Cellular Automata Model of Macroevolution

In this paper I describe a cellular automaton model of a multi-species ecosystem, suitable for the study of emergent properties of macroevolution. Unlike majority of ecological models, the number of coexisting species is not fixed. Starting from one common ancestor they appear by "mutations" of existent species, and then survive or extinct depending on the balance of local ecological interactions. Monte-Carlo numerical simulations show that this model is able to qualitatively reproduce phenomena that have been observed in other models and in nature.Comment: 8 pages, 3 figures, Fourteenth National Conference on Application of Mathematics in Biology and Medicine, Leszno 2008 (POLAND

Kinetics of the ancestral carbon metabolism pathways in deep-branching bacteria and archaea

The origin of life is believed to be chemoautotrophic, deriving all biomass components from carbon dioxide, and all energy from inorganic redox couples in the environment. The reductive tricarboxylic acid cycle (rTCA) and the Wood-Ljungdahl pathway (WL) have been recognized as the most ancient carbon fixation pathways. The rTCA of the chemolithotrophic Thermosulfidibacter takaii, which was recently demonstrated to take place via an unexpected reverse reaction of citrate synthase, was reproduced using a kinetic network model, and a competition between reductive and oxidative fluxes on rTCA due to an acetyl coenzyme A (ACOA) influx upon acetate uptake was revealed. Avoiding ACOA direct influx into rTCA from WL is, therefore, raised as a kinetically necessary condition to maintain a complete rTCA. This hypothesis was confirmed for deep-branching bacteria and archaea, and explains the kinetic factors governing elementary processes in carbon metabolism evolution from the last universal common ancestor

Visualization of metabolic interaction networks in microbial communities using VisANT 5.0

The complexity of metabolic networks in microbial communities poses an unresolved visualization and interpretation challenge. We address this challenge in the newly expanded version of a software tool for the analysis of biological networks, VisANT 5.0. We focus in particular on facilitating the visual exploration of metabolic interaction between microbes in a community, e.g. as predicted by COMETS (Computation of Microbial Ecosystems in Time and Space), a dynamic stoichiometric modeling framework. Using VisANT's unique metagraph implementation, we show how one can use VisANT 5.0 to explore different time-dependent ecosystem-level metabolic networks. In particular, we analyze the metabolic interaction network between two bacteria previously shown to display an obligate cross-feeding interdependency. In addition, we illustrate how a putative minimal gut microbiome community could be represented in our framework, making it possible to highlight interactions across multiple coexisting species. We envisage that the "symbiotic layout" of VisANT can be employed as a general tool for the analysis of metabolism in complex microbial communities as well as heterogeneous human tissues.This work was supported by the National Institutes of Health, R01GM103502-05 to CD, ZH and DS. Partial support was also provided by grants from the Office of Science (BER), U.S. Department of Energy (DE-SC0004962), the Joslin Diabetes Center (Pilot & Feasibility grant P30 DK036836), the Army Research Office under MURI award W911NF-12-1-0390, National Institutes of Health (1RC2GM092602-01, R01GM089978 and 5R01DE024468), NSF (1457695), and Defense Advanced Research Projects Agency Biological Technologies Office (BTO), Program: Biological Robustness In Complex Settings (BRICS), Purchase Request No. HR0011515303, Program Code: TRS-0 Issued by DARPA/CMO under Contract No. HR0011-15-C-0091. Funding for open access charge: National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. (R01GM103502-05 - National Institutes of Health; 1RC2GM092602-01 - National Institutes of Health; R01GM089978 - National Institutes of Health; 5R01DE024468 - National Institutes of Health; DE-SC0004962 - Office of Science (BER), U.S. Department of Energy; P30 DK036836 - Joslin Diabetes Center; W911NF-12-1-0390 - Army Research Office under MURI; 1457695 - NSF; HR0011515303 - Defense Advanced Research Projects Agency Biological Technologies Office (BTO), Program: Biological Robustness In Complex Settings (BRICS); HR0011-15-C-0091 - DARPA/CMO; National Institutes of Health)Published versio

Workshop on Closed System Ecology

Self maintaining laboratory scale ecological systems completely isolated from exchanges of matter with external systems were demonstrated. These research tools are discussed in terms of their anticipated value in understanding (1) global ecological material and energy balances, (2) the dynamics of stability and instability in ecosystems, (3) the effects of man-made substances and structures on ecosystems, and (4) the precise requirements for dynamic control of controlled ecology life support systems (CELSS)

The Assessment of the Real-Time Radiative Properties and Productivity of Limnospira platensis in Tubular Photobioreactors

The development of tools to predict the photobioreactors’ (PBRs) productivity is a significant concern in biotechnology. To this end, it is required to know the light availability inside the cultivation unit and combine this information with a suitable kinetic expression that links the distribution of radiant energy with the cell growth rate. In a previous study, we presented and validated a methodology for assessing the radiative properties necessary to address the light distribution inside a PBR for varying illuminating conditions through the cultivation process of a phototrophic microorganism. Here, we sought to utilise this information to construct a predictive tool to estimate the productivity of an autotrophic bioprocess carried out in a 100 [L] tubular photobioreactor (TPBR). Firstly, the time-dependent optical properties over ten batch cultures of L. platensis were calculated. Secondly, the local volumetric rate of photon absorption was assessed based on a physical model of the interaction of the radiant energy with the suspended biomass, together with a Monte Carlo simulation algorithm. Lastly, a kinetic expression valid for low illumination conditions has been utilised to reproduce all the cultures’ experimentally obtained dry weight biomass concentration values. Taken together, time-dependent radiative properties and the kinetic model produced a valuable tool for the study and scaling up of TPBRs.Fil: Ibañez, Manuel Vicente. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; ArgentinaFil: Leonardi, Rodrigo Jorge. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; ArgentinaFil: Krujatz, Felix. University of Applied Sciences Zittau; AlemaniaFil: Heinrich, Josué Miguel. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentin

The Effects of Multiple Stressors on Stream Communities: The Convergence of Drought, Nutrient Pollution, and Invasive Species

Freshwater systems experience multi-faceted degradation from a variety of ecological and environmental stressors. Three common stressors in these systems, drought, nutrient pollution, and invasive species, have wide-ranging effects on stream population- community- and ecosystem dynamics. We have a broad understanding of how each of these stressors works to influence stream systems independently. However, we still know relatively little about if, and how, these stressors might interact when they co-occur. Though drought is a natural part of many stream systems, all three of these stressors can be exacerbated or facilitated by anthropogenic actions. Accordingly, as human population and resource use continue to grow, it becomes increasingly likely that these stressors will co-occur. To address this, I undertook research that sought to better explore the effects of multiple, simultaneous stressors on stream ecosystems. Here, I performed a series of manipulative experiments and constructed mathematical models that examined the effects of varying combinations of drought, nutrients, and invasive species along several ecological scales. I found that each of these stressors can impact stream ecosystems in diverse ways. For instance, drought negatively impacted many portions of the community, while nutrients caused bottom-up trophic effects. Additionally, my models indicated that both drought and invasive species can increase terminal extinction risk for fish metapopulations. However, I also observed several interactive effects. Drought and nutrient pollution interacted both additively and antagonistically on various portions of the food web simultaneously in my experiments, and drought and invasive species interacted synergistically to increase terminal extinction risk in my metapopulation models. Across all examinations, I found that the effects of both individual and multiple stressors are context dependent. Trophic role, life history strategy, and physical habitat all shaped stressor response. This work highlights the complexity of multiple stressors in stream systems and emphasizes a growing need to undertake additional examinations across various taxonomic groups and ecological scales. Our broad knowledge of the effects of individual stressors might not translate to multi-stressor systems, and conservation and management plans that only account for individual stressors might be inadequate to protect resources in systems facing multiple stressors

Modern views of ancient metabolic networks

Metabolism is a molecular, cellular, ecological and planetary phenomenon, whose fundamental principles are likely at the heart of what makes living matter different from inanimate one. Systems biology approaches developed for the quantitative analysis of metabolism at multiple scales can help understand metabolism's ancient history. In this review, we highlight work that uses network-level approaches to shed light on key innovations in ancient life, including the emergence of proto-metabolic networks, collective autocatalysis and bioenergetics coupling. Recent experiments and computational analyses have revealed new aspects of this ancient history, paving the way for the use of large datasets to further improve our understanding of life's principles and abiogenesis.https://www.sciencedirect.com/science/article/pii/S2452310017302196Published versio

Climate change promotes parasitism in a coral symbiosis.

Coastal oceans are increasingly eutrophic, warm and acidic through the addition of anthropogenic nitrogen and carbon, respectively. Among the most sensitive taxa to these changes are scleractinian corals, which engineer the most biodiverse ecosystems on Earth. Corals' sensitivity is a consequence of their evolutionary investment in symbiosis with the dinoflagellate alga, Symbiodinium. Together, the coral holobiont has dominated oligotrophic tropical marine habitats. However, warming destabilizes this association and reduces coral fitness. It has been theorized that, when reefs become warm and eutrophic, mutualistic Symbiodinium sequester more resources for their own growth, thus parasitizing their hosts of nutrition. Here, we tested the hypothesis that sub-bleaching temperature and excess nitrogen promotes symbiont parasitism by measuring respiration (costs) and the assimilation and translocation of both carbon (energy) and nitrogen (growth; both benefits) within Orbicella faveolata hosting one of two Symbiodinium phylotypes using a dual stable isotope tracer incubation at ambient (26 °C) and sub-bleaching (31 °C) temperatures under elevated nitrate. Warming to 31 °C reduced holobiont net primary productivity (NPP) by 60% due to increased respiration which decreased host %carbon by 15% with no apparent cost to the symbiont. Concurrently, Symbiodinium carbon and nitrogen assimilation increased by 14 and 32%, respectively while increasing their mitotic index by 15%, whereas hosts did not gain a proportional increase in translocated photosynthates. We conclude that the disparity in benefits and costs to both partners is evidence of symbiont parasitism in the coral symbiosis and has major implications for the resilience of coral reefs under threat of global change

A Network-Scale Modeling Framework for Stream Metabolism, Ecosystem Efficiency, and Their Response to Climate Change

Climate change and the predicted warmer temperatures and more extreme hydrological regimes could affect freshwater ecosystems and their energy pathways. To appreciate the complex spatial and temporal interactions of carbon cycling in flowing waters, ecosystem metabolism (gross primary production [GPP] and ecosystem respiration [ER]) must be resolved at the scale of an entire river network. Here, we propose a meta-ecosystem framework that couples light and temperature regimes with a reach-scale ecosystem model and integrates network structure, catchment land cover, and the hydrologic regime. The model simulates the distributed functioning of dissolved and particulate organic carbon, autotrophic biomass, and thus ecosystem metabolism, and reproduces fairly well the metabolic regimes observed in 12 reaches of the Ybbs River network, Austria. Results show that the annual network-scale metabolism was heterotrophic, yet with a clear peak of autotrophy in spring. Autochthonous energy sources contributed 43% of the total ER. We further investigated the effect of altered thermal and hydrologic regimes on metabolism and ecosystem efficiency. We predicted that an increase of 2.5? in average stream water temperature could boost ER and GPP by 31% (24%-57%) and 28% (5%-57%), respectively. The effect of flashier hydrologic regimes is more complex and depends on autotrophic biomass density. The analysis shows the complex interactions between environmental conditions and biota in shaping stream metabolism and highlights the existing knowledge gaps for reliable predictions of the effects of climate change in these ecosystems

From pathway to regulon in Arabidopsis

Combined bioinformatic approaches, using genomic and transcriptomic data, are applied to investigate the fatty acid biosynthesis pathway, at the molecular level, and in the context of the system biology of Arabidopsis. Fatty acids are essential components of all known bacterial and eukaryotic cells with critical role in cells as energy reserves and the metabolic precursors for biological membranes. The pathway for fatty acid synthesis seems to be conserved across all living systems. Acetyl-CoA carboxylase, a member of a superfamily of biotin-dependent enzymes, catalyzes the first committed step of the fatty acid biosynthesis pathway. Phylogenetic study exposed complex and intertwined evolutionary histories of this family, with multiple domain fusions and rearrangements. As revealed by meta-analysis of a wide array of Arabidopsis transcriptomic data, fatty acid biosynthesis is transcriptionally regulated, and this regulation not only extends across all pathway reactions, but also some substrate- and cofactor-producing reactions, thus defining a major transcriptionally co-regulated pathway. Meta-analysis of the transcriptome is extended to find groups of coexpressed genes (also called modules, or regulons) in the Arabidopsis genome. Major functionally-coherent gene groups were identified. These comprise development, information processing, defense, and metabolism, as well as tissue- and organelle-specific processes