ISME Communications

Although several large-scale environmental microbial projects have been initiated in the past two decades, understanding of the role of complex microbiotas is still constrained by problems of detecting and identifying unknown microorganisms1-6.Currently, hypervariable regions of rRNA genes as well as internal transcribed spacer regions are broadly used to identify bacteria and fungi within complex communities7,8, but taxonomic and phylogenetic resolution is hampered by insufficient sequencing length9-11. Direct sequencing of full length rRNA genes is currently limited by read length using second generation sequencing or sacrificed quality and throughput by using single molecule sequencing. We developed a novel method to sequence and assemble nearly full length rRNA genes using second generation sequencing.Benchmarking was performed on mock bacterial and fungal communities as well as two forest soil samples. The majority of rRNA gene sequences of all species in the mock community samples were successfully recovered with identities above 99.5% compared to the reference sequences. For soil samples we obtained exquisite coverage with identification of a large number of putative new species, as well as high abundance correlation between replicates. This approach provides a cost-effective method for obtaining extensive and accurate information on complex environmental microbial communities.

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least ten studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z [≥] 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone - i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

Viruses play a crucial role in agroecosystem functioning. However, few studies have examined the diversity of the soil virome, especially when it comes to RNA viruses. Despite the great progress in viral metagenomics and metatranscriptomics (metaviromics) toward RNA viruses characterization, soil RNA viruses ecology is embryonic compared to DNA viruses. We currently lack a wet lab. method to accurately unhide the true soil viral diversity. To overcome this limitation, we developed dsRNA-based methods capitalizing on our expertise in soil RNA extraction and dsRNA extraction ported from studies of phyllosphere viral diversity. This proposed method detected both RNA and DNA viruses and is proven to capture a greater soil virus diversity than existing methods, virion-associated nucleic enrichment, and metaviromics. Indeed, using this method we detected 284 novel RNA-dependent RNA polymerases and expanded the diversity of Birnaviridae and Retroviridae viral families to agricultural soil, which, to our knowledge, have never been reported in such ecosystem. The dsRNA-based method is cost-effective in terms of affordability and requirements for data processing, facilitating large-scale and high-throughput soil sample processing to unlock the potential of the soil virome and its impact on biogeochemical processes (e.g. carbon and nutrient cycling). This method can also benefit future studies of viruses in complex environments, for example, to characterize RNA viruses in the human gut or aquatic environment where RNA viruses are less studied mainly because of technical limitations.

The soil-dwelling plant symbiont Sinorhizobium meliloti is a major model organism of Alphaproteobacteria. Despite numerous detailed OMICS studies, information about small open reading frame (sORF)-encoded proteins (SEPs) is largely missing, because sORFs are poorly annotated, and SEPs are hard to detect experimentally. However, given that SEPs can fulfill important functions, cataloging the full complement of translated sORFs is critical for analyzing their roles in bacterial physiology. Ribosome profiling (Ribo-seq) can detect translated sORFs with high sensitivity, but is not yet routinely applied to bacteria because it must be adapted for each species. Here, we established a Ribo-seq procedure for S. meliloti 2011 based on RNase I digestion and detected translation for 60% of the annotated coding sequences during growth in minimal medium. Using ORF prediction tools based on Ribo-seq data, subsequent filtering, and manual curation, the translation of 37 non-annotated sORFs with [≤] 70 amino acids was predicted with high confidence. The Ribo-seq data were supplemented by mass spectrometry (MS) analyses from three sample preparation approaches and two integrated proteogenomic search databases (iPtgxDBs). Searches against a standard and a 20-fold smaller Ribo-seq data-informed custom iPtgxDB confirmed many annotated SEPs and identified 11 additional novel SEPs. Epitope tagging and Western blot analysis confirmed the translation of 15 out of 20 SEPs selected from the translatome map. Overall, by applying MS and Ribo-seq as complementary approaches, the small proteome of S. meliloti was substantially expanded by 48 novel SEPs. Several of them are conserved from Rhizobiaceae to Bacteria, suggesting important physiological functions.

This study aimed to establish a robust, reproducible and reliable metaproteomic pipeline for an in-depth characterization of marine particle-associated (PA) bacteria. To this end, we compared six well-established protein extraction protocols together with different MS-sample preparation techniques using particles sampled during a North Sea spring algae bloom in 2009. In this optimized workflow, proteins are extracted using a combination of SDS-containing lysis buffer and cell disruption by bead-beating, separated by SDS-PAGE, in-gel digested and analysed by LC-MS/MS, before MASCOT search against a metagenome-based database and data processing/visualization with the in-house-developed bioinformatics tools Prophane and Paver.\n\nAs proof of principle, free-living (FL) and particulate communities sampled in April 2009 were analysed, resulting in an as yet unprecedented number of 9,354 and 5,034 identified protein groups for FL and PA bacteria, respectively. Our data revealed that FL and PA communities appeared similar in their taxonomic distribution, with notable exceptions: eukaryotic proteins and proteins assigned to Flavobacteriia, Cyanobacteria, and some proteobacterial genera were found more abundant on particles, whilst overall proteins belonging to Proteobacteria were more dominant in the FL fraction. In contrast, significant functional differences including proteins involved in polysaccharide degradation, sugar- and phosphorus uptake, adhesion, motility, and stress response were detected.\n\nOriginality-Significance StatementMarine particles consist of organic particulate matter (e.g. phyto- or zooplankton) and particle-associated (PA) microbial communities, which are often embedded in a sugary matrix. A significant fraction of the decaying algal biomass in marine ecosystems is expected to be mineralized by PA heterotrophic communities, which are thus greatly contributing to large-scale carbon fluxes. Whilst numerous studies have investigated the succession of planktonic marine bacteria along phytoplankton blooms, the community structure and functionality of PA bacterial communities remained largely unexplored and knowledge on specific contributions of these microorganisms to carbon cycling is still surprisingly limited. This has been mostly been due to technical problems, i.e. to the difficulty to retrieve genomic DNA and proteins from these polysaccharide-rich entities, their enormous complexity and the high abundance of eukaryotic microorganisms.\n\nOur study presents an innovative, robust, reproducible, and reliable metaproteomics pipeline for marine particles, which will help to address and fill the above-described knowledge gap. Employing the here established workflow enabled us to identify more than 5,000 PA proteins, which is, at least to our knowledge, the largest number of protein groups ever assigned to marine particles. Notably, the novel pipeline has been validated by a first, comparative metaproteome analysis of free-living and PA bacterial communities indicating a significant functional shift enabling surface-associated bacteria to adapt to particle-specific living conditions. In conclusion, our novel metaproteomics pipeline presents a solid and promising methodological groundwork for future culture-independent analyses of seasonal taxonomic and functional successions of PA microbial communities in aquatic habitats.

Bacteria colonizing in the phycosphere formed by phytoplankton exudates play important roles in marine ecosystems, yet their taxonomy is poorly defined. Here, we customized the analytical approaches for the microalga-attached microbiotas from 110 diatom and 86 dinoflagellate samples to reveal key bacterial players and their ecological significance in the phycosphere. The results demonstrated a co-occurrence of host-specificity and conservation of phytoplankton-associated bacterial communities, defined 8 diatom- and 23 dinoflagellate-affiliated characteristic genera, as well as identifying 14 core genera prevalent with phytoplankton populations. Further classification of these 14 core genera into three tiers showed their distinct ecological features regarding occupancy, connectivity and community-stabilizing, whilst also matching their inherent metabolic properties. Our study redefines the archetypal phytoplankton-associated bacteria taxa more specifically up to the genus level, highlighting the significance of rarely noticed bacteria in the phycosphere, which is invaluable when selecting target bacteria for studying phytoplankton-bacteria interactions.

BackgroundNon-cyanobacteria diazotrophs (NCDs) were shown to dominate in surface waters shifting the long-held paradigm of cyanobacteria dominance and raising fundamental questions on how these putative heterotrophic bacteria thrive in sunlit oceans. The absence of laboratory cultures of these bacteria significantly limits our ability to understand their behavior in natural environments and, consequently, their contribution to the marine nitrogen cycle. ResultsHere, we used a multidisciplinary approach and report an unprecedented finding in the diatom Phaeodactylum tricornutum (Pt) of NCDs in the phycosphere or the pelagic community sustaining its survival in the absence of bioavailable nitrogen. We sequenced the bacterial metacommunity associated with Pt and assembled several bacterial genomes, identifying multiple NCDs from the Rhizobiales order, including Bradyrhizobium, Mesorhizobium, Georhizobium and Methylobacterium. We demonstrated the nitrogen-fixing ability of PtNCDs through in silico identification of nitrogen fixation genes, or by using PCR, acetylene reduction, or 15N incorporation. We showed the wide occurrence of this type of interactions with the isolation of NCDs from other microalgae, their identification in the environment, and their predicted associations with photosynthetic microalgae. ConclusionsOur study underscores the importance of microalgae interactions with NCDs to permit and support nitrogen fixation. This work provides a unique model Pt-NCDs to study the ecology of this interaction advancing our understanding of the key drivers of global marine nitrogen fixation.

Bio-Orthogonal Non-Canonical Amino Acid Tagging (BONCAT) has emerged as a prominent molecular technique that enables microbial ecologists to visualize and identify metabolically active cells in cultures and complex microbial communities. To date, researchers have used just one non-canonical amino acid (ncAA) in a given experiment; here, we validate a novel approach using two different ncAAs in a single experiment. This advancement facilitates the detection of differentially active subpopulations within the same experimental context, thereby reducing the uncertainty and variability associated with parallel treatments, and providing precise spatial information about organisms that are active under distinct conditions or at different times. We show that both ncAAs can be taken up by E. coli cultures and by constituents of the Little Sippewissett Salt Marsh microbiome, resulting in fluorescence signals that are significantly higher than background and ncAA-free control experiments, as well as differential labeling patterns reflective of distinct subpopulations. As a proof of concept, we implemented this "dual-BONCAT" approach in salt marsh sediments, adding one ncAA during daytime hours and the other at night. Subpopulations of cells that were anabolically active during the day and/or night were distinguishable by both fluorescence microscopy, and by fluorescence-activated cell sorting. Subsequent high-throughput 16S rRNA gene amplicon sequencing of active subpopulations revealed that Methylobacterium, potentially feeding on plant exudate carbon, was preferentially active during the day, while sulfur-cycling taxa dominated the night-active population. Dual-BONCAT offers an important advancement in multiplexing substrate-analog probing techniques, providing a more realistic understanding of metabolic activity under distinct environmental conditions. ImportanceMicrobial communities are complex and dynamic, with different groups of microbes active under distinct conditions. Bio-Orthogonal Non-Canonical Amino Acid Tagging (BONCAT) uses synthetic amino acids to tag newly made proteins, allowing researchers to see and identify the active subset of a community. While BONCAT studies to date have used a single synthetic amino acid to evaluate cell activity in a single experimental context, here we introduce a new approach, "dual-BONCAT," using two synthetic amino acids to track differential responses to changing conditions. After validating the approach with E. coli, we deployed it in a salt marsh sediment community, finding that organisms potentially feeding on plant root sugars were more active during the day, and microbes likely metabolizing sulfur were more active at night. We believe dual-BONCAT will prove useful in many studies, as it illuminates microbial community responses to changing conditions, which has important implications for ecosystem dynamics.

Diatom blooms influence carbon cycling through organic matter production and its subsequent deposition or remineralization - processes that are all tightly mediated by interactions with the microbial community. Viruses, as integral part of microbial communities, are known to influence diatom bloom dynamics and can even terminate blooms. However, the three-way interactions between diatoms, their viruses and associated bacteria remain poorly resolved. In this study we examined how infection of the toxigenic diatom Pseudo-nitzschia galaxiae by its ssRNA virus PnGalRNAV reshapes host physiology, microbiome structure and organic-matter processing in non-axenic batch cultures. With an integrated transcriptomics and microscopy-based approach, we investigated the response of the bacterial community to dissolved organic matter (DOM) released by viral lysis of diatoms and observed a significant increase of Flavobacteriaceae (Bacteriodetes) suggesting a specialized role in utilizing DOM released due to viral lysis. Despite overwhelming viral RNA, bacterial metatranscriptomes revealed upregulation of polysaccharide-degradation associated genes, indicating active utilisation of virus-derived diatom glycans. Host transcripts showed broad repression of photosynthesis, silicon metabolism and core biosynthetic pathways, alongside induction of heat-shock and other stress-related genes, consistent with a senescence-like state. Our results demonstrate that PnGalRNAV infection speeds the termination of P. galaxiae growth, rapidly converting a productive diatom culture into a detrital DOM-rich environment that selects for specialised polysaccharide degraders and redirects carbon through the viral shunt. Infected cultures reached senescence much sooner than uninfected ones, suggesting that the ssRNA virus of Pseudo-nitzschia galaxiae can shorten bloom duration and accelerate nutrient recycling, with implications for coastal biogeochemistry. By integrating spatially resolved microscopy with community and metatranscriptomic profiling, this study links microbial composition, localization, and functional activity during diatom viral lysis. Our comprehensive approach can be extended to diverse diatom-virus systems in the future to better predict when viral outbreaks will favour recycling versus export of phytoplankton-derived carbon.

Viruses are exceedingly common, but little is known about their diversity let alone how they behave in extreme environments, and whether viruses facilitate adaptation of their hosts to harsh conditions. To set a foundation for understanding of these understudied viral-host interactions, we created a catalog of viruses through analysis of metagenomes from 50 unialgal but nonaxenic Cyanobacteria cultures with 47 cultures isolated from various terrestrial habitats, including desert soil and rock surfaces, tropical soil, and vernal pools. These cultures represent low diversity microbial consortia dominated by the terrestrial Cyanobacteria and its associated cyanosphere microbiome containing heterotrophic microbes. We identified viral sequences in metagenomes, grouped these into viral operational taxonomic units (vOTUs) and then placed vOTUs into viral clusters (VCs). We also calculated vOTU relative abundance and predicted possible bacterial hosts. In total we predicted 814 viral sequences representing 726 vOTUs. We assigned putative taxonomy to 72 of the 814 putative viral sequences; these were distributed into 15 VCs -- mostly assigned to the recently abolished Caudovirales order (now Caudoviricetes class) of viruses. We found that nonaxenic cultures were dominated by unclassified and unclustered viral sequences. Furthermore, we predicted putative bacterial hosts for 211 vOTUs, with the majority of viruses predicted to infect a Proteobacteria (now Pseudomonadota) host. Overall, while limited, these results are consistent with the notion that both viruses and Cyanobacteria isolated from extreme environments are underrepresented in reference datasets. This work increases knowledge of viral diversity and sets a foundation for future exploration of viruses associated with terrestrial Cyanobacteria and their heterotroph associates, such as connecting specific viruses to critical cycling processes and investigating their metabolic functions.

BackgroundBrown algae (Phaeophyceae) are essential species in coastal ecosystems where they form kelp forests and seaweed beds that support a wide diversity of marine life. Host-associated microbial communities are an integral part of phaeophyte biology. The bacterial microbial partners of brown algae have received far more attention than microbial eukaryotes. To our knowledge, this is the first study to investigate brown algal-associated eukaryotes (the eukaryome) using broadly targeting pan-eukaryotic primers and high throughput sequencing (HTS). Using this approach, we aimed to unveil the eukaryome of seven large common brown algal species. We also aimed to assess whether these macroalgae harbour novel eukaryotic diversity and to ascribe putative functional roles to the host-associated eukaryome, based on taxonomic affiliation and phylogenetic placement. ResultsOur sequence dataset was dominated by brown algal reads, from the host species and potential symbionts. We also detected a broad taxonomic diversity of eukaryotes in the brown algal holobiomes, with OTUs taxonomically assigned to ten of the eukaryotic major Kingdoms or supergroups. A total of 265 microeukaryotic and epi-endophytic operational taxonomic units (OTUs) were defined, using 97% similarity cut off during clustering, and were dominated by OTUs assigned to stramenopiles, Alveolata and Fungi. Almost one third of the OTUs we detected have not been found in previous molecular environmental surveys, and represented potential novel eukaryotic diversity. This potential novel diversity was particularly prominent in phylogenetic groups comprising heterotrophic and parasitic organisms, such as labyrinthulids and oomycetes, Cercozoa, and Amoebozoa. ConclusionsOur findings provide important baseline data for future studies of seaweed-associated microorganisms, and demonstrate that microeukaryotes and epi-endophytic eukaryotes should be considered as an integral part of brown algal holobionts. The potential novel eukaryotic diversity we found and the fact that the vast majority of macroalgae in marine habitats remain unexplored, demonstrates that brown algae and other seaweeds are potentially rich sources for a large and hidden diversity of novel microeukaryotes and epi-endophytes.

2.Solirubrobacter, a genus within the Actinobacteriota phylum, is commonly found in soils and rhizospheres yet remains unexplored despite its widespread presence and diversity, as revealed through metagenomic studies. Previously recognized as a prevalent soil bacterium, our study delved into phylogenomics, pangenomics, environmental diversity, and bacterial interactions of Solirubrobacter. Analyzing the limited genomic sequences available for this genus, we uncovered a pangenome consisting of 19,645 protein families, with 2,644 constituting a strict core genome. While reported isolates do not exhibit motility, we intriguingly discovered the presence of flagellin genes, albeit with an incomplete flagellum assembly pathway. Our examination of 16S ribosomal genes unveiled a considerable diversity (3,166 operational taxonomic units OTUs) of Solirubrobacter in Mexican soils, and co-occurrence network analysis indicated its extensive connectivity with other bacterial taxa. Through phylogenomic analysis, we delved into the relatedness of sequenced strains and notably dismissed ASM999324v1 as a member of this genus. Our investigation extended to the metagenomic diversity of Solirubrobacter across various environments, affirming its pervasive presence in rhizospheres and certain soils. This broader pangenomic view revealed genes linked to transcription, signal transduction, defense mechanisms, and carbohydrate metabolism, highlighting Solirubrobacters adaptability. We observed that Solirubrobacters prevalence in rhizospheres is geographically indiscriminate, prompting intriguing questions about its potential interactions with plants and the biotic and abiotic determinants of its soil occurrence. Given its richness and diversity, Solirubrobacter might be a versatile yet overlooked keystone species in its environments, meriting further recognition and study. 3. Impact statementThis study explored the enigmatic world of Solirubrobacter, a widespread microbe commonly found in soils and plants across various regions. Despite its prevalence, little is known about its genetic diversity and functionality and how it thrives in diverse environments. Our research unveils the genetic secrets of Solirubrobacter, shedding light on its adaptability and ecological interactors and roles. We showed that Solirubrobacter environmental prevalence makes it a good candidate for studying the genetic basis of being a successful microbe associated with soil and plants. 4. Data summaryData, scripts and statistical analysis available in GitHub: https://github.com/genomica-fciencias-unam/Solirubrobacter Sequences, phylogenetic analysis, raw data structures: https://doi.org/10.6084/m9.figshare.24446521 16S rRNA gene raw data: https://www.ncbi.nlm.nih.gov/sra/PRJNA603586 https://www.ncbi.nlm.nih.gov/sra/PRJNA603590 Shotgun metagenomes: https://www.ncbi.nlm.nih.gov/bioproject/603603 All supporting data, code, and protocols are within the article, supplementary files, and described repositories.

Quantifying the abundance and activity of bacteria within populations and communities is fundamental to systems microbiology and microbiome research. Yet direct microscopic cell counting remains low-throughput, labor-intensive, and prone to user variability, leading many researchers to rely on indirect proxies such as optical density or multicopy marker-gene quantification. These indirect approaches do not distinguish between active and inactive cells and can obscure ecological interpretation. Here, we introduce MATRIX (Microbial Activity and Total cell quantification via Rapid Imaging and eXtraction), an efficient workflow that integrates sample extraction, fluorescence staining, automated microscopy and image analysis, and Bayesian statistical inference to quantify total and redox-active cells and derive single-cell measurements for environmental microbial populations and communities. We demonstrate its reproducibility and versatility using both cultured isolates and high-diversity soil communities. The resulting quantitative, phenotypic datasets provide rapid, direct measurements of population of community size and activity, enabling well-powered analyses that strengthen mechanistic insight into microbial responses and improve the ecological grounding of microbiome studies. ImportanceMicrobiome studies commonly rely on relative abundance data, which cannot distinguish whether compositional shifts reflect true population growth, declines in total community size, or both. Without explicit measurements of population and community sizes, mechanistic interpretation of microbiome dynamics remains incomplete. Here we present a rapid, throughput workflow, MATRIX, that quantifies both total and redox-active bacterial cells from environmental samples. By integrating single-cell phenotypes with community-level metrics, this approach anchors microbiome datasets in direct ecological accounting rather than proxies. These measurements can clarify whether observed changes in community structure represent shifts in abundance, activity, or both, improving inference about microbial responses to stress or environmental change. MATRIX therefore offers an efficient way to incorporate quantitative ecology into systems-microbiology and microbiome studies and to strengthen the link between microbial cellular physiology, community dynamics, and eco-system function. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/712149v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@2e5883org.highwire.dtl.DTLVardef@b5412dorg.highwire.dtl.DTLVardef@1c9fbfaorg.highwire.dtl.DTLVardef@1bdde14_HPS_FORMAT_FIGEXP M_FIG C_FIG

Marine viruses are key players of ocean biogeochemistry, profoundly influencing microbial community ecology and evolution. Despite their importance, few studies have explored the temporal dynamics of viral genome abundances in marine environments. Viral dynamics are complex, influenced by multiple factors such as host population dynamics and environmental conditions. To disentangle the complexity of viral communities, we developed an unsupervised machine learning framework to classify viral genomes into "chronotypes" based on temporal abundance patterns. Analysing an inter-seasonal monthly time-series of surface viral metagenomes from the Western English Channel, we identified chronotypes and compared their functional and evolutionary profiles. Results revealed a consistent annual cycle with steep compositional changes from winter to summer and steadier transitions from summer to winter. Seasonal chronotypes were enriched in potential auxiliary metabolic genes like ferrochelatases and 2OG-Fe(II) oxygenases compared to non-seasonal types. Chronotypes clustered into four groups based on their correlation profiles with environmental parameters, primarily driven by temperature and nutrients. Viral genomes exhibited a rapid turnover of polymorphisms, akin to Red Queen dynamics. However, within seasonal chronotypes, some sequences exhibited annual polymorphism recurrence, which declined over a 16-month period, suggesting that a fraction of the seasonal viral populations evolve more slowly. Classification into chronotypes revealed viral genomic signatures linked to temporal patterns, likely reflecting metabolic adaptations to environmental fluctuations and host dynamics. This novel framework enables the identification of long-term trends in viral composition, environmental influences on genomic structure, and potential viral interactions.

Bacterial culture collections are essential resources for exploring the diversity of microorganisms and their interactions with each other and their hosts. Here, we report on the sequencing of the first 129 bacterial isolates, representing 34 genera, from a culture collection of more than 600 bacterial strains originally isolated from leaves of a naturalised Arabidopsis thaliana population from [O]tautahi (Christchurch), Aotearoa New Zealand. Epiphytic (leaf surface), and endophytic (apoplastic) bacteria were isolated separately from the same leaves, providing complementary insights into both compartments. The recovered isolates encompass the dominant taxa typically associated with the Arabidopsis phyllosphere, including Pseudomonas, Sphingomonas, Methylobacterium, and Flavobacterium. Their full genome assemblies (BUSCO average completeness > 99%, checkM average completeness > 97% and average contamination < 1%) were analysed and compared to assess genomic features across epiphytic and endophytic lineages. While the epiphytic and endophytic strain collections did not show large genomic differences, certain functional categories differ, such as terpene biosynthesis and biofilm formation being enriched in epiphytic strains, while arginine biosynthesis and carbohydrate degradation were associated with endophytic strains. These data provide a genomic foundation for future experimental work on leaf-associated microbial ecology and plant-microbe interactions. To our knowledge, this is the first Arabidopsis leaf culture collection established from a Southern Hemisphere source.

Mays stability theory [1, 2], which holds that large ecosystems can be stable up to a critical level of complexity, a product of the number of resident species and the intensity of their interactions, has been a central paradigm in theoretical ecology [3-7]. So far, however, empirically demonstrating this theory in real ecological systems has been a long-standing challenge, with inconsistent results [8]. Especially, it is unknown whether this theory is pertinent in the rich and complex communities of natural microbiomes, mainly due to the challenge of reliably reconstructing such large ecological interaction networks [9-11]. Here, we introduce a novel computational framework for estimating an ecosystems complexity without relying on a priori knowledge of its underlying interaction network. By applying this method to human-associated microbial communities from different body sites [12] and sponge-associated microbial communities from different geographical locations [13], we found that in both cases the communities display a pronounced trade-off between the number of species and their effective connectance. These results suggest that natural microbiomes are shaped by stability constraints, which limit their complexity.

Extensive agriculture and the use of chemical fertilizers cause notable environmental impacts on multiple levels, from reducing soil microbiota diversity to groundwater contamination. In this context, the usage of plant growth-promoting bacteria (PGPB) presents a sustainable alternative to enhance crop production while mitigating these adverse effects. Azospirillum, a bacterial genus renowned for its beneficial capabilities, particularly phytohormone production, is a key component of many commercial inoculants. In this work, we performed a comparative genomic analysis of all publicly available Azospirillum genomes and four novel isolates belonging to our microbial collection. Our analysis identified a species complex within the genus, which we designate the A. brasilense species complex, comprising species already used in commercial bioconsortia. This complex is characterized by a core set of exclusive genes linked to chemotaxis and host-recognition capability. Furthermore, we also validated the biosafety of the A. brasilense species complex and confirmed the plant growth-promoting potential of our novel isolates, highlighting their suitability for developing new biofertilizers.

Soil virus communities are diverse and dynamic but contributions to specific processes, such as nitrification, are largely uncharacterised. Chemolithoautotrophic nitrifiers perform this essential component of the nitrogen cycle and are established model groups for linking phylogeny, evolution and ecophysiology due to limited taxonomic and functional diversity. Ammonia-oxidising bacteria (AOB) dominate the first step of ammonia oxidation at high supply rates, with ammonia-oxidising archaea (AOA) and complete ammonia-oxidising Nitrospira (comammox) often active at lower supply rates or when AOB are inactive, and nitrite-oxidising bacteria (NOB) completing canonical nitrification. Here, the diversity and genome content of dsDNA viruses infecting different nitrifier groups were characterised after in situ enrichment via differential host inhibition, a selective approach that alleviates competition for non-inhibited populations to determine relative activity. Microcosms were incubated with urea to stimulate nitrification and amended with 1-octyne or 3,4-dimethylpyrazole phosphate (AOB inhibited), acetylene (all ammonia oxidisers inhibited), or no inhibitor (AOB stimulated), and virus-targeted metagenomes characterised using databases of host genomes, reference (pro)viruses and hallmark genes. Increases in the relative abundance of nitrifier host groups were consistent with predicted inhibition profiles and concomitant with increases in the relative abundance of their viruses, represented by 200 viral operational taxonomic units. These included 61 high-quality/complete virus genomes 35-173 kb in length and possessing minimal similarity to validated families. Most AOA viruses were placed within a unique lineage and viromes were enriched in AOA multicopper oxidase genes. These findings demonstrate that focussed incubation studies facilitate characterisation of host-virus interactions associated with specific functional processes.

Advances in next generation sequencing have made it possible to explore microbial community dynamics and regulation of functionally important genes through metagenomics and metatranscriptomics. However, the use of meta-omics to link enzyme function directly with complex, community-level phenotypes remain largely unexplored. To overcome this gap, we developed a novel framework that integrates ecological concepts by microbial community perturbation with association analysis to a targeted phenotype. Specifically, we introduce a hypothesis-free "bait and switch" strategy demonstrated through salt marsh soil microcosm pulse experiments to detect and characterize novel enzymes responsible for chitin degradation. Soil microbial communities were "baited" with shell compost, a chitin-rich substrate, to trigger community succession toward chitin degraders and gene upregulation of chitinases. A "switch" was then employed, by addition of glucose, inducing rapid downregulation of genes putatively responsible for chitin degradation. Results demonstrate the feasibility of this approach to identify functionally important enzymes, in this example, 48 hours after chitin addition. The bait and switch community perturbation provides a framework for discovery of polymer degrading enzymes present in complex microbial communities and serves as a proof of concept applicable for linking enzyme function with emergent community level phenotypes.

IntroductionCaves represent unique, nutrient-limited windows into the deep biosphere, yet the microbiology of the deep terrestrial subsurface remains remarkably under-explored. In this work, we took advantage of a rare expedition into Gourgouthakas Cave (Crete, Greece), one of the worlds deepest vertical systems, which had remained untouched by humans for 19 years. MethodsWe performed a high-resolution vertical profiling of the caves microbiome by sampling rock surfaces across nine different depths down to 1,100 meters. Through extensive cultivation using various media and temperatures, we established a biobank of 820 bacterial isolates. ResultsTaxonomic identification of a 362-isolate subset revealed a diverse community spanning 25 genera and 4 phyla, dominated by Pseudomonas, Bacillus, and Stenotrophomonas. Beyond characterizing diversity, we explored the biotechnological potential of these subterranean microbes against major agricultural threats. Screening 70 representative isolates against six key pathogens, including Ralstonia solanacearum, Verticillium dahliae, and Phytophthora nicotianae, uncovered a significant group of strains with potent antagonistic activity, particularly within the Pseudomonas and Brevibacillus groups. Genomic sequencing of cave-derived Actinobacteria (Streptomyces and Nocardiopsis isolates) further highlighted this potential, revealing 142 biosynthetic gene clusters (BGCs); notably, over half of these showed little to no similarity to known clusters, suggesting a hidden reservoir of novel secondary metabolites. Finally, ex vivo trials showed that the Pseudomonas sp. SRL917 isolate, significantly reduced Botrytis cinerea infections on tomato leaves, even surpassing the performance of a commercial biocontrol agent. DiscussionCollectively, our results demonstrate that deep karstic systems are not just geological wonders but vital hotspots for microbial innovation with tangible applications for sustainable agriculture.