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DOE OSTI2024

Multiplex characterization of microbial traits using dual barcoded nucleic acid fragment expression library

Disclosed herein are barcoded expression libraries comprising a plurality of expression vectors, wherein each expression vector comprises a nucleic acid fragment flanked by a first barcode and a second barcode. Further disclosed herein are methods of making the barcoded expression libraries and methods of conducting functional analysis using the barcoded expression libraries.

Mutalik, Vivek K.↗

DOE OSTI2021

MetFish: a Metabolomics Pipeline for Studying Microbial Communities in Chemically Extreme Environments

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here, we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exometabolomics analysis in sample matrices containing up to 2 M total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and it can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5 to 6 orders of magnitude) with excellent linearity, and low median interday reproducibility (e.g., 2.6%). MetFish was successfully applied in targeted and untargeted exometabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exometabolome during community succession; in situ in a native prairie soil, whose exometabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exometabolome over time in the well.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Genome-resolved metagenomics reveals role of iron metabolism in drought-induced rhizosphere microbiome dynamics

Recent studies have demonstrated that drought leads to dramatic, highly conserved shifts in the root microbiome. At present, the molecular mechanisms underlying these responses remain largely uncharacterized. Here we employ genome-resolved metagenomics and comparative genomics to demonstrate that carbohydrate and secondary metabolite transport functionalities are overrepresented within drought-enriched taxa. These data also reveal that bacterial iron transport and metabolism functionality is highly correlated with drought enrichment. Using time-series root RNA-Seq data, we demonstrate that iron homeostasis within the root is impacted by drought stress, and that loss of a plant phytosiderophore iron transporter impacts microbial community composition, leading to significant increases in the drought-enriched lineage, Actinobacteria. Finally, we show that exogenous application of iron disrupts the drought-induced enrichment of Actinobacteria, as well as their improvement in host phenotype during drought stress. Collectively, our findings implicate iron metabolism in the root microbiome’s response to drought and may inform efforts to improve plant drought tolerance to increase food security.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Neotropical termite microbiomes as sources of novel plant cell wall degrading enzymes

In this study, we used shotgun metagenomic sequencing to characterise the microbial metabolic potential for lignocellulose transformation in the gut of two colonies of Argentine higher termite species with different feeding habits, Cortaritermes fulviceps and Nasutitermes aquilinus. Our goal was to assess the microbial community compositions and metabolic capacity, and to identify genes involved in lignocellulose degradation. Individuals from both termite species contained the same five dominant bacterial phyla (Spirochaetes, Firmicutes, Proteobacteria, Fibrobacteres and Bacteroidetes) although with different relative abundances. However, detected functional capacity varied, with C. fulviceps (a grass-wood-feeder) gut microbiome samples containing more genes related to amino acid metabolism, whereas N. aquilinus (a wood-feeder) gut microbiome samples were enriched in genes involved in carbohydrate metabolism and cellulose degradation. The C. fulviceps gut microbiome was enriched specifically in genes coding for debranching- and oligosaccharide-degrading enzymes. These findings suggest an association between the primary food source and the predicted categories of the enzymes present in the gut microbiomes of each species. To further investigate the termite microbiomes as sources of biotechnologically relevant glycosyl hydrolases, a putative GH10 endo-β-1,4-xylanase, Xyl10E, was cloned and expressed in Escherichia coli. Functional analysis of the recombinant metagenome-derived enzyme showed high specificity towards beechwood xylan (288.1 IU/mg), with the optimum activity at 50 °C and a pH-activity range from 5 to 10. These characteristics suggest that Xy110E may be a promising candidate for further development in lignocellulose deconstruction applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Ecological insights into soil health according to the genomic traits and environment-wide associations of bacteria in agricultural soils

Abstract Soil microbiomes are sensitive to current and previous soil conditions, and bacterial ‘bioindicators’ of biological, physical, and chemical soil properties have considerable potential for soil health assessment. However, the lack of ecological or physiological information for most soil microorganisms limits our ability to interpret the associations of bioindicators and, thus, their utility for guiding management. We identified bioindicators of tillage intensity and twelve soil properties used to rate soil health using a 16S rRNA gene-based survey of farmland across North America. We then inferred the genomic traits of bioindicators and evaluated their environment-wide associations (EWAS) with respect to agricultural management practice, disturbance, and plant associations with 89 studies from agroecosystems. Most bioindicators were either positively correlated with biological properties (e.g., organic matter) or negatively correlated with physical and chemical properties. Higher soil health ratings corresponded with smaller genome size and higher coding density, while lower ratings corresponded with larger genomes and higher rrn copy number. Community-weighted genome size explained most variation in health ratings. EWAS linked prominent bioindicators with the impacts of environmental disturbances. Our findings provide ecological insights into bioindicators of soil properties relevant to soil health management, illustrating the tight coupling of microbiome and soil function.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Community‐Level Metabolic Shifts Following Land Use Change in the Amazon Rainforest Identified by a Supervised Machine Leaning Approach

ABSTRACT The Amazon rainforest has been subjected to high rates of deforestation, mostly for pasturelands, over the last few decades. This change in plant cover is known to alter the soil microbiome and the functions it mediates, but the genomic changes underlying this response are still unresolved. In this study, we used a combination of deep shotgun metagenomics complemented by a supervised machine learning approach to compare the metabolic strategies of tropical soil microbial communities in pristine forests and long‐term established pastures in the Amazon. Machine learning‐derived metagenome analysis indicated that microbial community structures (bacteria, archaea and viruses) and the composition of protein‐coding genes were distinct in each plant cover type environment. Forest and pasture soils had different genomic diversities for the above three taxonomic groups, characterised by their protein‐coding genes. These differences in metagenome profiles in soils under forests and pastures suggest that metabolic strategies related to carbohydrate and energy metabolisms were altered at community level. Changes were also consistent with known modifications to the C and N cycles caused by long‐term shifts in aboveground vegetation and were also associated with several soil physicochemical properties known to change with land use, such as the C/N ratio, soil temperature and exchangeable acidity. In addition, our analysis reveals that these alterations in land use can also result in changes to the composition and diversity of the soil DNA virome. Collectively, our study indicates that soil microbial communities shift their overall metabolic strategies, driven by genomic alterations observed in pristine forests and long‐term established pastures with implications for the C and N cycles.

carbon and nitrogen cycles↗

DOE OSTI2019

Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Root Influences on Mobilization and Export of Mineral-bound Soil Organic Matter

Biogeochemical cycles within mountainous watersheds are key regulators of ecosystem carbon storage and downstream nutrient loadings, and they have shown to be particularly vulnerable to climate change impacts. Increasing temperature and persistent droughts have already dramatically changed vegetation cover across the mountainous western US, with unknown consequences for soil carbon and nutrient cycles belowground. What remains elusive is to what extent associated changes in root-soil interactions may mobilize the vast pool of organic matter (OM) that has been stabilized by associations with minerals for centuries or millennia. Although plant root-driven OM mobilization from minerals may be a central control on carbon loss and nutrient export, such mechanisms are currently missing from conceptual and numerical models. The overall objective of this Exploratory Project is to identify the biogeochemical mechanisms by which roots destabilize mineral-associated organic matter (MAOM) and the cumulative impact on carbon and nutrient fate. To accomplish this goal, we integrated well-controlled laboratory experiments with in-field measurements and a scalable modeling approach. First, we conducted model system experiments to assess the vulnerability of MAOM to exudate-mediated mechanisms. Our results show that common root exudates effectively destabilize MAOM not only through direct, ligand-driven mobilization mechanisms, but also indirect, microbially-mediated mechanisms relying on secondary metabolites and enzymes. We further found that OM bound to poorly crystalline Fe and Al (hydr)oxides is more vulnerable to exudate-induced destabilization than OM bound to more crystalline phases, particularly in response to direct, ligand-promoted mechanisms. These findings demonstrate that the stability of MAOM is not just a function of their inherent properties, but also will depend in large parts on the ability of plant roots and microbes to produce exudates capable of triggering suitable mobilization mechanisms. We further employed a well-controlled rhizobox approach, combining advanced microsensor and mass spectrometry techniques, to resolve spatiotemporal variations in the composition and availability of exudates along single growing roots of grasses. Our results show that the composition of functionally relevant exudate compounds varies at extremely short time scales, seemingly shifting from ligands such as aromatic acids around root tips to less reactive metabolites such as amino acids around mature root segments. These results suggest a prevalence of direct MAOM mobilization mechanisms around the root tip, while indirect MAOM mobilization strategies may dominate around more mature root segments. Additionally, we utilized microsensor measurements in rhizoboxes to parameterize a rhizosphere (hydro)biogeochemistry reactive transport model (eSTOMP-ROOTS). The resulting model was used to assess how root exudations affects the stability of MAOM. Model simulations show that diel pulses of root exudation are strong enough to cause oscillations in biogeochemical conditions—particularly in pH, oxygen concentrations, and microbial activity— that repeatedly disrupt MAOM. Finally, we assessed field-scale impacts of root-driven MAOM destabilization over short and long time scales. A combination of in-field incubations and field-based characterizations showed that MAOM may not only be vulnerable to seasonal variations in root activity, but also to root-driven weathering over pedogenic time scales. In sum, results from our Exploratory Award highlight the strong control plant roots exert on MAOM mobilization and, thus, on the potential for carbon and nutrient export from watersheds.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Functional and evolutionary characterization of a secondary metabolite gene cluster in budding yeasts

Secondary metabolites are key in how organisms from all domains of life interact with their environment and each other. The iron-binding molecule pulcherrimin was described a century ago, but the genes responsible for its production in budding yeasts have remained uncharacterized. In this study, we used phylogenomic footprinting on 90 genomes across the budding yeast subphylum Saccharomycotina to identify the gene cluster associated with pulcherrimin production. Using targeted gene replacements in Kluyveromyces lactis, we characterized the four genes that make up the cluster, which likely encode two pulcherriminic acid biosynthesis enzymes, a pulcherrimin transporter, and a transcription factor involved in both biosynthesis and transport. The requirement of a functional putative transporter to utilize extracellular pulcherrimin-complexed iron demonstrates that pulcherriminic acid is a siderophore, a chelator that binds iron outside the cell for subsequent uptake. Surprisingly, we identified homologs of the putative transporter and transcription factor genes in multiple yeast genera that lacked the biosynthesis genes and could not make pulcherrimin, including the model yeast Saccharomyces cerevisiae. We deleted these previously uncharacterized genes and showed they are also required for pulcherrimin utilization in S. cerevisiae, raising the possibility that other genes of unknown function are linked to secondary metabolism. Lastly, phylogenetic analyses of this gene cluster suggest that pulcherrimin biosynthesis and utilization were ancestral to budding yeasts, but the biosynthesis genes and, subsequently, the utilization genes, were lost in many lineages, mirroring other microbial public goods systems that lead to the rise of cheater organisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Nutrient Exposure Alters Microbial Composition, Structure, and Mercury Methylating Activity in Periphyton in a Contaminated Watershed

The conversion of mercury (Hg) to monomethylmercury (MMHg) is a critical area of concern in global Hg cycling. Periphyton biofilms may harbor significant amounts of MMHg but little is known about the Hg-methylating potential of the periphyton microbiome. Therefore, we used high-throughput amplicon sequencing of the 16S rRNA gene, ITS2 region, and Hg methylation gene pair (hgcAB) to characterize the archaea/bacteria, fungi, and Hg-methylating microorganisms in periphyton communities grown in a contaminated watershed in East Tennes(see United States). Furthermore, we examined how nutrient amendments (nitrate and/or phosphate) altered periphyton community structure and function. We found that bacterial/archaeal richness in experimental conditions decreased in summer and increased in autumn relative to control treatments, while fungal diversity generally increased in summer and decreased in autumn relative to control treatments. Interestingly, the Hg-methylating communities were dominated by Proteobacteria followed by Candidatus Atribacteria across both seasons. Surprisingly, Hg methylation potential correlated with numerous bacterial families that do not contain hgcAB, suggesting that the overall microbiome structure of periphyton communities influences rates of Hg transformation within these microbial mats. To further explore these complex community interactions, we performed a microbial network analysis and found that the nitrate-amended treatment resulted in the highest number of hub taxa that also corresponded with enhanced Hg methylation potential. This work provides insight into community interactions within the periphyton microbiome that may contribute to Hg cycling and will inform future research that will focus on establishing mixed microbial consortia to uncover mechanisms driving shifts in Hg cycling within periphyton habitats.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Soils and sediments host Thermoplasmata archaea encoding novel copper membrane monooxygenases (CuMMOs)

Copper membrane monooxygenases (CuMMOs) play critical roles in the global carbon and nitrogen cycles. Organisms harboring these enzymes perform the first, and rate limiting, step in aerobic oxidation of ammonia, methane, or other simple hydrocarbons. Within archaea, only organisms in the order Nitrososphaerales (Thaumarchaeota) encode CuMMOs, which function exclusively as ammonia monooxygenases. From grassland and hillslope soils and aquifer sediments, we identified 20 genomes from distinct archaeal species encoding divergent CuMMO sequences. These archaea are phylogenetically clustered in a previously unnamed Thermoplasmatota order, herein named the Ca. Angelarchaeales. The CuMMO proteins in Ca. Angelarchaeales are more similar in structure to those in Nitrososphaerales than those of bacteria, and contain all functional residues required for general monooxygenase activity. Ca. Angelarchaeales genomes are significantly enriched in blue copper proteins (BCPs) relative to sibling lineages, including plastocyanin-like electron carriers and divergent nitrite reductase-like (nirk) 2-domain cupredoxin proteins co-located with electron transport machinery. Ca. Angelarchaeales also encode significant capacity for peptide/amino acid uptake and degradation and share numerous electron transport mechanisms with the Nitrososphaerales. Ca. Angelarchaeales are detected at high relative abundance in some of the environments where their genomes originated from. While the exact substrate specificities of the novel CuMMOs identified here have yet to be determined, activity on ammonia is possible given their metabolic and ecological context. The identification of an archaeal CuMMO outside of the Nitrososphaerales significantly expands the known diversity of CuMMO enzymes in archaea and suggests previously unaccounted organisms contribute to critical global nitrogen and/or carbon cycling functions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Increasing Bacterial Tolerance and Metabolism of the Biofuel, N-Butanol Using Community-Level Evolution and Functional Genomics

Bioremediation capability should be developed along with biofuel technology to mitigate the potential damage of future spills. One biofuel that is being developed is biobutanol, since n-butanol is more energy dense and less volatile than ethanol. A bottleneck for industrial production of biobutanol is its toxicity; most microbes cannot survive about 1.5% v/v. Thus, microbial bioremediation of n-butanol would need microbes that can both tolerate and metabolize butanol. We used ecological and evolutionary biology approaches to find bacteria that could tolerate and metabolize butanol. We then tried to increase the metabolism of butanol by promising bacterial strains and communities. Ecological community-level assays and screenings were conducted followed by 16S amplicon sequencing to identify butanol-tolerant artificial bacterial communities. Promising communities were then tested for growth with butanol as the sole carbon source. Secondly, we looked for bacteria with alcohol dehydrogenase enzymes and looked to increase butanol metabolism. We found that the tolerance for n-butanol may be improved with repeated exposure, but it was difficult to switch from tolerance to metabolism. Bacterial community v dynamics may be influenced by n-butanol concentration, and there was putative butanol metabolism found with both research approaches.

09 BIOMASS FUELS↗

DOE OSTI2019

Climatic controls of decomposition drive the global biogeography of forest-tree symbioses

The identity of the dominant microbial symbionts in a forest determines the ability of trees to access limiting nutrients from atmospheric or soil pools, sequester carbon and withstand the impacts of climate change. Characterizing the global distribution of symbioses, and identifying the factors that control it, are thus integral to understanding present and future forest ecosystem functioning. In this work we generate the first spatially explicit global map of forest symbiotic status using a database of over 1.1 million forest inventory plots with over 28,000 tree species. Our analyses indicate that climatic variables, and in particular climatically-controlled variation in decomposition rate, are the primary drivers of the global distribution of major symbioses. We estimate that ectomycorrhizal (EM) trees, which represent only 2% of all plant species, constitute approximately 60% of tree stems on Earth. EM symbiosis dominates forests where seasonally cold and dry climates inhibit decomposition, and are the predominant symbiosis at high latitudes and elevation. On the other hand, arbuscular mycorrhizal (AM) trees dominate aseasonally warm tropical forests and occur with EM trees in temperate biomes where seasonally warm-and-wet climates enhance decomposition. Continental transitions between AM and EM dominated forests occur relatively abruptly along climate driven decomposition gradients, which is likely caused by positive plant-microbe feedbacks. Symbiotic N-fixers, which are insensitive to climatic controls on decomposition compared with mycorrhizal fungi, are most abundant in arid biomes with alkaline soils and high maximum temperatures. The climatically driven global symbiosis gradient we document represents the first spatially-explicit, quantitative understanding of microbial symbioses at the global scale and demonstrates the critical role of microbial mutualisms in shaping the distribution of plant species.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Biological Mechanisms May Contribute to Soil Carbon Saturation Patterns: Modeling Archive

This Modeling Archive is in support of a TES-SFA publication “Biological Mechanisms May Contribute to Soil Carbon Saturation Patterns” (Craig et al., 2021). We ran and evaluated a multi-assumption soil organic carbon (SOC) model to investigate whether alternative assumptions regarding constraints on soil microbial biomass could lead to soil carbon saturation patterns. We developed this model in the Multi-Assumption Architecture and Testbed (MAAT, https://github.com/walkeranthonyp/MAAT, tag: v1.2.1_Craig2021; Walker et al. 2018). Using MAAT, we embedded three alternative hypotheses in a microbially explicit three-pool SOC model: 1) the efficiency of mineral-associated SOC formation decreases as mineral-associated SOC approaches a maximum value (“Mineral saturation”), 2) the microbial biomass turnover rate increases with increasing microbial biomass (“Density-dependent turnover”), and 3) community carbon use efficiency decreases as microbial biomass increases toward an upper limit (“Density-dependent growth”). We ran a factorial combination of these hypotheses resulting in eight models for three different classes of model (linear decay, Michaelis-Menten decay, or reverse Michaelis-Menten decay), resulting in 24 models, 12 of which are presented or discussed in the related publication. Models were parameterized using values from previous studies with similar models (Wang et al. 2013, Wieder et al. 2014, Li et al. 2014, Georgiou et al. 2017, Hassink and Whitmore 1997) and ran to an approximate steady state (200 years) at six (6) different C input rates corresponding to 0.5, 1, 2, 4, 7, and 10 times the default input value. Further model details are available in the related publication. This archive contains output from three MAAT simulations, and scripts to run these simulations and process and plot the data. Simulations are labeled “lin”, “MM_highKm”, and “RMM_highKm” reflecting factorial runs for linear, Michealis-Menten, and reverse Michaelis-Menten models, respectively. This archive contains: • 3 R scripts prepended with “init_MAAT_” to initialize runs (1 for each simulation), • 1 csv file containing years over which to run simulations (“met_year.csv”), • 1 bash script (.bs) to run MAAT, • 6 XML files that are output from MAAT describing a run (2 for each simulation), • 3 model output csv files prepended by “out_” (1 for each simulation), and • 1 analysis R script for reproducing figures 3 and 4 in Craig et al. 2021. See included user guide (Craig_2021_modeling_archive_20210315.pdf) for file organization details.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Dredged sediments contain potentially beneficial microorganisms for agriculture and little harmful cyanobacteria

Soils worldwide are degrading, raising concerns about our ability to feed the growing global population. Soil amendments that can alleviate degradation are gaining attention. The application of sediments dredged from waterways to agricultural fields has increasing promise as a means for improving degraded soils. However, herbaceous plant species may have difficulty establishing on dredged material because of low nutrient availability, inhibitory levels of toxins, unsuitable moisture conditions and lack of microorganisms capable of ameliorating these characteristics. To counteract these issues, we sought to understand if the use of a cover crop would increase the abundance, diversity and function of beneficial soil microorganisms compared to harmful microorganisms in dredged sediments. We collected soil samples from two 100% dredged sediment plots, one where winter cereal rye (Secale cereal) was grown as a winter cover crop and one left fallow over the winter, followed by traditional corn (Zea mays) planting. We sampled both plots three times during the growing season: before cover crop application, following cover crop application but before corn planting and following final corn harvest. We then used high-throughput sequencing to identify the bacterial and fungal communities present in the samples. Our data show that cover crop application did not alter the microbial community in these plots. However, sampling time decreased species diversity and altered the composition of both fungal and bacterial communities recovered from these plots. Across both plots, microorganisms associated with carbon cycling were more abundant than those associated with harmful effects, including microcystin-producing cyanobacteria, which were an extremely small portion of the overall community. Our work suggests that dredged sediments have the potential to improve soil function through the addition of microorganisms associated with nutrient cycling, but a cover crop is not necessary to incur these benefits.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models

Here, we investigate whether (and how) experimental design could aid in the estimation of the precision matrix in a Gaussian chain graph model, especially the interplay between the design, the effect of the experiment and prior knowledge about the effect. Estimation of the precision matrix is a fundamental task to infer biological graphical structures like microbial networks. We compare the marginal posterior precision of the precision matrix under four priors: flat, conjugate Normal-Wishart, Normal-MGIG and a general independent. Under the flat and conjugate priors, the Laplace-approximated posterior precision is not a function of the design matrix rendering useless any efforts to find an optimal experimental design to infer the precision matrix. In contrast, the Normal-MGIG and general independent priors do allow for the search of optimal experimental designs, yet there is a sharp upper bound on the information that can be extracted from a given experiment. We confirm our theoretical findings via a simulation study comparing (i) the KL divergence between prior and posterior and (ii) the Stein’s loss difference of MAPs between random and no experiment. Our findings provide practical advice for domain scientists conducting experiments to better infer the precision matrix as a representation of a biological network.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Direct extracellular electron transfer for high electricity production by a new type of marine microalgae Nannochloropsis sp. HDY2

A growing number of autotrophic microalgae have been found to have extracellular electron transfer (EET) capabilities. However, the mechanism and function of EET pathway in microalgae have not thoroughly investigated. This study presents evidence of direct extracellular electron transfer (DEET) for impressive electricity production by a new type of marine microalgae Nannochloropsis sp. HDY2 in the single and double-chamber photosynthetic microbial fuel cells (PFMCs). The electricity generation of Nannochloropsis sp. is strongly inhibited by photosynthetic inhibitors, suggesting that electrons involved in the extracellular electron transfer (EET) of Nannochloropsis sp. are derived from photosynthesis. The results of dialysis bag and supernatant experiments suggest that Nannochloropsis sp. produce electricity by DEET. The lack of typical redox peaks in cyclic voltammetry (CV) analysis and the appearance of extracellular filamentous component (EFC) around cells support this finding. Under high light conditions, the chlorophyll a and carotenoid content of Nannochloropsis sp. rapidly decreased while the fatty acid synthesis and electricity generation increased, suggesting that the DEET pathway play an active role in the resistance to photooxidation of Nannochloropsis sp. In conclusion, this study provides the first evidence that Nannochloropsis has the capability of performing EET and sheds new light on the positive role of DEET on the environmental adaptation of Nannochloropsis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Leveraging High-resolution Molecular Composition of Soil Organic Matter to Enhance Carbon Cycling Modeling

Soils store more carbon than the atmosphere and vegetation combined, yet Earth system models still struggle to predict how this vast reservoir will respond to environmental change. A central limitation is that most soil biogeochemical models represent organic matter using bulk conceptual pools or chemically homogeneous fractions, preventing direct use of rapidly expanding molecular-scale datasets. Here we develop and test a new soil decomposition framework that explicitly integrates high-resolution information on organic matter composition. First, we construct a molecularly informed litter decomposition module in which plant inputs are partitioned into five functional compound classes—carbohydrates, proteins, lignin-like aromatics, lipids, and carbonyls—using a molecular mixing model calibrated to solid-state 13 C Nuclear Magnetic Resonance (NMR) spectra. Class-specific kinetics, lignin-dependent physical protection, and substrate-driven microbial carbon use efficiency allow the module to capture metabolic tradeoffs associated with enzyme production and nutrient limitation. We then embed this litter module within a microbially explicit whole-soil model that tracks the transformation of these compound classes through particulate organic matter, dissolved organic matter, mineral-associated organic matter, and microbial biomass. High-resolution Fourier Transform Ion Cyclotron Resonance mass spectrometry (FTICR-MS) data are used to link internal pools to measurable soil organic matter fractions and to constrain key process parameters. Applications at soil-core and ecosystem scales demonstrate that the new model reproduces observed soil respiration dynamics while providing mechanistic attribution of CO 2 fluxes to specific chemical classes and pools. Compared to existing frameworks such as the Community Land Model soil biogeochemistry module and the Millennial model, our approach maintains competitive predictive skill while substantially improving interpretability and opportunities for data–model integration. This work illustrates a viable pathway for leveraging molecular-scale observations to reduce structural uncertainty in soil carbon–climate feedback projections.

54 ENVIRONMENTAL SCIENCES↗