:39we went back to a functional experiment.
• 27:42So here we're looking at the same
• 27:45old experiment where we take a
• 27:48mouse injected with beyond you
• 27:50and then check the cell cycle
• 27:53status and the speed of space.
• 27:56But now we were armed with some more
• 27:59information about early erythropoiesis.
• 28:02We used the slow upregulation of CD 71
• 28:06as a way of measuring sudo time by fax.
• 28:10And we were able to also.
• 28:14Staying for the P1 and P2
• 28:18subpopulations which mark there
• 28:20be a few Ian CF Louise subsets.
• 28:23And so we sort of these cells and
• 28:26looked at the beardi you incorporation
• 28:28in here we're looking at individual
• 28:31cells Bru positive and Bru negative.
• 28:34We arrange them along the CD 71
• 28:37expression suit of time and if I did
• 28:40this sort of time into 14 different
• 28:44Gates 7 seven percentile gates.
• 28:46And then we can look at each of
• 28:50these gates and analyze cell cycle
• 28:52status as well as S phase speed.
• 28:55So the first really quite clear.
• 29:01Finding is that cells in
• 29:03S phase of this cycle.
• 29:05Increased markedly with progression
• 29:06along the earlier we throw trajectory,
• 29:09so maybe 20% of this other INS phase
• 29:11at the early parts of the trajectory,
• 29:14and as we approach this,
• 29:16which essentially all the cells are in
• 29:18space and you could see this right here.
• 29:21So at the time of this which nearly all the
• 29:24cells are in a space where is around here,
• 29:28most of the cells are not.
• 29:31When we look at S phase speed,
• 29:34we see there is there.
• 29:36There is an increment.
• 29:37There is an increase in the
• 29:40speed of West phase early,
• 29:42but then it stays quite stable until
• 29:44the point of the switch to ATD.
• 29:47And so this quite stable speed of essays.
• 29:50In other words,
• 29:52quite stable S faced length
• 29:54can't explain the change in
• 29:56the number of cells in space.
• 29:59And so our interpretation.
• 30:01Is that what's happening is?
• 30:05Shortening in G and in the G1 phase.
• 30:08Of course,
• 30:09this massive increase in the
• 30:11number of S phase cells explains
• 30:14why S phase genes are increased
• 30:16throughout the trajectory.
• 30:21And we suspect that the reason
• 30:23for that is G1 shortening,
• 30:26and so as a proportion the number
• 30:28of cells in S phase increases.
• 30:31The later we are in the Seaview stage
• 30:34as we approach the actual switch.
• 30:38G1 is pretty short.
• 30:40The switch itself we think involves
• 30:43S phase shortening. So.
• 30:48To summarize what I've told you so far.
• 30:51We use single cell RNA sequencing
• 30:54to identify the erythroid
• 30:57developmental trajectory in the mouse.
• 31:01We were able to match specific
• 31:04stages that are identified based on
• 31:08transcriptomes to fax populations
• 31:10and to functional subsets.
• 31:13Functional progenitors based on
• 31:16confirmation potential and using
• 31:19these tools we began to analyze.
• 31:22The factors that control
• 31:24the switch from CFUE to ET.
• 31:26We found that this is a
• 31:29true transcriptional switch.
• 31:31And that there is no real clear change
• 31:35in transcription factor levels that
• 31:39reports the timing of this switch.
• 31:42By contrast, we do see really quite
• 31:46marked changes in the cell cycle.
• 31:49Initially we see a gradual shortening in G1.
• 31:54And at the time of the switch we
• 31:57see a further shortening in S phase.
• 32:01So that at the time of this which
• 32:03we have a very short cell cycle,
• 32:06our measurements indicate that this
• 32:07cell cycle is about 6 hours long,
• 32:09with S phase being only four hours.
• 32:13So.
• 32:14What we next asked his first of all,
• 32:19what regulates this really quite
• 32:21dramatic remodeling of the cell cycle?
• 32:24And the second question is,
• 32:26is this cell cycle remodeling
• 32:29relevant to linear development?
• 32:31Does it play a role in these
• 32:34important cell fate decisions?
• 32:36For example, this switch from CFUE to ETD.
• 32:39Is it correlate or does it determine it?
• 32:45And so to begin to look at that.
• 32:49Just before I get to that,
• 32:52I just wanted to show you some of the
• 32:55expression of cell cycle regulators
• 32:58during the original trajectory and
• 33:01what's quite interesting is that.
• 33:03Our different shifting shape of the
• 33:06cell cycle is probably regulated
• 33:08through changing cell cycle regulators.
• 33:11And of course we have no idea
• 33:14how that happens at this point,
• 33:17but we know that for example,
• 33:19the dominant E2F four transcription factor
• 33:22during most of the trajectory is E2F four,
• 33:26but at the time of the switch
• 33:30to ETD it becomes E2F2.
• 33:33Other regulators, for example,
• 33:35when we look at the cycling dies cycling D2,
• 33:40is present early on.
• 33:42But it is gradually
• 33:44downregulated whilst cycling.
• 33:46D3 takes over at the time of this switch
• 33:49so it is quite possible that these.
• 33:53Part of them.
• 33:55So how do I that is able to generate these
• 34:00quite different shapes of the cell cycle?
• 34:04So the first thing that we asked
• 34:07is what are the mechanisms that
• 34:10underlie this very short space?
• 34:13And there are two ways of
• 34:15getting a short space.
• 34:16One is to have more origins of
• 34:19replication and the other is
• 34:22to have folks that move faster.
• 34:24We know from model organisms that
• 34:27have extremely short as phase.
• 34:30Is that the way they manage to
• 34:33replicate the genome very fast is
• 34:36by having all of the origins of
• 34:38replication firing synchronously,
• 34:41and they're all very closely spaced.
• 34:44So having efficient firing of origins
• 34:48of replication would clearly be one
• 34:51mechanism that has a president.
• 34:54At the time that we were doing this work,
• 34:57we started to collaborate with
• 34:59Nick Rind at UMass Medical School.
• 35:02Who is studies replication in yeast?
• 35:04And we through discussion with him for that.
• 35:08That is likely we will find because
• 35:11there was really no precedent for folks
• 35:14speed being regulated physiologically.
• 35:17But so to approach this question,
• 35:19we learned from the rind.
• 35:21Leiber technique called DNA combing here.
• 35:24You take cells,
• 35:25pulse them with finding analogs.
• 35:27We pass them with two distinct
• 35:30finding analogs that we could stay
• 35:32in with two different colors during
• 35:35the pulse with bio deoxy uridine,
• 35:38we were, we are able to follow.
• 35:42Into a incorporation of Iodo.
• 35:46The that by.
• 35:47Later on stretching DNA fibers
• 35:50along a cover sleep,
• 35:52the green regions are the regions that were
• 35:57replicating at the time of the iota pals.
• 36:00Then we followed that 10 minutes
• 36:02later with a pass of chloro,
• 36:04uh.
• 36:04Deoxy uridine and here we see the
• 36:07red regions are being labeled that
• 36:10this is where Clara gets incorporated
• 36:13and by doing that we get both the
• 36:16speed of the fork and its direction.
• 36:18Ality because we know that green
• 36:21replication proceeds read replication
• 36:23and with that we can place the origins.
• 36:26So here we have a fork moving
• 36:28in One Direction,
• 36:29another fork in another service
• 36:32must be a replication bubble
• 36:34with origin in the center.
• 36:36And with this approach.
• 36:38We discovered it was actually no difference.
• 36:42No significant difference in the
• 36:44distance between origins of replication,
• 36:46but there was a marked difference
• 36:49in the speed of replication Forks.
• 36:52So on average we're looking
• 36:55globally in the genome here.
• 36:59The replication folks in S1
• 37:01move at 50% faster speed than
• 37:05replication folks in S note,
• 37:08and that really entirely accounts for
• 37:12this speed of four S8 shortening.
• 37:17And So what might be regulating that?
• 37:19And is it really relevant to self it?
• 37:23Well, the answer is still not fully clear,
• 37:26but we know of examples where
• 37:28esfe shortening is at least
• 37:30associated with cell fate decisions.
• 37:32Here we're looking at gastrulation,
• 37:34in mammals where we know that
• 37:37there is dramatic space shortening
• 37:39from 7 hours to 2 1/2 hours.
• 37:42We know more recent examples
• 37:45running Yale from Shank Xingguo,
• 37:48where ultrafast cycles.
• 37:52Mark the cells that are most likely
• 37:55two week program into I PS cells,
• 37:58so this is clearly worth following up.
• 38:01So what might be regulating
• 38:04as they shortening?
• 38:06We looked at one key regulator P 57.
• 38:10Keep two. This is a CD K inhibitor.
• 38:16An IT regulates all it inhibits all
• 38:18city case, except I think City K 6.
• 38:22Um? What we found is it that
• 38:25it is present in S, not cells,
• 38:29but is rapidly downregulated in S1.
• 38:32And here you can see that,
• 38:35unusually, it's expressing S phase
• 38:37of those cells rather than in G1,
• 38:40suggesting it play some kind
• 38:42of role in S phase here.
• 38:45Looking at our Western and at Q.
• 38:48PCR, which both indicated the same thing,
• 38:50and so we looked at the P57.
• 38:53Keep two deficient embryos
• 38:55is in the imprinted gene,
• 38:57so we can look at the heterozygous and
• 39:01have essentially a knockout phenotype.
• 39:04And we see that these mice are anemic.
• 39:07They die in the prenatal stage.
• 39:10I have multiple developmental abnormalities.
• 39:12We found that they were anemic.
• 39:14They had fewer cells in the fetal
• 39:17liver and when we looked at the
• 39:20differentiation they had trouble
• 39:22generating differentiated and we
• 39:24throw blasts from the early CF you.
• 39:26So what's going on here Weekly looked
• 39:30thought to look at the S phase.
• 39:33So here we're looking at S
• 39:35phase again in CFUE.
• 39:37It is maintained as along as
• 39:39phase and we in wild type.
• 39:42Projectors see shortening at the
• 39:44time of the switch from C FE2ET D.
• 39:48And here we're looking at RC71
• 39:50so that I'm in the wild type
• 39:53and in knockout littermate and
• 39:55what you can see is that S phase
• 39:59speed is consistently faster.
• 40:01Prematurely fast in the CF,
• 40:03UE of the P57 knockout embryos,
• 40:06so we have a premature shortening of space.
• 40:13When we did DNA combing,
• 40:14we found that the folks were moving
• 40:17faster in their knockout in S not
• 40:20fork speed was already almost as
• 40:22fast as it would be in the wild
• 40:25types of in the water plasma cells.
• 40:28And in the X one of the P57 deficient
• 40:32embryo S1 cells will break,
• 40:34virtually breaking the speed
• 40:35limit on fork speed,
• 40:37and so we have very fast folks.
• 40:40What's the significance of that functionally?
• 40:44Anemia is 1,
• 40:45but why exactly do we get anemia?
• 40:48We didn't find that out until we
• 40:51looked at CF self renewal in the dish.
• 40:55So it turns out that CF UE can
• 41:00undergo self renewal in the dish
• 41:04for quite prolonged periods of time.
• 41:08Up to a month for adult.
• 41:12See a few ehad is documented in the
• 41:16literature in our hands up to about 2 weeks.
• 41:19And this contrasts with CF you,
• 41:21even they differentiate their form rec
• 41:24cells within a matter of two to three days.
• 41:27And what stops a fuse from differentiating
• 41:30it keeps them in itself for in
• 41:33your state are glucocorticoids.
• 41:34And so when we placed glucocorticoid
• 41:3857 knock hard to safely.
• 41:41In this self renewal cocktail.
• 41:44We found that they failed to
• 41:47undergo efficient self renewal.
• 41:49And so that is very likely
• 41:52the reason for the anemia.
• 41:54So for some reason they fail
• 41:57to sell from you,
• 41:58and the reason we can clear when we
• 42:01looked at the expression of P57 in cells
• 42:04in the presence of glucocorticoids.
• 42:07Here we're looking at using Dex,
• 42:09which is a synthetic glucocorticoid,
• 42:12so cells express P57 and then P 57
• 42:14isn't used further by DEX and so it
• 42:17seems that dex and glucocorticoids
• 42:19in general probably work at least
• 42:22in part by inducing P.
• 42:2557.
• 42:25Inhibiting Assface CK activity and
• 42:28that in turn allows a stabilizes
• 42:31and long essays and promotes
• 42:34the safe UE self renewal state.
• 42:37So here we see a connection
• 42:39between along S phase and self
• 42:42renewal or persistence of a
• 42:45particular transcriptional state.
• 42:47Suggesting that maybe a fast S
• 42:51phase is somehow destabilizing
• 42:53to transcriptional program.
• 42:56Now we were able to rescue.
• 42:59The situation by adding
• 43:01to the knockout cells P.
• 43:0457 knockout cells acidic A2 inhibiting
• 43:07drugs so this will reduce CD K
• 43:11activity will inhibit CK activity
• 43:13in S phase cells and you can see
• 43:17that compared to the city 57.
• 43:19Knock ourselves the knockout cells
• 43:22treated with the drug almost completely
• 43:25resume normal self renewal activity.
• 43:30And so, um. You can we have a
• 43:34bit more data here, so yeah,
• 43:37so here we're looking at wild type cells.
• 43:40We can take this paradigm,
• 43:42feather and say, well,
• 43:43OK we have CF uees long essays.
• 43:46Stable self renewal can
• 43:47make it even more stable.
• 43:49Can we enhance the sea of yourself
• 43:52on your potential by adding city
• 43:54K inhibitors to the medium and
• 43:56prolonging S phase even more?
• 43:58And that indeed happens so you
• 44:00can see that compared to control
• 44:02cells undergoing self renewal
• 44:04in just dexamethasone.
• 44:05When we add the city K2 inhibitor with,
• 44:08these cells are completely blocked.
• 44:10They don't up regulator 119.
• 44:13When the S phase is slower and
• 44:16we can amplify them much further,
• 44:19so in red at the cells that have
• 44:23sydicate 2 inhibitors added on so we
• 44:26can amplify the CFL stage even further.
• 44:30And clearly this may have some
• 44:33translational applications.
• 44:34Maybe Syndicate two inhibitors will assist,
• 44:37or perhaps replace glucocorticoids in
• 44:40therapeutic approaches that target the CFUE.
• 44:43But it also for fundamental
• 44:45biology point of view.
• 44:47It tells us that stabilizing and
• 44:50prolonging S phase delays the switch.
• 44:56So I will. I'm running a little
• 44:58bit out of time so I will quickly
• 45:02summarize what we what I've shown
• 45:04you in the second part of the talk.
• 45:07See if you self renewal.
• 45:09Depends on a long space.
• 45:12And when that is.
• 45:15Impaired, for example,
• 45:17in the P57 knockout mouse.
• 45:21There are insufficient cycles of
• 45:22self renewal, and that causes anemia.
• 45:25And we can rescue that and in fact enhance.
• 45:29See if you see few suffering you even
• 45:32in wild type progenitors by inhibiting
• 45:35SDK activity and prolonging essays.
• 45:39So it appears that exercise shortening
• 45:41may be causally related to the switch,
• 45:44although the underlying mechanism
• 45:47of course isn't clear yet.
• 45:50And then in the last few minutes of my talk,
• 45:53I'll take just five minutes to tell you
• 45:57knew story that isn't yet published.
• 46:00Again, that seems to highlight the
• 46:03importance of the cycle in this
• 46:07time in terminal differentiation.
• 46:09So we know that E praeceptor becomes
• 46:11essential during terminal differentiation.
• 46:13Although it begins to be expressed much
• 46:17earlier in earlier with the Preseas.
• 46:20And with that,
• 46:21the power sector I've shown you earlier,
• 46:23we have no cells in terminal differentiation.
• 46:26And so we asked.
• 46:27And this is work by Daniel Hidalgo in my lab.
• 46:31We asked whether.
• 46:35The emperor sector has added
• 46:36functions other than survival
• 46:38during terminal differentiation,
• 46:40and two answer that we developed a
• 46:42genetic model in which we take the
• 46:45perceptive nokut fetal livers and
• 46:48introduce back either the EPO receptor
• 46:50obiesie ELEX to stop them from dying.
• 46:53And with this model system we
• 46:55were able to see that in fact
• 46:57you can get full differentiation
• 46:59without any equal receptor at all,
• 47:01as long as you keep the cells from dying by.
• 47:06D. Transgenic expression of BCLX.
• 47:10However, there were various abnormalities,
• 47:11and the biggest one was that the
• 47:14Sea Fury colonies that were formed
• 47:16were much smaller than the area,
• 47:19which is much smaller.
• 47:22And the second finding was that
• 47:24S phase wasn't as fast,
• 47:26so it was still pretty fast,
• 47:29but not as fast as in cells that
• 47:32were expressing the E prospectors.
• 47:35So clearly E.
• 47:36Praeceptor can further accelerate
• 47:38space speed.
• 47:39When we look at cell growth,
• 47:41this is in vitro.
• 47:44And see that cells expressing the ape
• 47:47receptor grow much faster than cells
• 47:50expressing BCLX and the doubling time.
• 47:53Let's look at control cells.
• 47:55That doubling time is only six hours in
• 47:58our cells that express the equal sector,
• 48:00but it climbs to a towers in cells that
• 48:04don't have a protective signaling.
• 48:06We were fortunate to be able to
• 48:09collaborate with Sean James Goose Lab,
• 48:11who developed a beautiful Reporter mice.
• 48:14This mouse reports the length of the
• 48:17cell cycle using a Fusion protein.
• 48:20H2B fluorescence timer Fusion.
• 48:23These Fusion is fluorescent blue
• 48:25when it is first synthesized and
• 48:28then becomes a fluoresces red
• 48:29about an hour or two later.
• 48:32And so cells that have a short cycle IBB
• 48:36lower than cells that have a longer cycle.
• 48:40And so with her lab,
• 48:42we injected mice with either Ipoh or Saline.
• 48:45And found that two mice injected
• 48:48with Saline here in blue.
• 48:50Um?
• 48:52Here we're looking at the ratio
• 48:54of blue to red fluorescence.
• 48:56We see a shift in that ratio when we look
• 48:59at two mice that are injected with people.
• 49:03And here we're looking at a specific
• 49:05erythroblast earlier Race for Life stage,
• 49:07and we can look at a number of our
• 49:10way through glass stages and at
• 49:12each stage we see a clear difference
• 49:14in cell cycle length.
• 49:16So it seems that if receptor
• 49:18can shorten space even further,
• 49:20and in fact shorten the cycle.
• 49:23I'm going to skip this next part,
• 49:26which very briefly,
• 49:27you would think that if a preceptor
• 49:30drives as shortest cycle and more
• 49:33numerous cycles in terminal differentiation,
• 49:35the red cells that would result
• 49:38would be smaller.
• 49:39But in fact we find exactly the opposite.
• 49:42We find that the rattles are formed at
• 49:46larger and I won't go through the data,
• 49:49but we see a larger diameter in cells that.
• 49:53Experienced high ipho and so
• 49:56that's a sort of paradox.
• 49:58This is interesting in its own right.
• 50:01I'm.
• 50:03And so I will summarize
• 50:04what I've told you so far.
• 50:07And summarize my talk.
• 50:08What we find is that during
• 50:10the arethra developmental trajectory,
• 50:13the cell cycle takes up a
• 50:16number of different shapes.
• 50:17If you like, it is long,
• 50:20early in the trajectory with
• 50:23along for a space and along G1.
• 50:26During the gradual progression
• 50:28through to see if you re staged
• 50:31towards the switch to ETD we have
• 50:35initially gradual shortening of G1.
• 50:37And sorry, gradual shortening of D1.
• 50:40And then at the time of this which we have.
• 50:44An abrupt shortening of essays,
• 50:46the shortening West phase is the result
• 50:49of downregulation of P57 Kip too,
• 50:51which is acidic Lee,
• 50:53two inhibitor.
• 50:53It inhibits S phase city K activity
• 50:56and that leads to an increase in
• 51:00the speed of replication Forks.
• 51:02The long ass face in the CFG stage
• 51:06is critical for the stability of that
• 51:09stage in it for its self renewal,
• 51:12and it appears that glucocorticoids
• 51:15utilize that by enhancing expression
• 51:18of of the silicate to inhibit P 57 and
• 51:22prolonging the CFO is suffering you'll stage.
• 51:25And we may be able to use that
• 51:27therapeutically with silicate
• 51:29two inhibitors as well.
• 51:30Once we cross this this late
• 51:33into terminal differentiation,
• 51:34the initial cycles are very short.
• 51:36In fact I forgot to mention this cycles
• 51:40of the earlier throw blasts as some
• 51:43of this shortest in the bone marrow.
• 51:47And these can be even further
• 51:51shorter when we.
• 51:53Use that when we simulate these cells.
• 51:56With people so at high levels of people
• 51:59which we would find in stress situations,
• 52:03high altitude or disease or bleeding.
• 52:06Cycles become even shorter.
• 52:09And that in itself is raises
• 52:12the question of why is that?
• 52:15And I did not have time to discuss that,
• 52:20but all the work shows that the
• 52:23fast cycles of earlier reefer blasts
• 52:26contribute to rapid DNA demethylation,
• 52:29and that interns assist the speed
• 52:32of the ATD transcriptional program.
• 52:35So it's possible that that might
• 52:38be the reason why.
• 52:40This takes place here,
• 52:41but of course we don't know that for sure.
• 52:45So I'd like to thank the people that
• 52:49did the work and these people in my lab.
• 52:55Including include US Warrior, Sami, Nathan.
• 52:57Better bear to see who did a lot
• 53:00of the single cell RNA SEQ work.
• 53:03Melinda Futron who worked in the DNA
• 53:07combing together with young Kwang
• 53:09who did all the work on P57 and
• 53:11Daniel Hidalgo who did the work on
• 53:14the ape receptor signaling and our
• 53:17collaborators were very fortunate
• 53:19in our collaborators and old clients
• 53:21lab with a single cell RNA SEQ.
• 53:23Necrime at UMass Medical School.
• 53:26Who helped us with the DNA combing
• 53:29and shanting Google in Yale who
• 53:32had been a great colleague,
• 53:34was also interested in the cell cycle and
• 53:38we've collaborated with her transgenic mouse.
• 53:41So thank you.
• 53:46Thank you very much for a great talk.
• 53:48We have two questions for
• 53:50you in the Q&A session.
• 53:51I don't know if you can see them wrong,
• 53:54but I can read them to the group.
• 53:57The first is from Doctor Liu says great talk.
• 54:00Any speculation in how CD K2 and
• 54:02P57 regulate fork speed in S phase.
• 54:05We would like to know that yeah,
• 54:07so we don't know there are many.