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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessment of the Biological Impact of Engineered Nanomaterials Using Mass Spectrometry-based MultiOmics Approaches

The widespread use of engineered nanomaterials (ENMs) has expanded further than our understanding of their toxicity, prompting research into the biological responses against exposure to such materials. Genomics and transcriptomics have been extensively used to evaluate the biological effects of exposure to various ENMs. By determining gene activities, these studies provided valuable information to infer how cells respond to the toxicological effects of many ENMs. The application of mass spectrometry (MS)-based omics tools, such as proteomics, lipidomics, and metabolomics, offer post-genomic perspectives of what cellular processes are altered. Individually, these technologies have revealed the proteome, lipidome, and metabolome landscape upon exposure to ENMs. Together, these approaches demonstrate the ENM-induced adaptation in a broad range of cellular processes at multiple levels and the complexity of ENM-cell interactions. As a result, integrating multiple layers of MS-based omics data is trending to complement genomics data. In this review chapter, we discuss the applications of these tools for a comprehensive systems-level characterization of the biological responses induced by engineered nanomaterials.

Engineered nanomaterials, Proteomics, Metabolomics↗
DOE OSTI2020

Effects of ingested nanocellulose on intestinal microbiota and homeostasis in Wistar Han rats

Micron scale crystalline and fibrillar cellulose materials are “generally regarded as safe” (GRAS) as binders and thickeners in food products. Yet, partly due to a lack of relevant toxicological data, nanocellulose (NC) materials, which have unique properties that can be exploited to improve food quality and safety, have yet to receive FDA approval as food ingredients. Results of in vitro and in vivo toxicological studies of ingested NC, detailed in a recent companion report, revealed minimal acute in vitro cytotoxicity, and no toxicity in a subacute rat gavage model, suggesting that NC materials are non-hazardous. However, ingested materials may also modulate gut microbial populations, or alter aspects of intestinal function not evaluated in standard totoxicity testing, which could have important health implications. Here, we report the results of studies of the effects of ingested cellulose nanofibrils (CNF) on the fecal microbiome and metabolome, intestinal (ileal) epithelial cell mRNA expression of cell junction genes, and ileal cytokine production. Feces, plasma, and ileum samples were collected from Wistar Han rats before and after five weeks of biweekly gavages of water or cream, with or without 1% w/w CNF. Analysis of fecal microbial populations revealed that CNF caused changes in both genus and species diversity, with specific effects on species that produce short chain fatty acids, and that have been associated with increased IgA production and elevation of insulin levels. Fecal metabolomic analysis revealed relatively few effects of CNF, with significant changes in the levels of only ten metabolites out of 366 measured. Exposure to CNF also caused differential regulation of mRNA expression of several genes involved in epithelial cell junctions, and increased production of cytokines that both promote and inhibit proliferation of CD8 T cells. These perturbations in intestinal homeostasis contrast somewhat with the absence of in vitro and in vivo toxicity observed previously but would appear to represent minor effects. Additionally, the gut microbiome is highly sensitive to ingested substances, and such disturbances of the intestinal microbial ecosystem do not necessarily represent or predict meaningful pathology. Further studies, including chronic feeding studies, are needed to assess the real health implications, if any, of these changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Graphene oxide exposure alters gut microbial community composition and metabolism in an in vitro human model

Graphene oxide (GO) nanomaterials have unique physicochemical properties that make them highly promising for biomedical, environmental, and agricultural applications. Despite the increasing interest and the use of GO, assessments of its nanotoxicity have largely not interrogated its potential impact on the gut microbiome. This study addresses an important knowledge gap by investigating the impact of GO exposure- both at low (25 ppm) and high (250ppm) doses and fed (nutrient rich) and fasted (nutrient deplete) conditions- on the gut microbial community structure and function, using an in vitro human colon bioreactor model. 16S rRNA amplicon sequencing revealed that GO exposure resulted in a restructuring of community composition. 25 ppm GO induced a marked decrease in the Bacteroidota phylum and increased the ratio of Firmicutes to Bacteroidota (F/B). Untargeted metabolomics on the supernatants indicated that 25 ppm GO impaired microbial utilization and metabolism of substrates (amino acids, carbohydrate metabolites) and reduced production of beneficial microbial metabolites such as 5-hydroxyindole-3-acetic acid and GABA. Exposure to 250 ppm GO resulted in community composition and metabolome profiles that were very similar to the controls that lacked both GO and digestive enzymes, suggesting that high concentrations of GO may interact with digestive enzymes to form protein coronas, causing their depletion in the gut environment. Differential abundance analyses revealed that 3 genera from the phylum Bacteroidota (Bacteroides, Dysgonomonas, and Parabacteroides) were more abundant after 250 ppm GO exposure, irrespective of feed state. Integrative correlation network analysis indicated that the phylum Bacteroidota showed strong positive correlations to multiple microbial metabolites including GABA and 3-indoleacetic acid, are much larger number of correlations compared to other phyla. These results show that GO exposure has a significant impact on gut microbial community composition and metabolism and different mechanisms are at play for low and high GO concentrations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

pmartR 2.0 : A Quality Control, Visualization, and Statistics Pipeline for Multiple Omics Datatypes

The pmartR (https://github.com/pmartR/pmartR) package was designed for the quality control (QC) and analysis of mass spectrometry (MS) data, tailored to specific characteristics of proteomic (isobaric or labelled), metabolomic, and lipidomic datasets. Since its initial release, the tool has been expanded to address the needs of its growing userbase and now includes QC and statistics for nuclear magnetic resonance (NMR) metabolomic data, and leverages the DESeq2, edgeR, and limma-voom R packages for some transcriptomic data analyses. These improvements have made progress towards a unified omics processing pipeline for ease of reporting and streamlined statistical purposes. The package’s statistics and visualization capabilities have also been expanded by adding support for paired data and by integrating pmartR with the trelliscopejs R package for the quick creation of trellis displays (https://github.com/hafen/trelliscopejs). Here, we present relevant examples of each of these enhancements to pmartR and highlight how each new feature benefits the omics community.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗
DOE OSTI2024

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Mapping microhabitats of lignocellulose decomposition by a microbial consortium

The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus Leucoagaricus gongylophorus are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of Atta cephalotes fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Interactions between microbial diversity and substrate chemistry determine the fate of carbon in soil.

Microbial decomposition drives the transformation of plant-derived substrates into microbial products that form stable soil organic matter (SOM). Recent theories have posited that decomposition depends on an interaction between SOM chemistry with microbial diversity and resulting function. Here, we explicitly test these theories by coupling quantitative stable isotope probing and metabolomics to track the fate of 13C enriched substrates that vary in chemical composition as they are assimilated by microbes and transformed into new metabolic products in soil. We found that mycorrhizal-driven differences in forest nutrient economies (e.g., nutrient cycling, microbial competition) led to arbuscular mycorrhizal (AM) soils harboring greater micro8ial diversity than ectomycorrhizal (ECM) soils. When incubated with 13C enriched substrates, substrate type drove shifts in the identity of active decomposers and their metabolic products in the highly diverse AM soils. The decomposition pathways were more static in the less diverse, ECM soil. Importantly, the majority of these shifts were driven by taxa only present in the AM soil suggesting a strong link between microbial identity and specialized function. Collectively, these results highlight an important interaction between ecosystem-level processes and microbial diversity; whereby the identity and function of active decomposers impacts the composition of decomposition products that can form stable SOM.

Raczka, Nanette↗
DOE OSTI2023

Exhaled breath condensate profiles of U.S. Navy divers following prolonged hyperbaric oxygen (HBO) and nitrogen-oxygen (Nitrox) chamber exposures

Prolonged exposure to hyperbaric hyperoxia can lead to pulmonary oxygen toxicity (PO 2 tox). PO 2 tox is a mission limiting factor for special operations forces divers using closed-circuit rebreathing apparatus and a potential side effect for patients undergoing hyperbaric oxygen (HBO) treatment. In this study, we aim to determine if there is a specific breath profile of compounds in exhaled breath condensate (EBC) that is indicative of the early stages of pulmonary hyperoxic stress/PO 2 tox. Using a double-blind, randomized 'sham' controlled, cross-over design 14 U.S. Navy trained diver volunteers breathed two different gas mixtures at an ambient pressure of 2 ATA (33 fsw, 10 msw) for 6.5 h. One test gas consisted of 100% O 2 (HBO) and the other was a gas mixture containing 30.6% O 2 with the balance N 2 (Nitrox). The high O 2 stress dive (HBO) and low O 2 stress dive (Nitrox) were separated by at least seven days and were conducted dry and at rest inside a hyperbaric chamber. EBC samples were taken immediately before and after each dive and subsequently underwent a targeted and untargeted metabolomics analysis using liquid chromatography coupled to mass spectrometry (LC-MS). Following the HBO dive, 10 out of 14 subjects reported symptoms of the early stages of PO 2 tox and one subject terminated the dive early due to severe symptoms of PO 2 tox. No symptoms of PO 2 tox were reported following the nitrox dive. A partial least-squares discriminant analysis of the normalized (relative to pre-dive) untargeted data gave good classification abilities between the HBO and nitrox EBC with an AUC of 0.99 (±2%) and sensitivity and specificity of 0.93 (±10%) and 0.94 (±10%), respectively. Furthermore, the resulting classifications identified specific biomarkers that included human metabolites and lipids and their derivatives from different metabolic pathways that may explain metabolomic changes resulting from prolonged HBO exposure.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Prediction of the development of islet autoantibodies through integration of environmental, genetic, and metabolic markers

The Environmental Determinants of the Diabetes in the Young (TEDDY) study has prospectively followed, from birth, children at increased genetic risk of type 1 diabetes. We evaluated the potential of machine learning to identify new biomarkers that predict imminent (within 6 months) development of persistent islet autoantibodies to insulin, GAD or IA-2 in TEDDY participants through integration of time-invariant risk factors with time-varying metabolomics. The predictive modeling was initiated with over 220 potential biomarkers; through ensemble-based feature evaluation, the optimal model included 42 biomarkers, returning a cross-validated receiver operating characteristic area under the curve of 0.74. The model identified a principal set of 20 time-invariant markers, including 16 single nucleotide polymorphisms and two HLA-DR genotypes, gestational age, and exposure to a prebiotic formula. Integration of the metabolome identified 22 high-priority metabolites and lipids, including adipic acid and ceramide d42:0, that predicted development of islet autoantibodies, dependent upon the time horizon. The majority (86%) of metabolites that predicted development of islet autoantibodies belonged to 3 pathways: lipid oxidation, phospholipase A2 signaling, and pentose phosphate pathway. TEDDY data suggest that these metabolic processes may play a role in triggering islet autoimmunity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Endophyte‐induced systemic spatial reprogramming of metabolism in Populus trichocarpa roots under drought

Beneficial, facultative endophytes help plants thrive in challenging environments by altering their host's metabolism, but how these cellular scale metabolic changes propagate to the systems biology scale is unknown. In this work, we employed a high-resolution chemical imaging approach to map metabolic changes at the Populus trichocarpa root-zone and cell-type levels combined with machine learning (ML) models to identify root metabolites and exudates that have predictive power over treatment class. We found that a nine-strain consortium of beneficial endophytes differentially altered the metabolome of droughted root tissues in a manner specific to cell type and root zone, with endophyte abundance showing a clear correlation to individual metabolites. Our study demonstrates that integrating spatial metabolomics with ML can reveal localized metabolic patterns linked to root–microbe interactions and generate novel hypotheses about underlying biological mechanisms.

Drought↗
DOE OSTI2021

The Azospirillum brasilense Core Chemotaxis Proteins CheA1 and CheA4 Link Chemotaxis Signaling with Nitrogen Metabolism

Bacterial chemotaxis affords motile bacteria the ability to navigate the environment to locate niches for growth and survival. At the molecular level, chemotaxis depends on chemoreceptor signaling arrays that interact with cytoplasmic proteins to control the direction of movement. In Azospirillum brasilense , chemotaxis is mediated by two distinct chemotaxis pathways: Che1 and Che4. Both Che1 and Che4 are critical in the A. brasilense free-living and plant-associated lifestyles. Here, we use whole-cell proteomics and metabolomics to characterize the role of chemotaxis in A. brasilense physiology. We found that mutants lacking CheA1 or CheA4 or both are affected in nonchemotaxis functions, including major changes in transcription, signaling transport, and cell metabolism. We identify specific effects of CheA1 and CheA4 on nitrogen metabolism, including nitrate assimilation and nitrogen fixation, that may depend, at least, on the transcriptional control of rpoN , which encodes RpoN, a global regulator of metabolism, including nitrogen. Consistent with proteomics, the abundance of several nitrogenous compounds (purines, pyrimidines, and amino acids) changed in the metabolomes of the chemotaxis mutants relative to the parental strain. Further, we uncover novel, and yet uncharacterized, layers of transcriptional and posttranscriptional control of nitrogen metabolism regulators. Together, our data reveal roles for CheA1 and CheA4 in linking chemotaxis and nitrogen metabolism, likely through control of global regulatory networks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rapid screening of secondary aromatic metabolites in Populus trichocarpa leaves

Abstract Background High-throughput metabolomics analytical methodology is needed for population-scale studies of bioenergy-relevant feedstocks such as poplar ( Populus sp.). Here, the authors report the relative abundance of extractable aromatic metabolites in Populus trichocarpa leaves rapidly estimated using pyrolysis-molecular beam mass spectrometry (py-MBMS). Poplar leaves were analyzed in conjunction with and validated by GC/MS analysis of extracts to determine key spectral features used to build PLS models to predict the relative composition of extractable aromatic metabolites in whole poplar leaves. Results The Pearson correlation coefficient for the relative abundance of extractable aromatic metabolites based on ranking between GC/MS analysis and py-MBMS analysis of the Boardman leaf set was 0.86 with R 2 = 0.76 using a simplified prediction approach from select ions in MBMS spectra. Metabolites most influential to py-MBMS spectral features in the Clatskanie set included the following compounds: catechol, salicortin, salicyloyl-coumaroyl-glucoside conjugates, α-salicyloylsalicin, tremulacin, as well as other salicylates, trichocarpin, salicylic acid, and various tremuloidin conjugates. Ions in py-MBMS spectra with the highest correlation to the abundance of extractable aromatic metabolites as determined by GC/MS analysis of extracts, included m/z 68, 71, 77, 91, 94, 105, 107, 108, and 122, and were used to develop the simplified prediction approach without PLS models or a priori measurements. Conclusions The simplified py-MBMS method is capable of rapidly screening leaf tissue for relative abundance of extractable aromatic secondary metabolites to enable prioritization of samples in large populations requiring comprehensive metabolomics that will ultimately inform plant systems biology models and advance the development of optimized biomass feedstocks for renewable fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2024

Clostridium autoethanogenum alters cofactor synthesis, redox metabolism, and lysine-acetylation in response to elevated H 2 :CO feedstock ratios for enhancing carbon capture efficiency

Clostridium autoethanogenum is an acetogenic bacterium that autotrophically converts carbon monoxide (CO) and carbon dioxide (CO 2 ) gases into bioproducts and fuels via the Wood–Ljungdahl pathway (WLP). To facilitate overall carbon capture efficiency, the reaction stoichiometry requires supplementation of hydrogen at an increased ratio of H 2 :CO to maximize CO 2 utilization; however, the molecular details and thus the ability to understand the mechanism of this supplementation are largely unknown. In order to elucidate the microbial physiology and fermentation where at least 75% of the carbon in ethanol comes from CO 2 , we established controlled chemostats that facilitated a novel and high (11:1) H 2 :CO uptake ratio. We compared and contrasted proteomic and metabolomics profiles to replicate continuous stirred tank reactors (CSTRs) at the same growth rate from a lower (5:1) H 2 :CO condition where ~ 50% of the carbon in ethanol is derived from CO 2 . Our hypothesis was that major changes would be observed in the hydrogenases and/or redox-related proteins and the WLP to compensate for the elevated hydrogen feed gas. Our analyses did reveal protein abundance differences between the two conditions largely related to reduction–oxidation (redox) pathways and cofactor biosynthesis, but the changes were more minor than we would have expected. While the Wood–Ljungdahl pathway proteins remained consistent across the conditions, other post-translational regulatory processes, such as lysine-acetylation, were observed and appeared to be more important for fine-tuning this carbon metabolism pathway. Metabolomic analyses showed that the increase in H 2 :CO ratio drives the organism to higher carbon dioxide utilization resulting in lower carbon storages and accumulated fatty acid metabolite levels. This research delves into the intricate dynamics of carbon fixation in C. autoethanogenum, examining the influence of highly elevated H 2 :CO ratios on metabolic processes and product outcomes. The study underscores the significance of optimizing gas feed composition for enhanced industrial efficiency, shedding light on potential mechanisms, such as post-translational modifications (PTMs), to fine-tune enzymatic activities and improve desired product yields.

09 BIOMASS FUELS↗
DOE OSTI2022

Microbial colonization and persistence in deep fractured shales is guided by metabolic exchanges and viral predation

Background: Microbial colonization of subsurface shales following hydraulic fracturing offers the opportunity to study coupled biotic and abiotic factors that impact microbial persistence in engineered deep subsurface ecosystems. Shale formations underly much of the continental USA and display geographically distinct gradients in temperature and salinity. Complementing studies performed in eastern USA shales that contain brine-like fluids, here we coupled metagenomic and metabolomic approaches to develop the first genome-level insights into ecosystem colonization and microbial community interactions in a lower-salinity, but high-temperature western USA shale formation. Results: We collected materials used during the hydraulic fracturing process (i.e., chemicals, drill muds) paired with temporal sampling of water produced from three different hydraulically fractured wells in the STACK (Sooner Trend Anadarko Basin, Canadian and Kingfisher) shale play in OK, USA. Relative to other shale formations, our metagenomic and metabolomic analyses revealed an expanded taxonomic and metabolic diversity of microorganisms that colonize and persist in fractured shales. Importantly, temporal sampling across all three hydraulic fracturing wells traced the degradation of complex polymers from the hydraulic fracturing process to the production and consumption of organic acids that support sulfate- and thiosulfate-reducing bacteria. Furthermore, we identified 5587 viral genomes and linked many of these to the dominant, colonizing microorganisms, demonstrating the key role that viral predation plays in community dynamics within this closed, engineered system. Lastly, top-side audit sampling of different source materials enabled genome-resolved source tracking, revealing the likely sources of many key colonizing and persisting taxa in these ecosystems. Conclusions: These findings highlight the importance of resource utilization and resistance to viral predation as key traits that enable specific microbial taxa to persist across fractured shale ecosystems. We also demonstrate the importance of materials used in the hydraulic fracturing process as both a source of persisting shale microorganisms and organic substrates that likely aid in sustaining the microbial community. Moreover, we showed that different physicochemical conditions (i.e., salinity, temperature) can influence the composition and functional potential of persisting microbial communities in shale ecosystems. Together, these results expand our knowledge of microbial life in deep subsurface shales and have important ramifications for management and treatment of microbial biomass in hydraulically fractured wells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rapid remodeling of the soil lipidome in response to a drying-rewetting event

Abstract Background Microbiomes contribute to multiple ecosystem services by transforming organic matter in the soil. Extreme shifts in the environment, such as drying-rewetting cycles during drought, can impact the microbial metabolism of organic matter by altering microbial physiology and function. These physiological responses are mediated in part by lipids that are responsible for regulating interactions between cells and the environment. Despite this critical role in regulating the microbial response to stress, little is known about microbial lipids and metabolites in the soil or how they influence phenotypes that are expressed under drying-rewetting cycles. To address this knowledge gap, we conducted a soil incubation experiment to simulate soil drying during a summer drought of an arid grassland, then measured the response of the soil lipidome and metabolome during the first 3 h after wet-up. Results Reduced nutrient access during soil drying incurred a replacement of membrane phospholipids, resulting in a diminished abundance of multiple phosphorus-rich membrane lipids. The hot and dry conditions increased the prevalence of sphingolipids and lipids containing long-chain polyunsaturated fatty acids, both of which are associated with heat and osmotic stress-mitigating properties in fungi. This novel finding suggests that lipids commonly present in eukaryotes such as fungi may play a significant role in supporting community resilience displayed by arid land soil microbiomes during drought. As early as 10 min after rewetting dry soil, distinct changes were observed in several lipids that had bacterial signatures including a rapid increase in the abundance of glycerophospholipids with saturated and short fatty acid chains, prototypical of bacterial membrane lipids. Polar metabolites including disaccharides, nucleic acids, organic acids, inositols, and amino acids also increased in abundance upon rewetting. This rapid metabolic reactivation and growth after rewetting coincided with an increase in the relative abundance of firmicutes, suggesting that members of this phylum were positively impacted by rewetting. Conclusions Our study revealed specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. The drought-induced nutrient limitation was reflected in the lipidome and polar metabolome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long-chain polyunsaturated fatty acids in dry soil suggest that lipids likely play an important role in the drought tolerance of microbial taxa capable of synthesizing these lipids. An increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest a metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions.

59 BASIC BIOLOGICAL SCIENCES↗
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↗