Complex oscillatory redox dynamics with signaling potential at the edge between normal and pathological mitochondrial function

The time-keeping properties bestowed by oscillatory behavior on functional rhythms represent an evolutionarily conserved trait in living systems. Mitochondrial networks function as timekeepers maximizing energetic output while tuning reactive oxygen species (ROS) within physiological levels compatible with signaling. In this work, we explore the potential for timekeeping functions dependent on mitochondrial dynamics with the validated two-compartment mitochondrial energetic-redox (ME-R) computational model, that takes into account (a) four main redox couples [NADH, NADPH, GSH, Trx(SH)2], (b) scavenging systems (glutathione, thioredoxin, SOD, catalase) distributed in matrix and extra-matrix compartments, and (c) transport of ROS species between them. Herein, we describe that the ME-R model can exhibit highly complex oscillatory dynamics in energetic/redox variables and ROS species, consisting of at least five frequencies with modulated amplitudes and period according to power spectral analysis. By stability analysis we describe that the extent of steady state—as against complex oscillatory behavior—was dependent upon the abundance of Mn and Cu, Zn SODs, and their interplay with ROS production in the respiratory chain. Large parametric regions corresponding to oscillatory dynamics of increasingly complex waveforms were obtained at low Cu, Zn SOD concentration as a function of Mn SOD. This oscillatory domain was greatly reduced at higher levels of Cu, Zn SOD. Interestingly, the realm of complex oscillations was located at the edge between normal and pathological mitochondrial energetic behavior, and was characterized by oxidative stress. We conclude that complex oscillatory dynamics could represent a frequency- and amplitude-modulated H2O2 signaling mechanism that arises under intense oxidative stress. By modulating SOD, cells could have evolved an adaptive compromise between relative constancy and the flexibility required under stressful redox/energetic conditions.Fil: Kembro, Jackelyn Melissa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Biológicas y Tecnológicas. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales. Instituto de Investigaciones Biológicas y Tecnológicas; ArgentinaFil: Cortassa, Sonia del Carmen. University Johns Hopkins; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Aon, Miguel A.. University Johns Hopkins; Estados Unido

The Scale-Free Dynamics of Eukaryotic Cells

Temporal organization of biological processes requires massively parallel processing on a synchronized time-base. We analyzed time-series data obtained from the bioenergetic oscillatory outputs of Saccharomyces cerevisiae and isolated cardiomyocytes utilizing Relative Dispersional (RDA) and Power Spectral (PSA) analyses. These analyses revealed broad frequency distributions and evidence for long-term memory in the observed dynamics. Moreover RDA and PSA showed that the bioenergetic dynamics in both systems show fractal scaling over at least 3 orders of magnitude, and that this scaling obeys an inverse power law. Therefore we conclude that in S. cerevisiae and cardiomyocytes the dynamics are scale-free in vivo. Applying RDA and PSA to data generated from an in silico model of mitochondrial function indicated that in yeast and cardiomyocytes the underlying mechanisms regulating the scale-free behavior are similar. We validated this finding in vivo using single cells, and attenuating the activity of the mitochondrial inner membrane anion channel with 4-chlorodiazepam to show that the oscillation of NAD(P)H and reactive oxygen species (ROS) can be abated in these two evolutionarily distant species. Taken together these data strongly support our hypothesis that the generation of ROS, coupled to redox cycling, driven by cytoplasmic and mitochondrial processes, are at the core of the observed rhythmicity and scale-free dynamics. We argue that the operation of scale-free bioenergetic dynamics plays a fundamental role to integrate cellular function, while providing a framework for robust, yet flexible, responses to the environment

Extensive regulation of metabolism and growth during the cell division cycle

Yeast cells grown in culture can spontaneously synchronize their respiration, metabolism, gene expression and cell division. Such metabolic oscillations in synchronized cultures reflect single-cell oscillations, but the relationship between the oscillations in single cells and synchronized cultures is poorly understood. To understand this relationship and the coordination between metabolism and cell division, we collected and analyzed DNA-content, gene-expression and physiological data, at hundreds of time-points, from cultures metabolically-synchronized at different growth rates, carbon sources and biomass densities. The data enabled us to extend and generalize an ensemble-average-over-phases (EAP) model that connects the population-average gene-expression of asynchronous cultures to the gene-expression dynamics in the single-cells comprising the cultures. The extended model explains the carbon-source specific growth-rate responses of hundreds of genes. Our data demonstrate that for a given growth rate, the frequency of metabolic cycling in synchronized cultures increases with the biomass density. This observation underscores the difference between metabolic cycling in synchronized cultures and in single cells and suggests entraining of the single-cell cycle by a quorum-sensing mechanism. Constant levels of residual glucose during the metabolic cycling of synchronized cultures indicate that storage carbohydrates are required to fuel not only the G1/S transition of the division cycle but also the metabolic cycle. Despite the large variation in profiled conditions and in the time-scale of their dynamics, most genes preserve invariant dynamics of coordination with each other and with the rate of oxygen consumption. Similarly, the G1/S transition always occurs at the beginning, middle or end of the high oxygen consumption phases, analogous to observations in human and drosophila cells.Comment: 34 pages, 7 figure

The Yin and Yang of Yeast Transcription: Elements of a Global Feedback System between Metabolism and Chromatin

When grown in continuous culture, budding yeast cells tend to synchronize their respiratory activity to form a stable oscillation that percolates throughout cellular physiology and involves the majority of the protein-coding transcriptome. Oscillations in batch culture and at single cell level support the idea that these dynamics constitute a general growth principle. The precise molecular mechanisms and biological functions of the oscillation remain elusive. Fourier analysis of transcriptome time series datasets from two different oscillation periods (0.7 h and 5 h) reveals seven distinct co-expression clusters common to both systems (34% of all yeast ORF), which consolidate into two superclusters when correlated with a compilation of 1,327 unrelated transcriptome datasets. These superclusters encode for cell growth and anabolism during the phase of high, and mitochondrial growth, catabolism and stress response during the phase of low oxygen uptake. The promoters of each cluster are characterized by different nucleotide contents, promoter nucleosome configurations, and dependence on ATP-dependent nucleosome remodeling complexes. We show that the ATP:ADP ratio oscillates, compatible with alternating metabolic activity of the two superclusters and differential feedback on their transcription via activating (RSC) and repressive (Isw2) types of promoter structure remodeling. We propose a novel feedback mechanism, where the energetic state of the cell, reflected in the ATP:ADP ratio, gates the transcription of large, but functionally coherent groups of genes via differential effects of ATP-dependent nucleosome remodeling machineries. Besides providing a mechanistic hypothesis for the delayed negative feedback that results in the oscillatory phenotype, this mechanism may underpin the continuous adaptation of growth to environmental conditions

Developing a tool to characterize the ultradian rhythm in diploid Saccharomyces cervisiae using the reporter gene green fluorescent protein

Biological rhythms control many temporal behaviors of organism, such as the sleep cycle, hearts rhythms, seasonal animal migrations etc. Understanding these rhythms would provide insight into the temporal process of living organisms. Saccharomyces cerevisiae, a budding yeast, is an ideal model organism to study biological rhythms in eukaryotic cells because of its sequenced genome and discerned processes. By characterizing the biological rhythm in budding yeast, insight can be gained into more complex organisms. Previous studies have exhibited oscillatory behavior of oxygen consumption and determined that deletion of the GTS1 gene dissipates this rhythm. However, to further understand the specific behavior of this gene, GTS1 needs to be simultaneous monitored as it is expressed. In this study to monitor this ultradian rhythm regulating gene, a promoter-reporter construct was inserted through homologous recombination to track the expression of GTS1 in a diploid yeast strain, BY 4743. The promoter-reporter construct replaced one copy of the GTS1. As the GTS1 was expressed, the construct was expressed and detected by its reporter gene, green fluorescent protein (GFP). Synchronization of the cell cycle and ultradian rhythm was achieved by addition of hydroxyurea and nocodazole to the growth media. GFP levels were quantified by flow cytometry, with samples taken every 10 minutes. The results showed GFP expression level from the transformed yeast strain exhibiting a 3.33-fold increase relative to the non-transformed yeast strain. GFP expression yielded a biological rhythm with two identifiable periods, each with a 70 minute period. The first oscillation began at time zero and had a GFP expression maximum of 2.96 times the control level and a minimum of 2.62. The second oscillation began at 70 minutes had a GFP expression maximum of 3.09 times the control and a minimum of 2.76. The biological rhythm observed was shorter than its own cell cycle, roughly 111 minutes. Oscillatory behavior was observed as long as the culture remained synchronous. This study characterized the behavior of GTS1, an ultradian rhythm gene. By characterizing the behavior of this gene in S. cerevisiae, homologous genes in more complex organisms such as rodents or humans can be better understood. By extrapolating temporal behavior in yeast to humans, a cost effective drug prescreening can be implemented to evaluate possible biological rhythmic changes

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

A tuneable attractor underlies yeast respiratory dynamics

Our understanding of the molecular structure and function in the budding yeast, Saccharomyces cerevisiae, surpasses that of all other eukaryotic cells. However, the fundamental properties of the complex processes and their control systems have been difficult to reconstruct from detailed dissection of their molecular components. Spontaneous oscillatory dynamics observed in self-synchronized continuous cultures is pervasive, involves much of the cellular network, and provides unique insights into integrative cell physiology. Here, in non-invasive experiments in vivo, we exploit these oscillatory dynamics to analyse the global timing of the cellular network to show the presence of a low-order chaotic component. Although robust to a wide range of environmental perturbations, the system responds and reacts to the imposition of harsh environmental conditions, in this case low pH, by dynamic re-organization of respiration, and this feeds upwards to affect cell division. These complex dynamics can be represented by a tuneable attractor that orchestrates cellular complexity and coherence to the environment