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83 records · Page 5

General Biology 2 Sugar Beet Lab - Spring 24

This module uses the Department of Energy Systems Biology Knowledgebase (KBase) platform to explore topics such as genome assembly, metagenomics, and phylogenomics. Here students will use sequences from DNA that they collected to compare the metagenomes of microbial communities from the rhizosphere of plants grown in fertilized vs. unfertilized soils. Using these data students will evaluate the impact of fertilizer on these communities and how these microbial communities influence soil health and plant growth.

Schirmer, Aaron [Northeastern Illinois University,↗

Genome collection processing for “Conserved upper thermal limits and small safety margins in soil copiotrophic bacteria”

We extracted the genomic DNA of 400 randomly selected isolates using a Quick-DNA Microprep Kit (Zymo Research D3020) according to the manufacturer’s protocol. We then submitted the extracted gDNA samples for short-read Illumina sequencing (200 Mbp) at SeqCoast Genomics (Portsmouth, NH, USA). After preprocessing the sequences using Trimmommatic (Bolger et al. 2014), we assembled the genomes using SPADES (Bankevich et al. 2012) and checked the quality of each assembly using QUAST (Gurevich et al. 2013). We processed the genome assemblies using a KBase (v1.4.0) pipeline (Allen et al. 2017; Arkin et al. 2018). Briefly, we used DRAM (v0.1.2) with default settings to annotate the genome assemblies. We then evaluated genome quality and possible contamination levels using CheckM (v1.0.18) (Parks et al. 2015) and retained genomes with completeness above 98% and contamination below 5% (n = 354), following the authors' guidelines. We then obtained taxonomic assignments for all remaining isolates using the Genome Taxonomy Database tool GTDB-Tk (v2.3.2, database version r214) (Chaumeil et al. 2019). We constructed a phylogenetic tree using the tool SpeciesTree (v2.2.0). We then trimmed the tree (using Trim SpeciesTree to GenomeSet- v1.4.0), retaining only tips within our collection with measured thermal performance.

59 BASIC BIOLOGICAL SCIENCES↗

General Biology 2 Sugar Beet Lab - SU2025 - Final

This module uses the Department of Energy Systems Biology Knowledgebase (KBase) platform to explore topics such as genome assembly, metagenomics, and phylogenomics. Here students will use sequences from DNA that they collected to compare the metagenomes of microbial communities from the rhizosphere of plants grown in fertilized vs. unfertilized soils. Using these data students will evaluate the impact of fertilizer on these communities and how these microbial communities influence soil health and plant growth.

59 BASIC BIOLOGICAL SCIENCES↗

Integrative Modeling and Analysis of Fungal Central Carbon Metabolism

Over a thousand fungal genomes have been sequenced, yet manually curated genome-scale metabolic models (GEMs) are available for only a limited number of species. Moreover, these models have often been developed independently, leading to inconsistencies in namespaces, compartment definitions, and pathway representations that hinder comparative analysis, the systematic reuse of prior curation efforts, and the integration of consolidated metabolic knowledge. Here, we present the Consolidated Fungal Core Metabolism Model (CFCMM), constructed by integrating thirteen published fungal models spanning Ascomycota, Mucoromycota, and both Crabtree-positive and Crabtree-negative yeasts. We harmonized metabolites and reactions into a non-redundant shared ModelSEED ontological space, standardized compartmentalization, and refined gene–protein–reaction (GPR) rules. Using pathway-level visualization and systematic gap detection, we further improved the integrated network through literature-guided curation to correct stoichiometry, stereospecificity, and pathway architecture. Orthologous protein family reconstruction and functional annotation workflows were used to validate and inform GPR associations, with particular emphasis on ambiguous enzyme superfamilies and membrane-associated components. Using the resulting CFCMM, we built high-quality central carbon core models for each fungus and performed flux balance analysis to quantify ATP-yield variation under aerobic and anaerobic conditions, explicitly evaluating scenarios driven by differences in electron transport chain (ETC) composition. Simulations reproduced the expected fermentative yield of approximately 2 mmol ATP per mmol glucose under anaerobic conditions and separated the thirteen fungi into two bioenergetic groups under aerobic respiration based on Complex I status, with predicted yields of approximately 30 versus 22 mmol ATP per mmol glucose. Forcing flux through the alternative oxidase bypass further reduced ATP yields to approximately 12 and 4 mmol ATP per mmol glucose in Complex I-containing and Complex I-lacking fungi, respectively. Collectively, this work provides a manually curated, ModelSEED-consistent, and extensible fungal core metabolic template, deployed in DOE KBase as a resource for automated reconstruction of central carbon core models from any sequenced fungal genome. In addition, the CFCMM provides modular components for developing GEMs with more accurate energy predictions and enables robust comparative analyses of fungal bioenergetics and core metabolic diversity

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of Multiple Trichloroethene, cis-Dichloroethene and 1,1-Dichloroethene Degrading Propanotrophic Communities

Aerobic cometabolism offers a viable strategy for the remediation of chlorinated solvent plumes at oxic sites where anaerobic approaches are limited. In this study, propane-enriched mixed cultures (derived from agricultural soils and an impacted site sediment) which previously degraded 1,4-dioxane, were evaluated for their capacity to also degrade trichloroethene (TCE), cis-1,2-dichloroethene (cDCE), and 1,1-dichloroethene (1,1-DCE) over successive transfers. Sustained biodegradation of TCE and cDCE was observed across multiple enrichments, and cultures enriched on one compound generally degraded the other. In contrast, 1,1-DCE biodegradation was restricted to a subset of cultures and removal times increased over transfers. Further, 1,1-DCE removal was absent at elevated concentrations, both trends consistent with inhibitory or toxic effects. Whole genome sequencing analyses revealed pronounced substrate-dependent selection of microbial communities, with cDCE-degrading cultures being dominated by Mycobacterium and Mycolicibacterium, whereas TCE-degrading cultures were dominated by Rhodococcus. Rhodococcus metagenome-assembled genomes (MAGs) in the TCE degrading cultures classified as R. opacus or R. wratislaviensis. 1,1-DCE degrading cultures were dominated by Pseudonocardia, although the associated MAGs contained a truncated propane monooxygenase alpha subunit. Functional gene analysis identified both group 5 (prmABCD) and putative group 6 propane monooxygenases. The following KBase narratives contain the quality controlled reads, MAGs (fasta assemblies) and the prokka annotations for each assembly TCE Site 1A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254918) TCE Soil 2A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254919) TCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254920) TCE Soil T4 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254921) cDCE Site 1A 1B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254915) cDCE Soils T2 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254927) cDCE Soil T3 A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254928) cDCE Soil 4A and B Propanotrophic MAGs (https://narrative.kbase.us/narrative/254942) 1,1-DCE T2 T3 Propanotrophic MAGs (https://narrative.kbase.us/narrative/254903)

59 BASIC BIOLOGICAL SCIENCES↗

Community Modeling and Flux Balance Analysis of Synthetic Bacterial Community in MOPS Medium

This narrative was used for the 4-member community modeling using MOPS medium for the bacteria isolated from Populus deltoides (PD). 10 bacterial strains isolated from PD were co-cultured as a synthetic microbial community in MOPS minimal medium. After 15 passages there were 4 members survived in MOPS medium. The genome of each community member was sequenced and uploaded into KBase for genome annotation and metabolic modeling. To simulate the metabolic interactions among the finally surviving community members, the individual metabolic models of each strain were merged into a compartmentalized community model, and then the community model was gapfilled using MOPS medium. The FBA modeling was performed and the metabolites exchange among community members was proposed. The publication by Jia Wang, Dana L. Carper, Leah H. Burdick, Him Shrestha, Manasa Appidi, Paul E. Abraham, Collin M. Timm, Robert L. Hettich, Dale A. Pelletier, Mitchel J. Doktycz can be found here: https://doi.org/10.​1016/​j.​csbj.​2021.​03.​034

59 BASIC BIOLOGICAL SCIENCES↗

Community Modeling and Flux Balance Analysis of Synthetic Bacterial Community in R2A Medium

This narrative was used for the 3-member community modeling using R2A medium for the bacteria isolated from Populus deltoides (PD). 10 bacteiral strains isolated from PD were co-cultured as a synthetic microbial community in R2A complex medium. After 15 passages, there were 3 members survived in R2A medium. The genome of each community member was sequenced and uploaded into KBase for genome annotation and metabolic modeling. To simulate the metabolic interactions among the finally surviving community members, the individual metabolic models of each strain were merged into a compartmentalized community model, and then the community model was gapfilled using R2A medium. The FBA modeling was performed and the metabolites exchange among community members was proposed. The publication by Jia Wang, Dana L. Carper, Leah H. Burdick, Him Shrestha, Manasa Appidi, Paul E. Abraham, Collin M. Timm, Robert L. Hettich, Dale A. Pelletier, Mitchel J. Doktycz can be found here: https://doi.org/10.​1016/​j.​csbj.​2021.​03.​034

59 BASIC BIOLOGICAL SCIENCES↗

Narrative for Bioproject PRJNA623111

This Narrative is part of a collection used in publications focused on the microbial ecology of fjord sediment in the high Arctic, Svalbard. This paper took a genome-centric approach to uncover novel metabolic capabilities of the Acidobacteriota clade. Metagenomic data was coupled with amplicon sequencing of 16S rRNA and dissimilatory sulfite reductase (dsrB) genes, and transcripts (available under NCBI-Genbank Bioproject PRJNA623111), and gene expression analyses of tetrathionate-amended microcosms. This Narrative contains the metagenomic assemblies that were constructed within KBase for reproducibility. These include: stnF metagenome assembly stnAB metagenome assembly stnAC metagenome assembly These metagenome assemblies served as the launching point for an additional publication focused on a different clade of bacteria (Buongiorno et al., 2020). Link to that Narrative landing page here. Please cite: Flieder, Mathias, Joy Buongiorno, Craig W. Herbold, Bela Hausmann, Thomas Rattei, Karen G. Lloyd, Alexander Loy, and Kenneth Wasmund. "Novel taxa of Acidobacteriota implicated in seafloor sulfur cycling." The ISME Journal (2021): 1-22.

59 BASIC BIOLOGICAL SCIENCES↗

Quantifying microbial roles in environmental iron oxidation via an integrated kinetics, `omics and metabolic modeling study (Final Report)

Iron oxyhydroxides are extremely reactive components of environmental systems, and therefore exert a strong influence on biogeochemical cycles. These oxyhydroxides strongly adsorb many biologically-relevant elements, including organic carbon and phosphate, as well as a wide range of metals including uranium and actinide species. Thus, the formation mechanism of iron oxyhydroxides are key to understanding both nutrient and contaminant cycling. Microorganisms can catalyze iron oxidation and promote the formation of Fe biominerals and thus are increasingly recognized as important players in biogeochemical cycling. However, it is completely unknown how much of environmental iron oxidation is biologically mediated versus abiotic, and various challenges in studying microbial iron oxidation have hindered accurate incorporation into hydrobiogeochemical models. The overarching goal of our work was to quantify and constrain microbial iron oxidation rates and use ‘omics to gain insight into the controls on this process, while developing tools to enable integration of biotic iron oxidation into hydrobiogeochemical models. Our work focused on the Savannah River Site (SRS) in South Carolina, where extensive microbial iron oxidation has been observed. At Tims Branch, part of the Argonne National Laboratory Wetland Hydrobiogeochemistry Science Focus Area (Argonne SFA), where groundwater discharges into a stream, iron-oxidizing microbial mats form and appear to be a major sink of uranium. In the wetlands that surround Tims Branch, there are wide swaths of iron microbial mats and flocs (mobilized mat). We measured biotic and abiotic iron oxidation rates using mats and water sampled from these sites and found that iron oxidation is primarily carried out by chemolithotrophic microorganisms. The resulting rate constants can be incorporated into models. These mats were characterized by metagenomics and metatranscriptomics, which showed that aerobic chemolithotrophs were the dominant iron-oxidizing bacteria (FeOB), and these included Gallionellaceae and Leptothrix, and possibly Rhodoferax, which is known as an Fe-reducer but may also oxidize Fe(II). This demonstrated that diverse FeOB can coexist and suggests that there are a range of niches and therefore drivers of chemolithotrophic iron oxidation. Analysis of reconstructed genomes strongly suggests that a major factor in diversity is carbon source, as genomes contained varied pathways for autotrophy and heterotrophy. We performed an in-depth analysis of Leptothrix ochracea genomes, since this sheath-former is one of the primary mat builders, yet its physiology remained unresolved. A combination of genomics, transcriptomics, and metabolic modeling suggest that L. ochracea grows mixotrophically using a combination of Fe(II) and organics for energy and both inorganic and organic carbon to create biomass. This contrasts with the largely autotrophic Gallionellaceae (Gallionella, Sideroxydans, and Ferriphaselus) also present in the mats and flocs. Remarkably, multiple FeOB, both Leptothrix and Gallionellaceae, showed activity in response to Fe(II) in live mat incubations. We tracked the gene expression of individual MAGs to Fe(II) and found that various autotrophic and heterotrophic FeOB responded to Fe(II), increasing expression of both carbon fixation and organic utilization genes. The results of the integrated field, kinetics, and omics studies give detailed insight into 1) the taxa that oxidize Fe, and 2) how they connect Fe, C, and N cycles. Towards the goal of connecting omics data to hydrobiogeochemical models, we worked with the KBase team to create a template metabolic model for chemolithotrophic iron oxidation. We initially modeled the well-characterized isolate Gallionellaceae Sideroxydans lithotrophicus, and also applied the model to the mixotroph L. ochracea. In all, we have characterized diverse FeOB in a representative wetland system and solved key problems that enable better incorporation of iron-oxidizing microbes into hydrobiogeochemical models.

54 ENVIRONMENTAL SCIENCES↗