Multiomics in the central Arctic Ocean for benchmarking biodiversity change.

Multiomics approaches need to be applied in the central Arctic Ocean to benchmark biodiversity change and to identify novel species and their genes. As part of MOSAiC, EcoOmics will therefore be essential for conservation and sustainable bioprospecting in one of the least explored ecosystems on Earth.

Metatranscriptomics sheds light on the links between the functional traits of fungal guilds and ecological processes in forest soil ecosystems.

Soil fungi belonging to different functional guilds, such as saprotrophs, pathogens, and mycorrhizal symbionts, play key roles in forest ecosystems. To date, no study has compared the actual gene expression of these guilds in different forest soils. We used metatranscriptomics to study the competition for organic resources by these fungal groups in boreal, temperate, and Mediterranean forest soils. Using a dedicated mRNA annotation pipeline combined with the JGI MycoCosm database, we compared the transcripts of these three fungal guilds, targeting enzymes involved in C- and N mobilization from plant and microbial cell walls. Genes encoding enzymes involved in the degradation of plant cell walls were expressed at a higher level in saprotrophic fungi than in ectomycorrhizal and pathogenic fungi. However, ectomycorrhizal and saprotrophic fungi showed similarly high expression levels of genes encoding enzymes involved in fungal cell wall degradation. Transcripts for N-related transporters were more highly expressed in ectomycorrhizal fungi than in other groups. We showed that ectomycorrhizal and saprotrophic fungi compete for N in soil organic matter, suggesting that their interactions could decelerate C cycling. Metatranscriptomics provides a unique tool to test controversial ecological hypotheses and to better understand the underlying ecological processes involved in soil functioning and carbon stabilization.

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes.

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC-ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.

Genome-scale phylogeny and comparative genomics of the fungal order Sordariales.

The order Sordariales is taxonomically diverse, and harbours many species with different lifestyles and large economic importance. Despite its importance, a robust genome-scale phylogeny, and associated comparative genomic analysis of the order is lacking. In this study, we examined whole-genome data from 99 Sordariales, including 52 newly sequenced genomes, and seven outgroup taxa. We inferred a comprehensive phylogeny that resolved several contentious relationships amongst families in the order, and cleared-up intrafamily relationships within the Podosporaceae. Extensive comparative genomics showed that genomes from the three largest families in the dataset (Chaetomiaceae, Podosporaceae and Sordariaceae) differ greatly in GC content, genome size, gene number, repeat percentage, evolutionary rate, and genome content affected by repeat-induced point mutations (RIP). All genomic traits showed phylogenetic signal, and ancestral state reconstruction revealed that the variation of the properties stems primarily from within-family evolution. Together, the results provide a thorough framework for understanding genome evolution in this important group of fungi.

Comparative genomics reveals a dynamic genome evolution in the ectomycorrhizal milk-cap (Lactarius) mushrooms.

Ectomycorrhizal fungi play a key role in forests by establishing mutualistic symbioses with woody plants. Genome analyses have identified conserved symbiosis-related traits among ectomycorrhizal fungal species, but the molecular mechanisms underlying host specificity remain poorly known. We sequenced and compared the genomes of seven species of milk-cap fungi (Lactarius, Russulales) with contrasting host specificity. We also compared these genomes with those of symbiotic and saprotrophic Russulales species, aiming to identify genes involved in their ecology and host specificity. The size of Lactarius genomes is significantly larger than other Russulales species, owing to a massive accumulation of transposable elements and duplication of dispensable genes. As expected, their repertoire of genes coding for plant cell wall-degrading enzymes is restricted, but they retained a substantial set of genes involved in microbial cell wall degradation. Notably, Lactarius species showed a striking expansion of genes encoding proteases, such as secreted ectomycorrhiza-induced sedolisins. A high copy number of genes coding for small secreted LysM proteins and Lactarius-specific lectins were detected, which may be linked to host specificity. This study revealed a large diversity in the genome landscapes and gene repertoires within Russulaceae. The known host specificity of Lactarius symbionts may be related to mycorrhiza-induced species-specific genes, including secreted sedolisins.

Linking secondary metabolites to gene clusters through genome sequencing of six diverse Aspergillus species.

The fungal genus of Aspergillus is highly interesting, containing everything from industrial cell factories, model organisms, and human pathogens. In particular, this group has a prolific production of bioactive secondary metabolites (SMs). In this work, four diverse Aspergillus species (A. campestris, A. novofumigatus, A. ochraceoroseus, and A. steynii) have been whole-genome PacBio sequenced to provide genetic references in three Aspergillus sections. A. taichungensis and A. candidus also were sequenced for SM elucidation. Thirteen Aspergillus genomes were analyzed with comparative genomics to determine phylogeny and genetic diversity, showing that each presented genome contains 15-27% genes not found in other sequenced Aspergilli. In particular, A. novofumigatus was compared with the pathogenic species A. fumigatus This suggests that A. novofumigatus can produce most of the same allergens, virulence, and pathogenicity factors as A. fumigatus, suggesting that A. novofumigatus could be as pathogenic as A. fumigatus Furthermore, SMs were linked to gene clusters based on biological and chemical knowledge and analysis, genome sequences, and predictive algorithms. We thus identify putative SM clusters for aflatoxin, chlorflavonin, and ochrindol in A. ochraceoroseus, A. campestris, and A. steynii, respectively, and novofumigatonin, ent-cycloechinulin, and epi-aszonalenins in A. novofumigatus Our study delivers six fungal genomes, showing the large diversity found in the Aspergillus genus; highlights the potential for discovery of beneficial or harmful SMs; and supports reports of A. novofumigatus pathogenicity. It also shows how biological, biochemical, and genomic information can be combined to identify genes involved in the biosynthesis of specific SMs.

Phased diploid genome assembly with single-molecule real-time sequencing.

While genome assembly projects have been successful in many haploid and inbred species, the assembly of noninbred or rearranged heterozygous genomes remains a major challenge. To address this challenge, we introduce the open-source FALCON and FALCON-Unzip algorithms (https://github.com/PacificBiosciences/FALCON/) to assemble long-read sequencing data into highly accurate, contiguous, and correctly phased diploid genomes. We generate new reference sequences for heterozygous samples including an F1 hybrid of Arabidopsis thaliana, the widely cultivated Vitis vinifera cv. Cabernet Sauvignon, and the coral fungus Clavicorona pyxidata, samples that have challenged short-read assembly approaches. The FALCON-based assemblies are substantially more contiguous and complete than alternate short- or long-read approaches. The phased diploid assembly enabled the study of haplotype structure and heterozygosities between homologous chromosomes, including the identification of widespread heterozygous structural variation within coding sequences.

Phylogenomics of Endogonaceae and evolution of mycorrhizas within Mucoromycota.

Endogonales (Mucoromycotina), composed of Endogonaceae and Densosporaceae, is the only known non-Dikarya order with ectomycorrhizal members. They also form mycorrhizal-like association with some nonspermatophyte plants. It has been recently proposed that Endogonales were among the earliest mycorrhizal partners with land plants. It remains unknown whether Endogonales possess genomes with mycorrhizal-lifestyle signatures and whether Endogonales originated around the same time as land plants did. We sampled sporocarp tissue from four Endogonaceae collections and performed shotgun genome sequencing. After binning the metagenome data, we assembled and annotated the Endogonaceae genomes. We performed comparative analysis on plant-cell-wall-degrading enzymes (PCWDEs) and small secreted proteins (SSPs). We inferred phylogenetic placement of Endogonaceae and estimated the ages of Endogonaceae and Endogonales with expanded taxon sampling. Endogonaceae have large genomes with high repeat content, low diversity of PCWDEs, but without elevated SSP/secretome ratios. Dating analysis estimated that Endogonaceae originated in the Permian-Triassic boundary and Endogonales originated in the mid-late Silurian. Mycoplasma-related endobacterium sequences were identified in three Endogonaceae genomes. Endogonaceae genomes possess typical signatures of mycorrhizal lifestyle. The early origin of Endogonales suggests that the mycorrhizal association between Endogonales and plants might have played an important role during the colonization of land by plants.

Draft Genome of Burkholderia cenocepacia TAtl-371, a Strain from the Burkholderia cepacia Complex Retains Antagonism in Different Carbon and Nitrogen Sources.

Burkholderia cenocepacia TAtl-371 was isolated from the rhizosphere of a tomato plant growing in Atlatlahucan, Morelos, Mexico. This strain exhibited a broad antimicrobial spectrum against bacteria, yeast, and fungi. Here, we report and describe the improved, high-quality permanent draft genome of B. cenocepacia TAtl-371, which was sequenced using a combination of PacBio RS and PacBio RS II sequencing methods. The 7,496,106 bp genome of the TAtl-371 strain is arranged in three scaffolds, contains 6722 protein-coding genes, and 99 RNA only-encoding genes. Genome analysis revealed genes related to biosynthesis of antimicrobials such as non-ribosomal peptides, siderophores, chitinases, and bacteriocins. Moreover, analysis of bacterial growth on different carbon and nitrogen sources shows that the strain retains its antimicrobial ability.

Comparative genomics of biotechnologically important yeasts.

Ascomycete yeasts are metabolically diverse, with great potential for biotechnology. Here, we report the comparative genome analysis of 29 taxonomically and biotechnologically important yeasts, including 16 newly sequenced. We identify a genetic code change, CUG-Ala, in Pachysolen tannophilus in the clade sister to the known CUG-Ser clade. Our well-resolved yeast phylogeny shows that some traits, such as methylotrophy, are restricted to single clades, whereas others, such as l-rhamnose utilization, have patchy phylogenetic distributions. Gene clusters, with variable organization and distribution, encode many pathways of interest. Genomics can predict some biochemical traits precisely, but the genomic basis of others, such as xylose utilization, remains unresolved. Our data also provide insight into early evolution of ascomycetes. We document the loss of H3K9me2/3 heterochromatin, the origin of ascomycete mating-type switching, and panascomycete synteny at the MAT locus. These data and analyses will facilitate the engineering of efficient biosynthetic and degradative pathways and gateways for genomic manipulation.

Genus-Wide Assessment of Lignocellulose Utilization in the Extremely Thermophilic Genus Caldicellulosiruptor by Genomic, Pangenomic, and Metagenomic Analyses.

Metagenomic data from Obsidian Pool (Yellowstone National Park, USA) and 13 genome sequences were used to reassess genus-wide biodiversity for the extremely thermophilic Caldicellulosiruptor The updated core genome contains 1,401 ortholog groups (average genome size for 13 species = 2,516 genes). The pangenome, which remains open with a revised total of 3,493 ortholog groups, encodes a variety of multidomain glycoside hydrolases (GHs). These include three cellulases with GH48 domains that are colocated in the glucan degradation locus (GDL) and are specific determinants for microcrystalline cellulose utilization. Three recently sequenced species, Caldicellulosiruptor sp. strain Rt8.B8 (renamed here Caldicellulosiruptor morganii), Thermoanaerobacter cellulolyticus strain NA10 (renamed here Caldicellulosiruptor naganoensis), and Caldicellulosiruptor sp. strain Wai35.B1 (renamed here Caldicellulosiruptor danielii), degraded Avicel and lignocellulose (switchgrass). C. morganii was more efficient than Caldicellulosiruptor bescii in this regard and differed from the other 12 species examined, both based on genome content and organization and in the specific domain features of conserved GHs. Metagenomic analysis of lignocellulose-enriched samples from Obsidian Pool revealed limited new information on genus biodiversity. Enrichments yielded genomic signatures closely related to that of Caldicellulosiruptor obsidiansis, but there was also evidence for other thermophilic fermentative anaerobes (Caldanaerobacter, Fervidobacterium, Caloramator, and Clostridium). One enrichment, containing 89.8% Caldicellulosiruptor and 9.7% Caloramator, had a capacity for switchgrass solubilization comparable to that of C. bescii These results refine the known biodiversity of Caldicellulosiruptor and indicate that microcrystalline cellulose degradation at temperatures above 70°C, based on current information, is limited to certain members of this genus that produce GH48 domain-containing enzymes.IMPORTANCE The genus Caldicellulosiruptor contains the most thermophilic bacteria capable of lignocellulose deconstruction, which are promising candidates for consolidated bioprocessing for the production of biofuels and bio-based chemicals. The focus here is on the extant capability of this genus for plant biomass degradation and the extent to which this can be inferred from the core and pangenomes, based on analysis of 13 species and metagenomic sequence information from environmental samples. Key to microcrystalline hydrolysis is the content of the glucan degradation locus (GDL), a set of genes encoding glycoside hydrolases (GHs), several of which have GH48 and family 3 carbohydrate binding module domains, that function as primary cellulases. Resolving the relationship between the GDL and lignocellulose degradation will inform efforts to identify more prolific members of the genus and to develop metabolic engineering strategies to improve this characteristic.

Comparative genomics and transcriptomics depict ericoid mycorrhizal fungi as versatile saprotrophs and plant mutualists.

Some soil fungi in the Leotiomycetes form ericoid mycorrhizal (ERM) symbioses with Ericaceae. In the harsh habitats in which they occur, ERM plant survival relies on nutrient mobilization from soil organic matter (SOM) by their fungal partners. The characterization of the fungal genetic machinery underpinning both the symbiotic lifestyle and SOM degradation is needed to understand ERM symbiosis functioning and evolution, and its impact on soil carbon (C) turnover. We sequenced the genomes of the ERM fungi Meliniomyces bicolor, M. variabilis, Oidiodendron maius and Rhizoscyphus ericae, and compared their gene repertoires with those of fungi with different lifestyles (ecto- and orchid mycorrhiza, endophytes, saprotrophs, pathogens). We also identified fungal transcripts induced in symbiosis. The ERM fungal gene contents for polysaccharide-degrading enzymes, lipases, proteases and enzymes involved in secondary metabolism are closer to those of saprotrophs and pathogens than to those of ectomycorrhizal symbionts. The fungal genes most highly upregulated in symbiosis are those coding for fungal and plant cell wall-degrading enzymes (CWDEs), lipases, proteases, transporters and mycorrhiza-induced small secreted proteins (MiSSPs). The ERM fungal gene repertoire reveals a capacity for a dual saprotrophic and biotrophic lifestyle. This may reflect an incomplete transition from saprotrophy to the mycorrhizal habit, or a versatile life strategy similar to fungal endophytes.

BIGMAC : breaking inaccurate genomes and merging assembled contigs for long read metagenomic assembly.

BACKGROUND: The problem of de-novo assembly for metagenomes using only long reads is gaining attention. We study whether post-processing metagenomic assemblies with the original input long reads can result in quality improvement. Previous approaches have focused on pre-processing reads and optimizing assemblers. BIGMAC takes an alternative perspective to focus on the post-processing step. RESULTS: Using both the assembled contigs and original long reads as input, BIGMAC first breaks the contigs at potentially mis-assembled locations and subsequently scaffolds contigs. Our experiments on metagenomes assembled from long reads show that BIGMAC can improve assembly quality by reducing the number of mis-assemblies while maintaining or increasing N50 and N75. Moreover, BIGMAC shows the largest N75 to number of mis-assemblies ratio on all tested datasets when compared to other post-processing tools. CONCLUSIONS: BIGMAC demonstrates the effectiveness of the post-processing approach in improving the quality of metagenomic assemblies.

Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data.

We present a hierarchical genome-assembly process (HGAP) for high-quality de novo microbial genome assemblies using only a single, long-insert shotgun DNA library in conjunction with Single Molecule, Real-Time (SMRT) DNA sequencing. Our method uses the longest reads as seeds to recruit all other reads for construction of highly accurate preassembled reads through a directed acyclic graph-based consensus procedure, which we follow with assembly using off-the-shelf long-read assemblers. In contrast to hybrid approaches, HGAP does not require highly accurate raw reads for error correction. We demonstrate efficient genome assembly for several microorganisms using as few as three SMRT Cell zero-mode waveguide arrays of sequencing and for BACs using just one SMRT Cell. Long repeat regions can be successfully resolved with this workflow. We also describe a consensus algorithm that incorporates SMRT sequencing primary quality values to produce de novo genome sequence exceeding 99.999% accuracy.

Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community.

BACKGROUND: The rapid development of sequencing technologies has provided access to environments that were either once thought inhospitable to life altogether or that contain too few cells to be analyzed using genomics approaches. While 16S rRNA gene microbial community sequencing has revolutionized our understanding of community composition and diversity over time and space, it only provides a crude estimate of microbial functional and metabolic potential. Alternatively, shotgun metagenomics allows comprehensive sampling of all genetic material in an environment, without any underlying primer biases. Until recently, one of the major bottlenecks of shotgun metagenomics has been the requirement for large initial DNA template quantities during library preparation. RESULTS: Here, we investigate the effects of varying template concentrations across three low biomass library preparation protocols on their ability to accurately reconstruct a mock microbial community of known composition. We analyze the effects of input DNA quantity and library preparation method on library insert size, GC content, community composition, assembly quality and metagenomic binning. We found that library preparation method and the amount of starting material had significant impacts on the mock community metagenomes. In particular, GC content shifted towards more GC rich sequences at the lower input quantities regardless of library prep method, the number of low quality reads that could not be mapped to the reference genomes increased with decreasing input quantities, and the different library preparation methods had an impact on overall metagenomic community composition. CONCLUSIONS: This benchmark study provides recommendations for library creation of representative and minimally biased metagenome shotgun sequencing, enabling insights into functional attributes of low biomass ecosystem microbial communities.

Genome sequencing provides insight into the reproductive biology, nutritional mode and ploidy of the fern pathogen Mixia osmundae.

Mixia osmundae (Basidiomycota, Pucciniomycotina) represents a monotypic class containing an unusual fern pathogen with incompletely understood biology. We sequenced and analyzed the genome of M. osmundae, focusing on genes that may provide some insight into its mode of pathogenicity and reproductive biology. Mixia osmundae has the smallest plant pathogenic basidiomycete genome sequenced to date, at 13.6 Mb, with very few repeats, high gene density, and relatively few significant gene family gains. The genome shows that the yeast state of M. osmundae is haploid and the lack of segregation of mating genes suggests that the spores produced on Osmunda spp. fronds are probably asexual. However, our finding of a complete complement of mating and meiosis genes suggests the capacity to undergo sexual reproduction. Analyses of carbohydrate active enzymes suggest that this fungus is a biotroph with the ability to break down several plant cell wall components. Analyses of publicly available sequence data show that other Mixia members may exist on other plant hosts and with a broader distribution than previously known.

Comparative genomics of xylose-fermenting fungi for enhanced biofuel production.

Cellulosic biomass is an abundant and underused substrate for biofuel production. The inability of many microbes to metabolize the pentose sugars abundant within hemicellulose creates specific challenges for microbial biofuel production from cellulosic material. Although engineered strains of Saccharomyces cerevisiae can use the pentose xylose, the fermentative capacity pales in comparison with glucose, limiting the economic feasibility of industrial fermentations. To better understand xylose utilization for subsequent microbial engineering, we sequenced the genomes of two xylose-fermenting, beetle-associated fungi, Spathaspora passalidarum and Candida tenuis. To identify genes involved in xylose metabolism, we applied a comparative genomic approach across 14 Ascomycete genomes, mapping phenotypes and genotypes onto the fungal phylogeny, and measured genomic expression across five Hemiascomycete species with different xylose-consumption phenotypes. This approach implicated many genes and processes involved in xylose assimilation. Several of these genes significantly improved xylose utilization when engineered into S. cerevisiae, demonstrating the power of comparative methods in rapidly identifying genes for biomass conversion while reflecting on fungal ecology.

Assessment of Autonomic Nervous System Activity Using Spectral Analysis of Heart Rate Variability After Continuous Positive Airway Pressure (CPAP) Therapy in Patients With Sleep Apnea.

Heart rate variability (HRV) measurements have emerged as a valuable tool for understanding the functioning of the autonomic nervous system (ANS) and assessing the health outcomes of obstructive sleep apnea (OSA) in patients. Sleep and the ANS exert a mutual influence on each other. Sleep promotes relaxation and recovery of the ANS. Conversely, ANS activity plays a role in regulating the onset and maintenance of sleep. The impact of continuous positive airway pressure (CPAP) therapy on patient recovery levels was investigated by assessing the restoration of ANS activity using HRV indicators. The study included patients with OSA who had been on CPAP for at least eight weeks. The patients were divided into two groups, namely the experimental group (CPAP-compliant) and the control group (CPAP-non-compliant). The study included a total of 38 patients, with 20 in the CPAP-compliant group and 18 in the CPAP-non-compliant group. The HRV analysis included time- and frequency-domain measures. Data was collected in various resting conditions, including lying down, standing, regular breathing, and under physiological stress induced by deep breathing and the Valsalva maneuver. After CPAP treatment, there was an increase in the average values for SDNN for deep breathing and Valsalva maneuvers. The mean changes in SDNN for CPAP-non-compliant versus CPAP-compliant groups for normal breathing increased from 32.50±5.33 to 42.40±8.03, while the values for Valsalva increased from 20.16±2.47 to 25.45±3.03. Despite the observed variations in SDNN, there was no significant change in the average change in heart rate (∆ HR), except during the Valsalva maneuver. Post-CPAP values for the Valsalva ratio were significantly decreased in deep breathing. The E:I ratio for the CPAP-compliant group during normal breathing was 1.08±.16 compared to 1.55±.09; t (36) =-11.15, p <0.001 in the CPAP-non-compliant group. During deep breathing, the ratio was 1.36±.15 versus 1.59±.24; t (36) =-3.578, p <0.001. The high frequency (HF)nu mean values for deep breathing were 34.06±5.546 compared to 35.00±6.358; t (36) = -.485, p=.630. For the Valsalva maneuver, the values were 29.94±4.721 versus 26.95±6.621; t (36) =1.589, p=.060. The HF/low frequency (LF) ratio was found to be significant only in supine, standing, and normal breathing. The utilization of CPAP therapy was found to be effective in achieving and sustaining autonomic balance during tasks like standing and engaging in regular breathing patterns. During activities that involve intense physical effort, like the Valsalva maneuver, the HRV metrics did not indicate any significant balance between sympathetic and parasympathetic activity. However, using CPAP therapy for a prolonged period can be beneficial in consistently improving the sympathovagal balance in these patients.

Microbial Metagenomes Across a Complete Phytoplankton Bloom Cycle: High-Resolution Sampling Every 4 Hours Over 22 Days.

In May and June of 2021, marine microbial samples were collected for DNA sequencing in East Sound, WA, USA every 4 hours for 22 days. This high temporal resolution sampling effort captured the last 3 days of a Rhizosolenia sp. bloom, the initiation and complete bloom cycle of Chaetoceros socialis (8 days), and the following bacterial bloom (2 days). Metagenomes were completed on the time series, and the dataset includes 128 size-fractionated microbial samples (0.22-1.2 µm), providing gene abundances for the dominant members of bacteria, archaea, and viruses. This dataset also has time-matched nutrient analyses, flow cytometry data, and physical parameters of the environment at a single point of sampling within a coastal ecosystem that experiences regular bloom events, facilitating a range of modeling efforts that can be leveraged to understand microbial community structure and their influences on the growth, maintenance, and senescence of phytoplankton blooms.

From soil to sequence: filling the critical gap in genome-resolved metagenomics is essential to the future of soil microbial ecology.

Soil microbiomes are heterogeneous, complex microbial communities. Metagenomic analysis is generating vast amounts of data, creating immense challenges in sequence assembly and analysis. Although advances in technology have resulted in the ability to easily collect large amounts of sequence data, soil samples containing thousands of unique taxa are often poorly characterized. These challenges reduce the usefulness of genome-resolved metagenomic (GRM) analysis seen in other fields of microbiology, such as the creation of high quality metagenomic assembled genomes and the adoption of genome scale modeling approaches. The absence of these resources restricts the scale of future research, limiting hypothesis generation and the predictive modeling of microbial communities. Creating publicly available databases of soil MAGs, similar to databases produced for other microbiomes, has the potential to transform scientific insights about soil microbiomes without requiring the computational resources and domain expertise for assembly and binning.