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DOE OSTI2021

Cognitive analysis of metabolomics data for systems biology

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Transcriptomic Changes in Seedlings from Seeds Exposed to Simulated Space Radiation

Outside the protection of Earth’s magnetic field, living organisms are constantly exposed to space radiation that consists of energetic protons and other heavier charged particles. With the goal of manned Mars exploration, the production of fresh crop during long duration space missions can be beneficial for meeting astronauts’ nutritional and psychological needs. In our study, we not only evaluated plant/fruit morphometrics and edible fresh mass, but also analyzed transcriptomic changes in seedlings from seeds of three plant species (Arabidopsis, mizuna, and tomato) exposed to simulated Galactic Cosmic Rays(GCR) and solar particle events(SPE). The radiation experiments were performed in the NASA Space Radiation Laboratory (NSRL) facility at Brookhaven National Lab (BNL). 10-day Arabidopsis seedlings were exposed acutely (~240 cGy/hr) to simulated GCR scenarios of combined ions including protons, helium, oxygen, titanium, and/or iron ions at 40 or 80 cGy. Seeds of Arabidopsis, mizuna, and tomato were exposed to 40 or 80 cGy simulated GCR (dry seeds) or SPE (imbibed seeds) at lower dose rates(20-26 cGy/hr). Seedlings from control and irradiated seeds were then collected in RNAlater at similar growth stages with true leaves emerged. Total RNA was isolated and analyzed via Illumina whole transcriptome sequencing technology. Plant species-specific bioinformatics revealed transcriptional biomarkers and signaling pathways induced by simulated space radiation that were found to be dose, dose-rate, and species dependent. DNA damage response, stress signaling, and metabolic pathways are among the most significant changes. These data highlight some critical insights on the mechanisms of how plants respond and adapt to the space radiation environment and provide a molecular basis for crop selection and refinement in deep space exploration.

Anirudha Dixit↗

NASA NTRS1998

Nitrogen recycling during phenylpropanoid metabolism in sweet potato tubers

In the first step of the phenylpropanoid metabolic pathway, L-phenylalanine (L-Phe) is deaminated to form E-cinnamate, in a conversion catalyzed by phenylalanine ammonia-lyase (PAL; EC 4.3.1.5). The metabolic fate of the ammonium ion (NH4+) produced in this reaction was investigated in sweet potato (Ipomoea batatas) tuber discs. [15N]-Labeled substrates including L-Phe, in the presence or absence of specific enzyme inhibitors, were administered to sweet potato discs in light under aseptic conditions. 15N-Nuclear magnetic resonance spectroscopic analyses revealed that the 15NH4+ liberated during the PAL reaction is first incorporated into the amide nitrogen of L-glutamine (L-Gln) and then into L-glutamate (L-Glu). These results extend our previous observations in pine and potato that PAL-generated NH4+ is assimilated by the glutamine synthetase (GS; EC 6.3.1.2)/glutamate synthase (GOGAT; EC 1.4.1.13) pathway, with the NH4+ so formed ultimately being recycled back to L-Phe via L-Glu as aminoreceptor and donor.

Non-NASA Center↗

DOE OSTI2022

Biocatalytic gateway to convert glycerol into 3-hydroxypropionic acid in waste-based biorefineries: Fundamentals, limitations, and potential research strategies

Microbial conversion of bioenergy-derived waste glycerol into value-added chemicals has emerged as an important bioprocessing technology due to its eco-friendliness, feasible technoeconomics, and potential to provide sustainability in biodiesel and bioethanol production. Glycerol is an abundant liquid waste from bioenergy plants with a projected volume of 6 million tons by 2025, accounting for about 10% of biodiesel and 2.5% of bioethanol yields. 3-Hydroxypropionic acid (3-HP) is a major product of glycerol bioconversion, which is the third largest biobased platform compound with expected market size and value of 3.6 million tons/year and USD 10 billion/year, respectively. Despite these biorefinery values, 3-HP biosynthesis from glycerol is still at an immature stage of commercial exploitation. The main challenges behind this immaturity are the toxic effects of 3-HPA on cells, the distribution of carbon flux to undesirable pathways, low tolerance of cells to glycerol and 3-HP, co-factor dependence of enzymes, low enzyme activity and stability, and the problems of substrate inhibition and specificity of enzymes. To address these challenges, it is necessary to understand the fundamentals of glycerol bioconversion and 3-HP production in terms of metabolic pathways, related enzymes, cell factories, midstream process configurations, and downstream 3-HP recovery, as discussed in this review critically and comprehensively. It is equally important to know the current challenges and limitations in 3-HP production, which are discussed in detail along with recent research efforts and remaining gaps. Finally, possible research strategies are outlined considering the recent technological advances in microbial biosynthesis, aiming to attract further research efforts to achieve a sustainable and industrially exploitable 3-HP production technology. Here, by discussing the use of advanced tools and strategies to overcome the existing challenges in 3-HP biosynthesis, this review will attract researchers from many other similar biosynthesis technologies and provide a common gateway for their further development.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Low-level resource partitioning supports coexistence among functionally redundant bacteria during successional dynamics

Members of microbial communities can substantially overlap in substrate use. However, what enables functionally redundant microorganisms to coassemble or even stably coexist remains poorly understood. Here, we show that during unstable successional dynamics on complex, natural organic matter, functionally redundant bacteria can coexist by partitioning low-concentration substrates even though they compete for one simple, dominant substrate. We allowed ocean microbial communities to self-assemble on leachates of the brown seaweed Fucus vesiculosus and then analyzed the competition among 10 taxonomically diverse isolates representing two distinct stages of the succession. All, but two isolates, exhibited an average of 90% ± 6% pairwise overlap in resource use, and functional redundancy of isolates from the same assembly stage was higher than that from between assembly stages, leading us to construct a simpler four-isolate community with two isolates from each of the early and late stages. We found that, although the short-term dynamics of the four-isolate communities in F. vesiculosus leachate was dependent on initial isolate ratios, in the long term, the four isolates stably coexist in F. vesiculosus leachate, albeit with some strains at low abundance. We therefore explored the potential for nonredundant substrate use by genomic content analysis and RNA expression patterns. This analysis revealed that the four isolates mainly differed in peripheral metabolic pathways, such as the ability to degrade pyrimidine, leucine, and tyrosine, as well as aromatic substrates. These results highlight the importance of fine-scale differences in metabolic strategies for supporting the frequently observed coexistence of large numbers of rare organisms in natural microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Omics-driven onboarding of the carotenoid producing red yeast Xanthophyllomyces dendrorhous CBS 6938

Transcriptomics is a powerful approach for functional genomics and systems biology, yet it can also be used for genetic part discovery. Here, we derive constitutive and light-regulated promoters directly from transcriptomics data of the basidiomycete red yeast Xanthophyllomyces dendrorhous CBS 6938 (anamorph Phaffia rhodozyma) and use these promoters with other genetic elements to create a modular synthetic biology parts collection for this organism. X. dendrorhous is currently the sole biotechnologically relevant yeast in the Tremellomycete class-it produces large amounts of astaxanthin, especially under oxidative stress and exposure to light. Thus, we performed transcriptomics on X. dendrorhous under different wavelengths of light (red, green, blue, and ultraviolet) and oxidative stress. Differential gene expression analysis (DGE) revealed that terpenoid biosynthesis was primarily upregulated by light through crtI, while oxidative stress upregulated several genes in the pathway. Further gene ontology (GO) analysis revealed a complex survival response to ultraviolet (UV) where X. dendrorhous upregulates aromatic amino acid and tetraterpenoid biosynthesis and downregulates central carbon metabolism and respiration. The DGE data was also used to identify 26 constitutive and regulated genes, and then, putative promoters for each of the 26 genes were derived from the genome. Simultaneously, a modular cloning system for X. dendrorhous was developed, including integration sites, terminators, selection markers, and reporters. Each of the 26 putative promoters were integrated into the genome and characterized by luciferase assay in the dark and under UV light. The putative constitutive promoters were constitutive in the synthetic genetic context, but so were many of the putative regulated promoters. Notably, one putative promoter, derived from a hypothetical gene, showed ninefold activation upon UV exposure. Thus, this study reveals metabolic pathway regulation and develops a genetic parts collection for X. dendrorhous from transcriptomic data. Therefore, this study demonstrates that combining systems biology and synthetic biology into an omics-to-parts workflow can simultaneously provide useful biological insight and genetic tools for nonconventional microbes, particularly those without a related model organism. This approach can enhance current efforts to engineer diverse microbes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Deconstructing the Soil Microbiome into Reduced-Complexity Functional Modules

The soil microbiome is an invaluable component of the biosphere and critical for ecosystem functions, including biogeochemical cycling, soil-atmosphere gas exchange, degradation of toxic compounds, and promotion of plant growth and stress resistance/resilience. An improved understanding of the soil microbiome will help with predicting how these processes respond to external perturbations, and with harnessing beneficial aspects of the soil microbiome for agronomic applications such as crop amendments. However, the extensive taxonomic and functional diversity inherent within the soil microbiome hinders efficient analysis of this system. Microbial biodiversity in soils is orders of magnitude greater than other commonly studied systems such as the human gut microbiome (Blum, Zechmeister-Boltenstern, and Keiblinger 2019; Berendsen, Pieterse, and Bakker 2012). Thousands of microbial taxa may be found in a single gram of soil (Roesch et al. 2007), and high rates of gene flow and mutation further promote microbial diversification (Sergaki et al. 2018). Concomitantly, functional diversity in soil is similarly extensive. Soil is a heterogeneous mixture of microenvironments with defined physical and chemical attributes (Bach et al. 2018), within which numerous microbial guilds of distinct life-strategies and metabolic capacities can be found (Perez-Garcia, Lear, and Singhal 2016; H.-S. Song et al. 2014). Furthermore, the soil microbiome harbors a significant fraction of rare and/or quiescent members (Blagodatskaya and Kuzyakov 2013) that exist below the threshold of detection of current technologies. Such rare taxa may make significant contributions to process rates (Shade and Gilbert 2015; Dawson et al. 2017), but their scarcity complicates their identification and analysis. Finally, the vast amounts of information generated through holistic analyses of soil communities represent an intense computational burden (Scholz, Lo, and Chain 2012; Prosser 2015) that precludes assessment of the complete functional and taxonomic diversity contained in this ecosystem.

Naylor, Dan T.↗

DOE OSTI2024

Tnseq to identify catabolism of b-5 linked aromatics by Novosphingobium aromaticivorans

This study investigates the catabolism of the b-5 linked aromatic dimer dehydrodiconiferyl alcohol (DC-A) by the bacterium Novosphingobium aromaticivorans. We used genome wide screens to identify candidate genes involved in DC-A catabolism. Subsequent in vivo and in vitro analyses of these candidates elucidated a catabolic pathway composed of four required gene products and several partially redundant dehydrogenases that convert DC-A to aromatic monomers that can be funneled into the central aromatic metabolic pathway of N. aromaticivorans.

Noguera, Daniel R.↗

DOE OSTI2024

Tnseq to identify catabolism of b-5 linked aromatics by Novosphingobium aromaticivorans

aromatic compounds↗

DOE OSTI2021

Probing Light-Dependent Regulation of the Calvin Cycle Using a Multi-Omics Approach

Photoautotrophic microorganisms are increasingly explored for the conversion of atmospheric carbon dioxide into biomass and valuable products. The Calvin-Benson-Bassham (CBB) cycle is the primary metabolic pathway for net CO 2 fixation within oxygenic photosynthetic organisms. The cyanobacteria, Synechocystissp. PCC 6803, is a model organism for the study of photosynthesis and a platform for many metabolic engineering efforts. The CBB cycle is regulated by complex mechanisms including enzymatic abundance, intracellular metabolite concentrations, energetic cofactors and post-translational enzymatic modifications that depend on the external conditions such as the intensity and quality of light. However, the extent to which each of these mechanisms play a role under different light intensities remains unclear. In this work, we conducted non-targeted proteomics in tandem with isotopically non-stationary metabolic flux analysis (INST-MFA) at four different light intensities to determine the extent to which fluxes within the CBB cycle are controlled by enzymatic abundance. The correlation between specific enzyme abundances and their corresponding reaction fluxes is examined, revealing several enzymes with uncorrelated enzyme abundance and their corresponding flux, suggesting flux regulation by mechanisms other than enzyme abundance. Additionally, the kinetics of 13 C labeling of CBB cycle intermediates and estimated inactive pool sizes varied significantly as a function of light intensity suggesting the presence of metabolite channeling, an additional method of flux regulation. These results highlight the importance of the diverse methods of regulation of CBB enzyme activity as a function of light intensity, and highlights the importance of considering these effects in future kinetic models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Diagnosing and Predicting Mixed-Culture Fermentations with Unicellular and Guild-Based Metabolic Models

Microbiomes are vital to human health, agriculture, and protecting the environment. Predicting behavior of self-assembled or synthetic microbiomes, however, remains a challenge. In this work, we used unicellular and guild-based metabolic models to investigate production of medium-chain fatty acids by a mixed microbial community that is fed multiple organic substrates. Modeling results provided insights into metabolic pathways of three medium-chain fatty acid-producing guilds and identified potential strategies to increase production of medium-chain fatty acids. This work demonstrates the role of metabolic models in augmenting multi-omic studies to gain greater insights into microbiome behavior.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Connecting agriculture and renewable energy: insights into microclimatic changes, physiological, biochemical, and yield responses under agrivoltaics: a review

Agrivoltaics, the synergistic integration of agriculture and solar energy production on the same piece of land, has emerged as a compelling dual-use solution that maximizes land productivity while simultaneously addressing the need for sustainable agricultural practices and renewable energy generation. Despite the growing global interest in this dual-use system, the microclimatic shifts created beneath solar panels and their consequences for crop performance remain insufficiently synthesized. This review highlights the intricate interactions between agrivoltaics systems and plant microclimates, discussing their impacts on various physiological processes, metabolic pathways, and overall yield responses in different crop species. Evidence indicates that moderated light intensity and altered microclimates can enhance water-use efficiency, stabilize photosynthetic function, and trigger beneficial metabolic adjustments; however, responses remain highly species-specific and strongly dependent on regional climate conditions and panel configuration. Yield outcomes vary widely among vegetables, cereals, pulses, and fruit crops, highlighting the necessity for tailored agronomic strategies and crop selection within agrivoltaic designs. A critical knowledge gap identified in this review concerns the limited understanding of molecular and omics-level responses underlying plant adaptation to agrivoltaic environments. We further provide a detailed and interdisciplinary overview of adaptive agronomic strategies, and optimal crop selection, tailored to agrivoltaic systems. Despite the benefits of land use efficiency and simultaneous food and energy production, challenges remain concerning initial investment, technological adaptation, social and legal barriers, and shade-induced yield penalties. Further research in this area will be critical to enhancing the agricultural, environmental, and economic sustainability of agrivoltaics while simultaneously augmenting their practical utility and appeal to farmers in the future.

14 SOLAR ENERGY↗

DOE OSTI2021

Portable bacterial CRISPR transcriptional activation enables metabolic engineering in Pseudomonas putida

Not provided.

Biotechnology & Applied Microbiology↗

DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism

Abstract Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be combined to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets, efficient library construction of metabolic pathway designs, and high-throughput biosensor-enabled screening for training diverse machine learning algorithms. From a single data-generation cycle, this enables successful forward engineering of complex aromatic amino acid metabolism in yeast, with the best machine learning-guided design recommendations improving tryptophan titer and productivity by up to 74 and 43%, respectively, compared to the best designs used for algorithm training. Thus, this study highlights the power of combining mechanistic and machine learning models to effectively direct metabolic engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Bacterial effectors mimicking ubiquitin-proteasome pathway tweak plant immunity

Plant pathogenic Gram-negative bacteria evade the host plant immune system by secreting Type III (T3E) and Type IV effector (T4E) proteins into the plant cytoplasm. Mostly T3Es are secreted into the plant cells to establish pathogenicity by affecting the vital plant process viz. metabolic pathways, signal transduction and hormonal regulation. Ubiquitin-26S proteasome system (UPS) exists as one of the important pathways in plants to control plant immunity and various cellular processes by employing several enzymes and enzyme components. Pathogenic and non-pathogenic bacteria are found to secrete effectors into plants with structural and/or functional similarity to UPS pathway components like ubiquitin E3 ligases, F-box domains, cysteine proteases, inhibitor of host UPS or its components, etc. The bacterial effectors mimic UPS components and target plant resistance proteins for degradation by proteasomes, thereby taking control over the host cellular activities as a strategy to exert virulence. Thus, the bacterial effectors circumvent plant cellular pathways leading to infection and disease development. Finally, this review highlights known bacterial T3E and T4E proteins that function and interfere with the ubiquitination pathway to regulate the immune system of plants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Pathway Evolution Through a Bottlenecking-Debottlenecking Strategy and Machine Learning-Aided Flux Balancing

The evolution of pathway enzymes enhances the biosynthesis of high-value chemicals, crucial for pharmaceutical, and agrochemical applications. However, unpredictable evolutionary landscapes of pathway genes often hinder successful evolution. Here, the presence of complex epistasis is identifued within the representative naringenin biosynthetic pathway enzymes, hampering straightforward directed evolution. Subsequently, a biofoundry-assisted strategy is developed for pathway bottlenecking and debottlenecking, enabling the parallel evolution of all pathway enzymes along a predictable evolutionary trajectory in six weeks. This study then utilizes a machine learning model, ProEnsemble, to further balance the pathway by optimizing the transcription of individual genes. The broad applicability of this strategy is demonstrated by constructing an Escherichia coli chassis with evolved and balanced pathway genes, resulting in 3.65 g L -1 naringenin. The optimized naringenin chassis also demonstrates enhanced production of other flavonoids. This approach can be readily adapted for any given number of enzymes in the specific metabolic pathway, paving the way for automated chassis construction in contemporary biofoundries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

raogroupuiuc/lipo11557_growth

Project: Systems analysis of Lipomyces starkeyi during growth on various plant-based sugars Authors: Anshu Deewan*, Jing-Jing Liu*, Sujit Sadashiv Jagtap, Eun Ju Yun, Hanna E Walukiewicz, Yong-Su Jin, Christopher V Rao (* - co-authors) Abstract : Oleaginous yeasts have received significant attention due to their substantial lipids storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. This analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

Deewan, Anshu↗