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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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At least 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Additionally, based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10 -3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

A Scalable Reduced‐Order Model for the Steady Navier–Stokes Equations

Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predictions in the deployment process, though traditional numerical methods are computationally intractable even for intermediate pilot plant scales. Recently, the component reduced order modeling method has been developed to tackle this challenge by combining projection reduced order modeling and discontinuous Galerkin domain decomposition. However, while many scientific or engineering applications involve nonlinear physics, this method has only been demonstrated for various linear systems. In this work, the component reduced order modeling method is extended to steady Navier–Stokes flow, with application to general nonlinear physics in view. The large‐scale, global domain is decomposed into a combination of small‐scale unit component. Linear subspaces for flow velocity and pressure are identified via proper orthogonal decomposition over sample snapshots collected from each small‐scale unit component. Velocity bases are augmented with a pressure supremizer to satisfy the inf–sup condition for stable pressure prediction. Two different nonlinear reduced order modeling methods are employed and compared for efficient evaluation of nonlinear advection: A third‐order tensor projection operator and the empirical quadrature procedure. The proposed method is demonstrated on the flow over arrays of five different unit objects, achieving a 23‐fold speedup with less than 4% relative error in domains up to 256 times larger than the unit components. Furthermore, a numerical experiment with the pressure supremizer strongly indicates the need for a supremizer for stable pressure prediction. A comparison between the tensorial approach and the empirical quadrature procedure revealed a slight advantage of the empirical quadrature procedure. The framework is compared with an alternating Schwarz‐based reduced‐order approach, demonstrating improved efficiency and robustness for the DG‐based global solver while retaining flexibility for sub‐scale iterative solvers. The method is further extended to a coupled advection–diffusion and Navier–Stokes system, illustrating its applicability to multi‐physics problems and its potential for more general, inter‐coupled nonlinear systems.

42 ENGINEERING↗
DOE OSTI2025

Monolayer TiS 2 Nanosheets on Au(111)–Structural Characterization and Effect of Edge Stability for Shape Control

Transition metal dichalcogenides are promising alternatives to noble metal catalysts, e.g., for (photo-)activation of greenhouse gases or hydrogenations. Herein, a direct synthetic route for 2D TiS 2 nanosheets on Au(111) by titanium deposition in the presence of a mild, organic, non-oxidizing sulfur source is presented. High-resolution scanning tunneling microscopy (STM) is used to gain atomic-level insights into the TiS 2 nanosheet morphology. In contrast to the literature, this protocol gains mostly hexagonal and truncated triangular nanosheets with an increased edge contrast in STM, analog to metallic edge states in MoS 2 . Synchrotron-based photoelectron spectroscopy allows insights into compositional details, specifically to distinguish different S sites on the TiS 2 sheets and other S species on the sample. Further, a minimum size is identified (9 S atoms side length), which underlines the importance of moiré reconstructions for stress relief. The TiS 2 sheets coexist with [Au]Ti 1 S 3 clusters, in which a single gold atom is alloyed into the surface and capped by three S atoms. Together with the finding of a critical sheet size, this points toward on-surface Ostwald ripening as a relevant process in the sheet formation. Ab-initio calculations (density functional theory) underscore that the chemical potential of S is an essential descriptor to maintain shape control.

2D nanomaterials↗
DOE OSTI2023

Investigation of the Effect of Chrome and Nickel Concentrations During Two-Piston Splat Quenching of Austenitic Stainless Steels

For solidification rates at or near equilibrium solidification conditions the effects of chrome (Cr) and nickel (Ni) on stainless steel solidification modes and microstructures are well detailed. However, fusion-based additive manufacturing (FBAM) processes that rely on faster, more rapid solidification rates call for a more in-depth understanding of the effects of rapid solidification on the solidification behavior and how these change with variations in alloy composition. Eleven custom stainless steel (SS) alloys with unique compositions based on 316L were made using targeted alloying element additions to generate feedstock with Cr/Ni eq ratios ranging from 0.9 to 2.1. Two-piston splat quenching (SQ) was used to produce rapid solidification conditions similar to those achieved in powder bed fusion processes in a fraction of the time and cost of traditional methods. Employing heat transfer simulations, SEM, TEM, and STEM characterization techniques, the SQ process was found to consistently produce solidification rates estimated to be between ~ 0.4 and 1.6 m/s. Five unique solidification microstructures were identified within the rapidly solidified SQ samples (primary austenite, massively transformed ferrite to austenite, primary austenite and massively transformed ferrite to austenite, primary ferrite, and primary ferrite and massively transformed ferrite to austenite). Both the primary ferrite solidification mode and primary ferrite phase were found to form at lower Cr/Ni eq values than previously predicted. SQ samples with compositions that were within the compositional specifications for 316L SS, an alloy which is commonly used in FBAM processes, demonstrated a wider range of potential solidification modes and microstructures that could form at rapid solidification rates than expected. Finally, by using SQ as a means to simulate rapid solidification conditions similar to those observed in FBAM processes, potential new alloy compositions can be screened faster and more cost effectively than purchasing and running test batches of the metallic powder.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Exploring the relationship between deposition method, microstructure, and performance of Nb/Si-based superconducting coplanar waveguide resonators

Superconducting quantum circuits (SQC) are one of the most promising hardware platforms for quantum computing, yet their performance is currently limited by the presence of various structural defects inside the circuit's structure. Despite impressive progress in the past decade, a precise understanding of the origin of these defects from various fabrication processes and their impact on coherence is still lacking. Here, in this study, we performed a comprehensive investigation on the microstructure, superconductivity, and resonator quality factor of Nb films deposited by high-power impulse magnetron sputtering (HiPIMS) and direct current (DC) magnetron sputtering. A suite of characterization techniques, including electron microscopy with spectroscopy, secondary ion mass spectrometry, magneto-optical microscopy, and pump-probe reflectivity spectroscopy is used. We reveal that niobium (Nb) resonators fabricated using HiPIMS exhibit a smaller average grain size, thicker surface oxide with larger thickness variations (rougher surface), and a thicker amorphous Nb/Si interface layer compared to samples deposited by DC sputtering. We identified that the amorphous Nb oxides (mainly located at the Nb surface and along the grain boundaries) and Nb-Si amorphous layers (at the Nb/Si interface) are major and potential sources of two-level system (TLS), while off-stochiometric oxides and suboxides of Nb close to the surface, crystalline defects (i.e., dislocations at grain boundary, point defects introduced during deposition) are main contributors of non-TLS sources. Our findings clarify the relationship between different defects and coherence loss mechanisms, highlighting the importance of material microstructure control on performance optimization in SQC.

36 MATERIALS SCIENCE↗
DOE OSTI2023

exRNA-eCLIP intersection analysis reveals a map of extracellular RNA binding proteins and associated RNAs across major human biofluids and carriers

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Characterization of Iron and Organic Carbon Colloids in Boreal Rivers and Their Fate at High Salinity

Riverine colloids are important carriers of macronutrients, trace metals, and pollutants into marine waters. The aim of the current study was to extend the understanding of iron (Fe) and organic carbon (OC) colloids in boreal rivers and their fate at higher salinities. X-ray absorbance spectroscopy (XAS) and dynamic light scattering (DLS) were combined to explore Fe speciation and colloidal characteristics such as size and surface charge and how these are affected at increasing salinity. XAS confirmed the presence of two Fe phases in the river waters—Fe-organic matter (OM) complexes and Fe(oxy)hydroxides. From DLS measurements on filtered and unfiltered samples, three particle size distributions were identified. The smallest particles (10–40 nm) were positively charged and suggested to consist of essentially bare Fe (oxy)hydroxide nanoparticles. The largest particles (300–900 nm) were dominated by Fe(oxy)hydroxides associated with chromophoric molecular matter. An intermediate size distribution (100–200 nm) with a negative surface charge was presumably dominated by OM and containing Fe-OM complexes. Increasing the salinity resulted in a removal of the smallest distribution. Unexpectedly, both the intermediate and largest size distributions were still detected at high salinity. The collective results suggest that Fe(oxy) hydroxides and Fe-OM complexes are both found across the wide size range studied and that colloidal size does not necessarily reflect either Fe speciation or stability toward salinity-induced aggregation. The findings further demonstrate that also particles beyond the typically studied <0.45-μm size range should be considered to fully understand the riverine transport and fate of macronutrients, trace metals, and pollutants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Femtosecond stimulated Raman spectro-microscopy for probing chemical reaction dynamics in solid-state materials

Femtosecond stimulated Raman spectroscopy (FSRS) is a chemically specific vibrational technique that has the ability to follow structural dynamics during photoinduced processes such as charge transfer on the ultrafast timescale. FSRS has a strong background in following structural dynamics and elucidating chemical mechanisms; however, its use with solid-state materials has been limited. As photovoltaic and electronic devices rely on solid-state materials, having the ability to track the evolving dynamics during their charge transfer and transport processes is crucial. Following the structural dynamics in these solid-state materials will lead to the identification of specific chemical structures responsible for various photoinduced charge transfer reactions, leading to a greater understanding of the structure–function relationships needed to improve upon current technologies. Furthermore, isolating the specific nuclear motions and molecular structures that drive a desired physical process will provide a chemical blueprint, leading to the rational design and fabrication of efficient electronic and photovoltaic devices. In this perspective, we discuss technical challenges and experimental developments that have facilitated the use of FSRS with solid-state samples, explore previous studies that have identified structure–function relationships in charge transfer reactions, and analyze the future developments that will broaden and advance the field.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Birth of a Be star: an APOGEE search for Be stars forming through binary mass transfer

ABSTRACT Motivated by recent suggestions that many Be stars form through binary mass transfer, we searched the APOGEE survey for Be stars with bloated, stripped companions. From a well-defined parent sample of 297 Be stars, we identified one mass-transfer binary, HD 15124. The object consists of a main-sequence Be star ($M_{\rm Be}=5.3\pm 0.6\, {\rm M}_{\odot }$) with a low-mass ($M_{\rm donor}=0.92\pm 0.22\, {\rm M}_{\odot }$), subgiant companion on a 5.47-d orbit. The emission lines originate in an accretion disc caused by ongoing mass transfer, not from a decretion disc as in classical Be stars. Both stars have surface abundances bearing imprint of CNO processing in the donor’s core: the surface helium fraction is YHe ≈ 0.6, and the nitrogen-to-carbon ratio is 1000 times the solar value. The system’s properties are well-matched by binary evolution models in which mass transfer begins while a $3-5\, {\rm M}_{\odot }$ donor leaves the main sequence, with the originally less massive component becoming the Be star. These models predict that the system will soon become a detached Be + stripped star binary like HR 6819 and LB-1, with the stripped donor eventually contracting to become a core helium-burning sdO/B star. Discovery of one object in this short-lived (∼1 Myr) evolutionary phase implies the existence of many more that have already passed through it and are now Be + sdO/B binaries. We infer that $(10-60)\, {{\ \rm per\ cent}}$ of Be stars have stripped companions, most of which are $\sim 100\, \times$ fainter than the Be stars in the optical. Together with the dearth of main-sequence companions to Be stars and recent discovery of numerous Be + sdO/B binaries in the UV, our results imply that binarity plays an important role in the formation of Be stars.

El-Badry, Kareem (ORCID:0000000268711752)↗
DOE OSTI2022

The miniJPAS survey quasar selection – I. Mock catalogues for classification

In this series of papers, we employ several machine learning (ML) methods to classify the point-like sources from the miniJPAS catalogue, and identify quasar candidates. Since no representative sample of spectroscopically confirmed sources exists at present to train these ML algorithms, we rely on mock catalogues. In this first paper, we develop a pipeline to compute synthetic photometry of quasars, galaxies, and stars using spectra of objects targeted as quasars in the Sloan Digital Sky Survey . To match the same depths and signal-to-noise ratio distributions in all bands expected for miniJPAS point sources in the range 17.5 ≤ r < 24, we augment our sample of available spectra by shifting the original r-band magnitude distributions towards the faint end, ensure that the relative incidence rates of the different objects are distributed according to their respective luminosity functions, and perform a thorough modelling of the noise distribution in each filter, by sampling the flux variance either from Gaussian realizations with given widths, or from combinations of Gaussian functions. Finally, we also add in the mocks the patterns of non-detections which are present in all real observations. Although the mock catalogues presented in this work are a first step towards simulated data sets that match the properties of the miniJPAS observations, these mocks can be adapted to serve the purposes of other photometric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Population Genomic Analyses Reveal Connectivity via Human-Mediated Transport across Populus Plantations in North America and an Undescribed Subpopulation of Sphaerulina musiva

Domestication of plant species has affected the evolutionary dynamics of plant pathogens in agriculture and forestry. A model system for studying the consequences of plant domestication on the evolution of an emergent plant disease is the fungal pathogen Sphaerulina musiva. This ascomycete causes leaf spot and stem canker disease of Populus spp. and their hybrids. A population genomics approach was used to determine the degree of population structure and evidence for selection on the North American population of S. musiva. In total, 122 samples of the fungus were genotyped identifying 120,016 single-nucleotide polymorphisms after quality filtering. In North America, S. musiva has low to moderate degrees of differentiation among locations. Three main genetic clusters were detected: southeastern United States, midwestern United States and Canada, and a new British Columbia cluster (BC2). Population genomics suggest that BC2 is a novel genetic cluster from central British Columbia, clearly differentiated from previously reported S. musiva from coastal British Columbia, and the product of a single migration event. Phenotypic measurements from greenhouse experiments indicate lower aggressiveness of BC2 on Populus trichocarpa. In summary, S. musiva has geographic structure across broad regions indicative of gene flow among clusters. The interconnectedness of the North American S. musiva populations across large geographic distances further supports the hypothesis of anthropogenic-facilitated transport of the pathogen.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Growth and characterization of large (Y,La)TiO 3 and (Y,Ca)TiO 3 single crystals

The Mott-insulating rare-earth titanates ( R TiO 3 , with R being a rare-earth ion) are an important class of materials that encompasses interesting spin-orbital phases as well as ferromagnet-antiferromagnet and insulator-metal transitions. The growth of these materials has been plagued by difficulties related to overoxidation, which arises from a strong tendency of Ti 3 + to oxidize to Ti 4 + . We describe our efforts to grow sizable single crystals of YTiO 3 , Y 1 - x La x TiO 3 ( x ≤ 0.25 ), and Y 1 - y Ca y TiO 3 ( y ≤ 0.35 ) with the optical traveling-solvent floating-zone technique. Finally, we present sample characterization via chemical composition analysis, magnetometry, charge transport, neutron scattering, x-ray absorption spectroscopy, and x-ray magnetic circular dichroism to understand macroscopic physical property variations associated with overoxidation. Furthermore, we demonstrate a good signal-to-noise ratio in inelastic magnetic neutron scattering measurements of spin-wave excitations. A superconducting impurity phase, found to appear in Ca-doped samples at high doping levels, is identified as TiO.

36 MATERIALS SCIENCE↗
DOE OSTI2025

XSub: Explanation-Driven Adversarial Attack against Blackbox Classifiers via Feature Substitution

Despite its significant benefits in enhancing the transparency and trustworthiness of artificial intelligence (AI) systems, explainable AI (XAI) can unintentionally provide adversaries with insights into blackbox models, increasing their vulnerability to various attacks. In this paper, we develop a novel explanation-driven adversarial attack against blackbox classifiers based on feature substitution, called XSub. The key idea of XSub is to strategically replace important features (identified via XAI) in the original sample with corresponding important features of a different label, thereby increasing the likelihood of the model misclassifying the perturbed sample. XSub only requires a minimal number of queries and can be easily extended to launch backdoor attacks in case the attacker has access to the model's training data. Our evaluation shows that XSub is not only effective and stealthy but also low-cost, showcasing its feasibility across a wide range of AI applications.

adversarial attack↗
DOE OSTI2021

Visual Tool for Assessing Stability of DER Configurations on Three-Phase Radial Networks

Here, we present a method and tool for evaluating the placement of Distributed Energy Resources (DER) on distribution circuits in order to control voltages and power flows. Our previous work described Phasor-Based Control (PBC), a novel control framework where DERs inject real and reactive power to track voltage magnitude and phase angle targets. Here, we employ linearized power flow equations and integral controllers to develop a linear state space model for PBC acting on a three-phase unbalanced network. We use this model to evaluate whether a given inverter-based DER configuration admits a stable set of controller gains, which cannot be done by analyzing controllability nor by using the Lyapunov equation. Instead, we sample over a parameter space to identify a stable set of controller gains. Our stability analysis requires only a line impedance model and does not entail simulating the system or solving an optimization problem. We incorporate this assessment into a publicly available visualization tool and demonstrate three processes for evaluating many control configurations on the IEEE 123-node test feeder (123NF).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Data-driven Event Identification in the U.S. Power Systems Based on 2D-OLPP and RUSBoosting Trees

Accurate event identification is an essential part of situation awareness ability for power system operators. Therefore, this work proposes an integrated event identification algorithm for power systems. First, to obtain and filter suitable inputs for event identification, an event detection trigger based on the rate of change of frequency (RoCoF) is presented. Then, the wave arrival time difference-based triangulation method considering the anisotropy of wave propagation speed is utilized to estimate the location of the detected event. Next, the two-dimensional orthogonal locality preserving projection (2D-OLPP)-based method, which is suitable for multiple types of measured data, is employed to achieve higher effectiveness in extracting the event features compared with traditional one-dimensional projection and principle component analysis (PCA). Finally, the random undersampling boosted (RUSBoosted) trees-based classifier, which can mitigate the data sample imbalance issue, is utilized to identify the type of the detected event. Furthermore, the proposed approach is demonstrated using the actual measurement data of U.S. power systems from FNET/GridEye. Comparison results show that the proposed event identification algorithm can achieve better performance than existing approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Organic preservation of vase‐shaped microfossils from the late Tonian Chuar Group, Grand Canyon, Arizona, USA

Abstract Vase‐shaped microfossils (VSMs) are found globally in middle Neoproterozoic (800–730 Ma) marine strata and represent the earliest evidence for testate (shell‐forming) amoebozoans. VSM tests are hypothesized to have been originally organic in life but are most commonly preserved as secondary mineralized casts and molds. A few reports, however, suggest possible organic preservation. Here, we test the hypothesis that VSMs from shales of the lower Walcott Member of the Chuar Group, Grand Canyon, Arizona, contain original organic material, as reported by B. Bloeser in her pioneering studies of Chuar VSMs. We identified VSMs from two thin section samples of Walcott Member black shales in transmitted light microscopy and used scanning electron microscopy to image VSMs. Carbonaceous material is found within the internal cavity of all VSM tests from both samples and is interpreted as bitumen mobilized from Walcott shales likely during the Cretaceous. Energy dispersive X‐ray spectroscopy (EDS) and wavelength dispersive X‐ray spectroscopy (WDS) reveal that VSM test walls contain mostly carbon, iron, and sulfur, while silica is present only in the surrounding matrix. Raman spectroscopy was used to compare the thermal maturity of carbonaceous material within the samples and indicated the presence of pyrite and jarosite within fossil material. X‐ray absorption spectroscopy revealed the presence of reduced organic sulfur species within the carbonaceous test walls, the carbonaceous material found within test cavities, and in the sedimentary matrix, suggesting that organic matter sulfurization occurred within the Walcott shales. Our suite of spectroscopic analyses reveals that Walcott VSM test walls are organic and sometimes secondarily pyritized (with the pyrite variably oxidized to jarosite). Both preservation modes can occur at a millimeter spatial scale within sample material, and at times even within a single specimen. We propose that sulfurization within the Walcott Shales promoted organic preservation, and furthermore, the ratio of iron to labile VSM organic material controlled the extent of pyrite replacement. Based on our evidence, we conclude that the VSMs are preserved with original organic test material, and speculate that organic VSMs may often go unrecognized, given their light‐colored, translucent appearance in transmitted light.

58 GEOSCIENCES↗
DOE OSTI2026

The need for standardization and improved open (meta)data practices in metaproteomics

Metaproteomics enables functional insight into microbial communities by identifying and quantifying proteins in complex samples. Yet, heterogeneous analytical workflows and the lack of standardization across experimental and bioinformatics stages hinder reproducibility and comparability, limiting integration with other omics data. We here present a community-developed reporting checklist tailored to the specific needs of metaproteomics. We also outline current efforts to enable structured and interoperable metadata capture, drawing on standards from proteomics and microbiome research wherever possible. By promoting transparent reporting and advancing metadata practices, our recommendations aim to align metaproteomics more closely with FAIR principles and support reproducible and interoperable research practices.

Armengaud, Jean [Universite Paris-Saclay, France]↗
DOE OSTI2023

BayFlux: A Bayesian method to quantify metabolic Fluxes and their uncertainty at the genome scale

Metabolic fluxes, the number of metabolites traversing each biochemical reaction in a cell per unit time, are crucial for assessing and understanding cell function. 13 C Metabolic Flux Analysis ( 13 C MFA) is considered to be the gold standard for measuring metabolic fluxes. 13 C MFA typically works by leveraging extracellular exchange fluxes as well as data from 13 C labeling experiments to calculate the flux profile which best fit the data for a small, central carbon, metabolic model. However, the nonlinear nature of the 13 C MFA fitting procedure means that several flux profiles fit the experimental data within the experimental error, and traditional optimization methods offer only a partial or skewed picture, especially in “non-gaussian” situations where multiple very distinct flux regions fit the data equally well. Here, we present a method for flux space sampling through Bayesian inference (BayFlux), that identifies the full distribution of fluxes compatible with experimental data for a comprehensive genome-scale model. This Bayesian approach allows us to accurately quantify uncertainty in calculated fluxes. We also find that, surprisingly, the genome-scale model of metabolism produces narrower flux distributions (reduced uncertainty) than the small core metabolic models traditionally used in 13 C MFA. The different results for some reactions when using genome-scale models vs core metabolic models advise caution in assuming strong inferences from 13 C MFA since the results may depend significantly on the completeness of the model used. Based on BayFlux, we developed and evaluated novel methods (P- 13 C MOMA and P- 13 C ROOM) to predict the biological results of a gene knockout, that improve on the traditional MOMA and ROOM methods by quantifying prediction uncertainty.

59 BASIC BIOLOGICAL SCIENCES↗