Extremal principles and goal functions of biocoenotic systems

A review considers known in the ecology two alternative principles of maximizing or minimizing the diversity-entropy of biological systems, and shows the inadequacy of both extremal principles in application to natural biocoenotic assemblages. A necessary condition for the multispecific system's existence is not extremization any of their parameters, but optimization of the relations of their parameters (including those that uniquely determine the value of species diversity). Thus, the goal function, which tends to minimize any biocoenotic system in the course of succession and evolution, is a deviation from this optimal ratio.     

Biochemical predetermination of the NO synthase and nitrite reductase components of the nitric oxide cycle.

This review presents some aspects of a concept of cellular evolution bearing a relationship to nitrate--nitrite respiration, the endosymbiosis theory, and the origin of NO synthase and nitrite reductase activity in heme-containing proteins. Analysis of structural and functional unity of the NO synthase and nitrite reductase systems suggests that these systems did not arise without any relation to evolutionarily ancient energetic systems of cells. The use of symmetry principles reveals commonalities among many electron transport chains which in the language of physics is called "invariance". This work also comparatively analyzes the nitric oxide cycle and the known nitrogen cycle. The ideas about evolution of the NO synthase and nitrite reductase systems developed here are clearly compatible with the endosymbiotic theory and the hypothesis that nitrate--nitrite respiration was a precursor of oxygen-dependent respiration.     

Visualisation and stereological assessment of blood and lymphatic vessels

The physiological processes involved in tissue development and regeneration also include the parallel formation of blood and lymphatic vessel circulations which involves their growth, maturation and remodelling. Both vascular systems are also frequently involved in the development and progression of pathological conditions in tissues and organs. The blood vascular system circulates oxygenated blood and nutrients at appropriate physiological levels for tissue survival, and efficiently removes all waste products including carbon dioxide. This continuous network consists of the heart, aorta, arteries, arterioles, capillaries, post-capillary venules, venules, veins and vena cava. This system exists in an interstitial environment together with the lymphatic vascular system, including lymph nodes, which aids maintenance of body fluid balance and immune surveillance. To understand the process of vascular development, vascular network stability, remodelling and/or regression in any research model under any experimental conditions, it is necessary to clearly and unequivocally identify and quantify all elements of the vascular network. By utilising stereological methods in combination with cellular markers for different vascular cell components, it is possible to estimate parameters such as surface density and surface area of blood vessels, length density and length of blood vessels as well as absolute vascular volume. This review examines the current strategies used to visualise blood vessels and lymphatic vessels in two- and three-dimensions and the basic principles of vascular stereology used to quantify vascular network parameters.     

A three-dimensional solubility parameter approach to nonaqueous enzymology

Widespread commercial application of enzymes as catalysts for specialty or commodity chemical synthesis will require their use in nonaqueous systems. While a number of non-aqueous enzyme applications have been demonstrated, the lack of useful rules for predicting enzyme-solvent interactions has hindered the development of this technology. Both Hildebrand and solvent hydrophobicity (octanol-water partition coefficient) parameters have been used previously to correlate and predict enzyme activity in nonaqueous systems, with some success, but any single-parameter approach is inherently limited in its ability to reflect the spectrum of possible enzyme-solvent interactions. Therefore, this study evaluates the three-dimensional solubility parameter space, as proposed by Hansen, to correlate and predict enzyme activity in microaqueous, miscible, and biphasic nonaqueous systems. Preliminary results suggest that Hansen parameters may be useful for correlating nonaqueous enzyme activity, and that the dispersive and polar parameters may be disproportionately important in single-phase microaqueous systems. The Hansen hydrogen-bonding parameter appears to be the only parameter yet evaluated capable of correlating the water requirement for enzyme activity in microaqueous systems, suggesting that water affects protein structure through enthalpic rather than entropic processes in nonaqueous systems. Insufficient data are available for miscible and biphasic systems, but it is proposed that enzyme activity may correlate with the average solubility parameters of miscible systems and of the aqueous phase in biphasic systems.     

Optimal Control of Transitions between Nonequilibrium Steady States

Biological systems fundamentally exist out of equilibrium in order to preserve organized structures and processes. Many changing cellular conditions can be represented as transitions between nonequilibrium steady states, and organisms have an interest in optimizing such transitions. Using the Hatano-Sasa Y-value, we extend a recently developed geometrical framework for determining optimal protocols so that it can be applied to systems driven from nonequilibrium steady states. We calculate and numerically verify optimal protocols for a colloidal particle dragged through solution by a translating optical trap with two controllable parameters. We offer experimental predictions, specifically that optimal protocols are significantly less costly than naive ones. Optimal protocols similar to these may ultimately point to design principles for biological energy transduction systems and guide the design of artificial molecular machines.     

Evolutionary optimization of speed and accuracy of decoding on the ribosome

Speed and accuracy of protein synthesis are fundamental parameters for the fitness of living cells, the quality control of translation, and the evolution of ribosomes. The ribosome developed complex mechanisms that allow for a uniform recognition and selection of any cognate aminoacyl-tRNA (aa-tRNA) and discrimination against any near-cognate aa-tRNA, regardless of the nature or position of the mismatch. This review describes the principles of the selection-kinetic partitioning and induced fit-and discusses the relationship between speed and accuracy of decoding, with a focus on bacterial translation. The translational machinery apparently has evolved towards high speed of translation at the cost of fidelity.     

A Natural View of Microbial Biodiversity within Hot Spring Cyanobacterial Mat Communities

This review summarizes a decade of research in which we have used molecular methods, in conjunction with more traditional approaches, to study hot spring cyanobacterial mats as models for understanding principles of microbial community ecology. Molecular methods reveal that the composition of these communities is grossly oversimplified by microscopic and cultivation methods. For example, none of 31 unique 16S rRNA sequences detected in the Octopus Spring mat, Yellowstone National Park, matches that of any prokaryote previously cultivated from geothermal systems; 11 are contributed by genetically diverse cyanobacteria, even though a single cyanobacterial species was suspected based on morphologic and culture analysis. By studying the basis for the incongruity between culture and molecular samplings of community composition, we are beginning to cultivate isolates whose 16S rRNA sequences are readily detected. By placing the genetic diversity detected in context with the well-defined natural environmental gradients typical of hot spring mat systems, the relationship between gene and species diversity is clarified and ecological patterns of species occurrence emerge. By combining these ecological patterns with the evolutionary patterns inherently revealed by phylogenetic analysis of gene sequence data, we find that it may be possible to understand microbial biodiversity within these systems by using principles similar to those developed by evolutionary ecologists to understand biodiversity of larger species. We hope that such an approach guides microbial ecologists to a more realistic and predictive understanding of microbial species occurrence and responsiveness in both natural and disturbed habitats.     

Application of quality by design principles to the development and technology transfer of a major process improvement for the manufacture of a recombinant protein

This study describes the application of quality by design (QbD) principles to the development and implementation of a major manufacturing process improvement for a commercially distributed therapeutic protein produced in Chinese hamster ovary cell culture. The intent of this article is to focus on QbD concepts, and provide guidance and understanding on how the various components combine together to deliver a robust process in keeping with the principles of QbD. A fed-batch production culture and a virus inactivation step are described as representative examples of upstream and downstream unit operations that were characterized. A systematic approach incorporating QbD principles was applied to both unit operations, involving risk assessment of potential process failure points, small-scale model qualification, design and execution of experiments, definition of operating parameter ranges and process validation acceptance criteria followed by manufacturing-scale implementation and process validation. Statistical experimental designs were applied to the execution of process characterization studies evaluating the impact of operating parameters on product quality attributes and process performance parameters. Data from process characterization experiments were used to define the proven acceptable range and classification of operating parameters for each unit operation. Analysis of variance and Monte Carlo simulation methods were used to assess the appropriateness of process design spaces. Successful implementation and validation of the process in the manufacturing facility and the subsequent manufacture of hundreds of batches of this therapeutic protein verifies the approaches taken as a suitable model for the development, scale-up and operation of any biopharmaceutical manufacturing process.     

Robustness analysis of cellular systems using the genetic tug-of-war method

Robustness is one of the principles of design inherent to biological systems. Cellular robustness can be measured as limits of intracellular parameters such as gene expression levels. We have recently developed an experimental approach coined as genetic Tug-Of-War (gTOW), which we used to perform robustness analysis in yeast. Using gTOW, we were able to measure the upper limit of expression of gene targets. In this review, we first elaborate on how the gTOW method compares to current mathematical simulation models prevalently used in the determination of robustness. We then explain the experimental principles underlying gTOW and its associated tools, and we provide concrete examples of robustness analysis using gTOW, i.e. cell cycle and HOG pathway gene expression analysis. Finally, we list a series of Q&As related to the experimental utilization of gTOW and we describe the potential impact of gTOW and its relevance to the understanding of biological systems.     

Microbial reductive dehalogenation.

A wide variety of compounds can be biodegraded via reductive removal of halogen substituents. This process can degrade toxic pollutants, some of which are not known to be biodegraded by any other means. Reductive dehalogenation of aromatic compounds has been found primarily in undefined, syntrophic anaerobic communities. We discuss ecological and physiological principles which appear to be important in these communities and evaluate how widely applicable these principles are. Anaerobic communities that catalyze reductive dehalogenation appear to differ in many respects. A large number of pure cultures which catalyze reductive dehalogenation of aliphatic compounds are known, in contrast to only a few organisms which catalyze reductive dehalogenation of aromatic compounds. Desulfomonile tiedjei DCB-1 is an anaerobe which dehalogenates aromatic compounds and is physiologically and morphologically unusual in a number of respects, including the ability to exploit reductive dehalogenation for energy metabolism. When possible, we use D. tiedjei as a model to understand dehalogenating organisms in the above-mentioned undefined systems. Aerobes use reductive dehalogenation for substrates which are resistant to known mechanisms of oxidative attack. Reductive dehalogenation, especially of aliphatic compounds, has recently been found in cell-free systems. These systems give us an insight into how and why microorganisms catalyze this activity. In some cases transition metal complexes serve as catalysts, whereas in other cases, particularly with aromatic substrates, the catalysts appear to be enzymes.     

Architecture of physiological functions: the same basis but new aspects

The principles of physiological functions formulated by J. Barckroft (constancy of the internal medium, reserves, any adaptation as an integration, principle of antagonism, doubling of mechanisms) are compared with principles of modern physiology. The place and role of physiology in the life sciences are discussed. The necessity of taking into consideration 4 level of regulation of functions (the nervous system, hormones, autacoids, physicochemical factors of the extracellular fluid) is substantiated, as well as the necessity of identification of 4 levels of organization of physiological systems. The main role of the water-salt homeostasis in maintaining the cell volume is suggested. Significance of various types of receptors and second messengers in regulation and modulation of functions is shown.     

A multi-objective differential evolutionary approach toward more stable gene regulatory networks

Models are of central importance in many scientific contexts. Mathematical and computational modeling of genetic regulatory networks promises to uncover the fundamental principles of living systems. Biological models, such as gene regulatory models, can help us better understand interactions among genes and how cells regulate their production of proteins and enzymes. One feature shared among living systems is their ability to cope with perturbations and remain stable, a property that is the result of evolutionary fine-tuning over many generations. In this study we use random Boolean networks (RBNs) as an abstract model of gene regulatory systems. By applying Differential Evolution (DE), an evolution-based optimization technique, we produce networks with increased stability. DE requires relatively few user-specified parameters, has fast convergence and does not rely on initial conditions to find the global minima within multi-dimensional search spaces.     

Chemical reactions and membranes: A macroscopic basis for active transport II. Non-linear aspects

The physical principles that material and charge are conserved provide a basis for the design of a membrane capable of performing active ion transport in which the connection between “metabolic energy” input and the ion transport process itself is electrical rather than material. Molecular interactions between components in this system are irrelevant to its function. A second model built on the same principles performs active ion transport in a statically symmetrical membrane. The basis of its operation is a weakly stable unsymmetrical concentration profile arising from an enzyme-catalyzed reaction occurring within the membrane. The function of this membrane is irreversibly terminated (“killed”) by interference either with intramembrane concentration gradients or with the reactions which maintain them. Hence, any attempt to study this system by breaking it apart destroys the basis of its function. The existence of these models reveals the logical insufficiency of the molecular biologist's approach to understanding the basis of active transport: Neither the experimental techniques for structure determination (disruption, purification, characterization, and reconstitution) nor the fundamental question of that discipline (What is the molecular connection between &*|… ?) of the molecular biologist are applicable to the study or interpretation of these model systems. While the model systems are artificial, they incorporate only widely applicable concepts of physical chemistry and biochemical kinetics. The is no reason for excluding such mechanisms in natural membrane transport systems. If they are present, then more effective strategies of investigation will be required.     

The Problem of Neuroimmunotherapy of Nervous Diseases

We analyzed the mechanisms of interaction between nervous and immune systems characterized by common principles of organization, common messenger molecules, and regulatory functions significant for the whole organism. Common components of neuroimmunity and nonimmune pathological processes underlie the possibility of their mutual potentiation [1]. Neuroimmune diseases are associated with the formation of cortical, subcortical, and brainstem neuronal ensembles involved in the regulation of immune and endocrine systems [2]. The comparison of these ensembles with neuroimmunological parameters allows us to examine the real mechanisms of pathological processes and to evaluate the efficacy of various kinds of therapy including neuroimmunocorrection by neurotropic drugs.     

Some Fundamental Molecular Mechanisms of Contractility in Fibrous Macromolecules

The fundamental molecular mechanisms of contractility and tension development in fibrous macromolecules are developed from the point of view of the principles of polymer physical chemistry. The problem is treated in a general manner to encompass the behavior of all macromolecular systems irrespective of their detailed chemical structure and particular function, if any. Primary attention is given to the contractile process which accompanies the crystal-liquid transition in axially oriented macromolecular systems. The theoretical nature of the process is discussed, and many experimental examples are given from the literature which demonstrate the expected behavior. Experimental attention is focused on the contraction of fibrous proteins, and the same underlying molecular mechanism is shown to be operative for a variety of different systems.     

The origin of ancestral bacterial metabolism

A model for metabolism of the last bacterial common ancestor based on biomimetic analysis of the metabolic systems of phylogenetically ancient bacteria is developed. The mechanism of natural selection and evolution of the autocatalytic chemical systems under the effect of natural homeostatic parameters, such as chemical potentials, temperature, and pressure of environment is proposed. Competition between particular parts of the autocatalytic network with positive-plus-negative feedback resulted in the formation of particular systems of primary autotrophic, mixotrophic, and heterotrophic metabolism. The model of the last common ancestor as a combination of coupled metabolic cycles among population of protocells is discussed. Physicochemical features of these metabolic cycles determined the major principles of natural selection towards ancestral bacterial taxa.     

The energy flux theory 35 years later: formulations and applications

Several models have been proposed for the energetic behavior of the photosynthetic apparatus and a variety of experimental techniques are nowadays available to determine parameters that can quantify this behavior. The Energy Flux Theory (EFT) developed by Strasser 35 years ago provides a straightforward way to formulate any possible energetic communication between any complex arrangement of interconnected pigment systems and any energy transduction by these systems. We here revisit the EFT, starting from the basic general definitions and equations and presenting applications in formulating the energy distribution in photosystem (PS) II units with variable connectivity, as originally derived, where certain simplifications were adopted. We then proceed to the derivation of equations for a PSII model of higher complexity, which corresponds, from the formalistic point of view, to the later formulated and now broadly accepted exciton–radical-pair model. We also compare the formulations derived with the EFT with those obtained, by different approaches, in the classic papers on energetic connectivity. Moreover, we apply the EFT for the evaluation of the excitation energy distribution between PSII and PSI and the distinction between state transitions and PSII to PSI excitation energy migration. Our analysis demonstrates that the EFT is a powerful approach for the formulation of any possible model, at any complexity level, even of models that may be proposed in the future, with the advantage that any possible energetic communication or energy transduction can be easily formulated mathematically by trivial algebraic equations. Moreover, the biophysical parameters introduced by the EFT and applicable for any possible model can be linked with obtainable experimental signals, provided that the theoretical resolution of the model does not go beyond the experimental resolution.     

Advantages and disadvantages of aggregating fluxes into synthetic and degradative fluxes when modelling metabolic pathways.

It is now widely accepted that mathematical models are needed to predict the behaviour of complex metabolic networks in the cell, in order to have a rational basis for planning metabolic engineering with biotechnological or therapeutical purposes. The great complexity of metabolic networks makes it crucial to simplify them for analysis, but without violating key principles of stoichiometry or thermodynamics. We show here, however, that models for branched complex systems are sometimes obtained that violate the stoichiometry of fluxes at branch points and as a result give unrealistic metabolite concentrations at the steady state. This problem is especially important when models are constructed with the S-system form of biochemical systems theory. However, the same violation of stoichiometry can occur in metabolic control analysis if control coefficients are assumed to be constant when trying to predict the effects of large changes. We derive the appropriate matrix equations to analyse this type of problem systematically and to assess its extent in any given model.