Environmental Microbiome最新文献

Background: Enhanced nitrogen (N) load was considered a critical factor influencing phosphorus (P) availability and P-cycling in marsh soils. However, information on the links between soil P availability and microbial genes involved in P-cycling processes under N enrichment conditions remains scarce.

Methods: A field N load experiment with four treatments (N₀, N_low, N_medium, and N_high) was conducted in Cyperus malaccensis marsh of the Min River estuary, and soil P availability, the relative abundances of P-cycling functional genes and their regulatory roles on P availability were investigated.

Results: The total phosphorus (TP) contents in soils were significantly positively correlated with N load levels (p < 0.05). Compared with the N₀ treatment, the TP in the N_low, N_medium and N_high treatments increased by 8.97%, 17.34% and 15.21%, respectively. With increasing N load levels, the proportions of easily- and moderately-available P in TP contents noticeably increased, suggesting that N additions enhanced soil P availability. Metagenomic sequence analyses showed that N enrichment markedly altered the relative abundances of P-cycling functional genes. Briefly, the abundances of inorganic P solubilization genes (particularly ppa and ppx) increased substantially with increasing N load levels. The total abundances of organic P mineralization genes in the N_low and N_medium treatments decreased markedly, while those in the N_high treatment increased greatly. The abundances of genes coding for phytase (phy and appA) markedly increased with increasing N load levels, implying that phytase was more sensitive to N enrichment. Furthermore, enhanced N load noticeably reduced the abundances of genes participated in P transportation (particularly ugpABEC) and those involved in P-assimilating process (e.g., phoR, phoB, pstABCS and pit). As affected by enhanced N load, the contents of easily-available P showed strong correlations with the abundances of genes involved in inorganic P solubilization while those of moderately-available P (particularly Sonic-P_i, Sonic-P_o and NaOH-P_i) were positively correlated with the abundances of genes involved in P regulation and transportation, indicating strong linkages between P-cycling functional genes and soil P availability.

Conclusions: This paper found that, under N enrichment conditions, the increased inorganic P solubilization potential and the weakened microbial P immobilization capacity were beneficial to increasing soil P availability.

Background: Viruses play key roles in regulating soil microbial dynamics and biogeochemical cycles. T4-like bacteriophages, one of the best-studied viral groups, are abundant in soils, but their biogeographical patterns and ecological drivers remain poorly understood. In this study, we performed the first large-scale assessment of soil T4-like bacteriophages based on metagenomic data using viral hallmark genes, revealing broad spatial structure, identifying dominant environmental factors, and projecting shifts under future climate scenarios.

Results: We analyzed two viral hallmark genes, gene 20 (g20) and gene 23 (g23), retrieved from global soil metagenomes, and National Center for Biotechnology Information (NCBI) reference sequences, yielding 2,385 and 2,928 full-length sequences clustered into 1,211 and 1,269 operational taxonomic units (OTUs), respectively. Phylogenetic analysis revealed that only a small fraction of soil-derived sequences could be assigned to established viral families, with most remaining unclassified below the class Caudoviricetes. The relative abundances of g20 and g23 were assessed at 116 sites spanning 14 biomes across six continents. Consistent biogeographic patterns were observed for both genes, with higher relative abundance in tropical climates and lower levels in polar and dry regions, indicating strong climatic influence. Temperature seasonality (BIO4) was identified as the primary environmental driver, showing a significant negative correlation with the relative abundance of both genes. Using an extreme gradient boosting (XGBoost) model, we predicted global distribution patterns based on extrapolation, revealing concordant global trends, with lower relative abundances in regions with greater seasonal temperature variation. Future projections of BIO4 and viral gene abundance further supported this significant negative correlation.

Conclusions: Our findings reveal that temperature seasonality constrains the abundance of soil T4-like bacteriophages, which serve as sensitive indicators of climate-driven environmental shifts and play important ecological roles within soil microbial communities.

Background: In this study, xTitan, a field-deployable, automated, and versatile nucleic acid extraction system was employed to characterize microbial communities in Red Sea-derived samples, including coral colonies, mangrove sediments, and seawater. The use of the xTitan in the field was intended to minimize sample transport bias, obtaining data that may be closer to "ground truth" for microbial diversity. The observed microbial communities from DNA extracted in the field using the xTitan system were compared to DNA extractions performed in a laboratory setting using both xTitan and a standard commercial kit (Qiagen) after approximately 24 h of sample transfer and storage.

Results: Microbial community analyses conducted on DNA extracted using the xTitan system and the Qiagen kit yielded similar alpha diversity metric values, with a trend toward higher diversity observed in most samples extracted with the xTitan. The microbial community structure in samples from a Pocillopora verrucosa colony, mangrove sediments, and seawater was affected by the DNA extraction system. In the P. verrucosa colony, 16S rRNA gene sequences affiliated to Endozoicomonas acroporae were preferentially abundant when DNA was extracted in the field with the xTitan system rather than in the lab. In mangrove sediments, significant differences (P-value < 0.05) in beta diversity and functional gene profiles were observed when comparing in-field to in-lab xTitan DNA extracts. In seawater, a pronounced decrease in the relative abundance of cyanobacterial populations was observed when DNA was extracted with both methods after samples were transported to the lab on ice. In addition, hundreds of species in mangrove-associated samples were differentially abundant when DNA was extracted on-site with the xTitan system compared to in-lab extractions. Balneolaceae was one of the most abundant taxa in mangrove sediments and several genera from this family were detected in all replicates across all DNA extraction systems.

Conclusions: The usability of different field-deployable instruments for microbial community characterization in marine-derived samples was demonstrated. Moreover, differences in beta diversity were observed when DNA was extracted in-field versus in-lab using the xTitan system, particularly for mangrove-associated samples. These results highlight the value of on-site nucleic acid extraction for enhancing the detection of microbial taxa that can be sensitive to cold storage. This study enabled the testing of the xTitan on Red Sea-derived samples, generating comprehensive information on the effects of DNA extraction systems and transportation of samples on coral and mangrove-associated microbiomes.

Background: River-lake ecosystems are crucial for the rational allocation of water resources, but frequent water diversion can destabilize water quality due to hydraulic disturbance. Microbial communities can respond rapidly to such external perturbations and influence these systems through the effects on nutrient metabolism. Therefore, understanding how microbial communities respond to hydraulic shocks in aquatic systems and whether they can adapt to such disturbances is essential for maintaining the health of river-lake systems. We used 16S rRNA and metagenomic sequencing technologies to examine the metabolic regimes of microbial communities during water regulation and non-regulation periods in river-lake systems.

Results: We found that hydraulic disturbance tended to drive the microbial community toward homogenized selection, thereby weakening its stability. Flow velocity (V) and the nitrate (NO₃^--N) concentration significantly affected microbial community composition and abundance, with clear threshold effects. We established low (V = 0.284 m/s, NO₃^--N = 0.031 mg/L) and high (V = 0.461 m/s, NO₃^--N = 0.055 mg/L) thresholds. These thresholds categorize microbial communities into three distinct regimes: regime1 (R1), regime 2 (R2), and regime 3 (R3). The microbial abundances in R1 and R3 were significantly higher than those in R2 (p < 0.01), while the community in R3 exhibited a strong denitrification capacity. In R3, the microbial community enhanced its denitrification metabolism by promoting the growth of denitrifying microbial genera (e.g., Pseudomonas and Flavobacterium) to counterbalance the impact of high V and NO₃^--N. These strains contributed the denitrification-related genes nasA, narB, nirB, and nirD to the community, thereby promoting the NO₃^--N metabolism and reducing environmental NO₃^--N concentrations. In addition, we predicted microbial community abundance using an artificial neural network to validate the thresholds we identified.

Conclusions: Our study provides theoretical support for understanding how microbial communities adapt to high-frequency hydraulic disturbances and offer valuable insights for managers to adjust water diversion strategies in a timely manner, thereby safeguarding the integrity of river-lake ecosystems.

Background: Biofiltration offers a sustainable, low-energy solution for drinking water treatment but suffers from inconsistent performance due to complex microbial dynamics. Current studies lack insight into early biofilter microbial community assembly. Here we perform a high-resolution spatial and temporal investigation of biomass accumulation and community development within biological activated carbon (BAC) filters over the first 6 months of operation.

Results: We found that initial biomass accumulation is not linear, instead characterised by periods of growth and decay. Mass balance identified an estimated + 6.54 × 10⁸ new cells daily during the growth phase (days 34-62), falling to a loss of 1.69 × 10⁹ by the decay phase (days 83-162). There was no significant increase in richness until the decay phase (ANOVA p values > 0.05 between days 34, 62 and 83). Significant stratification (ANOVA p values < 0.05) was observed with bed depth with 79% (± SD2.7%) of biomass found in the top 15 cm of the filter bed, the bottom section (90 cm) had 36.5-fold lower biomass. An abundant community of 20 primary colonisers made up to between 20 ± SD8% and 80 ± SD5% of the total community and persisted over time. This community increased in absolute number during the growth phase (140% increase) however remained stable after this. Conversely rare taxa were found to continue to increase into the decay phase (131% between days 62-162). Core community analysis and neutral modelling of the seeding influent water and the biofilter found that the abundant taxa stochastically assembled early from the water, while the rare taxa driving changes in diversity, were selected by deterministic factors within the filter bed with 38% advantaged by the filter environment, compared to only 20% of the persistent abundant community.

Conclusion: This study demonstrates that biofilter microbial communities undergo dynamic changes, with abundant early colonizers persisting steadily while rare taxa drive fluctuations in biomass through phases of growth and decay. Understanding these microbial dynamics and ecological interactions can inform engineering strategies to optimize biofilter performance, enhancing water treatment efficiency by targeting key microbial groups throughout filter maturation.

In marine sediments, microorganisms' roles in recycling organic and inorganic molecules, including hydrocarbons, are critical for ecosystem function. Genomic studies in the Gulf of Mexico (GoM) reveal that microbial community composition and function are shaped by environmental gradients, with hydrocarbon degradation relying on consortia dynamics rather than single species, highlighting their collective ecological importance. Our study evaluated the prokaryotic microbial community in deep-sea GoM sediments, under a depth gradient, in Coatzacoalcos and Perdido regions, two areas influenced by crude-oil efflux and petroleum extraction. Findings indicated depth was the primary driver of microbial community structure, with distinct compositional shifts between shallow (< 1000 m) and deep (> 1200 m) sediments, showcasing microbial adaptation to deep-sea nutrient-limited conditions. Furthermore, functional gene analysis revealed depth-specific metabolic partitioning, with Deltaproteobacteria dominating amino acid and energy metabolism in shallow sediments, while Alphaproteobacteria and Thaumarchaeota prevailed in deeper zones. This underlines the importance of microbial community shifts in composition and structure in ensuring environmental resilience. In addition, relatively low-abundance but critical hydrocarbon degradation genes were detected, primarily in shallow/transition zones, indicating niche-specific potential for bioremediation despite their apparent limited representation. This research contributes to advancing our understanding of alternative carbon and energy metabolisms linked to hydrocarbon degradation that are widely distributed across different microbial communities inhabiting deep-sea marine sediments.

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.