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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Prospects for Engineering Biophysical CO 2 Concentrating Mechanisms into Land Plants to Enhance Yields

Although cyanobacteria and algae represent a small fraction of the biomass of all primary producers, their photosynthetic activity accounts for roughly half of the daily CO 2 fixation that occurs on Earth. These microorganisms are able to accomplish this feat by enhancing the activity of the CO 2 -fixing enzyme Rubisco using biophysical CO 2 concentrating mechanisms (CCMs). Biophysical CCMs operate by concentrating bicarbonate and converting it into CO 2 in a compartment that houses Rubisco (in contrast with other CCMs that concentrate CO 2 via an organic intermediate, such as malate in the case of C 4 CCMs). This activity provides Rubisco with a high concentration of its substrate, thereby increasing its reaction rate. The genetic engineering of a biophysical CCM into land plants is being pursued as a strategy to increase crop yields. This review focuses on the progress toward understanding the molecular components of cyanobacterial and algal CCMs, as well as recent advances toward engineering these components into land plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Integrating Systems and Synthetic Biology to Understand and Engineer Microbiomes

Microbiomes are complex and ubiquitous networks of microorganisms whose seemingly limitless chemical transformations could be harnessed to benefit agriculture, medicine, and biotechnology. Here, the spatial and temporal changes in microbiome composition and function are influenced by a multitude of molecular and ecological factors. This complexity yields both versatility and challenges in designing synthetic microbiomes and perturbing natural microbiomes in controlled, predictable ways. In this review, we describe factors that give rise to emergent spatial and temporal microbiome properties and the meta-omics and computational modeling tools that can be used to understand microbiomes at the cellular and system levels. We also describe strategies for designing and engineering microbiomes to enhance or build novel functions. Throughout the review,we discuss key knowledge and technology gaps for elucidating the networks and deciphering key control points for microbiome engineering, and highlight examples where multiple omics and modeling approaches can be integrated to address these gaps.

42 ENGINEERING↗
DOE OSTI2024

Biological Upcycling of Plastics Waste

Plastic wastes accumulate in the environment, impacting wildlife and human health and representing a significant pool of inexpensive waste carbon that could form feedstock for the sustainable production of commodity chemicals, monomers, and specialty chemicals. Current mechanical recycling technologies are not economically attractive due to the lower-quality plastics that are produced in each iteration. Thus, the development of a plastics economy requires a solution that can deconstruct plastics and generate value from the deconstruction products. Biological systems can provide such value by allowing for the processing of mixed plastics waste streams via enzymatic specificity and using engineered metabolic pathways to produce upcycling targets. We focus on the use of biological systems for waste plastics deconstruction and upcycling. We highlight documented and predicted mechanisms through which plastics are biologically deconstructed and assimilated and provide examples of upcycled products from biological systems. Additionally, we detail current challenges in the field, including the discovery and development of microorganisms and enzymes for deconstructing non–polyethylene terephthalate plastics, the selection of appropriate target molecules to incentivize development of a plastic bioeconomy, and the selection of microbial chassis for the valorization of deconstruction products.

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

Stepping on the Gas to a Circular Economy: Accelerating Development of Carbon-Negative Chemical Production from Gas Fermentation

Owing to rising levels of greenhouse gases in our atmosphere and oceans, climate change poses significant environmental, economic, and social challenges globally. Technologies that enable carbon capture and conversion of greenhouse gases into useful products will help mitigate climate change by enabling a new circular carbon economy. Gas fermentation using carbon-fixing microorganisms offers an economically viable and scalable solution with unique feedstock and product flexibility that has been commercialized recently. Here, we review the state of the art of gas fermentation and discuss opportunities to accelerate future development and rollout. We discuss the current commercial process for conversion of waste gases to ethanol, including the underlying biology, challenges in process scale-up, and progress on genetic tool development and metabolic engineering to expand the product spectrum. We emphasize key enabling technologies to accelerate strain development for acetogens and other nonmodel organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Soil Microbiomes Under Climate Change and Implications for Carbon Cycling

Communities of soil microorganisms (soil microbiomes) play a major role in biogeochemical cycles and support of plant growth. Here we focus primarily on the roles that the soil microbiome plays in cycling soil organic carbon and the impact of climate change on the soil carbon cycle. We first discuss current challenges in understanding the roles carried out by highly diverse and heterogeneous soil microbiomes and review existing knowledge gaps in understanding how climate change will impact soil carbon cycling by the soil microbiome. Because soil microbiome stability is a key metric to understand as the climate changes, we discuss different aspects of stability, including resistance, resilience, and functional redundancy. We then review recent research pertaining to the impact of major climate perturbations on the soil microbiome and the functions that they carry out. Finally, we review new experimental methodologies and modeling approaches under development that should facilitate our understanding of the complex nature of the soil microbiome to better predict its future responses to climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ShadeLab/PAPER_Howe_2023_switchgrass_MetaT

The raw data (metagenomes and metatranscriptomes) for this study are available in the Joint Genomes Institute Genome Portal (https://genome.jgi.doe.gov/portal/ Project ID 503249) with projects designated by year and product type. The MAG genomes analyzed in this paper are available on NCBI, as bioproject PRJNA800073. Plants and microorganisms form beneficial associations. Understanding plant-microbe interactions will inform microbiome management to enhance crop productivity and resilience to stress. Here, we apply a genome-centric approach to identify ecologically important leaf microbiome members on field-grown switchgrass and miscanthus and to quantify their activities for switchgrass over two growing seasons. We integrate metagenome and metatranscriptome sequencing from 192 leaf samples collected over representative time points in crop phenology. We curated 40 medium- and high-quality metagenome-assembled-genomes (MAGs) and focused analysis on seasonal transcript recruitment to them. Classes represented by these focal MAGs (Actinomycetia, Alpha- and Gamma- Proteobacteria, and Bacteroidota) were active and had increases in transcripts for short-chain dehydrogenase, molybdopterin oxidoreductase, and polyketide cyclase in the late season. The majority of MAGs had activated stress-associated pathways, including trehalose metabolism, indole acetic acid degradation, betaine biosynthesis, and reactive oxygen species degradation, suggesting direct engagement with the host environment. We also detected seasonally activated biosynthetic pathways for terpenes (carotenoids and isoprenoids) and for various non-ribosomal peptide pathways that were poorly annotated. Overall, this study overcame laboratory and bioinformatic challenges associated with field-based leaf metatranscriptome analysis to inform both general and likely specialized activities of these phyllosphere populations. These activities collectively support that leaf-associated bacterial populations are seasonally dynamic, responsive to host cues, and interactively engage in feedback with the plant. This analysis represented quality filtering of metagenomes and metatranscriptomes (data-preparation folder), metagenome assemblies (metagenome-assembly folder) and metagenome-assembled genome binning, curation, refinement, annotation (mag-evaluation folder). Abundances of sequencing libraries were calculated based on reads mapped (mapping folder). Additionallly, analysis of our annotated results are also included (analysis folder).

Howe, Adina↗
DOE OSTI2025

Knowledge Oriented Graph Unified Transformer (KOGUT) v0.1

KOGUT — Knowledge Oriented Graph Unified Transformer KOGUT implements the Relational Graph Transformer (RelGT) architecture for knowledge graph link prediction in biological domains, with a primary focus on microbial growth media prediction. While the original RelGT (arXiv:2505.10960) targets relational tables, time series, and multi-table databases, KOGUT adapts this architecture for heterogeneous biological knowledge graphs, providing first-in-class AI predictive models for microbial cultivation. Key Adaptations Beyond Original RelGT: - Knowledge Graph Focus: Applied to biological KGs with semantic node types (taxa, chemicals, media, phenotypes, environments) versus generic relational database tables, trained on the KG-Microbe knowledge graph (1.3M entities, 2.9M edges, 24 relation types). - Multimodal Node Encoding: Integrates node labels, categories, descriptions, and synonyms from KG metadata through learned embedding layers—adapting relational column features to graph node attributes with textual semantics. - Extended K-Hop Subgraph Strategy: Optimized neighborhood sampling (3-hop default, configurable up to 200 nodes) tuned for sparse biological networks, building on the original local-global attention framework with biological relation preservation. - Biolink Predicate Preservation: Type-specific transformations for 24 biological edge semantics (occurs_in, consumes, produces, has_phenotype, subclass_of) beyond standard relational foreign keys, enabling multi-relation link prediction. - Inductive Learning Support: Enables zero-shot predictions for novel taxa through feature-based embeddings (temperature, oxygen requirements, gram stain, cell shape), extending the original transductive relational benchmark scope to uncultured microorganisms. CheapSOTA Performance Optimizations (This Distribution): - VQ-EMA Centroid Attention: Vector quantization with exponential moving average for improved global context modeling (+5-10% MRR improvement). - HDF5 Precomputed Data Loading: One-time preprocessing of k-hop subgraphs to eliminate redundant graph traversals (2-5× training speedup). - Distributed Data Parallel Training: Multi-GPU support for scaling to larger knowledge graphs (tested on 4× NVIDIA A100 GPUs at NERSC Perlmutter). - Mixed Precision Training: Automatic mixed precision (AMP) for memory efficiency and faster training. Advantages Over Standard Knowledge Graph Embedding Models: Combines RelGT's proven multi-element tokenization (features, type, hop, structure) with graph-native biological representations, enabling interpretable link prediction across heterogeneous entities that standard embedding models (TransE, RotatE, ComplEx) and table-based transformers cannot directly model. Achieves near-perfect performance on microbial growth media prediction (MRR: 0.9966, Precision@1: 0.9932, Hit@10: 1.0000) while maintaining explainability through attention-based reasoning over biological pathways. Training Data: - KG-Microbe merged knowledge graph: 1,379,337 nodes, 2,960,472 edges - 24 biological relation types including taxonomic hierarchies, metabolic interactions, phenotype associations, and environmental relationships - Primary prediction task: Growth media suitability for microbial taxa (biolink:occurs_in, 50K edges) - Multi-relation capability: Predicts links for any of the 24 relation types, including chemical consumption/production, phenotype associations, and taxonomic classification Citation: Original RelGT Architecture: Dwivedi et al., "Relational Graph Transformer", arXiv:2505.10960, 2025 KOGUT Implementation: Knowledge Oriented Graph Unified Transformer for Microbial Growth Media Prediction Developed at Lawrence Berkeley National Laboratory (LBNL) Trained on NERSC Perlmutter supercomputer

Joachimiak, Marcin [Lawrence Berkeley National Lab↗
DOE OSTI2020

Single-Cell Genomics and the Oral Microbiome

The human oral cavity is one of the first environments where microbes have been discovered and studied since the dawn of microbiology. Nevertheless, approximately 200 types of bacteria from the oral microbiota have remained uncultured in the laboratory. Some are associated with a healthy oral microbial community, while others are linked to oral diseases, from dental caries to gum disease. Single-cell genomics has enabled inferences on the physiology, virulence, and evolution of such uncultured microorganisms and has further enabled isolation and cultivation of several novel oral bacteria, including the discovery of novel interspecies interactions. This review summarizes some of the more recent advances in this field, which is rapidly moving toward physiologic characterization of single cells and ultimately cultivation of the yet uncultured. A combination of traditional microbiological approaches with genomic-based physiologic predictions and isolation strategies may lead to the oral microbiome being the first complex microbial community to have all its members cultivable in the laboratory. We conclude studying the biology of the individual microbes when in association with other members of the community, in controlled laboratory conditions and in vivo, should lead to a better understanding of oral dysbiosis and its prevention and reversion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Simulating metagenomic stable isotope probing datasets with MetaSIPSim

DNA-stable isotope probing (DNA-SIP) links microorganisms to their in-situ function in diverse environmental samples. Combining DNA-SIP and metagenomics (metagenomic-SIP) allows us to link genomes from complex communities to their specific functions and improves the assembly and binning of these targeted genomes. However, empirical development of metagenomic-SIP methods is hindered by the complexity and cost of these studies. We developed a toolkit, ‘MetaSIPSim,’ to simulate sequencing read libraries for metagenomic-SIP experiments. MetaSIPSim is intended to generate datasets for method development and testing. To this end, we used MetaSIPSim generated data to demonstrate the advantages of metagenomic-SIP over a conventional shotgun metagenomic sequencing experiment. Through simulation we show that metagenomic-SIP improves the assembly and binning of isotopically labeled genomes relative to a conventional metagenomic approach. Improvements were dependent on experimental parameters and on sequencing depth. Community level G + C content impacted the assembly of labeled genomes and subsequent binning, where high community G + C generally reduced the benefits of metagenomic-SIP. Furthermore, when a high proportion of the community is isotopically labeled, the benefits of metagenomic-SIP decline. Finally, the choice of gradient fractions to sequence greatly influences method performance. Metagenomic-SIP is a valuable method for recovering isotopically labeled genomes from complex communities. We show that metagenomic-SIP performance depends on optimization of experimental parameters. MetaSIPSim allows for simulation of metagenomic-SIP datasets which facilitates the optimization and development of metagenomic-SIP experiments and analytical approaches for dealing with these data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Metatranscriptomic dynamics after Verticillium dahliae infection and root damage in Olea europaea

Background: The olive tree is of particular economic interest in the Mediterranean basin. Researchers have conducted several studies on one of the most devastating disorders affecting this tree, the Verticillium wilt, which causes substantial economic losses in numerous areas. We analyzed metatranscriptomic samples taken from a previous study conducted on leaves and roots of Olea europaea that were infected with Verticillium dahliae. In addition, we also analyzed mechanically damaged roots. The aim of our approach is to describe the dynamics of the root microbiome after severe perturbations. Results: Our results not only describe the dynamics of the microbial community associated with the disturbance, but also show the high complexity of these systems and explain how this can lead to a conflicting assignment of the various types of parasitism observed in a specific organism. Conclusions: Our findings indicate that this infection, although led by Verticillium, is driven not by a single species, but by a polymicrobial consortium that also includes natural endophytes of the olive tree. This community contains both biotrophic and necrotrophic organisms that alternate and live together during the infection. In addition, opportunistic organisms appear that take profit not from plant tissues, but from new emerging populations of microorganisms. Therefore, this system can be described as a complex biological system composed of different interacting communities. Notably, our work has important considerations when it comes to classifying the type of parasitism of a given species.

Verticillium dahliae↗
DOE OSTI2021

Cellulosic biofuel production using emulsified simultaneous saccharification and fermentation (eSSF) with conventional and thermotolerant yeasts

Abstract Background Future expansion of corn-derived ethanol raises concerns of sustainability and competition with the food industry. Therefore, cellulosic biofuels derived from agricultural waste and dedicated energy crops are necessary. To date, slow and incomplete saccharification as well as high enzyme costs have hindered the economic viability of cellulosic biofuels, and while approaches like simultaneous saccharification and fermentation (SSF) and the use of thermotolerant microorganisms can enhance production, further improvements are needed. Cellulosic emulsions have been shown to enhance saccharification by increasing enzyme contact with cellulose fibers. In this study, we use these emulsions to develop an emulsified SSF (eSSF) process for rapid and efficient cellulosic biofuel production and make a direct three-way comparison of ethanol production between S. cerevisiae , O. polymorpha , and K. marxianus in glucose and cellulosic media at different temperatures. Results In this work, we show that cellulosic emulsions hydrolyze rapidly at temperatures tolerable to yeast, reaching up to 40-fold higher conversion in the first hour compared to microcrystalline cellulose (MCC). To evaluate suitable conditions for the eSSF process, we explored the upper temperature limits for the thermotolerant yeasts Kluyveromyces marxianus and Ogataea polymorpha , as well as Saccharomyces cerevisiae , and observed robust fermentation at up to 46, 50, and 42 °C for each yeast, respectively. We show that the eSSF process reaches high ethanol titers in short processing times, and produces close to theoretical yields at temperatures as low as 30 °C. Finally, we demonstrate the transferability of the eSSF technology to other products by producing the advanced biofuel isobutanol in a light-controlled eSSF using optogenetic regulators, resulting in up to fourfold higher titers relative to MCC SSF. Conclusions The eSSF process addresses the main challenges of cellulosic biofuel production by increasing saccharification rate at temperatures tolerable to yeast. The rapid hydrolysis of these emulsions at low temperatures permits fermentation using non-thermotolerant yeasts, short processing times, low enzyme loads, and makes it possible to extend the process to chemicals other than ethanol, such as isobutanol. This transferability establishes the eSSF process as a platform for the sustainable production of biofuels and chemicals as a whole.

09 BIOMASS FUELS↗
DOE OSTI2021

Co‑cultivation of the anaerobic fungus Caecomyces churrovis with Methanobacterium bryantii enhances transcription of carbohydrate binding modules, dockerins, and pyruvate formate lyases on specific substrates

Abstract Anaerobic fungi and methanogenic archaea are two classes of microorganisms found in the rumen microbiome that metabolically interact during lignocellulose breakdown. Here, stable synthetic co-cultures of the anaerobic fungus Caecomyces churrovis and the methanogen Methanobacterium bryantii (not native to the rumen) were formed, demonstrating that microbes from different environments can be paired based on metabolic ties. Transcriptional and metabolic changes induced by methanogen co-culture were evaluated in C. churrovis across a variety of substrates to identify mechanisms that impact biomass breakdown and sugar uptake. A high-quality genome of C. churrovis was obtained and annotated, which is the first sequenced genome of a non-rhizoid-forming anaerobic fungus. C. churrovis possess an abundance of CAZymes and carbohydrate binding modules and, in agreement with previous studies of early-diverging fungal lineages, N6-methyldeoxyadenine (6mA) was associated with transcriptionally active genes. Co-culture with the methanogen increased overall transcription of CAZymes, carbohydrate binding modules, and dockerin domains in co-cultures grown on both lignocellulose and cellulose and caused upregulation of genes coding associated enzymatic machinery including carbohydrate binding modules in family 18 and dockerin domains across multiple growth substrates relative to C. churrovis monoculture. Two other fungal strains grown on a reed canary grass substrate in co-culture with the same methanogen also exhibited high log2-fold change values for upregulation of genes encoding carbohydrate binding modules in families 1 and 18. Transcriptional upregulation indicated that co-culture of the C. churrovis strain with a methanogen may enhance pyruvate formate lyase (PFL) function for growth on xylan and fructose and production of bottleneck enzymes in sugar utilization pathways, further supporting the hypothesis that co-culture with a methanogen may enhance certain fungal metabolic functions. Upregulation of CBM18 may play a role in fungal–methanogen physical associations and fungal cell wall development and remodeling.

09 BIOMASS FUELS↗
DOE OSTI2022

Precursor prioritization for p-cymene production through synergistic integration of biology and chemistry

Abstract The strategy of synergistic application of biological and chemical catalysis is an important approach for efficiently converting renewable biomass into chemicals and fuels. In particular, the method of determining the appropriate intermediate between the two catalytic methods is critical. In this work, we demonstrate p -cymene production through the integration of biosynthesis and heterogenous catalysis and show how a preferred biologically derived precursor could be determined. On the biological side, we performed the limonene and 1,8-cineole production through the mevalonate pathway. Titers of 0.605 g/L and a 1.052 g/L were achieved, respectively. This difference is in agreement with the toxicity of these compounds toward the producing microorganisms, which has implications for subsequent development of the microbial platform. On the heterogeneous catalysis side, we performed the reaction with both biological precursors to allow for direct comparison. Using hydrogenation/dehydrogenation metals on supports with acid sites, both limonene and 1,8-cineole were converted to p -cymene with similar yields under equivalent reaction conditions. Thus, we could determine that the most promising strategy would be to target 1,8-cineole, the higher titer and lower toxicity bio-derived precursor with subsequent catalytic conversion to p -cymene. We further optimized the biological production of 1,8-cineole via fed-batch fermentation and reached the titer of 4.37 g/L which is the highest known 1,8-cineole titer from microbial production. This work provides a valuable paradigm for early stage considerations to determine the best route for the high-efficiency production of a target biobased molecule using an integration of biology and chemistry.

09 BIOMASS FUELS↗
DOE OSTI2023

Simultaneous expression of an endogenous spermidine synthase and a butanol dehydrogenase from Thermoanaerobacter pseudethanolicus in Clostridium thermocellum results in increased resistance to acetic acid and furans, increased ethanol production and an increase in thermotolerance

Abstract Background Sensitivity to inhibitors derived from the pretreatment of plant biomass is a barrier to the consolidated bioprocessing of these complex substrates to fuels and chemicals by microbes. Spermidine is a low molecular weight aliphatic nitrogen compound ubiquitous in microorganisms, plants, and animals and is often associated with tolerance to stress. We recently showed that overexpression of the endogenous spermidine synthase enhanced tolerance of the Gram-positive bacterium, Clostridium thermocellum to the furan derivatives furfural and HMF. Results Here we show that co-expression with an NADPH-dependent heat-stable butanol dehydrogenase from Thermoanaerobacter pseudethanolicus further enhanced tolerance to furans and acetic acid and most strikingly resulted in an increase in thermotolerance at 65 °C. Conclusions Tolerance to fermentation inhibitors will facilitate the use of plant biomass substrates by thermophiles in general and this organism in particular. The ability to grow C. thermocellum at 65 °C has profound implications for metabolic engineering.

09 BIOMASS FUELS↗
DOE OSTI2025

Resourceful and economical designing of fermentation medium for lab and commercial strains of yeast from alternative feedstock: ‘transgenic oilcane’

Sugarcane plant engineered to accumulate lipids in its vegetative tissue is being developed as a new bioenergy crop. The new crop would be a source of juice, oil, and cellulosic sugars. However, limited tolerance of industrially recognized yeasts towards inhibitors generated during the processing of lignocellulosic biomass to produce fermentable sugars is a major challenge in developing scalable processes for second-generation drop-in fuel production. To this end, hydrolysates generated from engineered sugarcane—‘oilcane’ bagasse contain added phenolics and fatty acids that further restrict the growth of fermenting microorganisms and necessitate nutrient supplementation and/or detoxification of hydrolysate which makes the fermentation process expensive. Herein, we propose a resourceful and economical approach for growing lab and commercial strains of S. cerevisiae on unrefined cellulosic sugars aerobically and fermentatively.

09 BIOMASS FUELS↗
DOE OSTI2020

Climate mediates continental scale patterns of stream microbial functional diversity

Understanding the large-scale patterns of microbial functional diversity is essential for anticipating climate change impacts on ecosystems worldwide. However, studies of functional biogeography remain scarce for microorganisms, especially in freshwater ecosystems. Here we study 15,289 functional genes of stream biofilm microbes along three elevational gradients in Norway, Spain and China. We find that alpha diversity declines towards high elevations and assemblage composition shows increasing turnover with greater elevational distances. These elevational patterns are highly consistent across mountains, kingdoms and functional categories and exhibit the strongest trends in China due to its largest environmental gradients. Across mountains, functional gene assemblages differ in alpha diversity and composition between the mountains in Europe and Asia. Climate, such as mean temperature of the warmest quarter or mean precipitation of the coldest quarter, is the best predictor of alpha diversity and assemblage composition at both mountain and continental scales, with local non-climatic predictors gaining more importance at mountain scale. Under future climate, we project substantial variations in alpha diversity and assemblage composition across the Eurasian river network, primarily occurring in northern and central regions, respectively. We conclude that climate controls microbial functional gene diversity in streams at large spatial scales; therefore, the underlying ecosystem processes are highly sensitive to climate variations, especially at high latitudes. This biogeographical framework for microbial functional diversity serves as a baseline to anticipate ecosystem responses and biogeochemical feedback to ongoing climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Meanders as a scaling motif for understanding of floodplain soil microbiome and biogeochemical potential at the watershed scale

Abstract Background Biogeochemical exports from watersheds are modulated by the activity of microorganisms that function over micron scales. Here, we tested the hypothesis that meander-bound regions share a core microbiome and exhibit patterns of metabolic potential that broadly predict biogeochemical processes in floodplain soils along a river corridor. Results We intensively sampled the microbiomes of floodplain soils located in the upper, middle, and lower reaches of the East River, Colorado. Despite the very high microbial diversity and complexity of the soils, we reconstructed 248 quality draft genomes representative of subspecies. Approximately one third of these bacterial subspecies was detected across all three locations at similar abundance levels, and ~ 15% of species were detected in two consecutive years. Within the meander-bound floodplains, we did not detect systematic patterns of gene abundance based on sampling position relative to the river. However, across meanders, we identified a core floodplain microbiome that is enriched in capacities for aerobic respiration, aerobic CO oxidation, and thiosulfate oxidation with the formation of elemental sulfur. Given this, we conducted a transcriptomic analysis of the middle floodplain. In contrast to predictions made based on the prominence of gene inventories, the most highly transcribed genes were relatively rare amoCAB and nxrAB (for nitrification) genes, followed by genes involved in methanol and formate oxidation, and nitrogen and CO 2 fixation. Within all three meanders, low soil organic carbon correlated with high activity of genes involved in methanol, formate, sulfide, hydrogen, and ammonia oxidation, nitrite oxidoreduction, and nitrate and nitrite reduction. Overall, the results emphasize the importance of sulfur, one-carbon and nitrogen compound metabolism in soils of the riparian corridor. Conclusions The disparity between the scale of a microbial cell and the scale of a watershed currently limits the development of genomically informed predictive models describing watershed biogeochemical function. Meander-bound floodplains appear to serve as scaling motifs that predict aggregate capacities for biogeochemical transformations, providing a foundation for incorporating riparian soil microbiomes in watershed models. Widely represented genetic capacities did not predict in situ activity at one time point, but rather they define a reservoir of biogeochemical potential available as conditions change.

54 ENVIRONMENTAL SCIENCES↗