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All sourcesNASA NTRSDOE OSTI
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 OSTI2025

Apple Bitter Rot: Biology, Ecology, Omics, Virulence Factors, and Management of Causal Colletotrichum Species

ABSTRACT Apple bitter rot is caused by various Colletotrichum spp. that threaten apple production globally resulting in millions of dollars in damage annually. The fungus causes a decline in fruit quality and yield, eventually rotting the fruit and rendering it inedible. The pathogen is difficult to keep out of orchards because of its broad host range and transmissibility by rain splash and insects. Once the disease manifests, pathogen identification is difficult due to evolving taxonomy and similar morphology between species. Current management strategies are threatened by an increase in fungicide resistance and regulations on many multisite fungicides, leading to a pressing need for new management options for control. This review aims to summarise the most current knowledge regarding the biology, virulence factors, ecology, omics and emerging management strategies for Colletotrichum species that cause apple bitter rot. Taxonomy Colletotrichum species—Domain Eukaryota, Kingdom Fungi, Phylum Ascomycota, Class Sordariomycetes, Order Glomerellales, Family Glomerellaceae, Genus Colletotrichum . Biology Hemibiotrophic pathogen with a wide host range that establishes a biotrophic interaction where it penetrates host plants using appressoria followed by a switch to necrotrophy causing rot symptoms. Toxins Cercosporin, colletotrichins, colletotric acid, ferricrocin. Host Range The host range varies by species but largely occurs on dicotyledonous plants and is less prevalent on monocots as well as gymnosperms, ferns, mosses and animals (e.g., insects). Disease Symptoms Symptoms often manifest as flat to sunken necrotic areas on fruit. Lesions on leaves and fruit can have concentric rings with abundant pathogen sporulation. Disease Control Colletotrichum spp. are primarily managed by single‐site quinone outside inhibitor (Qol), methyl benzimidazole carbamate (MBC), demethylation inhibitor (DMI) fungicides, and multisite dithiocarbamate and phthalimide fungicides. Susceptibility may vary with species, strain specificity, or geographic region. Other management options include clean stock production, cultural practices, resistance breeding, and biological control through the introduction of protective or competing microorganisms.

Boeckman, Nathanial J. [Plant Pathology Laboratory↗
DOE OSTI2024

Biological Parts Search Portal (BioParts) v1.0.0

BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.

Plahar, Hector↗
DOE OSTI2025

Optimal Transport as a Tool for Scientific Discovery in Radiation Biology

This report summarizes findings from research conducted for the “Exploration of the Poten tial for Artificial Intelligence and Machine Learning to Advance Low-Dose Radiation Biology Re search” (RadBio-AI) program, supported by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research, under Awards KP1601011/FWP CC121 and KP1601017/FWP CC121. The research reported here was undertaken in an effort to assess the potential of optimal measure transport methods as components within the larger scope of a com putational framework envisioned to support research in the radiation biology domain. Within this effort, our interest centered on enabling a unified generic framework where probabilistic modeling, inference, and statistical learning can be carried out for a wide range of data distributions. As described next in Section 1 (and in more detail in our original publication), optimal measure transport offers the possibility of such unified approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Physicochemical and biological characterization of a bispecific antibody in a CrossMab/KIH format that targets EGFR and VEGF-A

Introduction Bispecific antibodies (BsAbs) are a class of antibody therapeutics engineered in various molecular formats to bind two distinct antigens and potentially mediate multiple biological effects. These molecular formats are tailored to mediate specific mechanisms of action and possess unique physicochemical and biological properties that are necessary to assure product quality. In ovarian cancer (OC), both EGFR- and VEGF-A-mediated signaling pathways are often upregulated and cooperate to promote tumor growth and angiogenesis. Thus, inhibiting of EGFR- and VEGF-A pathways with a BsAb may provide synergistic anti-tumor activity. Methods Using publicly available sequences and applying immunoglobulin domain crossover (CrossMab) and knobs-into-holes (KIH) technologies, we generated a BsAb to simultaneously bind EGFR and VEGF-A (designated as anti-EGFR/VEGF-A BsAb). This BsAb served as a model for physiochemical and biological characterization of quality attributes that would be critical for the BsAb’s mechanisms of action. Our goal was to gain fundamental insights into BsAbs designed to target a receptor with one arm and a soluble ligand with the other, to support bioassay development and inform quality control strategies. Results Our data demonstrated that the CrossMab/KIH platform successfully produced a correctly assembled BsAb during cell culture. Characterization confirmed that the anti-EGFR/VEGF-A BsAb bound both EGFR and VEGF-A with comparable activity and affinity to the respective parental monoclonal antibodies. Functionally, the BsAb disrupted both EGF/EGFR and VEGF-A/VEGFR2 signaling pathways in OC and human umbilical vein endothelial cell (HUVEC) models. Furthermore, the BsAb effectively blocked angiogenic signaling driven by VEGF-A secreted from OC cells in a paracrine manner. Discussion Based on the combinatorial mechanism of action and our characterization findings, we concluded that two or more bioassays may be needed to accurately assess the activity of both arms of this type of BsAb.

Immunology↗
DOE OSTI2024

Reliability, biological variability, and accuracy of multi-frequency bioelectrical impedance analysis for measuring body composition components

Introduction Bioelectrical impedance analysis (BIA) systems are gaining popularity for use in research and fitness assessments as the technology improves and becomes more affordable and easier to use. Multifrequency BIA (MF-BIA) may improve accuracy and precision using octopolar contacts for segmental analyses. Purpose Evaluate reliability, biological variability, and accuracy of component measures (total body water, mass, and composition) of commercially available MF-BIA system (InBody 770, Cerritos, California, USA). Methods Fourteen healthy military-age adults were assessed by MF-BIA in duplicate on five laboratory visits across 3 weeks (10 measures each). Participants were evaluated at the same time of day after refraining from strenuous exercise (> 48 h), alcohol consumption (> 24 h), and caffeine, nicotine, and food (> 10 h). Systematic error (test–retest reliability) and biological variability (day-to-day reliability) were summarized by intraclass correlation coefficient (ICC) values determined for body mass (fat, fat-free, total) and body water (extracellular, intracellular, total). Body composition measurements derived from BIA on the second visit were also tested for accuracy compared to dual-energy x-ray absorptiometry (DXA). Results Test–retest reliability was very high for all measurements of whole-body water and mass (ICC ≥ 0.999) and high for regional body water and mass (ICC 0.973–1.000). Biological variability was observable with very minor differences between tests (same day) for total and regional body water (0.0–0.2 L) and total and regional body mass measurements (0.0–0.2 kg); while between day differences were slightly higher (0.0–0.5 L and 0.1–0.7 kg). Compared to DXA, the MF-BIA whole-body measures showed an offset in %BF (Bias −4.0 ± 2.8%; Standard error of the estimate (SEE), 2.6%), an overprediction for total body fat-free mass (Bias 2.8 ± 2.1 kg; SEE 2.2 kg) and an underprediction of total body fat mass (Bias −2.9 ± 2.0 kg; SEE 1.9 kg). Conclusion Under controlled conditions with fit and healthy men and women, this MF-BIA system has high methodological reliability and demonstrates stable day-to-day measurements of major body composition components. Previously reported ~3% body fat offset compared to criterion methods was again confirmed. Precision of the InBody 770 shows consistency and supports further testing of this specific device as a new military standards method and suitability across a wider range of %BF.

Nutrition & Dietetics↗
DOE OSTI2025

Backpropagation-based learning with local derivative approximation and memory replay in biologically plausible neural systems

When learning, the brain modifies individual synaptic connections to reach a desired behavior. Animal and human brains have been shown to be incredibly capable of learning complex and varied functions across a wide variety of tasks. In recent years, artificial neural networks, inspired by human and animal brains, have shown great capabilities in learning a wide variety of difficult tasks. However, artificial neural networks primarily teach themselves through the use of backpropagation, a learning method which has no clear analogue within the brain. Additionally, Artificial Neural Networks primarily use continuous activation functions, which differ significantly from the spiking neuronal behavior present in the brain. In this paper, we discuss and demonstrate a biologically plausible learning method that approximates backpropagation through two techniques on Spiking Neural Networks. First, we show that the local temporal derivatives that are necessary for backpropagation can be approximately recovered through reconstruction using spike timings. Second, we show that through learning during a sleep phase, inspired by neuroscience research into memory replay, the localized parallel feedback path can learn to approximate the derivative through the forward path weight matrix, thus solving the weight transport problem. Lastly, we demonstrate that the combination of these two methods can approach or exceed the accuracy of backpropagation-based methods for a variety of neuromorphic vision tasks while maintaining biological plausibility.

42 ENGINEERING↗
DOE OSTI2025

The development and evolution of biological AMS at Livermore: a perspective

Biological accelerator mass spectrometry (AMS) provides ultrasensitive carbon-14 isotopic analysis enabling a deeper understanding of human health concerns by enabling quantification of pharmacokinetics and other molecular endpoints directly in humans. It enables environmentally and human relevant studies of metabolic pathways through the use of very low concentrations of labeled metabolic substrates in cells and organisms. Here, we discuss why AMS is an important tool for the biosciences, the development and evolution of biological AMS at Livermore and discuss technical refinements that will improve the efficiency of operation for the measurement of ultra-trace levels of 14 C, which, long term, will enable greater ease of use and sample throughput.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Data for Production of a δ-Lactam from Glucose through Integrating Biological and Chemical Catalysis

We present a new strategy for the production of a δ-lactam from glucose that integrates biological production of triacetic acid lactone (TAL, 4-hydroxy-6-methyl-2H-2-one) with catalytic transformation of TAL into 6-methylpiperidin-2-one (MPO) through metabolic engineering, isomerization, amination, and catalytic hydrogenation/hydrogenolysis. We developed a sustainable and antibiotic-free fed-batch fermentation using genetically modified Rhodotorula toruloides IFO0880. This process achieved a yield of 2-hydroxy-6-methyl-4H-pyran-4-one (2H4P) at 0.05 g/g of glucose, corresponding to a 9.9 g/L titer. By adjusting the pH of the fermentation broth to 2, 2H4P was quantitatively converted into TAL. The TAL in the fermentation broth was directly converted by aminolysis into 4-hydroxy-6-methylpyridin-2(1H)-one (HMPO), which achieved an 18.5% yield with 94.3% purity. The HMPO yield was lower in the fermentation broth than in a clean feedstock (32.2%), suggesting that the biological impurities are inhibitors in this reaction. Further investigation revealed that lower pH levels and reduced TAL concentrations in the fermentation broth significantly decreased HMPO yields. Subsequently, the precipitated HMPO was filtered and dried and then subjected to the final catalytic conversion in H2O solvent, achieving a MPO yield of 91.8%. This integrated approach demonstrated the direct use of TAL in the filtered aqueous fermentation broth without the need to isolate TAL.

Catalysis↗
DOE OSTI2026

Acetate-based biological platforms: Bridging carbon dioxide utilization and high-value bioproduct production in oleaginous yeasts

Acetate is emerging as a promising two-carbon substrate in the circular bioeconomy, bridging the gap between single-carbon sources and high-value biofuels and bioproducts. This review examines the key pathways for acetate production, including the electrochemical reduction of carbon dioxide, syngas fermentation, and biological acetogenesis. It focuses on acetate metabolism in oleaginous yeasts, such as Yarrowia lipolytica and Rhodotorula toruloides, which efficiently convert acetate-derived acetyl-CoA units into diverse bioproducts such as lipids, fatty alcohols, triacetic acid lactone, and carotenoids. Recent advances in metabolic engineering, transcriptomics, and metabolic flux analysis have improved the understanding of acetate assimilation in these organisms, thereby increasing their potential for industrial applications. In addition, the feasibility of a biological gas-to-liquid platform that utilizes acetate as a central intermediate for scalable biomanufacturing is discussed. Integrating acetate utilization with sustainable production strategies offers a promising path to advance the bio-based economy. Using acetate as a versatile metabolic intermediate enables the conversion of industrial emissions into biofuels and bioproducts while avoiding the energetic and toxicity constraints associated with direct fermentation of gaseous substrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Plant synthetic biology as a tool to help eliminate hidden hunger

Agricultural systems are under increasing pressure from declining environmental conditions, a growing population, and changes in consumer preferences, resulting in widespread malnutrition-related illnesses. Improving plant nutritional content through biotechnology techniques such as synthetic biology is a promising strategy to help combat hidden hunger caused by the lack of affordable and healthy foods in human diets. Production of compounds usually found in animal-rich diets, such as vitamin D or omega-3 fatty acids, has been recently demonstrated in planta. Here, we review recent biotechnological approaches to biofortifying plants with vitamins, minerals, and other metabolites, and summarise synthetic biology advances that offer the opportunity to build on these early biofortification efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Optical 14 C Tracing for Biological and Pharmaceutical Applications Using Two-Color Cavity Ringdown Spectroscopy

Laser-based 14 C quantitation has been proposed as a more affordable, higher-throughput, table-top alternative to accelerator mass spectrometry (AMS). Here, we demonstrate the feasibility of a mid-IR 14 C detector based on two-color cavity ringdown spectroscopy (2C-CRDS) for low-level 14 C isotope tracing in biological studies. The 2C-CRDS technique quantifies the sample 14 C content by measuring the 14 CO 2 absorption signals from the combusted samples with mid-IR lasers. With 2C-CRDS, we previously demonstrated the most sensitive and accurate optical measurements of 14 CO 2 . The current detection sensitivity and quantitation accuracy of the instrument, at a few parts per quadrillion (where a quadrillion = 10 15 ) 14 C/C mole fraction, is competitive against AMS. Here, by applying the 2C-CRDS 14 C sensor to two applications relevant to 14 C-labeled biochemical analysis and pharmaceutical studies, we demonstrate sub-fCi level (where 1 fCi = 10 –15 Ci) quantitation of sample 14 C activity, with a minimum sample-size requirement of 3 mg of carbon. The current measurement throughput, ~25 min/sample, is largely limited by the sampling efficiency of the online combustion and CO 2 processing interface to the 2C-CRDS instrument. The possibility of a significantly improved measurement throughput of a few minutes per sample is suggested by the results of a flow-through 14 CO 2 sampling scheme. In conclusion, this improved measurement efficiency, combined with the relatively low cost and compact size of a 2C-CRDS sensor, could potentially revolutionize high-sensitivity 14 C tracing in biological, pharmaceutical, and clinical studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Production of a δ-Lactam from Glucose through Integrating Biological and Chemical Catalysis

We present a new strategy for the production of a δ-lactam from glucose that integrates biological production of triacetic acid lactone (TAL, 4-hydroxy-6-methyl-2H-2-one) with catalytic transformation of TAL into 6-methylpiperidin-2-one (MPO) through metabolic engineering, isomerization, amination, and catalytic hydrogenation/hydrogenolysis. We developed a sustainable and antibiotic-free fed-batch fermentation using genetically modified Rhodotorula toruloides IFO0880. This process achieved a yield of 2-hydroxy-6-methyl-4H-pyran-4-one (2H4P) at 0.05 g/g of glucose, corresponding to a 9.9 g/L titer. By adjusting the pH of the fermentation broth to 2, 2H4P was quantitatively converted into TAL. The TAL in the fermentation broth was directly converted by aminolysis into 4-hydroxy-6-methylpyridin-2(1H)-one (HMPO), which achieved an 18.5% yield with 94.3% purity. The HMPO yield was lower in the fermentation broth than in a clean feedstock (32.2%), suggesting that the biological impurities are inhibitors in this reaction. Further investigation revealed that lower pH levels and reduced TAL concentrations in the fermentation broth significantly decreased HMPO yields. Subsequently, the precipitated HMPO was filtered and dried and then subjected to the final catalytic conversion in H2O solvent, achieving a MPO yield of 91.8%. Furthermore, this integrated approach demonstrated the direct use of TAL in the filtered aqueous fermentation broth without the need to isolate TAL.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Limits on the evolutionary rates of biological traits

Abstract This paper focuses on the maximum speed at which biological evolution can occur. I derive inequalities that limit the rate of evolutionary processes driven by natural selection, mutations, or genetic drift. These rate limits link the variability in a population to evolutionary rates. In particular, high variances in the fitness of a population and of a quantitative trait allow for fast changes in the trait’s average. In contrast, low variability makes a trait less susceptible to random changes due to genetic drift. The results in this article generalize Fisher’s fundamental theorem of natural selection to dynamics that allow for mutations and genetic drift, via trade-off relations that constrain the evolutionary rates of arbitrary traits. The rate limits can be used to probe questions in various evolutionary biology and ecology settings. They apply, for instance, to trait dynamics within or across species or to the evolution of bacteria strains. They apply to any quantitative trait, e.g., from species’ weights to the lengths of DNA strands.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Spatial modeling algorithms for reactions and transport in biological cells

Biological cells rely on precise spatiotemporal coordination of biochemical reactions to control their functions. Such cell signaling networks have been a common focus for mathematical models, but they remain challenging to simulate, particularly in realistic cell geometries. Here we present Spatial Modeling Algorithms for Reactions and Transport (SMART), a software package that takes in high-level user specifications about cell signaling networks and then assembles and solves the associated mathematical systems. SMART uses state-of-the-art finite element analysis, via the FEniCS Project software, to efficiently and accurately resolve cell signaling events over discretized cellular and subcellular geometries. We demonstrate its application to several different biological systems, including yes-associated protein (YAP)/PDZ-binding motif (TAZ) mechanotransduction, calcium signaling in neurons and cardiomyocytes, and ATP generation in mitochondria. Throughout, we utilize experimentally derived realistic cellular geometries represented by well-conditioned tetrahedral meshes. These scenarios demonstrate the applicability, flexibility, accuracy and efficiency of SMART across a range of temporal and spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Psychosocial experiences are associated with human brain mitochondrial biology

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these “mind-mitochondria” associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Phenylpropanoid methyl esterase unlocks catabolism of aromatic biological nitrification inhibitors

Microbial nitrification of fertilizers represents is a significant global source of greenhouse gas emissions. This process increases emissions, fosters toxic algal blooms, and raises crop production costs. Some plants naturally release biological nitrification inhibitors to suppress ammonium-oxidizing microbes and reduce nitrification. Engineering nitrification inhibitor production into food and bioenergy crops via synthetic biology offers a promising mitigation strategy, but its success depends on addressing gaps in our understanding of inhibitor degradation in soil. This study begins to fill this gap by identifying a previously unknown microbial pathway for degrading phenylpropanoid methyl esters, a key class of aromatic nitrification inhibitors. Using transcriptomics and high-throughput functional genomics, we discovered genes essential for phenylpropanoid methyl ester degradation. Genetic and biochemical analyses revealed two novel enzymes, including a newly identified phenylpropanoid methyl esterase, that direct phenylpropanoid methyl esters into known metabolic pathways. Importantly, transferring these genes into bacteria capable of metabolizing other phenylpropanoids enabled them to use the methyl esters as a carbon source. This work provides critical insights into microbial nitrification inhibitor degradation, a poorly understood element of the nitrification cycle.

Genetic Engineering↗
DOE OSTI2024

A science-driven approach to optimize the design for a biological small-angle neutron scattering instrument

Biological small-angle neutron scattering (SANS) instruments facilitate critical analysis of the structure and dynamics of complex biological systems. However, with the growth of experimental demands and the advances in optical systems design, a new neutron optical concept is necessary to overcome the limitations of current instruments. This work presents an approach to include experimental objectives ( i.e. the science to be supported by a specific neutron scattering instrument) in the optimization of the neutron optical concept. The approach for a proposed SANS instrument at the Second Target Station of the Spallation Neutron Source at Oak Ridge National Laboratory, USA, is presented here. Further, the instrument is simulated with the McStas software package. The optimization process is driven by an evolutionary algorithm using McStas output data, which are processed to calculate an objective function designed to quantify the expected performance of the simulated neutron optical configuration for the intended purpose. Each McStas simulation covers the complete instrument, from source to detector, including realistic sample scattering functions. This approach effectively navigates a high-dimensional parameter space that is otherwise intractable; it allows the design of next-generation SANS instruments to address specific scientific cases and has the potential to increase instrument performance compared with traditional design approaches.

47 OTHER INSTRUMENTATION↗