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Results for “dynamic flux balance analysis”

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6 recordsLinked to original sources

PubMed2026

dAMN: a genome-scale neural-mechanistic hybrid model to predict bacterial growth dynamics.

SUMMARY: This study presents dAMN, a genome-scale neural-mechanistic hybrid model that combines neural networks with dynamic flux balance analysis to predict bacterial growth dynamics across diverse nutrient environments. Using a residual network architecture, dAMN predicts reaction fluxes and lag-phase parameters from initial medium composition, then integrates these predictions under stoichiometric constraints derived from genome-scale metabolic models. Trained on Escherichia coli and Pseudomonas putida growth datasets across combinatorial media, dAMN accurately forecasts temporal growth dynamics and generalizes to unseen media conditions, with mean R² ≥ 0.9. The model also reproduces biologically relevant behaviors including substrate depletion, acetate overflow, and diauxic shifts, while explicitly modeling lag phases usually absent from standard dFBA. AVAILABILITY AND IMPLEMENTATION: The dAMN software, associated models, and datasets are available at https://github.com/brsynth/dAMN-main-release and via Zenodo DOI: 10.5281/zenodo.17908125.

Escherichia coli↗

PubMed2026

Dynamic metabolic modelling of ATP allocation during viral infection.

Viral pathogens, like SARS-CoV-2, hijack the host's macromolecular production machinery, imposing an energetic burden that is distributed across cellular metabolism. To explore the dynamic metabolic tension between the host's survival and viral replication, we developed a computational framework that uses genome-scale models to perform dynamic flux balance analysis of human cell metabolism during virus infections. Relative to previous models, our framework addresses the physiology of viral infections of non-proliferating host cells through two new features. First, by incorporating the lipid content of SARS-CoV-2 biomass, we discovered activation of previously overlooked pathways giving rise to new predictions of possible drug targets. Furthermore, we introduce a dynamic model that simulates the partitioning of resources between the virus and the host cell, capturing the extent to which the competition depletes the human cells from essential ATP. By incorporating viral dynamics into our COMETS framework for spatio-temporal modelling of metabolism, we provide a mechanistic, dynamic and generalizable starting point for bridging systems biology modelling with viral pathogenesis. This framework could be extended to broadly incorporate phage dynamics in microbial systems and ecosystems.

Humans↗

PubMed2025

Biophysical metabolic modeling of complex bacterial colony morphology.

Microbial colony growth is shaped by the physics of biomass propagation and nutrient diffusion and by the metabolic reactions that organisms activate as a function of the surrounding environment. While microbial colonies have been explored using minimal models of growth and motility, full integration of biomass propagation and metabolism is still lacking. Here, building upon our framework for computation of microbial ecosystems in time and space (COMETS), we combine dynamic flux balance modeling of metabolism with collective biomass propagation and demographic fluctuations to provide nuanced simulations of E. coli colonies. Simulations produced realistic colony morphology, consistent with our experiments. They characterize the transition between smooth and furcated colonies and the decay of genetic diversity. Furthermore, we demonstrate that under certain conditions, biomass can accumulate along "metabolic rings" that are reminiscent of coffee-stain rings but have a completely different origin. Our approach is a key step toward predictive microbial ecosystems modeling. A record of this paper's transparent peer review process is included in the supplemental information.

Models, Biological↗

PubMed1977

Material balance analysis of trichlorofluoromethane and carbon tetrachloride in the atmosphere.

Using the historical worldwide emission and monitoring data on trichlorofluormethane, a transfer constant (0.03 yr-1) was evaluated for the movement of the gas from the troposphere to the stratosphere. The movement between the northern and southern troposphere was estimated from literature data on other gases to be 0.6 yr-1. The flux between the ocean and air was calculated using water solubility and vapor pressure measurements. These transfer constants were then combined in a dynamic material balance model which has the capability of predicting furture trends. The procedure was then applied to a similar set of data for carbon tetrachloride. The agreement between the calculated atmospheric and water concentration for carbon tetrachloride was within 20% of the actual experimental observation thus lending credence to this type of budgetary analysis.

Air Pollutants↗

PubMed2026

Antarctic Peninsula soil carbon stock and efflux: A complex interplay of soil properties and heavy metals.

This study establishes a quantitative framework for understanding surface soil carbon dynamics and ecosystem connectivity in Fildes Peninsula and Ardley Island, King George Island, South Shetland Islands, Antarctic Peninsula. The mean soil organic carbon (SOC) stock across all study sites was 1.10 ± 1.93 kg C/m². Restricting net carbon balance analysis to Fildes Peninsula, where soil respiration (Rs) data were available, yielded a site-specific SOC stock of 0.45 ± 0.45 kg C/m². Scaling Rs to a realistic 120-day active season and assuming stable SOC stocks resulted in estimated annual carbon loss of 15 g C/(m2·yr), equivalent to 3.3 % of standing SOC. Comprehensive sensitivity analyses spanning plausible winter respiration (0 %-20 % of summer rates) and annual change in SOC stocks (-1 %-2 %) consistently supported a net carbon sink, with turnover rates constrained to 3.3 %/yr-4.7 %/yr. Principal component analysis showed that ornithogenic processes as the dominant control on SOC, total nitrogen (TN), zinc (Zn), copper (Cu), and cadmium (Cd) provide a clear multivariate signature of marine-derived nutrient, while Pb was decoupled from this gradient and associated instead with fine-particle size controls. These results reveal dual but independent drivers of soil metal enrichment in this region. Despite their limited spatial extent, ornithogenic soils store disproportionately large carbon pools. Overall, this integrated analysis reveals how marine-terrestrial subsidies regulate Antarctic carbon cycling and provides a quantitative and reproducible framework for assessing carbon dynamics under ongoing climate change.

Antarctic Regions↗

PubMed2026

Microbial succession and assembly shaped by sulfur, spatial partitioning, and water flow in a volcanic acidic river of northern Patagonia.

Extreme acidic environments represent natural laboratories for investigating the mechanisms of microbial community assembly, yet the ecological processes structuring these communities remain incompletely understood. Here, we investigate how spatial partitioning, hydrodynamics, and colonization history shape microbial succession in a unique sulfur-rich, acidic river of volcanic origin in northern Patagonia. We combined 16S rRNA gene profiling and shotgun metagenomics with a multi-scale experimental framework encompassing water column fractionation and colonization assays under native and controlled conditions. Microbial diversity was strongly influenced by spatial fractionation, with free-living communities exhibiting higher richness and temporal variability than particle-associated assemblages. Water flow modulated community structure, increasing evenness in free-living fractions under high-flow conditions, but had limited impact on particle-attached communities. Colonization of sulfur-beads followed a structured successional trajectory, with autotrophic sulfur oxidizers dominating early stages and heterotrophs adapted to biofilm lifestyles increasing over time. Ex situ recolonization assays revealed strong priority effects, with initial colonizers determining successional trajectories. Turnover analyses revealed that the balance among stochastic and deterministic assembly processes shifted across communities with pronounced stochasticity in the water column and flow-dependent effects in free-living communities, while biofilm associated communities on sulfur-beads exhibited stronger contribution of deterministic selection. These ecological patterns were mirrored by functional differentiation, with gene enrichment analyses revealing adaptive signatures of substrate attachment and resource acquisition. By integrating fine-scale environmental variation with colonization dynamics, this study reveals how microscale habitat structure and temporal fluxes jointly modulate microbial community assembly rules, offering a nuanced framework to dissect ecological processes in extreme systems.

Sulfur↗