Mind the gap - Relevant design for laboratory oil exposure of fish as informed by a numerical impact assessment model.

Laboratory experiments provide knowledge of species-specific effects thresholds that are used to parameterize impact assessment models of oil contamination on marine ecosystems. Such experiments typically place individuals of species and life stages in tanks with different contaminant concentrations. Exposure concentrations are usually fixed, and the individuals experience a shock treatment being moved from clean water directly into contaminated water and then back to clean water. In this study, we use a coupled numerical model that simulates ocean currents and state, oil dispersal and fate, and early life stages of fish to quantify oil exposure histories, specifically addressing oil spill scenarios of high rates and long durations. By including uptake modelling we also investigate the potential of buffering transient high peaks in exposure. Our simulation results are the basis for a recommendation on the design of laboratory experiments to improve impact assessment model development and parameterization. We recommend an exposure profile with three main phases: i) a gradual increase in concentration, ii) a transient peak that is well above the subsequent level, and iii) a plateau of fixed concentration lasting ∼3 days. In addition, a fourth phase with a slow decrease may be added.

An annual profile of the impacts of simulated oil spills on the Northeast Arctic cod and haddock fisheries.

We simulate the combined natural and pollutant-induced survival of early life stages of NEA cod and haddock, and the impact on the adult populations in response to the time of a major oil spill in a single year. Our simulations reveal how dynamic ocean processes, controlling both oil transport and fate and the frequency of interactions of oil with drifting fish eggs and larvae, mediate the magnitude of population losses due to an oil spill. The largest impacts on fish early life stages occurred for spills initiated in Feb-Mar, concomitant with the initial rise in marine productivity and the earliest phase of the spawning season. The reproductive health of the adult fish populations was maintained in all scenarios. The study demonstrates the application of a simulation system that provides managers with information for the planning of development activities and for the protection of fisheries resources from potential impacts.

G3BPs tether the TSC complex to lysosomes and suppress mTORC1 signaling.

Ras GTPase-activating protein-binding proteins 1 and 2 (G3BP1 and G3BP2, respectively) are widely recognized as core components of stress granules (SGs). We report that G3BPs reside at the cytoplasmic surface of lysosomes. They act in a non-redundant manner to anchor the tuberous sclerosis complex (TSC) protein complex to lysosomes and suppress activation of the metabolic master regulator mechanistic target of rapamycin complex 1 (mTORC1) by amino acids and insulin. Like the TSC complex, G3BP1 deficiency elicits phenotypes related to mTORC1 hyperactivity. In the context of tumors, low G3BP1 levels enhance mTORC1-driven breast cancer cell motility and correlate with adverse outcomes in patients. Furthermore, G3bp1 inhibition in zebrafish disturbs neuronal development and function, leading to white matter heterotopia and neuronal hyperactivity. Thus, G3BPs are not only core components of SGs but also a key element of lysosomal TSC-mTORC1 signaling.

Identification of evolutionary and kinetic drivers of NAD-dependent signaling.

Nicotinamide adenine dinucleotide (NAD) provides an important link between metabolism and signal transduction and has emerged as central hub between bioenergetics and all major cellular events. NAD-dependent signaling (e.g., by sirtuins and poly-adenosine diphosphate [ADP] ribose polymerases [PARPs]) consumes considerable amounts of NAD. To maintain physiological functions, NAD consumption and biosynthesis need to be carefully balanced. Using extensive phylogenetic analyses, mathematical modeling of NAD metabolism, and experimental verification, we show that the diversification of NAD-dependent signaling in vertebrates depended on 3 critical evolutionary events: 1) the transition of NAD biosynthesis to exclusive usage of nicotinamide phosphoribosyltransferase (NamPT); 2) the occurrence of nicotinamide N-methyltransferase (NNMT), which diverts nicotinamide (Nam) from recycling into NAD, preventing Nam accumulation and inhibition of NAD-dependent signaling reactions; and 3) structural adaptation of NamPT, providing an unusually high affinity toward Nam, necessary to maintain NAD levels. Our results reveal an unexpected coevolution and kinetic interplay between NNMT and NamPT that enables extensive NAD signaling. This has implications for therapeutic strategies of NAD supplementation and the use of NNMT or NamPT inhibitors in disease treatment.

SBMLmod: a Python-based web application and web service for efficient data integration and model simulation.

BACKGROUND: Systems Biology Markup Language (SBML) is the standard model representation and description language in systems biology. Enriching and analysing systems biology models by integrating the multitude of available data, increases the predictive power of these models. This may be a daunting task, which commonly requires bioinformatic competence and scripting. RESULTS: We present SBMLmod, a Python-based web application and service, that automates integration of high throughput data into SBML models. Subsequent steady state analysis is readily accessible via the web service COPASIWS. We illustrate the utility of SBMLmod by integrating gene expression data from different healthy tissues as well as from a cancer dataset into a previously published model of mammalian tryptophan metabolism. CONCLUSION: SBMLmod is a user-friendly platform for model modification and simulation. The web application is available at http://sbmlmod.uit.no , whereas the WSDL definition file for the web service is accessible via http://sbmlmod.uit.no/SBMLmod.wsdl . Furthermore, the entire package can be downloaded from https://github.com/MolecularBioinformatics/sbml-mod-ws . We envision that SBMLmod will make automated model modification and simulation available to a broader research community.