Christopher Donahue:
I'm -- in case you don't know me, I'm Christopher
Donahue.
I'm a historian of the -- I'm the historian
of the NGHRI.
I also help out with the NHGRI history of
genomics program.
And so, Dr. Alan Love is the second speaker
in the NHGRI history of genomics and molecular
biology lecture series, and we are extraordinarily
pleased to have him.
I'm going to just give a few lines of introduction,
and then he's going to give his talk, in the
interest of time.
So, Alan is an associate professor of philosophy
at the University of Minnesota, and director
of the Minnesota Center for Philosophy of
Science.
And the Minnesota Center for the Philosophy
of Science is the oldest and -- basically
an extraordinarily study center for the philosophy
of science.
So, his research focuses on conceptual issues
of biology, and much of his work has concentrated
in concepts of innovation and novelty, and
evolution and developmental biology.
He is also interested in issues that arise
in developmental biology and functional morphology.
He uses a combination of approaches to investigate
a variety of philosophical questions: conceptual
change, explanatory pluralism, the structure
of evolutionary theory, reductionism, and
nature of historical science, and interdisciplinary
epistemology.
Other areas of Alan's history include the
role of history in philosophical research,
and the nature intuition generated by thought
experiments and philosophical inquiry.
And his talk is titled, as you can see, Physics,
Genetics, and Investigative Reasoning in Developmental
Biology.
And with that, I'm going to turn it over to
Alan.
Thank you very much.
Alan Love:
Thank you, Christopher.
Really a delight to be here.
I'm going to jump right in, so that I can
move through the talk, and have as much time
for discussion as is possible.
In some ways, this talk may be a little bit
different in bringing up some more contemporary
or philosophical issues, as well as some of
the historical issues, but I think that this
is a great audience to hear from, in terms
of this material.
So, let me start with an outline of where
I want to go.
I want to talk a little bit about the opening
puzzle, which is what I'm calling the Renaissance
of Physics in Developmental Biology.
And then, contextualize that with a little
bit of deeper background about the long history
of interaction between physics and development.
And then, move farther forward into the 20th
century to a time when -- what I term mathematical
modeling fails, and is, I think, really illuminating
for why physics kind of backs away, or is
no longer as important.
And part of that story is experimental tools
flourishing in developmental biology.
And then, what I want to try and do is use
that historical material to tell a philosophical
story about what might be going on with the
reasoning, and help understand better why
we got to the place that we did in the present.
And then, I'll close with a little bit of
a discussion about my own research, and how
some of this has been reframed by the analysis,
and maybe applies to some issues in philosophy
more broadly that I think are interesting.
So, let's start with the puzzle, the Renaissance
of Physics and Developmental Biology.
So, there's a lot of attention being paid
to physics in biology right now.
If anybody has been watching, you see papers
coming out quite regularly.
Here's just one quotation from a paper a couple
years back: “There's been a renewed appreciation
of the fact that to understand morphogenesis
and three dimensions, it's necessary to combine
molecular insights with knowledge of physical
processes.”
Now, interestingly, that comes from this paper
on the growth and form of the gut, from Nature
2011.
It's the Tabin Lab of Harvard.
The title is important because of course,
“On Growth and Form,” refers back to a
very famous book by D'Arcy Thompson, On Growth
and Form, originally published in 1917.
Second edition came out in 1942, which tried
to offer mathematized or physical style explanations
of lots of biological properties, including
developmental ones.
And so, we see in this contemporary research,
a lot of interest in what is termed the interplay
of gene expression and physical forces.
And in fact -- I'm not going to read these
quotes, but I want to just sort of highlight
this terminology of interplay.
Shows up, over and over again, in the way
it gets discussed.
Here, I've just tried to make that term bold
in these quotes, that what people are really
flagging is a kind of interaction between
the physics and the genetics, and that's what
is drawing people in.
And so, this terminology interplay has gotten
enough cache to then play a role, and actually,
the repeated emphasis that's being placed
on that in these different contexts by different
researchers.
So, why this is significant has to do with
the fact that for anybody who's been involved
in developmental biology, genetic explanatory
approaches are predominant.
That's in part due to the way in which the
field has developed, out of some really powerful
experimental techniques in the 1980s, and
that's some of what I'm going to talk about
later.
And it leads to, you know, statements of this
kind that you would find in a textbook: “Developmental
biology deals with the process by which the
genes and the fertilized egg control cell
behavior in the embryo, and so determine its
pattern and its form.”
Now, this is maybe a milder version of this
statement, but if we want a less mild version,
there's always somebody we can go to.
Eric Davidson, who just passed away last year.
Here's the way he has phrased it: “Elements
of the genome contain the sequence-specific
code for development.
They determine a particular outcome in developmental
processes.”
And then, most recently in the book that was
published right before he died, “Developmental
complexity is the direct output of the spatially
specific expression of particular gene sets,
and it's at this level that we can address
causality in development.”
So, given that this is the situation, and
John Gerhart has summed it up, “For some
researchers, development can now be reduced
to the interplay of cell-cell signaling and
transcriptional regulation.”
And some people have recognized this effect,
even in some sense, obscuring a link between
physics and biology as a consequence of the
success.
That's the puzzle.
You know, if you've got this genetics orientation
that's so predominant, and we know that physics
is in the background on history, where is
this renaissance coming from?
How is it kind of coming back onto the table
in this kind of way?
So, let me step back in time and say a little
bit about how physics and development have
had some relationships in the deeper past.
The most famous of these is an interaction
in the late 19th century between Ernst Haeckel
and Wilhelm His.
Ernst Haeckel, many of you might be familiar
with him, appealed to evolutionary history
in his famous idea “ontology recapitulates
phylogeny” to try and understand how development
works.
Wilhelm His rejected that outright, and actually
favored physical explanations where you explicitly
make an analogy with physical structures to
try and understand what's going on in the
embryo.
So, if you got physical forces operating on
non-living materials, and those yield certain
properties, then if physical forces operate
on similar living entities, then you should
get similar kinds of behavior.
And so, one of the examples that was given
by His was this comparison of two and three-day
old chick brains with a rubber tube folding
under the pull of a thread.
And the point is that you're saying analogous
behavior between the living and the non-living
materials to try and give an account of why
the living materials would behave the way
they do during embryogenesis.
Now, you might think, “oh, that was just
the 19th century.”
Let's go back to this paper on growth and
form of the gut.
They basically did the exact same thing, okay?
So, what you have on the top is the rubber
simulacrum of the gut looping, which was created
by putting those two different materials together,
and then stretching and relaxing them.
And then, on the bottom you have the chick
gut, right?
So, again, you're comparing in a directly
analogous way, in some respects, quite similar
to what His was arguing, more than 100 years
ago.
Now, when D'Arcy Thompson was making his arguments,
he was appealing to different rates of growth
and geometrical relationships.
He thought this similar line of reasoning
applied, if the physical forces generate morphologies
in these viscoelastic materials, then they
should do the same thing when they're operating
in organisms.
And if you could see this visually, this would
be part of the reason why you should become
convinced of it, okay?
That sort of the visual representation of
that, which we've already see in the case,
both of the present paper and in the past
paper, that's part of what you would find
persuasive.
So, this is the comparison, in terms of jellyfish
structure, that you might use between the
liquid splash drop and that morphology.
And this is the way Thompson encapsulates
that.
He says that “The living medusa has a geometrical
similarity so marketed and regular as to suggest
a physical or mechanical element in the little
creature's growth and construction.
We seem able to discover various actual phases
of the splash or drop in all but innumerable
types of jellyfish.
These analogies indicate, at the very least,
how certain simple organic forms might be
naturally assumed by one fluid mass within
another when the physical forces play their
part.”
Now, I've highlighted in blue -- these might
be, can be -- these statements which indicate
that this is the analogy, right?
That you've not made a direct demonstration.
You're making a claim by that.
So, Thompson was clear that you couldn't just
have physical forces, right?
And this is an important part.
It's not about somehow being in competition
with genetics because one of the things Thompson
was dealing with was the rise of classical
genetics, and the power that came out of the
Morgan Lab in chromosomal theory that was
developing in the early part of the 20th century.
And so, he is clear, it would be an exaggeration
to see in every bone, nothing more than a
result of direct physical or mechanical conditions,
for to do so would be to deny the existence
of a principle of heredity.
But it would still be an exaggeration if we
neglected the direct and mechanical -- physical
and mechanical modes, right?
That you can't neglect either one.
And of course, that's part of what makes this
interesting about how we've gotten to the
point of today, because it does seem like
there has been that neglect, at least in points
of the history.
Now, in the middle of the 20th century, just
to sort of end this potted history, there
were further physical approaches to developmental
phenomena, probably the most famous is Alan
Turing's model of a spatially constrained
reaction diffusion mechanism to get coloration
patterns in animals.
And again, you see similar kind of reasoning
in his paper from 1952.
It suggests that a system of chemical substances
called morphogens reacting together and diffusing
through a tissue is adequate to account for
the main phenomena of morphogenesis.
Certain well-known physical laws are sufficient
account for many of the facts, okay?
It's not that you've actually demonstrated
this in the system.
You've just said I -- this kind of physical
mechanism is capable of accounting for these
behavioral patterns.
Now, I think what this highlights is a really
important part of the history that we can
glean that all this explanatory reasoning
is analogous, right?
So, you're saying if it happens in the physical
systems this way, then it should happen in
the biological systems this way, but you actually
are not demonstrating it the biological systems
in most of these cases.
They're how possibly explanations, not how
actually explanations.
Might be, can be, could be.
You get that kind of language.
And then, there's a sort of assumption of
a symmetry between the physical and the biological
explanations.
Right?
So, if physics is sufficient, why would you
need to do anything else, right?
That's the -- so, that's kind of an implicit
premise in some of the argumentation.
There's nothing further to do if the physics
was sufficient.
And I think this xkcd cartoon captures it.
It might be a little bit hard to see -- I'll
read it.
So, the one says to another, you're trying
to predict the behavior of complicated system
-- fill it in, just model it as simple object
-- fill it in, and then add some secondary
terms to account for complications I just
thought of -- fill it in.
Easy, right?
So, why does your field -- fill it in, need
a whole journal, anyway?
[laughter]
And then, the bottom caption is “Liberal
arts majors may be annoying sometimes, but
there's nothing more obnoxious than a physicist
first encountering a new subject.”
So, I think this is a little bit in the background
of this reasoning, and this is a funny way
of putting it.
Okay, so that brings us to much more recent
history, and this idea of mathematical modeling
failing, as I'm calling it.
It's in quotation marks because the failure
is not so much that the models themselves
were bad, but rather that they didn't get
traction in the research community.
A lot of those were variations on Turing models,
which you see here -- some of that represented
on whether you have one or two morphogens,
and what kinds of interactions they have between
them, what kinds of spatial patterns they
can make, and you can do the mathematical
modeling for these different combinations,
and tune the parameters, and see what possibilities
are there.
And through the 1980s, you see a lot of these
papers being published, and they're being
published in places where developmental biologists
would work.
So, Journal of Embryology and Experimental
Morphology -- that journal doesn't exist anymore
because it was renamed Development, okay?
So, you know, this is happening during a time
when you would think, oh, this is what a developmental
biologist is reading?
And you can see, these are models for vertebrate
limbs, segmentation, and the like.
This is Hans Meinhardt, one of the key architects
of some of these models in that period.
Another group of people, George Auster, James
Murray, again, lots of modeling of the limb.
And you can see that it's being published
in these standard places, Development, Developmental
Biology.
And some of it is even experimental, and I've
picked out one individual who I think is interesting
but who hasn't received that much attention,
Albert Harris, who was not simply drawing
physical analogy, but in some cases, trying
to do experiments with physical substrates
to see if you could make this argument a little
bit stronger.
At the same time, if you go in and you look
at the language in these papers, you don't
have to read the whole quotes.
Just look at the blue.
Because the blue, again, indicates that in
most of these situations, you have a similar
sort of claim as we had 100 years before,
right?
How they can.
How these processes would be the cause, right?
That same kind of language.
And here, from the paper by Albert Harris,
this is showing some of the images that he
has.
He has cells that are creating traction force
on a thin silicone rubber.
And so, you can see the rubber wrinkling.
That's what he's showing in these images.
Our observations imply that cell locomotion
in vivo could generate large tension fields.
And then, you would, often times, get these
additional sorts of claims, it would be unlike
evolution not to make use of these fields
to guide morphogenesis.
But of course, you were still making a how
possibly explanation by analogy.
Now, looking a little bit more at Harris,
I think, helps us see the transition that
was taking place during this time.
So, this is from a letter that he wrote to
his adviser, John Trinkaus, who was an embryologist
at Yale.
He says, “One of the things I'm most interested
in modeling is the limb bud, and the mechanical
relations between the elasticity and/or contractility
of the ectoderm to the shaping of the bud.
Okay?
So, that just gives you his general physical
orientation.
“My main working assumption is that the
peculiar shape of the cells of the apical
ridge results from some mechanical properties,
and this is the key to the shaping of the
whole bud.”
Now, part of this reasoning, the key to the
shaping is casual reasoning, right?
That this is the explanation why it takes
the shape that it does.
Harris encountered a lot of resistance, and
that frustration was with molecular geneticists,
in particular, those working on the vertebrate
limb.
This is from a later letter.
He says, “John Saunders tells me he's on
his way to the fifth international conference
on limb bud development.
I was at the third in the series five years
ago, and was infuriated by the tunnel vision
of the molecular types.
They are just so blind to mechanics.
They see things their way, and only their
way, and the flood of solid data their techniques
is producing, reinforces, and validates their
narrowness, so you can't argue with them.”
Now, I don't want to get into the sociological
dynamics here.
I want to highlight the blue text in the letter,
which I think is an important feature of what
was going on at the time.
“The flood of solid data their techniques
were producing.”
And this showed up in another dimension of
Harris's reasoning, which was interpreting
all of the touring type pattern formation,
genetically, especially Wolpert's French flag
model, which I won't go into detail, but the
key thing is that when Wolpert talks about
positional information, what he ends up doing
is emphasizing genetic properties -- that
is, cells' ability to interpret signals, as
opposed to their reaction diffusion mechanism,
which is a physical type explanation.
And this is the way Wolpert put himself, “Cells
acquire positional identities in a courted
system, and then interpret their positions
to give the spatial patterns.”
And this is --
Male Speaker:
Before you go on --
Alan Love:
Yeah?
Male Speaker:
What did they mean by, “a flood of solid
data?”
What is solid data --
Alan Love:
So, what I think Harris is acknowledging here
is that, from his perspective, as somebody
in the field at the time, he is not being
critical of the fact that the community is
generating data that's relevant to what they're
trying to do.
Male Speaker:
The geneticists?
Alan Love:
Well, in this case, I think he has in mind
developmental biologists who are starting
to use molecular genetic methods.
Male Speaker:
So, it's like -- is this like --
Male Speaker:
So, the he did experiments on the -- the FGF
on the limb buds.
This is on molecular biology --
Alan Love:
And --
[inaudible commentary]
Male Speaker:
-- this wasn't like, you know, CDNA sequencing,
EST generation of the '90s --
Alan Love:
No.
Male Speaker:
Could've been that.
Alan Love:
No, no, that's --
Male Speaker:
So, it's not --
Male Speaker:
Well, that enabled these guys --
Alan Love:
Right, but this is a little bit earlier, so
that -- you're right, that's -- it's not the
EST.
It's more -- and it's also early in situ hybridization,
which I'm going to come to, which was -- which
was coming out of the blocks at this point
in time.
Male Speaker:
Trinkaus went to one of the first zebra fish
meetings, and complained that we were spending
too much time generating too many cheap mutants.
Alan Love:
Yeah.
Male Speaker:
Why can't we just study one?
Alan Love:
I could talk more about --
[laughter]
-- Trinkaus is not the focus of this, but
I could talk more about him because I've looked
at his stuff.
So anyway, just for reference point, this
is the French flag model where you get this
-- different cells interpreting their identity
based on where they are, and differentiating.
Now, this is a nice thing about working in
archives.
You get to see some things that you might
not see otherwise.
This is a handout that Harris created, and
it is meant tongue in cheek.
“Differentiating cells become organized
in space by first learning just where they
are, and then interpreting this information
according to their genetic program.
How else could they possibly do it?”
And of course, he wants to say this is not
a good explanation, and he's criticizing the
-- kind of Wolpert orientation.
And then, it gets a little bit more extreme
in another one.
Remember, if cells or groups of cells tend
to round up, become spherical, this is caused
by surface tension, which is a force of nature,
like gravity.
And also, it means that their components are
trying to maximize their contact with one
another.
And of course, the side parentheses, “If
these turkeys knew any thermodynamics, I wouldn't
have to be telling them this.
Why do I bother?”
So, I mean, this is -- this is just a way
of sort of showing Harris's frustration in
some of the ways he expressed it in cartoons
that he really felt like he was having trouble
communicating the significance of these physical
dynamics to the developmental biologists at
the time.
Now, here's one way of seeing this, I think,
more concretely, outside of Harris's own personal
reaction, and this is from a news and view
in Nature in 1989, a very famous paper on
Drosophila segmentation.
And if -- it might be hard to read, but if
you look within this, right, the first thing
to highlight is, “Periodicity might be generated
in one of two ways.
An elegant mechanism, favored by model builders,
would use an intrinsically periodic patterning
interaction with a gradient.”
All right?
So, that's the first claim.
And then, you get a little bit farther one,
you get this: “But the protein products
of the gap genes are not so precisely localized.”
Okay?
So, the modelers would do it this way.
Turns out, that's wrong.
Okay?
And of course, this is why the title is what
it is.
It's supposed to sort of push a little bit
on the if you make elegant assumptions, you
could be making bad assumptions.
Sean Carroll, I think, captured this explicitly
in his 2005 book on evo devo.
“Many theoreticians sought to explain how
periodic patterns could be organized across
entire large structures.
While the math and models are beautiful, none
of this theory has been borne out by the discoveries
of the last 20 years.
The mathematicians never envisioned that modular
genetic switches held the key to pattern formation,
or that the periodic patterns we see are actually
the composition of numerous individual elements.”
All right?
So, there is the -- could be that way, just
turns it's not.
And since it's not, what's the best way to
get at it?
It's to do these genetic experiments.
And then, this is a nice quote that Evelyn
Fox Keller got from a proposal in the mid-'90s,
“The physics of how embryos change shape
is neither an important or an interesting
question.”
And I think that that kind of statement is
interestingly precise because it doesn't mesh
with what we saw.
For a long time, people have thought this
was a really important and interesting question,
so it's almost like there's a moment in time
when it wasn't thought to potentially be interesting.
And Albert Harris ended up being right in
the middle of that time and experiencing that.
So, that brings us to kind of fill out the
story a little bit.
And this, I'm going to go a little bit fast
because I'm talking to an audience who knows
these things in detail.
What we are seeing, I think, in this period
is the application of these recombinant DNA
tools in developmental biology.
And so, the molecular biology toolkit, all
of that, plus ways to visualize differential
gene expression, as we see in in situ hybridization,
ways to determine if a gene is necessary for
a process, such as with knockouts and knockdowns,
and ways to determine if a gene is sufficient
for a process, such as expressing it somewhere
else.
Most famously, in a place that you would not
expect it to be, such as an eye on an antenna.
Okay?
This is all happening in the 1980s within
developmental biology because that's when
these tools are becoming standardized in a
way that everybody can start to use them and
apply them, and get this solid flood of data
that is being referred to by Harris.
Now, I'm going to concentrate on in situ hybridization
because I think it plays a special in developmental
biology as a way of visualizing it.
I won't go over the process because this is
a cartoon version meant mostly for audiences
who don't know the biology.
But the important part is it's a way of labeling
a segment of DNA, and ascertaining to what
degree a particular gene is expressed at a
particular time or stage in development, and
at a particular location.
Now, if we analyze the growth of in situ hybridization,
just by doing a pub med sort of search, you
can see -- and you can compare this with other
key terms, they do not show the same pattern.
This dramatic rise of in situ hybridization
-- basically at the end of the '80s, and into
the early '90s.
And so, just to kind of map what we've been
looking at, right, those mathematical models
are flourishing in this period.
All right?
Theirs making stripes inelegantly, right?
It's kind of at the beginning of the growth
curve.
And by the time you're here, the physics of
how embryos change shape is neither an important
or interesting question.
And I think this is a really, you know, helpful
angle on understanding why it would be the
case that people would no longer think that
these kinds of questions are important, in
part because they're able to experimentally
access genetic features of development in
this way.
So, what to make of all of this?
Right?
So, in a sense, that's a potted history because
I'm, you know, giving you very, you know,
quick looks at 100 years ago, and then a little
bit of a zooming in on about 25, 30, 40 years
ago.
But what I hope I was able to convince you
of is that this relationship between physics
and development is old.
It's been around a long time.
That style of reasoning that's analogy is
important that people have constantly appealed
to it, and that there was a particular moment
in the 1980s when that really exploded in
the face of the mathematical modelers because
it turned out that in some of these experimental
-- high profile, experimental cases, what
actually was going on was very different,
and that that conditioned the way people thought
about it.
Well, so, what to make of it?
Well, I think we need to understand how important
the genetic molecular approach is in developmental
biology.
If we think about in classical genetics, it
was the primary investigative reasoning strategy,
as Ken Waters has put it, “You discover
naturally occurring or artificially produced
mutants that exhibit a difference relevant
to some biological process, and then you carry
out a genetic analysis of the mutants.”
It's something that's still being done today,
but that was a real innovation at the time,
and it was based on the ability to track differences
in a gene that caused uniform phenotypic differences
in specific contexts.
Change the context, and the effect of the
gene might change.
And so, part of the research strategy is making
sure you can control those contexts.
And then, that was reworked, molecularly,
obviously in the early days of classical genetics.
It was not a molecular approach, but it was
reworked as such, and gave the capacity to
manipulate and investigate many processes
of dramatic increase in the period that we're
talking about right now, for developmental
biology, especially.
Now, what's going on in this case is what
Ken Waters refers to as investigative reasoning.
Right?
If you think about the classical genetics
examples, what they could actually explain
was maybe not as dramatic as what they could
manipulate, okay?
They could do these amazing triple crosses,
and you know, get these mutants to exhibit
certain phenotypes, but in terms of our, say,
understanding of how that phenotype was produced,
it was still relatively limited.
So, I think that one of the things that we
really need to highlight is that the transformation
that we're talking about is a transformation
in terms of how you do investigation, not
necessarily in how you offer an explanation.
And here, this is something that's important
for how philosophers think about science because
philosophers typically assume that scientific
knowledge is structured by explanatory reasoning,
and that research programs are organized around
filling out a theory.
Okay?
That's kind of like, well, what else would
scientists be doing?
Well, it turns out, I think, a lot more.
And it's often times these investigative strategies
which guy day to day reasoning.
What is that?
Practical know-how about doing experiments,
being able to maintain stocks, produce mutants,
having basic descriptive knowledge of some
casual regularities, and evaluating how that's
going to help you leverage further research.
Okay?
Not so much having an explanation, but having
a tool that lets me do more.
Now, I think one of the things that is going
on is that the explanatory potential of the
physical approaches as we track them did not
change a lot through the 20th century.
But what has changed is the precision of the
physical manipulations that you can do in
developing systems.
And that has increased the practical knowledge
that you can look at those physical variables
during embryogenesis, okay?
It's not because we somehow now have a very
rich physical explanation of development.
It's that we can manipulate development physically
in a way that was simply not possible, and
was not what the mathematical modelers were
doing.
So, I think a central reason for the renaissance
of these physical approaches is their amenability
to experimental manipulation on analogy with
mutational analysis in the genetic approach.
You're applying the same kind of casual reasoning
to the physics that you did to the genetics.
That's what changed, okay?
This kind of reasoning -- I won't go over
it in detail.
It's been described in some philosophical
literature as casual reasoning, in terms of
difference making where variables represent
causes in which you manipulate the value under
certain contexts, and then figure out different
ways in which you can establish certain things
will happen under certain conditions.
It's -- allows you presume context, as long
as you can hold it stable.
And that's a key part of it is being able
to control variables.
And you can recognize many causes because
you can manipulate one cause, and hold other
things fixed, and then you can hold that cause
fixed, and manipulate something else.
So, that's what researchers are deliberately
doing.
They're constructing experimental situations
where they can do those kinds of interventions
and establish whether or not a particular
factor makes a difference in a particular
context.
So, one of the things that has been highlighted
in this discussion is the difference between
an actual difference maker -- that is something
that is making a different in the population,
as opposed to something that could.
So, something that could, right -- well, it
might, in a population, if you were able to
see the value of the variable of change.
If it actually does, it's because it changes,
that makes the difference, okay?
The important thing is that until recently,
all of that discussion about physics was about
potential, right?
It was about this could possibly make a difference,
right, but we haven't experimentally established
that it does.
All the mathematical modeling is in terms
of potential difference making, and that was
the primary strategy.
So, I think this helps explain the rise of
physical approaches because in a sense, what's
going on is you're actually able to manipulate
physical variables, and show that they make
a difference, and that just wasn't possible
in most experimental systems before that.
Now, very briefly, let me illustrate this
with a case that's now a few years old on
fluid forces in cardiogenesis.
Here, what was important was the ability to
do quantitative in vivo imaging that allowed
you to track the flow and then modify that
flow via some kind of occlusion that was stable
and reliable, and you could then measure the
effects.
And importantly, it's directly analogous to
the measurement of gene expression differences
through imaging.
You have to be able to see it -- so, similar
to in situ hybridization, you have to see
what the intervention does, and you change
the value of a variable by over expression
or knockdown.
So, the occlusion is doing something similar
in that way.
So, this is just some of the images from the
paper showing the schematic of the occlusion.
Here's some of the way the authors themselves
described it: “Embryos with an impaired
cardiac flow demonstrated three dramatic phenotypes.
The hearts did not form.
They lacked heart looping.”
This is what's fascinating.
“This latter phenotype is reminiscent of
the zebra fish Jekyll mutant which demonstrates
abnormal blood flow.”
I think this is a really important part of
the reasoning here, is showing we're doing
something just like the geneticists are doing
in creating mutants, but we didn't modify
a gene.
We modified a physical force.
That's what wasn't being done before.
So, I think developmental biology uses the
genetic approach because it lets you get at
actual difference makers, but that doesn't
require it to be a genetic one.
If you can manipulate physical variables that
way, they, too, are susceptible to that kind
of analysis.
And if you can do it with physical forces,
then you could show it.
And so, that directly parallels gene expression
visualization and mutation analysis.
That's standard in the genetic approach.
I think this is a lot of what accounts for
why physics get a kind of renaissance in developmental
biology.
It's not because it somehow got recognized
again as an important explanation.
It's because we could, for the first time,
manipulate it in a way that we could -- the
way genetically we did with the systems already.
All right.
So, that brings me to my last section, and
this is going to explain the pictures of the
zebra fish that were -- skeletons that were
on the first slide.
So, for those zebra fish researchers who are
curious what I was doing, I'm going to explain.
So, one of the projects I've been engaged
in is trying to look at how biologists put
together physical or generic explanations
with genetic ones.
It's something I've been interested in, and
it shows up in this case, and in others.
But you'll notice that the way my research
is framed is in terms of explanation, right?
And to some degree, I was, initially, misled
in trying to understand this current situation
because I was looking for those explanatory
models, rather than looking at investigative
reasoning.
Okay?
Now, you might think, well, why were you misled?
Well, if you look, biologists seem to be saying
“we needed integration” right?
The field needs increased integration between
cell biology, biomechanic analyses -- integrating
biomechanics with genetic analysis, right?
But what was happening was I was tending to
read those as explanation, not investigation,
right?
And so, I think that an important part of
the analysis here is really reframing some
of these questions, in terms of investigation.
That is, the call for bringing together physics
and genetics is not necessarily a call for
bringing them together in explanation, but
rather, bringing them together in investigation,
in the tools that we use to get at systems.
That doesn't mean there isn't integration
or some kind of thing to think about there,
but it's very different in its structure,
I think.
So, that leaves an open question of why the
explanatory power of physics has not been
more actively countenanced by developmental
biologists, and I'm still exploring that.
I think that's an open question, but I have
a hypothesis, and that's that the standards
of investigation and explanation are aligned
in genetic approaches to development.
That is, there's a sense in which they run
on the same rails.
What's not clear is that the standards of
investigation/explanation run on the same
rails for physics.
And if that's the case, that would be one
reason for this kind of discrepancy.
Now, you might say, “Well, what would align
them?”
And here, I think the explanation might be
very pragmatic.
And if we go back to that fluid flow paper,
all right, they talk about the experiments
that lead to those effects.
They emphasize this: “Approximately 40 percent
of congenital heart defects involve a valve
abnormality.
Our defects in hearts with no genetic lesion
suggest that a critical role is played by
blood flow induced forces during normal heart
development, and suggests that altered hemodynamics
may contribute to the cardiac phenotype in
some cardiac mutants, and perhaps all the
birth defects.”
So, here, it's not that you're offering some
kind of comprehensive physical explanation,
but you're actually saying “This might be
medically relevant.
This might have medical payoff.”
A pragmatic relevance.
And in fact, that's why those fish are there
because they are an example of this being
done recently in zebra fish, where they were
able to produce mutants that exhibited this
very dramatic spinal curvature by changing
the fluid flow of the cerebral spinal fluid,
and seeing a kind of model of idiopathic scoliosis
in the zebra fish.
And so, if you look at the way it's framed
here in this most recent paper, irregularities
in cerebral spinal fluid flow represent the
underlying cell biological cause of idiopathic
scoliosis, right?
And so, this idea that you need to reexamine
the anatomy, the physiology, and the genetics
in terms of flow.
So, maybe it's medical impact that could really
cause some of the realignment in investigative
and exploratory standards.
And that brings out something that may be
more of interest to philosophers, but I think
it's worth talking about in this context,
which is many philosophers distinguish between
epistemic reasons or criteria, like accurate
representation and pragmatic reasons like
successful medical treatment, and they think
that the epistemic considerations are more
important.
That, you know, it's more important that you
somehow represent things correctly, whether
or not you can change the world or treat people
would be secondary.
But if we remember that investigative reasoning
yields knowledge that's typically categorized
as pragmatic, that's going to suggest that
there are standards that are dependent on
pragmatic criteria in a way that philosophers
have not paid as much attention to.
And so, I think they may need to be blended
together because what we're seeing is that
investigative reasoning is essential in lots
of sciences.
I've talked about developmental biology.
And so, I think we might want to resist pulling
these two things apart, and actually start
talking about them together.
That in many cases, we are finding that a
joint justification, in terms of pragmatic
and epistemic, might be what is going on.
And if so, that might be a way to understand
how you could align the investigative and
explanatory standards for physical approaches
to development.
Instead of the how possible sufficiency that
we saw through a lot of the history, we can
focus on how actually, justified by a combined
pragmatic/epistemic rationale where that rationale
includes the explicit ability to treat medical
pathology.
So, I won't go back over, but this is just
a reminder of us moving through the sort of
renaissance of current physics, through the
history to an interpretation of why that might've
been so, and I'm happy to take your questions
in that regard.
Thank you.
[applause]
Christopher Donahue:
Okay.
So, questions, comments, et cetera?
You'll have to use the microphone.
[inaudible dialogue]
Male Speaker:
So, I don't think you touched on this, but
I'd be curious, if there's any correlation
between people who formally trained in physics
and then crossed into --
Alan Love:
Yeah.
Male Speaker:
-- developmental biology, or really -- or
any of the -- [unintelligible] biological
sciences, and sort of how they described the
challenges, or how they described --
Alan Love:
Good.
Male Speaker:
-- I mean, and sort of influences that a cross-training
might've had on their views of some of these
issues.
Alan Love:
Yeah.
So, I think this is a really important point
because it is quite clear that in many of
these laboratory contexts, the ability to
manipulate the physics is coming out of a
kind of hybrid of having a physicist there,
who has some kind of training -- but that
training is about the manipulation of the
physical variables, not manipulation of the
animal or the plant.
And so, you need a fusion of those two things.
And so, in most of these cases that I've studied,
you have that clearly represented.
Somebody has come into the lab with a physics
background, and has some of that -- but they
themselves are also only able to do what they're
doing because of the experimental expertise
that those working on the model organisms
already have, in terms of how to manipulate
some of the genetics as well.
Male Speaker:
But none of the -- none of the prominent developmental
biologists that you talked about, none of
them have formal training in physics.
Alan Love:
Almost all of the prominent people in these
situations are primarily genetic oriented
in their training, and then they have picked
up the physics through a post doc, or through
bringing something -- somebody else in.
So, there are very few researchers -- Lance
Davidson would be one, but in his case, he
ends up working in engineering more so than
in developmental biology.
Now, this is a really important point for
another reason, and that is that in talking
with some developmental biologists about this
off the record, there are complaints that
some of the physicists who have come in don't
really know how to do the experiments right.
And so, you get this issue about whether or
not the standards are really being met.
And there, you see the genetic standards,
or standards for what counts as a genetic
manipulation and experiment are, in some sense,
governing what will count as a legitimate
experiment, with respect to physical factors.
I think some of that's backing off.
But it's there, and it's there for the reasons
that you talked about, that you have this
differential expertise.
Male Speaker:
So, how far back do you push [inaudible]?
Christopher Donahue:
No, no.
I think this is for the camera --
Male Speaker:
Oh.
Christopher Donahue:
Yeah, this is for the video.
My apologies.
Male Speaker:
So, how far back do you push the line, right?
So, you make a physical block in the heart,
but parts of the heart don't --
Alan Love:
Yeah.
Male Speaker:
-- form, right?
And parts of the heart don't form because
there's a genetic cascade that's a result,
right?
Alan Love:
Yep.
Male Speaker:
So, when do you stop calling it physics, and
you push it back to saying this is a genetic
response?
Alan Love:
Right.
So, this is part of the reason why I see this
project as combining the two.
That is, it's not about sort of fighting is
it really physics?
Is it really genetics?
But it's somehow about putting the two together,
and some of that has to do with time.
That is, how time is organized in the way
you study.
If I start my study here, then I'm going to
look at factors as they move forward.
But I could've started back further, and then,
the causal variables that I want to focus
on could be different.
They could be more -- they could be genetic.
They could be physical, and the like.
What's interesting is that at least in the
different cases that I've looked at, no matter
where you slide that sort of temporal window,
and you can find those interactive dynamics
possible.
In fact, some of the fascinating stuff coming
out of work by Michael Levanitt [spelled phonetically]
toughs on the role of electrical gradients,
I think, is a good example of this.
In symmetry breaking, in particular -- shows
that the physical dynamics can be of a certain
kind -- it can be very early in a process.
I think, at the end of the day, the important
point is not sort of a fight over whether
it's best characterized one way or the other,
but how we construct models that allow us
to put them together, and that that actually
turns out to be somewhat tricky because you
-- and this is a problem with the on growth
and form of the gut paper, which is -- so,
this paper begins by talking about we really
need to combine them.
And then, the whole paper is about the physics
of the gut, and it's not about combining them.
And so, this is, I think, part of the reason
why this is intriguing, as a philosopher,
is, I think, there's a desire to combine them,
but actually doing it is quite tricky and
hard, and that's still being done.
And some of the strategies, I think, involve
choice of windows of time, and how judicious
that is.
Like, you know, if you narrow it in a certain
way, you can actually get a good account of
the back and forth dynamics.
But if you widen it too far, or if you try
to take into account to larger region -- spatial
region of an embryo, or something like that.
But those are -- I mean, it's part of the
difficulty, for sure.
It's a good question.
Male Speaker:
So, your discussion's been about, almost entirely,
embryological development.
And I'm wondering if -- do you or the people
involved in this debate or these controversies
regard embryological development as a special
case of all development, including later development
of a fetus and development of a young child
because --
Alan Love:
Ah.
Male Speaker:
-- the reason I ask this is because --
Alan Love:
Yeah.
Male Speaker:
-- you know, physicians have known for centuries,
if not millennia, that physical forces --
Alan Love:
Yeah.
Male Speaker:
-- relate to development.
You know, a child who doesn't talk will not
end up at age 21 with normal leg bones.
They don't grow because of the physical -- you
know, something --
Alan Love:
Right.
Male Speaker:
-- related to weight bearing and so on.
And there's many other examples, so is this
something special?
Why should it not be the case?
Why should this be special?
Why should it not be obvious that physical
forces are related to some forms of development?
Alan Love:
Well, so I think that the -- so, the recognition
that the forms are related, or that physical
forces are related in some sense to development
has always been there, right?
So, this is part of why it's a puzzle, right?
I mean, in a sense -- all the way back in
the 19th century, people were recognizing,
physical forces play some kind of role.
And that's manifested in different models
over time -- D'Arcy Thompson, Alan Turing,
and these others.
And I think you raise the point that it's
also when you think of development on a longer
life cycle type scale, it's clearly relevant
in these other contexts.
I think it has to do with the experimental
manipulation context of developmental biology.
I think that's one of the key things going
on here is that, the degree to which the community
built up a set of standards for what counts
as an experiment that's legitimate.
That you can say, this experiment gives me
a result I can trust.
And once that standard was set up, then you
had a benchmark that's -- allows you to say,
“Okay, the degree to which I can acknowledge
the physics playing a role is the degree to
which I can show -- similar to the way I've
already shown in genetic manipulations that
it makes a difference in this way.”
And that's a relatively new invention.
Now, in the case of the physical forces for
later stages of, say, human development, or
any animal, for that matter, there, you have
an issue about a different kind of investigative
context that that's not happening in a laboratory
in the same way.
You're often times doing longitudinal prospective
studies, following cohorts.
Again, I think that there's going to be a
question about whether or not the standards
that establish one type of cause are applicable
across the board, but I think that -- the
case that I've been describing, there's this
key element in the recent history that makes
the kind of putting physics at arms' length
-- it helps explain why that happened.
Male Speaker:
So, something that I haven't understood -- maybe
I just wasn't getting it.
It sounds like you're saying the, you know,
the precision tools for looking at the impact
of physical determinants of development weren't
there until recently?
Alan Love:
For --
Male Speaker:
In the modern era.
Alan Love:
For --
Male Speaker:
Now -- you said, now we have more precise
tools to do these experiments.
We didn't have them before.
Alan Love:
Not --
Male Speaker:
I'm not sure why --
Alan Love:
Not so much precise tools.
So, the issue has a lot to do with whether
or not the way you can manipulate the value
of the variables meets this particular strategy
about creating mutants, and then, being able
to recreate them in the same fashion, over
and over again.
It's -- that's the parallel.
So, it's not casual reasoning generally.
It's casual reasoning in genetics.
And it has these particular dimensions that
I think show up in this experimental reasoning,
and that's what was not being done with the
physical forces earlier.
Male Speaker:
So, I'm still a little confused.
Maybe I'm dense, but could you just give an
example or two of things that people are doing
now that measure the effects of physical variables
that couldn't have been done 30 years ago?
Alan Love:
That couldn't have been done 30 years ago?
Okay, so some of it -- so, if we go back to
the case that I described about the cardiac
fluid flow in the zebra fish heart.
Okay?
That couldn't have been done 30 years ago,
in part because it required the ability to
have the high speed camera imaging to be able
to track the flow and the changes in the flow.
And the implantation of the bead might've
been possible, if you had that, but you wouldn't
have been able to reliably track what it was
doing, other than messing things up, I think.
And so, that's the kind of thing I'm highlighting
that's a --
Male Speaker:
Well, you know, I'm thinking that there are
-- there are things that -- maybe they were
done.
I'm just curious about this, but one could've
looked at, decades or centuries ago, in small
-- development of small organisms, the effect
of centrifugal force -- develop -- you know,
development in centrifugal force --
Alan Love:
Ah, yes.
Male Speaker:
-- in space.
We've been going into space --
Alan Love:
Yeah, yeah.
Male Speaker:
-- and taking organisms there since 1960 --
Alan Love:
No, no.
Male Speaker:
-- surely, somebody must've been looking at
the development --
Alan Love:
They did.
Male Speaker:
-- of organisms that were weightless.
Alan Love:
Actually, they did.
So, here, you have an issue about whether
an experiment has been done, and whether a
community has coalesced around a set of methods.
So, in the 18th century, I'm going to forget
his name -- he designed basically a water
wheel for plant growth, and was able to show,
by changing the gravity dynamic, that it changes
the way the plant grew.
So, he establishes a physical force effect
on the development of the plant.
So, yes, you're right, you can, you know,
show that.
That doesn't spawn a sort of community of
research working on it.
It's kind of a one-off.
And I think one of the things that's important
here is about how communities develop around
certain standards.
And that's true, especially of a couple figures,
if you think about the people in the early
20th century, who we highlighted -- people
like D'Arcy Thompson or Alan Turing, these
are people who kind of -- they're independent
geniuses.
They're often times working across different
fields.
They're not well ensconced in any particular
community.
And so, I think that this development of a
community standard is an important part of
the story.
Not it was somehow physically impossible to
ever do an experiment of that kind, though
clearly, some of the technological innovations
are, you know, dramatic.
I think it's also a story about the social
organization of the research that's important.
I don't know if that --
Male Speaker:
No, I think -- and it raises a lot of thoughts
because what I see in science now is a lot
of fad science.
You know, ideas get ingrained.
They may be the wrong ideas.
They may not be the best ideas, but they just
take hold.
It's like an epidemic of ideas, and then a
whole bunch of scientists waste time doing
minimalist research, and not addressing big
questions.
I'm an infectious disease guy.
I see that all the time.
Alan Love:
Yeah.
Male Speaker:
It's a -- you know, sociological phenomenon,
I guess.
Something about group behavior.
Alan Love:
I do think that you -- I mean, one of the
things that is true of post-World War II science
that starts to be funded centrally by the
federal government, you clearly have a different
dynamic than you had prior to that, when you
have different funding structures.
And so, you're going to have susceptibility
to group think and things like that, that
emerge as the community gets larger and is
reliant upon, say, a central source of funding,
or something like that.
So, it's not going to be the case that simply
a community has coalesced, or is chasing particular
item that that's somehow automatically justified.
I think, in the present case, what's of interest
to me is the fact that you have something
that has a long history of people thinking
this is important and it's interesting.
People offering these mathematical models,
and yet, there's a -- this really distinctive
phase transition that happens where all of
a sudden, it kind of fades.
But it fades, in part, right at time when
this set of experimental tools really solidifies
the community of developmental biology.
Which, of course, include model organism entrenchment,
you know, in terms of which models you're
committed to working with, and the same thing.
So, that's not going to be the same if I move
into infectious diseases or other places.
There's going to be different historical dynamics
that will create that, and that does create
fads.
I'm sure the developmental biologists in the
room will say there's plenty of fads to highlight
as well.
Male Speaker:
Can I say this one last question?
Alan Love:
Yeah.
Male Speaker:
With respect to this, perhaps, group think,
or people going off in trends and fashionable
areas of thinking -- reasons of thinking,
what do you think is involved in that?
Is it professional societies, or disciplinary
training, or disciplinary identity?
Why does this happen?
Because most of us -- at least nowadays, most
of us are individual scientists.
We get individual R01 type grants.
We don't necessarily have to sheep in a big
herd.
What's making this happen, whereas it didn't
happen very much in the 1800s?
Or to a much -- to a lesser extent.
Alan Love:
To a lesser extent.
I mean, I think that's a really good sociological
question that I can't give a good question,
in short order, in part because I'm not a
sociologist, and so don't know well enough
the kind of social dynamics that would be
relevant.
But what I do think is that the kinds of things
that we're highlighting for how groups of
scientists might behave are clearly going
to not be only manifested in science.
There are going to be patterns of social behavior
that humans adopt, and that once we have the,
you know, relevant analytical tools, you know,
we can make the comparisons about why -- under
certain dynamics like the last, say, 30 or
40 years, you see this trend occurring in
a way that you didn't see it so visibly before
that.
Male Speaker:
I think it's linked to specific technological
breakthroughs, right?
Alan Love:
Yeah.
Male Speaker:
I mean, PCR, CRISPR, cheap sequencing.
These things drive specific, you know, it's
looking for your keys under the lamppost,
even though --
Alan Love:
Yeah.
Male Speaker:
-- you lost them over there because the light's
here.
Alan Love:
The light's here.
Male Speaker:
That story.
I think these -- some of these fads are driven
by -- there's all of a sudden a new way to
look at the problem you've been tackling for
a generation.
And so, everyone moves to this new technology
because they haven't -- they didn't have that
access to that way of answering a question
before.
And so, I think some of it's not even sheep
mentality, it's just like all of a sudden,
there's a release of tension.
You know, you've been blocked at addressing
this question for so long that all of a sudden
you can do it, everyone moves into that area
because they can for the first time.
Male Speaker:
It sometimes causes resentment, which is what
the solid data --
Alan Love:
Yeah.
[talking simultaneously]
Yeah, that's right.
That's absolutely right.
Male Speaker:
And that's this idea that technology is driving
this group thing is also -- applies for 18th
century optics.
[inaudible dialogue]
Like microscopy.
Male Speaker:
Yeah, most of the physicists that get into
developmental biology, there were all microscopists.
They were developing new ways to look.
Male Speaker:
Yeah.
Male Speaker:
They weren't manipulating.
Alan Love:
Right.
They weren't manipulating.
Male Speaker:
They were just looking.
Alan Love:
Right.
Christopher Donahue:
So, any -- we're slightly over time.
So, any further quick questions?
All right.
Thank you very much for coming, and it was
a wonderful talk.
Wonderful questions.
Thank you.
Alan Love:
Thank you.
[applause]
[end of transcript]
