1
CONTROL SYSTEMS IN METAZOANS
The fixity of the internal environment is in short the
condition of mental activity.
J. Barcroft
As open systems, metazoans obey the second lawof thermodynamics: they
continually lose order at all the levels of molecular, cellular, and
supracellular organization. And still, in defiance of that law, during their
lifetime, they succeed in maintaining their order and structural identity at
all the levels of organization. This indicates that a mechanism that figures
out and compensates for the lost order is operational in metazoans. The
maintenance of the thermodynamically improbable metazoan structure, is function
of an integrated control system (ICS), in principle similar to control systems
used in engineering. The system consists of the nervous system and its effector
structures. The controller of the ICS is the central nervous system. Adequate
experimental evidence shows that the ICS in metazoans is responsible for the
maintenance of the homeostasis, comprising animal morphology, physiology, life
history and behavior. To perform all these functions the ICS has to continually
- Monitor the state of the system via the sensory input from
interoceptors,
- Compare the input on the state of the system with the normal state, implying
that the system is in possession of information for the normal state,
- Identify and figure out losses of the structural order,
- Make decisions and send instructions to the target sites for
compensating losses.
The Thermodynamic Enigma of Living
Systems
The ability of
living systems to maintain their structure, in apparent defiance
of the second law of thermodynamics, has long amazed and perplexed
scientists. What makes living systems so extraordinary and unique?
In
What is life?
(1943), Erwin Schrödinger
dealt with the issue and popularized the idea of entropy in living
systems. According to the second law, all processes occurring in
material systems, living systems included, lead to increase of the
entropy or the loss of order in the system. Schrödinger attempted
to resolve the enigma of the existence and maintenance of the
thermodynamically improbable structure of living systems by
assuming that living organisms “suck” order or negative entropy (negentropy)
from the environment. In other words, they use an external source
of order (food for animals and the sun and carbon dioxide for
plants) to compensate for the order they inescapably lose, thus
avoiding structural degradation.
His pioneering idea, however,
was incongruous with some basic physiological knowledge: the first
step an organism undertakes after taking the food is to break the
ingested organic compounds down to their low molecular organic
compounds (amino acids, monosacharides, faty acids, glycerol,
nitrogen bases, pentoses, etc.). In doing so it destroys the
original order, i.e. increases the entropy of ingested nutrients
for creating its own species-specific order (proteins,
carbohydrates, lipids and other compounds resulting from the
activity of its proteins).
Biological systems do not
maintain their structure by absorbing “order” from the environment
for the food contains no utilizable order of the specific
type metazoans need for building their structures. With the
benefit of the knowledge accumulated ever since, we know that
being in possession of a control system, living beings are able to
use free energy for generating their own species-specific order
out of the non-specific order or negentropy embodied in nutrients.
Thus, what the organism “sucks” with the food is not the order it
contains for that order is not utilizable order so that, as
mentioned earlier, the organism first has to destroy it; what it
utilizes from the food for generating its species-specific ordered
structure, its species-specific molecular and cytological building
blocks, is the “raw material” and the free energy.
Hence, the organism is a generator of its own order rather than
consumer of external order. And there is nothing more essential
and enigmatic in the existence and evolution of living systems
than the mechanism of generation of the information for
producing the species-specific order in its cellular and
supracellular structure.
On the Order and
Information in Material Systems
One of the simplest formulations
of the second law of thermodynamics is that in isolated systems
only processes that are associated with increase of entropy can
occur.
In anorganic systems, usually
the concept of order is used as equivalent of the negative entropy
(negentropy). Both terms were used to measure or describe the
degree of atomic order in the system. Later, with the advent of
the science of communication systems, especially with the
introduction of the concept of information, a controversial triple
relationship between entropy, order, and information arose.
The concept of information is an
equivocal one that is used in widely different meanings in
different fields of science.
Thermodynamic concept of order.
From a conventional
phenomenological view, information is a measure of structucal
order in a system, i.e. the opposite of entropy. Hence, the
greater the entropy of the system - the lower the order and the
amount of information in the system will be, and the reverse. A
freezing temperature, e.g., transforms the water into ice phase,
implying an increase of the order of the system resulting from
restriction of movements of the water molecules within the system.
The order in physical systems, thus, is temperature-dependent and
in the zero absolute (−273.150C),
when the system is devoid of almost all the forms of energy, and
movement of molecules comes to an end, the system will have its
maximal amount of order and information.
In physical systems, thus, the
informational content of the system is function of the
temperature. A rise in temperature increases the degree of freedom
of the components of the system, thus decreasing the order and
information content of the system, and vice versa.
Communication systems concept of
information. In
communication theory, the concept of information implies
transmission of information from the sender to the receiver and
the entropy measures the fidelity of transmission of the
information to the receiver. Due to intrinsic
causes, noise or errors occur in the process of transmission of
information through communication channels and in the process of
decoding of the message by the receiver. These errors represent
the thermodynamic equivalent of the entropy and the Shannon’s
equation of uncertainty
is similar to the equation of entropy.
Both the
thermodynamic and Shannon’s equations and concepts of information
derive from the study of anorganic systems, in which the order and
information content of the system can be measured in units of
information, bits (binary digits).
However, the fact that in both
the physical systems and communication systems the amount of
information can be measured by the same standard bit units does
not necessarily indicate that there are no qualitative differences
between the information in communication systems and the negative
entropy (information) of natural physical systems. Qualitatively
different objects or processes may be measured by the same unit or
may be subject to the same methods of study.
Unlike physical systems,
communication systems imply transmission of information from a
part of the system (the sender) to the other (the receiver), but
such a transmissibility of information (or flow of order or
negentropy) within the system is unknown in physical systems.
On the Meaning of
Biological Information
Genetic vs. Epigenetic Information
Even within the field of the
study of biological systems the concept of information is used in
different meanings. To a large extent, the confusion on the
meaning of information in biological systems derives from the
fusion of two distinct concepts of information, the thermodynamic
and the communication systems concepts.
As it will be used in this work,
biological information is an entity that when communicated to a
system or to parts of it can produce new and specific structural
order. Biological information in metazoans consists of genetic
information and epigenetic information. Both these forms of the
biological information functionally transcend or go beyond
themselves, displaying some kind of intentionality, or purpose (a
teleonomic purpose sensu Mayr).
Essential differences, however,
exist as far as the origins and nature the genetic and epigenetic
information is concerned. In the case of the genetic information
that purpose is to provide instructions for building a protein, in
the case of epigenetic information - to activate a particular
signal cascade for achieving a specific phenotypic (behavioral,
physiological or morphological) result.
Genetic information consists of
sequences of nitrogen bases in genes, which code for specific
proteins. Unlike anorganic systems, there is no strict equivalence
between the order and the information in the DNA molecule (gene).
A randomly occurring mutation in a nitrogen base does not change
the amount of order in the molecule but it may cause a loss or
gain in the genetic information of the gene. Thus, a mutational
event may not produce loss of order in the gene but
may cause a loss of information that manifests itself in
the loss of function of the product of the gene. In other words,
the product of the mutated gene will lose the “meaning” and cannot
serve its purpose that is the building of a functioning protein
molecule.
Genetic information, thus has a
new attribute, unknown in anorganic systems: it has a “meaning”;
the system can lose or acquire information while the order of the
system remains constant.
Epigenetic information will be
defined here as the information that is computationally generated
in neural circuits. Its “purpose” is to activate a particular
signal cascade for achieving a particular adaptive phenotypic
change at a supracellular or organismic level by inducing
1. Expression of a
nonhousekeeping gene,
2. Cell proliferation,
3. Cell differentiation,
4. Molding or restoring a
morphological trait,
5. Maintaining physiological
states,
6. Determining a behavior, and
7. Determining a life history
trait.
While new genetic information is
acquired via randomly occurring changes in the sequence of
nitrogen bases, the new epigenetic information is an
adaptation-oriented product of computational activity of neural
circuits. It manifests itself in the form of a chemical outcome
resulting from the processing of the internal/external stimuli in
neural circuits. The chemical product of the computational
activity of the neural circuit is released for activating a signal
cascade that leads to an adaptive phenotypic result aimed at
maintaining/restoring the structural and functional order or the
equililibrium between the organism and its environment.
The genetic and
epigenetic forms of information produce order at different levels
of structural organization, at the molecular and at the
supracellular level respectively.
Novel Properties of the Biological Information
Essential differences also exist
between the biological (genetic and epigenetic) concepts
information, on the one hand, and the thermodynamic and
communications theory concept of information, on the other.
While the order and information
in physical systems are identical, in organic systems the
structural order of the system is product, embodiment ot
manifestation of the biological information.
At variance with anorganic
systems, the order in living systems is not temperature-dependent;
within the normal range, the temperature has no influence on the
amount of the order in the system.
Unlike physical systems,
living systems are able to create different patterns of order in
different part of the system by differential investment of
information in different parts of the system. They are also
capable of transmitting order and transmitting information outside
the system in the process biological reproduction.
Biological concept of
information is related to, but distinct from, Shannon’s
communications concept of information. The order in communication
systems depends on the fidelity of the transmission of information
from the sender to the receiver after the information is decoded.
In an ideal case, the information transmitted by the sender to the
receiver would be identical to the information or the order (negentropy)
the receiver gets. In living systems, on the contrary, there is no
equivalence between the biological information transmitted from
the sender and the order it induces in the structure of the
receiver (a group of cells or tissue). Instead of equivalence, the
relationship of biological information of the sender and the
receiver is characterized by correspondence, determined by
encoding properties of the biological (genetic and epigenetic)
information. So, at variance with the symmetry of
transmission of information in communication systems, transmission
of information in biological systems is asymmetrical, in the
meaning that the information transmitted from the sender (the
source of information) produces an order that corresponds to, but
is different from, the order generated by the target organ
(receiver of the information) according to the information
provided by the sender.
This asymmetry and symbolism of the transmission of the genetic
and epigenetic information is at the basis of what is called
meaningfulness of biological information.
While the information in the
communication systems is decoded by the receiver, the epigenetic
information is decoded by the signal cascade it chooses to
activate, i.e. it reaches the receiver in a decoded form or as
“instruction”.
The decision for
activation a particular signal cascade by a neural circuit
represents the solution to the problem that a specific input on
the state of the system or an environmental agent poses to the
neural circuit. The solution results from the processing of the
input of electrical spike trains in a number of steps in the
neural circuit until the appropriate chemical outcome (a
neurotransmitter, neuromodulator or a neuropeptide) is generated.
Theoretically, any
operation that is designed to solve a problem implies a purpose
and prediction of the phenotypic result, which precede the
solution. There can be no solution per se, a solution is
searched and found for the sake of the purpose. The stepwise
processing of the input, which comes to the neural circuit as a
problem requiring solution represents essentially a natural
algorithm that living systems began to use with the evolution
of the nervous system more than half billion years ago. It
comprises the teleonomic purpose, the desired result and the
consecutive steps for achieving the desired phenotypic result.
The chemical ouput
of the neural origin activates a chemical algorithm involving a
signal cascade, including the intracellular signal transduction
pathway that leads to the final solution that is activation of a
gene or a group of genes
Thus, the
epigenetic information generated in the neural circuit as a result
of the processing of the electrical input (a neural algorithmic
solution to the problem that the input poses to the neural
circuit) is used for selecting and activating a chemical signal
cascade. The phenotypic solution comes as a result of a double
(electrical and chemical) algorithm.
The end result of the
double algorithmic solution is an adaptive phenotypic outcome that
tends to restore the lost order or for generating the new order in
gametes in adult organisms or for developing species-specific
structure in the process of individual development.
The Control System in
Metazoans and the von Neumann’s Machine
A basic implication of the
second law of thermodynamics is that the molecular order of
components of the cell, as well as cells themselves, will
gradually and unavoidably be degraded and lost. As
already mentioned, while continually losing molecular and cellular
components, metazoans succeed in maintaining a steady state, a
flowing equilibrium (Flieβgleichgewicht sensu von
Bertalanffy), continually restoring the lost structural order at
all the levels, from the molecular to the cellular and
supracellular levels. Easy as it is to say that living systems
manage to circumvent the second law, the continual replacement of
inevitably degrading components in metazoans, the most complex
structures known in the universe, is a formidable task. That
replacement implies that metazoans
1. Continually monitor the state of the system
2. Are in possession of information on the normal state of the
system,
3. Are capable of comparing the actual state with the normal
(desired) state, and on this basis
2. Quantify the lost/degraded molecular and cytological
components,
3. Determine the kinds and amounts of molecular and cytological
components to be produced,
4. Via signal cascades, send to the right places at the right time
instructions for producing and replacing the lost components.
The above
functions are basic functions of the human-engineered control
systems in electronics. This strongly suggests that a control
system similar to the human engineered control systems may be
operational in metazoans.
Due to the
multiplicity of the levels of controls and the hierarchical
nature, the metazoan control system may be characterized as an
integrated control system (ICS).
The ability of the
ICS to continually monitor the status of the system in metazoans
implies, and is based on, the omnipresence of the neural tissue
throughout the animal body down to the level of individual cells.
The integration
and processing of the interoceptive input on the state of the
system, as well as decision-making for restoring the normal state,
are functions of the controller of the ICS, which is the
CNS (central nervous system). By comparing the information on the
actual structure with the “normal” structure, the CNS identifies
deviations and sends instructions for activating signal cascades
for restoring the normal structure.
Evolution of the
control system was a sine qua non for the emergence of life
on earth and for maintaining the structure and function of living
systems. The control system is a novel and essential feature of
living systems, unknown in the anorganic world. All the rest
of basic properties of the multicellular life depend on the
presence and function of the control system. No growth,
development, reproduction, metabolism, and evolutionary change
would be possible in metazoans in the absence of a control system.
In unicellulars,
the control system is represented by the genome and the apparatus
of gene expression including supramolecular structures involved in
gene expression and regulation of gene activity. Additionally, it
comprises still little known epigenetic mechanisms and epigenetic
information necessary for determining the spatial arrangement of
molecular components in specific spatial patterns from which cell
organelles arise (see also Epigenetic Information in
Unicellulars and Unicellular Precursors of Epigenetic
Informational Structures in chapter 13).
As argued before
(Cabej, 2005a), as well as in the Introduction of this
book, the genetic information is qualitatively inappropriate and
quantitatively negligible for determining the spatial order of
cells of various types in the multicellular structure. Transition
to multicellularity required an additional type of information for
determining the spatial arrangement of the myriad of cells of
different types in multicellular structures. Evolution of
structures for generating that new form of information necessary
for determining relative spatial arrangement of the astronomical
number of cells of hundreds of different types of cells in
multicellulars has been a long, complex, and very difficult task
as it is witnessed by the fact that the evolution of these
information-generating structures took more than ¾ of the time of
the existence of life on Earth. It was a basic requirement for the
evolution of the ICS (integrated control system), which would take
over all the control of all the basic functions in metazoans, from
the maintenance of the structure and function to their
reproduction.
The metazoan
epigenetic information is encoded meaningful information
computationally generated in the nervous system that uses signal
cascades for achieving strictly predictable phenotypic results
when communicated to the target cells and tissues.
The epigenetic
information, thus is flexible (in clear distinction from the
genetic information that is strictly determined as a result of the
high conservatism of the genetic information and the “frozen”
nature of the genetic code). The sensory input from the actual
structure, after being integrated and processed in the CNS, is
compared with the normal (desired) state and, on this basis,
instructions (signal cascades) necessary for restoring the normal
structure are computated and determined.
The last stage in
the life cycle of all living beings is the unavoidable death, but
they again succeed in preserving their kind by reproducing
themselves before dying. Being in possession of information on the
normal species-specific structure, the control system is
responsible for the biological reproduction and metazoans.
The evolution of the ICS, this
uniquely biological antientropic contrivance, which figures out
when, where, how much, and what kind of information to invest in
the system, first for producing the adult structure in the process
of individual development and later, during the adult life, for
restituting the unavoidably degrading normal structure and
function, marks the most critical moment for the evolution of
metazoans.
Recognition of the control
systems in living organisms in general and the integrated control
system (ICS) in metazoans, resolves the thermodynamical
paradox of the evolution and survival of metazoans as highly
improbable structures.
The solution to
the problem of determining the spatial arrangement of
billions/trillions of cells of the most different types for
molding animal morphology came sometime around the Cambrian
explosion by evolution of a type of biological replicator that
reminds the von Neumann machine.
That crucial
moment in the history of the kingdom Animalia began with
the differentiation of the nervous cell and the nervous system
(see also Diffuse Neural Control System: The
Eumetazoan’s Eureka, chapter 13). Differentiation of the
neuron and the nervous system represents the greatest
informational revolution after the evolution of the genetic code
with the emergence of life on earth, more than 3 billion years
ago.
Metazoans do not
produce copies of themselves as unicellulars do. They cannot do so
because of
the formidable
problems related to production of copies of multicellular
structures. Instead of producing copies of themselves, metazoans
produce specialized cells, gametes, which can develop into adult
metazoan organisms themselves or by uniting with their sexual
counterpart. Parents provide gametes with the epigenetic
information necessary for developing up to an early embryonic
stage, the phylotypic stage, when only one organ system, the
nervous system is operational. The CNS at this early embryonic
stage, when the maternal epigenetic information provided with
gametes is exhausted, is already capable to stepwise computate the
epigenetic information necessary for the development of the adult
metazoan supracellular structures.
Neural computation is not a
random process; it finds solutions to problems by activating
appropriate signal cascades leading to predictable phenotypic
results. In other words, neural computation is capable of
excluding possible signal cascades in favor of the one that leads
to the desired result, what is another way of saying that it
generates information in Shannon’s meaning ]
Evolution of
metazoans, and multicellular organisms in general, was a complex
task that transcends the most courageous dreams of human genius.
von Neumann dreamed of a machine (replicator) that would be able
to build copies of its own when provided with necessary parts. The
machine then would install and switch on the operating program in
the completed daughter machine, which could then enter a
self-repeating cycle of production of self-replicating von Neumann
machines. Even this over-ambitious dream of building a
self-replicating machine, looks very unsophisticated when compared
with what actually a metazoan organism accomplishes during its
lifetime.
In the case of the
“living machine” the parent(s) builds neither the machine nor the
machine in miniature that by growing in size would become a
complete operating and replicating machine of its kind; nor does
the parent insert operating program in it. It rather provides
epigenetic information for building a rudimentary model of the
adult form, the Bauplan at the phylotypic stage.
What is beyond the
reach of even the wildest human imagination is that at the
phylotypic stage the embryo is in possession of an awesome
information-generating machine, the central nervous system, which
starts functioning and generating information for building its own
species-specific metazoan structure and its own operating program,
long before the construction of “living machine” is completed.
Now, let’s try to
substantiate the functioning of the metazoan ICS (integrated
control system) with some empirical evidence on the central neural
control of the maintenance and development of the animal phenotype
(behavior, morphology, physiology and life history).
In anticipation,
let me respond to the neoDarwinian argument that the central
control of animal phenotype is ultimately determined by genes. At
this juncture, I find it appropriate to say that this is
emphatically not true but I will extensively elaborate on the
non-genetic, computational, epigenetic nature of that control in
the next chapter.
Central Control of Animal
Physiology
Physiological knowledge accumulated during the last two centuries
shows that the vital functions of all the organs and organ systems
inhigher invertebrates and vertebrates, are centrally regulated by
the CNS (central nervous system). An initial theoretical
breakthrough in understanding that control represents the
development of the concept of la fixité du milieu intérieur
by the French physiologist Claude
Bernard in the second part of the 19th century, now
generally known as homeostasis,
a term coined by Walter Cannon in the 1930s. According to this
concept, living organisms are able to keep constant,
within certain limits, their interior environment, i.e. the
chemical composition of body fluids (blood, lymph, and
intercellular fluid,), temperature, etc. Homeostasis is a
necessary condition for the maintenance of the function and
structure (“la condition de la vie libre” in C. Bernard’s
expression) in metazoans.
The maintenance of homeostasis is a function of the central
nervous system:
The entire central nervous system is involved in the maintenance
of internal homeostasis. (Pacak and Palkovits, 2001)
Experimental studies on the mechanisms that enable metazoans to
maintain numerous components of their internal environment within
“physiological” limits offer some of the best examples of the
function of the integrated control system, with the CNS as its
controller, at the organismic level in metazoans.
Homeostasis here will be used in a broader sense to comprise
not only the maintenance of the steady state of the body fluids
but also the maintenance of the normal structure and function of
the animal organism in its entirety. Modern physiology provides
ample evidence on the CNS control of vital functions of all the
organs and organ systems in animals, including heart work, blood
circulation and pressure, respiration, digestion, endocrine
activity, etc. For illustration, let’s only consider some well
known examples of CNS control of homeostasis, including the
central circadian control of expression of non-housekeeping genes
in cells throughout the animal body.
Brain Control of Water Content
The drop of water content in metazoans
is sensed by a specialized part of the hypothalamus as a rise
above a threshold of the osmotic pressure (rise in the
concentration of particles) of body fluids. Osmoreceptor
neurons in the circumventricular organ OVLT (organum vasculosum
of the lamina terminalis) and SFO (subfornical
nucleus), in response to increased osmolality, respectively
via the MnPO (median preoptic nucleus) and directly, send
signals to the magnocellular neurons in the hypothalamic PVN (paraventricular
nucleus). PVN also receives baroregulatory information from the
brainstem (Lechan and Toni, 2004; figure 1.1 ). In response
to the input of information on “thirst”, hypothalamic
magnocellular neurons release vasopressin (antidiuretic
neurohormone) that via the pituitary is released in the body
fluids. The hormone acts as
antidiuretic by binding its receptors on the membranes of the
cells of the distal kidney tubules. Elevated levels of
vasopressin stimulate the reabsorption of water in kidney tubules
and production of highly concentrated urine, leading to lower
osmotic pressure. When the water
content increases and the osmolality drops, this is again sensed
by osmoreceptor neurons, which in a negative feedback loop,
inhibit vasopressin secretion and increase urination.
Figure 1.1.
Schematic drawing of the major pathways involved in regulation of
vasopressin secretion. Information about osmolality is relayed to
the hypothalamus largely through osmoreceptor cells in the organum
vasculosum of the lamina terminalis (OVLT), subfornical organ (SFO)
and medial preoptic nucleus (MnPO). Baroregulatory information is
carried to magnocellular neurons in the paraventricular nucleus (PVN)
and supraoptic nucleus (SON) largely by direct afferent projections
from the brainstem, including the bed nucleus of the stria
terminalis (NTS) and ventrolateral medulla (VLM) using
catecholamines as its neurotransmitter, or indirectly through the
parabrachial nucleus (PBN). Vasopressin secretion can also be
stimulated by activation of the chemoreceptor trigger zone in the
area postrema (AP) (From Lechan and Toni, 2004).
Central Control of Glucose and Insulin Biosynthesis
A hypothalamic
mechanism of regulation of glucose level, a “glucostat” involving
the endocrine pancreas, liver and adrenal gland has been identified
more than two decades ago (Benzo, 1983). The
hypothalamus plays a critical role in hypoglycemia-induced responses
of adrenomedullary, sympathoneuronal, and other systems (Pacak and
Palkovits, 2001). Experimental lesions of the PVN (hypothalamic
paraventricular nucleus) result in hypoglycemia. From PVN
starts a descending pathway to the ILM (intermedio-lateral cell
column) and the dorsal vagal nucleus of the vagus innervating VMH
stimulates pancreatic secretion. Electrical stimulation of the
hypothalamus inhibits insulin secretion (Li et al., 2003) neurons
with pancreatic projections (figure 1.2).
Figure 1.2.
Proposed neuronal pathways involved in the response to experimental
hypoglycemia by a single insulin injection. Hypothalamic projections
to autonomic centers, and autonomic innervation of the pancreas.
Abbreviations:
AN, Arcuate nucleus; CG, celiac ganglion;D, duodenum; DM,
dorsomedial nucleus; DVN, dorsal motor nucleus of the vagus; GN,
sensory gastric fibers; IML, intermediolateral cell column; VG,
vagal ganglionic cells; X, vagus nerve (From Pacák and Palkovits,
2001).
Glucose sensors for detecting
hypoglycemia have been identified in the forebrain and the brainstem
and especially in the VMH (ventromedial hypothalamus), which
responds to the hypoglycemic state by activating hormonal
mechanisms, including secretion of glucagon and food intake. The
lateral and posterior parts of the hypothalamus release the
neuropeptide orexin (Miyasaka et al., 2002), which stimulates food
intake and via the vagal efferent nerve stimulates exocrine hormonal
secretion in the pancreas (Wu et al., 2004). Ablation of the lateral
hypothalamus inhibits the vagal pancreatic nerve firing and
pancreatic secretion.
Stimulation of the parasympathetic
nervous system leads to insulin secretion and inhibition of glucagon
secretion, irrespective of whether the stimuli occur at the lateral
hypothalamic nuclei, the motor nuclei of the vagus, or the mixed
pancreatic nerves. Stimulation of the sympathetic nervous system or
application of epinephrine likewise stimulates glucagon production
and inhibit insulin secretion. (Norman and Litwack, 1997c)
The above evidence demonstrates that
the CNS directly controls the secretion of hormones insulin and
glucagon in pancreas.
Brain Control of Circadian Rhythms
24-hour daily rhythms of gene
expression are observed in most peripheral cells and tissues in many
invertebrates and vertebrates. Cell circadian oscillators consist of
positive elements that induce transcription of clock genes, whereas
the products of these genes, clock proteins, act as negative
elements in the feedback loop of the oscillator, and expression of
clock-controlled genes determines the cyclic character of the cell
metabolism (Dunlap, 1999).
Given that circadian clocks and the rhythms they produce are not
accurate and need to be adjusted, they are centrally controlled and
reset by the suprachiasmatic circadian pacemaker (a group of neurons
in the SCN) in the hypothalamus, via neural, hormonal, and
behavioral influences (Akhtar et al. 2002).
Any cell in fungi, plants, or
protists could be a clock cell, but only neurons kept time in
organisms that had them. (Dunlap, 1999)
The “circadian photoreceptor”
responsible for resetting the circadian clock is a group of
malanopsin-containing retinal ganglion neurons, which transmits the
photic signal to the SCN via the retinohypothalamic tract (RHT)
(figure 1.3).
In response to the input of
electrical signals, the RHT releases glutamate and PACAP (pituitary
adenylate cyclase-activating peptide) in SCN neurons. The dorsal and
median raphe nucleus have serotonergic projections to the circadian
pacemaker. Electrical stimulation of the dorsal and median raphe
nucleus neurons induces serotonin release and the pacemaker responds
to it by modulating its rhythm phase
(Meyer-Bernstein and Morin, 1999; Glass et al., 2003).
After
an earlier observation that a nighttime light pulse caused
phosphorylation of histone H3 in SCN clock cells
(Crosia et al., 2000), recently it was discovered
that CLOCK protein, which has been considered to be the central element
in determining circadian cycles, is in fact a histone
acetyltransferase that has enzymatic specificity for histones H3 and
H4. By acetylating these histones, it remodels the chromatine, thus
facilitating access of transcriptional activators and coactivators
to the promoter region of clock genes and regulation of the
circadian physiology (Doi et al., 2006). It is noteworthy that this
acetylation enzyme is induced in the SCN central circadian pacemaker
as a downstream element in a signal cascade that starts with the
reception in the “circadian photoreceptor” and activation of D2R,
the receptor for the neurotransmitter dopamine in retina.
Figure 1.3.
Photic input signal transduction pathways in the SCN neuron. Solid
and dashed lines indicate direct and indirect pathways,
respectively.
Abbreviations:
BIT – brain immunoglogulin-like molecule with tyrosine based
activation motifs; CAmK II – calcium/calmodulin kinase II; CRE –
cAMP response element; CREB – CRE binding protein; PACAP –
pituitary adenylate cyclase-activating peptide; PKGII – cGMP-dependent
protein kinase II (From
Hirota and Fukada, 2004).
The main genes involved in the
circadian clock are Per1 (Period 1), Per2, and
Per3, as well as Cry1 and Cry2 (the negative
limb of the clock), and Clock and Bmal1
(representing the positive limb of the clock, by activating both
Per and Cry genes) (Arjona and Sarkar, 2005).
Accumulation of Per and Cry acts as
a feedback signal for suppressing their own production.
The activity of the SCN circadian
pacemaker is autonomous but, as noted earlier, it also can be
entrained by light-dark cycles.
Environmental photic
stimuli received by the photoreceptive system are transmitted to
the circadian pacemaker of the hypothalamic SCN for integration
and processing.
Photic stimuli have to be above a
sensitivity threshold of irradiance in order to induce any effect
on the pacemaker.
Exposure to light during the subjective night induces
phase-shifting of the SCN-controlled rhythms. The light-induced
phase-shift results from expression within the SCN of clock genes,
such as
Per1
and
Per2
and of immediate early genes (IEGs), such as c-fos,
fos-B,
jun-B,
nur77,
and
zif268
(Guido et al., 1999).
SCN that via neural and neurohormonal signals continually restores
the rhythm in peripheral clocks. However, the SCN receives
information from the peripheral clocks which are coupled with the
peripheral cell metabolism.
Sleep deprivation can reduce the
light-induced phase shifts of the pacemaker via the resulting
serotonergic and metabolic signals from other regions of the brain
(Challet et al., 2001).
Peripheral clocks lose their rhythm and it is the The mutual
relationship between the central clock and peripheral clocks is
illustrated in the figure 1.4.
Figure 1.4.
Interaction between peripheral and central clocks. An
illustration of the main pathways by which peripheral and central
clocks might communicate with the central nervous system. The
hypothalamus is the chief target for both. Information from the
suprachiasmatic nucleus (SCN) is translated mainly by the
paraventricular nucleus of the hypothalamus (PVN) into a hormonal
and autonomic signal. These hormonal, parasympathetic and
sympathetic signals will reach peripheral organs such as the
adrenal gland, liver, fat tissue and gonads. From these organs,
both visceral sensory and hormonal information will reach the
hypothalamus. Sympathetic sensory information enters the brain at
the level of layers I and V in the dorsal horn and will reach the
hypothalamus via the nucleus of the solitary tract (NTS) and the
parabrachial nucleus (PBN). Vagal sensory information enters the
brain at the level of the NTS and reaches the hypothalamus
directly or indirectly via the PBN. These connections provide the
hypothalamus with information that allows the organism to adjust
and balance peripheral light–dark information with metabolic
information from the peripheral organs.
Abbreviations:
DMV, dorsal motor nucleus of the vagus; IML, intermediolateral
columns (From Buijs and Kalsbeek, 2001).
The circadian system, regulated and
coordinated by the hypothalamic circadian pacemaker, in mammals
performs the temporal control of virtually every biochemical,
physiological, and neurobiological process (Fuller,
2006). It is estimated that expression of 8-10% of genes in
peripheral organs is regulated in this neurally determined
circadian mode (Storch et al., 2002).
Neural Control of
Thermoregulation
The mechanism of regulation of body
temperature in vertebrates, from fish to mammals, is essentially
similar (Crawshaw et al., 1985). It is a central mechanism and the
main thermoregulatory organ is again a part of the brain, the
hypothalamus, particularly the preoptic area, where the sensory
input on the brain temperature and core temperature are integrated
(Boulant, 2000). Other parts of the central nervous system, such
as the brain stem and spinal cord, are also involved in
thermoregulation. There are three functionally different groups of
neurons in the hypothalamic preoptic area (figure 1.5):
warm-sensitive neurons, representing almost one third of the total
number of preoptic neurons, which increase the firing rate in
response to higher temperature and decrease it when the brain
temperature drops; “cold-sensitive neurons” (~5% of preoptic
neurons), which normally are inhibited from the warm sensitive
neurons but are activated when synaptic inhibition is removed as a
result of the decrease of the firing rate of warm-sensitive
neurons during cooling; the remaining 60% of neurons of the
preoptic area are temperature-insensitive (Boulant, 2000).
Figure 1.5.
Firing rate activity of
3 types of preoptic neurons. Warm-sensitive neurons
(W) increase their firing rates during increases
in preoptic temperature (Tpo).
Warm-sensitive neurons also synaptically inhibit
cold-sensitive neurons (C), which increase their
firing rates during decreases in Tpo.
It has been postulated that some cold-sensitive
neurons play a partial role in heat
production and heat retention responses, which
also increase during decreases in Tpo.
Temperature-insensitive neurons (I) show little change
in their firing rates during changes in Tpo,
and these neurons may provide tonic synaptic
input that is compared with synaptic input
from warm-sensitive neurons. Warm-sensitive neurons are
also affected by pyrogens and afferent synaptic
input from skin and spinal thermoreceptors.
+, excitation; -, inhibition (From Boulant, 2000).
High temperature, as
well as experimental warming of preoptic area, decreases
thermogenesis via inhibition of thyroid gland secretion, and
increases heat loss via neural cholinergic stimulation of
sweating, vasodilatation, as well as panting and behavioral
abandonment of the warm environment. By contrast, lower
temperatures and experimental cooling of the preoptic area
stimulate increased thermogenesis by inducing secretion of thyroid
hormones, by stimulating heat production by neural (adrenergic)
induction of constriction of skin blood vessels, as well as by
neural stimulation of shivering and movement toward warmer places.
Soon after the discovery of
thermosensory neurons in the hypothalamus, in 1963, a set point
for body temperature was discovered in this brain gland (Hammel et
al., 1963). Set points in the brain are not permanent, they can
adaptively change during the individual development. For example,
rabbits acclimated to lower temperatures show lower temperature
set points than the control ones (Tzschenke and Nichelmann, 1997).
Lower than optimal temperatures of incubation induce increased
hypothalamic thermosensitivity and stimulate increase in the
number of warm sensitive neurons. The opposite effect is observed
when eggs are incubated at higher than optimal temperatures (Tzschenke
and Basta, 2002). The incubation temperature has a considerable
influence on the hypothalamic thermosensitivity: during ontogeny,
it is observed that birds incubated at higher than the optimal
temperature (37.50C), during the 10 first days post
hatching, have higher preferred temperatures than birds incubated
at lower temperatures. The hypothalamic thermosensitivity, i.e.
the hypothalamic set points for body temperature, may change
during the evolution of species and even during the adult life of
an individual.
Under stress
conditions, and depending on the degree of the stress, metazoans
may modify the neural set points in order to adapt the physiology
to the stressful conditions. The normal temperature set points are
also changed in response to cyclical variations in hormonal levels
(warm-sensitive neurons increase their activity in response to
estrogens and cool-sensitive neurons - in response to
progesterone, leading to lower and higher temperature set points,
respectively). It is possible that the fever may be an adaptive
mechanism of the hypothalamus, which in response to various
bacterial endotoxins, and other pyrogenic substances, raises the
temperature set point (Boulant,
2000), thus inhibiting
bacterial division. Boulant
concluded that it is in the hypothalamic preoptic area where
Peripheral temperature information
is compared with central temperature information.
As a result of this integration, the
preoptic region controls the level of output
for a set of thermoregulatory responses that are most
appropriate for the given internal and environmental
temperatures. (Boulant, 2000)
Bear in mind that both the
comparison of central and peripheral temperatures and the
integration and processing of temperature information for
producing the neural output that activates the mechanisms of
thermoregulation are computational, hence nongenetic, epigenetic
processes. There is no evidence that any genes are involved in the
determination of set points for the normal or abnormal temperature
in warm-blooded animals or in the mechanisms of thermoregulation.
Central Control of Animal Behavior
Animal behavior is another field of
biological research where the existence and activity of the
control system has clearly been demonstrated.
Animal behavior
comprises motor actions of metazoans in response to external and
internal stimuli. It may be innate or learned. Innate behaviors
are stereotyped motor acts that the animal performs in a
determined sequence. Usually innate behaviors represent adaptive
responses to external and internal stimuli that trigger their
release. Any innate/instinctive behavior is based on the
activation of a set of so-called fixed action patterns (FAP)
determined by specific circuits in the nervous system triggered by
external stimuli known as sign stimuli or releasers.
Examples of instinctive behaviors are migrations, sexual behavior,
oviposition, predation, etc.
Learned behaviors, which only are characteristic
of metazoans (with some exceptional cases observed in eukaryotic
unicellulars), are modifications of normal behaviors as a result
of experience. While learning makes use of species-specific
behavioral elements, experimentally is demonstrated that learning
may significantly influence (strengthen or weaken) innate
behaviors (Mery and Kavecki, 2004) and this results from
modifications of neural circuits/networks for innate behaviors. At
the basis of learning itself is the memory, which is an epigenetic
phenomenon. Imprinting is a classical example of the close
relationship between the learned and innate behaviors.
Brain Control of Locomotion
Vertebrate locomotion results from
coordinated movement patterns produced by CPGs (central pattern
generators) in the central nervous system. It is estimated that
mammal locomotion involves activation of hundreds of muscles and
in particular phases of the movement cycle, which are under
control of the spinal cord CPG (Grillner et al., 1995). Similar
CPGs regulate swimming in lampreys by alternatively activating
motor neurons in both sides of each of 100 segments, successively
but with a phase delay, producing thus an undulatory locomotion.
Initiation of locomotion is function of brainstem neurons. They
project to the spinal cord, activating thus motor neurons and
interneurons (Grillner et al., 1995; figure 1.6)
Figure 1.6.
The segmental neuronal network that co-ordinates locomotion. A
schematic representation of the brainstem, segmental and sensory
components of the neural system that generate burst activity. The
reticulospinal glulamatergic brainstem [R] project to the spinal
cord, and excite all the spinal neurons that are depicted within
the black box. The excitatory interneurones (E) excite all types
of spinal neurones within the box, that is, inhibitory glycinergic
intemeurones (I) that cross the midline and inhibit all neurones
within the contralateral box, the lateral intemeurone (L), which
inhibits the I interneurone, and motoneurones (M), which are
cholinergic. The stretch-receptor neurones are of an excitatory (SRE)
type that excites neurones within the ipsilateral box and an
inhibitory (SRI) type that inhibits all neurones within the
contralateral box. Synapses that are shown to terminate on the
frame of the box indicate effects that are common to all neurones
within the box. The excitatory and inhibitory effects from the
spinal neurones (box) back to the phasic neurones are indicated as
monosynaptic but might have additional relay interneurons. The
tonic neurons receive no feedback from the spinal cord. Note that
only one cell of each type is indicated in the scheme although
each cell represents a group of cells (From Grillner et al.,
1995).
Locomotion in metazoans is epigenetically regulated by the
activity of specific neural circuits and there is no evidence that
any differences in genes may be responsible for different forms of
locomotion in metazoans. The spinal cord provides the motor
pattern (figure 1.7). Excitatory neurons in the spinal cord
project to all other interneurons and motor neurons.
Figure 1.7.
Neural Circuits for Locomotor Behavior in Vertebrate Animals.
(A) A central pattern generator (CPG), located in the ventral
spinal cord controls muscle activity in each limb. CPGs that
control ipsilateral limbs are connected through propriospinal
interneurons. Similarly, the CPGs for homologous limbs on either
side of the body are connected via commissural interneurons. (B)
Renshaw cells and Ia inhibitory interneurons are thought to play
important role in alternation of flexor and extensor motor
neurons (From Sharma and Peng, 2001).
Brain Determination of
Monogamy in Prairie Voles
The prairie vole, Microtus
ochrogaster, is a monogamous species, displaying strong pair
bonding. Exposure of female voles to male olfactory cues,
stimulates estrus and mating-induced pair bonding. The social
attachment in voles is triggered by reception of olfactory cues
by sensory neurons of the vomeronasal organ. This is proven by
the fact that female prairie voles with experimentally lesioned
vomeronasal organ, induced to estrus and mating by
administration of estrogens, do
not exhibit monogamy (Curtis et al., 2001). Sensory neurons
transform the olfactory signal into electrical signals that, via
vomeronasal nerves, are transmitted for processing to
accessory olfactory bulb, the
medial amygdala, stria terminalis, and the anterior hypothalamus
(Keverne, 1999), with the latter determining the monogamous
behavior.
The social attachment is
maintained by a distinctly specific pattern of expression of
receptors for oxytocin and vasopressin (Young et al., 1998), as
well as dopamine (Smeltzer et al., 2005), in specific brain
regions, in monogamous and in promiscuous species. The neural
circuits related to the interaction between oxytocin and
dopamine responsible for monogamous behavior are located in the
brain area known as nucleus accumbens (Liu and Wang,
2003). No changes in genes are involved in determining monogamy
or lack of it in voles.
In humans as well it has been
observed that even smelling of male androgen-like pheromones in
females and female estrogen-like pheromones of human
urine/armpit sweat induces changes in distinct parts of the
hypothalamus in women and men respectively
(Savic et al., 2001). Furthermore, application of male armpit
sweat extracts leads to more regular menstrual cycles in women
(Cutler et al., 1986).
Central
Control of Metazoan Morphology
Examples presented earlier in
this chapter unambiguously show that a number of behaviors and
physiological/homeostatic parameters are under central,
nongenetic control and regulation. However, it would be
inappropriate to use these empirically established facts in
inductive reasoning for generalizing or extrapolating from them
to the entire metazoan kingdom. I take these facts for nothing
more than they are: evidence that some phenotypic characters
(physiological/homeostatic parameters and animal behaviors) are
centrally, nongenetically regulated. These facts, and many more
similar examples, have been long known. I merely have to place
emphasis on the central nongenetic control of these phenotypic
characters.
If two aspects of the metazoan
phenotype, the animal behavior and animal physiology, are
centrally regulated and maintained, it is reasonable to inquire
whether the third aspect, the development of metazoan
morphology, the most visible feature of metazoan evolution, may
also be centrally controlled. My research and my conclusions on
this issue I have made known in my previous work, Neural
Control of Development - An Epigenetic Theory of Heredity
(2004). However, the scope of this book requires that I
include in the present work the basic evidence and arguments I
have already used for substantiating the idea of the central
neural control of animal morphology.
The fact that metazoans are able
to maintain their morphology within “normal” limits, by
appropriately replacing millions of cells and supracellular
structural components they are continually losing, suggests that
the input of received data on losses the organism experiences is
somehow compared to a set of pre-established set points, or
information for the normal metazoan structure. By comparing the
actual state with the desired state (self-established set
points), decisions are made and via signal cascades instructions
are sent for restituting the normal structure.
The myriad of coordinated
chemical and cell interactions, cell proliferation, and cell
apoptosis taking place in the metazoan body are
information-requiring processes rather than random events. If a
control system really maintains the animal morphology, it has to
provide at the cell level the information necessary for these
processes to take place. Hence, one would expect that tracing
back intracellular transduction pathways and further upstream,
outside the cell, signal cascades that activate intracellular
transduction pathways, we might finally reach, to the source of
that information.
As all the above processes (cell
death, cell proliferation, as well as prevention of cell
proliferation) start at the molecular level of gene products, our
attempt for tracing back the flow of information necessary for
these processes has to begin with the signals that induce genes to
synthesize their products.
With genes being effectors and the
focal point of all processes at the molecular level, a basic
prediction of the hypothesis of the neural control of morphology
is that non-housekeeping genes, genes that perform organismic
functions, other than survival and reproduction of the cell, have
to be under central control.
The science of biology has
demonstrated the existence of controls on many different levels
such as the level of genes and signal transduction pathways at the
cellular level, as well as the endocrine, neuroendocrine, and
neural control at organismic levels. I have shown that all these
levels of control form a single hierarchical control system with
each downstream level of control subordinated to the next upstream
level of control (Cabej, 2004). In the following sections I will
attempt to reconstruct this hierarchical integrated control
system (ICS).
Epigenetic Control of Expression of
Nonhousekeeping Genes
No metazoan cell lives exclusively
by itself and for itself. Each of them lives a double life: as an
autoregulated cell per se, and as a virtuoso that, under
the control of extracellular signals, performs one or more
specific functions not for itself, but for the organism. This
double life of cells has determined two different ways of the
control of gene expression in metazoans. On the one hand, as a
heritage from their unicellular ancestry, there is a group of
housekeeping genes, which are necessary for cell’s own
metabolism, subsistence, and reproduction. These genes, whose
minimal number, depending on the metazoan species, is estimated
between several hundred and a few thousands, are autoregulated in
response to signals on the presence of their products and
respective substrates in the cell nucleus or cytoplasm. Such
autoregulatory circuits are demonstrated to exist and be
operational in both unicellulars and multicellulars.
On the other hand, there is the
group of nonhousekeeping genes, which are responsible for
specific functions of each cell within the general scheme of the
division of labor at the organismic level. These specific
functions (mainly the synthesis and secretion of specific
proteins) of the differentiated cells are not related to the needs
of the cell itself, but to the demands of the organism. Hence,
instructions for performing those functions by the differentiated
cells in metazoans are obligatorily extracellular in
origin.
Examples of extracellular signals
known to induce expression of nonhousekeeping genes are numerous.
The orderly activation of Hox genes is known to specify the
establishment of A-P axis during gastrulation in vertebrates. But,
adequate empirical evidence demonstrates that the immediate source
of their activation is an extracellular signal, the hormone RA
(retinoic acid). The hormone is a common immediate regulator of
the activity of almost all of the known homeotic genes, since the
earliest stages of the embryonic development and during the
postnatal development in metazoans (Conlon, 1995; De Luca and
Ross, 1996; Marshall et al., 1996; Clagett-Dame and Plum, 1997;
Cupp et al., 1999; Malpel et al., 2000). In many species RA is
provided maternally, but from the stage of early gastrula it is
secreted by Hensen’s node (Hogan et al., 1992). Other hormones
secreted by endocrine glands, as well, are known to act as
switches for various Hox genes. So, e.g. members of the
Abdominal B (AbdB) Hox gene family, which control the
morphogenesis of the reproductive tract in vertebrates have been
demonstrated to be themselves under the hormonal control of the
estrogen and progesterone (Ma et al., 1998). Administration of
diethylstilbestrol, a synthetic nonsteroidal estrogen in mice, via
estrogen receptors alters the pattern of expression of several
Hox genes involved in the patterning of the
reproductive tract, leading to developmental anomalies (Block et
al., 2000).
No nonhousekeeping gene is master
of its destiny; all of them are, downstream elements of signal
cascades. Far from being “selfish” or “altruistic”, a
non-housekeeping gene is subordinate to upstream elements of
signal cascades. It is these upstream, epigenetic signals that
determine whether a npnhousekeeping gene will be expressed or not.
Chromatin Remodeling in
Control of Gene Expression
The advent of chromatin in
unicellular eukaryotes is a crucial event in the evolution of the
control of gene expression. Adequate evidence demonstrates that
acetylation/deacetylation and methylation of histones by
remodelling the chromatin exert an epigenetic control on gene
expression (Jenuwein and Allis, 2001; Arney et al., 2002; Reik et
al., 2001; Rideout et al., 2001; Nakayama et al., 2001). It can be
imagined that, except for housekeeping genes, probably all the
rest of the metazoan genes, at particular times in particular
cells, are prevented from being transcribed by changes in the
conformation of the chromatin caused by deacetylation (less
frequently by acetylation) of histone proteins (figure 1.8).
Acetylases,
enzymes that induce acetylation of histones, form complexes with
transcription factors, making the binding of the latter to the
regulatory regions of the DNA and the expression of respective
genes possible. Deacetylase enzymes, on the other hand, by
deacetylating histones cause them to wrap the DNA and prevent
transcription of genes (Jenuwein and Allis, 2001). Acetylation/deacetylation
enzymes represent the link between the transcription factors and
genes.
Due to their small molecular mass,
some hormones such as steroid hormones, RA, thyroid hormones, etc.
are essentially involved in the process of chromatine remodeling (Minucci
et al., 1997; Bhattacharyya et al., 1997; Collingwood et al.,
1999; Sachs and Yun-Bo, 2000; Aranda and Pascual, 2001). Mediators
of the effects of these hormones on gene expression are their
nuclear receptors. In the absence of the hormone, its specific
receptor recruits a histone deacetylase complex, thus compacting
the chromatin and preventing gene transcription. In the presence
of the hormone, a complex ligand-receptor forms, which can recruit
a protein with acetylase activity that looses the chromatin
structure making the gene transcription possible.
Figure 1.8. Simplified model of the biochemical basis of
nucleosomal remodeling by histone acetyltransferases and histone
deacetylases. Catalytic transfer of acetyl groups to the terminal
amino groups of lysine residues of histones H2A, H2B, H3, and H4
histones by histone acetylases is thought to result in disruption
of interactions between nucleosomes and DNA, between nucleosomes
and neighboring nucleosomes, and possibly between nucleosomes and
other proteins. The overall loss of compact nucleosomal structure
facilitates access of transcriptional activators and coactivators
to the promoter template. Conversely, recruitment of histone
deacetylases is thought to result in loss of the acetyl groups,
reestablishing the coherence of the nucleosomal structure, and
restricting access of transcription factors to the promoter. Other
covalent modifications may also have a role in regulating
nucleosome interactions (From
McKenna et al.,
1999).
During amphibian metamorphosis,
for instance, thyroid hormone (TH) enters the nucleus where it
binds its nuclear receptor, TR, which forms a heterodimer with
RXR (retinoid Xenopus receptor) and in this active form
it binds to DNA TH response elements (TREs) inducing expression
of genes involved in amphibian metamorphosis or changing their
transcription rate.
Most recently it has been
demonstrated that a histone acetyltransferase (HAT), which
acetylates histones H3 and H4 represents a downstream element of
a signal cascade starting with electrical signals in the retina
and via RHT (retinohypothalamic tract) (glutamate) stimulates a
transduction pathway leading to expression of clock genes, thus
regulating the circadian physiology.
In order to carry out chromatine remodeling, acetylases and deacetylases
first need to be activated by upstream signals, i.e. by
transcription factors. As regulatory proteins, transcription
factors can activate (or inhibit) transcription of specific
genes by binding to their regulatory regions (promoters and
enhancers). But to do so they first need themselves to be
activated. As shown earlier, they may be activated by combining
with specific inducers (nuclear hormones, e.g.). Other times,
their activation results from phosphorylation of their molecules
by terminal elements of signal transduction pathways. Signal
transduction pathways link transcription factors with
extracellular signals. These pathways consist of chains of
intracellular signaling proteins. They are activated by specific
extracellular signals. When an extracellular signal (protein
hormone, growth factor, or secreted protein) binds to its
specific cell membrane receptor it activates enzymatically the
cytoplasmic portion of the receptor. In this active form, the
receptor phosphorylates the first protein of the pathway thus
starting a chain of phosphorylation of other proteins downstream
the pathway, including the transcription factor. The
phosphorylation transforms the transcription factor into an
active form that can induce expression of specific gene(s). In
some cases, signals from the brain, via signal cascades, are
known to be responsible for chromatin remodeling (figure 1.9).
So, e.g. signals from the nonhypothalamic brain induce the
hypothalamus to secrete GnRH (gonadotropin-releasing hormone),
which stimulates the pituitary to secrete FSH (follicle-
stimulating hormone). The latter, in turn, binds its membrane
receptor and via a signal
transduction pathway induces phosphorylation and acetylation of
histone H3 on lysine 14 and/or lysine 9, leading to a
selective gene expression by binding its membrane receptor on
ovarian granulosa cells (Salvador et al., 2001).
It is observed that even a pure
neural process as novel taste learning elicits histone
acetylation and chromatin remodeling (Swank and Sweatt, 2001).
Figure
1.9. Proposed
model for FSH signaling to activate histone H3.
FSH via the catalytic (C) subunit of PKA catalyzes both histone
H3 and CREB phosphorylation as well as histone H1
phosphorylation. Phosphorylated CREB, possibly in conjunction
with SF-1 and Sp1, recruits CBP and possibly other HATs such as
PCAF, inducing histone H3 acetylation and gene transactivation.
Abbreviations:
FSH, follicle-stimulating hormone; CREB, cAMP-response
element-binding protein; PKA, protein kinase A; HAT, histone
acetylase; CBP, p300/CREB-binding protein; SF-1, steroidogenic
factor-1; PCAF, CBP-associated factor (Modified from Salvador et
al., 2001).
A number of neuroactive
substances, antipsychotics as valproic acid and mood
stabilizers, widely used in clinical practice, produce their
effects by stimulating/inhibiting synthesis of acetylases/deacetylases
and inducing gene expression in the neurons. Benzamide MS-275 (Simonini
et al. 2006) and valproic acid (Jeong et al., 2003) inhibit
deacetylases, dopamine antagonists induce acetylases (Li et al.,
2004), and so do pilocarpine and kainic acid (Crosio et al.,
2003).
Extracellular Control of
Signal Transduction Pathways and Transcription Factors
Extracellular signals for gene
expression belong to two main classes: hormones (including
growth factors and neuropeptides) and secreted signal proteins.
Both these groups of inducers are conveyors of upstream
messages. Protein hormones, having a larger mass, cannot enter
the cell and bind specific cell membrane receptors. These
receptor molecules are proteins with a transmembrane and a
cytoplasmic region. Binding of the protein causes
phosphorylation of the cytoplasmic domain of the receptor
molecule. This leads to phosphorylation and activation of the
first protein and then, sequentially, of the rest of the
elements of the transduction pathway. Phosphorylation of the
terminal element of the pathway makes it able to enter the
nucleus where it activates a specific transcription factor by
phosphorylating it. One of the most important signal
transduction pathways is the PKC (protein kinase C) pathway (10
proteins of the PKC family are known so far). The pathway is
used by various hormones, neurotransmitters, and growth factors.
Having shown the causal link
between controls at the levels of genes, chromatine remodeling,
transcription factors, and signal transduction pathways at the
lower portion of the causal chain leading to gene activation,
now let’s attempt to reconstruct and visualize the upstream
signal cascade. The next upstream step is represented by
secreted proteins, growth factors, and protein hormones.
Endocrine Control of Secreted
Proteins and Growth Factors
The most important families of
secreted proteins and growth factors act by binding their
specific receptors on the cell membrane, thus activating
intracellular signal transduction pathways and transcription
factors. Adequate evidence shows that the synthesis of secreted
proteins and growth factors is under control of hormones of the
terminal endocrine glands, the pituitary, or neuropeptides.
The Wnt family
of secreted glycoproteins is involved in modulating cell
proliferation, cell polarity, cell differentiation, and cell
migration during the embryonic and postnatal development. Their
specific cell surface receptors are frizzled proteins and the
intracellular beta-catenin, downstream the pathway (Cadigan and
Nusse, 1997). Wnt proteins act as mediators of hormone
functions. So, e.g. formation of the mammary gland during
adolescence, puberty, and pregnancy, is under hormonal control
of the pituitary, ovary, uterus, and placenta, especially of
estrogen and progesterone. But, recently it has been shown that
it is Wnt-4 that mediates the morphogenetic functions (ductal
branching and budding) of the progesterone in the development of
the mammary gland during the puberty and pregnancy. Via its
nuclear receptor in the mammary epithelial cells, progesterone
stimulates expression of the wnt-4, i.e. the
synthesis of the paracrine Wnt-4 that induces the ductal
side branching (Brisken et al., 2000; Robinson et al., 2000; see
later figure 1.12).
The EGF (epidermal growth
factor) family. The
mitogenic effect of the estrogen, manifested in the growth and
cell differentiation, is mediated by the growth factor, EGF, and
administration of EGF alone mimicks all the effects of the
estrogen (Nelson et al., 1991). The function of testosterone in
differentiation of the reproductive tract is also mediated by
EGF, which phosphorylates its own receptor and other proteins
resulting in activation of genes that make the formation of the
Wolffian duct and its components, the epididymal duct, and
seminal vesicle, possible (Gupta et al., 1991). Estrogen induces
the growth response of the breast epithelial cells by activating
an inactive EGF receptor signaling pathway (Briand et al.,
1999). It is also observed that overexpression of estrogen
receptor-alpha in a cell line inhibits secretion of VEGF
(vascular endothelial growth factor) and the growth of the
vascular wall (Ali et al., 1999). Estrogens and androgens
stimulate transcription of the vegf gene and secretion of
VEGF protein which promotes formation of new blood vessels (Rouhola
et al., 1999). Both EGF and TGF (transforming growth factor)
(Nelson et al., 1991) mediate the proliferative and
differentiation functions of the estrogen in the reproductive
tract of rodents.
The TGF-beta superfamily.
A member of the TGF-beta family is inhibin, a secreted protein.
Its secretion coincides with that of gonadotropin. Inhibin B
secretion by the Sertoli cells is stimulated by FSH
(follicle-stimulating hormone) and inhibited by LH (luteinizing
hormone) (Ramaswamy and Plant, 2001).
The hormone RA (retinoic acid)
stimulates expression of three growth factors of TGF-beta group
of peptides (TGF-beta 1, TGF-beta 2, TGF-beta 3). These factors
also mediate the inhibitory effect of the RA (retinoic acid) on
the embryonic and postnatal seminiferous cord formation and
testis growth (Cupp et al., 1999). RA itself is synthesized from
vitamin A by enzymes aldehyddehydrogenase 1 (Aldh 1),
retinaldehyde dehydrogenase 2 (Raldh 2), and cytochrome P450 (Cyp
26). Expression of these enzyme genes in the female mouse
reproductive system is also under hormonal control of
gonadotropin and can be stimulated by administration of
chorionic gonadotropin (CG) (Vermot et al., 2000).
The FGF
(Fibroblast growth factor) family. In mammals this
family is represented by 10 secreted proteins. They are involved
in various developmental processes, especially in mesoderm
formation, angiogenesis, and in formation of long bones. FGF2
mediates the cell proliferating effect of the hormone
dihydrotestosterone (DHT) in certain prostate cancer cells (the
hormone enables the release of the FGF-2 entraped in the
extracellular matrix) (Kassen et al., 2000). Expression of
FGF-8 (fibroblast growth factor-8) and SHH (sonic hedgehog) are
necessary for the formation of mid- and upper face and brain in
the chick embryo. It is demonstrated that in sites of their
expression the level of the hormone RA (retinoic acid) is
increased as well. Moreover, it is observed that facial and
brain anomalies in the embryos that do not express genes for
those factors may be rescued by local treatment not only with
FGF-8 and SHH proteins but also by RA (Schneider et al., 2001).
Experimental evidence suggests that GH (growth hormone)
expression contributes to the tissue specific expression of the
Igf-1 (insulin-like growth factor-1) gene during
development (Shoba et al., 1999). It is also suggested that the
neurohormone VIP (vasoactive intestinal peptide), may function
as a regulator of Igf-1 gene expression (Hill et al.,
1999; Servoss et al., 2001).
In turn, secreted proteins, via
feedback loops, influence secretion of hormones by endocrine
glands and even by the hypothalamus. So, e.g. the hypothalamic
LHRH (luteinizing hormone-releasing hormone) controls the onset
of puberty in mammals. But growth factors of the EGF/TGF-alpha
family in astrocytes induce production of prostaglandin E2,
which stimulates the secretion of LHRH by the respective
hypothalamic neurons (Ojeda and Ma, 1998).
Neural Control of the Endocrine Function
We have already shown that what
have been considered to be discrete controls at the gene level
via transcription factors, at the epigenetic level of chromatine
remodeling (via acetylation/ deacetylation of nucleosomal
histones), at the level of nuclear hormones and signal
transduction pathways, at the level of protein hormones,
secreted proteins and growth factors are only levels of a single
hierarchical control system.
The remaining upstream portion of
the control system mostly belongs to the history of the 20th
century biology. Production of hormones by target endocrine
glands (gonads, thyroid gland, parathyroid, adrenal, pancreas,
thymus, etc.) in vertebrates is under control of hormones
secreted by the pituitary gland, a fact that led to the
long-held belief that the pituitary was the master gland, which
regulates secretion of hormpnes by the target endocrine glands.
By the middle of the 20th
century, biologists found that secretion of pituitary hormones
is itself under control of a part of brain, the hypothalamus
(weighing only 4-5 grams in humans). With more than 15
“releasing” hormones, and a number of other protein and peptide
hormones (gastrin, angiotensin II, substance P, enkephalins,
etc.) secreted by this gland in higher vertebrates, the
hypothalamus controls the synthesis of most of the pituitary
hormones and appeared to be at the top of the hierarchy of the
neuroendocrine system. But, it is not. The hypothalamus itself
is stimulated or “instructed” to secrete its hormones by
chemical and electrical signals it receives from brainstem
centers (Scott et al., 1999), hipocampus (Lathe, 2001), and
aminergic or cholinergic neurons of various brain centers
(Norman and Litwack, 1997a).
The hypothalamus is not the only
producer of hormones (neuropeptides) in the nervous tissue.
Numerous neuropeptides are secreted by various neurosecretory
cells in many brain centers (what led to the concept of the
“endocrine brain”). Neurosecretory cells in various organs, such
as gonads, pancreas, peripheral nerves, gastrointestinal tract,
etc. also produce important neuropeptides. In distinction from
the hypothalamic hormones that perform their functions via the
pituitary-terminal endocrine glands axis, these neuropeptides
act directly on target cells, by binding to their membrane
receptors. This is the earliest form of neural control, which
evolved in lower eumetazoans and still controls their growth,
metabolism, reproduction (Strand, 1999h), morphogenesis,
organogenesis and regeneration. This control, characteristic for
extant primitive metazoans such as cnidarians and other lower
invertebrates, is known as hormonal system of the first order,
and, as part of the integrated control system, it is still
conserved in the higher vertebrates, including humans. An
example of direct control via neuropeptides is the control
(independently of insulin) of the basal glucose blood level in
rats by the suprachiasmatic nucleus (la Fleur et al., 1999).
At an intermediary and
evolutionarily more advanced position is the endocrine system in
other invertebrates. In insects, for instance, the prothoracic
gland that secretes ecdysteroids is under control of brain
neurohormone PTTH (prothoracicotropic hormone) and other
neuropeptides, while the secretion of juvenile hormone (JH) by
corpora allata is stimulated by neurohormones allatotropins (and
is inhibited by allatostatins), by neurogenic signals via
nervi corporis allati I (from corpora cardiaca) and
nervi corporis allati II coming from the suboesophageal
ganglion, and probably by other brain neuropeptides.
Numerous examples of brain
signals regulating hormonal secretion in the hypothalamus
(sometimes in the pituitary, as well) are known. So, for
example, locus coeruleus in the brainstem exerts an
excitatory influence on the HPA (hypothalamic-pituitary-adrenocortical)
axis by promoting neuroendocrine mechanisms controlling the
physiological mechanisms of the acute stress (Ziegler et al.,
1999). Various receptors in the hippocampus bind ligands that
reflect the physiological status of the organism (stress, blood
pressure, ion balance, reproductive activity, etc.) (Lathe,
2001), an interoceptive process that enables the brain to
constantly monitor the physiological state of body fluids. By
processing that input, it generates its output, i.e. information
that, in the form of chemical/electrical signals, is sent to the
hypothalamus, but probably to other sites as well. By processing
that information on the state of physiological parameters, the
hypothalamus and other brain centers, start signal cascades for
restoring normal levels of various homeostatic parameters. It is
demonstrated that three neurotransmitter systems are directly
(not via the hypothalamus) involved in regulation of the normal
pulsatile LH (luteinizing hormone) release by the pituitary in
the female guinea pigs (Gore and Terasawa, 2001). In experiments
on ewes, Scott et al. (1999) have shown that the noradrenergic
neurons in certain regions of the brainstem possessing oestrogen
receptors (ER), sense the level of estrogen, process that input
and project the information to the GnRH neurons in the
hypothalamus.
The brain-hypothalamic-pituitary
pathway is used for secretion of several pituitary hormones.
For example, the growth hormone (GH) is synthesized in response
to hypothalamic stimulatory- and inhibitory-releasing
neurohormones, GHRH (GH-releasing hormone) and GHRIH (GH
releasing-inhibiting hormone), also known as somatostatin (SS) (Glavaski-Joksimovic
et al., 2002). In turn, GH by binding its receptor, GHR, in the
presence of other compounds, phosphorylates other proteins of
the pathway leading to activation genes for various proteins,
including the IGF (insulin-like growth factor).
Let’s visualize the structure and
function of the control system in a real example on the control
of expression of a gene in muscles, liver, and adipose tissue
(figure 1.10).
Summarizing the evidence
presented so far, it may be said that specific hormones control
expression of the growth factor- and secreted protein genes
and/or activation of their receptors and, consequently,
expression of nonhousekeeping genes. Secretion of the hormones
of the target endocrine glands is induced by specific pituitary
hormones, which in turn are induced by specific hypothalamic
neurohormones. The ultimate upstream signals in this hierarchic
system of control are signals from various parts of the brain
which determine secretion of the hypothalamic “releasing”
hormones (figure 1.11).
The mechanism of expression of
non-housekeeping genes in metazoan organisms includes not only
linear signal cascades but also cross talk between cascades,
activation of neural non-hypothalamic pathways and downstream
gene regulatory networks involved in complex interactions
between them.
It may be argued that no
generalization on the extracellular control of expression of
non-housekeeping genes can be made for neither all the signal
cascades triggering transcription of nonhousekeeping genes have
been demonstrated, nor are all metazoan species investigated in
this respect. As a counterargument, I might remind the reader
that the same anti-inductive judgement could be used against
most of the general concepts of modern biology. The common
origin of metazoans and the amount of evidence accumulated so
far, provides sufficient grounds to infer that the
extracellular and central regulation is the general mode of
transcription of non-housekeeping genes in metazoans.
Nature does not make tricks.
Figure 1.10.
Diagram of regulation of insulin, growth hormone (GH), and
insulin-like growth factor-1 (IGF-1).
Abbreviations:
IGFBP-3, IGF-binding protein-3; ALS, acid-labile subunit
(Slightly extended from Clemmons, 2004,).
Note that the diagram presents
not simply a signal cascade but the whole neuroendocrine system
that effectuates the “cascade”. The cascade is a systemic
response of the organism to external/internal stimuli and the
diagram comprises some basic components and features of the ICS
(integrated control system) in vertebrates. It shows the
hierarchical character and the presence of feedback loops in the
ICS. The feedback loops enable the monitoring function of the
control system and the central nervous system represents the
controller of the system, the place where the data on the state
of the system are sent and processed for generating the
information on the actual state of the system, which is
compared with the information on the normal state, i.e.
with neurally determined set points/thresholds (=epigenetic
information) in the CNS. By comparing the input on the state of
the system with the “normal” state of the system, the CNS
determines deviations from the norm and computates instructions
for restoring the normal state. These instructions for restoring
the normal state are sent to respective target cells/tissues via
signal cascades (biological algorithms). Note also that the
direction of the flow of information for adaptive changes is
from the central nervous system all the way down to the target
cells and tissues.
Figure 1.11.
Diagramatic representation of the cascade of events in the
neuroendocrine system. A cascade of hormonal signals starting
with an external or internal environmental signal. This is
transmitted first to the CNS and may involve components of the
limbic system, such as the hippocampus and amygdala. These
structures innervate the hypothalamus in a specific region,
which responds with secretion of a specific releasing hormone.
Thick arrows represent the flow of information through signal
cascades; thin arrows represent the input on the state of the
system and dotted arrows represent the feedback input (Modified
from Norman and Litwack, 1997).
Examples of Central Control
of Metazoan Morphology
Now, let’s consider just three
representative examples of the CNS control of the
development of animal morphology by visualizing the signal
cascades (including associating feedback loops and cross talk)
and intracellular pathways in the process of the translation
of brain signals into animal morphology. An extensive review
of the issue is presented in chapter 6 (Neural Control of
Post-phylotypic Development).
Development of the Mammary
Gland
Mammary gland is a unique
mammal structure that evolved some 200 million years ago to
provide the mammalian newborns with milk. Although mammals are
born with a mammal Anlage, the gland develops predominantly
after the puberty and post partum.
The entire developmental
program, mimicking embryonic development of other organs, can
be viewed and followed in the post partum animals. (Hennighausen
and Robinson, 1998)
Formation of the gland is under
a complex control of systemic hormonal signals from the
pituitary (prolactin) and the ovary (estrogen, progesterone).
Local mediators of these hormones are growth factors such as
Wnt (Sasson, 1999), EGF, TGF-beta proteins, and hormones like
VIP (vasoactive intestinal peptide), and hypothalamic TRH (thyrotropin-releasing
hormone) (Gilbert, 1997d). The developmental pathway starts in
the CNS (figure 1.12): in response to internal signals
related to the activation of the GnRH pulse generator in the
hypothalamus, and especially to gestation. Critical for the
development of the gland is the release a neuropeptide, PrRP (prolactin-releasing
peptide) by neurons of the caudal part of the solitary tract.
The neurohormone, by acting directly on the pituitary, or
indirectly, by stimulating secretion by the hypothalamus of
the PRF (prolactin-releasing factor) and PRIF (prolactin-releasing
inhibition factor), induces secretion of pituitary prolactin.
Figure 1.12.
Simplified diagram of the development of the mammary gland
during puberty and gestation in mammals.
Abbreviations: GnRH, gonadotropin-releasing hormone;
PRF, prolactin-releasing factor, in post partum animals. (Hennighausen
and Robinson, 1998).
The Central Control of Body
Mass
Besides the known hormonal
mechanisms of the control of body mass (Pelleymounter et al.,
1995; Halaas et al., 1995; Norman and Litwack, 1997d), recent
studies suggest the existence in the vertebrate CNS of a set
point for the body mass.
Intraperitoneal implantation of
metabolically inert masses in the deer mouse, Peromyscus
maniculatus, causes an equivalent compensatory loss of
body weight. In the third day after the removal of the implant
the animals regained the preexperimental body weight.
Investigators argue that the changes in the body weight
suggest the existence of a set
point that is sensitive to changes in the perception of mass
and that is transduced via neural pathways. (Adams et
al., 2001)
They also believe that numerous
mechanoreceptors located within muscles and tendons that have
afferent pathways to cerebral cortex could provide the input
necessary for changing the set point. Since the set point is
located in the brain and is related to the processing of the
sensory input by the brain, the growth processes adjusting the
body weight to the changed set point must start with brain
signals as well (Adams et al., 2001).
Administration of some
centrally acting substances, such as sibutramine, lower body
weight set point and have found some use as medicaments for
body weight loss in medicine. In response to administration of
sibutramine rats increase the sympathetic activity, reset and
decrease levels of NPY (neuropeptide Y) and POMC (proopiomelanocortin).
Since sibutramine is a serotonin reuptake blocker, rats also
respond to its administration by elevating the extracellular
level of serotonin in the rat hypothalamic arcuate nucleus,
thus centrally inducing body weight loss (Levin and Dunn-Meynell,
2000). A similar central effect for inducing body weight loss
has experimental administration of another neuroactive
substance, the serotonin-releasing agent, fenfluramine
(Fantino et al., 1986).
In insects, insulin signaling
is necessary for normal growth. Insulin-like peptides are
neurohormones, whose secretion is
controlled by the central
nervous system. This is important, because it implies that
growth, and size, must ultimately be controlled by mechanisms
that include the neurosecretory system of the brain. (Nijhout,
2003)
Nijhout also believes
that growth, and size, must
ultimately be controlled by mechanisms that include the
neurosecretory system of the brain. (Nijhout, 2003)
He reasons that the
developmental control of body size essentially is control of
the moment when to stop growing and in insects this is related
to the timing of the secretion of ecdysteroid hormones, which
depends on the timing of secretion of the brain hormone, PTTH
(prothoracicotropic hormone), which depends on the brain
photoperiodic clock. While insulin-like peptides/insulin
growth factors, produced mainly by neurosecretory cells,
stimulate the insect growth, secretion of ecdysone and its
receptor counteracts that effect in a neurally controlled
circuit (Colombani et al., 2005).
For further information on the
neural control of the body mass see also Neural
Control of the Body Mass (chapter 6) and
Evolution of Body Size (chapter 14).
Maintenance of Normal
Obesity
In adult vertebrate organisms
fluctuations in the body weight chiefly result from
fluctuations of the fat storage. Maintenance of the normal
weight implies, among other things, the existence of a
mechanism that regulates the food intake. This regulation is
very complex but, reduced to its essentials, the regulatory
mechanism consists of specific neurons of the hypothalamic
arcuate nucleus and neurons in another region of the brain.
The arcuate nucleus contains two types of neurons,
eating-stimulating and eating-inhibiting neurons. Two
different groups of signals are received by those neurons. In
response to increases in fat store, the appetite-inhibiting
neurons are activated and the appetite-stimulating neurons in
the arcuate nucleus are inhibited. The signals from the
appetite-inhibiting neurons will dominate the input in the
neurons that control the food intake and energy expenditure.
Thus, by decreasing the food intake and energy expenditure,
the brain induces decreases the excess of fat in the body.
Besides this long-term mechanism, in vertebrates there is a
short-term mechanism based on the release of three kinds of
hormones, ghrelin (released by the stomach), cholecystokinin,
and the peptide hormone PYY3-36,
released by the colon in an immediate response to food intake.
The input of these three hormones is processed in the
appetite-stimulating neurons of the arcuate nucleus and via
the shown pathway stimulates food intake (Batterham et al.,
2002; Schwartz and Morton, 2002; figure 1.13).
Figure 1.13.
Hormones that control eating.
Leptin and insulin (lower part of the figure) circulate in the
blood at concentrations proportionate to body-fat mass. They
decrease appetite by inhibiting neurons (centre) that produce the
molecules NPY and AgRP, while stimulating melanocortin-producing
neurons in the arcuate-nucleus region of the hypothalamus, near
the third ventricle of the brain. NPY and AgRP stimulate eating,
and melanocortins inhibit eating, via other neurons (top).
Activation of NPY/AgRP-expressing neurons inhibits melanocortin-producing
neurons. The gastric hormone ghrelin stimulates appetite by
activating the NPY/AgRP-expressing neurons. Batterham et al.
have now shown that PYY3-36, released from the colon, inhibits
these neurons and thereby decreases appetite for up to 12 hours.
PYY3-36 works in part through the autoinhibitory NPY receptor Y2R
(From Schwartz and Morton, 2002).
In response to PYY3-36 hypothalamic
circuits modify their synaptic morphology (Batterham et al., 2002)
and probably their output. Neurons expressing the receptor for
melanocortin4 (MC4-R) in the arcuate nucleus respond rapidly to
signals of satiety that do not require changes in leptin and control
organism’s metabolic and behavioral responses to the fat diet
(Butler et al., 2001).
The Integrated Control System
We have argued that metazoan
organisms, while are continually losing their structural order at
the cytological and molecular levels still avoid structural and
functional degradation and maintain their biological identity.
It is impossible to imagine how a structure enormous
complexity, such
as a metazoan organism is, would be maintained in absence of a
control system. Human experience shows that even the
incomparably simpler man-made systems cannot function without a
control system (in the form of built-in mechanisms or human
supervision and operation) for maintaining its structure and
function.
A control system for maintaining the structure and function is a
sine qua non condition for metazoan life as it is for
unicellulars.
Adequate evidence, a small part of
which was presented in this chapter, shows that there is a central
neural control, which regulates not only metazoan behaviors and
physiological/ homeostatic variables, but also expression of
nonhousekeeping genes. Finally, I have presented three examples of
the central control of the development and maintenance of metazoan
morphology. Based on that evidence, I argued that the maintenance
of the eroding metazoan structure implies the existence in
metazoans of a control system, which compensates for losses and
directs the restoration of that structure.
Extensive evidence on the neural
control of the development of animal phenotype will be presented
in chapters 6 (Neural Control of Post-phylotypic Development),
9 (Behavioral Adaptation to Changed Conditions of Living),
11 (Intragenerational Developmental Plasticity), 12
(Transgenerational Developmental Plasticity), 14 (Origins
of Evolutionary Novelty), and 19 (Epigenetics of Sympatric
Speciation).
A conceptual barrier separating
what have been considered discrete and independent mechanisms of
control at the genetic, intracellular-epigenetic, endocrine,
paracrine, autocrine, and neural levels is rapidly crumbling. The
emerging picture shows them all to be elements of a single
integrated control system (ICS).
Now I will attempt to visualize the
main features of the ICS in metazoans.
The concept of the control system
in metazoans implies a system that controls and regulates their
function and structure at all the levels of the organism. In
general terms, the control system in metazoans performs:
1. Monitoring of the status of the
system,
2. Comparison of the input on the
state of the system with the norm (=neurally determined set
points),
3. Identification and assessment of
deviations from the norm, and
4. Decision-making and transmission
to effectors of “instructions” for restoring the “norm” or for
adapting the organism to the new conditions of living by
activating appropriate signal cascades.
We have seen that, in the cases of
phenotypic (behavioral, physiological, and morphological)
characters considered in this chapter, the above functions are
performed by the pervasive nervous system and the endocrine system
as its physiological extension.
The ICS (integrated control system)
is a hierarchical system with the CNS (cental nervous
system) functioning as the
controller of the system (figure 1.14). Vast
experimental evidence shows that signal cascades for expression of
nonhousekeeping genes and for the development of many organs
during individual development, as well as for developmental
plasticity, originate in the CNS, suggesting that the latter is in
possession of information on the normal supracellular structure,
or morphology in general. This arises a crucial question on the
nature and origin of this information. How this nongenetic
information is generated and stored in the central nervous
system/nervous system will be subject of a special section in
chapter 2.
The Hypothesis
of the Epigenetic System of Heredity and its Predictions
The idea on the presence of control
systems in metazoans is not conjectural. In this chapter I have
presented illustrative evidence demonstrating its role in
controlling and regulating the animal phenotype: behavior,
physiology and morphology. This, and the extensive evidence on the
essential involvement of the CNS in the individual development to
be dealt with later in this work (chapters 3, 4, 5 and 6), led me
to the formulation of the hypothesis that the integrated
control system (ICS), with the CNS as its controller, in the
process of animal reproduction, functions as an epigenetic system
of heredity, providing the information for animal morphology
(Cabej, 2004b).
Figure 1.14.
Generalized and simplified diagram of the control system in
metazoans with CNS acting as controller of the system. Metazoan
structure degrades continually due to intrinsic
thermodynamically-determined causes as well as a result of adverse
influences of the environment. Changes in the structure and
function of the organism and environmental changes are monitored
by a pervasive network of interoceptors and exteroceptors and
communicated to the controller. In the CNS, the input is compared
with the neurally-determined set points (1). Deviations from the
norm are identified (2) and pathways for restoring the norm are
determined (3). “Instructions” (=epigenetic information) for
restoring the norm (4) are sent to effectors in target tissues
and cells through signal cascades. Via a feedback input the
controller receives information on the restored/degraded state of
the system.
This hypothesis is empirically
verifiable and falsifiable; it is open to scientific inquiry and
experimentation. The basic predictions of the hypothesis are the
following:
1. The expression of
nonhousekeeping genes in metazoans is controlled and regulated by
signal cascades originating in the CNS.
2. Initial signals, or the
information, for starting signal cascades in the CNS are
nongenetic, i.e. epigenetic, by origin.
3. The reproduction cycles and
gametogenesis, production of egg- and sperm cells, in metazoans
are under control of the epigenetic system of
heredity, with the CNS as source of the epigenetic information.
4. The transfer of the epigenetic
information (parental cytoplasmic factors and gene imprinting) in
gametes is regulated by the parental epigenetic system(s) of
heredity.
5. At the phylotypic stage, when
the function of maternal cytoplasmic factors terminates, the
embryonic CNS is operational and takes
over the control of the embryonic development up to
adulthood.
6.
Signal cascades determining the postphylotypic development
originate in the embryonic CNS.
For
verifying the hypothesis of the epigenetic system of heredity in
the following chapters of the first part of this book I will
present evidence that the ICS, which in the process of metazoan
reproduction serves as an epigenetic system of heredity, controls
and regulates all the main stages of the process of biological
reproduction:
-
Reproduction cycles (chapter 3),
-
Gametogenesis, i.e. formation of the mature egg and sperm cell
(chapter 4),
-
Early embryonic development, up to the phylotypic stage (chapter
5), and
-
Post-phylotypic development (chapter 6).
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