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Results for “multicellular model”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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9 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Cadmium alters whole animal ionome and promotes the re-distribution of iron in intestinal cells of Caenorhabditis elegans

The chronic exposure of humans to the toxic metal cadmium (Cd), either occupational or from food and air, causes various diseases, including neurodegenerative conditions, dysfunction of vital organs, and cancer. While the toxicology of Cd and its effect on the homeostasis of biologically relevant elements is increasingly recognized, the spatial distribution of Cd and other elements in Cd toxicity-caused diseases is still poorly understood. Here, we use Caenorhabditis elegans as a non-mammalian multicellular model system to determine the distribution of Cd at the tissue and cellular resolution and its effect on the internal levels and the distribution of biologically relevant elements. Using inductively coupled plasma-mass spectrophotometry (ICP-MS), we show that exposure of worms to Cd not only led to its internal accumulation but also significantly altered the C. elegans ionome. Specifically, Cd treatment was associated with increased levels of toxic elements such as arsenic (As) and rubidium (Rb) and a decreased accumulation of essential elements such as zinc (Zn), copper (Cu), manganese (Mn), calcium (Ca), cobalt (Co) and, depending on the Cd-concentration used in the assay, iron (Fe). We regarded these changes as an ionomic signature of Cd toxicity in C. elegans. We also show that supplementing nematode growth medium with Zn but not Cu, rescues Cd toxicity and that mutant worms lacking Zn transporters CDF-1 or SUR-7, or both are more sensitive to Cd toxicity. Finally, using synchrotron X-Ray fluorescence Microscopy (XRF), we showed that Cd significantly alters the spatial distribution of mineral elements. The effect of Cd on the distribution of Fe was particularly striking: while Fe was evenly distributed in intestinal cells of worms grown without Cd, in the presence of Cd, Fe, and Cd co-localized in punctum-like structures in the intestinal cells. Together, this study advances our understanding of the effect of Cd on the accumulation and distribution of biologically relevant elements. Considering that C. elegans possesses the principal tissues and cell types as humans, our data may have important implications for future therapeutic developments aiming to alleviate Cd-related pathologies in humans.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Generative diffusion model surrogates for mechanistic agent-based biological models

Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution. The Cellular-Potts Model (CPM) is a powerful and popular framework for developing and interrogating these models. CPMs become computationally expensive at large space- and time- scales making application and investigation of developed models difficult. Surrogate models may allow for the accelerated evaluation of CPMs of complex biological systems. However, the stochastic nature of these models means each set of parameters may give rise to different model configurations, complicating surrogate model development. In this work, we leverage denoising diffusion probabilistic models (DDPMs) to train a generative AI surrogate of a CPM used to investigate in vitro vasculogenesis. We describe the use of an image classifier to learn the characteristics that define unique areas of a 2-dimensional parameter space. We then apply this classifier to aid in surrogate model selection and verification. Our CPM model surrogate generates model configurations 20,000 timesteps ahead of a reference configuration and demonstrates approximately a 22x reduction in computational time as compared to native code execution. Our work represents a step towards the implementation of DDPMs to develop digital twins of stochastic biological systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

RootSlice —A novel functional-structural model for root anatomical phenotypes

Root anatomy is an important determinant of root metabolic costs, soil exploration, and soil resource capture. Root anatomy varies substantially within and among plant species. RootSlice is a multicellular functional-structural model of root anatomy developed to facilitate the analysis and understanding of root anatomical phenotypes. RootSlice can capture phenotypically accurate root anatomy in three dimensions of different root classes and developmental zones, of both monocotyledonous and dicotyledonous species. Several case studies are presented illustrating the capabilities of the model. For maize nodal roots, the model illustrated the role of vacuole expansion in cell elongation; and confirmed the individual and synergistic role of increasing root cortical aerenchyma and reducing the number of cortical cell files in reducing root metabolic costs. Integration of RootSlice for different root zones as the temporal properties of the nodal roots in the whole-plant and soil model OpenSimRoot/maize enabled the multiscale evaluation of root anatomical phenotypes, highlighting the role of aerenchyma formation in enhancing the utility of cortical cell files for improving plant performance over varying soil nitrogen supply. Such integrative in silico approaches present avenues for exploring the fitness landscape of root anatomical phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Surrogate modeling of Cellular-Potts agent-based models as a segmentation task using the U-Net neural network architecture

The Cellular-Potts model is a powerful and ubiquitous framework for developing computational models for simulating complex multicellular biological systems. Cellular-Potts models (CPMs) are often computationally expensive due to the explicit modeling of interactions among large numbers of individual model agents and diffusive fields described by partial differential equations (PDEs). In this work, we develop a convolutional neural network (CNN) surrogate model using a U-Net architecture that accounts for periodic boundary conditions. We use this model to accelerate the evaluation of a mechanistic CPM previously used to investigate in vitro vasculogenesis. The surrogate model was trained to predict 100 computational steps ahead (Monte-Carlo steps, MCS), accelerating simulation evaluations by a factor of 562 times compared to single-core CPM code execution on CPU. Over short timescales of up to 3 recursive evaluations, or 300 MCS, our model captures the emergent behaviors demonstrated by the original Cellular-Potts model such as vessel sprouting, extension and anastomosis, and contraction of vascular lacunae. This approach demonstrates the potential for deep learning to serve as a step toward efficient surrogate models for CPM simulations, enabling faster evaluation of computationally expensive CPM simulations of biological processes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Building a predictive model for polycyclic aromatic hydrocarbon dosimetry in organotypically cultured human bronchial epithelial cells using benzo[ a ]pyrene

The airway epithelium is a primary route of exposure for inhaled toxicants, and organotypic culture models represent an important advancement for toxicity testing compared to simple in vitro models that may lack metabolic capability and multicellular structure/communication associated with the bronchial epithelium in vivo. A quantitative understanding of chemical dosimetry is key for interpreting and extrapolating study results; however, dosimetry is understudied in organotypic models limiting ability to predict toxicity. We developed a dosimetry model for primary human bronchial epithelial cells (HBECs) cultured at the air-liquid interface (ALI) using benzo[a]pyrene (BAP), a representative polycyclic aromatic hydrocarbon. Dose and time course evaluation of metabolite formation and enzyme activity and expression were utilized to parameterize a cellular dosimetry model to improve the utility of ALI-HBECs for assessing chemical risk. Dosimetry analysis demonstrated absorption of BAP into cells and an increase in Phase 1 and 2 metabolites over time that correlated with regulation of metabolizing enzymes. BAP was cleared from cells by 48 h after exposure, and the primary metabolites generated in ALI-HBECs were BAP-3-phenol, BAP-4,5-dihydrodiol, BAP-7,8-dihydrodiol, BAP-9,10-dihydrodiol, BAP-7,8,9,10-tetrol, BAP-3-phenol-glucuronide, BAP-4,5-dihydrodiol-glucuronide, and BAP-9,10-dihydrodiol-glucuronide. The resulting dosimetry model described BAP and 7,8-dihydrodiol toxicokinetics in ALI-HBECs and suggested active excretion of 7,8-dihydrodiol. Overall, this study demonstrates metabolic competency of ALI-HBECs for BAP metabolism, demonstrates the usefulness of complex in vitro systems for human-relevant toxicity data, and exhibits how in silico models can be utilized for understanding the dosimetry of test compounds to aid in in vitro to human extrapolation of toxicity data for risk assessments.

Benzo[a]pyrene↗
DOE OSTI2023

Evolutionary consequences of nascent multicellular life cycles

A key step in the evolutionary transition to multicellularity is the origin of multicellular groups as biological individuals capable of adaptation. Comparative work, supported by theory, suggests clonal development should facilitate this transition, although this hypothesis has never been tested in a single model system. We evolved 20 replicate populations of otherwise isogenic clonally reproducing ‘snowflake’ yeast (Δace2/∆ace2) and aggregative ‘floc’ yeast (GAL1p::FLO1 /GAL1p::FLO1) with daily selection for rapid growth in liquid media, which favors faster cell division, followed by selection for rapid sedimentation, which favors larger multicellular groups. While both genotypes adapted to this regime, growing faster and having higher survival during the group-selection phase, there was a stark difference in evolutionary dynamics. Aggregative floc yeast obtained nearly all their increased fitness from faster growth, not improved group survival; indicating that selection acted primarily at the level of cells. In contrast, clonal snowflake yeast mainly benefited from higher group-dependent fitness, indicating a shift in the level of Darwinian individuality from cells to groups. Through genome sequencing and mathematical modeling, we show that the genetic bottlenecks in a clonal life cycle also drive much higher rates of genetic drift—a result with complex implications for this evolutionary transition. Our results highlight the central role that early multicellular life cycles play in the process of multicellular adaptation.

Life Sciences & Biomedicine - Other Topics↗
DOE OSTI2026

Sampling Microbial Dynamics in the Salish Sea Estuary: Evaluating Methods to Capture Cyanobacteria and Cyanophage

Introduction: Picocyanobacteria from the genera Prochlorococcus and Synechococcus thrive across the globe in aquatic environments, have relatively small genomes, and have growth dynamics regulated by both viral interactions and abiotic conditions, making them excellent model organisms for exploring host-pathogencoevolution. Methods: We developed and refined methods to sample and sequence cyanobacteria, cyanophages, and measured features of their abiotic environment. Results: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons. Our preferred final protocol from this exploratory effort included a combination of in-line and single vacuum flask filtrations, which reduced filtration processing time by over threefold in some cases compared to other tested methods, such as a fully in-line sequence or in-site filtrations. We successfully extracted an average of approximately 400–1200 ng for all filter fractions, with some variations between kits. Discussion: The protocol described herein can successfully discriminate large-cell eukaryotic organisms, but size fractionation of picocyanobacteria appears to be affected by the presence of free DNA, multicellular structures, and abundant tycheposons.

Salish Sea↗
DOE OSTI2023

Gene loss during a transition to multicellularity

Multicellular evolution is a major transition associated with momentous diversification of multiple lineages and increased developmental complexity. The volvocine algae comprise a valuable system for the study of this transition, as they span from unicellular to undifferentiated and differentiated multicellular morphologies despite their genomes being similar, suggesting multicellular evolution requires few genetic changes to undergo dramatic shifts in developmental complexity. Here, the evolutionary dynamics of six volvocine genomes were examined, where a gradual loss of genes was observed in parallel to the co-option of a few key genes. Protein complexes in the six species exhibited novel interactions, suggesting that gene loss could play a role in evolutionary novelty. This finding was supported by gene network modeling, where gene loss outpaces gene gain in generating novel stable network states. These results suggest gene loss, in addition to gene gain and co-option, may be important for the evolution developmental complexity.

59 BASIC BIOLOGICAL SCIENCES↗