Implications of the ‘Energide’ concept for communication and information handling in the central nervous system

Abstract

Recently a revision of the cell theory has been proposed, which has several implications both for physiology and pathology. This revision is founded on adapting the old Julius von Sach’s proposal (1892) of the Energide as the fundamental universal unit of eukaryotic life. This view maintains that, in most instances, the living unit is the symbiotic assemblage of the cell periphery complex organized around the plasma membrane, some peripheral semi-autonomous cytosol organelles (as mitochondria and plastids, which may be or not be present), and of the Energide (formed by the nucleus, microtubules, and other satellite structures). A fundamental aspect is the proposal that the Energide plays a pivotal and organizing role of the entire symbiotic assemblage (see Appendix 1). The present paper discusses how the Energide paradigm implies a revision of the concept of the internal milieu. As a matter of fact, the Energide interacts with the cytoplasm that, in turn, interacts with the interstitial fluid, and hence with the medium that has been, classically, known as the internal milieu. Some implications of this aspect have been also presented with the help of a computational model in a mathematical Appendix 2 to the paper. Finally, relevances of the Energide concept for the information handling in the central nervous system are discussed especially in relation to the inter-Energide exchange of information.

Appendices

Appendix 1

In view of the difficulties in moving from a ‘scientific paradigm’ to a new one, it is important to clarify the theoretical basis of the new paradigm. Accordingly to Kuhn, a new paradigm gains status when it is found to be more successful than its competitors in solving problems that had previously been recognized, within the old accepted paradigm, as critical ‘sticking points’ (Kuhn 1996).

Premises

According to the classical Cell Paradigm, cells represent the basic unit of living systems. In this cellular view of life, the limiting membrane plays the dominant role whereas the internal parts are extremely variable. They vary from having just a few DNA molecules encoding several proteins within highly reduced organelles, up to the extremely complex cellular interiors of coenocytes and syncytia encompassing hundreds of nuclei and enormous numbers of other organelles (also cells) within a common communal cytoplasm (Baluška et al. 2004a, 2004b; Shepherd et al. 2004). All this blurs the Cell Paradigm.

In contrast to this diffuse and vague situation with cells, the Energide Paradigm clearly indicates two components:

• The Energide, which consists of a nucleus (the ‘Energide core’ where the DNA is localized), centrosome, microtubules, ER, GA, GA-based secretory vesicles, and ribosomes. It gains control over the original cell periphery-based structures, such as the actin cytoskeleton and endosomes.

• The Cell Periphery Complex, which consists of the plasma membrane, extracellular matrix/cell wall, endosomes, and the actin cytoskeleton. The DNA has been mostly transferred into the nucleus. Nevertheless, the cell periphery still maintains some structural independence as it is essential for sheltering the Energide, providing it with information about the environment outside the cell, and generating the endosomes, lysosomes, as well as vacuoles in order to provide the Energide with nutrition, to process these nutritionally relevant substances, as well as to store nutritive and energy-rich compounds. Also, this system is responsible for detoxification of toxic compounds entering cells. Early in cellular evolution, this endosomal system was adjusted for rapid repair of damaged cell periphery and for final events in cytokinesis.

It should be noted that the structure and morphology of the Energides are essentially the same throughout the eukaryotic super-kingdom, implying that they are more useful for defining the basic vital units of supra-cellular eukaryotic life (Baluška et al. 2006a). Furthermore, the Energide has all the tools necessary to regulate its own motility, the distribution of organelles and the reproduction of enclosing cell. Some autonomy is still maintained by other evolutionary more novel guest cells like mitochondria and plastids.

Importantly, an inherent feature of most cells seems to be the capability of forming cell–cell channels (known plasmodesmata in plants and tunneling nanotubes in animals). Furthermore, in some instances it has been shown that if cell–cell channels are sufficiently large, even the whole of an Energide can move from its original cell into an adjacent cell (Baluška et al. 2004a). In particular, for mycorrhiza fungi it is known there are numerous genetically different Energides in one cytoplasmic space and that transcellularly moving fungal Energides communicate with their mating partners via pheromone-like signalling mechanisms (Kuhn et al. 2001; Sanders 2002; Hijri and Sanders 2005; Croll et al. 2008). Thus, each Energide is a genetical individuum and, from its own cellular space, it communicates with Energides located in other cellular spaces. On the basis of this exchange of information, the mating process can or cannot proceed. This can be taken as evidence that, at least in this case, the Energide is an autonomous organism representing the universally valid unit of supra-cellular eukaryotic life.

Analysis of the two paradigms

It can be a clarifying approach to examine the resemblances and the differences between the old paradigm (the Cell) and the new paradigm (the Energide), just following Bacon’s suggestion:

A mind agile enough to recognize the resemblance of things (and this is the most important), and sufficiently steadfast and eager to observe the refinements of their diversity [Bacon: De Interpretatione Naturae Spedding, Vol. vi (1603)].

From this analysis we will proceed to point out which aspects of the current Energide paradigm is not in a total agreement with the available experimental evidence. On this basis, a broader and less rigid definition of ‘Energide’ will be proposed.

• 1. Resemblances between the two concepts:

• a. The Cell and the Energide are both intended to be the ‘fundamental unit of the living beings’ as such they are supposed to be:

  • Capable of independent life.

  • Capable of synthesizing their entire structure.

• b. The Cell and the Energide are both separated form the environment, which embeds them.

• 2. Differences between the two concepts:

  • a. The Cell and the Energide have different sizes. The Cell size is much bigger than the Energide size.

  • b. The Cell is separated by its external environment by the cell membrane, hence by a well defined structure. The Energide is separated by its external environment by perinuclear radiating microtubules, which define spheres of influence of individual Energides and are essential for preventing accidental nuclear fusions, which would easily happen either during cytokinesis or after cell–cell fusions. Thus, more than from a structural encasing boundary (as the Cell), the Energide is limited by a functional barrier determined by microtubules which allow active intracellular movements (Baluška et al. 2001).

  • c. The Cell and the Energide have markedly different mechanisms to control the exchange of information and/or substances with the environment, which embeds them. It could be stated that while the Cell is exposed to its external environment, the Energide lives in a privileged internal milieu or subcellular niche (the cytosol, a micro-cosmos accordingly to the present paper). As a consequence while the Cell is impinged upon by any signal present in its external milieu, the Energide works on signals that are acquired (filtered) and most of the times already processed at the plasma membrane level.

  • d. The Cell has no independence from the Energide (in particular from the nucleus and its DNA) while the Energide can survive for short time periods without the cell periphery and thanks to the endosomes regenerate new cell periphery (see Baluška et al. 2006b). It is important to stress that endosomes represent miniature cell periphery complexes. Actually, their limiting membrane is derived from the plasma membrane and the endosomal interior is biochemically equivalent to the cellular exterior.

  • e. The Energide has exploratory capabilities of its own cellular-space, i.e. of its own micro-cosmos. As a matter of fact:

    • Energide-associated dynamic microtubules can act as vehicles allowing the movement of whole Energides through cellular space (Baluška et al. 2001, 2004b, 2006a).

    • The Energide can even abandon its own micro-cosmos to invade, via tunneling nanotubes, adjacent cellular spaces (e.g. Giovannetti et al. 2001, 2006).

  • f. The Energide can repair old and generate new cell periphery structures from endosomes and Golgi complexes (Baluška et al. 2006b). Importantly in this respect, perinuclear microtubules of premitotic plant cells induce local endocytosis and endosome formation (Dhonukshe et al. 2005) which are later used for new generation of cell periphery during cytokinesis (Dhonukshe et al. 2005, 2006; Baluška et al. 2006b). It has been also shown that the Energide can generate the cell periphery complex de novo during spore formation in fungi (Shimoda 2004; Neiman 2005; Nakamura et al. 2008) and sperm cells in plants (Baluška 2004b, 2006b). Similarly as during new cell periphery formation in termination of cytokinesis (Dhonukshe et al. 2006; Baluška et al. 2006b), also here endosomes recruited by active Energides plays the critical role. De novo formation of the new cell periphery was also described in protoplasts derived from marine green alga (Kim et al. 2001; Ram and Babbar 2002).

  • g. It should be stressed, on the contrary with respect with the cell periphery, that an entirely new Energide can be formed only by a previous Energide by a process of mitosis. So the Energide is the primary, more independent, and self-replicative part of eukaryotic cell.

• 3. Characteristics not supported by the available experimental evidence for:

  • a. The paradigm of ‘Cell’: the usual definition of Cell lists as components of this basic structure a nucleus (or at least DNA), some cytoplasmic organelles and the plasma membrane. It has been demonstrated that these situations are possible:

    • Cells without the plasma membrane.

    • Cells with more than one nucleus (coenocytes and syncytia).

    • Cells without nucleus (red blood cells) or of some of the peripheral organelles.

  • b. The paradigm of ‘Energide’: lives out some other guests of the cell space, namely mitochondria and plastids. These organelles have their own DNA and their membrane structure serves as a template for the assembling of the molecules added to the structure during the replication process to reach the condition of fission.

A refined definition of the basic living unit

It is suggested that a less rigid definition of the basic living unit can better satisfy the available experimental evidence. It can be proposed that the basic living unit of the eukaryotic life domain is a mosaic assemblage of different components, which are organized around a pivotal primary structure, the Energide.

Thus, in most instances the living unit is the:

• Supra-Energide, that is the symbiotic assemblage of the Energide (pivotal and primary component) with some peripheral semi-autonomous cytosol organelles (as mitochondria and plastids), which may be or not be present.

In agreement with the new paradigm, the basic living unit the eukaryotic life domain is the Energide. However, in view of the fact that in eukaryotic cells mitochondria and plastids are usually present, the Supra-Energide Paradigm should be considered.

Appendix 2

When compared to the structural organization where just one internal milieu (i.e. the interstitial fluid) exists between the external world and the living unit (i.e. the cell), the organization of the internal environment in two nested milieux can increase the capability of the system to buffer stress and disturbances, leading to more stable conditions in the environment surrounding the Energide (assumed to be the smallest eukaryotic living unit). Simple abstract systems exhibiting such an improved buffering property can be devised. They can be considered as toy models of a system of nested milieux, useful to illustrate some very basic properties of its dynamics and the potential advantage of this structural organization.

Basic assumptions of the model

• A milieu is represented by a set of state variables {p _i , i = 1,…,n}. We can think at them as representing some physical (e.g. electrical polarization) or chemical (e.g. concentration of some substance) characteristic of the milieu, important for the proper function of the living unit.

  The value each state variable assumes will depend on the value assumed by a sub-set of the other variables. The polarization level, for instance, is dependent on the concentrations reached by some key ion. Thus, in general we can write:

  $$ p_{i} = f_{i} (p_{j} ) \quad \left\{ {p_{j} } \right\} \subseteq \left\{ {p_{i} ,i = 1, \ldots ,n} \right\} $$

  An example consistent with such a structure is provided in Fig. 5a.

• Two nested milieux will be characterized by two sets of state variables:

  $$ \begin{gathered} {\text{Milieu 1:}}\;\left\{ {p_{i} ,i = 1, \ldots ,n} \right\} \hfill \\ {\text{Milieu 2:}}\;\left\{ {P_{i} ,i = 1, \ldots ,m} \right\} \hfill \\ \end{gathered} $$

  We will assume that the two milieux are open and can exchange entropy (Toussaint and Schneider 1998). As a consequence, they are coupled and the value of each state variable will depend in general on the values exhibited by a sub-set of state variables belonging to the same milieu, as well as on the value of some state variables of the other milieu:

  $$ \left\{ {\begin{array}{*{20}c} {p_{i} = f_{i} (p_{j} ,P_{k} )} & {\left\{ {p_{j} } \right\} \subseteq \left\{ {p_{i} ,i = 1, \ldots ,n} \right\}} & {\left\{ {P_{k} } \right\} \subseteq \left\{ {P_{i} ,i = 1, \ldots ,m} \right\}} \\ {P_{i} = F_{i} (p_{z} ,P_{t} )} & {\left\{ {p_{z} } \right\} \subseteq \left\{ {p_{i} ,i = 1, \ldots ,n} \right\}} & {\left\{ {P_{t} } \right\} \subseteq \left\{ {P_{i} ,i = 1, \ldots ,m} \right\}} \\ \end{array} } \right. $$

  An example consistent with such a structure is provided in Fig. 5b.

• Many biological processes undergo substantial changes only when environmental parameters are below or above some threshold level. Examples include the concentration of glucose to stimulate insulin secretion or the extracellular aminoacid concentration needed for protein synthesis (Griffiths 1972). Thus, as a first approximation, the state variables will be here assumed to be binary quantities, i.e. able to assume two values only (e.g. ‘low’ or ‘high’ concentrations, ‘negative’ or ‘positive’ polarization etc.), which will be scored with the values ‘0’ and ‘1’ respectively.

Fig. 5

a Possible organization of a single milieu characterized by four state variables. As indicated, the value each variable assumes in the time depends on its actual value and on the values exhibited by other two state variables of the system. b Example of a system formed by two interacting nested milieux, each characterized by four state variables. Each state variable depends on other two variables of the same milieu, but also on the value of a state variable of the other one. Thus, as for the system in a, the value assumed by each variable is controlled by three input values. c Basins of attraction for the system in a when the transformation rule described in the text is assigned to each variable of the system. Basins of attraction are shown as graphs (called transition graphs) representing the set of configurations converging to a same attractor. Configurations are shown as dots linked to their successors and the direction of time is inwards from the more external dots to the attractor cycle, located at the centre. The number of configurations belonging to each basin is reported at the bottom of each graph as percent of the total number of configurations available to the system. d. Basin of attraction when the same rule is applied to the system in b. In this case, the observed attractor is a single (stable) configuration

As a consequence, the above mentioned f _i and F _i functions will become discrete transformation rules assigning a value to the i-th variable based on the values of the variables from which it depends. With reference to the structures illustrated in Fig. 5a, b, in which each variable depends on the value of other three variables, an example of discrete f _i (or F _i) is the following transformation table:

p k k = 1,…,3	1	1	1	1	0	0	0	0
	1	1	0	0	1	1	0	0
	1	0	1	0	1	0	1	0
f i (p k )	1	0	0	0	1	0	1	1

It associates a value to the i-th variable for each of the eight possible combinations of values exhibited by the three argument variables.

Following these simplifying assumptions a milieu, or a system of two nested milieux, can be roughly approximated with a Boolean network (Kauffman 1993). In fact, Boolean networks are dynamic systems, composed of binary units, in which each unit change state in discrete time steps by the application of a simple local rule, i.e. based on the states of a number of other units with which it is connected.

According to this representation, we can define a state-space of a milieu (or a system of nested milieux) as the set of all possible configurations it can have. For a milieu of size N (i.e. with N state variables) there are 2 ^N unique configurations. Starting from some initial configuration and repeatedly applying a transformation rule the system will move through a succession of configurations which can be seen as a trajectory in the state-space. Because the state-space is finite, sooner or later the trajectory must encounter a state that occurred before. When this happens, because the system is deterministic, the trajectory becomes trapped in a cycle of repeating configurations, or attractor. The number of time-steps between the repeats of a configuration is the attractor period, which could be just one if the system is stable in a fixed configuration or could be very large if the system is characterized by a chaotic behaviour. The same attractor can be reached starting from many different initial configurations and the set of trajectories that flow in it is called the basin of attraction. The whole set of basins of attraction of a specific milieu is known as the basin of attraction field. Since it partitions, categorizes, the whole state-space into a limited number of attractors, the basin of attraction field provides an explicit global portrait of a milieu entire repertoire of behaviour.

Numerical simulations of the system

All the simulations were performed by using the DDLab software (Wuensche 2003) and routines specifically developed by the authors.

The present simulations have been carried out on the milieu structures illustrated in Fig. 5a, b to derive some insight on the differences between the two organizations in terms of stability by exploring the configurations at equilibrium (attractors) in the two cases. To make easier a comparison the same f _i (i.e. the same transformation rule) was applied to all the state variables involved.

• In a first simulation the transformation rule reported in the table above was used. As shown in Fig. 5c, the dynamics of the system corresponding to a single milieu (Fig. 5a) is characterized by two attractors: one is stable (a single configuration) and the other is ‘chaotic’, since at equilibrium the system cycles through four different states, a quite large number being the system characterized by only 2⁴ = 16 unique configurations. Moreover, starting from a random configuration, the probability to converge to the stable attractor is 0.25, while for the chaotic attractor is 0.75.

  When the same rule was used in the system representing two nested milieux (Fig. 5b) the stability of the system significantly increases, being the system characterized by a single stable attractor (Fig. 5d), meaning that perturbations can be completely buffered.

• The just described result, however, refers to a specific choice of the transformation function, while the number of possible transformation rules in a system where the value of each element depends on the values of three inputs is 256 (Wuensche 2003). An exhaustive analysis performed on the whole spectrum of transformation rules showed that about 6% of the rules led to single stable attractors when applied to a system formed by a single milieu. Such a percentage increased to about 15% when the system was organized in two nested milieux. Moreover, the attractor cycles resulted on average 25% shorter in this system as compared to the organization formed by a single milieu.

Altogether the results provided by the simple toy model here described support the hypothesis that a structural organization of the internal environment in two nested milieux can provide advantages in terms of stability and resistance to disturbances.