Kauffman, Stuart A.

"Dueling Selectively With Darwin,"

Personal Communication, The Scientist, 10

August l987.

(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

selection, Stuart."

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

see.

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

orderly fashion?

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

selection.

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

correct.

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

emerging.

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.