Environmental Microbiome最新文献

Background: Hairy root disease (HRD), caused by rhizogenic Agrobacterium strains, is a significant disease threat to modern hydroponic greenhouses, which can result in up to 15% loss in yield. Our prior research has suggested increased alpha diversity after infection in hydroponic tomato root-associated microbiota. However, a more detailed investigation of how root-associated microbial components (MCs; clusters of weighted bacterial features) respond to disease and the underlying mechanisms remains lacking. To address this gap, we applied Latent Dirichlet Allocation (LDA) to analyze MCs from 12 Belgian commercial hydroponic tomato greenhouses. Using high-throughput amplicon sequencing of the 16S rRNA locus, three locations along each greenhouse irrigation system (beginning, middle, and end) were sampled at 5 time points throughout the 2018 growing season.

Results: In this study, we used LDA to identify root-associated MCs and gained insights into temporal changes and new health statuses. First, we observed a structured temporal pattern from the early stage (ES; sampling time points 1 and 2) through a transitional stage (TS; sampling time point 3) to the late stage (LS; sampling time points 4 and 5), showing different MC trajectories by health status. Second, MC4 (characterised by Paenibacillus spp.) was pronounced for healthy greenhouses in the ES, MC7 (characterised by rhizogenic Agrobacterium spp., Devosia and Limnobacter amplicon sequence variants (ASVs)) was pronounced for pre-symptomatic status, while MC0 (characterized by Comamonadaceae spp. ASVs) was indicative of an intermediate state between healthy and infected conditions. Furthermore, the ratio between Paenibacillus ASV and rhizogenic Agrobacterium ASV can be used as a biomarker to assess greenhouse health status in both ES and LS.

Conclusion: We investigated hydroponic tomato root-associated MCs responses to HRD using LDA, which revealed different MC trajectories in terms of plant health. Our study advances knowledge of hairy root disease regarding the mechanisms that can improve plant health monitoring in greenhouses and biocontrol strategies. From a computational perspective, we demonstrate how to apply LDA-a powerful analytical tool-to understudied subfields through visual analytics.

Background: Peptide Nucleic Acid (PNA) clamps represent a crucial molecular tool for reducing host DNA contamination during plant tissue microbiome profiling. This is particularly important when there is sequence similarity between the host organellar DNA (e.g., mitochondrial) and the targeted PCR sequences. However, the effectiveness and optimal concentration of universal PNA clamps can vary between plant species, necessitating a case-by-case evaluation. Here, we assessed the effectiveness of five concentrations (0.0, 0.25, 1.0, 2.0 and 4.0 µM) of mitochondrial and chloroplast PNA blockers (mPNA and pPNA) in reducing the amplification of organellar DNA and enhancing the profiling of prokaryotic communities across root tissues from 34 maize and 27 wheat samples cultivated under various soil and climatic conditions.

Results: We observed that host plant contamination in root samples was consistently high, with an average rate exceeding 95% across all samples. The application of PNA clamps significantly reduced plant host contamination by 2.4-27.2 times in a concentration-dependent manner. This reduction was more pronounced in maize samples than in wheat samples, particularly at lower doses (PNA ≤ 1.0 µM). PNA clamps also increased the read abundance of more than half of the observed microbiome phyla in the root tissues. The most substantial increase in prokaryotic read abundance was observed at a PNA concentration of 1.0 µM, without introducing significant bias to the prokaryotic community.

Conclusions: In conclusion, the introduction of universal PNA clamps during PCR assays significantly reduced amplification of host contamination and enhanced the detection of low-abundance microbiome and the depth of microbial profiling in both maize and wheat root tissues, with effects being concentration- and crop-specific.

Coastal mangroves are one of the significant hotspots of natural methane (CH₄) emissions, yet the seasonal dynamics of these emissions and the underlying microbial drivers remain poorly understood. A clearer understanding of these processes is critical for predicting and mitigating methane emissions from these crucial ecosystems. In this study, we conducted a seasonal investigation (from March 2021 to January 2022) in mangrove sediments of the Futian Natural Reserve. We measured in situ methane fluxes and analyzed the microbial community structure via 16S rRNA gene sequencing, metagenomics and metatranscriptomics. Our results revealed significant seasonal variations in methane emissions, with the highest rates occurring in summer. Based on relative abundance of 16S rRNA gene amplicons and methyl-coenzyme M reductase (mcrA) and particulate methane monooxygenase (pmoA) gene sequences obtained from metagenomes, we identified three dominant methanogenic lineages (hydrogenotrophic Methanomicrobiales, acetoclastic Methanosaeta and H₂-dependent methylotrophic Methanomassiliicoccales), two anaerobic methanotrophic archaea (ANME-1 and ANME-2b) and one group of aerobic methanotrophic bacteria (Methylococcaceae). Metatranscriptomic data further illuminated that the transcripts of methanogenic mcrA genes were significantly higher in summer and autumn, while the transcriptional activity of anaerobic (ANME-mcrA) and aerobic (pmoA) methanotrophs were most pronounced in autumn. Correlation analyses established a significantly negative relationship between methane emissions and salinity levels. This study highlights that salinity is a key environmental factor mediating methane emissions in mangroves, likely through suppressing methanogenic activity. Our findings thus reveal that seasonal microbial interactions regulate mangrove methane flux, providing critical insights for modeling global methane budgets and guiding climate-smart mangrove management.

Background: As an important driver of plant performance, the rhizobiome is altered throughout plant maturation and agricultural management, such as diversified crop rotation systems. However, a comprehensive understanding of the temporal changes in the rhizobiome (bacteria, fungi, and protists) community composition and functioning during plant maturation remains little known, especially in response to different rotation systems.

Results: We collected rhizobiome samples in four developmental stages of wheat across four different rotation systems in a long-term field experiment. Across rotation systems, wheat maturation increased bacterial and fungal diversity, and changed their community compositions, while protist communities remained unaffected. Subsequently, we validated the functioning of rhizobiomes specific to distinct rotation systems and wheat developmental stages in a greenhouse experiment. The rhizobiome in the jointing stage enhanced maize height, which was best explained by a higher relative abundance of rhizobiome predators (predominantly protists) irrespective of rotation systems. We also found a positive correlation of rhizobiome predators with the maize shoot/root biomass ratio in our greenhouse experiment, suggesting that rhizobiome predators mobilize nutrients to favour plant shoot growth.

Conclusions: We conclude that a tight plant-rhizobiome feedback loop is, independent of agricultural management, internally fostered by rhizobiome predators and wheat maturation. Our results call for studies that aim to elucidate the potential drivers underlying plant growth-induced changes in the rhizobiome to develop targeted manipulations of plant growth promoting rhizobiomes.

Background: Future climate projections indicate shifts in intra-annual precipitation patterns, with intensified rainfall events and prolonged dry periods. These changes may alter soil biotic communities and their interactions within food webs, particularly in semi-arid and arid ecosystems. However, the influence of varying rainfall regimes and increasing aridity on multitrophic associations in drylands remains poorly understood.

Methods: We leveraged a long-term rainfall manipulation experiment across 6 dryland sites in eastern Australia, including 2 arid ecosystems and 4 semi-arid ecosystems with different levels of rainfall (coefficient of variation, CV), resulting in 3 different climatic conditions. Surface soil was collected from replicated plots subjected to increased (+ 65%) or reduced (- 65%) rainfall relative to ambient conditions using rainout shelter. We characterized bacteria, fungi, protist, and nematode communities using high-throughput amplicon sequencing targeting 16S rRNA, ITS, 18S rRNA and 28S rRNA regions, respectively. Multitrophic co-occurrence network among these groups were constructed to assess biotic responses to rainfall and climatic variations.

Results: Soil biotic community composition in drylands was primarily shaped by environmental conditions, with rainfall treatments exerted no main effect. Belowground multitrophic co-occurrence networks varied significantly across climatic conditions, with aridity promoting positive bacterial associations. Bacteria, fungi, protist formed highly connected modules, and their interactions were central in maintaining multitrophic network structure. Oligotrophic bacteria and pathotrophic fungi emerged as dominant keystone taxa, with their abundance strongly influenced by mean annual precipitation (MAP), underscoring the role of long-term climatic gradients over short-term rainfall changes.

Conclusions: Our findings demonstrate that increasing aridity and rainfall variability reshape soil multitrophic networks in drylands, favoring communities dominated by stress-adapted taxa. The concurrent rise of fungal pathotrophs, potentially driven by declines in protist consumers, may undermine ecosystem resilience. Incorporating multitrophic perspectives into climate impact assessments is essential for anticipating and mitigating emerging threats, such as rising soil-borne pathogens in dryland ecosystems.

In response to climate change, plants in mountain regions are shifting their distribution ranges upward, exposing them to novel abiotic conditions such as reduced atmospheric pressure. While these changes are likely to affect plant physiology, their impact on plant-associated microorganisms in the rhizosphere has not yet been investigated. In this study, we used the terraXcube Ecotron facility to experimentally discriminate air pressure from other elevation-related factors like humidity and temperature, and to assess its influence on the rhizosphere microbiota of three plant species: a grass (Brachipodium rupestre), a forb (Hieracium pilosella), and a legume (Trifolium pratense). Plants were grown under controlled environmental conditions at four simulated elevations (260, 1500, 2500, and 4000 m a.s.l.), corresponding to pressure levels of 98, 85, 75, and 62 kPa, respectively. Microbial biomass and activity were significantly influenced by air pressure, but in a plant-specific manner. In addition, air pressure also led to notable and plant-specific shifts in the community composition of prokaryotes and, to a lesser extent, fungi. Redundancy analysis identified air pressure as a central predictor of these rhizosphere community shifts. Notably, no correlations were detected between microbial community composition and morphological and physiological plant traits, suggesting that air pressure should directly affect microorganisms, independently of plant-mediated effects. This study demonstrates that even under constant temperature and humidity, air pressure alone can restructure rhizosphere microbial communities, highlighting a critical yet often overlooked driver of plant-microbe dynamics during uphill range shifts. Whether such alterations in the rhizosphere microbiota ultimately enhance or impair soil chemistry, plant health, and ecosystem functioning remains an important question for future research.

Background: Linezolid resistance poses an ecological threat to the health of humans, animals, and the environment. Vegetable may serve as reservoirs for resistance genes, yet its prevalence remain underexplored. Therefore, this study aims to investigate the prevalence of linezolid resistance gene-positive Gram-positive bacteria in vegetables, and to explore the genetic relatedness between linezolid resistance gene reservoirs from vegetables and various niches.

Result: In this study, 70 Gram-positive bacteria carrying linezolid resistance genes were isolated from 115 samples, with Enterococcus as the main host bacteria (45/70). Among them, Enterococcus casseliflavus was most frequently identified (26/70), followed by Lactococcus lactis (18/70). Phylogenetic analysis revealed that the genetic backgrounds of these strains were significantly different from the linezolid resistance gene reservoirs in other niches. The results of the antimicrobial susceptibility test showed that these strains had high resistance rates of chloramphenicol, erythromycin, and tetracycline, and the resistance rate of linezolid was 37.1%. The overall carriage rate of linezolid resistance genes was 30.4% (95% CI 21.4-39.4%). The optrA was the most common linezolid resistance gene, with a carriage rate of 29.7% (34/115), followed by poxtA, cfr, and cfr(D) gene, with carriage rates of 2.6% (3/115), 1.7% (2/115), and 0.9% (1/115), respectively. No strains were positive for cfr(B), cfr(C), or cfr(E) genes. Among the 68 strains carrying the optrA gene, a total of 18 variants were identified. The KLDP variant was the most common (n = 25), followed by EDD (n = 10) and EDM (n = 10). Some strains also exhibited multiple OptrA variant carriage. The flanking structures of the optrA gene showed diversity, with IS1216E-fexA-optrA-Δerm(A) and Tn558-araC-optrA being the most common.

Conclusion: This study highlighted a high prevalence of the optrA gene in vegetables. E. casseliflavus was the predominant host for linezolid resistance genes, followed by L. lactis. Significant differences in genetic background were found in the linezolid resistance gene reservoirs from vegetables when compared to those from humans, animals, and the environment.

Background: Public washrooms (toilets) are potential hubs for pathogen transmission, yet the risk of microbial re-contamination via post-handwashing surfaces remains understudied. We characterized the prevalence and distribution of multidrug-resistant organisms (MDROs) and antimicrobial resistance genes (ARGs) in post-handwashing areas by sampling four high-contact sites, including faucets, paper dispensers, hand dryers, and exit door handles, in public washrooms across healthcare, commercial, and recreational facilities.

Results: From the 232 post-handwashing surface samples collected, we isolated 17 MDROs (7.33% prevalence) from cultures, including extended-spectrum beta-lactamase (ESBL)-producing Enterobacterales (ESBL-E, n = 10), carbapenem-resistant Pseudomonas aeruginosa (CRPA, n = 5), and methicillin-resistant Staphylococcus aureus (MRSA, n = 2). Additionally, we novelly employed targeted probe capture metagenomics (TCM), which utilizes oligonucleotide probes to enrich and detect low-abundance microbial species and ARG sequences. TCM revealed the detection of human pathogenic taxa in 65.2% of samples, including P. aeruginosa (78.4%), Acinetobacter baumannii (77.9%), and S. aureus (71.1%). Clinically critical ARGs, such as blaCTX-M (2.0%), blaNDM (2.9%), blaSHV (3.4%), and mecA (62.3%), were detected in 63.7% of samples, indicating a potential transmission within the post-handwashing area.

Conclusions: Our findings highlight the role of post-handwashing areas as underrecognized reservoirs for MDROs, particularly MRSA. Furthermore, this study demonstrates the utility of TCM in public health surveillance by enabling a sensitive detection of rare but high-risk microbial species and drug resistance determinants in low-biomass environmental samples. This study offers a comprehensive and nuanced view of the microbial and resistome landscape of washroom environments, offering a revolutionary approach for future environmental surveillance.

Background: Soil microbiomes harbor complex communities from which diverse ecological roles unfold, shaped by syntrophic interactions. Unraveling the mechanisms and consequences of such interactions and the underlying biochemical transformations remains challenging due to niche multidimensionality. The Atacama Desert is an extreme environment that includes unique combinations of stressful abiotic factors affecting microbial life. In particular, the Talabre Lejía transect is a natural laboratory for understanding microbiome composition, functioning, and adaptation.

Results: We propose a computational framework for the simulation of the metabolic potential of microbiomes, as a proxy of how communities are prepared to respond to the environment. Through the coupling of taxonomic and functional profiling, community-wide and genome-resolved metabolic modeling, and regression analyses, we identify key metabolites and species from six contrasting soil samples across the Talabre Lejía transect. We highlight the functional redundancy of whole metagenomes, which act as a gene reservoir, from which site-specific adaptations emerge at the species level. We also link the physicochemistry from the puna and the lagoon samples to metabolic machineries that are likely crucial for sustaining microbial life in these unique environmental conditions. We further provide an abstraction of community composition and structure for each site that allowed us to describe microbiomes as resilient or sensitive to environmental shifts, through putative cooperation events.

Conclusion: Our results show that the study of multi-scale metabolic potential, together with targeted modeling, contributes to elucidating the role of metabolism in the adaptation of microbial communities. Our framework was designed to handle non-model microorganisms, making it suitable for any (meta)genomic dataset that includes high-quality environmental data for enough samples.

Background: Since recent years, German sea buckthorn (SBT) cultivation is increasingly affected by dieback. Wildly growing plants from dunes and cultivated plants from plantations show symptoms of wilt, lesions and discolorations in shoot cross sections. The cause of final plant death is not yet resolved and asymptomatic plants are rare to find. Our aim was to investigate the associated fungal communities of visibly dieback affected plants. A culture-dependent isolation approach in parallel with a culture-independent sequencing approach by metabarcoding of ITS1 was used to investigate SBT shoot fungal communities. Evaluation of the sequencing data was supported with random forest modelling.

Results: Results of both approaches complement each other and are consistent. Members of the ascomycete genera Hymenopleella and Diaporthe were most frequently isolated from symptomatic samples. Alternaria, Aureobasidium, Cladosporium, Epicoccum and Penicillium could be identified in both sample types, i.e. symptomatic and asymptomatic plants, with high frequencies. Sequencing of shoot samples revealed that the fungal community composition differs significantly between symptomatic and asymptomatic plants. Pielou's evenness was significantly reduced for symptomatic plants indicating a dominance of few fungal taxa in symptomatic samples pointing to a dysbiosis in fungal communities. In a random forest modelling approach, abundance of Capnocheirides amplicon sequence variants had the highest relative importance for the model and high relative abundance is considered as predictor for absence of SBT symptoms. In symptomatic plants, Hymenopleella and Diaporthe had high relative abundances and were suggested as predictors.

Conclusions: Overall, our combined approach has revealed an increased abundance of Hymenopleella and Diaporthe in symptomatic sea buckthorn in Germany along with changes in the total fungal community. The relative abundances derived from amplicon sequencing were reflected by the isolation frequencies of the respective taxa.