|
A
peer-reviewed electronic journal published by the Institute for Ethics and ISSN
1541-0099 23(1)
– December 2013 |
Book review: James
A. Shapiro’s Evolution: A View
from the 21st Century
Thomas Johnson
Graduate
School of Humanities and Social Sciences
University
of Melbourne
Journal of Evolution and Technology - Vol. 23 Issue 1 – December 2013 - pgs 61-64
This1
is an extraordinary book in many respects, not least for its sheer number of
references. While the ideas are presented in four parts over a mere 147 pages
of the main text, the references number no less than 1162. As the material can
often be quite technical, the author has included an extensive glossary to help
non-specialist readers. He wisely prefaces the book with a note assuring those
readers that they can skip the very technical sections and read only the
Introduction, along with the beginning and concluding sections of each part.
Those wishing to explore particular topics in more detail are invited to visit
a companion website for the book or the author’s own website, both of which provide
suggested readings for a general audience. So the book goes to considerable
lengths to cater for specialists and general readers alike. As the bulk of the
voluminous references consists of research presented in specialist journals and
books, the technical discussions are thoroughly and meticulously documented.
And the opening and closing sections of each part are written in a clear and
coherent style that will undoubtedly be appreciated by the non-specialist.
The
broad perspective implied in the book’s title could easily mislead readers
unfamiliar with James Shapiro’s work. As a specialist in molecular biology, his
interest in evolution has mainly focused on microbial organisms and cells, and
while occasionally describing or theorizing about the evolution of plants,
insects, and mammals, including humans, this book retains a focus on molecular
biology. But anyone interested in evolutionary processes will learn much, as
the book provides very substantial evidence for the neglected but vital
activities at the cellular level that are already known to apply in the growth
and evolution of more complex organisms.
When
the precise structure of DNA was discovered in the 1950s, Darwin’s theory was
at last furnished with a clearly identifiable means of heredity that could
conceivably account for all biological evolution. This set a new theoretical
paradigm that came to be known as neo-Darwinism –
best represented in the “gene’s eye view” proposed by William Hamilton but
later popularized by Richard Dawkins. However, this attempt to reduce the
source of evolutionary change to a single mechanism has always been difficult
to reconcile with the behavior of organisms observed in the laboratory or in
their own natural habitats. These observations have led to the formulation of
alternative theories that provide a much richer account of the myriad ways in
which organisms themselves actively alter the structure of their environments.
By making the environment more conducive to their own development, or that of
their progeny, organisms often contribute to their own survival in ways that
the “gene’s eye view” cannot adequately capture.
Consistent
with similar arguments by proponents of systems biology, Shapiro points out
that genes alone are incapable of any action, let alone self-replication. The
activities involved in replication, repair, and the production of novel
functions are produced by “natural genetic engineering.” Philosophers in
particular may be disturbed by that description in the belief that it implies
the need for an engineer. However, Shapiro stresses that these adaptive behaviors
are not reducible to the effect of any single attribute or component in the cell,
but typically rely on the co-ordinated actions of different functional
elements. Many of the technical sections go into great detail explaining how
cells function and develop in much the same way as any intelligent organism,
i.e. by sensing the environment, transmitting signals, and even
“decision-making.”
In
Part I, Shapiro uses several apt examples to illustrate how cells exhibit this
apparent intelligent agency. Drawing on Jacques Monod’s experiments, which
began even before the structure of DNA was properly understood, Shapiro
describes how bacteria that had two types of sugar available – one promoting
high growth (glucose), the other low growth (lactose) –
consistently consumed the high-growth sugar before pausing and then consuming
the low-growth type. This was observed even when the two types were mixed in
different proportions. At first glance, a biological process that produces such
a predictable result from only two possible responses would seem more plausibly
interpreted as a simple case of tropism, as when a plant grows towards the
strongest light source, or its roots grow towards the richest source of
nutrients. Even more parsimoniously, such processes could be seen as analogous
to purely physical laws, for example as similar to the way metals respond to
magnetic forces. However, discoveries revealing the numerous, complex actions
behind this bacterial response show that it is more analogous to the logical
Boolean circuits in computer programs.
These
discoveries have shown that sugar metabolism in the E. coli bacterium is
in fact governed by “at least five general principles of cellular information
processing and communication within the genome” (9). Shapiro’s description of
these principles is quite technical but essentially and effectively shows how
they involve sensing and signaling between proteins and other molecules,
ultimately resulting in responses that are conditioned by the data obtained.
This is also well-illustrated in Shapiro’s example of how DNA damage is
repaired in a two-stage process: during replication, misplacement of a
nucleotide in the strand is detected by a sensory mechanism which then
activates the correction procedure. Any subsequent errors are detected and
fixed by different proteins performing dedicated tasks in sequence.
Shapiro
also cites the phenomenon of programmed cell death as an example of
“decision-making,” as it is not a hard-wired response but the result of
variable signaling actions between and within cells. Programmed cell-death
allows bacteria to “maintain genetic stability and ensure survival of a
proportion of the cells in multicellular populations” (23). Cells evidently use
feedback mechanisms that regulate their functions. And many of these mechanisms
may work in ways that are consistent with basic Boolean operations. So in these
respects at least, Shapiro’s examples present a convincing case that cellular
growth and reproduction rely on actions of sensing and signaling that enable
adaptive responses. While cells do not possess the sensory apparatus of complex
organisms, or the brain that allows genuine language and self-reflection, they
evidently use cognitive processes that resemble those of artificial
intelligence.
Progress
in artificial intelligence, particularly in the design of “neural” algorithms,
shows that the activity of learning is itself an evolutionary process that is
not confined to capacities in the neo-cortex. Artificial analogues of these
biological learning mechanisms enable robots to discover an optimal series of maneuvers
to reach a specific goal. With continual feedback obtained through trial and
error, the robot progressively updates its original program, effectively
“overwriting” it with new conditional rules. Despite the progress and
respectability of this evolutionary paradigm as modeled by artificial neural
networks, the dominant theory among geneticists has been that “the genome is a
read-only memory (ROM) system subject to change by stochastic damage and
copying errors” (28). However, the overwhelming evidence that Shapiro and other
molecular biologists have accumulated over several decades simply cannot be
accommodated by that theory.
This
“Central Dogma of Molecular Biology” as Crick was hastily content to name it,
was always problematic as it was formulated on the basis of limited
observations about protein synthesis. But major revelations in understanding
the workings of the genome and epigenetic functions now warrant a significant
theoretical shift in viewing the genome as “a read-write (RW) memory system
subject to non-random change by dedicated cell functions” (28). It is worth
noting that this perspective is not entirely new or as radical as it might
sound, as it coheres with earlier conceptions of evolutionary mechanisms such
as that proposed by Baldwin at the end of the nineteenth century. While Shapiro
does mention these earlier views, readers would have benefited from some
reference to the most prominent of them, as many of their insightful
observations have now been rediscovered in the light of our contemporary
knowledge.
The
central problem faced by adherents of the “Central Dogma” is explicit in
Shapiro’s use of the computer analogy to indicate that genome changes are
largely driven by self-regulating cellular activities and therefore do not rely
on random mutations to evolve. And while Shapiro remarks at the very beginning
of the book that “the accidental, stochastic nature of mutations is still the
prevailing and widely accepted wisdom on the subject” (1), this is something of
an exaggeration and is liable to add to a common misconception about randomness
in evolutionary change. Even the most prominent popularizers of the
neo-Darwinist view2 recognize that organisms themselves actively
restructure their environments, thereby creating selection pressures that
favour the evolution of genotypes best adapted to that changed environment.
Thus, while insisting on random mutations as the main source of
evolutionary change, the conventional view also acknowledges that the effects
of those changes need not be random.
To
some extent then, in recent decades the modern synthesis has itself been forced
to loosen its central tenets to better account for the observed frequency of
genetic selection pressures created by organisms themselves. The problem with
the prevailing view is not that it fails to recognize the role of non-random
changes in evolution. Rather, it fails to appreciate how such processes at the
cellular level are essential to the normal life cycle of organisms. In terms of
Shapiro’s computer analogy, neo-Darwinism fundamentally underestimates the
read-write capacities of living cells.
It
is strikingly ironic that strict adherents of the modern synthesis should have
such difficulty in giving due recognition to these well-observed capacities,
especially given that they are fully consistent with a Darwinian account of
heritability informed by the functional properties of DNA. After all, these
capacities are vital functional mechanisms and as such are themselves genetically
inherited. So there is no sense in which their operation can be seen as
violating either Darwin’s theory or modern genetics.
In
Part II, Shapiro gives very detailed descriptions of how these vital functions
operate as part of the normal life cycle. He does an admirable job in
attempting to explain the complex nature of these interactive processes. While
the glossary certainly helps to guide the general reader through this
relatively long section, many will find the technical discussions difficult to
follow. However, the example of the mammalian adaptive immune system, while no
less technical in description, is particularly instructive and its significance
can be easily appreciated from Shapiro’s introductory summation. This immune
response can only evolve and work efficiently by quickly learning to recognize
and act against “a virtually infinite and largely unpredictable range of
invaders” (66). As Shapiro notes, DNA in the germ cells can accommodate only a
limited range of proteins, so resistance to all these potential threats could
not be inherited via reproduction. But neither could it be achieved through an
unstructured trial and error process testing each potential antibody. Instead,
rapid immunity is reached by “targeted mutagenesis” where DNA is rearranged by
molecular processes that vastly increase the range of potential antibodies and
thereby accelerate the evolution of successful ones.
Like
the adaptive mechanisms involved in the development of the immune response, the
genome can also be restructured by horizontal DNA transfer, e.g. from viruses and
by symbiogenesis, where different organisms effectively pool their genetic
resources for mutual benefit. As these terms suggest, both processes involve
growth and evolution through genetic combinations that do not result from
mutations. As the effect of these alternatives to reproductive genome
transmission have been largely neglected until recently, in Part III Shapiro
discusses their likely role in the evolutionary history of bacteria, plants,
and animals. And in discussing how cells themselves evolved these various
capacities to actively alter genomes, he notes that modern genome data
sequencing has revealed that proteins share functional domains. Clearly, this
facilitates and accelerates major evolutionary changes. Adapting protein
functions to new activities would not have to occur in a random, piecemeal
fashion, as numerous versions of already existing functional segments will be
readily available for rearrangement into novel combinations.
The
fourth and final part delves further into the means available for generating
novelty, but from a more expansive and long range view of evolution that is
best captured by use of another analogy – that of systems engineering. Here,
readers might pause to wonder if Shapiro has suddenly abandoned the earlier
read-write computer analogy. But it appears that he intends both analogies to
describe actions at different levels of detail. Cells do not simply receive and
copy genomic information but actively rewrite it. Though valid and useful for
explaining how cells are agents of evolution, this information-processing
analogy does not fully account for the often simultaneous, co-ordinated actions
needed to generate and stabilize the structure of novel functions. So the
systems engineering analogy is indeed an apt one and of course coheres closely
with the well-established theoretical approach of systems biology.
From
the vantage point of this more comprehensive systems perspective, Shapiro
sketches the idea that many of the cellular and molecular mechanisms
responsible for reorganizing genomic functions may also play a heuristic role
by orienting the placement of particular recombinations. Again, this idea not
only coheres well with research in systems biology, but also with the Evo-Devo
research program, the niche-construction process and some interpretations of
the rediscovered Baldwin Effect.
Shapiro
calls for an urgent paradigm shift that gives due recognition to the
evolutionary role of cellular activities and it is certainly well overdue.
However, in noting that the journal Nature Immunology dedicated its August
2010 edition to “decision-making in the immune system,” he takes this an
indication that these ideas have “gone mainstream” (137). This book builds on
an already extensive body of work over many decades and fully lives up to its
name in providing a view of evolution that should greatly expand future
research into this new century and beyond.
Notes
1. All
page references in the text are to Shapiro (2011).
2. In discussing the research of Shapiro and others,
Evelyn Fox Keller (2000) refers to a paper by Richard Dawkins entitled “The
Evolution of Evolvability.” Here, Dawkins himself remarks that he has “been led
to think differently as a result of creating and using computer models of
artificial life” (Keller 2000, 201). This led him to propose an account of
“higher level selection, a selection not for survivability but for
evolvability” (218).
References
Keller,
E. F. The Century of the Gene. 2000. Cambridge, Mass: Harvard University
Press.