Cybernetic cloning - a biologist's view

by
POULAMI MITRA
School Medicine,
University of Pittsburgh
Pennsylvania (USA)

Great minds have always been intrigued by the inherent complexity and diversity in the life process.  We are living in a time where the understanding of mysteries of Nature is expanding at an explosive pace.  The ultimate goal in science is to decipher the mysteries of Nature and Life, and the different paths to do so are called by different names like Physics, Mathematics, Biology, etc.  Biological systems largely rest on a holistic approach, adhering by the principles of physics, chemistry and mathematics and for that matter all possible logistic sciences.  Physics, characterized by uniformity and generality, is a strongly reductionistic science and has significantly prospered in this way.  Based on the assumptions of simplicity and with the aid of mathematical formulations, physics attempts to understand biological phenomena, with the presumption that complex systems have underlying simple laws.  As a result, biological sciences also suffer from permeation by mechanistic reductionism in the guise of two metaphors : (1) the dynamic metaphor of organisms as machines and (2) the information metaphor of life as a blueprint on DNA.

 

Firstly let us consider the dynamic metaphor of treating life as a 'machine'.  Machine runs on the basis of physical laws, precisely on Newtonian dynamics.  The difficulty of applying the simple machine model to biological systems is more than one.  Firstly, organisms are of intermediate size and cannot be treated as particles.  Secondly, they are internally heterogeneous, meaning that their state of motion or normalcy is determined by a multiplicity of interacting individual causal chains of influences.  Thirdly, these individual heterogeneous systems enter into complex causal relations with other heterogeneous systems.  All these make it difficult for us to separate causes from effects,  So, in biology we land up having causal explanations, whereas in physics we have generalizations of the behavior of objects, such as Kepler's laws of planetary movements.

 

The concept of feeding loops has now firmly entered into the treatment of physical systems as a result of the development of cybernetic and control theory.  Cybernetics or the principle of 'controls' has been applied to biology, where regulation and feedback are the criteria for normalcy.  The importance of control system engineering lies in determining operating conditions and stability of the mechanical models.  A system requires stability through feedback mechanisms.  Consider a servo motor which employs the principle of negative feedback to stabilize gain and frequency responses.  Feedback essentially consists of' feeding a part of the output back to the input to determine error conditions and also to detect whether the desired output has been reached, within the specific tolerance level.

 

Now let us take ap a simple example to consider what happens when biological systems are modeled according to system analysis. Consider a cell and its environment. The external conditions imposed on the cell are the ‘inputs’ as in mechanical models and the cell responses are same as 'outputs' : the cell also maintains feeback loops to attain dynamic equilibrium with the environment.  We must remember that apart from changes going on with the cell changes are incessantly occurring in the environment as well. So, we have two systems interacting with each other with the goal of establishing a dynamic equilibrium state. Scrutiny reveals that in the case of cell an its environment we are actually being unable to decide where to place the reference frame : whether in the cell or in the environment. In other words, the biological system is non-Newtonian. Again, to develop nuemerical methods of analysis for this biological model we will have continuously changing transfer functions from the output to the input that will lead to ‘varying stability criteria’. The number of iteration (such as temperature, pressure, pH etc.) therefore required would be too large to handle. This will lead to formulation of what is called in mechanistic terms ‘inexact differentials’ that is, there will always remain  a factor that will vary from state to state thereby jeopardizing the aim of establishing a set format.

 

Another aspect of biology that gets gainsaid in consideration of the machine model is that organisms have a history. This history is at two levels: the individual life stories that began with a single fertilized ovum a collective history that started billions of years ago when proteins gelled together into ‘living’ protoplasm. The designers of modern cars do not have to consult Diamler’s origin design for an internal combustion engine, whereas, the problem of brain function in perception and memory is precisely the problem of how the neural connections come to be formed under the influence of sights, sound, caresses and blows.

 

Let its now consider the second metaphor for life, that is ‘information metaphor, according to which genomic DNA contains the information for all life processes of an individual. The constant reiteration of the claims that genes determine organism is consequence the ease with which major genetic changes can be induced experimentally and large effects that these changes have on experimental objects.  A closer look reveals those phenomena are considered that lend themselves. The DNA sequence alone cannot tell us what organism will look like, except in general terms.  It is, on the other hand, determined an intricate play of the genes, the environment and the organism itself.  Development is not simply the realization of an internal program (transcription and translation of DNA) but the outside also matters.  Stage theories in developmental processes very clearly prove this point in the process of embryonic development to the ‘2 cell stage’ to ‘4 cell stage’ to ‘blastocyst’, an embryo may get stuck at any intermediate stage : the problem might be internal or external.  The tropical vine will never switch (dictated by genes) from a creeper state to a climber state unless it encounters a trunk (the environment).  Organisms are therefore a result of both its genes and the temporal sequence of environments through which it has passed.

 

Nature poses problems that the organism must solve or perish.  The internal make up of the organism tries to solve these problems imposed by the external world by way of say random mutation and evolution of the species occurs.  The organism thus becomes the passive nexus of internal and external forces.  The organism is nevertheless considered important because it is impossible to judge the problems posed by Nature without describing the organism for which the problem exists.  Again, we cannot characterize the environment except in the presence of the organism that it surrounds.  So, by and large, it is an intricate complex and non-linear interaction of genes, environment and the organism that will determine a pattern.

 

We should thus realize that simplicity in biological functional order is an exception and complexity is the rule.  We must accept that there lies many aspects of nonreducibility at the core of all life's beauty, that man is yet to comprehend and then only he may cybernetically clone life.