Synthetic Biology and
Supercomputers - innovation approaches
and methods
Salvatore Santoli
INT - International Nanobiological Testbed Ltd
c/o LBIC - London BioScience Innovation Centre
The subject of this
paper is some topics of area "Synthetic biology" and area "Supercomputers",
that are close connected with each other methodologically.
Nothing in life is to be feared.
It is only to be understood.
Marie Curie
As a
nanobiologist with a strong interest in computational nanoscience and a bent
for looking at Biology through theoretical physical glasses, I have identified
the basic problems involved in the formulation of the research plans of Synthetic Biology and its branch Synthetic Life - concretely emerging
very adventurous paths undertaken by human mind - as the problem of revisiting
and possibly redefining the concept of computation. An old adage warns that "computing is not number; it is insight",
but why should this adage be recalled, and
what and where would the source of proper insight be? Indeed, an
overview of the programs, their historical roots and some comments on such kind
of research, considered as extreme
engineering and by somebody as a scary research plan aiming even at
crossing the line where Man starts playing at God, will make clear the whys of my standpoint and the roots of
my proposition.
Synthetic Biology is a new area of biological research that combines science and engineering. This term encompasses a variety of different
approaches, methodologies and disciplines, and many different definitions
exist. What they all have in common, however, is that they see "synthetic biology" as the design and
construction of new biological functions and systems not found in nature. The
conception of this idea already has a history. This program has been rapidly
developing indeed in the recent years, but the concept dates back to 1974, when
the Polish geneticist Waclaw Szybalski introduced the term "synthetic biology", writing:
Let me now comment on the question "what
next". Up to now we are working on the descriptive phase of molecular
biology. ... But the real challenge will start when we enter the synthetic
biology phase of research in our field. We will then devise new control
elements and add these new modules to the existing genomes or build up wholly
new genomes. This would be a field with the unlimited expansion potential and
hardly any limitations to building "new better control circuits" and
..... finally other "synthetic" organisms, like a "new better
mouse". ... I am not concerned that we will run out of exciting and novel
ideas, ... in the synthetic biology, in general.
The
synthesis of genes has already reached a high level of success. In 2010,
J.Craig Venter's group*) announced they had been able to assemble a
complete genome of millions of base pairs, to insert it into a cell, and to
cause that cell to start replicating. This
arose some basic concerns about what Venter and others in the new field of
synthetic biology were doing. First, the objection was raised that one of these
synthetic organisms might escape from the lab and run amok. And, second, it was
warned by some fearful people that this kind of work would cross a line where
humans would start playing at God**. As to questions concerning biosecurity and
biosafety there has been an involvement also of stakeholders and intellectual
property experts, and the IASB -
International Association for Synthetic Biology*** launched an initiative
for self-regulation, suggesting that
specific measures should be implemented by Synthetic Biology industries.
Symposia were also organized to discuss the societal issues and possible
policies of such a research/development effort.
There's
now a wide literature concerning the synthesis of quite complex genes with the
aim at causing existing cells to behave differently from their natural behavior
as to reproduction and basic properties, but there's also an approach based on
the building of organs and organ systems replacing in cells the natural organs
to obtain different products in upper-rank living systems. An example of this
engineering-minded approach is the work of Chris Voigt who succeeded in the
redesigning of the Type III secretion system used by Salmonella thyphimurium to secrete spider silk proteins, i.e. a
strong and elastic material, instead of its own natural infectious proteins.
While all
such approaches are based on the use of natural members of living matter, the
special approach to Synthetic Biology that plans to build living systems
through full synthesis from chemicals is called Synthetic Life. The most recent
success along this pattern of thinking is an attempt at creating a new organism
by replacing the genome in an existing natural cell with a different genome
created by gene synthesis. This has
been achieved with the creation of Synthia in 2010. But what all such
approaches share necessarily is a mathematics and models for designing and
developing the realizations envisaged, i.e. the fundamentals for creation of a
proper technology as the basis for the engineering design and manufacturing of
biosynthetic products. Stated otherwise, the key concepts toward the foundation
of a branch of Biology that could be dubbed "biological engineering" would be the standardization of biological
parts and of any hierarchical abstraction process allowing these parts to be
used to build in a controlled way increasingly complex synthetic systems.
Many kinds of mathematics - stochastic differential equations, partial differential
equations, ordinary differential equations, integral-differential equations,
and even graph theory - have been exploited for such tasks. Multiscale models
of gene regulatory network have been developed for Synthetic Biology
applications. Simulations have been used that model all biomolecular
interactions in functions like transcription, translation, regulation and
induction of gene regulatory networks, guiding the design of synthetic systems.
And provisions have been made for accurate measurements. But all such attempts
have been carried out on the basis of a computing concept which is supported by
gate-logic based computers, mainly of very high power of computation as to
speed and massive parallelism of data processing. Now, it has been shown that
such purely syntactic - i.e. not semantic - computing systems are hopeless in
supplying a definite model even for a relatively simple problem of prediction
of protein folding on insertion of further amino acids, the increasing
computing power of such tools giving rise just to an increasing and
disorienting multitude of models as a
thick fog on the way to solve the problem. Moreover, biological evolution from
the very few hundreds of bits on the primeval Earth up to the complexity of
human brain has been shown to have occurred in quite an extralogical, heuristic
way: Nature appears to work as a tinker, not as an engineer, and by so doing
she computes well beyond Bremermann's
limit, i.e. the limit in information processing rate for any computing system made up of atoms and electrons, be it natural
or artificial. This "transcomputing"
ability would concern both classical and quantum level computation.
Two kinds
of lessons are to be learned from Nature to proceed rapidly and hopefully with
the Synthetic Biology and Synthetic Life conceptions: 1) what is the meaning of
"computing" for a system that is
mainly information-driven, not
energy-driven, and whose evolutionary character necessarily involves simulation of the environment, i.e. the decoding of it as the basic ability to
survival - the first condition for evolution, i.e. the gaining of stability - and growth - the second condition or the dynamics for moving from any
stable state on, against entropic degradation; and 2) what are the dynamics of a
system self-developing into more informational structures, i.e. structures of
levels of increasing abstraction as reduction of the number of degrees of
freedom for describing the environment and the lower-rank levels. Indeed, computing will mean to add a second
dimension, which is the semantics or
meaning added to what would be just blind syntax capable to describe in the
logical space of any automaton what in phase space would be just an isentropic,
i.e. not creative, flow of information: recursive functions only. (the
notions of convergent thinking and divergent thinking there are in
A.G.Grappone's paper). Any meaning
successfully added is just the correct pragmatics
- i.e. actuation - embodying the relationships
with the environment that ensure survival and growth. This can be depicted by
the closed chain of holistic structure-function undividable unity shown
herein below:
SENSING ↔ INFORMATION PROCESSING ↔ ACTUATING
This is a self-referential
and yet not paradoxical system just because it is dissipative; a paradox of
infinite regression would appear in a fully logical - i.e. isentropic - system. Dissipation dispels paradox. Thus, extralogical self-referential computing
embodies what is called semantic
computing, which does not occur in the standard phase space conceived for describing energy-driven systems, but in
a space of coded interactions, i.e.
of interactions depending on frequencies and/or on space arrangements. The concept
of meaning and of codes, and of complex codes-of-codes or hierarchies of codes
introduces the thought category of quality,
and more specifically of quantifiable
qualities, a notion that hiddenly underlies all modern science, the latter
being thought of according to an usual misconception as the success of the mere
category of quantity.
A proper source of
insight as the capability of semantic computing would be embodied by Geometry,
mainly the non-commutative branch, and Topology, which both consist of quality
and quantity, and by their connections with the general concept of field as a
physical quantity associated to a point in spacetime: the field that occupies space, contains energy, and whose
presence eliminates a true vacuum, but that also contains information through its wave
dynamics and the ubiquitous phenomenon of synchronization that goes from
macroreality to Heisenberg molecular field. Geometrization, as a fully energy-free
approach to the analysis and synthesis of evolutionary systems would add quality to our equations and any
computing tool, and would overcome transcomputational and non-computability
problems, be they of classical or quantum nature, and would unveil the actual
nature and the meaning of "measurement"
for evolutionary systems. Indeed, differently with respect to measurements in
the case of so-called inanimate systems, in the case of evolutionary
self-reproducing systems like living matter, measuring is a real dialog between
the observing and the observed system, where both such systems try to decode
each other and build an "image" of
one another ("Living matter is matter
that chooses" as the famous biologist E. Margulis puts it). The entropy
produced when an improper language is used, like that of syntactic computers,
to decode a semantic system would just consist in the huge number of imperfect
models, obtainable by means of the most powerful supercomputers; a number that
would overwhelm the processing capabilities of the human observer. The effort
for reaching the ability of measuring and computing along these lines would
lead to descriptions of biosystems in the realm of spacetime and quantum field
theories, deeply down to their envisageable aspects of macroscopic quantum
objects linked to the underlying physics of the Universe, for their well
controlled, fully from-scratch synthesis according to the ultimate plan
formulated by Synthetic Biology and Synthetic Life: nothing to be feared, but
just to be understood.
Notes
*) Scientists Reach Milestone On Way To
Artificial Life, National Public Radio, Interview of 20th
May 2010. The J. Craig Venter Institute was formed in October
2006 through the merger of several affiliated and legacy organizations - The
Institute for Genomic Research (TIGR) and The Center for the Advancement of
Genomics (TCAG), The J. Craig Venter Science Foundation, The Joint Technology
Center, and the Institute for Biological Energy Alternatives (IBEA). Today all
these organizations have become one large multidisciplinary genomic-focused
organization. With more than 400 scientists and staff, more than
**)
This fear, of ancestral origin, has been affecting mankind for some centuries
and has been coming again from time to time, mainly since when the scientific
thinking was formulated and got some results deeply biting at beliefs and
nibbling at principles or uncanny beliefs within which the general historical
conscience was framed and societies were established. A vivid characterization
of this can be found in a scene of Goethe's Faust, where Mephistopheles, in
disguise as a university professor, when asked respectfully by one of his
students to write a dedication on the student's workbook, takes the workbook,
writes something and gives it back to the student, who takes it and reads aloud
what Mephistopheles had written. It is, in Latin, the biblical devilish
sentence of temptation to Man in the earthly paradise: "Eritis sicut Deus,
scientes bonum et malum - You will be similar to God, with the knowledge of
good and evil". Then the student bows and leaves. And while he is leaving,
Mephistopheles says to himself "Follow so far the old saying of my uncle the
Serpent, as you please; the day will surely come when you will be afraid of
being similar to God". Knowledge is thus felt as a devilish dangerous trap,
and ignorance as an imposed status to which Man is doomed for a happy and quiet life.
***) IASB, c/o febit
synbio GmbH, Im Neuenheimer Feld 519, 691220 Heidelberg, Germany
© 1995-2008 Kazan State University