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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Entrainment, Detrainment, and Dilution of Dry and Moist Atmospheric Thermals

Here this study examines the entrainment, detrainment, and dilution of dry and moist (cloud) atmospheric thermals in large-eddy simulations. In a neutrally stable environment (with respect to dry dynamics), moist thermals have an increase in radius R with thermal height z t (α ≡ dR/dz t ) about 4 times smaller compared to dry thermals when density stratification is considered and ~2.4 times smaller without density stratification (i.e., applying the Boussinesq approximation). An analytic expression relating α to several dimensionless parameters is derived from the thermal impulse–circulation relation to clarify the factors impacting α. This expression shows that the difference in buoyancy structure between moist and dry thermals, with buoyancy concentrated in the central cores of moist thermals owing to latent heating, explains their smaller spreading rates. Individual contributions of entrainment and detrainment are analyzed using a direct parcel-based approach in the simulations. Moist thermals have similar fractional detrainment but much smaller fractional entrainment rates compared to dry thermals, consistent with the differences in α. Despite having smaller α, moist thermals are similarly dilute (quantified by a passive tracer) as dry thermals because of their greater mixing efficiency with the environment. Thus, moist thermals are substantially dilute but expand much less in size/volume as they rise compared to dry thermals. The α values for moist thermals in (dry) neutral and statically stable environments are similar, but fractional entrainment and especially detrainment rates are greater in the stable environment. Large detrainment rates are associated with a breakdown of the broader thermal vortex ring structure, especially with low environmental relative humidity, attributed in part to evaporation and buoyancy reversal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Interseasonal Connections between the Timing of the Stratospheric Final Warming and Arctic Sea Ice

Connections across seasons in atmospheric circulation and sea ice have long been sought to advance seasonal prediction. This study presents a link between the springtime stratosphere and Arctic sea ice in summer through autumn. The polar stratospheric vortex dominates the winter stratosphere before breaking down each spring, which is called the stratospheric final warming, as solar radiation returns to the pole. Interannual variability of this breakdown is dynamically driven, leading to different springtime tropospheric and surface circulation patterns. To examine the different impacts of delayed and early final warmings, a multimodel composite was generated from selected CMIP5 models. Additionally, regressions were performed on JRA-55 against an index of springtime polar vortex strength. In both the multimodel composites and reanalysis regressions, significant anomalies in sea ice thickness persist several months following an anomalous timing of the final warming. A later final warming or stronger springtime polar stratospheric vortex leads to negative sea ice thickness anomalies in the East Siberian Sea and positive anomalies in the Beaufort Sea in comparison with an earlier final warming or weaker polar vortex. The spring polar stratospheric vortex is related to spring polar surface circulation patterns. The winds associated with this pattern induce anomalous sea ice motion, moving ice from the East Siberian Sea toward the Beaufort Sea. Reduced sea ice in the East Siberian Sea is linked to anomalous warmth over this region in autumn. Our results suggest that the timing of the stratospheric final warming exerts an influence on the tropospheric circulation and sea ice through autumn, which has implications for seasonal climate prediction.

Kelleher, Michael↗
DOE OSTI2021

Resilience and fault tolerance in high-performance computing for numerical weather and climate prediction

Progress in numerical weather and climate prediction accuracy greatly depends on the growth of the available computing power. As the number of cores in top computing facilities pushes into the millions, increased average frequency of hardware and software failures forces users to review their algorithms and systems in order to protect simulations from breakdown. This report surveys hardware, application-level and algorithm-level resilience approaches of particular relevance to time-critical numerical weather and climate prediction systems. A selection of applicable existing strategies is analysed, featuring interpolation-restart and compressed checkpointing for the numerical schemes, in-memory checkpointing, user-level failure mitigation and backup-based methods for the systems. Numerical examples showcase the performance of the techniques in addressing faults, with particular emphasis on iterative solvers for linear systems, a staple of atmospheric fluid flow solvers. The potential impact of these strategies is discussed in relation to current development of numerical weather prediction algorithms and systems towards the exascale. Trade-offs between performance, efficiency and effectiveness of resiliency strategies are analysed and some recommendations outlined for future developments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Proteome profiling of enriched membrane-associated proteins unraveled a novel sophorose and cello-oligosaccharide transporter in Trichoderma reesei

Trichoderma reesei is an organism extensively used in the bioethanol industry, owing to its capability to produce enzymes capable of breaking down holocellulose into simple sugars. The uptake of carbohydrates generated from cellulose breakdown is crucial to induce the signaling cascade that triggers cellulase production. However, the sugar transporters involved in this process in T. reesei remain poorly identified and characterized. To address this gap, this study used temporal membrane proteomics analysis to identify five known and nine putative sugar transporters that may be involved in cellulose degradation by T. reesei. Docking analysis pointed out potential ligands for the putative sugar transporter Tr44175. Further functional validation of this transporter was carried out in Saccharomyces cerevisiae. The results showed that Tr44175 transports a variety of sugar molecules, including cellobiose, cellotriose, cellotetraose, and sophorose. This study has unveiled a transporter Tr44175 capable of transporting cellobiose, cellotriose, cellotetraose, and sophorose. Our study represents the first inventory of T. reesei sugar transportome once exposed to cellulose, offering promising potential targets for strain engineering in the context of bioethanol production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The SEMA3F-NRP1/NRP2 axis is a key factor in the acquisition of invasive traits in in situ breast ductal carcinoma

A better understanding of ductal carcinoma in situ (DCIS) is urgently needed to identify these preinvasive lesions as distinct clinical entities. Semaphorin 3F (SEMA3F) is a soluble axonal guidance molecule, and its coreceptors Neuropilin 1 (NRP1) and NRP2 are strongly expressed in invasive epithelial BC cells. We utilized two cell line models to represent the progression from a healthy state to the mild-aggressive or ductal carcinoma in situ (DCIS) stage and, ultimately, to invasive cell lines. Additionally, we employed in vivo models and conducted analyses on patient databases to ensure the translational relevance of our results. We revealed SEMA3F as a promoter of invasion during the DCIS-to-invasive ductal carcinoma transition in breast cancer (BC) through the action of NRP1 and NRP2. In epithelial cells, SEMA3F activates epithelialmesenchymal transition, whereas it promotes extracellular matrix degradation and basal membrane and myoepithelial cell layer breakdown. Together with our patient database data, these proof-of-concept results reveal new SEMA3F-mediated mechanisms occurring in the most common preinvasive BC lesion, DCIS, and represent potent and direct activation of its transition to invasion. Moreover, and of clinical and therapeutic relevance, the effects of SEMA3F can be blocked directly through its coreceptors, thus preventing invasion and keeping DCIS lesions in the preinvasive state.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Enhancing anaerobic digestion of lignocellulosic biomass by mechanical cotreatment

Abstract Background The aim of this study was to increase the accessibility and accelerate the breakdown of lignocellulosic biomass to methane in an anaerobic fermentation system by mechanicalcotreatment: milling during fermentation, as an alternative to conventionalpretreatment prior to biological deconstruction. Effluent from a mesophilic anaerobic digester running with unpretreated senescent switchgrass as the predominant carbon source was collected and subjected to ball milling for 0.5, 2, 5 and 10 min. Following this, a batch fermentation test was conducted with this material in triplicate for an additional 18 days with unmilled effluent as the ‘status quo’ control. Results The results indicate 0.5 – 10 min of cotreatment increased sugar solubilization by 5– 13% when compared to the unmilled control, with greater solubilization correlated with increased milling duration. Biogas concentrations ranged from 44% to 55.5% methane with the balance carbon dioxide. The total biogas production was statistically higher than the unmilled control for all treatments with 2 or more minutes of milling (α = 0.1). Cotreatment also decreased mean particle size. Energy consumption measurements of a lab-scale mill indicate that longer durations of milling offer diminishing benefits with respect to additional methane production. Conclusions Cotreatment in anaerobic digestion systems, as demonstrated in this study, provides an alternative approach to conventional pretreatments to increase biogas production from lignocellulosic grassy material.

Biotechnology & Applied Microbiology↗
DOE OSTI2024

Increased triacylglycerol production in Rhodococcus opacus by overexpressing transcriptional regulators

Lignocellulosic biomass is currently underutilized, but it offers promise as a resource for the generation of commercial end-products, such as biofuels, detergents, and other oleochemicals. Rhodococcus opacus PD630 is an oleaginous, Gram-positive bacterium with an exceptional ability to utilize recalcitrant aromatic lignin breakdown products to produce lipid molecules such as triacylglycerols (TAGs), which are an important biofuel precursor. Lipid carbon storage molecules accumulate only under growth-limiting low nitrogen conditions, representing a significant challenge toward using bacterial biorefineries for fuel precursor production. In this work, we screened overexpression of 27 native transcriptional regulators for their abilities to improve lipid accumulation under nitrogen-rich conditions, resulting in three strains that accumulate increased lipids, unconstrained by nitrogen availability when grown in phenol or glucose. Transcriptomic analyses revealed that the best strain (#13) enhanced FA production via activation of the β-ketoadipate pathway. Gene deletion experiments confirm that lipid accumulation in nitrogen-replete conditions requires reprogramming of phenylalanine metabolism. By generating mutants decoupling carbon storage from low nitrogen environments, we move closer toward optimizing R. opacus for efficient bioproduction on lignocellulosic biomass.

09 BIOMASS FUELS↗
DOE OSTI2022

Metagenomics-resolved genomics provides novel insights into chitin turnover, metabolic specialization, and niche partitioning in the octocoral microbiome

Abstract Background The role of bacterial symbionts that populate octocorals (Cnidaria, Octocorallia) is still poorly understood. To shed light on their metabolic capacities, we examined 66 high-quality metagenome-assembled genomes (MAGs) spanning 30 prokaryotic species, retrieved from microbial metagenomes of three octocoral species and seawater. Results Symbionts of healthy octocorals were affiliated with the taxa Endozoicomonadaceae , Candidatus Thioglobaceae , Metamycoplasmataceae , unclassified Pseudomonadales , Rhodobacteraceae , unclassified Alphaproteobacteria and Ca. Rhabdochlamydiaceae . Phylogenomics inference revealed that the Endozoicomonadaceae symbionts uncovered here represent two species of a novel genus unique to temperate octocorals, here denoted Ca. Gorgonimonas eunicellae and Ca. Gorgonimonas leptogorgiae . Their genomes revealed metabolic capacities to thrive under suboxic conditions and high gene copy numbers of serine-threonine protein kinases, type 3-secretion system, type-4 pili, and ankyrin-repeat proteins, suggesting excellent capabilities to colonize, aggregate, and persist inside their host. Contrarily, MAGs obtained from seawater frequently lacked symbiosis-related genes. All Endozoicomonadaceae symbionts harbored endo-chitinase and chitin-binging protein-encoding genes, indicating that they can hydrolyze the most abundant polysaccharide in the oceans. Other symbionts, including Metamycoplasmataceae and Ca. Thioglobaceae , may assimilate the smaller chitin oligosaccharides resulting from chitin breakdown and engage in chitin deacetylation, respectively, suggesting possibilities for substrate cross-feeding and a role for the coral microbiome in overall chitin turnover. We also observed sharp differences in secondary metabolite production potential between symbiotic lineages. Specific Proteobacteria taxa may specialize in chemical defense and guard other symbionts, including Endozoicomonadaceae , which lack such capacity. Conclusion This is the first study to recover MAGs from dominant symbionts of octocorals, including those of so-far unculturable Endozoicomonadaceae , Ca. Thioglobaceae and Metamycoplasmataceae symbionts. We identify a thus-far unanticipated, global role for Endozoicomonadaceae symbionts of corals in the processing of chitin, the most abundant natural polysaccharide in the oceans and major component of the natural zoo- and phytoplankton feed of octocorals. We conclude that niche partitioning, metabolic specialization, and adaptation to low oxygen conditions among prokaryotic symbionts likely contribute to the plasticity and adaptability of the octocoral holobiont in changing marine environments. These findings bear implications not only for our understanding of symbiotic relationships in the marine realm but also for the functioning of benthic ecosystems at large.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fine scale transitions of the microbiota and metabolome along the gastrointestinal tract of herbivorous fishes

Abstract Background Gut microorganisms aid in the digestion of food by providing exogenous metabolic pathways to break down organic compounds. An integration of longitudinal microbial and chemical data is necessary to illuminate how gut microorganisms supplement the energetic and nutritional requirements of animals. Although mammalian gut systems are well-studied in this capacity, the role of microbes in the breakdown and utilization of recalcitrant marine macroalgae in herbivorous fish is relatively understudied and an emerging priority for bioproduct extraction. Here we use a comprehensive survey of the marine herbivorous fish gut microbial ecosystem via parallel 16S rRNA gene amplicon profiling (microbiota) and untargeted tandem mass spectrometry (metabolomes) to demonstrate consistent transitions among 8 gut subsections across five fish of the genus of Kyphosus . Results Integration of microbial phylogenetic and chemical diversity data reveals that microbial communities and metabolomes covaried and differentiated continuously from stomach to hindgut, with the midgut containing multiple distinct and previously uncharacterized microenvironments and a distinct hindgut community dominated by obligate anaerobes. This differentiation was driven primarily by anaerobic gut endosymbionts of the classes Bacteroidia and Clostridia changing in concert with bile acids, small peptides, and phospholipids: bile acid deconjugation associated with early midgut microbiota, small peptide production associated with midgut microbiota, and phospholipid production associated with hindgut microbiota. Conclusions The combination of microbial and untargeted metabolomic data at high spatial resolution provides a new view of the diverse fish gut microenvironment and serves as a foundation to understand functional partitioning of microbial activities that contribute to the digestion of complex macroalgae in herbivorous marine fish.

Sparagon, Wesley J. (ORCID:0000000296274174)↗
DOE OSTI2025

Dataset for manuscript "Equipartition and the temperature of maximum density of TIP4P/2005 water"

We simulate TIP4P/2005 water in the temperature range of 257 K to 318 K with time-steps 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density-temperature behavior obtained using 0.25 or 0.50 fs are in excellent agreement with each other but differ from those obtained using time-steps that have been shown earlier to lead to a breakdown of equipartition. The temperature of maximum density (TMD) is 277.15 K with time-step 0.25 or 0.50 fs, but is shifted to progressively lower values for longer time-steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water-water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid-vapor phase envelope. We present a simple physically transparent reasoning to highlight the separation of the time-scales between translational and rotational motion. We also develop a metric, Chi, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating Chi is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time-steps (less than or equal to 0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct-ensemble sampling is fundamental to ensure reproducibility across codes and simulation alogrithms. The included dataset provides the raw data used in the preparation of the graphs noted in the manuscript.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Core Design Optimization of the Westinghouse Lead Fast Reactor

Westinghouse is pursuing an advanced Nuclear Power Plant design based on Lead Fast Reactor (LFR) technology for global commercialization. To achieve an optimal combination of key attributes, such as safety, sustainability, and economic competitiveness, Westinghouse and ANL partnered in developing and applying a formalized core design optimization strategy. An LFR analysis workflow was developed to automate a suite of reactor physics, fuels performance, safety, and economics simulations on a selected LFR concept. The workflow streamlines analysis of a wide range of LFR designs with different dimensions and fuel types to assess their viability and economic performance, significantly reducing human processing time and risks of processing errors. The LFR optimization exercise was defined, resulting in selection of the design constraints (geometric, neutronics, thermo-mechanical, safety, thermal-hydraulics, and economics) and performance metrics researched (minimization of both the fuels LCOE and the first core inventory cost). A total of 14 varied design parameters were considered, including assembly dimensions, coolant temperature, and enrichment distribution throughout the core. The LFR analysis workflow was connected to DAKOTA for sensitivity and optimization analyses. Due to the extremely large size of the potential LFR optimization solution space relative to the computing time required to characterize one LFR solution, a multi-stage optimization approach was proposed to breakdown the problem into several stages with more reasonable sizes. This optimization approach enabled finding various viable core solutions with different cost tradeoffs that were considered by Westinghouse and justify selection of a smaller core with multi-batch 2-year cycle length.

Stauff, Nicolas E.↗
DOE OSTI2021

Emissions in short-gated ns/ps/fs-LIBS for fuel-to-air ratio measurements in methane-air flames

A study of short-gated 10 nanosecond (ns), 100 picosecond (ps), and 100 femtosecond (fs) laser induced breakdown spectroscopy (LIBS) was conducted for fuel-to-air ratio (FAR) measurements in an atmospheric Hencken flame. The intent of the work is to understand which emission lines are available near the optical range in each pulse width regime and which emission ratios may be favorable for generating equivalence ratio calibration curves. The emission spectra in the range of 550–800 nm for ns-LIBS and ps-LIBS are mostly similar with slightly elevated atomic oxygen lines by ps-LIBS. Spectra from fs-LIBS show the lowest continuum background and prominent individual atomic lines, though have significantly weaker ionic emission from nitrogen. A qualitative explanation based on assumed local thermodynamic equilibrium and electron temperatures calculated by the N I I ( 565 n m ) and N I I ( 594 n m ) emissions is presented. In studying line emission ratios for FAR calculation, it is found that H α <#comment/> ( 656 n m ) / N I I ( 568 n m ) is best for FAR measurements with ns-LIBS and remains viable for ps-LIBS, while H α <#comment/> ( 656 n m ) / O I ( 777 n m ) is optimal for the ps-LIBS and fs-LIBS cases. Due to low continuum background and short time delay for spectra collection, fs-LIBS is very promising for high-speed FAR measurements using short-gated LIBS.

Gragston, Mark (ORCID:0000000324698995)↗
DOE OSTI2023

Machine learning in analytical spectroscopy for nuclear diagnostics [Invited]

Analytical spectroscopy methods have shown many possible uses for nuclear material diagnostics and measurements in recent studies. In particular, the application potential for various atomic spectroscopy techniques is uniquely diverse and generates interest across a wide range of nuclear science areas. Over the last decade, techniques such as laser-induced breakdown spectroscopy, Raman spectroscopy, and x-ray fluorescence spectroscopy have yielded considerable improvements in the diagnostic analysis of nuclear materials, especially with machine learning implementations. These techniques have been applied for analytical solutions to problems concerning nuclear forensics, nuclear fuel manufacturing, nuclear fuel quality control, and general diagnostic analysis of nuclear materials. The data yielded from atomic spectroscopy methods provide innovative solutions to problems surrounding the characterization of nuclear materials, particularly for compounds with complex chemistry. Implementing these optical spectroscopy techniques can provide comprehensive new insights into the chemical analysis of nuclear materials. In particular, recent advances coupling machine learning methods to the processing of atomic emission spectra have yielded novel, robust solutions for nuclear material characterization. This review paper will provide a summation of several of these recent advances and will discuss key experimental studies that have advanced the use of analytical atomic spectroscopy techniques as active tools for nuclear diagnostic measurements.

Rao, Ashwin P. (ORCID:0000000319312568)↗
DOE OSTI2025

Implementation of stacked ensemble machine learning for the detection of surrogate plutonium contamination in soil via LIBS

Supervised machine learning methods have demonstrated increased utility for the quantification of lanthanide and actinide elements in atomic spectroscopy applications. This study implements laser-induced breakdown spectroscopy (LIBS) for the identification of plutonium surrogate material (CeO 2 ) in soil matrices by training supervised machine learning methods on the recorded spectral data. A bagged ensemble using Random Forest yields the highest sensitivity predictions with a detection limit of 0.015 wt.% CeO 2 . However, high precision in Ce content prediction required the use of a stacked ensemble regression, which provided the superlative Ce quantification model with an error of 0.107% and a detection limit of 0.022 wt.%. Furthermore, the high performance of the stacked ensemble demonstrates its potential to enhance the accuracy and sensitivity of nuclear contaminant detection using field-deployable spectroscopic analyzers in real-world scenarios.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Comparison of damage and ablation dynamics of multilayer dielectric films initiated by few-cycle pulses versus longer femtosecond pulses

The importance of high intensity few- to single-cycle laser pulses for applications such as intense isolated attosecond pulse generation is constantly growing, and with the breakdown of the monochromatic approximation in field ionization models, the few-cycle pulse (FCP) interaction with solids near the damage threshold has ushered a new paradigm of nonperturbative light–matter interaction. In this Letter, we systematically study and contrast how femtosecond laser-induced damage and ablation behaviors of SiO 2 /HfO 2 -based reflective multilayer dielectric thin film systems vary between FCP and 110 fs pulses. With time-resolved surface microscopy and ex situ analysis, we show that there are distinct differences in the interaction depending on the pulse duration, specifically in the “blister” morphology formation at lower fluences (damage) as well as in the dynamics of debris formation at higher fluences (ablation).

42 ENGINEERING↗
DOE OSTI2024

Excitation of optically trapped single particles using femtosecond pulses

Excitation from optically trapped particles is examined through laser-induced breakdown spectroscopy following interactions with mJ-level fs pulses. Optical emissions from sub-ng ablation of precisely positioned cupric oxide microparticles are used as a method to spatially resolve laser–particle interactions resulting in excitation. External focusing lenses are often used to change the dynamics of nonlinear self-focusing of fs pulses to form laser filaments or, alternatively, to form very intense air plasmas. Given the significant implications external focusing has on laser propagation and plasma conditions, single-particle emissions are studied with focusing lenses ranging from 50 to 300 mm. It is shown that, while single particles are less excited at longer focal lengths due to limited energy transfer through laser–particle interactions, the cooler plasma results in a lower thermal background to reveal resolved single-shot emission peaks. Furthermore, by developing an understanding in the fundamental interaction that occurs between single particles and fs pulses and filaments, practical improvements can be made for atmospheric remote sensing of low-concentration aerosols.

42 ENGINEERING↗
DOE OSTI2025

Detection limits for laser absorption spectroscopy of Li in laser ablation plumes

A high-sensitivity laser absorption spectroscopy (LAS) method is demonstrated for rapid and non-contact analysis of Li in solids. Glass samples with Li concentrations ranging from 1-500 ppm by mass are ablated in 5 Torr air, and time-resolved Li atomic absorption is measured using a tunable laser near 671 nm. Significant improvements in analytical performance over prior laser-induced breakdown techniques are demonstrated. Here, a single-shot limit of detection (LOD) of 180 ppb is shown for fixed wavelength operation, improving to 6 ppb with averaging over 1000 ablation shots (100 s acquisition time). Isotope-resolved Li absorption spectra are measured with a 17 ppb LOD in 40 s. Methods for optimizing LOD based on noise/averaging properties of LAS experiments in LA plumes are discussed.

(020.3260) Isotope shifts↗
DOE OSTI2023

The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions

The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R . palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R . palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R . palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R . palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R . palustris Bis A53 ( i DT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. i DT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.

59 BASIC BIOLOGICAL SCIENCES↗