Olga Lepieszynska prosila o zamieszczenie, co z przyjemnoscia spelniam
cz
;-)
PS. OL jest bardzo lagodna niewiasta, ale jak donosi moj kontakt operacyjny z dziewiatego kregu piekiel, Trofim Lysenko wespol ze Stuartem A Newmanem i MIT Press szykuja kolejna prowokacje wymierzona w Richarda Dawkinsa. Bedzie ciekawie...
The Scientist
Volume 19 | Issue 12 | Page 20 | Jun. 20, 2005
[
www.the-scientist.com/2005/6/20/20/1do www dostep jest wolny, nalezy tylko sie zarejestrowac]
The Uncertain Future for Central Dogma
Uncertainty serves as a bridge from determinism and reductionism to a new
picture of biology
By Arnold F. Goodman, Cláudia M. Bellato and Lily Khidr
Kenneth Eward/BioGrafx/Photo Researchers Inc.
Nearly two decades ago, Paul H. Silverman testified before Congress to
advocate the Human Genome Project. He later became frustrated when the
exceptions to genetic determinism, discovered by this project and other
investigations, were not sufficiently incorporated in current research and
education.
In "Rethinking Genetic Determinism,"1 Silverman questioned one of the
pillars of molecular genetics and documented the need for determinism's
expansion into a far more valid and reliable representation of reality. He
would receive correspondence from all over the world that reinforced this
vision.
Silverman firmly believed that we needed a wider-angled model, with a new
framework and terminology, to display what we know and to guide future
discovery. He also viewed this model as being a catalyst for exploring
uncertainty, the vast universe of chance differences on a cellular and
molecular level that can considerably influence organismal variability.
Uncertainty not only undermines molecular genetics' primary pillars of
determinism and reductionism, but also provides a bridge to future research.
PILLARS CHALLENGED
Arnold Goodman (left) is an associate director of the Center for
Statistical Consulting at the University of California, Irvine. Cláudia
Bellato (center) is an independent researcher at CENA, University of Sao
Paulo, Brazil. Lily Khidr (right) is a PhD candidate at UC-Irvine. They
dedicate this article to the memory of Paul Silverman and thank Nancy, his
wife, for her assistance.
Various commentaries detail deviation from determinism within the cellular
cycle. Here we use the term cellular cycle not in the traditional sense, but
rather to describe the cyclical program that starts with gene regulation
through transcription, translation, post-processing and back into
regulation.
Richard Strohman at UC-Berkeley describes the program in terms of a complex
regulatory paradigm, which he calls "dynamic epigenetics." The program is
dynamic because regulation occurs over time, and epigenetic because it is
above genetics in level of organization.2 "We thought the program was in the
genes, and then in the proteins encoded by genes," he wrote, but we need to
know the rules governing protein networks in a cell, as well as the
individual proteins themselves.
John S. Mattick at the University of Queensland focuses upon the hidden
genetic program of complex organisms.3 "RNAs and proteins may communicate
regulatory information in parallel," he writes. This would resemble the
advanced information systems for network control in our brains and in
computers. Indeed, recent demonstrations suggest that RNA might serve as a
genetic backup copy superseding Mendelian inheritance.4
Gil Ast of Tel Aviv University writes: "Alternative splicing enables a
minimal number of genes to produce and maintain highly complex organisms by
orchestrating when, where, and what types of proteins they manufacture."5
About 5% of alternatively spliced human exons contain retrotransposon Alu
sequences. These elements represent an engine for generating alternative
splicing.
Thus we see a genetic control system regulated by protein products, RNAs,
and interventions from DNA itself. Yet throughout, the consideration of
genetic uncertainty as a bridge to cellular behavior is conspicuously
absent.
Genetic reductionism, the other pillar of molecular genetics, has many
challengers. Among them is Stephen S. Rothman at UC-Berkeley, who described
the limits of reductionism in great detail within his comprehensive and
well-constructed book.6
A more recent publication by Marc H.V. Van Regenmortel at France's National
Center for Scientific Research updated this assessment by discussing not
only the deficiencies of reductionism, but also current ways of overcoming
them. "Biological systems are extremely complex and have emergent properties
that cannot be explained, or even predicted, by studying their individual
parts."7
NEW CELL MODEL
Molecular genetics appears to be at a crossroads, since neither determinism
nor reductionism is capable of accurately representing cellular behavior. In
order to transition from a passive awareness of this dilemma to its active
resolution, we must move from simply loosening the constraints of
determinism and reductionism toward a more mature and representative
combination of determinism, reductionism, and uncertainty.
To facilitate this expansion, we propose a model for the cellular cycle.
Although only a framework, it provides a vehicle for broader and deeper
appreciation of the cell. The figure on page 25 provides a novel structure
for understanding current knowledge of the cycle's biological stages, as
well as a guide for acquiring new knowledge that may include genetic
uncertainty.
Organismal Regulation: The organism specifies its cellular needs (bottom
red) for the cell to act upon. It converts the comparison of proteins with
organismal needs into metabolic agents. The organism then defines its
cellular needs (top red). It employs metabolic effects to alter the
extra-cellular matrix and signal other needs.
Cellular Regulation: Within the bounds of a cell's membrane, cellular needs
transmission (top blue) directs the cell in various ways, including
proliferation, differentiation, and programmed cell death. It uses such
factors as receptors and enzymes to yield molecular messengers. In the
cell's nucleus, chromatin remodeling (bottom blue) then rearranges DNA
accessibility by uncoiling supercoiled DNA and introducing transcription
factors.
Transcription: Transcription (left green) DNA serves as the template for
RNAs, both regulatory sequences and pre-messenger RNAs. It transcribes
polymerases and binding partners into heterogeneous nuclear RNAs.
Pre-messenger RNAs then undergo highly regulated splicing and processing
(right green). They turn pre-messenger RNAs into mature messenger RNAs.
Translation: Within the cytoplasm, messenger RNAs and ribosomes translate
2D-unfolded proteins (left magenta). Secondary structuring and thermodynamic
energy (right magenta) then enable physical formations that complete the
process with folded proteins and oligonucleotides.
Postprocessing: Again within the cytoplasm, tertiary structuring and
modification (top aqua) use assemblers, modifiers and protein subunits to
supply regulated proteins. Then feedback regulation (bottom aqua) produces
heritable gene expression from small RNAs, proteins and DNA. The proteins
and gene expression, rather than being an endpoint, now begin the whole
process over again by signaling other cells, altering and maintaining the
genome, and editing RNA transcripts.
CELL-BEHAVIOR BRIDGE
Model for the Cellular Cycle
Click for larger version Click for larger version
Helen M. Blau was a keynote speaker at the recent UC-Irvine stem-cell
symposium in memory of Paul Silverman and Christopher Reeve.8 She observed:
"Where we look and how we look determine what we see." Although only a brief
prescription, we now propose an approach to the exploration for uncertainty
that involves both where we look and how we look. We examine those
cellular-cycle outputs having a relatively high likelihood of diversity and
its frequent companion, uncertainty.
As an example of exploring for uncertainty in a cellular cycle, consider the
following example: Suppose an organismal regulatory program for cellular
differentiation might alter the signaling milieu in the extracellular
matrix. The signal is internalized by a cell, which might, in turn, alter
transcription, produce mature messenger RNAs, produce the 3D-folded
proteins, and feed back to alter gene expression for all daughter cells.
Now suppose the ECM signaling milieu is altered with a probability p1; the
signal is internalized by a cell with a probability p2; transcription will
change with a probability p3; mature mRNAs are produced with a probability
p4, producing the 3D-folded protein with a probability p5 and altering
heritable gene expression with a probability p6. The probabilities p2, p3,
p4, p5, and p6 are all conditional on results from the step preceding them,
so that the resulting probability of altered heritable gene expression is
the product of all of them. Although this probability may be small, is it
not preferable to know its form and to later estimate it, than to simply
ignore its existence?
When we consider all possible stage alterations, the diversity of outputs
and complexity of our probability calculations will increase. If we also
consider all possible interactions, the diversity of outputs and complexity
of probability calculations will increase quite substantially.
The implications reach far beyond the regulation of a single cell or
organism. Sean B. Carroll of the University of Wisconsin, Madison,
summarizes evolutionary developmental biology,9 invoking Jacques Monod's
landmark Chance and Necessity, and the Democritus quote upon which it is
based: "Everything existing in the universe is the fruit of chance and
necessity."
Why wouldn't chance also be included in our observations of biology at the
molecular level?
