Kauffman, Stuart A.
"Dueling Selectively With Darwin,"
Personal Communication, The Scientist, 10
(Kauffman is a professor of biochemistry
and biophysics at the University of
Pennsylvania Medical School. He is also the editor
of The Journal of Theoretical Biology, and a recent
winner of a MacArthur Foundation "genius" grant.)
Turning points in my intellectual life have never
been welcome; I always seem to resist them until
forced to do otherwise. One such passage occurred
some 10 years ago, as I was walking one spring
morning in the Downs of southern England with the
evolutionary biologist John Maynard Smith and his
biologist wife Sheila. John, remarking on our
proximity to Charles Darwin's home, chided me
gently: "You really must think about natural
How his comment shocked me! Of course I should
think more about it! But I had spent more than a
decade exploring the idea that much biological
order might reflect inherent self-organized
properties of complex systems, even in the absence
of selection. Since Darwin, of course, we have
come to view natural selection, sifting out rare
useful mutations from myriads of useless ones, as
the sole source of order in biological systems.
But is this view correct? Might not complex systems
spontaneously exhibit order? I had begun to ask
this question in medical school, when Francois
Jacob and Jacques Monod published their famous
operon model. Biologists began thinking of the
genome as a kind of biochemical computer, in which
a gene or its products turn other genes on or off.
This view, first worked out in bacteria and viruses
and now being extended to eukaryotes, implies that
cell differentiation in development from the
fertilized egg is mediated by a complex genetic
regulatory network that coordinates synthetic
activities of the roughly 100,000 genes in each
cell type of a higher eukaryote. By current
criteria, a mammal has on the order of 200 to 300
distinct cell types. The regulatory network is
thought to control gene expression patterns in
these different types.
To analyze the problem, it's useful to simplify and
imagine that each gene can only be active or
inactive. Think of a genomic regulatory network as
a computer with an on-off switch representing each
gene's activity. Since each gene can be on or off,
there are 2/100,000 possible patterns of activity--
a number large enough to catch the attention of
even Carl Sagan.
How are we to understand a system with 100,000
genes switching one another on and off? In part,
by our natural bent for reductionistic analysis.
But even should we succeed in analyzing the
detailed circuitry in the face of the genome's
scrambling the regulatory system in evolution, we
need to integrate our knowledge and understand what
features of that circuitry mediate the order we
At this point my old interest in self-organization
suggested a new viewpoint. I had studied logic
before medicine; hence the idea of "logical
switching circuits" seemed a reasonable way to
approach genomic networks. The question I posed
early on was whether the richness of connectivity
in a genomic network--that is, the number of genes
that directly regulate any specific gene--might
have an important bearing on the spontaneous
emergence of orderly behavior in model genetic
networks. To my delight, the answer was yes.
This fact still astonishes me. Consider a model
regulatory system with, say, a mere 10,000 on-off
genes. Hook the genes together randomly, with each
gene directly regulated by only two other genes.
Then assign to each gene at random one of 16
possible logical switching rules. Since such a
network, which has both random "wiring diagrams"
and random "logic," is supposed to model a real
genomic system, once it is constructed its
structure is fixed.
It is therefore a random sample drawn
from the pool of all model genetic
regulatory systems built with the same constraints
on numbers of genes and numbers of inputs per gene.
Do such random systems typically behave in an
The surprising result I found over 20 years ago is
that if each gene has only a few direct input
genes, which is true in bacteria and viruses and
may well be true in eukaryotes, then a system with
10,000 on-off genes settles down to one of only a
few recurrent patterns of gene expression.
Those patterns are also stable to perturbation: If a
gene's activity is transiently reversed, the system
typically returns to the same pattern. If we think
of a recurrent pattern of gene activity as a cell
type in the repertoire of the genomic system, then
these "random networks" exhibit an order that is
strikingly predictive of features seen in
organisms. The cyclic patterns are stable to
perturbation, mimicking the homeostatic stability
of cell types.
If a cyclic pattern is a cell type,
the typical features of these networks is that any
cell type can differentiate directly into only a
few neighboring cell types, and from those to a few
others. We know that the ontogeny in all higher
eukaryotes takes place by just such sequences of
branching patterns of cell differentiation. Is
this due to natural selection? Or is it a
universal feature of ontogeny despite selection?
I have wanted to believe that such deep properties
of ontogeny as the prevalence of branching pathways
of differentiation reflect the self-ordered
properties of complex genomic systems, not
More generally, the fact that randomly
assembled model genomic systems exhibit marked
order even roughly reminiscent of that found in
organisms strikes a blow at our world view, in
which selection is the sole source of order in
biology. I think that view is wrong. Complex
systems exhibit far more spontaneous order than we
have supposed, an order evolutionary biology has
ignored. But that realization only begins to state
our problem, for Maynard Smith's admonition is
We must think about natural selection.
Now the task becomes much more trying, for we must
not only envision the self-ordered properties of
complex systems but also try to understand how such
self-ordering interacts with, guides and constrains
natural selection. It's worth noting that this
problem has never been addressed.
The challenge has set me thinking about how
selection interacts with such self-ordered
properties. This job is hardly begun, but several
points are clear. First, two kinds of "complexity
catastrophes" tend to limit the capacity of
selection to attain genomic regulatory systems that
are extremely untypical in the ensemble of possible
genomic systems. Classical population genetic
results have long hinted at a limit to selection's
power to achieve "maximally fit" genotypes in the
face of a constant mutation rate as the number of
loci in the genomic system increases. Eventually,
mutation overwhelms selection and disperses an
adapting population away from optimal genotypes.
But a second limitation on selection seems to be
Natural selection is a kind of combinatorial
optimiation process. Typically such processes face
a rugged, multipeaked "fitness landscape" due to
conflicting design requirements. Under strong
selection, a population will at least climb to a
local peak. Simon Levin at Cornell and I found
recently that as genetic networks under selection
become more complex, attainable fitness peaks
become lower! Worse, this appears to be a general
tendency in any combinatorial optimization process.
As the entities under selection become more
complex, the optima that can be reached become
progressively more mediocre. Does this mean that
even strong selection cannot achieve highly complex
and precise systems?
Perhaps selection results in organisms that can
adpat well because they "adapt on" fitness
landscapes that escape these tendencies. What in
the post-Darwin world this might imply has me even
more deeply puzzled.
Dueling with Darwin? Not really. Embracing him,
and moving on.
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