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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 667 records · Page 37
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DOE OSTI2021

Land Surface Modeling 2.0 for agricultural climate change impact assessments

Focus Area: This white paper addresses DOE AI4ESP focus area #2 by providing a sketch blueprint for a next generation, hybrid AI/process-based global Land Surface Modeling (LSM) framework to improve projections of climate change impacts on the land surface system including agriculture and the hydrological cycle. Science Challenge: Climate change impacts on agriculture are highly uncertain: -50% to +150% global production changes for major grains under high-end climate change, for example. The core challenge in land surface system predictability is the large gap between the scale at which the relevant biological processes act and the scale at which the risks need to be assessed. Conventional empirical and process-based modeling approaches are insufficient. A new multi-scale modeling paradigm which employs AI/ML to learn from new streams of remote sensing data and targeted ’gene-to-global’ simulations is needed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Secreted Effector Proteins of Poplar Leaf Spot and Stem Canker Pathogen Sphaerulina musiva Manipulate Plant Immunity and Contribute to Virulence in Diverse Ways

We report fungal effectors play critical roles in manipulating plant immune responses and promoting colonization. Sphaerulina musiva is a heterothallic ascomycete fungus that causes Septoria leaf spot and stem canker disease in poplar (Populus spp.) plantations. This disease can result in premature defoliation, branch and stem breakage, increased mortality, and plantation failure. However, little is known about the interaction between S. musiva and poplar. Previous work predicted 142 candidate secreted effector proteins in S. musiva (SmCSEPs), 19 of which were selected for further functional characterization in this study. SmCSEP3 induced plant cell death in Nicotiana benthamiana, while 8 out of 19 tested SmCSEPs suppressed cell death. The signal peptides of these eight SmCSEPs exhibited secretory activity in a yeast signal sequence trap assay. Confocal microscopy revealed that four of these eight SmCSEPs target both the cytoplasm and the nucleus, whereas four predominantly localize to discrete punctate structures. Pathogen challenge assays in N. benthamiana demonstrated that the transient expression of six SmCSEPs promoted Fusarium proliferatum infection. The expression of these six SmCSEP genes were induced during infection. SmCSEP2, SmCSEP13, and SmCSEP25 suppressed chitin-triggered reactive oxygen species burst and callose deposition in N. benthamiana. The candidate secreted effector proteins of S. musiva target multiple compartments in the plant cell and modulate different pattern-triggered immunity pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring

The laboratory identification of antibacterial resistance is a cornerstone of infectious disease medicine. In vitro antimicrobial susceptibility testing has long been based on the growth response of organisms in pure culture to a defined concentration of antimicrobial agents. By comparing individual isolates to wild type susceptibility patterns, strains with acquired resistance can be identified. Acquired resistance can also be detected genetically. After many decades of research, the inventory of genes underlying antimicrobial resistance (AMR) is well known for several pathogenic genera including zoonotic enteric organisms such as Salmonella and Campylobacter and continues to grow substantially for others. With the decline in costs for large scale DNA sequencing, it is now practicable to characterize bacteria using whole genome sequencing (WGS), including the carriage of resistance genes in individual microorganisms and those present in complex biological samples. With genomics we can generate comprehensive, detailed information on the bacterium, the mechanisms of antibiotic resistance, clues to its source, and the nature of mobile DNA elements by which resistance spreads. These developments point to a new paradigm for antimicrobial resistance detection and tracking for both clinical and public health purposes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

HypoRiPPAtlas as an Atlas of hypothetical natural products for mass spectrometry database search

Abstract Recent analyses of public microbial genomes have found over a million biosynthetic gene clusters, the natural products of the majority of which remain unknown. Additionally, GNPS harbors billions of mass spectra of natural products without known structures and biosynthetic genes. We bridge the gap between large-scale genome mining and mass spectral datasets for natural product discovery by developing HypoRiPPAtlas, an Atlas of hypothetical natural product structures, which is ready-to-use for in silico database search of tandem mass spectra. HypoRiPPAtlas is constructed by mining genomes using seq2ripp, a machine-learning tool for the prediction of ribosomally synthesized and post-translationally modified peptides (RiPPs). In HypoRiPPAtlas, we identify RiPPs in microbes and plants. HypoRiPPAtlas could be extended to other natural product classes in the future by implementing corresponding biosynthetic logic. This study paves the way for large-scale explorations of biosynthetic pathways and chemical structures of microbial and plant RiPP classes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Animal-associated jumbo phages as widespread and active modulators of gut microbiome ecology and metabolism

Huge phages are widespread in the biosphere, yet their prevalence and ecology in the human gut remain poorly characterized. Here, we report Jug (jumbo gut) phages with genomes of 360 to 402 kilobase pairs that comprise ~1.1% of the reads in human gut metagenomes, and are predicted to infect Bacteroides and/or Phocaeicola. Although three of the four major groups of Jug phages shared >90% genome-wide sequence identity, their large terminase subunits exhibited only 38 to 57% identity, suggesting horizontal acquisition from other phages. Over 1500 genomes of Jug phages were recovered from human and animal gut metagenomes, revealing their broad distribution, with largely shared gene content suggestive of frequent cross-animal-host transmission. Jug phages displayed high gene transcription activities, including the gene for a calcium-translocating P-type ATPase not detected previously in phages. These findings broaden our understanding of huge phages and highlight Jug phages as potential major players in gut microbiome ecology.

Chen, LinXing [University of Science and Technolog↗
DOE OSTI2021

A Novel Freshwater to Marine Evolutionary Transition Revealed within Methylophilaceae Bacteria from the Arctic Ocean

Bacteria inhabiting polar oceans, particularly the Arctic Ocean, are less studied than those at lower latitudes. Discovering bacterial adaptations to Arctic Ocean conditions is essential for understanding responses to the accelerated environmental changes occurring in the North. The Methylophilaceae are emerging as a model for investigating the genomic basis of habitat adaptation, because related lineages are widely distributed across both freshwater and marine ecosystems. Here, we investigated Methylophilaceae diversity in the salinity-stratified surface waters of the Canada Basin, Arctic Ocean. In addition to a diversity of marine OM43 lineages, we report on the genomic characteristics and evolution of a previously undescribed Methylophilaceae clade (BS01) common to polar surface waters yet related to freshwater sediment Methylotenera species. BS01 is restricted to the lower-salinity surface waters, while OM43 is found throughout the halocline. An acidic proteome supports a marine lifestyle for BS01, but gene content shows increased metabolic versatility compared to OM43 and evidence for ongoing genome-streamlining. Phylogenetic reconstruction shows that BS01 colonized the pelagic ocean independently of OM43 via convergent evolution. Salinity adaptation and differences in one-carbon and nitrogen metabolism may play a role in niche differentiation between BS01 and OM43. In particular, urea utilization by BS01 is predicted to provide an ecological advantage over OM43 given the limited amount of inorganic nitrogen in the Canada Basin. These observations provide further evidence that the Arctic Ocean is inhabited by distinct bacterial groups and that at least one group (BS01) evolved via a freshwater to marine environmental transition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genetics and Genomics of Pathogen Resistance in Switchgrass (Final Report)

This project was funded by DOE under Grant no. DE-SC0016108. Originally approved for the 2016-2019 period, two no-cost extensions were solicited and approved, which prolonged the lifespan through July 2021. This final report informs on the results obtained so far from the research implemented. The research hinged on integrating genomics (genomic selection, RNAseq, virus-plant interactions) with classical genetics (conventional breeding) to incorporate durable resistance to fungal (rust) and viral (mosaic) diseases in switchgrass (Panicum virgatum) populations being bred for bioenergy. Higher biomass yield, higher quality (low lignin content), and durable disease resistance are key features to make lignocellulosic switchgrass feedstocks economically competitive and sustainable. Genomic selection is being applied on three generations of a switchgrass population derived from crossing two ecotypes (Kanlow as lowland female and Summer as upland male) with differential performance in terms of biomass yield and quality, disease resistance, and winter survivability. Target populations were screened for rust and mosaic in field and/or lab and phenotyped for biomass yield and quality traits. Genetic analyses were applied across generations to capture the joint inheritance of the targeted traits and predict breeding values for parents and progeny with greater accuracy. Parental and a panel of different switchgrass populations were genotyped with the DArTseq technology to develop SNP (0, 1, 2) and in-silico (presence/absence) DArT markers. Rust inoculations techniques were developed and applied successfully on switchgrass. The original populations (Kanlow and Summer) were sequenced with RNAseq to capture the gene expression profiles across sequential time-points and appraise the basis of greater resistance in the Kanlow vs the Summer ecotype. Constructs of PMV and sPMV mosaic virus were assembled and tested first on proso millet to find the best protocol to use later on switchgrass. Results from the preliminary analyses indicate that 1) ample additive genetic variation is available for selection and improving this inter-ecotypic population for yield, quality, and disease traits, 2) significant gains are to be expected with the genetic correlations being favorable between yield and lignin content and between yield and disease ratings, 3) substantial differences exist in the genetic regions controlling rust resistance in the two ecotypes, 4) co-infection with PMV isolates from Nebraska and its satellite from Kansas elicit severe mosaic symptoms, and 5) two different genetic systems are responsible for imparting resistance to rust and virus in switchgrass.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mining the Penicillium expansum Genome for Virulence Genes: A Functional-Based Approach to Discover Novel Loci Mediating Blue Mold Decay of Apple Fruit

Blue mold, a postharvest disease of pome fruits, is caused by the filamentous fungus Penicillium expansum. In addition to the economic losses caused by P. expansum, food safety can be compromised, as this pathogen is mycotoxigenic. In this study, forward and reverse genetic approaches were used to identify genes involved in blue mold infection in apple fruits. For this, we generated a random T-DNA insertional mutant library. A total of 448 transformants were generated and screened for the reduced decay phenotype on apples. Of these mutants, six (T-193, T-275, T-434, T-588, T-625, and T-711) were selected for continued studies and five unique genes were identified of interest. In addition, two deletion mutants (Δt-625 and Δt-588) and a knockdown strain (t-434 KD ) were generated for three loci. Data show that the Δt-588 mutant phenocopied the T-DNA insertion mutant and had virulence penalties during apple fruit decay. We hypothesize that this locus encodes a glyoxalase due to bioinformatic predictions, thus contributing to reduced colony diameter when grown in methylglyoxal (MG). This work presents novel members of signaling networks and additional genetic factors that regulate fungal virulence in the blue mold fungus during apple fruit decay.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Strategies for community-sourced biocuration in bioinformatics: a case study on MIBiG 4.0

Biocuration is essential to transform molecular sequence data into standardized, machine-readable resources. Such curated datasets enable comparative analysis, predictive modeling, and data integration across bioinformatics platforms. While professional biocuration is resource-intensive and usually limited to institutional settings, community-driven approaches can mobilize large-scale annotation of specialized datasets and are more resilient to disruptions in scientific funding. Here, we present a model for community-powered curation applied to the Minimum Information about a Biosynthetic Gene Cluster (MIBiG) repository. Through a framework of workflows for metadata capture, annotation validation, and contributor coordination, the MIBiG 4.0 initiative recruited 267 scientists across 178 institutions from 33 countries, volunteering an estimated 4000 h of work. These efforts expanded the MIBiG repository by 22% and enhanced its usability in downstream molecular data analyses in comparative genomic analyses, natural product discovery, and machine learning applications. We provide strategies and actionable lessons for adopting this model, supporting the sustainability of curated bioinformatics resources central to nucleic acid research and related fields.

biocuration↗
DOE OSTI2021

Random sub-diffusion and capture of genes by the nuclear pore reduces dynamics and coordinates inter-chromosomal movement

Hundreds of genes interact with the yeast nuclear pore complex (NPC), localizing at the nuclear periphery and clustering with co-regulated genes. Dynamic tracking of peripheral genes shows that they cycle on and off the NPC and that interaction with the NPC slows their sub-diffusive movement. Furthermore, NPC-dependent inter-chromosomal clustering leads to coordinated movement of pairs of loci separated by hundreds of nanometers. We developed fractional Brownian motion simulations for chromosomal loci in the nucleoplasm and interacting with NPCs. These simulations predict the rate and nature of random sub-diffusion during repositioning from nucleoplasm to periphery and match measurements from two different experimental models, arguing that recruitment to the nuclear periphery is due to random sub-diffusion and transient capture by NPCs. Finally, the simulations do not lead to inter-chromosomal clustering or coordinated movement, suggesting that interaction with the NPC is necessary, but not sufficient, to cause clustering.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genome-scale metabolic rewiring improves titers rates and yields of the non-native product indigoidine at scale

Abstract High titer, rate, yield (TRY), and scalability are challenging metrics to achieve due to trade-offs between carbon use for growth and production. To achieve these metrics, we take the minimal cut set (MCS) approach that predicts metabolic reactions for elimination to couple metabolite production strongly with growth. We compute MCS solution-sets for a non-native product indigoidine, a sustainable pigment, in Pseudomonas putida KT2440, an emerging industrial microbe. From the 63 solution-sets, our omics guided process identifies one experimentally feasible solution requiring 14 simultaneous reaction interventions. We implement a total of 14 genes knockdowns using multiplex-CRISPRi. MCS-based solution shifts production from stationary to exponential phase. We achieve 25.6 g/L, 0.22 g/l/h, and ~50% maximum theoretical yield (0.33 g indigoidine/g glucose). These phenotypes are maintained from batch to fed-batch mode, and across scales (100-ml shake flasks, 250-ml ambr®, and 2-L bioreactors).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

pH Homeostasis and Sodium Ion Pumping by Multiple Resistance and pH Antiporters in Pyrococcus furiosus

Multiple Resistance and pH (Mrp) antiporters are seven-subunit complexes that couple transport of ions across the membrane in response to a proton motive force (PMF) and have various physiological roles, including sodium ion sensing and pH homeostasis. The hyperthermophilic archaeon Pyrococcus furiosus contains three copies of Mrp encoding genes in its genome. Two are found as integral components of two respiratory complexes, membrane bound hydrogenase (MBH) and the membrane bound sulfane sulfur reductase (MBS) that couple redox activity to sodium translocation, while the third copy is a stand-alone Mrp. Sequence alignments show that this Mrp does not contain an energy-input (PMF) module but contains all other predicted functional Mrp domains. The P. furiosus Mrp deletion strain exhibits no significant changes in optimal pH or sodium ion concentration for growth but is more sensitive to medium acidification during growth. Cell suspension hydrogen gas production assays using the deletion strain show that this Mrp uses sodium as the coupling ion. Mrp likely maintains cytoplasmic pH by exchanging protons inside the cell for extracellular sodium ions. Deletion of the MBH sodium-translocating module demonstrates that hydrogen gas production is uncoupled from ion pumping and provides insights into the evolution of this Mrp-containing respiratory complex.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Catabolic pathway acquisition by rhizosphere bacteria readily enables growth with a root exudate component but does not affect root colonization

Horizontal gene transfer (HGT) is a fundamental evolutionary process that plays a key role in bacterial evolution. The likelihood of a successful transfer event is expected to depend on the precise balance of costs and benefits resulting from pathway acquisition. Most experimental analyses of HGT have focused on phenotypes that have large fitness benefits under appropriate selective conditions, such as antibiotic resistance. However, many examples of HGT involve phenotypes that are predicted to provide smaller benefits, such as the ability to catabolize additional carbon sources. We have experimentally simulated the consequences of one such HGT event in the laboratory, studying the effects of transferring a pathway for catabolism of the plant-derived aromatic compound salicyl alcohol between rhizosphere isolates from the Pseudomonas genus. We find that pathway acquisition enables rapid catabolism of salicyl alcohol with only minor disruptions to the existing metabolic and regulatory networks of the new host. However, this new catabolic potential does not confer a measurable fitness advantage during competitive growth in the rhizosphere. We conclude that the phenotype of salicyl alcohol catabolism is readily transferable but is selectively neutral under environmentally relevant conditions. We propose that this condition is common and that HGT of many pathways will be self-limiting because the selective benefits are small.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Eco-evolutionary strategies for relieving carbon limitation under salt stress differ across microbial clades

With the continuous expansion of saline soils under climate change, understanding the eco-evolutionary tradeoff between the microbial mitigation of carbon limitation and the maintenance of functional traits in saline soils represents a significant knowledge gap in predicting future soil health and ecological function. Through shotgun metagenomic sequencing of coastal soils along a salinity gradient, we show contrasting eco-evolutionary directions of soil bacteria and archaea that manifest in changes to genome size and the functional potential of the soil microbiome. In salt environments with high carbon requirements, bacteria exhibit reduced genome sizes associated with a depletion of metabolic genes, while archaea display larger genomes and enrichment of salt-resistance, metabolic, and carbon-acquisition genes. This suggests that bacteria conserve energy through genome streamlining when facing salt stress, while archaea invest in carbon-acquisition pathways to broaden their resource usage. These findings suggest divergent directions in eco-evolutionary adaptations to soil saline stress amongst microbial clades and serve as a foundation for understanding the response of soil microbiomes to escalating climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cryptic cycling by electroactive bacterioplankton in Trout Bog Lake

The potential for extracellular electron transfer (EET) is a prevailing genomic feature of humic lake bacterioplankton. However, there has been little evidence for the substantial ecological contribution predicted by genetics. We hypothesized that anoxygenic phototrophic electrotrophs and accompanying heterotrophic electrogens cycle dissolved organic matter (DOM) between oxidized and reduced states. We predicted that such bacterioplankton would exhibit diel-scale oscillations due to the light dependency of photosynthesis. Using Trout Bog Lake in Wisconsin, USA, as our model ecosystem, we profiled the water column with depth-discrete metagenomic, physiochemical, and electrochemical analyses. We observed variation in oxidation reduction potential (ORP) in response to sunlight, initiating at depths populated by anoxygenic phototrophs with EET genes. We developed an automated buoy to measure electric current flow between many pairs of electrodes simultaneously, observing correlation in electron consumption to sunlight. Our results, combined with published metatranscriptomic analysis, indicate the occurrence of electron cycling between phototrophic oxidation (electrotrophic metabolism) by Chlorobium and anaerobic respiration (electrogenic metabolism) by Geothrix, involving DOM. We also repeatedly observed gradual seasonal increases in hypolimnion ORP throughout summer. These diel and seasonal patterns imply that electroactive DOM mediates the ecology of electroactive bacteria in lakes, controlling humic lake methane emissions.IMPORTANCEWe investigated the physical, chemical, and redox characteristics of a bog lake and electrodes hung therein to test the hypothesis that dissolved organic matter is being cycled between oxidized and reduced states by electroactive bacterioplankton powered by phototrophy. To do so, we performed field-based analyses on multiple timescales using both established and novel instrumentation. We paired these analyses with recently developed bioinformatics pipelines for metagenomics data to investigate genes that enable electroactive metabolism and accompanying metabolisms. Our results are consistent with our hypothesis and yet upend some of our other expectations. Our findings have implications for understanding greenhouse gas emissions from lakes, including electroactivity as an integral part of lake metabolism throughout more of the anoxic parts of lakes and for a longer portion of the summer than expected. Our results also give a sense of what electroactivity occurs at given depths and provide a strong basis for future studies.

carbon emissions↗
DOE OSTI2023

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗