Quantitative analysis of the effective functional structure in yeast glycolysis

The main sources of molecular organization in the cell. Atlas of self-organized and self-regulated dynamic biostructures

One of the most important goals of contemporary biology is to understand the principles of the molecular order underlying the complex dynamic architecture of cells. Here, we present an overview of the main driving forces involved in the cellular molecular complexity and in the emergent functional dynamic structures, spanning from the most basic molecular organization levels to the complex emergent integrative systemic behaviors. First, we address the molecular information processing which is essential in many complex fundamental mechanisms such as the epigenetic memory, alternative splicing, regulation of transcriptional system, and the adequate self-regulatory adaptation to the extracellular environment. Next, we approach the biochemical self-organization, which is central to understand the emergency of metabolic rhythms, circadian oscillations, and spatial traveling waves. Such a complex behavior is also fundamental to understand the temporal compartmentalization of the cellular metabolism and the dynamic regulation of many physiological activities. Numerous examples of biochemical self-organization are considered here, which show that practically all the main physiological processes in the cell exhibit this type of dynamic molecular organization. Finally, we focus on the biochemical self-assembly which, at a primary level of organization, is a basic but important mechanism for the order in the cell allowing biomolecules in a disorganized state to form complex aggregates necessary for a plethora of essential structures and physiological functions. In total, more than 500 references have been compiled in this review. Due to these main sources of order, systemic functional structures emerge in the cell, driving the metabolic functionality towards the biological complexity.

Agent-based models for detecting the driving forces of biomolecular interactions

Agent-based modelling and simulation have been effectively applied to the study of complex biological systems, especially when composed of many interacting entities. Representing biomolecules as autonomous agents allows this approach to bring out the global behaviour of biochemical processes as resulting from local molecular interactions. In this paper, we leverage the capabilities of the agent paradigm to construct an in silico replica of the glycolytic pathway; the aim is to detect the role that long-range electrodynamic forces might have on the rate of glucose oxidation. Experimental evidences have shown that random encounters and short-range potentials might not be sufficient to explain the high efficiency of biochemical reactions in living cells. However, while the latest in vitro studies are limited by present-day technology, agent-based simulations provide an in silico support to the outcomes hitherto obtained and shed light on behaviours not yet well understood. Our results grasp properties hard to uncover through other computational methods, such as the effect of electromagnetic potentials on glycolytic oscillations.

Self-Organization and Information Processing: From Basic Enzymatic Activities to Complex Adaptive Cellular Behavior

One of the main aims of current biology is to understand the origin of the molecular organization that underlies the complex dynamic architecture of cellular life. Here, we present an overview of the main sources of biomolecular order and complexity spanning from the most elementary levels of molecular activity to the emergence of cellular systemic behaviors. First, we have addressed the dissipative self-organization, the principal source of molecular order in the cell. Intensive studies over the last four decades have demonstrated that self-organization is central to understand enzyme activity under cellular conditions, functional coordination between enzymatic reactions, the emergence of dissipative metabolic networks (DMN), and molecular rhythms. The second fundamental source of order is molecular information processing. Studies on effective connectivity based on transfer entropy (TE) have made possible the quantification in bits of biomolecular information flows in DMN. This information processing enables efficient self-regulatory control of metabolism. As a consequence of both main sources of order, systemic functional structures emerge in the cell; in fact, quantitative analyses with DMN have revealed that the basic units of life display a global enzymatic structure that seems to be an essential characteristic of the systemic functional metabolism. This global metabolic structure has been verified experimentally in both prokaryotic and eukaryotic cells. Here, we also discuss how the study of systemic DMN, using Artificial Intelligence and advanced tools of Statistic Mechanics, has shown the emergence of Hopfield-like dynamics characterized by exhibiting associative memory. We have recently confirmed this thesis by testing associative conditioning behavior in individual amoeba cells. In these Pavlovian-like experiments, several hundreds of cells could learn new systemic migratory behaviors and remember them over long periods relative to their cell cycle, forgetting them later. Such associative process seems to correspond to an epigenetic memory. The cellular capacity of learning new adaptive systemic behaviors represents a fundamental evolutionary mechanism for cell adaptation.

Oscillation in tissue oxygen index during recovery from exercise

It was hypothesized that an oscillation of tissue oxygen index (TOI) determined by near-infrared spectroscopy during recovery from exercise occurs due to feedback control of adenosine triphosphate and that frequency of the oscillation is affected by blood pH. In order to examine these hypotheses, we aimed 1) to determine whether there is an oscillation of TOI during recovery from exercise and 2) to determine the effect of blood pH on frequency of the oscillation of TOI. Three exercises were performed with exercise intensities of 30 % and 70 % peak oxygen uptake (V(.)o(2)peak) for 12 min and with exercise intensity of 70 % V(.)o(2)peak for 30 s. TOI during recovery from the exercise was analyzed by fast Fourier transform in order to obtain power spectra density (PSD). There was a significant difference in the frequency at which maximal PSD of TOI appeared (Fmax) between the exercises with 70 % V(.)o(2)peak for 12 min (0.0039+/-0 Hz) and for 30 s (0.0061+/-0.0028 Hz). However, there was no significant difference in Fmax between the exercises with 30 % (0.0043+/-0.0013 Hz) and with 70 % V(.)o(2)peak for 12 min despite differences in blood pH and blood lactate from the warmed fingertips. It is concluded that there was an oscillation in TOI during recovery from the three exercises. It was not clearly shown that there was an effect of blood pH on Fmax.

Elements of the cellular metabolic structure

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell.

On the dynamics of the adenylate energy system: homeorhesis vs homeostasis

Biochemical energy is the fundamental element that maintains both the adequate turnover of the biomolecular structures and the functional metabolic viability of unicellular organisms. The levels of ATP, ADP and AMP reflect roughly the energetic status of the cell, and a precise ratio relating them was proposed by Atkinson as the adenylate energy charge (AEC). Under growth-phase conditions, cells maintain the AEC within narrow physiological values, despite extremely large fluctuations in the adenine nucleotides concentration. Intensive experimental studies have shown that these AEC values are preserved in a wide variety of organisms, both eukaryotes and prokaryotes. Here, to understand some of the functional elements involved in the cellular energy status, we present a computational model conformed by some key essential parts of the adenylate energy system. Specifically, we have considered (I) the main synthesis process of ATP from ADP, (II) the main catalyzed phosphotransfer reaction for interconversion of ATP, ADP and AMP, (III) the enzymatic hydrolysis of ATP yielding ADP, and (IV) the enzymatic hydrolysis of ATP providing AMP. This leads to a dynamic metabolic model (with the form of a delayed differential system) in which the enzymatic rate equations and all the physiological kinetic parameters have been explicitly considered and experimentally tested in vitro. Our central hypothesis is that cells are characterized by changing energy dynamics (homeorhesis). The results show that the AEC presents stable transitions between steady states and periodic oscillations and, in agreement with experimental data these oscillations range within the narrow AEC window. Furthermore, the model shows sustained oscillations in the Gibbs free energy and in the total nucleotide pool. The present study provides a step forward towards the understanding of the fundamental principles and quantitative laws governing the adenylate energy system, which is a fundamental element for unveiling the dynamics of cellular life.

Oscillation in O2 uptake in impulse exercise

The purpose of the present study was to examine 1) whether O(2) uptake (VO(2)) oscillates during light exercise and 2) whether the oscillation is enhanced after impulse exercise. After resting for 1 min on a bicycle seat, subjects performed 5-min pre-exercise with 25 watts work load, 10-s impulse exercise with 200 watts work load and 15-min post exercise with 25 watts work load at 80 rpm. VO(2) during pre-exercise significantly increased during impulse exercise and suddenly decreased and re-increased until 23 s after impulse exercise. In the cross correlation between heart rate (HR) and VO(2) after impulse exercise, VO(2) strongly correlated to HR with a time delay of -4 s. Peak of power spectral density (PSD) in HR appeared at 0.0039 Hz and peak of PSD in VO(2) appeared at 0.019 Hz. The peak of the cross power spectrum between VO(2) and HR appeared at 0.0078 Hz. The results suggested that there is an oscillation in O(2) uptake during light exercise that is associated with the oscillation in O(2) consumption in active muscle. The oscillation is enhanced not only by change in O(2) consumption but also by O(2) content transported from active muscle to the lungs.

Comparison of oscillations of skin blood flow and deoxygenation in vastus lateralis in light exercise

The purpose of the present study was to compare oscillation of skin blood flow with that of deoxygenation in muscle during light exercise in order to determine the physiological significance of oscillations in deoxygenation. Prolonged exercise with 50% of peak oxygen uptake was performed for 60 min. Skin blood flow (SBF) was measured using a laser blood flow meter on the right vastus lateralis muscle. Deoxygenated haemoglobin/myoglobin (DHb/Mb) concentration in the left vastus lateralis were measured using a near-infrared spectroscopy system. SBF and DHb/Mb during exercise were analysed by fast Fourier transform. We classified frequency bands according to previous studies (Kvernmo et al. 1999, Kvandal et al. 2006) into phase I (0.005-0.0095 and 0.0095-0.02 Hz), phase II (0.02-0.06 Hz: phase II) and phase III (0.06-0.16 Hz). The first peak of power spectra density (PSD) in SBF appeared at 0.0078 Hz in phase I. The second peak of PSD in SBF appeared at 0.035 Hz. The third peak of PSD in SBF appeared at 0.078 Hz. The first peak of PSD in DHb/Mb appeared at 0.0039 Hz, which was out of phase I. The second peak of PSD in DHb/Mb appeared at 0.016 Hz. The third peak of PSD in DHb/Mb appeared at 0.035 Hz. The coefficient of cross correlation was very low. Cross power spectra density showed peaks of 0.0039, 0.016 and 0.035 Hz. It is concluded that a peak of 0.016 Hz in oscillations of DHb/Mb observed in muscle during exercise is associated with endothelium-dependent vasodilation (phase I) and that a peak of 0.035 Hz in DHb/Mb is associated with sympathetic nerve activity (phase II). It is also confirmed that each peak of SBF oscillations is observed in each phase.

Comparative proteomics analysis of engineered Saccharomyces cerevisiae with enhanced biofuel precursor production

The yeast Saccharomyces cerevisiae was metabolically modified for enhanced biofuel precursor production by knocking out genes encoding mitochondrial isocitrate dehydrogenase and over-expression of a heterologous ATP-citrate lyase. A comparative iTRAQ-coupled 2D LC-MS/MS analysis was performed to obtain a global overview of ubiquitous protein expression changes in S. cerevisiae engineered strains. More than 300 proteins were identified. Among these proteins, 37 were found differentially expressed in engineered strains and they were classified into specific categories based on their enzyme functions. Most of the proteins involved in glycolytic and pyruvate branch-point pathways were found to be up-regulated and the proteins involved in respiration and glyoxylate pathway were however found to be down-regulated in engineered strains. Moreover, the metabolic modification of S. cerevisiae cells resulted in a number of up-regulated proteins involved in stress response and differentially expressed proteins involved in amino acid metabolism and protein biosynthesis pathways. These LC-MS/MS based proteomics analysis results not only offered extensive information in identifying potential protein-protein interactions, signal pathways and ubiquitous cellular changes elicited by the engineered pathways, but also provided a meaningful biological information platform serving further modification of yeast cells for enhanced biofuel production.

Comparison of oscillation of oxygenation in skeletal muscle between early and late phases in prolonged exercise

The aim of the present study was to compare the oscillations of oxygenation in skeletal muscle between early and late phases in prolonged exercise. During prolonged exercise at 60 % of peak oxygen uptake (V(.)o(2)) for 60 min and at rest, oxygenated hemoglobin/myoglobin (Hb/MbO(2)) and total Hb/Mb (THb/Mb) were determined by near-infrared spectroscopy in the vastus lateralis. Power spectra density (PSD) for the difference between Hb/MbO(2) and THb/Mb (-HHb/MbO(2): deoxygenation) was obtained by fast Fourier transform at rest, in the early phase (1-6 min) and in the late phase (55-60 min) in exercise. Peak PSD in the early phase was significantly higher than that at rest. There were at least three peaks of PSD in exercise. The highest peak was a band around 0.01 Hz, the next peak was a band around 0.04 Hz, and the lowest peak was a band around 0.06 Hz. PSD in the early phase was not significantly different from that in the late phase in exercise. Heart rate (HR) showed a continuous significant increase from 3 min in exercise until the end of exercise. Skin blood flow (SBF) around the early phase was significantly lower than that around the late phase. It was concluded that oscillation of oxygenation in the muscle oxygen system in the early phase is not different from that in the late phase in prolonged exercise despite cardiovascular drift.

Attractor metabolic networks

BACKGROUND

The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity.

METHODOLOGY/PRINCIPAL FINDINGS

In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools, studying some macroscopic properties such as the global information and the energy of the system. We have also obtained an equivalent Hopfield network using a Boltzmann machine. Our main result shows that the dissipative metabolic network can behave as an attractor metabolic network.

CONCLUSIONS/SIGNIFICANCE

We have found that the systemic enzymatic activities are governed by attractors with capacity to store functional metabolic patterns which can be correctly recovered from specific input stimuli. The network attractors regulate the catalytic patterns, modify the efficiency in the connection between the multienzymatic complexes, and stably retain these modifications. Here for the first time, we have introduced the general concept of attractor metabolic network, in which this dynamic behavior is observed.