Regulation in Biological Systems

Abstract

Any processes which occur in thermodynamically open systems must be automatically regulated if they are to maintain a steady state. Note that there is an important difference between a steady state and a state of equilibrium, since in the latter case no spontaneity is possible. The need to maintain a steady state ensuring homeostasis is an essential concern in nature, while negative feedback loop is the fundamental way to ensure that this goal is met. The regulatory system determines the interdependences between individual cells and the organism, subordinating the former to the latter. In trying to maintain homeostasis, the organism may temporarily upset the steady-state conditions of its component cells, forcing them to perform work for the benefit of the organism. Adopting a systemic approach to the study of regulatory mechanisms explains the mutual dependencies which, taken together, form the foundation of life.

On a cellular level, signals are usually transmitted via changes in concentrations of reaction substrates and products. This simple mechanism is made possible due to limited volume of each cell. Such signaling plays a key role in maintaining homeostasis and ensuring cellular activity. On the level of the organism, signal transmission is performed by hormones and the nervous system. This work addresses the problems of regulation on a systemic level.

Maintaining a steady state in thermodynamically open systems requires regulation.

• 1. Regulation and control—what is the difference?

• 2. Types of control.

• 3. What is the importance of the allosteric effect for biological regulation mechanisms?

• 4. Role and mechanism of action of G proteins.

• 5. What is the relationship between the organism and the cell in terms of regulation?

• 6. Why and when does amplification of signals become necessary?

• 7. When must a regulatory signal be encoded?

• 8. When must a regulatory signal be actively attenuated?

• 9. How is function encoded in genes, and how is such information transmitted?

• 10. What is the cause and logic behind autocrine and paracrine regulation?

• 11. What role do positive feedback loops play?

• 12. Examples of receptor cells and effector cells.

• 13. The properties of extracellular regulatory processes: blood coagulation and complement system activation.

• 14. How are regulatory loops coupled to one another, and what is the result of such coupling?

• 15. Why are cells universally small and have low internal volume?

The mechanisms described in this chapter can be experimented with using web applications we provide for the reader’s convenience: The NF Organized Systems (NFS, negative feedback system) tool, available at https://nfs.sano.science, where the user may model interconnected systems and their interactions, depending on system parameters—such as receptor sensitivity, effector reaction speed, or the time it takes for signals to travel between the receptor and the effector.

[Wach J, Bubak M, Nowakowski P, Roterman I, Konieczny L, Chłopaś K. Negative feedback inhibition—Fundamental biological regulation in cells and organisms. In: Simulations in Medicine—Pre-Clinical and clinical applications. Ed: Irena Roterman-Konieczna, Walter de Gruyter 2015, pp. 31–56]

Biological entities (cells and organisms) are thermodynamically open systems, which means that they require regulation to maintain a steady state of nonequilibrium. In non-sentient systems regulation must be automatic and based on negative feedback loops. This principle is universally supported by scientific evidence. Given the fact that negative feedback is a precondition of a stable nonequilibrium state, all biological structures may be treated as components of negative feedback loops. Such loops can therefore be interpreted as structural units, representative of specific biological functions. Interrupting a feedback loop at any point results in its malfunction or complete loss of function. Figure 4.1 presents a negative feedback loop with receptor and effector units.

Fig. 4.1

Automatic control of processes occurring in biological systems. Symbolic depiction of a negative feedback loop with inflow of substrates and release of products

Although the principle of regulation remains unchanged, specific technical solutions (the structure of receptors, effectors, and transmission channels) may differ depending on the circumstances.

4.1 The Cell and the Organism

Cells and organisms differ with respect to their regulatory strategies. Clearly, the organism is hierarchically superior to the cell. Its task is to coordinate the function of specialized cells, protect them from harm, and create conditions which promote homeostasis. The relation between a cell and an organism is similar to the citizen-state model. Its hierarchical aspects are quite real and reflected in the structure and function of both entities.

Each living cell is an independent biological unit (with its own source of power), capable of maintaining its internal processes in a steady state through automatic regulation based on negative feedback loops.

Most intracellular signal pathways work by altering the concentrations of selected substances inside the cell. Signals are registered by forming reversible complexes consisting of a ligand (reaction product) and an allosteric receptor complex. When coupled to the ligand, the receptor inhibits the activity of its corresponding effector, which in turn shuts down the production of the controlled substance ensuring the steady state of the system.

Signals coming from outside the cell are usually treated as commands (covalent modifications), forcing the cell to adjust its internal processes and enter a new steady state. Although both types of signals (intracellular and extracellular ones) belong to negative feedback loops, they differ with respects to the mechanisms they employ.

Cells are automatic systems, devoid of decision centers. Thus, they are incapable of commanding themselves and can only respond to some external commands. Such commands can arrive in the form of hormones, produced by the organism to coordinate specialized cell functions in support of general homeostasis (in the organism). These signals act upon cell receptors and are usually amplified before they reach their final destination (the effector). Proper functioning of effector cells in organic regulatory pathways can be ensured in two ways:

• 1. In a non-dividing cell by:

  • A. Activation or inhibition of existing proteins (mostly enzymes) without altering their concentrations

  • B. Synthesis or degradation of proteins

• 2. Through cell proliferation and expression of their biological functions (Fig. 4.2)

Fig. 4.2

Three ways in which an effector cell belonging to an organic regulatory pathway may perform its task: (a) by regulating the activity of existing proteins (the signal does not pass through the nucleus), (b) through gene expression (altering the quantity of proteins—the signal passes through the nucleus), and (c) through cell proliferation (both a and b)

Although many regulatory phenomena have not yet been sufficiently studied, current scientific knowledge enables us to formulate some generalizations.

4.2 The Principle and Mechanism of Automatic Intracellular Regulation

Basic intracellular signals are expressed through changes in concentrations of reaction substrates and products. This basic form of signaling remains effective so long as the signal does not undergo dilution. By reacting to its own product, a synthesis process may upregulate or downregulate itself, maintaining the genetically programmed concentration of the substance it synthesizes.

The role of negative feedback loop is to stabilize processes whose products are recognized by their own detection subsystems, downregulating the activity of effectors. Automatic control of all internal processes makes the cell an autonomous entity.

4.2.1 Cellular Receptors

Each concentration-mediated signal must first be registered by a detector. Once activated, the detector issues another signal, triggering a process which counteracts the observed change. Intracellular detectors are typically based on allosteric proteins.

Allosteric proteins exhibit a special property: they have two stable structural conformations and can shift from one form to the other as a result of changes in ligand concentrations. Examples of such proteins include regulatory enzymes which play a key role in regulating intracellular metabolic pathways. They enable specific binding of reaction products (acting as receptors), but they also exhibit effector-like properties. Most intracellular allosteric enzymes are linked to regulatory functions. Both types of activity (receptor and effector) are interlinked via allosteric effects.

Some regulatory tasks can only be fulfilled by protein complexes due to the fact that the energy cost associated with reconfiguration of subunits is relatively low and can be covered by forming a reversible bond with the ligand. On the other hand, the protein-ligand interaction must result in significant structural rearrangement of the complex, precipitating a significant change in its activity in spite of the relatively low energy associated with such interactions. The allosteric properties of regulatory proteins enable weakly interacting ligands to effectively control biological processes. Their function may be compared to that of converters in electrical circuits, where relatively low currents regulate the action of powerful effector devices.

Allosteric effects are not equivalent to regulatory systems: they merely enable proteins to adapt to changing conditions by undergoing structural rearrangement, resulting in increased or decreased activity; they do not, however, stabilize reactions. This is why allosteric modifications (e.g., in the structure of hemoglobin, which compensates for changes in the availability of oxygen) should be counted among adaptation mechanisms. Allosteric proteins enhance or support regulatory loops but do not replace them. (An exception should be made for certain autonomous proteins which act as receptors as well as effectors, implementing all elements of a regulatory loop—for instance, hexokinase in muscle (see Fig. 4.3). The product of hexokinase—glucose-6-phosphate—is also its inhibitor, responsible for stabilizing the synthesis process.)

Fig. 4.3

Symbolic depiction of an allosteric enzyme which implements all elements of a negative feedback loop (hexokinase). A single protein molecule can act as a receptor (recognizing the concentration of glucose-6-phosphate) and an effector (synthesizing additional glucose-6-phosphate molecules). 1, ATP; 2, glucose; 3, glucose-6-phosphate

Subunits of regulatory enzymes which double as intracellular detectors may be either identical or dissimilar. Subunits which react with the product of a given reaction and perform adjustments by way of allosteric effects are called regulatory subunits, while those directly involved in biological functions are known as functional subunits (or catalytic subunits in the case of enzymes; see Fig. 4.4). If the subunits of an allosteric protein are identical to one another, they may perform receptor and catalytic functions at the same time using different active sites for each function (cumulative feedback inhibition). A classic example is bacterial glutamine synthetase. This enzyme consists of identical subunits (12) which are capable of reacting with various ligands, adjusting the productivity of the entire complex in general. In general the structure of allosteric proteins must enable changes in activity caused by reversible interaction with their own products or with the products of other coordinating processes.

Fig. 4.4

The action of an intracellular receptor. (a) Active regulatory enzyme. (b) Regulatory enzyme suppressed by the product. (a1 and b1) Enzyme subunits, shown separately as individual parts of a negative feedback loop. Gray structures, receptor regulatory subunits. White structures, catalytic subunits and enzymes associated with effector activity. The zigzag pattern symbolizes allosteric properties of the protein

The concentration of a product (or substrate) which triggers structural realignment in the allosteric protein (such as a regulatory enzyme) depends on the genetically determined affinity of the active site to its ligand. Low affinity results in high target concentration of the controlled substance, while high affinity translates into lower concentration (Fig. 4.5). In other words, high concentration of the product is necessary to trigger a low-affinity receptor (and vice versa).

Fig. 4.5

Negative feedback loop receptors with varying degrees of affinity to their product: high (a), moderate (b), and low (c) concentrations of the product resulting from variations in receptor affinity

Most intracellular regulatory mechanisms rely on noncovalent interactions. Covalent bonding is usually associated with extracellular signals, generated by the organism and capable of overriding the cell’s own regulatory mechanisms by modifying the sensitivity of receptors (Fig. 4.6). Noncovalent interactions may be compared to requests, while covalent signals are treated as commands.

Fig. 4.6

Schematic view of the changes in receptor affinity resulting from covalent modification of its structure (phosphorylation)

Signals which do not originate in the receptor’s own feedback loop but modify its affinity are known as steering signals (Fig. 4.7). A controlled regulatory system resembles a servomechanism (i.e., an autonomous, self-regulating mechanical device whose action is subject to external commands). Steering signals play an important role in coordinating biological processes.

Fig. 4.7

Schematic view of a negative feedback loop coupled to a control unit (model of servomechanism)

Receptor affinity may change as a result of external commands.

According to this definition, intracellular coordinating signals may be described as steering signals; however their interaction with the receptor is noncovalent, unlike the action of signals coming from the organism (the issue of coordination will be discussed in a separate chapter).

Noncovalent interactions—dependent on substance concentrations—impose spatial restrictions on regulatory mechanisms. Any increase in cell volume requires synthesis of additional products in order to maintain stable concentrations. The volume of a spherical cell is given as V = 4/3 π * r³, where r indicates cell radius. Clearly, even a slight increase in r translates into a significant increase in cell volume, diluting any products dispersed in the cytoplasm. This implies that cells cannot expand without incurring great energy costs. It should also be noted that cell expansion reduces the efficiency of intracellular regulatory mechanisms because signals and substrates need to be transported over longer distances. Thus, cells are universally small, regardless of whether they make up a mouse or an elephant.

4.2.2 Cellular Effectors

An effector is an element of a regulatory loop which counteracts changes in the regulated quantity.

Cellular effectors usually assume the form of degradation processes or feedback-controlled synthesis mechanisms. In both cases the concentration of the regulated product is subject to automatic stabilization and control. From the point of view of the entire organism, each cell can be treated as a separate effector.

Synthesis and degradation of biological compounds often involve numerous enzymes acting in sequence. The product of one enzyme is a substrate for another enzyme. With the exception of the initial enzyme, each step of this cascade is controlled by the availability of its substrate and does not require separate allosteric regulators (Fig. 4.8).

Fig. 4.8

Regulation of CTP (cytidine triphosphate) synthesis in a bacterial cell

The effector consists of a chain of enzymes, each of which depends on the activity of the initial regulatory enzyme (aspartate transcarbamoylase—ATCase) as well as on the activity of its immediate predecessor which supplies it with substrates.

The function of all enzymes in the effector chain is indirectly dependent on the initial enzyme, allosterically linked to a receptor subsystem. This coupling between the receptor and the first link in the effector chain is a universal phenomenon. It can therefore be said that the initial enzyme in the effector chain is, in fact, a regulatory enzyme. (Note that by “initial enzyme” we mean the enzyme whose product unambiguously triggers a specific chain of reactions.)

The product of the effector chain (or its functional derivatives) forms reversible complexes with the regulatory enzyme, controlling the production process, and through it—the function of the effector itself. By binding its assigned product, the regulatory enzyme acts as an intracellular receptor in addition to catalyzing the reaction.

Most cell functions depend on enzymatic activity. Even nonenzymatic processes (e.g., the action of motor proteins) are indirectly mediated by enzymes. It seems that a set of enzymes associated with a specific process which involves a negative feedback loop is the most typical form of an intracellular regulatory effector. Such effectors can be controlled through activation or inhibition of their associated enzymes.

A typical eukaryotic cell is, however, largely incapable of affecting enzymes other than by synthesizing their activators or inhibitors. Due to the fact that organisms actively strive to maintain internal homeostasis, enzymatic control cannot be enforced through major changes in temperature, pH, or substance concentrations. Instead, control rests upon the interaction between allosteric enzymes and their receptors. The dynamics of metabolic pathways depend on the concentrations of their own products and substrates (regulation) as well as on the products of other reactions for coordination (steering).

Certain processes involve a somewhat different enzymatic effector control mechanism which exploits changes in the concentration of active enzymes through regulated synthesis of proteins (gene expression). A negative feedback loop which alters the concentrations of proteins (or their products) in order to control effectors was first described by F. Jacob and J. Monod, who studied the so-called lactose operon in E. coli bacteria (Fig. 4.9). This operon includes a receptor called a repressor (or, more specifically, its detection subunit). The repressor binds its assigned product (or substrate) and undergoes allosteric realignment which causes it to gain (or lose) the ability to attach to the operator subunit, thereby activating (or inhibiting) the function of polymerase. In this way the effector may be inactivated once the concentration of the product exceeds a genetically determined level, thus preventing excessive accumulation of products. Similar modulation of transcription is also observed in eukaryotic organisms, although in this case it must occur simultaneously in many areas of the genome, as the encoded information concerning the given activity is often partitioned into different chromosomes. Instead of repressors, eukaryotes employ so-called transcription factors—having special structural matrices (zinc fingers or leucine zippers) capable of attaching to DNA strands in response to external signals.

Fig. 4.9

The bacterial operon—a negative (self-regulated) feedback loop with transcription and translation as its basic effector mechanisms

Receptor activity is exhibited by repressor subunits which react with the product (called an inductor) and allosterically modify the repressor’s ability to bind to DNA.

Transcription activation processes have been extensively studied; however most of these studies involve extracellular signals, i.e., signals generated by the organism. Transduction of such signals is ensured by membrane receptors and other specific transduction factors (such as G proteins). It is not clear, however, how the cell regulates transcription for its own purposes. The simplest model seems to be an operon-like construct where the protein product (e.g., enzyme) directly interacts with the transcription factor, upregulating or downregulating transcription as required. Nevertheless, our knowledge of this mechanism is not yet sufficient to attempt generalizations.

Another related model involves partial or complete appropriation of the own intracellular machinery for interpreting hormonal signals sent by the organism. This is realized by auto- or paracrine signaling (see Figs. 4.14, 4.15, 4.16, and 4.18).

4.3 Regulatory Coupling Between Cells and Organisms: Hierarchical Properties of Regulation

Automatic regulation enables cells to act as autonomous units, which means that—in given suitable environmental conditions—cells may survive on their own. In an organism, however, the autonomy of individual cells is severely restricted. The relation between the cell and the organism is hierarchical, and although the organism only controls specific areas of the cell’s activity, its demands cannot be met without the aid of basic intracellular processes.

A question arises: how can an involuntary automatic system (i.e., the cell) integrate with the organism’s own regulatory mechanisms? This issue can be better explained by comparing the cell to a simple automaton, namely, a refrigerator. The refrigerator includes an automatically controlled thermostat, based on a negative feedback loop with a temperature sensor coupled to a heat pump. Like most automatons, it is an autonomous system, capable of stabilizing its own internal temperature. However, most refrigerators also permit external control by an operator who may change the desired temperature. Operator intervention occurs by way of interacting with a separate panel (receptor) which registers and interprets steering signals.

Assuming that the stabilization curve for negative feedback loops is sinusoid-shaped, the effect of control is similar to that depicted in Fig. 4.10. A good biological example is fever, where bacterial toxins act upon organic temperature receptors which in turn modulate body temperature. Once the bacteria are cleared from the organism, the temperature stabilization loop reverts to its original parameters. Such changes in receptor sensitivity are perceived as a cold or heat sensation which persists until the desired temperature is reached.

Fig. 4.10

Changes in stabilization thresholds caused by steering signals

While refrigerator settings can be modified at will, signals issued by the organism are themselves products of other hierarchically superior regulatory loops which control the functions of the organism as a whole. This mechanism is depicted in Fig. 4.11. Hormones which act upon cells are, by their nature, steering signals: they enforce the superiority of the organism in relation to individual cells. The stabilization loop of a homeostatic parameter becomes a source of control if its signals are capable of affecting cellular receptors by altering their structure or introducing other permanent changes (such as the formation of complexes). This effect can be attained, e.g., by covalent modification of receptor units.

Fig. 4.11

Changes in cellular receptor sensitivity (in this case—downregulation, resulting in increased tolerance to the product) caused by a hormonal steering signal which originates outside of the cell’s own regulatory loops

This schematic relation is an expression of the cell-organism hierarchy.

A well-studied example of the presented mechanism involves regulation of blood glucose levels through degradation and synthesis of glycogen in hepatic cells. In this case an intracellular regulatory loop maintains the desired low concentration of glucose inside the cell (as indicated by glucose-6-phosphate). Glucose can be obtained from glycogen in the course of phosphorolysis, which is dependent on the concentration of ATP. Signals generated by a hierarchically superior control loop may force the cell to intensify its metabolism by altering the sensitivity of an allosteric enzyme—glycogen phosphorylase. Covalent (hormonally induced phosphorylation) modifications to this enzyme increase its tolerance to the product it controls (see Fig. 4.12).

Fig. 4.12

The change of glycogen phosphorylase activity through hormonally induced phosphorylation. Changes in sensitivity of the receptor result in adjustment of glucose-6-phosphate concentrations, depicted on the vertical axis. Gray structures represent receptor units

Hormonal modification significantly reduces the affinity of the receptor to glucose-6-phosphate. As a result, the concentration of glucose-6-phosphate (and, consequently, of glucose) increases. Excess glucose is expelled into the bloodstream where it can compensate for the deficiency which triggered the initial hormonal steering signal.

In summary, regulatory loops of the organism rely on the effector activity of individual cells through (1) modifying the activity of specific intracellular proteins, (2) degradation or synthesis of proteins connected with the given activity, and (3) cell proliferation or programmed cell death. Hormone-induced activity, although specific, affects also the entire biological machinery of the cell.

4.4 Regulatory Mechanisms on the Organism Level

The organism is a self-contained unit represented by automatic regulatory loops which ensure homeostasis. Its program is expressed in the structure of its receptors. Effector functions are conducted by cells which are usually grouped and organized into tissues and organs. Signal transmission occurs by way of body fluids, hormones, or nerve connections. Cells can be treated as automatic and potentially autonomous elements of regulatory loops; however their specific action is dependent on the commands issued by the organism. This coercive property of organic signals is an integral requirement of coordination, allowing the organism to maintain internal homeostasis.

Coercive action can be achieved through (1) significant amplification of signals issued by the organism to its effector cells, (2) covalent nature of modifications triggered by organic signals, and (3) a possible slow degradation of organic signals which have reached the cell. The effects of these mechanisms can be compared to an army drill, where the instructor enforces obedience by persistently shouting orders.

Activities of the organism are themselves regulated by their own negative feedback loops. Such regulation differs however from the mechanisms observed in individual cells due to its place in the overall hierarchy and differences in signal properties, including in particular:

• 1. Significantly longer travel distances (compared to intracellular signals)

• 2. The need to maintain hierarchical superiority of the organism

• 3. The relative autonomy of effector cells

In order to remain effective, the signal coming from the organism must be amplified and encoded; moreover its activity should be independent of its concentration (through specific covalent bonding).

It is also necessary to provide signal deactivation mechanisms which can shield effectors from undue stress caused by the outliving hierarchical signal (note that the effectors in organic regulatory pathways are living cells which require protection).

Most organic signals travel with body fluids; however if a signal has to reach its destination very rapidly (for instance, in muscle control), it is sent via the nervous system and becomes only humoral at entering the cell.

As mentioned above, organic signals act upon cellular regulatory loops which control cell development and/or homeostasis. Responding to such signals and fulfilling the requested tasks require the cell to adjust its internal metabolism.

4.4.1 Signal Encoding

The relatively long distance traveled by organic signals (compared to intracellular ones) calls for amplification. As a consequence, any errors or random distortions in the original signal may be drastically exacerbated.

A solution to this problem comes in the form of encoding, which provides the signal with sufficient specificity while enabling it to be selectively amplified. This situation can be compared to talking over a shortwave radio. When engaged in a normal conversation, we are usually facing our interlocutor who can hear us clearly, despite any ambient noise. In order to communicate over longer distances, we need to use a radio transceiver which encodes our voice as an electromagnetic wave (unlike acoustic waves, electromagnetic signals are unaffected by ambient noise). Once received and amplified by the receiver, the signal may be heard by the other party. Note that a loudspeaker can also assist in acoustic communication, but due to the lack of signal encoding, it cannot compete with radios in terms of communication distance.

The same reasoning applies to organism-originated signals, which is why information regarding blood glucose levels is not conveyed directly by glucose but instead by adrenalin, glucagon, or insulin.

Information encoding is handled by receptors and hormone-producing cells. Target cells are capable of decoding such signals, thus completing the regulatory loop (Fig. 4.13).

Fig. 4.13

Encoding and decoding of organic signals in a negative feedback loop (regulation of blood glucose levels)

The receptor system is associated with the endocrine gland cell.

Hormonal signals may be effectively amplified because the hormone itself does not directly participate in the reaction it controls—rather, it serves as an information carrier. If blood glucose concentration was to manifest itself purely through changes in glucose levels (without hormonal action), local distortions and random effects would—following intracellular amplification—interfere with correct interpretation of the input signal. Thus, strong amplification invariably requires encoding in order to render the signal sufficiently specific and unambiguous.

The above mechanism is ubiquitous in nature. An interesting example is the E. coli lactose operon, exploiting as an inducer allolactose which is attuned as a tiny component to lactose instead of the somewhat more expected lactose itself (the proper substrate). Registering an increase in the concentration of allolactose serves as direct evidence that lactose levels have also increased. As a consequence, the operon activates gene expression for additional enzymes, adjusting the cell’s energy management mechanisms.

Allolactose has the properties of an encoded signal. If the receptor were to react directly to lactose, it would have to cope with the relative abundance of this substance by lowering its own sensitivity—this, however, would also decrease its specificity and increase the probability of errors.

4.4.2 Signal Amplification

As mentioned above, one of the key differences between intracellular and organism-originated signals is the distance each has to travel. Long-distance communication introduces the need for signal amplification.

An important subgroup of regulatory components involved in organism-originated homeostasis processes is represented by amplifiers. Unlike organisms, cells usually do not require amplification in their internal regulatory loops—even the somewhat rare instances of intracellular amplification only increase signal levels by a small amount.

Without the aid of an amplifier, messengers coming from the organism level would need to be highly concentrated at their source, which would result in decreased efficiency as all such molecules need to be synthesized first (and then degraded once the signal has served its purpose). The need for significant amplification is also tied to the specific properties of organism-originated signals which must override the cell’s own regulatory mechanisms.

Two types of amplifiers are observed in biological systems:

• 1. Cascade amplifier

• 2. Positive feedback loop

4.4.3 Cascade Amplifier

A cascade amplifier is usually a collection of enzymes which perform their action in strict sequence. This mechanism resembles multistage (sequential) synthesis or degradation processes; however instead of exchanging reaction products, amplifier enzymes communicate by sharing activators or by directly activating one another. Cascade amplifiers are usually contained within cells. They often consist of kinases. A classic example is the adenylate cyclase cascade in the glucagon synthesis pathway (response to decreased blood glucose levels), whose individual stages are invoked through phosphorylation (Fig. 4.14). Activation of amplifier stages may also occur by way of protease or esterase interaction, release of calcium ions, etc. (Fig. 4.15). Figure 4.16 presents the amplification of growth factors. Amplification is also involved in gene expression as each stage amplifies information via repeated transcription and interpretation of genetic code as well as through prolonged reuse of the resulting proteins to synthesize additional products or perform some other activity (Fig. 4.17).

Fig. 4.14

Amplification mechanisms associated with intracellular hormonal action: adenylate cyclase cascade. Gray triangles represent staged amplification

Fig. 4.15

Amplification mechanisms associated with intracellular hormonal action: phospholipase C cascade. (a) Conditions prior to hormonal activation of the cell. (b) The cell in its activated state. Gray triangles represent amplification. DAG, 1,2-diacylglycerol; PIP₂, phosphatidyl-inositol-4,5-biphosphate; IP₃, inositol-1,4,5-triphosphate; PKC, protein C kinases; G, proteins; PLC, phospholipase C

Fig. 4.16

Amplification mechanisms associated with intracellular hormonal action: RAS protein cascade activated by the growth factor

Fig. 4.17

Amplification in gene expression

The effector cell regulates the amplifier by synthesizing its substrates (such as ATP). Amplification effects occurring at each stage of the cascade contribute to its final result. In the case of adenyl cyclase, the amplified hormone allows for synthesis of approximately 10⁴ cyclic AMP molecules before it is inactivated. While the kinase amplification factor is estimated to be on the order of 10³, the phosphorylase cascade results in 10¹⁰-fold amplification. It is a stunning value, though it should also be noted that the hormones involved in this cascade produce particularly powerful effects.

Due to their low volume, cells usually have no need for signal amplification. Even so, amplification may play a certain role in special cases, such as autocrine signaling, where a signal produced by the cell returns to it and is recognized by a receptor. This situation corresponds to a self-issued command. Autocrine amplification becomes necessary in transcription-inducing processes as it enables the cell to “repurpose” mechanisms normally used to amplify external signals (Fig. 4.18).

Fig. 4.18

Autocrine signaling—repurposing the hormonal signal pathways for amplification of the cell’s own signals

4.4.4 Positive Feedback Loop

A positive feedback loop is somewhat analogous to a negative feedback loop; however in this case the input and output signals work in the same direction—the receptor upregulates the process instead of inhibiting it. Such upregulation persists until the available resources are exhausted.

Positive feedback loops can only work in the presence of a control mechanism which prevents them from spiraling out of control. They cannot be considered self-contained and only play a supportive role in regulation. The effects of an uncontrolled feedback loop can be easily observed by attaching a loudspeaker to a microphone and placing both of them close together. Any sound registered by the microphone is amplified and transmitted over the loudspeaker, further increasing the input volume and causing a runaway feedback reaction which manifests itself as the familiar screeching noise.

In biological systems positive feedback loops are sometimes encountered in extracellular regulatory processes where there is a need to activate slowly migrating components and greatly amplify their action in a short amount of time. Examples include blood coagulation and complement factor activation (Figs. 4.19 and 4.20).

Fig. 4.19

Amplifying an extracellular process through a positive feedback loop—blood coagulation cascade

Fig. 4.20

Amplifying an extracellular process through a positive feedback loop—complement factor activation cascade

Positive feedback loops may play a role in binary control systems which follow the “all or nothing” principle. Due to its auto-catalytic character, the positive feedback loop is used for construction of binary switching mechanisms and governing cell fate decisions.

Positive feedback loops are often coupled to negative loop-based control mechanisms. Such interplay of loops may impart the signal with desirable properties, for instance, by transforming a flat signal into a sharp spike required to overcome the activation threshold for the next stage in a signaling cascade. An example is the ejection of calcium ions from the endoplasmic reticulum in the phospholipase C cascade, itself subject to a negative feedback loop. Positive feedback is also observed in the activation of cyclins.

Feedback-based amplification of weak signals may also double as intracellular memory. It is believed that the high rate of activation and deactivation of signals in nerve cells relies on positive feedback mechanisms.

4.4.5 Signal Attenuation

Strong signal amplification carries an important drawback: it tends to “overshoot” its target activity level, causing wild fluctuations in the process it controls. While sinusoid fluctuations are a natural property of many stabilized processes, high amplitudes are usually considered undesirable even if average values remain in agreement with biological programming (Fig. 4.21). Significant deviations from the norm, though temporary, may have a negative impact on biological systems.

Fig. 4.21

Stabilization of a substance concentration or activity level as a function of a negative feedback loop: changes in amplitude and frequency

The danger associated with strong fluctuations is particularly evident in organism-originated regulatory loops. Nature has evolved several means of signal attenuation. The most typical mechanism superimposes two regulatory loops which affect the same parameter but act in opposite directions. An example is the stabilization of blood glucose levels by two contradictory hormones: glucagon and insulin. Similar strategies are exploited in body temperature control and many other biological processes.

Each cellular receptor acts upon a single type of effector: its input signal can only work in one specific direction, for instance, by activating the synthesis of some product or counteracting a decrease in its concentration. A single receptor cannot issue contradictory signals, simultaneously upregulating and downregulating a process (Fig. 4.22). This limitation usually does not hamper intracellular machinery due to the limited space in which reaction components are contained and the efficiency with which they can be processed. However, significant fluctuations may be observed in certain slow-acting processes such as gene expression where the persistence of mRNA may sometimes induce overexpression. Maintaining the programmed level of activity, free of undue fluctuations, requires proper degradation and removal of intermediate products.

Fig. 4.22

Fluctuations in a controlled quantity, given (a) unidirectional detection and control and (b) bidirectional control based on two contradictory negative feedback loops

The attenuation mechanism involved in the action of the bacterial operon has been well studied. It is able to recognize the concentration of the product prior to transcription necessary for its synthesis and prevent its excessive buildup as a result of recycling transcripts.

4.4.6 Signal Inactivation

The coercive properties of signals coming from the organism carry risks associated with the possibility of overloading cells. The regulatory loop of an autonomous cell must therefore include an “off switch,” controlled by the cell.

An autonomous cell may protect itself against excessive involvement in processes triggered by external signals (which usually incur significant energy expenses). Once acknowledged, hormones must be quickly inactivated.

It is natural to expect that the inactivation mechanism will be found along the signal pathway (before the position of amplifier). The action of such mechanisms is usually timer-based, meaning that they inactivate signals following a set amount of time. A classic example of an inactivator is found in protein G (see Figs. 4.14 and 4.15). This protein is activated by hormonal signals, but immediately upon activation it also triggers the corresponding inactivation process. Protein G activation occurs by swapping GDP for GTP and by subsequent reorganization of its subunits. Inactivation proceeds in the opposite direction through autocatalysis (the protein exhibits GTPase activity). The time it takes to complete the hydrolysis process automatically determines the duration of the signal. A similar property is observed in Ras proteins, where GTPase activity of the initiation complex eventually interrupts the signal (Fig. 4.23). We should also note the association between receptor phosphorylation and phosphatase activity in many other processes.

Fig. 4.23

Signal inactivation (RAS protein). (a) Conditions prior to activation and (b) hormone-activated complex (the clock symbolizes the “off timer” which depends on GTPase activity). Signal inactivation by protein G is depicted in Figs. 4.14 and 4.15. RAS, RAS proteins; Grb2 and Sos, proteins assisting RAS; Raf, MEK, and MAPK, amplifier kinases

Although all proteins which undergo phosphorylation eventually revert to their initial state via phosphatase activity, the phosphorylation/dephosphorylation effects are particularly pronounced at the entry point of the amplifying cascade which should therefore be considered the proper inactivation place. Signal inactivation may also occur as a result of receptor pinocytosis (Fig. 4.24). The ability to interrupt signals protects cells from exhaustion. Uncontrolled hormone-induced activity may have detrimental effects upon the organism as a whole. This is observed, e.g., in the case of the Vibrio cholerae toxin which causes prolonged activation of intestinal epithelial cells by locking protein G in its active state (resulting in severe diarrhea which can dehydrate the organism). Similar dysregulation is associated with the prolonged action of acetylcholine resulting from inhibition of acetylcholinesterase by phosphoorganic compounds.

Fig. 4.24

Surface receptor density controlled by degradation and synthesis. (a) Degradation of ligands and (b) degradation of ligands and receptors

4.4.7 Discrimination

Biological systems in which information transfer is affected by high entropy of the information source and ambiguity of the signal itself must include discriminatory mechanisms. These mechanisms usually work by eliminating weak signals (which are less specific and therefore introduce ambiguities). They create additional obstacles (thresholds) which the signals must overcome. A good example is the mechanism which eliminates the ability of weak, random antigens to activate lymphatic cells. It works by inhibiting blastic transformation of lymphocytes until a so-called receptor cap has accumulated on the surface of the cell (Fig. 4.25). Only under such conditions can the activation signal ultimately reach the cell nucleus (likely with the aid of phosphatase) and initiate gene transcription. Aggregation of immunoglobulin receptors on the membrane surface is a result of interaction with the antigen; however weak, reversible nonspecific interactions do not permit sufficient aggregation to take place. This phenomenon can be described as a form of discrimination against weak signals.

Fig. 4.25

Hypothetical discrimination mechanism preventing the randomly induced blastic transformation in B cells. Accumulation of receptors is required for signal transduction to take place. Gray circles represent antigens, while lines represent surface receptors

In addition to antigen recognition and effector activity of individual immunoglobulins, another activation threshold exists in the complement factor activation cascade, which requires a suitable aggregation of antibodies. Discrimination is effected by a special T lymphocyte receptor which consists of many independent subunits, each capable of forming weak bonds with the antigen and contributing to the overall binding strength (Fig. 4.26).

Fig. 4.26

Schematic structure of the T lymphocyte receptor consisting of many weakly binding molecules which together provide sufficient antigen binding strength. This structure provides discrimination against random, nonspecific signals. CD28, LFA-1, CD4, CD3, TCR, CD2, B7, ICAM-1, MHC II, and LFA-3—cell receptors and markers

Discrimination may also be linked to effector activity. One example is the restricted propagation of blood clots beyond the specific site of vessel damage. Blood coagulation automatically triggers fibrinolysis, which counteracts further clotting by degrading fibrin molecules (Fig. 4.27).

Fig. 4.27

Fibrinolysis as a discriminator against excessive clotting beyond the specific site of damage

4.4.8 Coordinating Signals on the Organism Level

Mindful of the hierarchical relation between the cell and the organism, we can assume that hormones act by coordinating the function of cells in order to ensure homeostasis. Hormonal signals supersede intracellular regulatory mechanisms and subordinate the needs of cells to those of the organism as a whole. This hierarchical structure is further reinforced by signal amplification and covalent modification of signal mediators within the cell.

According to the presented criteria, hormones follow a specific plan of action, roughly outlined in Fig. 4.28, which presents several transduction pathways. It also depicts some atypical means of signaling—for instance, nitric oxide, which acts as a hormone even though it is not associated with any specific membrane receptor. A signal may be treated as a hormone regardless of its source, as long as it originates outside the cell and affects intracellular machinery. Hormonal control may be effected over long distances (via the bloodstream) or short distances, when the signal comes from adjacent cells (e.g., growth factors or morphogens). Nitric oxide permeates the cellular membrane and activates the guanylyl cyclase cascade. The specificity of this unusual hormone is probably a result of the proximity of its source to the effector mechanism as well as its rapid rate of its degradation.

Fig. 4.28

Examples of various hormone transduction pathways

Another atypical means of signaling is observed in steroids, whose receptors are located inside the cell and—once activated—can perform the role of transcription modulators. The coercive nature of steroids is supported by their persistent action inside the cell (compared to hormones which only interact with surface receptors) as well as their high affinity to receptors (equilibrium constant in the 10⁹ range). It should also be noted that biological processes induced by steroids are usually slow-paced and therefore do not require strong amplification. Hormonal signaling is itself a relatively slow process—signals which need to reach their destination very rapidly (for instance, signals controlling muscle contractions) are usually transmitted via nerve connections.

As mentioned above, if the organism is to coordinate the action of various tissues, its signals must override the autonomous regulatory mechanisms of individual cells.

4.4.9 Extracellular Process Control

Most enzymes reside inside cells, acting as effectors in intracellular pathways. There are, however, processes which require cells to release enzymes into the extracellular space. These include food metabolism, blood coagulation, complement factor activation, and some tissue-related mechanisms. Under such circumstances the cell effectively relinquishes control of the given process. While enzymatic activity can be easily regulated inside the cell (for instance, by automatically controlling the concentration of its product), external processes admit no such regulation and can potentially prove dangerous (this applies to, e.g., proteolytic enzymes). Occasionally, enzymes may enter the outer cell space as a result of cell degradation or diffusion from the gastrointestinal tract.

Inadvertent (but manageable) enzyme “leaks” are dealt with by specialized natural inhibitors called serpins which exist in the bloodstream specifically for that purpose. Proper regulation only applies to enzymes secreted by cells in programmed biological processes. As a general rule, such enzymes are released in their inactive state. They can be activated by a specific signal once the organism has taken steps to protect itself from uncontrolled proliferation of active forms.

Activation of gastrointestinal enzymes is therefore coupled to processes which protect the intestinal wall from being attacked. In blood coagulation, enzymatic activity is tightly linked to the developing clot, while in the complement factor activation cascade, degradation processes are limited to antigen-antibody complexes present on the surface of the antigen cell. The principle of production and secretion of inactive enzymes is evident in extracellular mechanisms where controlling such enzymes may be difficult; however it can also be observed in certain intracellular pathways where some enzymes are activated ab initio to fulfill specific tasks. This situation occurs, e.g., in kinases (activated through phosphorylation) or in proteolytic enzymes (especially caspases) tightly connected with apoptosis.

4.4.10 Cell Population Control

Basic cell population control mechanisms include proliferation by division (mitosis) and programmed cell death (apoptosis). Both processes must be controlled by extracellular signals because they produce important effects for the organism as a whole.

Cell division is governed by the so-called growth factors. Once triggered, the division process may proceed autonomously, progressing through successive checkpoints of the mitosis program (Fig. 4.29).

Fig. 4.29

Schematic depiction of cell division (mitosis). Colored areas indicate the activation pathway. Gray belts show the activity of cyclins (A to E)

If the process consists of several stages, control must be sequential, i.e., each stage starts with a checkpoint which tests whether the previous stage has completed successfully.

Cell division requires the entire genome to be copied, which involves not just DNA replication but also synthesis of additional DNA-binding proteins. This so-called S phase comes at a tremendous cost to the cell’s resources. It is followed by the G₂ phase, which prepares the cell for actual division (itself occurring in the M phase). All processes associated with division are subject to strict control. Each stage must fully complete before the next stage is triggered.

Phosphorylation and dephosphorylation (mediated by kinases and phosphatases) appear to effect control over the mitosis process. However, each phase of mitosis is ushered in by special proteins called cyclins. These are synthesized in parallel with other division-related structures and broken down shortly thereafter.

The cell may maintain a steady state (G₀ phase) for a long time. Entering the G₁ phase signals readiness for division; however the transition from G₀ to G₁ is reversible. Cells protect themselves against accidental division by raising the activation threshold. This mechanism is mediated by a protein known as p53, which can also inhibit division in later phases, should irregularities occur.

Cell division is counterbalanced by programmed cell death. The most typical example of this process is apoptosis (Fig. 4.30). Apoptosis occurs as a result of proapoptotic signals (such as the tumor necrosis factor-alpha (TNF-α)) which pierce the mitochondrial membrane and release the contents of mitochondria into the cytoplasm. Once released, mitochondrial cytochrome C activates specific apoptotic enzymes called caspases, which proceed to degrade cell organelles and effectively kill the cell.

Fig. 4.30

Schematic depiction of apoptosis. Activation pathways marked in color

Each cell is prepared to undergo controlled death if required by the organism; however apoptosis is subject to tight control. Cells protect themselves against accidental triggering of the process via IAP proteins. Only strong proapoptotic signals may overcome this threshold and initiate cellular suicide (Fig. 4.30).

Supervision of both processes—cell division and death—enables the organism to maintain a controlled population of cells (Fig. 4.31).

Fig. 4.31

Simplified view of cell population management via controlled proliferation and destruction of cells. (a) Reacting to population deficiency and (b) eliminating surplus cells

4.5 Development Control

Biological regulation relies on the assumption that processes can be automatically controlled via negative feedback loops. Such regulation appears useful both for the organism and for individual, mature cells which strive to maintain a steady state. However, it cannot be readily applied to development control where the goal is to increase the population of cells and cause irreversible changes in their structure. Developmental changes are controlled at specific checkpoints during the process and following its conclusion (see Chap. 3, Fig. 3.13). Signals which guide development are themselves an expression of an evolving genetic blueprint. They control cell differentiation as well as the shaping of organs and the entire organism.

Development control algorithms are implemented through sequential induction of cell proliferation and differentiation, where cells and signals are subject to hierarchical management. Information may be conveyed through direct interactions between adjacent cells or by hormonal signals (typically acting at short ranges). A simple model which may serve to explain this process is the formation of a photoreceptor in the insect eye ommatidium. This element normally consists of eight separate cells, controlled by a specialized cell called R8. The R8 cell is also sometimes called BOSS—an acronym of the term Bride Of SevenlesS, referring to a specific mutation which interferes with the differentiation of the seventh cell and reinforces the supervisory role of the eighth cell. Figure 4.32 presents the differentiation algorithm for the development of the ommatidium photoreceptor, showing the differences in processes occurring on each side of the R8 cell. This differentiation mechanism results in asymmetric arrangement of the photoreceptor element, which in turn enables the insect to determine which direction the light is coming from. The staged, programmed maturation of photoreceptor cells is an example of a generalized process from which specialized organs and structures may emerge.

Fig. 4.32

Development of organized structures: formation of a photoreceptor in the insect ommatidium—simplified view (active cells shown in color) and algorithmic depiction. Symbols: circle, beginning and end of the process; rectangle, command to be executed; rhombus, conditional instruction with two possible outcomes (TRUE and FALSE); parallelogram, input/output interface

4.6 Basic Principles of Regulation in Biology

In general, it can be said that any activity which ensures the stability of biological processes may be called regulation and that regulation is dependent on negative feedback loops. Regulatory mechanisms work to maintain cellular and organic homeostasis, utilizing receptor systems which determine, e.g., the concentrations of various substances in blood or in cell cytoplasm.

On the other hand, signals which alter the default stabilization levels are called steering signals. They originate beyond the loop which they control and may be divided into intracellular signals (allosteric effectors) and hormonal signals which guide the specific activity of the cell. Steering signals may also supervise the development process by triggering the formation of new structures and expression of their functions.

From the point of view of kinetics, biological control mechanisms may be divided into three groups:

• 1. Response control, characteristic of metabolic processes where the intensity of a given process closely follows the concentration of a regulatory hormone. Examples include the reaction of hepatic cells to insulin and glucagon. Such processes can be roughly compared to the action of servomechanisms in a power steering system.

• 2. Extremal control, where the signal releases or inhibits a specific process, e.g., secretion of stomach acid, cell division, apoptosis, sexual maturation, etc. An appropriate mechanical counterpart is the activation/deactivation of a light switch by a photodetector.

• 3. Sequential control. This type of control is observed in development and growth. Steering signals are issued sequentially, according to a specific algorithm. Each stage of development is triggered once the previous stage has concluded and a checkpoint has been reached. In the developing embryo, this involves activation of successive gene packets, while in cell development, it applies to the action of cyclins. Sequential control can also be observed in many macroscopic devices, for instance, in washing machines and assembly-line production environments. In biological systems it is usually effected by activating specific genes.

4.7 Regulation Levels

Assuming that biological systems are, in fact, automatons and that their properties can be explained by their automatic nature, we can generalize and categorize regulatory phenomena. One example of such categorization involves treating negative feedback loops as a basic mechanism of automatic regulation and—at the same time—a basic building block of biological systems. Our ever-deepening knowledge of regulatory mechanisms seems to support this theory and provides much evidence of the universality of negative feedback loops.

The above assumptions force us to consider the function of more advanced biological mechanisms such as the nervous system, which enables fine-tuned regulation that would otherwise be impossible in a simple feedback loop. Two questions arise in this scope: are such advanced mechanisms merely modified feedback loops? How should the term “advanced regulation” be defined?

In general, an advanced regulatory system is a system where the effector has significant freedom in choosing the strategy which it will apply to a given task. In the above-described systems, effector units (particularly intracellular ones) have no such freedom—they follow a genetically determined procedure. Advanced feedback loops may, however, emerge as a result of linking many simpler systems. There are several ways in which regulatory systems may be coupled to one another. Cooperation occurs when the product of one system is used by another system. Bringing together two contradictory systems reduces the amplitude of fluctuations and promotes signal attenuation. Finally, as mostly promising for the progress, systems can be linked via coordination pathways, modifying the sensitivity of their receptors.

Sensitivity-based coupling enables one system to drive the action of another and introduces a specific hierarchy of needs, similar to the hierarchy which exists between the cell and the organism. However, coordination does not directly translate into increased effector freedom as long as at least one receptor is not subject to control. New properties may only emerge in systems which are fully coupled to each other, where neither system maintains complete dominance (see Fig. 4.33 a–c). Such conditions occur naturally in the nervous system, owing to its enormous diversity of feedback loops, all interlinked and capable of affecting one another’s actions. The resulting “regulatory superloop” exhibits great variability, although it still relies on a centralized memory store. The malleability and adaptability of this complex system are far greater than that in any of its individual components. The “superloop” works by implementing a single, shared task, but in doing so, it may choose from a great number of strategies, all of which lead to the same goal.

Fig. 4.33

Coupling of regulatory loops via mutual control—formation of a “superloop”—hypothetical mechanism for the emergence of higher-level regulatory systems

It should be noted that such “superloops” can be further integrated with one another, providing even greater effector independence.

The presented “effector freedom” criterion enabled the French philosopher and cybernetics expert Pierre de Latil to propose the following tiered structure of regulation:

• 1. Stabilization tier, associated with intracellular and organic regulation not mediated by the nervous system. Systems belonging to this tier work by following simple, rigid programming in order to provide answers to questions such as how? and what? For instance, if the concentration of some substance decreases, the cell must try to restore it in a predetermined way. As long as regulation is based on the action of individual circuits (regardless of their complexity), the overall system belongs to the stabilization tier.

• 2. Determinism tier, where systems achieve certain freedom in choosing how to implement the given tasks. This type of action is based on instincts (single answer to the what? question) but may involve numerous answers to the how? question. For instance, the need to acquire food is instinct-driven, but does not involve a single, predetermined strategy—the regulatory system exercises its freedom by choosing one of the available food acquisition strategies.

• 3. Goal tier, which results from development of the cerebral cortex along with massive improvements in both memory and reasoning mechanisms. Conscious, abstract thinking introduces a new quality called the goal of action, where systems may freely determine not only how to proceed but also what to do. This level of regulation is characteristic of Homo sapiens.

4.8 Hypothesis

4.8.1 Proteome Construction Hypothesis

Genetics and genomics (i.e., in silico genetics) have enabled scientists to study specific genes with the help of ever more accurate stochastic mechanisms. It appears that the theoretically estimated number of proteins is greater than the number of proteins actually known to biochemists. Genomics can be treated as a tool which allows us to establish a complete set of proteins, including those which have not yet been experimentally observed.

Simply knowing the sequences, structures, or even functions of individual proteins does not provide sufficient insight into the biological machinery of living organisms. The complexity of individual cells and entire organisms calls for functional classification of proteins. This task can be accomplished with a proteome—a theoretical construct where individual elements (proteins) are grouped in a way which acknowledges their mutual interactions and interdependencies, characterizing the information pathways in a complex organism.

Most ongoing proteome construction projects focus on individual proteins as the basic building blocks (Fig. 4.34). Due to the relatively large number of proteins (between 25,000 and 40,000 in the human organism), presenting them all on a single graph with vertex lengths corresponding to the relative duration of interactions would be unfeasible. This is why proteomes are often subdivided into functional subgroups such as the metabolome (proteins involved in metabolic processes), interactome (complex-forming proteins), kinomes (proteins which belong to the kinase family), etc.

Fig. 4.34

Traditional proteome, where each circle represents a single protein. The length of each vertex should, in theory, correspond to the duration of interaction between two proteins

Figure 4.34 presents a sample proteome based on the assumptions and suggestions outlined in this handbook. Our model should be considered strictly hypothetical since it lacks numerical verification.

The proposed construction of the proteome bases on the following assumptions:

• 1. The basic unit of the proteome is one negative feedback loop (rather than a single protein) as the main regulation mechanism ensuring steady state and homeostasis.

• 2. Relations between units can be mediated by:

  • A. Effectors

  • B. Receptors

The effector relation is inherently cooperative: each effector may be targeted by a signal sent by another feedback loop. The signal changes the efficiency of the effector and may force a reaction without that effector’s “consent.” This type of signal should be treated as a cooperation mechanism because it is issued in response to a local surplus of a certain effector substrate.

Receptor-mediated signals force changes in the receptor’s sensitivity. Any receptor affected in this manner will, in turn, adjust its own feedback loop, along with all processes which participate in a given cycle.

Figure 4.35 depicts a model proteome based on negative feedback loops. Solid lines indicate effector-mediated relations, while dashed lines correspond to receptor-mediated relations. Line length is irrelevant.

Fig. 4.35

Model proteome conforming to the description proposed in this chapter. Negative feedback loops are represented by lines (solid lines for effector-mediated relations and dashed lines for receptor-mediated relations)

For the sake of comparison, Fig. 4.34 presents a traditional proteome, where each unit corresponds to a single protein. According to its assumptions, the length of each connecting line should indicate the relative stability of a protein complex (however, this requirement is difficult to fulfill given a large number of proteins). The model of proteome building proposed in this chapter tries to avoid taking into account individual proteins. Assuming automatic control of all biological processes and steady state as the incoming program of their action, the proteome used as a tool in studies of the cell and organism strategy could be presented as the relation of independent automatic devices rather than individual proteins. The automatic character of devices controlling biological processes allows treating them as independent units involving the final, controlled product intermediates and the whole regulatory arrangement as well as non-protein components of the process.

We believe that the construction of such proteome could reveal in future studies the still hidden strategic relations in living cells and organisms (Figs. 4.36 and 4.37).

Fig. 4.36

Proteome model (see Fig. 4.35) extended with information regarding the molecular structure of each loop

Fig. 4.37

The multi-tier properties of the proteome. The bottom tier corresponds to feedback loops, while the top tier involves concentrations of specific substances in each compartment of a fully differentiated cell

Such a system, if properly simulated, would present a valuable tool, enabling scientists to further study the variations (both random and targeted) in biological processes. The effects of these variations could then be compared with existing medical knowledge—for example, the symptoms of known diseases. A suitable proteome model would be very helpful in ascertaining the causes and effects of complex pathological processes.

A complete, multi-tiered (including the tissue and organism tiers) in silico proteome might even be called an “in silico organism”—it would facilitate virtual experiments on humans which cannot be carried out in the real world for technical or ethical reasons. It would also provide valuable insight into systemic pathologies which are difficult to study when focusing on small-scale subunits of living organisms, such as individual cells.