Environmental Microbiome

Metabarcoding is a powerful tool for biodiversity comparisons, where standard-size DNA barcodes (>500 bases) offer better taxonomic resolution than shorter ones. Still, the choice of sequencing platforms and bioinformatics pipelines may strongly affect inferred diversity due to various technical biases. We assessed the relative performance of Illumina MiSeq i100 (2x500 paired-end), PacBio Revio and Oxford Nanopore MinION sequencing and bioinformatics pipelines, using full-length ITS amplicon sequencing datasets from a 103-species mock community and 45 composite soil samples. Despite numerous low-quality reads, PacBio yielded the lowest overall error rate and highest number of taxa. Illumina revealed the highest proportion of chimeric and index-switched reads, along with a strong bias towards shorter amplicons. MinION data analysed using PRONAME and Minovar - a bioinformatics pipeline presented here - had the largest proportion of low-quality data, and rare taxa were lost during data filtering and read polishing steps. Although Minovar enabled amplicon sequence variant (ASV) level precision for common taxa, we recommend clustering ASVs into OTUs. For PacBio, standard filtering approaches outperformed the ASV approach because they retained rare taxa. For Illumina, a stringent ASV approach or removal of rare OTUs would limit artefacts. Across all platforms, excess PCR cycles promoted chimeric and low-quality reads and lost quantitativity in biodiversity assessments. With moderate differences in effect sizes, all analytical approaches supported the conclusion that sampling design determines how we see soil biodiversity responses to land use. For biodiversity surveys based on the full-length ITS metabarcoding, we recommend using PacBio sequencing with standard, non-ASV pipelines.

Aridification and climate stress threaten global plant productivity, but the survival strategies of desert plants remain only partly understood. In this study, we examined how the microbiome of Citrullus colocynthis, a hardy desert cucurbit valued for its ecological and medicinal benefits, may influence the plants ability to withstand harsh conditions. Using 16S rRNA amplicon sequencing, shotgun metagenomics, and culture-based methods, we analyzed microbiome changes across two regions of the UAE during the rainy and dry seasons. Leaf and root bacterial communities showed clear seasonal shifts, with greater richness in winter and higher evenness in summer, while soil microbiomes remained stable. Dominant bacterial groups, Actinomycetota and Pseudomonadota, varied seasonally, indicating trade-offs between stress tolerance and metabolic flexibility. Fungal communities (mainly Ascomycota and Basidiomycota) were stable at the phylum level but reorganized by order between seasons; archaeal populations showed little change. Among 24 cultured bacterial isolates, including three potential new species, we identified multiple stress tolerance and plant growth-promoting traits. Genomic data revealed biosynthetic clusters for antimicrobial and stress-protective functions, as well as adaptation genes in Pseudomonas orientalis. These results demonstrate that the dynamic, functionally diverse microbiome of C. colocynthis enhances its resilience to desert stress, offering potential for arid-land agriculture.

Microbes play a vital role in plant development, health, and resilience, yet relatively little is known about the specific metabolic mechanisms driving interactions in these host-associated communities. Systems biology models enable a computational approach to understanding metabolic interactions, which can be difficult to pinpoint experimentally; however, these methods cannot yet accommodate the large number of species in natural communities. Synthetic communities (SynComs) provide a more tractable alternative to explore targeted interactions. Here, we investigated metabolite exchange in a seven-member maize root-associated SynCom, specifically accounting for plant host context by designing a customized exudate medium. We constructed metabolic models for each bacterial species and curated them with in vitro phenotyping data to reflect experimentally based carbon uptake potential. Flux balance analysis of individual species demonstrated that integrating phenotype data and changing medium type had substantial impacts on predicted growth rates, which in turn shaped potential interspecies interactions. In silico community growth optimization of the seven-member community model showed that the exudate medium supported a more diverse community composition compared to minimal medium, with predictions of community member abundance closely aligned to literature-derived experimental results. Predicted metabolite exchange in the root exudate environment showed Enterobacter ludwigii as a community hub, and cross-feeding of indole suggested a potential effect of bacterial community interactions on the plant host. Our in silico findings indicate the host plays an important role in structuring microbial interactions and cross-feeding at the metabolic level, underscoring the importance of considering environmental context from both theoretical and experimental perspectives. IMPORTANCETrue understanding of a system is marked by the ability to predict its behavior. The complexity of natural host-microbe systems represents a frontier of knowledge that scientists are working to understand, and elucidating principles of interactions within multi-partite microbial communities remains a challenge in microbial ecology. Synthetic communities provide a tractable starting point for investigating interaction mechanisms, and computational approaches complement laboratory experiments by systematically evaluating multiple possibilities for metabolic pathway processing, thereby allowing us to comprehensively study the interconnected metabolic networks of host-associated microbiota. The model we developed for the seven-member maize root-associated bacterial community presents a step toward predicting plant-microbe behavior, providing hypotheses for future experimental testing and serving as a template for expanding model complexity to more members and other systems.

BackgroundAdult vestimentiferan tubeworms inhabiting hydrothermal vents and cold seeps lack a mouth and anus and rely entirely on organic matter produced by sulfur -oxidizing autotrophic bacterial symbionts in their trophosomes. These symbionts, which predominantly belong to the genus Proteobacteria, are acquired horizontally from the environment. However, the effects of rearing conditions that differ from natural habitats on the microbiome composition or abundance of these bacteria remain unclear. MethodsWe conducted a metagenomic analysis of Lamellibrachia satsuma reared in an aquarium under sulfide-supplemented and sulfide-free conditions. ResultsImmediately after collection, the microbiome was dominated by known symbionts within {gamma}-Proteobacteria, exhibiting low species diversity. After 6 months of rearing, the abundance of these symbionts significantly decreased under both conditions, whereas overall bacterial diversity increased. In particular, -Proteobacteria became more abundant under sulfide-supplemented conditions, while {delta}-Proteobacteria predominated in the absence of sulfide. Despite these changes, symbionts were not entirely lost, and the hosts survived for 6 months, likely due to their low metabolic rate. These findings suggest that the microbiome of L. satsuma can respond flexibly to changes in the rearing environment. They also indicate that the hosts metabolism can be maintained even with a smaller quantity of symbiotic bacteria.

Understanding how host-microbiome interactions influence tree disease is critical for understanding forest resilience. Here, we present foliar microbiome ITS2 metabarcoding transcriptomic datasets from Pinus sylvestris to investigate susceptibility to Dothistroma needle blight (DNB), a globally important foliar disease caused by Dothistroma septosporum. We hypothesised that host genotype shapes foliar microbial communities and their interactions, thereby influencing disease outcomes. Samples were collected from a progeny-provenance field trial in the south of Scotland representing a broad spectrum of disease susceptibilities. The dataset comprises ITS2 metabarcoding samples from 200 genotypes across three timepoints and RNAseq samples from 48 genotypes across two timepoints. Sampling captured key stages of pathogen exposure and disease progression. Both standardised and bespoke protocols were used for nucleotide extraction, sequencing, and quality control, including multiple negative and positive controls. These datasets, available in the European Nucleotide Archive (project accession PRJEB88228), enable analysis of temporal dynamics in foliar fungal communities, host-microbiome transcriptional responses, and genotype-dependent variation in disease susceptibility.

Scalable soil microbiome monitoring requires sampling methods that are reproducible across operators, field sites, and logistical constraints. Here, we evaluated three key methodological choices that commonly limit comparability in agricultural rhizosphere studies: how the rhizosphere sampling unit is operationally defined, sample pooling strategies, and preservation methods. We introduce the RhizoCore, a standardized root-zone soil core defined by core diameter, depth, position relative to the plant, and subsample volume, as a practical proxy for traditional rhizosphere sampling. The RhizoCore method captured more than 92% of the sequencing depth found in traditional rhizosphere samples, with differences limited predominantly to low-abundance taxa. Preservation methods significantly affected bacterial communities, while sample pooling showed greater impact on fungal diversity and substantially reduced within-group variability across all treatments. Despite these effects, differential abundance analysis revealed minimal compositional changes, with only a small fraction of microbial taxa significantly affected by either pooling or preservation method. Our findings demonstrate that the RhizoCore method provides a reproducible, and scalable approach for rhizosphere sampling that balances scientific rigor with practical field implementation, offering a framework for large-scale soil microbiome monitoring programs and for improving comparability among agricultural microbiome studies across diverse environmental conditions.

Microbial communities are central to the biogeochemical cycling of nutrients, critically shaping ecosystem functioning and influencing climate change mitigation. Mangrove ecosystems are among the most important global carbon sinks that enable large amounts of carbon to be sequestered and stored. However, gaps persist in understanding the fundamental aspects of microbial-driven carbon cycling in these environments. This research explores the microbial taxonomic and functional diversity related to carbon cycling in selected tropical mangrove sediments across various locations and depths. Sequencing data analyses based on the 16S rRNA gene revealed distinct microbial community composition but conserved predicted functions across the different mangrove locations. Depth was a strong influence on the functional composition, with carbon-related pathways and metabolic strategies differing between top and bottom sediments. Putative functional gene abundance analyses revealed that carbon fixation processes were among the top carbon-related pathways, suggesting the key role of mangrove microbial communities in sustaining long-term carbon storage. Within these communities, Desulfobacterota appeared as a primary contributor to carbon fixation, while Chloroflexota played a significant role in carbon metabolism and methane cycling. Co-occurrence network analyses also revealed that these microbial groups were among the keystone taxa in mangrove sediments. Our study adds on to the body of knowledge on the mangrove microbiome and their carbon metabolic processes, which helps to improve strategies for managing and leveraging these vital carbon sinks.

Global change drivers are reshaping agroecosystems and their sustained functions worldwide. While soil microorganisms underpin the resilience of these systems, the individual and interactive effects of multiple anthropogenic stressors on microbial community structure and function using large-scale field experiments remain poorly understood. Here, we utilize a full-factorial field experiment in a subtropical agroecosystem to investigate how land-use intensity, cattle grazing intensity, and altered precipitation regimes interact to shape soil microbiomes. Combining microbiome sequencing with network analyses and functional bioinformatics, we evaluated effects of these drivers on prokaryotic and fungal diversity, composition, predicted functional profiles, and community structure. Land-use intensity emerged as the primary driver of microbial responses, explaining 25% and 13% of the total variation in community composition for prokaryotes and fungi, respectively. Compared to intensively managed pastures, semi-natural pastures had significantly different community composition for prokaryotes and fungi and exhibited 22% higher fungal diversity. Semi-natural pastures were enriched with decomposer-associated taxa and metabolic pathways related to energy and lipid metabolism indicating enhanced microbial activity. Surprisingly, intensively managed pastures showed higher network modularity but lower network richness, suggesting a trade-off between community compartmentalization and complexity under intensive land management. Grazing and precipitation manipulations induced core microbiome changes within land-use intensities but had no impact on overall community structure and no significant interactions with land-use. Together, these findings suggest that long-term land-use legacies exert a persistent influence on soil microbial community structure, function, and organization, shaping the context within which other global change drivers operate in subtropical agroecosystems.

Phyllosphere microbiomes are increasingly recognized as key regulators of plant health and stress responses, although they are also known to change considerably over both space and time. In the phyllosphere, members of the genus Methylobacterium are often abundant and ecologically important as plant growth promoting bacteria. However, knowledge about the temporal abundances and community dynamics of Methylobacterium in agricultural systems remains limited. To address this gap, we characterized seasonal shifts in Methylobacterium-specific and total phyllosphere bacterial loads and community structure on two common summer crops and one overwintering cover crop. Leaf samples of Zea mays (corn), Glycine max (soybean), and Thlaspi arvense L. (pennycress) plants were collected over one year in Minnesota, USA and analyzed with host-associated microbial PCR (hamPCR). Microbial loads and community composition varied strongly among hosts and across growing seasons. Corn supported the highest Methylobacterium and total bacterial loads, increasing towards senescence, while pennycress exhibited the lowest loads and the most distinct communities. While there were strong host-specific patterns, a group of most abundant genera were shared across all crops (Methylobacterium, Sphingomonas, Pseudomonas, and Massilia) and the most abundant Methylobacterium amplicon sequence variants were present on all three hosts. Our findings highlight how microbial loads and community composition change during phyllosphere assembly across diverse summer and overwintering crops, with a small core of versatile taxa dominating multiple agricultural hosts. Understanding these host and season-linked patterns provides a foundation of harnessing Methylobacterium strains to enhance crop productivity and resilience.

O_LIA productivity-driven higher nutrient demand of trees in diverse mixtures is frequently reported. Yet, it remains unclear how tree diversity influences microorganisms-plants interactions, in which microbes facilitate tree nutrient acquisition in exchange for carbon (C) to meet the resource demand of both. C_LIO_LIUsing a long-term tree diversity experiment in the subtropics, we assessed microbial investment in C-, nitrogen (N)-, and phosphorus (P)-acquiring enzymes in litter and mineral soil, testing the effects of tree species richness and mycorrhizal type (arbuscular (AM)- vs. ectomycorrhizal (EcM)-associated tree species). C_LIO_LIWith increasing tree species richness, microbial investment in C acquisition decreased, while investment in N and/or P acquisition increased in litter and in mineral soil. In mineral soil of AM-associated tree mixtures, ecoenzymatic stoichiometry revealed a shift from microbial investment in C toward P acquisition as tree species richness increased. C_LIO_LIOur findings suggest that tree diversity strengthens microbe-tree interactions in terms of C-for-nutrient exchange. This highlights the key role of soil microorganisms, particularly in AM symbiosis, shaping tree diversity-biogeochemical feedbacks. C_LI

Plant growth promoting microbes enhance developmental progression of the host by influencing its nutrient availability or by deploying secondary metabolites responsible for manipulating the hormonal crosstalk. Microbacterium bengalense sp. nov. GB16_1_BI (Accession number: SRX9280401), a newly identified ammonium releasing Actinomycetota, could enhance plant growth by manipulating rhizosphere bacteria. Amplicon sequencing of the 16S rRNA V3-V4 region from the rhizosphere of the black rice (Chakhao Poireiton) showed that GB16_1_BI could inhibit most bacteria. However, GB16_1_BI inoculation encouraged the growth of rare bacteria specific to waterlogged rice rhizosphere. Analysis of the OTUs using PICRUSt2 (Phylogenetic investigation of communities by reconstruction of unobserved states) showed increased abundance in the marker genes for nitrogen cycling (nifH, nrfA and nrt) but not for nifD or nifK which was also reflected in the ANOSIM analysis in the OTUs of the N-fixing bacteria. Marker genes for methane metabolism (comA, comB, cofG and cofH) were also more abundant in the inoculated plants than the control; however, ANOSIM studies did not support this observation in the OTUs of methane cycling bacteria. Both Methylosinus and Methylocystis, the two most abundant methanotrophic OTUs, are also known to be nitrogen fixers. Hence, GB16_1_BI could influence plant growth predominantly by manipulating nitrogen cycling microbes. The genome sequence as well as untargeted metabolome analyses of GB16_1_BI showed abundance of secondary metabolites with probable antimicrobial activity. GB16_1_BI could utilize varied carbohydrates and amino acid as energy source and form persister-like cells may help it to survive in the soil in absence of the host plant.

Antibiotic use in agricultural systems can unintentionally disrupt beneficial rhizosphere microorganisms, yet the consequences of this dysbiosis for plant fitness remain insufficiently understood. Building on previous findings that application of streptomycin to the roots decreases cyanobacteria and increases tomato plant susceptibility to foliar Xanthomonas infection, this study aimed to determine whether this relationship reflects causation or correlation. We evaluated whether targeted inoculation with the filamentous nitrogen-fixing cyanobacterium Cylindrospermum sp. (CI) or a complex rhizosphere microbiome transplant (RMT) could mitigate antibiotic-induced dysbiosis. As expected, streptomycin treatment significantly increased bacterial spot disease severity and reduced microbial richness in the rhizosphere, marked by a pronounced decline in cyanobacterial and Cylindrospermum operational taxonomic units. Co-occurrence network analysis revealed that this dysbiotic state was defined by reduced community connectivity and increased negative associations, indicating a breakdown in cooperative microbial relationships. Notably, both CI and RMT reduced plant disease severity, though they caused distinct rhizosphere community reassembly outcomes. While RMT relied on microbial functional redundancy, the targeted CI approach achieved more robust colonization and effectively "patched" the functional gap left by dysbiosis. Microbiome restoration directly influenced host physiology, significantly reducing the overactivation of ethylene-mediated defense genes, such as ERF1, and partially reinstating auxin-responsive signaling pathways (IAA21) that were disrupted under dysbiosis. These findings suggest that targeted microbial inoculation could reverse dysbiosis and enhance plant resilience under pathogen pressure as effectively as complex microbial transplants. This work highlights a shift in microbiome management: from the complex rebuilding of communities to the strategic repair of specific functional gaps.

The slightly-alkaline (pH [~]8.5), boiling ([~]90{degrees}C) vent-water of a Trans-Himalayan geothermal spring, moderately-rich in dissolved solids ([~]1500 ppm), was explored six times over a year. 11 archaeal and 46 bacterial species were detected consistently, while nine bacteria occurred intermittently, in the vent-epicenter featuring a largely-stable physicochemical milieu. All 11 archaea were detected as metagenome-assembled genomes ascribable to Thermoproteota. Of the total 55 bacteria detected, 32 were retrieved as MAGs, 20 as isolates, and three in both forms. Four bacteria could not be classified below the domain-level; three and four belonged to hyperthermophilic (Aquificia) and thermophilic (Thermaceae and Thermoflexaceae) taxa respectively; 27 belonged to taxa having some moderately-thermophilic members; 17 belonged to mesophilic taxa. According to metagenomics, an Aquificia, followed by two Thermoprotei and one Thermoproteales, dominated the microbiome overwhelmingly. Metatranscriptomically, however, the Thermoproteales was most active. Metatranscriptomic signatures envisaged the in situ metabolic status of the 66 species discovered as follows. Among the 18 putative hyperthermophiles and thermophiles identified, 17 rendered wide-ranging activities including growth; one Thermoproteota species had considerable activities sans growth. One new-phylum-level bacterium rendered wide-ranging activities including growth, while three such entities had considerable/minimal activities sans growth. Among the 27 potential moderate-thermophiles discovered, two Armatimonadota and one Thermosynechococcus species rendered wide-ranging activities including growth, 20 had considerable/minimal activities sans growth, whereas four had zero activities. Among the 17 mesophiles identified, 16 rendered considerable/minimal activities sans growth, whereas one had zero activity. Molecular drivers were envisaged from the metatranscriptomic data to explain the trends of inequitable population ecology.

The 16S rRNA gene is the most widely used genetic marker for microbial community profiling, but its limited sequence divergence often prevents species-level identification. The RNA polymerase {beta}-subunit gene (rpoB) offers higher sequence variability, single-copy occurrence, and stronger phylogenetic consistency, yet its adoption in metataxonomic studies has been constrained by the lack of universal primer sets. Here, we present a novel universal primer pair that amplifies an [~]1,800 bp rpoB region (rpoB_MV) compatible with long-read sequencing platforms. In silico evaluation across 17683 bacterial reference genomes demonstrated high universality, with over 86% of genomes predicted to amplify. Compared with full-length and partial 16S rRNA gene markers, the rpoB_MV amplicon exhibited significantly greater inter-species sequence divergence and improved phylogenetic concordance with core-genome trees. Sequencing of two complementary mock communities confirmed superior species-level identification accuracy, with misclassification rates below 0.01% and no reads assigned to unresolved species clusters. These results establish rpoB_MV as a robust alternative to 16S rRNA gene-based profiling for high-resolution metataxonomic applications. IMPORTANCEMicrobial community studies increasingly require species-level resolution because species within the same genus can differ substantially in pathogenicity, ecological function, and metabolic capacity. Current 16S rRNA gene-based methods frequently fail to distinguish closely related species, collapsing biologically distinct organisms into the same taxonomic assignment and obscuring community differences that matter for clinical diagnostics, food safety, and environmental monitoring. The rpoB_MV primer pair presented here overcomes this limitation by targeting a longer, more variable region of the rpoB gene, enabling accurate species-level identification across diverse bacterial phyla. Combined with advances in long-read sequencing, this approach provides researchers with a practical tool to resolve microbial communities at the species-level.

Northern peatlands store large carbon stocks but are sensitive to disturbance. Hydrology, vegetation, herbivory and snow conditions may affect the soil microorganisms driving methane (CH) and nitrous oxide (N2O) cycling. We investigated how reindeer exclusion and snow depth (increased and reduced relative to ambient) manipulations (ongoing for three seasons) influenced archaeal and bacterial communities in a boreal rich fen. Metagenomic (MG) and metatranscriptomic (MT) sequencing were combined with pore-water chemistry and CH flux measurements to link the microbiome to ecosystem processes. Microbial communities differed between outside and inside the exclosure. However, these patterns primarily reflected underlying hydrological variation. Slightly wetter inside plots showed higher expression of denitrification genes (norB, nosZ) and lower (nirS+nirK)/nosZ ratios, indicating greater potential for complete denitrification to N2 instead of N2O. Methane dynamics were mainly associated with vegetation: plots associated with Carex rostrata exhibited lower pmoA/mcrA ratios and elevated CH fluxes. Snow manipulations had subtle effects: reduced snow depth decreased the expression of taxa dependent on microbial interactions, while the effect to the investigated metabolic marker genes was small. Overall hydrology, leading to variations in redox conditions and nutrient availability, together with vegetation appeared as the primary drivers on microbial greenhouse gas processes in this peatland.

Beneficial interactions between plants and microorganisms strongly influence plant health and productivity, and root exudates play a central role in shaping these associations. This study analyzed the transcriptional responses of the bacterial endophytes Enterobacter asburiae RCA24 and Kosakonia sacchari RCA25 to root exudates from two commercial Italian rice accessions (Oryza sativa Baldo and Vialone Nano) and from an accession of the wild progenitor of tropical rice, Oryza rufipogon. Bacterial transcriptome analyses revealed that RCA24 responds differently to O. sativa varieties and that RCA25 was more stimulated by O. rufipogon. Changes in bacterial gene expression were mainly related to central metabolism, stress response, and signal transduction, highlighting a precise pattern of interaction. On the other hand, transcriptome analysis of inoculated rice revealed that RCA24 triggered broader transcriptional changes in plants than RCA25. Differentially expressed genes were related, especially in shoots, to defense responses, hormone-mediated signaling, and ribosome biogenesis, revealing that plants discriminate bacterial strains in a genotype-specific manner at the transcriptional level. Our findings suggest that traits beneficial to plant-soil microbiota interactions present in O. rufipogon and lost during domestication and diversification could be identified and reintroduced into modern rice varieties to improve sustainable field performance through beneficial microbial associations.

Brown rot wood-degrading fungi release carbon (C) from deadwood but leave behind a large fraction of C sequestered in lignin residues or as fungal metabolites. The strength of sequestration in these C residuals remains unclear, but proteobacteria-dominated bacterial communities have been implicated in metabolizing C from decay residues, possibly erasing the C sequestration potential assumed for brown rot. Here, we paired a model brown rot fungus (Rhodonia placenta) with a model Alphaproteobacterium (Rhodopseudomonas palustris) to track fungal release and bacterial utilization of C derived from decaying wood. We found that fungal decay products generated by R. placenta could be used by R. palustris for growth, and later decay stages contained more usable substrates than early stages. High performance liquid chromatography with mass spectrometry identified a range of aromatic and non-aromatic compounds in the fungal-decayed wood, but after 95 days of bacterial growth, R. palustris preferentially consumed non-aromatic acids over aromatic lignin monomers. Genes involved with aromatic compound degradation were unimportant for bacterial growth, and RNA sequencing revealed that aromatic compound degradation genes were repressed on decayed wood extract. Randomly barcoded transposon sequencing failed to identify a solitary catabolic pathway used by R. palustris, suggestive of substrate co-utilization, and surprisingly, showed that genes involved with copper toxicity were essential. Finally, we found that genes involved with biosynthesis of certain cofactors and amino acids were no longer essential on decayed wood extract, suggesting these nutrients were readily accessible. This study helps lay the foundation to understand potential bacterial-fungal interactions in decayed wood. Graphical abstractTo explore how brown rot fungi support and compete with bacterial partners in the wood decay environment, the model brown rot fungus Rhodonia placenta was used to degrade aspen wafers which were then infused into bacterial growth medium. By leveraging the range of molecular biology tools available for the model Alphaproteobacterium Rhodopseudomonas palustris, we discovered that R. palustris preferentially consumes short organic acids instead of aromatic lignin monomers which it would otherwise consume if provided in isolation. Additionally, R. palustris scavenged certain amino acids (AAs) and enzyme cofactors including methionine, biotin, and PLP from the decayed wood extract, highlighting these as key shared resources for bacterial-fungal partnerships. We found that R. placenta increased the concentration of certain metals (Cu and Al) inducing a metal stress response in R. palustris, indicating that metal toxicity could be an important mode of competition between fungi and bacteria in the wood decay environment. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/723453v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@16f31fcorg.highwire.dtl.DTLVardef@13a9b34org.highwire.dtl.DTLVardef@a37dcforg.highwire.dtl.DTLVardef@198bf1c_HPS_FORMAT_FIGEXP M_FIG C_FIG

Genes for CO2 fixation occur in soil microorganisms, but little is known about the pathways that are most common across ecosystem types, the organisms with these genes, where different CO2 fixation pathways are most prevalent, and the energy sources that support autotrophy across ecosystems.Here, we investigated microbial capacity for autotrophy in soils using 853 metagenomes and 201 metatranscriptomes from a wide range of terrestrial ecosystems (agricultural soils, wetlands, weathering rock). Autotrophy-associated RuBisCO (Form I and II) is widely encoded across all soils and occurs in bacteria from numerous lineages (38 phyla). RuBisCO Form IE is consistently more phylogenetically diverse in soils than in marine ecosystems, suggesting that it may have evolved to function in soil-like environments. A newly discovered deeply branching Form I RuBisCO, Form I, supports the hypothesis that Form I RuBisCO originated in anaerobic environments. Further, saturated soils harbor more, and more distinct, autotrophic microbes, many of which may use the Calvin-Benson-Bassham cycle or Wood-Ljungdahl pathway for CO2 fixation. Overall, the results indicate that autotrophy is a particularly important metabolism in deep, saturated soils and weathering rock.

Short-read amplicon sequencing is widely used for fungal surveys but can limit taxonomic resolution. Long-read sequencing enables recovery of the full internal transcribed spacer (ITS) region and may improve ecological and taxonomic inference. Here, we conducted a paired comparison of Illumina ITS2 and PacBio HiFi full-length ITS sequencing using identical DNA extracts from built-environmental air and surface samples (n = 68) collected across homes, a dormitory, and laboratories. Both datasets were taxonomically assigned using the same algorithm and reference database. We performed paired statistics, in-silico ITS2 trimming of long-read sequences, and cross-platform mapping at multiple identity thresholds. Full-length ITS provided higher taxonomic resolution, assigning a greater fraction of ASVs at the family (98% vs. 88%) and species (42% vs. 32%) ranks than ITS2 (paired Wilcoxon q = 0.002). Alpha-diversity comparisons showed similar Shannon diversity across pipelines, whereas richness metrics were consistently higher for full-length ITS. Beta-diversity analyses indicated broadly comparable community-level patterns, although full-length ITS revealed stronger sample-type- and location-associated structure (PERMANOVA R{superscript 2} [≥] 0.06, p = 0.0001). In-silico ITS2 trimming reduced these differences, indicating that amplicon length is a major contributor to enhanced taxonomic resolution and ecological inference. Cross-platform mapping further showed extensive one-to-many relationships between ITS2 and full-length ITS ASVs, consistent with increased sequence resolution in long-read data. Together, these results show that ITS2 sequencing provides robust community-level profiling, while full-length ITS enables improved richness estimates and finer ecological and taxonomic resolution. This paired, bias-aware framework provides a practical template for selecting fungal amplicon sequencing strategies in built-environment mycobiome studies. ImportanceFungal communities in built environments influence indoor air quality and human exposure, yet their characterization depends strongly on sequencing strategy. This study provides a controlled, paired comparison of short-read ITS2 and long-read full-length ITS sequencing, showing that differences in amplicon length substantially contribute to variation in taxonomic resolution and ecological inference. While both approaches yield comparable community-level patterns, full-length ITS improves richness estimates, species-level assignment, and environmental discrimination by resolving sequence variation collapsed in ITS2 surveys. By integrating paired diversity analyses, in-silico ITS2 trimming, and cross-platform ASV mapping, this work offers a bias-aware framework for evaluating fungal amplicon pipelines. Importantly, improved species-level resolution enables functional interpretation of indoor fungi, for example the identification of taxa associated with pathogenic traits, allergen production, or toxin synthesis, supporting the development of more informative exposure metrics and targeted assays relevant to human health in built environments.

Interactions between amoebae and bacteria are increasingly viewed as key drivers of zoonotic pathogen emergence in rodent-dwelling burrows, yet the environmental factors shaping these interactions remain poorly understood. Here, we analyzed soil characteristics and used absolute quantitative high-throughput sequencing to assess microbial communities in active burrow, inactive burrow, and off-burrow soils across four rodent species (marmot, squirrel, gerbil, and vole) in the Hulunbuir grassland of Inner Mongolia, China. This study demonstrates that rodent activity creates chemically distinct soil microhabitats, with nitrate (NO --N) enrichment in active burrow soils consistently observed across rodent species. Elevated soil NO3--N was associated with reduced microbial phylogenetic diversity and reorganization of amoeba-co-occurring bacterial assemblages. Both absolute abundance-based correlations and functional prediction of co-occurring bacteria indicated that amoebae were primarily associated with nitrogen-cycling bacteria in off-burrow soils. In burrow soils, amoebae increasingly interacted with bacterial taxa associated with pathogenicity while retaining ties to nitrogen-cycling taxa. Structural equation modeling and mediation analysis revealed that NO3--N enrichment indirectly linked to increased infectious disease-related functional potential by amoeba-associated bacterial restructuring and coordinated shifts in nitrogen cycling, independent of changes in bacterial abundance. Together, our findings highlight the importance of rodent-driven soil heterogeneity in shaping amoeba-bacteria interactions and suggest that rodent-mediated NO --N enrichment may promote the emergence and persistence of potentially pathogenic bacteria, with broader implications for soil ecosystem functioning and disease-related processes in terrestrial ecosystems.