Population diversification in a yeast metabolic program promotes anticipation of environmental shifts.
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ABSTRACT:
SUBMITTER: Venturelli OS
PROVIDER: S-EPMC4307983 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A large-scale functional genomics study revealed shifting energy generating processes in white muscle during the final 1,300 km migration of wild sockeye salmon to their spawning grounds in the Fraser River, British Columbia. In 2006, Lower Adams stock sockeye salmon ceased feeding after passing the Queen Charlotte Islands, 850 km from the Fraser River. Enhanced protein turnover and reduced transcription of actin, muscle contractile and heme-related proteins were early starvation responses in saltwater. Arrival to the estuarine environment triggered massive protein turnover through induction of proteasoma and lysosomal proteolysis and protein biosynthesis, and a shift from anaerobic glycolysis to oxidative phosphorylation. Response to entry into freshwater was modest, with up-regulation of heat shock proteins and nitric oxide biosynthesis. High river temperatures resulted in a strong defense/immune response and high mortalities in 50% of fish. Arrival to the spawning grounds triggered further up-regulation of oxidative phosphorylation and proteolysis, down-regulation of protein biosynthesis and helicase activity, and continued down-regulation of muscle proteins and most glycolytic enzymes. However, sharp up-regulation of PFK-I indicated induction of glycolytic potential at the spawning grounds. The identification of potential environmental cues triggering genome-wide transcriptional shifts in white muscle associated with migration and the strong activation of proteasomal proteolysis were both novel findings. Keywords: Functional genomics study on wild-caught fish The experiment was based on expression profiles of white muscle tissue collected from wild migrating adult sockeye salmon during their return spawning migration back to the Fraser River. Fish were collected from seven sites along the final 1,300 km migration path, and white muscle samples were quickly frozen in liquid nitrogen upon capture. Marine sampling sites included (from north to south) the Queen Charlotte Islands (QCI), Johnstone Strait (JS), Juan de Fuca Strait (JDFS), and the Strait of Georgia (SOG). Freshwater sampling sites included Whonnock (W), Savona (SV) and the Lower Adams Spawning Grounds. Genetically-based stock ID was used to identify the natal sites of fish collected from the wild. The experiment was designed to profile the transcriptional shifts associated with migration of the Adams River stock complex. The total experiment included 80 microarray slides, with a minimum biological replicate size per site of 6 (SV), and maximum of 18 (JS) (see supplemental table for details). Additional intra-site variables, which could only be addressed in some sites, included sex (female biased) and river entry timing (for JS, JDFS and W sites; identified through radio-tracking of marine collected fish). Total RNA was amplified (1 round) with MessageAmpTMII-96 kit (Ambion, TX, USA), and reverse transcribed to cDNA before labelling with ALEXA dyes using the Invitrogen Indirect Labelling Kit. The experiment was based on a reference design, with the reference containing the combined aRNA of all individuals used in the experiment. Individual samples were labelled with Alexa 555 and the reference control with Alexa 647, with no dye flips included. A single technical replicate of one SV fish (replicate 5) was included in the experimental design. This experiment is part of a larger white muscle experiment containing additional sockeye salmon stocks.
2010-05-15 | E-GEOD-13657 | biostudies-arrayexpress
Project description:A large-scale functional genomics study revealed shifting energy generating processes in white muscle during the final 1,300 km migration of wild sockeye salmon to their spawning grounds in the Fraser River, British Columbia. In 2006, Lower Adams stock sockeye salmon ceased feeding after passing the Queen Charlotte Islands, 850 km from the Fraser River. Enhanced protein turnover and reduced transcription of actin, muscle contractile and heme-related proteins were early starvation responses in saltwater. Arrival to the estuarine environment triggered massive protein turnover through induction of proteasoma and lysosomal proteolysis and protein biosynthesis, and a shift from anaerobic glycolysis to oxidative phosphorylation. Response to entry into freshwater was modest, with up-regulation of heat shock proteins and nitric oxide biosynthesis. High river temperatures resulted in a strong defense/immune response and high mortalities in 50% of fish. Arrival to the spawning grounds triggered further up-regulation of oxidative phosphorylation and proteolysis, down-regulation of protein biosynthesis and helicase activity, and continued down-regulation of muscle proteins and most glycolytic enzymes. However, sharp up-regulation of PFK-I indicated induction of glycolytic potential at the spawning grounds. The identification of potential environmental cues triggering genome-wide transcriptional shifts in white muscle associated with migration and the strong activation of proteasomal proteolysis were both novel findings. Keywords: Functional genomics study on wild-caught fish
2008-12-09 | GSE13657 | GEO
Project description:Phylogenetic trees of present-day species allow investigation of the rate of evolution that led to the present-day diversity. A recent analysis of the mammalian phylogeny challenged the view of explosive mammalian evolution after the Cretaceous-Tertiary (K/T) boundary (65 Mya). However, due to lack of appropriate methods, the diversification (speciation minus extinction) rates in the more recent past of mammalian evolution could not be determined. In this paper, I provide a method that reveals that the tempo of mammalian evolution did not change until ? 33 Mya. This constant period was followed by a peak of diversification rates between 33 and 30 Mya. Thereafter, diversification rates remained high and constant until 8.55 Mya. Diversification rates declined significantly at 8.55 and 3.35 Mya. Investigation of mammalian subgroups (marsupials, placentals, and the six largest placental subgroups) reveals that the diversification rate peak at 33-30 Mya is mainly driven by rodents, cetartiodactyla, and marsupials. The recent diversification rate decrease is significant for all analyzed subgroups but eulipotyphla, cetartiodactyla, and primates. My likelihood approach is not limited to mammalian evolution. It provides a robust framework to infer diversification rate changes and mass extinction events in phylogenies, reconstructed from, e.g., present-day species or virus data. In particular, the method is very robust toward noise and uncertainty in the phylogeny and can account for incomplete taxon sampling.
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Project description:Humans serve as both host and reservoir for Mycobacterium tuberculosis, making tuberculosis a theoretically eradicable disease. How M. tuberculosis alternates between host-imposed quiescence and sporadic bouts of replication to complete its life cycle, however, remains unknown. Here, we identify a metabolic adaptation that is triggered upon entry into hypoxia-induced quiescence but facilitates subsequent cell cycle re-entry. Catabolic remodelling of the cell surface trehalose mycolates of M. tuberculosis specifically generates metabolic intermediates reserved for re-initiation of peptidoglycan biosynthesis. These adaptations reveal a metabolic network with the regulatory capacity to mount an anticipatory response.
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Project description:Transcriptional noise is a necessary consequence of the molecular events that drive gene expression in prokaryotes. However, some environmental microorganisms that inhabit polluted sites, for example, the m-xylene degrading soil bacterium Pseudomonas putida mt-2 seem to have co-opted evolutionarily such a noise for deploying a metabolic diversification strategy that allows a cautious exploration of new chemical landscapes. We have examined this phenomenon under the light of deterministic and stochastic models for activation of the main promoter of the master m-xylene responsive promoter of the system (Pu) by its cognate transcriptional factor (XylR). These analyses consider the role of co-factors for Pu activation and determinants of xylR mRNA translation. The model traces the onset and eventual disappearance of the bimodal distribution of Pu activity along time to the growth-phase dependent abundance of XylR itself, that is, very low in exponentially growing cells and high in stationary. This tenet was validated by examining the behaviour of a Pu-GFP fusion in a P. putida strain in which xylR expression was engineered under the control of an IPTG-inducible system. This work shows how a relatively simple regulatory scenario (for example, growth-phase dependent expression of a limiting transcription factor) originates a regime of phenotypic diversity likely to be advantageous in competitive environmental settings.
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Project description:Using protein counts sampled from single cell proteomics distributions to constrain fluxes through a genome-scale model of metabolism, Population flux balance analysis (Population FBA) successfully described metabolic heterogeneity in a population of independent Escherichia coli cells growing in a defined medium. We extend the methodology to account for correlations in protein expression arising from the co-regulation of genes and apply it to study the growth of independent Saccharomyces cerevisiae cells in two different growth media. We find the partitioning of flux between fermentation and respiration predicted by our model agrees with recent 13C fluxomics experiments, and that our model largely recovers the Crabtree effect (the experimentally known bias among certain yeast species toward fermentation with the production of ethanol even in the presence of oxygen), while FBA without proteomics constraints predicts respirative metabolism almost exclusively. The comparisons to the 13C study showed improvement upon inclusion of the correlations and motivated a technique to systematically identify inconsistent kinetic parameters in the literature. The minor secretion fluxes for glycerol and acetate are underestimated by our method, which indicate a need for further refinements to the metabolic model. For yeast cells grown in synthetic defined (SD) medium, the calculated broad distribution of growth rates matches experimental observations from single cell studies, and we characterize several metabolic phenotypes within our modeled populations that make use of diverse pathways. Fast growing yeast cells are predicted to perform significant amount of respiration, use serine-glycine cycle and produce ethanol in mitochondria as opposed to slow growing cells. We use a genetic algorithm to determine the proteomics constraints necessary to reproduce the growth rate distributions seen experimentally. We find that a core set of 51 constraints are essential but that additional constraints are still necessary to recover the observed growth rate distribution in SD medium.
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Project description:BackgroundThe ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks.ResultsUsing recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks.ConclusionsOur work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple environments. This organizational principle is insensitive to the environments we consider and to the number of reactions in a metabolic network. Because we observe this principle not just in one or few biological networks, but in large random samples of networks, we propose that it may be a generic principle of metabolic network organization.
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Project description:We consider panacea formation in the framework of adaptive learning and decision for social-ecological systems (SESs). Institutions for managing such systems must address multiple timescales of ecological change, as well as features of the social community in which the ecosystem policy problem is embedded. Response of the SES to each candidate institution must be modeled and treated as a stochastic process with unknown parameters to be estimated. A fundamental challenge is to design institutions that are not vulnerable to capture by subsets of the community that self-organize to direct the institution against the overall social interest. In a world of episodic structural change, such as SESs, adaptive learning can lock in to a single institution, model, or parameter estimate. Policy diversification, leading to escape from panacea traps, can come from monitoring indicators of episodic change on slow timescales, minimax regret decision making, active experimentation to accelerate model identification, mechanisms for broadening the set of models or institutions under consideration, and processes for discovery of new institutions and technologies for ecosystem management. It is difficult to take all of these factors into account, but the discipline that comes with the attempt to model the coupled social-ecological dynamics forces policy makers to confront all conceivable responses. This process helps induce the modesty needed to avoid panacea traps while supporting systematic effort to improve resource management in the public interest.
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