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Cell Motility and the Cytoskeleton

Transcript of Part 2: Mechanics and Dynamics of Rapid Cell Motility

00:07.2	Hello.  I'm Julie Theriot.					
00:10.0	I'm a professor at Stanford University.					
00:12.2	And for the second part of my					
00:14.0	iBioSeminars presentation today,					
00:15.2	I'd like to delve into the details					
00:17.1	of the mechanics and dynamics					
00:19.1	of rapid cell motility.					
00:21.0	Now, to get us started here,					
00:23.0	we see two images of a particular kind of					
00:26.0	very rapidly moving cell					
00:27.1	that comes from the skin of fish, called a keratocyte.					
00:29.3	Over on the left, we have a fixed cell					
00:31.2	that's been labeled for filamentous actin,					
00:33.2	so you can see the distribution					
00:35.1	of the actin cytoskeleton throughout the cell.					
00:38.1	On the right, we have a video image					
00:40.3	of the same kind of cell moving					
00:42.1	in the same direction					
00:44.1	that the fixed cell was at the time that it was					
00:46.1	frozen with formaldehyde.					
00:47.3	And what I'd like to talk about particularly					
00:49.2	is the way that all of the different molecular machines					
00:51.3	that have to operate in the context					
00:53.2	of a moving cell					
00:55.0	are able to coordinate with one another					
00:57.0	in order to get this incredibly smooth and elegant					
00:59.1	gliding motion					
01:00.2	that you see in rapidly moving cells.					
01:03.1	So, focusing a little bit on the details					
01:06.0	of these molecular machines...					
01:07.2	these are things that have actually been intensively studied					
01:10.0	by biochemists and cell biologists					
01:11.1	for many decades,					
01:12.2	and at this point we're pretty familiar					
01:14.3	with many of the proteins that are necessary					
01:17.1	and, to some extent even maybe sufficient,					
01:19.1	for generating the forces and dynamics					
01:21.3	that we see associated with cell motility.					
01:24.1	And in general, for large-scale cell biological processes					
01:26.2	like motility,					
01:28.0	the proteins within the cell					
01:29.2	that are responsible for that kind of behavior					
01:31.2	arrange themselves into nanomachines					
01:34.3	where a number of different proteins will work together.					
01:37.2	Now, one nanomachine that's very important					
01:39.2	in cell motility					
01:41.0	is the assembly of branched actin structures					
01:42.2	at the leading edge of a motile cell,					
01:45.1	and in the first part of this presentation					
01:48.0	I talked in some detail					
01:50.2	about how these different components have been identified					
01:52.2	and how they're thought to work together.					
01:54.2	But this particular little nanomachine					
01:56.1	of growing actin filaments					
01:57.3	pushing against the membrane r					
01:59.2	eally only operates					
02:01.1	in this very front part of the cell,					
02:02.3	just a few microns back from the plasma membrane					
02:04.2	at the very leading edge.					
02:07.1	Another nanomachine that's also been quite intensively studied					
02:09.2	and is very important for motility					
02:11.1	is shown here.					
02:12.2	This is the adhesion that actually binds the cell to the substrate,					
02:16.1	enabling it to generate traction					
02:18.2	so that it can move itself forward,					
02:20.1	and here too a lot of the protein components have been identified,					
02:23.2	and in this particularly beautiful example					
02:25.1	from Clare Waterman's lab					
02:27.0	even the spatial orientation of all the different components					
02:29.1	have been very carefully measured					
02:31.0	with respect to one another.					
02:33.0	But this particular nanomachine					
02:34.2	that makes this well-organized adhesion					
02:36.2	really operates only in, again,					
02:38.2	a very small zone right at the back of the cell.					
02:41.0	And in order to understand					
02:42.2	the overall process of cell motility...					
02:44.1	when the cell is moving forward,					
02:46.0	it's incredible how well all of these things					
02:48.1	seem to be coordinated with one another.					
02:50.0	The cell looks like it's					
02:52.0	gliding over the substrate without changing shape,					
02:53.3	even though it's got to be assembling actin filaments like mad					
02:57.1	at the leading edge in order to push that membrane forward,					
02:59.1	and then it's got to be building and then disassembling					
03:01.2	the adhesions at the rear.					
03:03.0	All of these things have to be coordinated					
03:04.3	to happen at the same pace,					
03:06.2	so that the left side of the cell					
03:08.1	moves at the same rate as the right side of the cell					
03:10.0	so it can go straight,					
03:11.2	so that the front extends					
03:13.2	at exactly the same rate that the back retracts					
03:15.0	so that it can appear to move forward					
03:16.2	without changing its size.					
03:18.2	So it's a really fundamental and interesting question, I think,					
03:21.3	about how all of these different nanomachines					
03:23.1	can coordinate with one another					
03:25.2	over the entire span of the cell,					
03:27.0	which is tens of microns across,					
03:29.0	so many of orders of magnitude larger					
03:31.2	than, certainly, the individual proteins					
03:33.0	that make up the machine,					
03:34.1	but even any of these individual assemblies on their own.					
03:37.3	Now, in order to address these kinds of questions					
03:40.2	about how you get large-scale coordination					
03:41.3	in moving cells,					
03:43.0	we've taken a lot of advantage					
03:44.2	of these fish skin cells,					
03:46.0	so I'd just like to give you a bit of background					
03:47.1	about where they come from					
03:48.2	and how we isolate them.					
03:50.1	It turns out that pretty much all fish					
03:52.1	and many other amphibians					
03:53.2	have a bilayered epidermis,					
03:55.2	and the basal layer of that epidermis					
03:58.1	is made up of these cells					
04:00.1	that seem to be specialized					
04:01.2	for very rapid wound healing.					
04:03.2	So in the context of a fish,					
04:05.0	when there are scales					
04:06.3	coming out of the flank of the fish,					
04:08.2	the epidermis actually wraps around the scale,					
04:12.0	so if you go in with a pair of blunt forceps					
04:13.3	and pluck a scale off of a fish					
04:16.1	and then put it in culture,					
04:17.2	the scale comes along with just a little bit of skin					
04:20.1	right along the edge.					
04:21.2	Now, the fish is not happy about this,					
04:23.2	but it can grow a new scale,					
04:24.3	and actually turning over the scales					
04:26.1	is part of its normal skin regenerative process,					
04:29.2	so it doesn't cause any significant damage.					
04:32.1	But in the meantime, in culture,					
04:33.2	now we have this scale					
04:35.0	with a little bit of skin that's just wrapped around the tip of it,					
04:36.2	and the cells at the edge					
04:38.3	of that little bit of tissue					
04:40.1	essentially think that the surface of the fish					
04:42.1	has been wounded,					
04:43.3	and so their response					
04:45.1	is to try to start crawling outward					
04:47.0	to close that gap,					
04:48.2	and so you can see here,					
04:50.0	both at the bottom and at the top of this particular scale,					
04:53.0	these big clumps of cells					
04:54.2	that start coming off first as epithelial sheets					
04:56.3	and then eventually break up to make					
04:59.0	all these little individual cells that seem to go					
05:01.1	buzzing around more or less on their own.					
05:03.1	Now, here we can look at that same process					
05:04.3	at higher magnification,					
05:06.2	here at the edge of a sheet					
05:08.0	as if first starts coming off,					
05:09.2	and then here, again,					
05:11.0	this is what the isolated cells look like					
05:12.2	once they break away from that epithelium.					
05:14.2	And I hope you can appreciate					
05:16.0	from looking at these movies					
05:17.2	why these cells are such a spectacular model system					
05:19.1	for studying the mechanics of cell motility.					
05:21.2	They move extremely fast.					
05:23.1	They are among the fastest animal cells that are known.					
05:26.1	And they also have this very characteristic,					
05:28.1	stereotyped geometry,					
05:30.0	which is very well illustrated by the cell over here.					
05:32.1	It has a very large, flat,					
05:35.1	broad lamellipodium, which is its motile organ,					
05:37.2	and then it carries all the rest of its organelles,					
05:40.0	its nucleus, its Golgi apparatus,					
05:41.2	even all its microtubules,					
05:43.1	it carries in this little package of a cell body					
05:45.3	that it just keeps right behind it.					
05:48.2	The movement is very fast,					
05:50.0	the movement is very persistent,					
05:51.2	the movement is essentially unidirectional					
05:53.1	- that is, they don't really have a very strong tendency					
05:55.0	to change.					
05:56.1	So they're essentially moving at steady state.					
05:59.1	The fact that the movement is so regular					
06:01.0	and is so stereotyped					
06:02.2	makes it very good for biophysical analyses					
06:04.1	of the kind that I'm going to be delving into today.					
06:08.2	This shows you a little bit more detail					
06:10.2	about how the cytoskeleton is organized in these particular cells,					
06:13.1	and in this beautiful					
06:15.1	structured illumination micrograph					
06:16.3	taken by my student Sunny Lou,					
06:18.2	you can see the distribution of actin filaments, shown in green,					
06:21.1	myosin-II filaments, that is, contractile myosin, shown in red,					
06:25.2	and we're going to come back to the role of myosin					
06:27.1	in this coordination quite a lot.					
06:29.2	And then, also, you can see labeled in blue					
06:31.2	the focal adhesions					
06:33.1	that are adhering the cell to its substrate.					
06:35.2	And diagrammatically,					
06:37.1	shown down here looking at the cell from the top,					
06:39.3	you can see the actin filament branched network					
06:42.1	is primarily oriented towards the front of the cell					
06:45.2	and then in the back of the cell,					
06:47.1	down here at the bottom,					
06:48.2	you can see the filaments have become rearranged					
06:50.1	to form these parallel bundles					
06:51.3	that are being organized by the myosin.					
06:54.1	Now, if we take a cross-section					
06:55.3	through one of these cells and look at it sideways,					
06:58.1	it looks like a baseball cap,					
06:59.2	where the lamellipodium is very, very thin and flat,					
07:02.2	only about 200 nanometers from top to bottom,					
07:05.0	and the the cell body can rise up several microns high.					
07:11.0	As these cells move forward,					
07:12.1	they follow the same general steps					
07:14.1	of actin-based cell motility					
07:15.2	that are shared by many other motile animal cells					
07:18.1	and also a large number of					
07:20.0	eukaryotic unicellular organisms,					
07:21.2	such as amoeba.					
07:23.1	Overall, the first thing that has to happen					
07:25.2	is the cell has to establish polarity,					
07:27.2	that is, it has to distinguish its front from its back.					
07:30.0	And then it has to be able extend the leading edge,					
07:32.1	and in this cell,					
07:33.2	as in many other motile cells,					
07:35.1	the force for that extension					
07:37.0	is thought to be driven by actin polymerization itself.					
07:40.1	As it's extending the new leading edge,					
07:42.0	it needs to form new adhesions to its substrate,					
07:45.1	and at the same time be able to contract its rear,					
07:49.0	to bring the cell body forward,					
07:51.2	and then retract and disassemble					
07:53.2	the adhesions that are at the back.					
07:57.3	One of the fun things about keratocytes					
08:00.2	is it's actually possible to demonstrate in these cells					
08:02.2	that all of the components necessary					
08:04.2	for that whole cycle of motility					
08:06.1	are contained only in the lamellipodium					
08:09.0	- you don't actually need any contributions from the cell body.					
08:11.2	And that was first proved in this really classic					
08:14.1	1984 experiment by Ursula Euteneuer and Manfred Schliwa,					
08:18.0	where they sliced little bits					
08:20.2	off of the lamellipodium of a keratocyte,					
08:22.2	leaving the cell body behind,					
08:24.1	and were able to see that those small fragments					
08:26.1	of the keratocyte lamellipodium					
08:27.3	were able to continue to translocate on their own,					
08:30.2	and move at just about the same speed					
08:32.1	and just about as persistently					
08:34.2	as the whole cell was when it was intact.					
08:38.0	And this movie shows a modern reenactment of that experiment					
08:40.2	that was done by my student Erin Barnhart.					
08:42.2	Here you see a fragment that's been					
08:45.0	isolated away from its cell body					
08:46.2	that's nothing but lamellipodium,					
08:48.3	with all of these dynamic cytoskeletal structures inside of it.					
08:51.1	And when the movie plays you can see					
08:53.2	it's crawling along very nicely,					
08:54.2	it's got a clear front and a clear rear.					
08:56.2	It's about to crawl over a little piece of schmutz on the coverslip					
08:59.1	that actually is going to separate					
09:02.0	this crawling lamellipodial fragment into two bits.					
09:05.1	The membrane connection between them resolves					
09:07.0	and they're both able to crawl off on their own,					
09:09.1	until they eventually get sliced into some unit					
09:11.2	that's too small to movie.					
09:13.3	So, with this system					
09:15.2	we have favorable geometry					
09:17.0	-- it's very, very simple, very reproducible from one cell to another --					
09:19.2	and we also have a fairly simple self-contained system					
09:22.0	where we know that it's only the					
09:24.2	components of the lamellipodium					
09:26.1	that are necessary for persisten motility.					
09:28.2	So, from analyzing the behavior of these cells					
09:31.2	over many years,					
09:33.0	my group has been able to identify and specifically					
09:35.1	measure the contributions of all of the					
09:38.1	different force-generating elements					
09:40.0	that help the cell to move,					
09:41.2	and those are all illustrated here.					
09:43.3	At the leading edge, we have actin polymerization,					
09:46.1	that's shown in red,					
09:47.2	which pushes the membrane outward,					
09:49.1	and that polymerization is actually opposed					
09:51.2	by tension in the plane of the membrane.					
09:54.1	And that tension serves					
09:55.3	both to act as the barrier					
09:58.0	that the growth of the actin filament pushes against,					
10:00.2	and also, in fact,					
10:02.0	helps to coordinate the motion					
10:04.2	over the entire surface of the cell,					
10:06.1	as we'll see in a little bit more detail.					
10:08.1	Now, there's also adhesions that have to contribute,					
10:12.0	and those adhesions are assembled in the front					
10:14.0	and then disassembled in the back.					
10:16.1	And then there's contractile forces that are driven by myosin,					
10:18.2	primarily acting at the back.					
10:21.0	Because that myosin contraction is happening					
10:23.1	at the back and squeezing the cytoskeleton inward,					
10:25.2	that actually creates a forward					
10:27.3	hydrodynamic fluid flow					
10:29.1	that squirts fluid through the meshwork of the lamellipodium					
10:32.3	to deliver components up to the front of the leading edge.					
10:36.1	Now, as I said, we've been able to measure					
10:38.2	the quantitative contributions of each of these different forces					
10:40.3	within the context of this very simple kind of motile cell,					
10:44.0	and what I'd like to do over the next few minutes					
10:45.2	is share with you a couple of highlights of things					
10:48.1	that we've learned					
10:49.2	that are somewhat surprising in retrospect					
10:51.1	as to how this coordination is able to work					
10:53.1	over such a large scale.					
10:56.0	So, in order to make these kind of measurements,					
10:57.2	we've had to develop methods					
10:59.3	both for measuring behaviors of the cells very precisely,					
11:02.3	and also methods for perturbing the behaviors of the cells					
11:05.2	so that we could understand what aspects					
11:07.3	were dependent on what other aspects.					
11:09.3	So, one example of a kind of measurement that we can make,					
11:12.3	shown here in a movie from Cyrus Wilson,					
11:16.0	is tracking of the overall motion of the actin network					
11:20.0	using a technique called speckle microscopy					
11:22.2	that was originally developed by Clare Waterman.					
11:24.2	And in this technique,					
11:26.1	the cells are electroporated with a small amount					
11:28.2	of a fluorescent dye that binds to the actin filaments,					
11:31.0	but a sufficiently small amount that					
11:33.0	rather than labeling the whole cell uniformly					
11:35.1	you instead see this little speckly, textured pattern.					
11:38.2	And then if we take the movies					
11:40.0	as the come off the microscope,					
11:41.2	which is what you see up top,					
11:43.2	and then convert them into a different frame of reference,					
11:47.1	where instead of looking at the cell in the lab frame of reference,					
11:50.0	we now translate everything					
11:52.2	as if the cell had a GoPro camera attached to its head,					
11:55.2	and we're looking just right down at the cell itself					
11:58.1	from its own point of view.					
12:00.0	Then you can see, now, quite a bit more detail in terms of...					
12:03.2	both in phase contrast and then with this fluorescent speckle microscopy,					
12:06.1	how everything inside the cell is moving.					
12:08.1	So, looking at the fluorescent speckles,					
12:10.0	I hope you can now appreciate					
12:11.2	that the whole actin network is sort of raining downwards					
12:14.1	from the front towards the back of the cell					
12:16.1	in the cell's frame of reference,					
12:18.1	and is also being gathered inwards on the side,					
12:20.1	down at the back here,					
12:21.2	where the myosin is able to contract it.					
12:24.1	Now, once we can do that frame of reference shift					
12:26.3	and look at things from the cell's point of view,					
12:28.3	Cyrus Wilson was able to work together with					
12:31.3	Gaudenz Danuser and people in his lab,					
12:34.0	including Lin Ji,					
12:35.2	to develop quantitative methods for					
12:37.3	measuring the flow of all of this material					
12:39.3	in the lamellipodium very precisely,					
12:41.2	and was able to map, overall,					
12:44.0	how the motion of these particles					
12:45.2	depend on the location inside of the cell.					
12:47.2	So, here from the lab frame of reference,					
12:49.2	what you can see is that the motion of the particles					
12:51.2	with respect to the substrate is actually very little,					
12:54.3	that is, the actin is actually pretty stationary					
12:56.2	with respect to the glass that the cell is crawling over,					
12:59.1	except at the very back where you see this massive					
13:02.0	inward sweeping driven by myosin.					
13:03.3	However, if you look from the cell's point of view,					
13:06.0	you see there's a low of flux,					
13:08.0	a lot of turnover of constantly treadmilling actin network,					
13:11.2	where it's assembling at the front					
13:13.1	and then disassembling under the cell body.					
13:17.0	So, in order to try to understand this process					
13:18.3	of assembly and disassembly a little bit better,					
13:21.0	we also wanted to be able to					
13:22.2	manipulate the behaviors of the cells,					
13:24.1	to perturb them so that we could look at					
13:26.1	how they responded to changes in their environments.					
13:28.2	And one kind of perturbation					
13:30.1	that was actually very informative					
13:32.0	for understanding how these things couple together					
13:33.2	was worked out by Erin Barnhart,					
13:35.2	specifically where she was able to					
13:37.2	change the degree of adhesivity,					
13:39.2	or the degree of stickiness,					
13:41.1	of the substrate that the cells were crawling over.					
13:43.2	And what she found is that when cells					
13:45.3	are on a sort of moderately sticky substrate,					
13:47.1	they're able to move exactly the same way					
13:49.1	that they would on glass					
13:51.1	or in fact on the surface of an aminal.					
13:53.2	When they're put on substrates that were less sticky,					
13:55.2	so, ones that were more slippery,					
13:57.3	you can see the cells actually change shape					
13:59.2	#NAME?					
14:01.0	and you can see the accumulation of these characteristic					
14:03.1	pleats in their lamellipodium,					
14:04.3	where the inward flow of the actin					
14:06.2	is now actually faster than the motion of the cell,					
14:09.1	so it's really spinning its wheels					
14:11.1	because it can't quite get a grip on its surface.					
14:14.1	Now, most interestingly, I think,					
14:16.1	when they're put on high adhesion substrates,					
14:18.1	their behavior changes very dramatically,					
14:20.1	and instead of now having this steady state motion					
14:23.0	where they glide forward uniformly,					
14:24.3	they now do this completely crazy thing					
14:26.1	of putting out small bits of lamellipodium					
14:28.0	that seem to sweep sideways.					
14:30.3	And we're in the process of trying to figure out					
14:33.0	how all of these different things work,					
14:34.1	but I hope you can appreciate that even this					
14:36.3	very, very simple motile cell					
14:39.2	that seems like, you know, sort of the stripped down,					
14:41.0	minimalized, like, soapbox derby version of a motile cell,					
14:44.0	even this is able to extremely					
14:46.1	expand its behaviors depending on cues					
14:48.3	that it's getting from the environment,					
14:50.1	in this particular case,					
14:51.2	mechanical cues in the form of the stickiness of the substrate.					
14:56.3	So, the several examples					
14:59.0	that I want to tell you about					
15:00.3	mostly have to do with surprising roles for myosin.					
15:03.2	Now, myosin, of course,					
15:05.0	we're mostly familiar with in the context of skeletal muscle,					
15:07.2	where it's able to contract sarcomeres					
15:09.3	by sliding stable arrays of actin filaments					
15:12.1	relative to one another.					
15:14.2	Myosin in non-muscle cells,					
15:16.0	myosin II in non-muscle cells,					
15:17.2	also acts as a contractile protein,					
15:20.1	and its assembly is regulated,					
15:22.1	so the monomeric state of the myosin					
15:25.0	in non-muscle cells					
15:26.2	is folded up on itself,					
15:28.1	and then when it receives an appropriate signal,					
15:30.2	the phosphorylation of the					
15:34.1	regulatory light chains on myosin					
15:35.3	enables it to extend outwards					
15:37.3	so that it can then assemble into bipolar thick filaments					
15:39.2	that are much more similar to the organization inside of muscle.					
15:42.2	And so we look at the myosin in keratocytes...					
15:45.1	what you can see is there's very little myosin at the front,					
15:48.1	where the actin is actively polymerizing,					
15:50.2	and instead there's actually quite a lot of myosin					
15:52.1	right at the back,					
15:53.2	and in particular it's in these very bright spots					
15:55.2	right on either side of the cell body.					
15:59.0	Okay, so bearing all that in mind,					
16:00.2	now let's go back to this question of assembly and disassembly.					
16:03.2	One of the things we're able, now, to measure,					
16:06.0	that we can track the motion of the actin					
16:07.2	and know where all these other elements are located,					
16:09.3	is Cyrus was able to actually figure out					
16:12.1	how to make a map of,					
16:14.0	quantitatively,					
16:15.2	how much assembly and disassembly of the actin cytoskeleton					
16:17.2	takes place over the context of the whole cell.					
16:20.1	And what he found was that the assembly					
16:22.1	is very much biased towards the leading edge,					
16:24.1	specifically right in the middle of the front of the leading edge,					
16:26.3	which is very much what we'd expect,					
16:28.3	but the disassembly, unexpectedly,					
16:31.0	was found in these two very intense spots					
16:33.3	right on either side of the cell body.					
16:36.0	And Cyrus recognized that					
16:38.2	those locations were actually					
16:40.1	very similar to the locations where we found myosin.					
16:43.1	Now, we can also look at the distribution					
16:45.0	of mysoin II in these cells.					
16:46.2	Here, using a cell that's been transfected					
16:48.2	with myosin light chain carrying YFP.					
16:51.1	And now, in the cell frame of reference,					
16:53.1	you can actually see the motion of these little speckles,					
16:55.3	which now are mini-filaments of myosin,					
16:58.3	that is, bipolar filaments that have been assembled.					
17:01.2	And what you can see is they seem to					
17:04.0	stick onto the actin network					
17:05.2	and then they rain backwards					
17:07.1	towards the back of the cell body,					
17:09.1	essentially riding on the actin network					
17:11.1	until you get right all the way to the back,					
17:13.1	where they then start forming these contractile cables,					
17:15.2	pulling in the actin network					
17:17.0	and making these bundles that go from one side to the other.					
17:20.1	Now, it's suggestive that the spatial distribution of myosin II in these cells					
17:26.3	is exactly the same as the foci of disassembly,					
17:30.0	and we can also inhibit disassembly of actin in these cells,					
17:34.1	for example, by inhibiting the motor activity of myosin.					
17:36.2	So, we hypothesized that					
17:38.3	the myosin itself is actually contributing					
17:40.2	to the disassembly of the actin cytoskeleton					
17:42.3	by buckling and breaking and ripping apart the actin filaments					
17:46.3	using, directly, its force-generating capabilities.					
17:49.1	And one of the strongest pieces of evidence					
17:50.3	in favor of that hypothesis					
17:52.2	is this very nice experiment done by Mark Tsuchida,					
17:55.1	where instead of using moving living cells,					
17:58.1	he used extracted cytoskeletons.					
18:00.2	So, if you take a keratocyte					
18:02.3	as it's crawling across a substrate					
18:04.1	and then sneak up on it with a little bit of detergent,					
18:06.2	you can get the membrane to dissociate,					
18:08.2	leaving behind only the insoluble parts of the cytoskeleton,					
18:12.0	so, the assembled actin filaments,					
18:13.2	whatever actin binding proteins are bound to them,					
18:17.0	but having now gotten rid of all soluble components,					
18:19.1	including actin monomers, ATP, everything else.					
18:24.2	Mark was then able to label those extracted cytoskeletons with phalloidin					
18:28.1	to see where the actin filaments were,					
18:30.1	and then add back ATP					
18:32.1	to those extracted cytoskeletons.					
18:34.0	That added ATP was able to then					
18:36.2	activate the myosins that were left behind,					
18:38.2	so he could see if,					
18:40.0	in this sort-of semi in vitro environment,					
18:42.1	myosin activity could actually					
18:44.2	drive destruction of the actin filament network.					
18:47.1	And so that's what you're going to see in this movie					
18:49.0	#NAME?					
18:51.2	When the movie starts to play,					
18:53.2	the ATP is going to be added, and you can see the network					
18:55.3	just melted right in the back,					
18:57.2	right where the myosin is located.					
18:59.1	And you can also see that by comparing					
19:00.2	this before and after shot,					
19:02.0	where the blue shows the places where					
19:04.0	the actin network disappeared					
19:05.2	when the myosin was activated.					
19:07.1	So, although we normally think of myosin					
19:09.0	as actually contributing to contraction,					
19:11.1	in this context, at least,					
19:12.3	it seems like one of its more important functions					
19:14.1	is destroying the actin network					
19:16.1	when it gets to the back of the cell.					
19:19.1	So, putting that together,					
19:21.1	we came up with this idea for					
19:23.2	myosin driving overall network treadmilling in the lamellipodium,					
19:27.1	as illustrated here,					
19:28.3	where initially, towards the front,					
19:30.3	there's very little myosin in the network,					
19:33.1	it's hard for the myosin mini-filaments					
19:34.2	to diffuse through the network,					
19:36.1	as it's actively assembling and					
19:38.0	essentially pushing everything backwards,					
19:39.2	but a few fo them get ahold of the filaments,					
19:41.0	and then as they start contracting					
19:42.2	they start rearranging the actin filaments					
19:44.1	to form more parallel structures					
19:45.3	that are of more favorable geometry for force generation by myosin.					
19:49.2	After that goes on for a while,					
19:51.0	by the time you get to the back of the cell,					
19:52.2	the actin is now all in parallel bundles					
19:55.0	rather than a dendritic network,					
19:56.2	and the high concentration of myosin					
19:58.1	that's able to accumulate there over time					
20:00.1	is enough to rip that network apart.					
20:02.3	So, overall, we think that's a major mechanism					
20:05.1	for determining what the distance is					
20:07.1	from the front of the cell to the back of the cell.					
20:08.2	It's just determined by how much time it takes					
20:11.0	for myosin to incorporate,					
20:12.2	and for myosin to destroy the network.					
20:16.0	Now, so far, I've been talking about keratocytes					
20:19.1	as if they're all exactly identical,					
20:20.3	and certainly that's one of the useful things about them					
20:23.0	is that they're similar, but,					
20:24.2	like any other organism,					
20:25.3	if you look at the closely enough,					
20:27.1	you'll see they actually have very interesting differences					
20:29.0	from one another.					
20:30.1	So, this shows a gallery of a whole bunch of different keratocytes					
20:33.1	that were collected by Kinneret Keren and Zach Pincus,					
20:36.3	showing that from even one scale					
20:39.3	of a particular individual fish					
20:41.1	you can have quite a lot of variation,					
20:42.2	both in terms of the size of the individual cells,					
20:45.0	and then also their shape.					
20:46.1	So, some of them are quite round					
20:47.3	and some of them are quite elongated					
20:49.2	and almost canoe-shaped.					
20:51.1	And to summarize a lot of work,					
20:53.0	what we've been able to find is that					
20:55.2	these cell-to-cell shape differences					
20:57.1	are both persistent					
20:59.0	-- so, if you follow a cell over time,					
21:00.1	it keeps its shape --					
21:02.0	and they're also cell-intrisic					
21:04.0	#NAME?					
21:05.3	and let it grow back,					
21:07.2	it will grow back to exactly the same shape it was before.					
21:10.3	And from quantitative analysis of those kinds of measurements,					
21:13.2	what we found is that these shape differences					
21:15.1	are essentially extremes of a continuous spectrum,					
21:18.2	where some cells are very large and wide and smooth,					
21:22.0	and these are the ones that are canoe-shaped,					
21:24.0	and those are also the fastest moving cells.					
21:26.2	And some of the other cells,					
21:28.0	such as the ones over on the left side of this gallery,					
21:30.1	and rounder, they tend to be smaller,					
21:33.2	their leading edges look kind of rough,					
21:35.2	and they also move kind of slow					
21:37.1	and in a less persistent manner.					
21:39.0	And so we call the wide, smooth cells,					
21:41.2	we call those coherent cells,					
21:43.1	and the smaller, narrower, rough cells,					
21:45.1	we call decoherent cells.					
21:47.1	But overall, we can find every behavior in between,					
21:50.3	so we think the differences that we see among these shapes of the cells					
21:53.3	basically just has to do with the					
21:56.1	exact quantitative amount of all of these					
21:58.3	force-generating elements they have present					
22:01.1	within their cytoplasm					
22:02.3	that balance each other in slightly different ways					
22:04.2	to give overall cell shapes.					
22:07.3	And overall, we can					
22:09.3	quantitatively measure these variations in cell shape,					
22:11.2	particularly identifying principle modes of shape variation,					
22:14.2	and the mode I've been most frequently referring to					
22:18.1	is this second mode,					
22:19.2	where we go from the wide cells to					
22:22.2	the rounder, more D-shaped cells.					
22:24.2	And our modeling that we've done together with Alex Mogilner,					
22:28.0	together with experimental work,					
22:29.1	has suggested that really the variation in those shapes					
22:31.3	is primarily due to					
22:34.1	the back-and-forth force balance					
22:35.2	between actin polymerization pushing on the membrane					
22:37.1	and membrane tension restraining the actin polymerzation.					
22:41.2	And the short version is that					
22:44.1	cells that have very forceful actin polymerization					
22:46.2	are able to assume this coherent, wide lamellipodium,					
22:50.0	and cells that have weaker actin polymerization,					
22:51.3	for whatever reason,					
22:53.2	are the ones that end up in the rounder D-shape,					
22:55.2	and also move slower.					
22:57.2	Now, if that idea is true,					
22:59.2	then it should be the case that we can					
23:01.2	take an individual cell					
23:03.2	and somehow increase or decrease					
23:05.2	its overall rate of actin polymerization,					
23:07.1	and have that individual cell					
23:09.1	change across this entire shape spectrum.					
23:12.2	And so that experiment actually was done by Greg Allen,					
23:15.1	where the method he chose to change the rate of actin polymerization in the cell					
23:19.3	was simply to lower and raise the temperature.					
23:22.2	So, here we're going to watch a movie					
23:25.1	of a cell and as it moves along					
23:27.1	you can see it's fairly slow,					
23:28.2	it's got this more sort-of D-shaped pattern,					
23:31.1	and Greg is first going to start					
23:33.3	dropping the temperature,					
23:36.1	and as the temperature drops					
23:38.1	you can see the lamellipodium gets rounder and rounder,					
23:40.3	and the cell is moving slower and slower.					
23:45.0	And at this point,					
23:48.1	when we get down to just about 7 degrees Celsius,					
23:50.0	he's now going to start raising the temperature,					
23:53.1	and as the temperature comes back up					
23:55.1	you can see the cell not only goes faster and faster,					
23:57.2	but it also assumes a wider shape.					
24:01.1	And so following cells like this quantitatively					
24:03.1	using a variety of different metrics,					
24:04.3	what we were able to find is that, in fact,					
24:06.2	individual cells can explore					
24:08.2	this entire range of behavior					
24:10.0	that we see in the context of cell-to-cell variation,					
24:12.0	and it's all consistent with the idea that					
24:14.1	the primary determinant of the shape of the cell					
24:16.2	as well as the speed of the cell					
24:18.1	is simply how fast the actin is polymerizing.					
24:23.1	Now, another really fun thing about keratocytes					
24:25.1	is they have the ability to sense and respond to electric fields,					
24:29.2	and this is something they actually have in common					
24:31.2	with many other motile cells.					
24:32.3	Pretty much any motile cell					
24:34.3	that you put in a DC electric field					
24:36.2	will choose either the anode or the cathode					
24:38.2	and will head in one direction.					
24:41.1	This was first described for keratocytes					
24:43.1	by Cooper and Schliwa back in 1986,					
24:45.1	and Greg was able to replicate this					
24:47.3	using a setup that he built in our lab					
24:49.3	to look at motion of individual cells					
24:52.2	as the electric field was switched from one direction to the other.					
24:57.0	So, in this movie, we see a cell					
24:58.3	that's moving along in an electric field					
25:01.1	that is oriented in this direction					
25:03.1	#NAME?					
25:04.2	and also the magnitude listed over here --					
25:06.2	and you can see the cell is following that line.					
25:08.2	Now, when the label turned red,					
25:10.2	that was when the field was flipped around,					
25:12.2	and you can see the cell has turned					
25:15.1	and is now heading back in the other direction.					
25:17.1	And now, once again, the orientation of the field is flipped,					
25:21.1	the cell flips back around,					
25:22.2	and now heads back in the direction that it has been told to go.					
25:26.1	So, the cells obviously...					
25:28.1	even though I've been emphasizing					
25:31.0	how good they are at balancing forces					
25:32.3	across the front of the cell and between the front and the back of the cell,					
25:35.0	they are able to also initiate imbalances in their forces					
25:38.2	so that they're able to turn.					
25:40.2	So, Greg Allen looked a little bit more deeply into the mechanism					
25:43.1	of how they turn					
25:44.2	and he found a couple of interesting things.					
25:46.1	So, for example,					
25:47.3	if we look at a single turning cell					
25:49.3	-- in this case we're looking at it both in the lab frame of reference,					
25:52.1	like it looks on the microscope,					
25:53.3	and then in the cell frame of reference,					
25:55.1	where we've repositioned everything					
25:57.0	to see things in the cell's point of view --					
25:59.0	you can see there is a physical asymmetry					
26:01.0	in a turning cell,					
26:02.2	where the part that's on the inside of the curve,					
26:05.0	that is, the part that's going slower,					
26:06.3	has this very round shape that we call decoherent,					
26:10.1	and it's characteristic of slow motion.					
26:12.3	And on the outside of the turn, the part that's going faster,					
26:16.0	has a much more elongated, coherent shape					
26:18.2	that we associate with fast motion.					
26:20.3	So, this variation that we see,					
26:22.2	both at the population level					
26:24.0	and in individual cells as the temperature					
26:26.2	is raised and lowered,					
26:28.1	can actually also happen even within the context of an individual cell,					
26:31.0	where one side can end up being much faster					
26:34.0	than the other side.					
26:36.1	Now, there's a number of different things					
26:37.3	that contribute to this asymmetry,					
26:39.2	but at this point you won't be surprised					
26:41.0	that one of the major things that contributes					
26:42.2	is the left-right distribution of myosin.					
26:45.2	So, I showed you before that the myosin					
26:47.1	accumulates in these two spots on either side of the cell body,					
26:50.2	and those two spots aren't always necessarily equal in size.					
26:54.1	So, this is an example of a cell					
26:56.2	where there's a relatively low amount of myosin					
26:59.0	in the spot on the left side,					
27:01.0	and a much higher amount of myosin in the spot on the right side.					
27:03.2	And looking in the movie,					
27:05.0	you can see the consequences of that,					
27:06.2	here with the myosin labeled:					
27:08.0	the side that has more myosin is moving faster					
27:12.2	and is therefore sweeping around the outside part of the turn.					
27:14.2	Now, there's of course other elements					
27:16.2	that also contribute to this turning					
27:18.1	-- there are differences in adhesion,					
27:19.3	there are differences in traction force,					
27:21.1	there are differences in rates of actin polymerization --					
27:23.1	but they all seem connected to one another,					
27:25.1	and specifically connected to one another					
27:27.2	through the mechanism of myosin action.					
27:30.0	So, to summarize what we think is going on here,					
27:32.2	we think as the cell begins to turn					
27:35.3	the actin network flow starts to flow...					
27:37.2	instead of just flowing straight back to the back of the cell,					
27:40.0	starts to flow at a slight angle.					
27:41.3	Because the myosin is carried along					
27:44.1	on that flowing actin network,					
27:45.2	the myosin then accumulates					
27:47.2	at the outside corner of the cell.					
27:50.1	That myosin is able to contract faster,					
27:52.1	pull in that side of the					
27:55.3	back of the wing of the lamellipodium					
27:57.1	and help the cell sort of flip around.					
27:59.0	At the same time, because the myosin					
28:01.1	is depolymerizing the actin filaments,					
28:02.2	it's generating a gradient of G-actin,					
28:04.3	such that there's more actin available for polymerization					
28:08.0	on that same side of the cell					
28:09.3	where you have more myosin					
28:11.1	and where you have faster motion.					
28:12.3	And all of these things, we think,					
28:14.2	are able to actually feed back on one another					
28:17.0	in a positive sense,					
28:18.1	such that once a cell starts making one of these turns					
28:20.3	it actually is able to continue to make that turn					
28:22.3	in a persistent way					
28:24.1	actually for quite a long time,					
28:26.0	until it's then forced to turn in another direction.					
28:30.1	So, so far what I've shown you					
28:32.1	is that in the context of these very simple					
28:34.2	steady-state moving cells,					
28:36.1	myosin in the back of the cell					
28:37.2	is actually doing a tremendous number of exciting things					
28:40.0	that help the cell move overall and that help coordinate the front and the back.					
28:43.3	It's helping to disassemble the network					
28:45.1	and it's also specifically contributing to					
28:47.2	left-right aymmetries that help the cell to turn.					
28:49.3	Now, the keratocytes are fairly unusual cells					
28:53.0	-- they're unusual in their appearance,					
28:54.2	they're unusual in the steadiness of their motion --					
28:56.3	and so it became very natural then for us to ask					
28:59.3	whether similar mechanisms might be at play					
29:01.2	in more complicated cells					
29:03.1	that are doing more complicated tasks.					
29:05.2	And one of the very interesting cells that's been well-studied					
29:09.0	in the context of motility					
29:10.2	is the neutrophil, the human neutrophil,					
29:12.2	a white blood cell,					
29:14.1	whose job is to go after and engulf the					
29:16.2	bacteria that are invading the human body.					
29:19.1	And you can actually isolate neutrophils					
29:21.2	from your own blood					
29:23.1	and watch them crawl around and eat things					
29:24.3	-- it's really very gratifying --					
29:26.1	but also we have a call line,					
29:28.1	a neutrophil-like cell line,					
29:30.0	that is able to behave much like a neutrophil					
29:31.3	but that we can also transform					
29:33.2	and look at protein distributions					
29:35.2	in moving versions of the cell.					
29:38.1	So, Tony Tsai in the lab					
29:40.1	decided that it was time					
29:43.0	to actually break out of the keratocyte mold					
29:45.0	and start looking at motion in more complicated kinds of cells,					
29:48.1	including neutrophils,					
29:50.1	and just to show you how dramatic					
29:52.2	the behavior of these cells is,					
29:53.2	this is one of these HL60 cells					
29:55.3	that's been put in a chamber with some Candida albicans,					
29:58.1	which is a pathogenic yeast,					
30:00.2	and what you see as the movie loops					
30:02.0	is the neutrophil starts off over on the right side, here,					
30:05.1	and then runs across					
30:07.2	to this little pile of yeast					
30:08.3	and is able to actually phagocytose and engulf them.					
30:11.0	So it really is a very					
30:13.0	neutrophil-behaving tissue culture cell.					
30:16.0	Now, looking at the shapes,					
30:17.3	they're obviously much more complicated than the keratocytes,					
30:20.1	and putting in labels for the actin,					
30:22.2	which is shown here in green,					
30:23.3	the myosin, shown in red,					
30:25.1	and then DAPI to stain the nucleus in blue,					
30:27.2	what you can see is that the shapes are not only					
30:29.1	much more variable than keratocytes					
30:30.2	but also much, much more dynamic.					
30:32.3	All of the cytoskeletal elements					
30:34.2	are drastically rearranging themselves					
30:36.2	over periods of just a few seconds					
30:38.1	as the cell is crawling around.					
30:40.1	So, although this makes it a more interesting question,					
30:42.1	I think,					
30:43.2	to figure out what is going on in terms of					
30:45.2	the mechanics and dynamics of this behavior,					
30:47.2	it's also a much more challenging problem					
30:49.1	as far as quantitative analysis goes.					
30:53.1	So, Tony so far has been able to work out					
30:55.1	a number of quantitative techniques					
30:57.1	to be able to break down this complex motion					
30:59.1	so we can actually watch changes over time.					
31:02.0	So, for example, he can track the edges					
31:04.0	of one of these moving neutrophils					
31:05.1	and then go back and calculate,					
31:07.1	for the cell as it's moving,					
31:09.1	how much of the cell is extending in every time frame,					
31:12.0	in this case, every couple of seconds,					
31:13.2	how much is retracting,					
31:15.2	calculate the overall area of the cell					
31:17.1	as well as the extension of its leading edge,					
31:19.1	and the amount of retraction of its body.					
31:22.3	At the same time, we can look at labeled proteins inside the cell,					
31:26.1	and obviously one of the ones we're most interested in looking at					
31:29.3	is myosin,					
31:31.1	and look at the overall fluorescence intensity distribution					
31:33.2	and see how that changes as the cell moves around.					
31:36.1	And what you'll probably be able to see					
31:38.1	is that the myosin localization itself is also very dynamic.					
31:40.2	It's often in the back of the cell,					
31:42.0	sometimes in these bright spots,					
31:43.2	but then those bright spots will disassemble,					
31:45.1	the myosin will become more uniform					
31:47.2	or will move to a different location within the cell.					
31:50.3	And tracking all those things quantitatively over time,					
31:53.1	what Tony was able to find					
31:55.2	was that when a cell was speeding up,					
31:57.2	that the accumulation of the myosin					
32:00.2	in response to that change in cell behavior					
32:03.0	happens later, happens about 12 or 15 seconds					
32:06.0	after the initial movement of the leading edge.					
32:09.0	So, whereas in the keratocytes					
32:10.2	it seems like the actin and the myosin					
32:12.2	were always in perfect balance					
32:14.1	so that the cells were always gliding forward,					
32:16.1	in the neutrophils the story is a little bit different					
32:18.1	#NAME?					
32:20.1	and the myosin is then reacting.					
32:22.1	So, as the cell initially extends,					
32:24.3	it then activates the accumulation of myosin at the rear					
32:27.2	to pull the back together.					
32:29.1	So, instead of gliding,					
32:30.2	it's doing more of an inchworm motion.					
32:34.2	How does this affect cell turning?					
32:36.1	Well, the same way that Tony was able to come up with					
32:38.3	quantitative metrics for the localization of myosin,					
32:41.0	he was also able to come up with					
32:42.2	quantitative descriptions for the orientation change of the cell					
32:46.0	and then the left-right asymmetry of the myosin					
32:48.3	with respect to its immediate orientation.					
32:51.0	And you can already see the answer, actually,					
32:53.1	quite dramatically,					
32:54.3	with this maximal intensity projection,					
32:56.2	where this is just a low magnification movie					
32:59.2	of a cell that's undergoing a sinusoidal path,					
33:02.1	and we're looking now only at the myosin					
33:04.1	that's accumulating at its rear,					
33:05.2	and what you can see is that the myosin					
33:07.1	always accumulates on the outside of the turn,					
33:10.0	and when it changes its direction,					
33:12.0	the myosin then changes which side of the cell it's on.					
33:16.1	So, this is actually very reminiscent of the keratocytes,					
33:18.2	where we saw, again,					
33:20.1	the myosin on the outside of the turn,					
33:22.0	except in the case of neutrophils, again,					
33:24.1	there's a little bit of a time lag					
33:27.0	between when the turning initially starts					
33:30.1	versus when the myosin accumulates on the outside of the turn.					
33:33.0	So, here too it looks like					
33:34.3	the actin is calling the shots in terms of direction,					
33:36.2	the flow direction of the actin					
33:39.0	that's changing					
33:40.2	then gathers the myosin on the outside of the turn,					
33:43.1	that then causes disassembly of that cytoskeleton					
33:46.1	in a way that enables the neutrophil					
33:48.1	to essentially swing its tail around					
33:50.1	so that the whole cell is now oriented in the proper direction.					
33:54.1	So, overall, comparing these two stories...					
33:56.2	if you look at a movie of a keratocyte versus a neutrophil,					
33:59.2	they seem like they're behaving rather differently,					
34:01.2	but what we understand when we dissect					
34:04.1	the mechanics and the dynamics of this behavior					
34:05.2	is that they're strikingly similar.					
34:07.1	In particular, I've shown you					
34:09.2	recent data that myosin accumulates at the cell rear					
34:11.3	due to this actin network retrograde transport					
34:13.3	and mediates actin network disassembly					
34:16.0	in a way that is then able to coordinate					
34:17.3	not only front-rear motion of the cell					
34:20.1	but also give you asymmetries					
34:22.1	that can lead to turning.					
34:23.2	And both of those things seem to happen					
34:25.2	in very similar ways					
34:27.0	in both the keratocytes and the neutrophils.					
34:29.2	Now, one last little hint I want to leave you with is,					
34:32.2	as I showed you before with this movie,					
34:34.1	we can force keratocytes					
34:36.0	to behave more like neutrophils					
34:38.0	in terms of changing their shape all the time					
34:39.2	if we simply change the environment,					
34:41.1	and particularly if we put them on					
34:43.1	very, very sticky substrates.					
34:44.2	So you might wonder, can we do the flipside;					
34:47.2	can we make a neutrophil behave more like a keratocyte,					
34:50.2	into something that will have a steady-state motion					
34:52.1	where everything is happening at the same rate?					
34:55.1	Well, it turns out when you take a neutrophil					
34:57.1	and you confine it to a very narrow channel					
35:01.0	and then watch it move over time,					
35:03.0	these guys now are moving at steady-state.					
35:05.3	The speed is an absolute constant,					
35:07.3	the distribution of myosin is constant,					
35:09.2	it's always found at the rear,					
35:11.2	and they'll continue to move like this					
35:13.0	for many tens of minutes					
35:14.2	without any obvious changes					
35:16.0	in terms of their overall shape or overall behavior.					
35:18.2	And taking this same movie and now making a kymograph of it,					
35:21.2	where the time is moving from top to bottom					
35:23.3	and each one of these slices					
35:25.2	is an individual frame of this movie,					
35:27.0	you can see, really, how constant this speed is over time.					
35:30.1	So, not only can we force keratocytes					
35:32.2	to become more crazy					
35:33.2	and change their direction like neutrophils,					
35:35.1	we can also force neutrophils					
35:37.1	to behave more in a steady-state like keratocytes.					
35:40.0	And moving forward, I think the combination					
35:42.1	of our ability to both measure and manipulate					
35:44.0	these different kinds of motile cells					
35:45.2	will help us to understand					
35:47.3	the general principles that govern motility					
35:49.3	for all animal cells					
35:51.3	that use actin polymerization to drive their movement.					
35:56.1	So, as an overall summary,					
35:58.2	I think the main point here is that					
36:00.3	actin and myosin have to cooperate					
36:02.2	in order to make cells move,					
36:04.1	not just in order to generate force,					
36:05.2	but also just in order to do things					
36:07.2	like steer them and determine their shape.					
36:09.0	And we found that myosin plays actually					
36:12.0	several very unexpected roles at the rear of cells,					
36:13.2	not just contributing to contraction,					
36:15.2	as we might have expected,					
36:17.1	but also contributing specifically to actin network turnover					
36:20.1	and to asymmetries that lead to cell turning.					
36:22.3	And overall, we've been very surprised					
36:24.2	by how similar the mechanics are					
36:27.0	between fish skin keratocytes and human neutrophils.					
36:33.2	So, obviously, there have been					
36:35.3	a lot of very talented people					
36:37.2	who have contributed to the work that I just described,					
36:39.1	and I've listed here the many members of my group					
36:41.2	who have contributed to different aspects of cell motility projects					
36:44.2	over the last 15 years or so,					
36:46.1	and also our wonderful collaborators.					
36:48.2	And I'd particularly like to mention this in this context					
36:51.2	our very productive long-term collaboration					
36:53.0	with Alex Mogilner,					
36:54.2	who has done a lot of the quantitative physical modeling					
36:56.2	that has driven the thought processes behind our experiments.					
37:00.0	Thank you.					

This material is based upon work supported by the National Science Foundation and the National Institute of General Medical Sciences under Grant No. 2122350 and 1 R25 GM139147. Any opinion, finding, conclusion, or recommendation expressed in these videos are solely those of the speakers and do not necessarily represent the views of the Science Communication Lab/iBiology, the National Science Foundation, the National Institutes of Health, or other Science Communication Lab funders.

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