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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Expression of macromolecular organic nitrogen degrading enzymes identifies potential mediators of soil organic N availability to an annual grass

Abstract Nitrogen (N) is frequently limiting to plant growth, in part because most soil N is present as polymeric organic compounds that are not readily taken up by plants. Microbial depolymerization of these large macromolecular N-substrates gradually releases available inorganic N. While many studies have researched and modeled controls on soil organic matter formation and bulk N mineralization, the ecological—spatial, temporal and phylogenetic—patterns underlying organic N degradation remain unclear. We analyzed 48 time-resolved metatranscriptomes and quantified N-depolymerization gene expression to resolve differential expression by soil habitat and time in specific taxonomic groups and gene-based guilds. We observed much higher expression of extracellular serine-type proteases than other extracellular N-degrading enzymes, with protease expression of predatory bacteria declining with time and other taxonomic patterns driven by the presence (Gammaproteobacteria) or absence (Thermoproteota) of live roots and root detritus (Deltaproteobacteria and Fungi). The primary chitinase chit1 gene was more highly expressed by eukaryotes near root detritus, suggesting predation of fungi. In some lineages, increased gene expression over time suggests increased competitiveness with rhizosphere age (Chloroflexi). Phylotypes from some genera had protease expression patterns that could benefit plant N nutrition, for example, we identified a Janthinobacterium phylotype and two Burkholderiales that depolymerize organic N near young roots and a Rhizobacter with elevated protease levels near mature roots. These taxon-resolved gene expression results provide an ecological read-out of microbial interactions and controls on N dynamics in specific soil microhabitats and could be used to target potential plant N bioaugmentation strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Sticky roots--implications of widespread, cryptic, viral infection of plants in natural and managed ecosystems for soil carbon processing in the rhizosphere

Plants strongly influence soil properties through rhizodeposition, in which exudates diffuse from roots, additional secretions are actively released, and root cells are sloughed into the soil. This contribution by plants of carbon compounds belowground is at the core of soil health, water holding capacity, and the soil carbon storage that pulls carbon dioxide out of the atmosphere. Once in soil, organic matter can bind with minerals such as iron hydroxides, where it can be protected from microbial attack for millenia, preserving very large terrestrial soil carbon pools. However, those same compounds contributed by roots to soil may also destabilize the long-term protective associations of SOM with minerals, making that soil organic matter (SOM) more vulnerable to microbial attack and decomposition. Plant roots thus influence both the buildup and breakdown of soil carbon pools. DOE’s E3SM Land Model (ELM) includes a representation of soil carbon storage on minerals, but the potential vulnerability of SOM–mineral associations to effects of rhizodeposition is not yet represented in ELM. To begin testing for this effect of rhizodeposition on soil carbon storage and decomposition, we worked to develop a novel approach during this TES Exploratory project DE-SC0019142 – we harnessed the power of plant viral infection. We examined whether plant virus infection can serve as a tool to intensify rhizodeposition at the root surface, and therefore possibly intensify mobilization of SOM from minerals making it visible to our analytical techniques. Viral infection is widespread in terrestrial ecosystems; 25-70% of plants have virus infection, yet the influence of such infection on root traits and terrestrial soil carbon dynamics remains largely unexplored. We used two plant hosts: the annual Avena sativa (oats) and the genetically tractable, model grass Brachypodium distachyon. These grasses were infected with the broad host range virus Barley Yellow Dwarf Virus (BYDV) via aphids (Rhopalosiphum padi). BYDV infects at least 150 grass species in agricultural and natural ecosystems, and in previous experiments, oats infected with BYDV had roots that were very sticky to the touch, strongly suggesting that infection altered rhizodeposition. We developed this new experimental approach mostly in a one virus (Barley Yellow Dwarf Virus)–one plant (Avena sativa) system. (Several effects of infection in a Brachypodium-BYDV system were similar in nature to effects on Avena sativa, but were more variable.) In the BYDV-Avena system, we developed protocols for consistently infecting target plants (and avoiding infection of control plants) using aphid caging on leaves. We measured that infected plants exhibited reduced photosynthesis, plant (including root) biomass, and root:shoot ratio, as well as simplified root system architecture. We established procedures for sampling the organic compounds carried specifically in phloem (vascular tissue) of leaves and roots, using aphid stylectomy. We used FTICR-MS, Orbitrap GC-MS, and LC-MS/MS to analyze organic compounds in phloem, liquid around roots of plants grown hydroponically, and pore water around roots in soil, and found differences in the compounds in solution bathing roots when infected and uninfected plants were grown hydroponically. Finally, we synthesized isotopically-labeled mineral–organic matter (MAOM) associations in the lab and developed assays using them in solution and in soil. Assays quantified the extent and rate of mineralization of labeled MAOM that was mobilized by functionally distinct rhizodeposits and then attacked by microbes. Two mechanisms for MAOM mobilization emerged, with distinct dynamics. During “direct” mobilization, rhizodeposits such as the strong ligand oxalic acid could drive rapid dissolution of minerals, mobilizing MAOM. During “indirect” mobilization, rhizodeposits such as the simple sugar glucose did not attack minerals directly but instead intensified microbial activity, which led to mobilization via changes in e.g. pH, Eh, and microbial metabolite production (Li et al. 2021). Mechanistic understanding derived from these data and our ongoing experiments using these techniques will inform future development of ELM. Plant roots not only contribute newly fixed organic compounds to soils, but also root activities can drive mineralization of the carbon and nutrients mobilized off minerals via “indirect” or “direct” mechanisms. Using viral infection as a new tool, ongoing combined experimentation and modeling will explore the strength and larger-scale significance of the cascade of processes from rhizodeposition to MAOM mobilization for soil carbon storage and nutrient cycling in terrestrial ecosystems. And if viral infection leads quite generally to “sticky roots”, our perception of the potential importance of prevalent virus infection in terrestrial landscapes will be transformed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Interactions among soil texture, pore structure, and labile carbon influence soil carbon gains

Perennial vegetation with high plant diversity, e.g., restored prairie, is known for stimulation of soil carbon (C) gains, due in part to enhanced formation of pore structure beneficial for long-term C storage. However, the prevalence of this phenomenon across soils of different types remains poorly understood. The aim of the study was to assess the associations between pore structure, soil C, and their differences in monoculture switchgrass and polyculture restored prairie vegetation across a wide range of soils dominating the Upper Midwest of the USA. Six experimental sites were sampled, representing three soil types with texture ranging from sandy to silt loams. The two vegetation systems studied at each site were (i) monoculture switchgrass (Panicum virgatum L.), and (ii) polyculture restored prairie, also containing switchgrass as one of its species. X-ray computed micro-tomography (µCT) was employed to analyze soil pore structure. Structural equation modeling and multiple path analyses were used to assess direct and indirect effects of soil texture and pore characteristics on microbial biomass C (MBC), particulate organic matter (POM), dissolved organic C (DOC), short-term respiration (CO 2 ), and, ultimately, soil organic C (SOC). Across studied sites, prairie increased fractions of medium (50–150 µm Ø) pores by 11–45 %, SOC by 3–69 %, and MBC by 18–59 % (except for one site). The greater were the prairie-induced increases in the medium pore volumes, the greater were the prairie-induced SOC gains. Greater C losses via CO 2 and DOC contributed to slower C accumulation in the prairie soil. We surmise that the interactive feedback loop relating medium pores and soil C acts across a wide range of soil textures and is an important mechanism through which perennial vegetation with high plant diversity, such as restored prairie, promotes rapid SOC gains.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Three Decades of Wetland Methane Surface Flux Modeling by Earth System Models–Advances, Applications, and Challenges

Earth System Models (ESMs) simulate the exchange of mass and energy between the land surface and the atmosphere, with a key focus on modeling natural greenhouse gas feedbacks. Methane is the second most important greenhouse gas after carbon dioxide. There are growing concerns over the rapidly increasing methane concentration in the atmosphere, underscoring the need for accurate global modeling of its emissions using ESMs. Of the multitude of sources of methane globally, wetlands are the largest natural emitters for methane, leading to significant efforts targeting their representation in ESMs with a special focus on their methane emissions. In this review, we first provide a historical overview of including wetland–methane components in ESMs and how methane modeling approaches have evolved over time. Second, we discuss recent modeling advancements that show promise for improvements in methane emissions predictions, namely the coupling of surface and atmospheric modules of ESMs, the representation of microtopography and transport mechanisms, the resolution of microbial processes at different spatial–temporal scales, and the improved mapping of wetland area extent across the different wetland types. Third, we shed light on the different challenges hindering accurate estimations of wetland–methane emissions, as shown by the consistent discrepancy between bottom–up and top–down models' predictions. Finally, we emphasize that more detailed representation of biogeochemistry and dynamic hydrology while resolving the within–wetland vegetation heterogeneity should improve model predictions, especially when coupled with expanding ground–based measurement networks and high–resolution remote sensing mapping of methane–relevant variables, such as water elevation, water table depth, and methane concentration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Identification and characterization of a skin microbiome on Caenorhabditis elegans suggests environmental microbes confer cuticle protection

ABSTRACT In the wild, C. elegans are emersed in environments teeming with a veritable menagerie of microorganisms. The C. elegans cuticular surface serves as a barrier and first point of contact with their microbial environments. In this study, we identify microbes from C. elegans natural habitats that associate with its cuticle, constituting a simple “skin microbiome.” We rear our animals on a modified CeMbio, mCeMbio, a consortium of ecologically relevant microbes. We first combine standard microbiological methods with an adapted micro skin-swabbing tool to describe the skin-resident bacteria on the C. elegans surface. Furthermore, we conduct 16S rRNA gene sequencing studies to identify relative shifts in the proportion of mCeMbio bacteria upon surface-sterilization, implying distinct skin- and gut-microbiomes. We find that some strains of bacteria, including Enterobacter sp. JUb101 , are primarily found on the nematode skin, while others like Stenotrophomonas indicatrix JUb19 and Ochrobactrum vermis MYb71 are predominantly found in the animal’s gut. Finally, we show that this skin microbiome promotes host cuticle integrity in harsh environments. Together, we identify a skin microbiome for the well-studied nematode model and propose its value in conferring host fitness advantages in naturalized contexts. IMPORTANCE The genetic model organism C. elegans has recently emerged as a tool for understanding host–microbiome interactions. Nearly all of these studies either focus on pathogenic or gut-resident microbes. Little is known about the existence of native, nonpathogenic skin microbes or their function. We demonstrate that members of a modified C. elegans model microbiome, mCeMbio, can adhere to the animal's cuticle and confer protection from noxious environments. We combine a novel micro-swab tool, the first 16S microbial sequencing data from relatively unperturbed C. elegans , and physiological assays to demonstrate microbially mediated protection of the skin. This work serves as a foundation to explore wild C. elegans skin microbiomes and use C. elegans as a model for skin research.

16S RNA↗
DOE OSTI2024

Salt marsh soil organic carbon is regulated by drivers of microbial activity

Abstract Soil organic carbon is the foundation for soil health and a livable climate. Organic carbon is concentrated in coastal wetland soils, but dynamics that govern carbon persistence in coastal ecosystems remain incompletely understood. Whether microbial activity results in a gain or loss of carbon depends on environmental conditions that regulate microbial community attributes. We sought to identify which drivers of microbial activity have the greatest impact on organic carbon content in salt marsh soils. To address this question, we used the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) statement to compile data on soil and ecosystem characteristics from 50 studies of over 60 salt marshes located around the world. We conducted a meta-analysis with structural equation modeling, including mediation and moderation analyses, to identify environmental drivers of salt marsh soil organic carbon content. High salinity, pH, nitrogen, and phosphorus were associated with increased microbial biomass carbon and soil organic carbon. Correlations between microbial biomass and organic carbon were strengthened by soil salinity and nitrogen, and weakened by soil water content. These results suggest that environmental conditions that control microbial growth and activity have potential to preserve or degrade organic carbon in salt marsh soils.

Erb, Hailey (ORCID:0000000337295634)↗
DOE OSTI2022

Utilization of lignocellulosic biofuel conversion residue by diverse microorganisms

Lignocellulosic conversion residue (LCR) is the material remaining after deconstructed lignocellulosic biomass is subjected to microbial fermentation and treated to remove the biofuel. Technoeconomic analyses of biofuel refineries have shown that further microbial processing of this LCR into other bioproducts may help offset the costs of biofuel generation. Identifying organisms able to metabolize LCR is an important first step for harnessing the full chemical and economic potential of this material. In this study, we investigated the aerobic LCR utilization capabilities of 71 Streptomyces and 163 yeast species that could be engineered to produce valuable bioproducts. The LCR utilization by these individual microbes was compared to that of an aerobic mixed microbial consortium derived from a wastewater treatment plant as representative of a consortium with the highest potential for degrading the LCR components and a source of genetic material for future engineering efforts. We analyzed several batches of a model LCR by chemical oxygen demand (COD) and chromatography-based assays and determined that the major components of LCR were oligomeric and monomeric sugars and other organic compounds. Many of the Streptomyces and yeast species tested were able to grow in LCR, with some individual microbes capable of utilizing over 40% of the soluble COD. For comparison, the maximum total soluble COD utilized by the mixed microbial consortium was about 70%. This represents an upper limit on how much of the LCR could be valorized by engineered Streptomyces or yeasts into bioproducts. To investigate the utilization of specific components in LCR and have a defined media for future experiments, we developed a synthetic conversion residue (SynCR) to mimic our model LCR and used it to show lignocellulose-derived inhibitors (LDIs) had little effect on the ability of the Streptomyces species to metabolize SynCR. We found that LCR is rich in carbon sources for microbial utilization and has vitamins, minerals, amino acids and other trace metabolites necessary to support growth. Testing diverse collections of Streptomyces and yeast species confirmed that these microorganisms were capable of growth on LCR and revealed a phylogenetic correlation between those able to best utilize LCR. Identification and quantification of the components of LCR enabled us to develop a synthetic LCR (SynCR) that will be a useful tool for examining how individual components of LCR contribute to microbial growth and as a substrate for future engineering efforts to use these microorganisms to generate valuable bioproducts.

09 BIOMASS FUELS↗
DOE OSTI2023

Dissecting the Division of Labor in Microbial Consortia for the Production of Biofuels and Chemicals (Final Technical Report)

The overarching objective of this project is to elucidate the fundamental design rules for microbial division of labor (DOL), the core of ecosystem organization, in the context of artificial yeast—lactic acid bacteria consortia that produce advanced biofuel and chemical from cellulosic biomass. Over the course of four years, we have successfully achieved the objective through three lines of research that combines experiment with mathematical modeling. Specifically, we have shown that compositional and temporal DOL is effective in modulating mixed sugar fermentation by an engineered consortium and uncovered general quantitative criteria for conditions under which microbial DOL outperforms single superbugs for simultaneous utilization of mixed substrates. We also demonstrated, in synthetic consortia of yeast and lactic acid bacteria, that partitioning the labor for substrate breakdown and end-product synthesis can allow an efficient production of 2-butanol that is difficult otherwise for a single yeast strain. Additionally, by systematically probing the stability of an engineered cooperative consortium, we found that the stability of microbial symbiosis is governed by the topological structure of the underlying cellular interactions rather than specific microbial species and that rational modulation of the interactions may facilitate the restoration of collapsed consortia as well as the intervention of target communities. Together, this project has advanced the fundamental knowledge of microbial DOL in terms of its strength in mixed substrate fermentation, production of complex chemicals, and ecological system stability in the context of microbial consortia. It also provides valuable insights into the design, construction and optimization of artificial consortia for the utilization of cellulosic biomass and economic production of biofuel and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Emergence and disruption of cooperativity in a denitrifying microbial community

Anthropogenic perturbations to the nitrogen cycle, primarily through use of synthetic fertilizers, is driving an unprecedented increase in the emission of nitrous oxide (N 2 O), a potent greenhouse gas and an ozone depleting substance, causing urgency in identifying the sources and sinks of N 2 O. Microbial denitrification is a primary contributor to biotic production of N 2 O in anoxic regions of soil, marine systems, and wastewater treatment facilities. Here, through comprehensive genome analysis, we show that pathway partitioning is a ubiquitous mechanism of complete denitrification within microbial communities. We have investigated mechanisms and consequences of process partitioning of denitrification through detailed physiological characterization and kinetic modeling of a synthetic community of Rhodanobacter thiooxydans FW510-R12 and Acidovorax sp. GW101-3H11. We have discovered that these two bacterial isolates, from a heavily nitrate (NO 3 − ) contaminated superfund site, complete denitrification through the exchange of nitrite (NO 2 − ) and nitric oxide (NO). The process partitioning of denitrification and other processes, including amino acid metabolism, contribute to increased cooperativity within this denitrifying community. We demonstrate that certain contexts, such as high NO 3 − , cause unbalanced growth of community members, due to differences in their substrate utilization kinetics. The altered growth characteristics of community members drives accumulation of toxic NO 2 − , which disrupts denitrification causing N 2 O off gassing.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Thermodynamic Constraints on Electromicrobial Protein Production

Global consumption of protein is projected to double by the middle of the 21st century. However, protein production is one of the most energy intensive and environmentally damaging parts of the food supply system today. Electromicrobial production technologies that combine renewable electricity and CO 2 -fixing microbial metabolism could dramatically increase the energy efficiency of commodity chemical production. Here we present a molecular-scale model that sets an upper limit on the performance of any organism performing electromicrobial protein production. We show that engineered microbes that fix CO 2 and N 2 using reducing equivalents produced by H 2 -oxidation or extracellular electron uptake could produce amino acids with energy inputs as low as 64 MJ kg −1 , approximately one order of magnitude higher than any previous estimate of the efficiency of electromicrobial protein production. This work provides a roadmap for development of engineered microbes that could significantly expand access to proteins produced with a low environmental footprint.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

A holistic framework integrating plant-microbe-mineral regulation of soil bioavailable nitrogen

Abstract Soil organic nitrogen (N) is a critical resource for plants and microbes, but the processes that govern its cycle are not well-described. To promote a holistic understanding of soil N dynamics, we need an integrated model that links soil organic matter (SOM) cycling to bioavailable N in both unmanaged and managed landscapes, including agroecosystems. We present a framework that unifies recent conceptual advances in our understanding of three critical steps in bioavailable N cycling: organic N (ON) depolymerization and solubilization; bioavailable N sorption and desorption on mineral surfaces; and microbial ON turnover including assimilation, mineralization, and the recycling of microbial products. Consideration of the balance between these processes provides insight into the sources, sinks, and flux rates of bioavailable N. By accounting for interactions among the biological, physical, and chemical controls over ON and its availability to plants and microbes, our conceptual model unifies complex mechanisms of ON transformation in a concrete conceptual framework that is amenable to experimental testing and translates into ideas for new management practices. This framework will allow researchers and practitioners to use common measurements of particulate organic matter (POM) and mineral-associated organic matter (MAOM) to design strategic organic N-cycle interventions that optimize ecosystem productivity and minimize environmental N loss.

Environmental Sciences & Ecology↗
DOE OSTI2024

Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Nutrient Cycling at a Coastal Terrestrial‐Aquatic Interface

Abstract The complex interactions among soil, vegetation, and site hydrologic conditions driven by precipitation and tidal cycles control the biogeochemical transformations and bi‐directional exchange of carbon and nutrients across the terrestrial–aquatic interfaces (TAIs) in coastal regions. This study uses a highly mechanistic model, Advanced Terrestrial Simulator (ATS)‐PFLOTRAN, to explore how these interactions affect exchanges of materials and carbon and nitrogen cycling. We used a transect in the Chesapeake Bay region that spans zones of open water, coastal wetland, transition, and upland forest. We designed several simulation scenarios to parse the effects of the individual controlling factors and the sensitivity of carbon cycling to reaction rate parameters derived from laboratory experiments. Our simulations reveal an active zone for carbon cycling under the transition zones between the wetland and the upland. Evapotranspiration is found to enhance the exchange fluxes between the surface and subsurface domains, resulting in a higher dissolved oxygen concentration in the TAIs. The transport of organic carbon derived from plant leaves and roots provide an additional source of organic carbon needed for the aerobic respiration and denitrification processes in the TAIs. The variability in reaction rate parameters associated with microbial activities is also found to play a dominant role in controlling the heterogeneity and dynamics of the simulated redox conditions. This modeling‐focused exploratory study enabled us to better understand the complex interactions among soil, water and microbes that govern the hydro‐biogeochemical processes at the TAIs, which is an important step toward representing coastal ecosystems in larger‐scale Earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)

Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Data for High Yield Production of 3-Hydroxypropionic Acid Using Issatchenkia orientalis

Biomanufacturing provides a more sustainable alternative to fossil-based chemical manufacturing. 3-Hydroxypropionic acid (3HP) is a top Department of Energy value-added chemical and precursor to bioplastics, yet cost-effective microbial production remains elusive. Here, we establish the acid-tolerant yeast Issatchenkia orientalis as a robust host for low-pH 3HP biosynthesis. Genome-scale modeling identifies the β-alanine pathway as optimal, offering the highest theoretical yield and lowest oxygen requirement. Thermodynamic analysis confirms its favorability under acidic conditions. Using sequence similarity network analysis, we discover highly active aspartate 1-decarboxylase (PAND), β-alanine-pyruvate aminotransferase (BAPAT), and 3HP dehydrogenase (YDFG), which significantly improve the pathway efficiency. Next, to further elevate the production, pathway optimization through multi-copy PAND integration, byproduct elimination (knockouts of pyruvate decarboxylase and glycerol-3-phosphate dehydrogenase), and reinforcement of aspartate flux by overexpression of pyruvate carboxylase and aspartate amino transferase improves the titer to 29 g/L in shake flasks. Fed-batch fermentation at pH 4 with low-cost corn steep liquor medium further increases the production to 92 g/L with 0.7 g/g yield and 0.55 g/L/h productivity. Techno-economic analysis indicates that such performance could potentially enable a financially viable process for sustainable acrylic acid production. This work establishes I. orientalis as a next-generation platform for cost-effective 3HP production and paves the way toward industrial commercialization.

Bioproducts↗
DOE OSTI2026

Characterization of the biofilm landscape of Bacillus subtilis by spatial microproteomics

Bulk proteomics has been demonstrated to differentiate subpopulations within bacterial colonies, yet advanced analyses by mass spectrometry imaging (MSI) hold even greater promise for the future. This technology can enable high-throughput spatial phenotyping that can reshape biological discovery by providing visualization of components of various biomolecular mechanisms. With high mass resolving power and high spatial resolution analyses being routine, we can confidently enable intact protein imaging directly from samples with minimal preparation. Pairing those analyses with bulk experimental libraries can provide high confidence in annotations of post-translational modifications (PTMs) and truncations. Revealing PTM localization within the samples unlocks a direct window into unknown biology at the microscale. However, top-down proteomics (TDP) is not commonplace for microbial species, largely due to challenges in identifying detected peptides and proteins; considering the theoretical proteome of even the well-studied model bacterium Bacillus subtilis was only partially mapped recently. With little still known about the form and function of many of these proteins – let alone proteoforms, where PTMs and truncations of the same protein may possess unique physiological roles – there is a wealth of work to be done. Here we jointly apply TDP and MSI to describe the microscale spatial proteomic landscape within B. subtilis and further demonstrate the feasibility of detecting differentiated subpopulations through proteoforms across the biofilm landscape.

bacterial biofilms↗
DOE OSTI2020

FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genomes and metagenome assemblies

Iron is a micronutrient for nearly all life on Earth. It can be used as an electron donor and electron acceptor by iron-oxidizing and iron-reducing microorganisms and is used in a variety of biological processes, including photosynthesis and respiration. While it is the fourth most abundant metal in the Earth’s crust, iron is often limiting for growth in oxic environments because it is readily oxidized and precipitated. Much of our understanding of how microorganisms compete for and utilize iron is based on laboratory experiments. However, the advent of next-generation sequencing and surge in publicly available sequence data has made it possible to probe the structure and function of microbial communities in the environment. To bridge the gap between our understanding of iron acquisition, iron redox cycling, iron storage, and magnetosome formation in model microorganisms and the plethora of sequence data available from environmental studies, we have created a comprehensive database of hidden Markov models (HMMs) based on genes related to iron acquisition, storage, and reduction/oxidation in Bacteria and Archaea. Along with this database, we present FeGenie, a bioinformatics tool that accepts genome and metagenome assemblies as input and uses our comprehensive HMM database to annotate provided datasets with respect to iron-related genes and gene neighborhood. An important contribution of this tool is the efficient identification of genes involved in iron oxidation and dissimilatory iron reduction, which have been largely overlooked by standard annotation pipelines. We validated FeGenie against a selected set of 28 isolate genomes and showcase its utility in exploring iron genes present in 27 metagenomes, 4 isolate genomes from human oral biofilms, and 17 genomes from candidate organisms, including members of the candidate phyla radiation. We show that FeGenie accurately identifies iron genes in isolates. Furthermore, analysis of metagenomes using FeGenie demonstrates that the iron gene repertoire and abundance of each environment is correlated with iron richness. While this tool will not replace the reliability of culture-dependent analyses of microbial physiology, it provides reliable predictions derived from the most up-to-date genetic markers. FeGenie’s database will be maintained and continually updated as new genes are discovered.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Scaling High-Resolution Soil Organic Matter Composition to Improve Predictions of Potential Soil Respiration Across the Continental United States

Despite the importance of microbial soil organic matter (SOM) respiration in regulating the flux of carbon between soils and the atmosphere, soil carbon cycling models remain primarily based on climate and soil properties, leading to large uncertainty in predictions. To address this knowledge gap, we analyzed high-resolution water-extractable SOM profiles from soil cores collected across the United States by the 1,000 Soils Pilot of the Molecular Observation Network. Our innovation lies in using machine learning to distill thousands of SOM formula into tractable units; and it enables integrating data from molecular measurements into soil respiration models. In surface soils, SOM chemistry provided better estimates of potential soil respiration than soil physicochemistry, and using them combined yielded the best prediction. Overall, we identify specific subsets of organic molecules that may improve predictions of global soil respiration and create a strong basis for developing new representations in process-based models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI feat ), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI feat , we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

59 BASIC BIOLOGICAL SCIENCES↗