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At least 361 records · Page 20

KBase Silver Case Study: Determining Media Formulation Requirements for Isolation of Microbiome Constituents

KBase has powerful tools for extracting microbial genomes from metagenomes and performing phylogenomic analysis and metabolic modeling. These tools can be used to predict key media ingredients for isolating uncultured members of microbiomes. Essential to this process are high-quality genomes extracted from metagenomic assemblies, and Kbase has a tool for assessing the quality of genomes too. Below we identify growth factors for a myxobacteria ("slime bacteria") yet to be isolated from the rhizosphere of Miscanthus xgiganteus (hybrid of "Silvergrass"), cultivated at the Kellogg Biological Station in Michigan. Data was transferred with Globus from JGI-IMG. This narrative and the "KBase Gold Case Study: Can you find Delftia?" make up the Silver and Gold Narrative Set for teaching metagenomics concepts to students in the BIT 477/577 course at North Carolina State University. This tutorial will guide the user through the process of extracting and annotating high-quality genomes from a metagenomic data, performing phylogenomic analysis, building a metabolic model, and using these to predict nutrient requirments for growth and isolation of corresponding microbes.

59 BASIC BIOLOGICAL SCIENCES↗

Accurate and complete genomes from metagenomes

Genomes are an integral component of the biological information about an organism; thus, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures, and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs); but gaps, local assembly errors, chimeras, and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and, in some cases, achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of about 7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. The analysis of cumulative GC skew identified potential misassemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.

59 BASIC BIOLOGICAL SCIENCES↗

PET-FBA: A lightweight enzyme allocation and thermodynamics-constrained flux analysis approach to explore Escherichia coli metabolic adaptation to intracellular acidification

Escherichia coli employs diverse strategies to adapt to acidic environments that disrupt enzyme activity and the thermodynamic feasibility of essential reactions. To understand the impact of pH stress on cell metabolism, we present the PET-FBA (pH-, Enzyme protein allocation-, and Thermodynamics-constrained Flux Balance Analysis) framework. PET-FBA extends genome-scale modeling by integrating enzyme protein costs and reaction Gibbs free energy changes. Additionally, by incorporating pH-dependent enzyme kinetics in response to intracellular acidification, this framework enables the simulation of E. coli's metabolic adjustments across varying external pH levels. The model's accuracy is validated by comparing in silico growth simulations with experimental measurements under both anaerobic and aerobic conditions, as well as in silico gene knockouts of essential genes. By explicitly incorporating pH effects, our model accurately replicates the metabolic shift towards lactate production as the primary fermentation product at low pH in anaerobic conditions. This shift is only predicted when enzyme kinetics are dynamically adjusted as a function of pH. Further analysis revealed that this shift can be attributed to the reduced protein efficiency of the acetyl-CoA branch compared to lactate dehydrogenase under acidic stress, which then becomes crucial for maintaining NAD regeneration and cell growth at low pH. Furthermore, we identified strategies for enhancing cell growth under acidic anaerobic conditions by improving the enzyme activity of lactate dehydrogenase and pyruvate formate lyase, which increases NAD production efficiency and reduces enzyme protein allocation costs. Designed as a lightweight yet versatile framework, PET-FBA enables efficient genome-scale metabolic analysis. Using E. coli as a model system, our framework provides a systematic approach to understanding metabolic responses to environmental stress, pinpointing key metabolic bottlenecks, and identifying potential targets for strain optimization.

42 ENGINEERING↗

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the “chassis” organism’s metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

59 BASIC BIOLOGICAL SCIENCES↗

Identification of a new circulating recombinant form of human immunodeficiency virus type 1, CRF124_cpx involving subtypes A, G, H, and CRF27_cpx in Angola

Angola, located in Central Africa, has around 320,000 (270,000–380,000) people living with human immunodeficiency virus (HIV)/AIDS, equivalent to 1% of the country’s population at the end of 2021. A previous study conducted in 2012, using Angolan samples collected between 2008 and 2010 revealed a high prevalence of HIV-1 recombinants, around 42% of sequences, with 21% showing the same UH profile in partial pol region which were grouped into a monophyletic cluster with high bootstrap support. Thus, the objective of the present work was to obtain complete genomes of those sequences and characterize them, aiming at a description of a new circulating recombinant form (CRF). Whole blood from nine HIV-1 UH pol -infected individuals had their genomic DNA extracted, and nested PCR was used to amplify seven overlapping fragments targeting the full-length HIV-1 genome. The final classification was based on maximum likelihood trees, and recombination analyses were performed using a bootscan from the Simplot program. BLAST and Los Alamos Database inspections were used to search other similar H-like pol sequences. Complete genome amplification was possible for three samples, partial genomes were obtained for the other three, and only pol was available for the remaining three sequences. Bootscan analysis of the two whole-genome and three partial genome sequences retrieved from people living with HIV/AIDS (PLHIVA) without epidemiological linkage showed the same complex recombination profile involving HIV-1 subtypes A/G/H/CRF27_cpx, with a total of six recombinant breakpoints, aiming to classify a new HIV-1 CRF124_cpx. We found no other full-length HIV-1 genomes with the same mosaic profile; however, we identified 33 partial pol sequences, mainly sampled from Angola between 2001 to 2019, with the same H-like profile. Bayesian analysis of H and H-like pol sequences indicates that CRF124_cpx probably originated in Angola at mid-1970s, indicating that this CRF has been circulating in the country for a long time. In summary, our study describes a new CRF circulating principally in Angola and highlights the importance of continuing molecular surveillance studies, especially in countries with high molecular diversity of HIV.

60 APPLIED LIFE SCIENCES↗

PhycoCosm, a comparative algal genomics resource

Abstract Algae are a diverse, polyphyletic group of photosynthetic eukaryotes spanning nearly all eukaryotic lineages of life and collectively responsible for ∼50% of photosynthesis on Earth. Sequenced algal genomes, critical to understanding their complex biology, are growing in number and require efficient tools for analysis. PhycoCosm (https://phycocosm.jgi.doe.gov) is an algal multi-omics portal, developed by the US Department of Energy Joint Genome Institute to support analysis and distribution of algal genome sequences and other ‘omics’ data. PhycoCosm provides integration of genome sequence and annotation for >100 algal genomes with available multi-omics data and interactive web-based tools to enable algal research in bioenergy and the environment, encouraging community engagement and data exchange, and fostering new sequencing projects that will further these research goals.

59 BASIC BIOLOGICAL SCIENCES↗

Diploid-dominant life cycles characterize the early evolution of Fungi

Most of the described species in kingdom Fungi are contained in two phyla, the Ascomycota and the Basidiomycota (subkingdom Dikarya). As a result, our understanding of the biology of the kingdom is heavily influenced by traits observed in Dikarya, such as aerial spore dispersal and life cycles dominated by mitosis of haploid nuclei. We now appreciate that Fungi comprises numerous phylum-level lineages in addition to those of Dikarya, but the phylogeny and genetic characteristics of most of these lineages are poorly understood due to limited genome sampling. Here, we addressed major evolutionary trends in the non-Dikarya fungi by phylogenomic analysis of 69 newly generated draft genome sequences of the zoosporic (flagellated) lineages of true fungi. Our phylogeny indicated five lineages of zoosporic fungi and placed Blastocladiomycota, which has an alternation of haploid and diploid generations, as branching closer to the Dikarya than to the Chytridiomyceta. Our estimates of heterozygosity based on genome sequence data indicate that the zoosporic lineages plus the Zoopagomycota are frequently characterized by diploid-dominant life cycles. We mapped additional traits, such as ancestral cell-cycle regulators, cell-membrane– and cell-wall–associated genes, and the use of the amino acid selenocysteine on the phylogeny and found that these ancestral traits that are shared with Metazoa have been subject to extensive parallel loss across zoosporic lineages. Together, our results indicate a gradual transition in the genetics and cell biology of fungi from their ancestor and caution against assuming that traits measured in Dikarya are typical of other fungal lineages.

59 BASIC BIOLOGICAL SCIENCES↗

Analysis of the cyanobacterial amino acid metabolism with a precise genome-scale metabolic reconstruction of Anabaena sp. UTEX 2576

Filamentous cyanobacteria such as Anabaena sp. UTEX 2576 (a.k.a., Nostoc sp. PCC 7120) are a sustainable platform for commodity and specialty chemical production. Anabaena is a model cyanobacterium adopted to study production of nitrogen-containing metabolites useful for chemical, cosmetic, and pharmaceutical industries. Therefore, a precise description of the Anabaena metabolic network is desired to analyze their amino-acid metabolism and elucidate potential applications of these cyanobacteria as host organisms for biotechnological production. Secondary metabolite production depends on the metabolic availability of amino acids. We provide new insight on the biotechnological utilization of Anabaena after predicting phycocyanobilin and amino-acid production rates, using a genome-scale metabolic model (iDN1004). This metabolic reconstruction is a highly comprehensive representation of the global metabolism of Anabaena, which also contains experimental biomass equations and constraints under photoautotrophic and photodiazotrophic growth. Modelling results ranked proteinogenic amino acids based on predicted metabolic fluxes through amino-acid producing reactions. From these, l-aspartate, glycine, l-serine, l-valine, l-alanine, l-threonine, and l-leucine were selected as the best branching points to conduct metabolic engineering, where l-aspartate, l-serine, l-valine and glycine serve as potential precursors of the secondary metabolites Schizokinen (a siderophore), Sphingosine (a ceramide), Lyngbyatoxin A (an alkaloid), and Shinorine (a sunscreen).

59 BASIC BIOLOGICAL SCIENCES↗

Chronic Lunar Dust Exposure on Rat Cornea: Evaluation by Gene Expression Profiling

Lunar dust is capable of entering habitats and vehicle compartments by sticking to spacesuits or other objects that are transferred into the spacecraft from the lunar surface and has been reported to cause irritation upon exposure. During the Apollo missions, crewmembers reported irritation specifically to the skin and eyes after contamination of the lunar and service modules. It has since been hypothesized that ocular irritation and abrasion might occur as a result of such exposure, impairing crew vision. Recent work has shown that both ultrafine and unground lunar dust exhibited minimal irritancy of the ocular surface (i.e., cornea); however, the assessment of the severity of ocular damage resulting from contact of lunar dust particles to the cornea has focused only on macroscopic signs of mechanical irritancy and cytotoxicity. Given the chemical reactive properties of lunar dust, exposure of the cornea may contribute to detrimental effects at the molecular level including but not limited to oxidative damage. Additionally, low level chronic exposures may confound any results obtained in previous acute studies. We report here preliminary results from a tissue sharing effort using 10‐week‐old Fischer 344 male rats chronically exposed to filtered air or jet milled lunar dust collected during Apollo 14 using a Jaeger‐NYU nose‐only chamber for a total of 120 hours (6 hours daily, 5 days a week) over a 4‐week period. RNA was isolated from corneas collected from rats at 1 day and 7 days after being exposed to concentrations of 0, 20, and 60 mg/m3 of lunar dust. Microarray analysis was performed using the Affymetrix GeneChip Rat Genome 230 2.0 Array with Affymetrix Expression Console and Transcriptome Analysis Console used for normalization and secondary analysis. An Ingenuity iReport"TM" was then generated for canonical pathway identification. The number of differentially expressed genes identified increases with dose compared to controls suggesting a more severe response to the lunar dust insult at higher levels. Pathways of interests that have been identified in all exposed samples include oxidative stress response, mitochondrial dysfunction, fibrosis, epithelial healing, TGF-Beta signaling, and extracellular matrix remodeling. Several biological processes related to cell migration, cellular proliferation, and eye development were also identified to be altered by exposure to lunar dust. Our preliminary results suggest that even a chronic insult of lunar dust as low as 20 mg/m(exp 3) elicits a molecular response in cornea tissue. Lunar dust on the surface of the moon would have the added properties of ionization and activation potentially leading to further damage to the cornea and greater sensitivity to any other environmental insult such as exposure to radiation. Additional studies are required to fully assess the risk of vision impairment and the mechanistic responses initiated in cornea exposed to lunar dust as well as the potential for long‐term effects to astronaut health

Theriot, C. A.↗

Global analysis of the yeast knockout phenome

Genome-wide phenotypic screens in the budding yeast Saccharomyces cerevisiae, enabled by its knockout collection, have produced the largest, richest, and most systematic phenotypic description of any organism. However, integrative analyses of this rich data source have been virtually impossible because of the lack of a central data repository and consistent metadata annotations. Here, we describe the aggregation, harmonization, and analysis of ~14,500 yeast knockout screens, which we call Yeast Phenome. Using this unique dataset, we characterized two unknown genes (YHR045W and YGL117W) and showed that tryptophan starvation is a by-product of many chemical treatments. Furthermore, we uncovered an exponential relationship between phenotypic similarity and intergenic distance, which suggests that gene positions in both yeast and human genomes are optimized for function.

59 BASIC BIOLOGICAL SCIENCES↗

Chromosome-level assembly and analysis of Camelina neglecta : a novel diploid model for Camelina biotechnology research

Camelina neglecta is a new diploid Brassicaceae species, which has great research value because of its close relationship with the hexaploid oilseed crop Camelina sativa. Here, we report a chromosome-level assembly of C. neglecta with a total length of 210 Mb. By adopting PacBio sequencing and Hi-C technology, the C. neglecta genome was assembled into 6 chromosomes with scaffold N50 of 29.62 Mb. C. neglecta has undergone the whole-genome triplication (γ) shared among eudicots and two whole-genome duplications (α and β) shared by crucifers, but it has not undergone a specific whole-genome duplication event. By synteny analysis between C. neglecta and C. sativa, we successfully used the method of calculating Ks to distinguish the three subgenomes of C. sativa and determined that C. neglecta was closest to the first subgenome (SG1) of C. sativa. Further, transcriptomic analysis revealed the key genes associated with seed oil biosynthesis and its transcriptional regulation, including SAD, FAD2, FAD3, FAE1, ABI3, WRI1 and FUS3 displaying high expression levels in C. neglecta seeds. The high representability of C. neglecta as a model species for Camelina-based biotechnology research has been demonstrated for the first time. In particular, floral Agrobacterium tumefaciens infiltration-based transformation of C. neglecta, leading to overexpression of CvLPAT2, CpDGAT1 and CvFatB1 transgenes, was demonstrated for medium-chain fatty acid accumulation in C. neglecta seed oil. This study provides an important genomic resource and establishes C. neglecta as a new model for oilseed biotechnology research.

60 APPLIED LIFE SCIENCES↗

VIZARD: analysis of Affymetrix Arabidopsis GeneChip data

SUMMARY: The Affymetrix GeneChip Arabidopsis genome array has proved to be a very powerful tool for the analysis of gene expression in Arabidopsis thaliana, the most commonly studied plant model organism. VIZARD is a Java program created at the University of California, Berkeley, to facilitate analysis of Arabidopsis GeneChip data. It includes several integrated tools for filtering, sorting, clustering and visualization of gene expression data as well as tools for the discovery of regulatory motifs in upstream sequences. VIZARD also includes annotation and upstream sequence databases for the majority of genes represented on the Affymetrix Arabidopsis GeneChip array. AVAILABILITY: VIZARD is available free of charge for educational, research, and not-for-profit purposes, and can be downloaded at http://www.anm.f2s.com/research/vizard/ CONTACT: moseyko@uclink4.berkeley.edu.

Non-NASA Center↗

Haplotype‐resolved genome assembly of Populus tremula × P. alba reveals aspen‐specific megabase satellite DNA

SUMMARY Populus species play a foundational role in diverse ecosystems and are important renewable feedstocks for bioenergy and bioproducts. Hybrid aspen Populus tremula × P. alba INRA 717‐1B4 is a widely used transformation model in tree functional genomics and biotechnology research. As an outcrossing interspecific hybrid, its genome is riddled with sequence polymorphisms which present a challenge for sequence‐sensitive analyses. Here we report a telomere‐to‐telomere genome for this hybrid aspen with two chromosome‐scale, haplotype‐resolved assemblies. We performed a comprehensive analysis of the repetitive landscape and identified both tandem repeat array‐based and array‐less centromeres. Unexpectedly, the most abundant satellite repeats in both haplotypes lie outside of the centromeres, consist of a 147 bp monomer PtaM147, frequently span >1 megabases, and form heterochromatic knobs. PtaM147 repeats are detected exclusively in aspens (section Populus ) but PtaM147‐like sequences occur in LTR‐retrotransposons of closely related species, suggesting their origin from the retrotransposons. The genomic resource generated for this transformation model genotype has greatly improved the design and analysis of genome editing experiments that are highly sensitive to sequence polymorphisms. The work should motivate future hypothesis‐driven research to probe into the function of the abundant and aspen‐specific PtaM147 satellite DNA.

Zhou, Ran↗

Disentangling Sources of Gene Tree Discordance in Phylogenomic Data Sets: Testing Ancient Hybridizations in Amaranthaceae s.l

Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. that was previously supported by morphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations.

59 BASIC BIOLOGICAL SCIENCES↗

JGI-Trichoderma v1.0

There is a series of Python and bash scripts to parse genomics datasets used to evaluate the coevolution of gene families and the feature importance of gene families using an SVM classifier. - Cover analysis: takes a list of single-copy genes in a set of genomes, aligns and builds the gene trees to determine if two gene families have a signature of covariation with one another. It parses the files to run phykit cover script described here: https://jlsteenwyk.com/PhyKIT/usage/index.html - SVM-classifier: This Python script is an SVM-based genomic classifier designed for biological data analysis. It combines machine learning with feature selection to identify important genomic markers and classify biological samples. Core Functionality: The script uses Support Vector Machines from scikit-learn to classify genomic data, incorporating SelectKBest for automated feature selection and leave-one-out cross-validation for performance assessment. It operates in multiple modes: feature ranking, optimal combination discovery, and sample prediction. Primary Applications: Genomic sample classification and biomarker discovery Feature importance analysis in high-dimensional biological datasets Prediction of sample categories based on genomic profiles Research applications requiring robust classification of biological data Key Advantages: High-dimensional handling: SVMs excel with genomic data's typical high feature-to-sample ratios Integrated feature selection: Reduces noise and computational overhead while identifying key markers Probability estimation: Provides confidence scores essential for biological interpretation Validation robustness: Leave-one-out cross-validation ensures reliable performance metrics Operational flexibility: Multiple analysis modes support different research phases from exploration to prediction

Stecca Steindorff, Andrei [Lawrence Berkeley Natio↗

A genome-wide association study of suicide attempts in the million veterans program identifies evidence of pan-ancestry and ancestry-specific risk loci

In this study, to identify pan-ancestry and ancestry-specific loci associated with attempting suicide among veterans, we conducted a genome-wide association study (GWAS) of suicide attempts within a large, multi-ancestry cohort of U.S. veterans enrolled in the Million Veterans Program (MVP). Cases were defined as veterans with a documented history of suicide attempts in the electronic health record (EHR; N = 14,089) and controls were defined as veterans with no documented history of suicidal thoughts or behaviors in the EHR ( N = 395,064). GWAS was performed separately in each ancestry group, controlling for sex, age and genetic substructure. Pan-ancestry risk loci were identified through meta-analysis and included two genome-wide significant loci on chromosomes 20 ( p = 3.64 × 10 -9 ) and 1 ( p = 3.69 × 10 -8 ). A strong pan-ancestry signal at the Dopamine Receptor D2 locus ( p = 1.77 × 10 -7 ) was also identified and subsequently replicated in a large, independent international civilian cohort ( p = 7.97 × 10 -4 ). Additionally, ancestry-specific genome-wide significant loci were also detected in African-Americans, European-Americans, Asian-Americans, and Hispanic-Americans. Pathway analyses suggested over-representation of many biological pathways with high clinical significance, including oxytocin signaling, glutamatergic synapse, cortisol synthesis and secretion, dopaminergic synapse, and circadian rhythm. These findings confirm that the genetic architecture underlying suicide attempt risk is complex and includes both pan-ancestry and ancestry-specific risk loci. Moreover, pathway analyses suggested many commonly impacted biological pathways that could inform development of improved therapeutics for suicide prevention.

60 APPLIED LIFE SCIENCES↗

Genome Extraction from Shotgun Metagenome Sequence Data

Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).

Chivian, Dylan↗

Moab Desert Crust - Sample 4E

Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).

Chivian, Dylan↗