Search NASA⌕ Search

SEARCH · Search NASA

Results for “GENOMICS INFORMATION”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predictions of rhizosphere microbiome dynamics with a genome-informed and trait-based energy budget model

Abstract Soil microbiomes are highly diverse, and to improve their representation in biogeochemical models, microbial genome data can be leveraged to infer key functional traits. By integrating genome-inferred traits into a theory-based hierarchical framework, emergent behaviour arising from interactions of individual traits can be predicted. Here we combine theory-driven predictions of substrate uptake kinetics with a genome-informed trait-based dynamic energy budget model to predict emergent life-history traits and trade-offs in soil bacteria. When applied to a plant microbiome system, the model accurately predicted distinct substrate-acquisition strategies that aligned with observations, uncovering resource-dependent trade-offs between microbial growth rate and efficiency. For instance, inherently slower-growing microorganisms, favoured by organic acid exudation at later plant growth stages, exhibited enhanced carbon use efficiency (yield) without sacrificing growth rate (power). This insight has implications for retaining plant root-derived carbon in soils and highlights the power of data-driven, trait-based approaches for improving microbial representation in biogeochemical models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Next generation modeling of microbial souring – Parameterization through genomic information

Biogenesis of hydrogen sulfide (H 2 S) (microbial souring) has detrimental impacts on oil production operations and can cause health and safety problems. Understanding the processes that control the rates and patterns of sulfate reduction is crucial in developing a predictive understanding of reservoir souring and associated mitigation processes. This work demonstrates an approach to utilize genomic information to constrain the biological parameters needed for modeling souring, providing a pathway for using microbial data derived from oil reservoir studies. Minimum generation times were calculated based on codon usage bias and optimal growth temperatures based on the frequency of amino acids. We show how these derived parameters can be used in a simplified multiphase reactive transport model by simulating the injection of cold (30 °C) seawater into a 70 °C reservoir, modeling the shift in sulfate reducing microorganisms (SRM) community composition, sulfate and sulfide concentrations through time and space. Finally, we explore the question of necessary model complexity by comparing results using different numbers of SRM. Simulations showed that the kinetics of a SRM community consisting of twenty-five SRM could be adequately represented by a reduced community consisting of nine SRM with parameter values derived from the mean and standard deviations of the original SRM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Importance of appropriate genome information for the design of mating type primers in black and yellow morel populations

Abstract Morels are highly prized edible fungi where sexual reproduction is essential for fruiting-body production. As a result, a comprehensive understanding of their sexual reproduction is of great interest. Central to this is the identification of the reproductive strategies used by morels. Sexual reproduction in fungi is controlled by mating-type ( MAT ) genes and morels are thought to be mainly heterothallic with two idiomorphs, MAT1-1 and MAT1-2. Genomic sequencing of black (Elata clade) and yellow (Esculenta clade) morel species has led to the development of PCR primers designed to amplify genes from the two idiomorphs for rapid genotyping of isolates from these two clades. To evaluate the design and theoretical performance of these primers we performed a thorough bioinformatic investigation, including the detection of the MAT region in publicly available Morchella genomes and in-silico PCR analyses. All examined genomes, including those used for primer design, appeared to be heterothallic. This indicates an inherent fault in the original primer design which utilized a single Morchella genome, as the use of two genomes with complementary mating types would be required to design accurate primers for both idiomorphs. Furthermore, potential off-targets were identified for some of the previously published primer sets, but verification was challenging due to lack of adequate genomic information and detailed methodologies for primer design. Examinations of the black morel specific primer pairs (MAT11L/R and MAT22L/R) indicated the MAT22 primers would correctly target and amplify the MAT1-2 idiomorph, but the MAT11 primers appear to be capable of amplifying incorrect off-targets within the genome. The yellow morel primer pairs (EMAT1-1 L/R and EMAT1-2 L/R) appear to have reporting errors, as the published primer sequences are dissimilar with reported amplicon sequences and the EMAT1-2 primers appear to amplify the RNA polymerase II subunit ( RPB2 ) gene. The lack of the reference genome used in primer design and descriptive methodology made it challenging to fully assess the apparent issues with the primers for this clade. In conclusion, additional work is still required for the generation of reliable primers to investigate mating types in morels and to assess their performance on different clades and across multiple geographical regions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Genomics-informed isolation and characterization of a symbiotic Nanoarchaeota system from a terrestrial geothermal environment

Biological features can be inferred, based on genomic data, for many microbial lineages that remain uncultured. However, cultivation is important for characterizing an organism’s physiology and testing its genome-encoded potential. Here we use single-cell genomics to infer cultivation conditions for the isolation of an ectosymbiotic Nanoarchaeota (‘Nanopusillus acidilobi’) and its host (Acidilobus, a crenarchaeote) from a terrestrial geothermal environment. The cells of ‘Nanopusillus’ are among the smallest known cellular organisms (100–300 nm). They appear to have a complete genetic information processing machinery, but lack almost all primary biosynthetic functions as well as respiration and ATP synthesis. Lastly, genomic and proteomic comparison with its distant relative, the marine Nanoarchaeum equitans illustrate an ancient, common evolutionary history of adaptation of the Nanoarchaeota to ectosymbiosis, so far unique among the Archaea.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A genome-informed higher rank classification of the biotechnologically important fungal subphylum Saccharomycotina

The subphylum Saccharomycotina is a lineage in the fungal phylum Ascomycota that exhibits levels of genomic diversity similar to those of plants and animals. The Saccharomycotina consist of more than 1 200 known species currently divided into 16 families, one order, and one class. Species in this subphylum are ecologically and metabolically diverse and include important opportunistic human pathogens, as well as species important in biotechnological applications. Many traits of biotechnological interest are found in closely related species and often restricted to single phylogenetic clades. However, the biotechnological potential of most yeast species remains unexplored. Although the subphylum Saccharomycotina has much higher rates of genome sequence evolution than its sister subphylum, Pezizomycotina, it contains only one class compared to the 16 classes in Pezizomycotina. The third subphylum of Ascomycota, the Taphrinomycotina, consists of six classes and has approximately 10 times fewer species than the Saccharomycotina. These data indicate that the current classification of all these yeasts into a single class and a single order is an underappreciation of their diversity. Our previous genome-scale phylogenetic analyses showed that the Saccharomycotina contains 12 major and robustly supported phylogenetic clades; seven of these are current families (Lipomycetaceae, Trigonopsidaceae, Alloascoideaceae, Pichiaceae, Phaffomycetaceae, Saccharomycodaceae, and Saccharomycetaceae), one comprises two current families (Dipodascaceae and Trichomonascaceae), one represents the genus Sporopachydermia, and three represent lineages that differ in their translation of the CUG codon (CUG-Ala, CUG-Ser1, and CUG-Ser2). Using these analyses in combination with relative evolutionary divergence and genome content analyses, we propose an updated classification for the Saccharomycotina, including seven classes and 12 orders that can be diagnosed by genome content. This updated classification is consistent with the high levels of genomic diversity within this subphylum and is necessary to make the higher rank classification of the Saccharomycotina more comparable to that of other fungi, as well as to communicate efficiently on lineages that are not yet formally named.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

A genomics-informed study of oxalate and cellulase regulation by brown rot wood-degrading fungi

Wood-degrading fungi that selectively remove carbohydrates (brown rot) combine Fenton-based oxidation and enzymatic hydrolysis to degrade wood. These two steps are incompatible in close proximity. To explain this, brown rot fungi may stagger oxidative reactions ahead of hydrolysis, but the scale and environmental controls for such a mechanism have not been resolved in solid wood. Here, we focused on one reaction control parameter, oxalate. In coordination with Fe 3+ -reducing compounds (e.g., 2,5-dimethoxyhydroquinone), oxalate can either promote Fenton chemistry by mobilizing Fe 3+ as mono-oxalates (facilitative) or inhibit Fenton chemistry (protective) by restricting reducibility and the formation of Fenton’s reagent as Fe 3+ /Fe 2 -(oxalate) 2,3 . We sectioned wood wafers colonized directionally by Postia placenta and Gloeophyllum trabeum to map end-to-end the expression of oxalate synthesis genes and to overlay enzyme activities, metabolites, and wood modifications. Near advancing hyphal fronts, oxaloacetase expression was up upregulated for both fungi, while regulation patterns of paralogous of isocitrate lyases and glyoxylate dehydrogenases varied, suggesting different physiological roles. Oxalate decarboxylase (ODC) expression in G. trabeum was induced in more decayed wood behind the hyphal front, but was constitutively expressed in all P. placenta sections. Relative ODC activities increased and oxalate levels stabilized in more decayed wood behind the hyphal front. Endoglucanase (EG) activity, on the other hand, peaked for both fungi in later decay stages. These oxalate optimization patterns are in line with previous whole-block ‘spiking’ experiments tracking oxalate, but we provide here information on its genetic controls across a spatial gradient. As a complement, we also demonstrate in vitro the plausibility of a protective role for oxalate, to emphasize that these fungi might be optimizing oxalate at a given level to maximize Fenton reactions but to minimize oxidative damage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dissection of Carbon and Nitrogen Cycling in Post-Fire Soil Environments using a Genome- Informed Experimental Community (Final Technical Report)

Wildfires are a natural part of many forest ecosystems, with globally important carbon (C) storage and nutrient cycling consequences, and they are increasing in frequency and severity in Western North America. Forest fires affect soil C stocks in complex ways; some C is released into the atmosphere through combustion, while a large percentage of the C is added to the soil in the form of pyrogenic organic matter. Worldwide, it is estimated that 16% of soil organic matter is pyrogenic, while locally, this number may be as high as 80%. Understanding how wildfires affect soil organic matter cycling requires understanding how microbes respond to pyrogenic organic matter and other post-fire soil conditions. However, our understanding of microbial interactions within post-fire soil was in its infancy at the time of our proposal. Outstanding questions included: Which microbes are capable of degrading pyrogenic organic matter? What are the relevant genes and metabolites associated with this degradation? What are the key interactions among post-fire microbes? Key highlights of outcomes supported by this grant included training eleven early-career scientists and two early-career PIs, publication of twelve peer-reviewed papers, cross-lab collaborations that empowered complex scientific approaches, the development of an open-source automated gas sampler to drive novel insights in C cycling, enhanced understanding of post-fire microbial community dynamics, and novel genetic and molecular insights into microbial responses to fire.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Extraction of Tumor Site from Cancer Pathology Reports using Deep Filters

Purpose: Pathology reports are the primary source of information concerning the millions of cancer cases across the United States. Cancer registries manually process the pathology reports to extract the pertinent information including primary tumor site, behavior, histology, laterality, and grade. Processing a large volume of the pathology reports in a timely manner is a continuing challenge for cancer registries. The purpose of this study is to develop an information extraction pipeline to reliably and efficiently extract reportable information. Method: We have developed a novel inverse-regression (IR) based information extraction pipeline. The inverse-regression based supervised filter has been successfully applied to many application domains. However, its application to the information extraction from unstructured text is hindered primarily by the extreme high-dimensionality of n-gram representations of text. In this study, we attempt to overcome the obstacles by a novel bootstrapping strategy. First, we use an information-theoretic mutual information based filter to discard the excessive and redundant n-gram features. This step reduces the size and improves the condition number of the sample covariance matrix, thus reducing the computational cost and improving the numerical stability of the subsequent inverse-regression step. Then we use localized sliced inverse-regression (LSIR) to learn a low-dimensional discriminatory subspace for information inference. In particular, we use the k-nearest neighbors of an unlabeled pathology report in the learned representation to infer the desired information from the labeled data in a supervised manner. Results: The experiments were conducted on a set of de-identified pathology reports with human expert labels as the ground truth. Our pipeline consistently performed better than or comparable to the best performing state-of-the-art methods while reducing the training and inference times substantially. Conclusion: Our results demonstrate the potential of inverse-regression based information extraction pipeline for reliable and efficient information extraction from unstructured text. The information extracted from the pathology reports can be used along with clinical information, medical imaging, and genomic information to instigate discoveries in cancer research.

Dubey, Abhishek↗
DOE OSTI2026

Methods for safely sharing dual-use genetic data

Background: Some genetic data has dual-use potential. Sharing pathogen data has shown tremendous value. For example therapeutic development and lineage tracking during the COVID pandemic. This data sharing is complicated by the fact that these data have the potential to be used for harm. The genome sequence of a pathogen can be used to enable malicious genetic engineering approaches or to recreate the pathogen from synthetic DNA. Standard data security methods can be applied to genetic data, but when data is shared between institutions, ensuring appropriate security can be difficult. Sensitive data that is shared internationally among a wide array of institutions can be especially difficult to control. Methods for securely storing and sharing genetic data with potential for dual-use are needed to mitigate this potential harm.Results: Here we propose new methods that allow genetic data to be shared in a data format that prevents a nefarious actor from accessing sensitive aspects of the data. Our methods obfuscate raw sequence data by pooling reads from different samples. This approach can ensure that data is secure while stored and during electronic transfer. We demonstrate that by pooling raw sequence data from multiple samples of the same organism, the ability to fully reconstruct any individual sample is prevented. In the pooled data, most genomic information remains, but reads or mutations cannot be directly attributed to any individual sample. To further restrict access to information, regions of a genome can be removed from the reads.Conclusion: Our methods obscure genomic information within raw sequence reads. This method can allow genetic data to be stored and shared while preventing a nefarious actor from being able to perfectly reconstruct an organism. Broad-scale sequence information remains, while fine scale details about specific samples are difficult or impossible to reconstruct. Our software is available at https://github.com/Geneinfosec-Inc/ReadMixer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Elucidating Syntrophic Butyrate-Degrading Populations in Anaerobic Digesters Using Stable-Isotope-Informed Genome-Resolved Metagenomics

Linking the genomic content of uncultivated microbes to their metabolic functions remains a critical challenge in microbial ecology. Resolving this challenge has implications for improving our management of key microbial interactions in biotechnologies such as anaerobic digestion, which relies on slow-growing syntrophic and methanogenic communities to produce renewable methane from organic waste. In this study, we combined DNA stable-isotope probing (SIP) with genome-centric metagenomics to recover the genomes of populations enriched in 13 C after growing on [ 13 C]butyrate. Differential abundance analysis of recovered genomic bins across the SIP metagenomes identified two metagenome-assembled genomes (MAGs) that were significantly enriched in heavy [ 13 C]DNA. Phylogenomic analysis assigned one MAG to the genus Syntrophomonas and the other MAG to the genus Methanothrix. Metabolic reconstruction of the annotated genomes showed that the Syntrophomonas genome encoded all the enzymes for beta-oxidizing butyrate, as well as several mechanisms for interspecies electron transfer via electron transfer flavoproteins, hydrogenases, and formate dehydrogenases. The Syntrophomonas genome shared low average nucleotide identity (<95%) with any cultured representative species, indicating that it is a novel species that plays a significant role in syntrophic butyrate degradation within anaerobic digesters. The Methanothrix genome contained the complete pathway for acetoclastic methanogenesis, indicating that it was enriched in 13 C from syntrophic acetate transfer. This study demonstrates the potential of stable-isotope-informed genome-resolved metagenomics to identify in situ interspecies metabolic cooperation within syntrophic consortia important to anaerobic waste treatment as well as global carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

An archaeal symbiont-host association from the deep terrestrial subsurface

DPANN archaea have reduced metabolic capacities and are diverse and abundant in deep aquifer ecosystems, but little is known about their interactions with other microorganisms that reside there. In this work, we offer evidence for an archaeal host-symbiont association from a deep aquifer system at the Colorado Plateau (Utah, USA). The symbiont, Candidatus Huberiarchaeum crystalense , and its host, Ca. Altiarchaeum hamiconexum , show a highly significant co-occurrence pattern over 65 metagenome samples collected over six years. The physical association of the two organisms was confirmed with genome-informed fluorescence in situ hybridization depicting small cocci of Ca. H. crystalense attached to Ca. A. hamiconexum cells. Based on genomic information, Ca. H. crystalense potentially scavenges vitamins, sugars, nucleotides, and reduced redox-equivalents from its host and thus has a similar metabolism as Nanoarchaeum equitans . These findings give insight into host-symbiont interactions among members of two uncultivated archaeal phyla that thrive in a deep subsurface aquifer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genome-Wide Informative Microsatellite Markers and Population Structure of Fusarium virguliforme from Argentina and the USA

Soybean sudden death syndrome (SDS) is a destructive disease that causes substantial yield losses in South and North America. Whereas four Fusarium species were identified as the causal agents, F. virguliforme is the primary SDS-causing pathogen in North America and it also contributes substantially to SDS in Argentina. In this study, we comparatively analyzed genome assemblies of four F. virguliforme strains and identified 29 informative microsatellite markers. Sixteen of the 29 markers were used to investigate the genetic diversity and population structure of this pathogen in a collection of 90 strains from Argentina and the USA. A total of 37 multilocus genotypes (MLGs) were identified, including 10 MLGs in Argentina and 26 in the USA. Only MLG2, the most dominant MLG, was found in both countries. Analyses with three different approaches showed that these MLGs could be grouped into three clusters. Cluster IA consisting of four MLGs exclusively from the USA has much higher genetic diversity than the other two clusters, suggesting that it may be the ancestral cluster although additional data are necessary to support this hypothesis. Clusters IB and II consisted of 13 and 21 MLGs, respectively. MLGs belonging to these two clusters were present in all four sampled states in Argentina and all five sampled states in the USA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Defining Disease, Diagnosis, and Translational Medicine within a Homeostatic Perturbation Paradigm: The National Institutes of Health Undiagnosed Diseases Program Experience [plus supplemental information]

Traditionally, the use of genomic information for personalized medical decisions relies on prior discovery and validation of genotype–phenotype associations. This approach constrains care for patients presenting with undescribed problems. The National Institutes of Health (NIH) Undiagnosed Diseases Program (UDP) hypothesized that defining disease as maladaptation to an ecological niche allows delineation of a logical framework to diagnose and evaluate such patients. Herein, we present the philosophical bases, methodologies, and processes implemented by the NIH UDP. The NIH UDP incorporated use of the Human Phenotype Ontology, developed a genomic alignment strategy cognizant of parental genotypes, pursued agnostic biochemical analyses, implemented functional validation, and established virtual villages of global experts. This systematic approach provided a foundation for the diagnostic or non-diagnostic answers provided to patients and serves as a paradigm for scalable translational research.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Signatures of optimal codon usage in metabolic genes inform budding yeast ecology

Reverse ecology is the inference of ecological information from patterns of genomic variation. One rich, heretofore underutilized, source of ecologically relevant genomic information is codon optimality or adaptation. Bias toward codons that match the tRNA pool is robustly associated with high gene expression in diverse organisms, suggesting that codon optimization could be used in a reverse ecology framework to identify highly expressed, ecologically relevant genes. To test this hypothesis, we examined the relationship between optimal codon usage in the classic galactose metabolism ( GAL ) pathway and known ecological niches for 329 species of budding yeasts, a diverse subphylum of fungi. We find that optimal codon usage in the GAL pathway is positively correlated with quantitative growth on galactose, suggesting that GAL codon optimization reflects increased capacity to grow on galactose. Optimal codon usage in the GAL pathway is also positively correlated with human-associated ecological niches in yeasts of the CUG-Ser1 clade and with dairy-associated ecological niches in the family Saccharomycetaceae. For example, optimal codon usage of GAL genes is greater than 85% of all genes in the genome of the major human pathogen Candida albicans (CUG-Ser1 clade) and greater than 75% of genes in the genome of the dairy yeast Kluyveromyces lactis (family Saccharomycetaceae). We further find a correlation between optimization in the GAL actose pathway genes and several genes associated with nutrient sensing and metabolism. This work suggests that codon optimization harbors information about the metabolic ecology of microbial eukaryotes. This information may be particularly useful for studying fungal dark matter—species that have yet to be cultured in the lab or have only been identified by genomic material.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A new comprehensive method for detection of livestock-related pathogenic viruses using a target enrichment system

Highlights: • Development of a comprehensive method to detect viruses using SureSelect system. • A method by which almost the full length of the viral genome can be determined without virus isolation. • Widely available methods for comprehensive analysis of virus genomic information. We tested usefulness of a target enrichment system SureSelect, a comprehensive viral nucleic acid detection method, for rapid identification of viral pathogens in feces samples of cattle, pigs and goats. This system enriches nucleic acids of target viruses in clinical/field samples by using a library of biotinylated RNAs with sequences complementary to the target viruses. The enriched nucleic acids are amplified by PCR and subjected to next generation sequencing to identify the target viruses. In many samples, SureSelect target enrichment method increased efficiencies for detection of the viruses listed in the biotinylated RNA library. Furthermore, this method enabled us to determine nearly full-length genome sequence of porcine parainfluenza virus 1 and greatly increased Breadth, a value indicating the ratio of the mapping consensus length in the reference genome, in pig samples. Our data showed usefulness of SureSelect target enrichment system for comprehensive analysis of genomic information of various viruses in field samples.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Insights of biomass recalcitrance in natural Populus trichocarpa variants for biomass conversion

Populus has been investigated as a promising biomass feedstock for alternative fuels and chemicals. Physicochemical characteristics and genomic information of biomass feedstocks are among the essential information that can help not only advance our understanding of biomass recalcitrance but also in its efficient utilization. Here in this paper, the recalcitrance of natural Populus variants was elucidated in three aspects: (1) sugar release, (2) physicochemical properties, and (3) relative variation of gene expression within natural poplar variants. The sugar release performance of natural Populus variants was evaluated with their correlation with biomass recalcitrance-related characteristics. Among the physicochemical properties of poplar, the lignin content, lignin molecular weight, lignin S/G ratio, and cellulose accessibility were found to correlate with sugar release. The results demonstrated that the lignin content was negatively correlated with sugar release, whereas the lignin molecular weight, lignin S/G ratio, and cellulose accessibility were positively associated with poplar sugar release. The trend of differential gene expression of each variant also supports the characterization results and their effects on biomass conversion.

09 BIOMASS FUELS↗
DOE OSTI2016

The “Who” and “How” of Microbial Control over Soil Carbon Dynamics: a Multi-omics, Stable Isotope Probing, and Modeling Approach

Soils are the largest repository of organic carbon (C) in the terrestrial biosphere and represent an important source of CO 2 to the atmosphere, releasing 60-75 Pg C annually through microbial decomposition of organic materials. Microbes are key drivers of C cycling, and exhibit a large range in C use efficiency (CUE). CUE is the substrate C incorporated into biomass per substrate assimilated. While small changes in CUE can have profound effects on soil CO 2 flux, our understanding of the intersection of genomic and abiotic factors driving soil CUE dynamics is still very limited. Our long-term goal is to better predict the fate of soil C by developing mathematical and ecosystem models of SOM decomposition that incorporate a genetic and physiological understanding of CUE. The goal of this work was to define genes, metabolic pathways, and phylogenetic signals associated with microbial CUE for terrestrial microorganisms (bacteria and fungi). Our specific objectives are to: (1) Define genomic markers that indicate how terrestrial bacteria and fungi change CUE in response to environmental drivers of microbial activity; (2) Determine how well genomic markers identified predict CUE in soils; and (3) Improve predictions of soil C by incorporating genomics-informed CUE into ecosystem C models based on genomic features defined in and validated for soil in the course of this work. We address these objectives by coupling multi-omics analyses (genomics, metatranscriptomics) with physiological assays (CUE, enzyme activities) across environmental drivers (substrate quantity/quality, temperature, moisture). We employ a hierarchical approach to incrementally scale from cells to ecosystems, starting with pure cultures of bacteria and fungi, then mock communities in artificial, organic matter-free soil, then finally field soil manipulated to elicit microbial communities differing in community composition and CUE. By focusing on microbial isolates and communities in a temperate forest (Harvard Forest), we leverage a rich context for validating data based on multiple ongoing field, lab and modeling studies of soil C cycling. This research couples two culture collections of fungi and bacteria isolated from the Harvard Forest, along with over a decade of field measurements of CUE and C cycling, and microbial community analyses using metagenomics and metatranscriptomics. Because microbial feedbacks to the environment are regulated at the organismic level, the foundation of this research is the physiology and genomics of CUE among isolates that we have determined to be either dominant in our soil system, sensitive to climate change factors, or both. A series of three experiments using artificial soil, lab incubation of field-collected soil, and a field manipulation is designed to validate potential omics-informed, novel genomic markers to be used as proxies for CUE in models. We test our new understanding of the genetic basis for CUE and its implications for soil C dynamics using the trait-based model DEMENT and the ecosystem models MIIMICS and SCAMPS. All models are modified to simulate SOM decomposition in mineral soils and validated with other temperate forest climate change manipulation studies. By developing mathematical and ecosystem models of SOM decomposition that incorporate a genetic and physiological understanding of CUE, we hope to facilitate more realistic models of SOM decomposition for C cycling in soils.

54 ENVIRONMENTAL SCIENCES↗