Seasonal Changes in Soil Microbial Community and Co-Occurrence Network of Species of the Genus Corylus.
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ABSTRACT:
SUBMITTER: Ma W
PROVIDER: S-EPMC8625130 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Exploring large environmental datasets generated by high-throughput DNA sequencing technologies requires new analytical approaches to move beyond the basic inventory descriptions of the composition and diversity of natural microbial communities. In order to investigate potential interactions between microbial taxa, network analysis of significant taxon co-occurrence patterns may help to decipher the structure of complex microbial communities across spatial or temporal gradients. Here, we calculated associations between microbial taxa and applied network analysis approaches to a 16S rRNA gene barcoded pyrosequencing dataset containing >160?000 bacterial and archaeal sequences from 151 soil samples from a broad range of ecosystem types. We described the topology of the resulting network and defined operational taxonomic unit categories based on abundance and occupancy (that is, habitat generalists and habitat specialists). Co-occurrence patterns were readily revealed, including general non-random association, common life history strategies at broad taxonomic levels and unexpected relationships between community members. Overall, we demonstrated the potential of exploring inter-taxa correlations to gain a more integrated understanding of microbial community structure and the ecological rules guiding community assembly.
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| S-EPMC3960547 | biostudies-literature
Project description:Coal mining subsidence lakes are classic hydrologic characteristics created by underground coal mining and represent severe anthropogenic disturbances and environmental challenges. However, the assembly mechanisms and diversity of microbial communities shaped by such environments are poorly understood yet. In this study, we explored aquatic bacterial community diversity and ecological assembly processes in subsidence lakes during winter and summer using 16S rRNA gene sequencing. We observed that clear bacterial community structure was driven by seasonality more than by habitat, and the α-diversity and functional diversity of the bacterial community in summer were significantly higher than in winter (p < 0.001). Canonical correspondence analysis indicated that temperature and chlorophyll-a were the most crucial contributing factors influencing the community season variations in subsidence lakes. Specifically, temperature and chlorophyll-a explained 18.26 and 14.69% of the community season variation, respectively. The bacterial community variation was driven by deterministic processes in winter but dominated by stochastic processes in summer. Compared to winter, the network of bacterial communities in summer exhibited a higher average degree, modularity, and keystone taxa (hubs and connectors in a network), thereby forming a highly complex and stable community structure. These results illustrate the clear season heterogeneity of bacterial communities in subsidence lakes and provide new insights into revealing the effects of seasonal succession on microbial assembly processes in coal mining subsidence lake ecosystems.
| S-EPMC9936157 | biostudies-literature
Project description:BackgroundCo-occurrence networks-ecological associations between sampled populations of microbial communities inferred from taxonomic composition data obtained from high-throughput sequencing techniques-are widely used in microbial ecology. Several co-occurrence network methods have been proposed. Co-occurrence network methods only infer ecological associations and are often used to discuss species interactions. However, validity of this application of co-occurrence network methods is currently debated. In particular, they simply evaluate using parametric statistical models, even though microbial compositions are determined through population dynamics.ResultsWe comprehensively evaluated the validity of common methods for inferring microbial ecological networks through realistic simulations. We evaluated how correctly nine widely used methods describe interaction patterns in ecological communities. Contrary to previous studies, the performance of the co-occurrence network methods on compositional data was almost equal to or less than that of classical methods (e.g., Pearson's correlation). The methods described the interaction patterns in dense and/or heterogeneous networks rather inadequately. Co-occurrence network performance also depended upon interaction types; specifically, the interaction patterns in competitive communities were relatively accurately predicted while those in predator-prey (parasitic) communities were relatively inadequately predicted.ConclusionsOur findings indicated that co-occurrence network approaches may be insufficient in interpreting species interactions in microbiome studies. However, the results do not diminish the importance of these approaches. Rather, they highlight the need for further careful evaluation of the validity of these much-used methods and the development of more suitable methods for inferring microbial ecological networks.
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Project description:The milpa is a traditional maize-based polyculture in Mexico that is typically practiced as rainfed agriculture. Because milpa cultivation has been practiced over a vast range of environmental and cultural conditions, this agroecosystem is recognized as an important repository of biological and cultural diversity. As for any agroecosystem, the relationship between plant development and the biogeochemical processes of the soil is critical. Although the milpa has been studied from different perspectives, the diversity and structure of microbial communities within milpa soils remain largely unexplored. In this study, we surveyed a milpa system in Central Mexico across cropping season: before planting (dry season; t1), during the early growth of plants (onset of the rainy season; t2), and before harvest (end of the rainy season; t3). In order to examine changes in community structure through time, we characterized bacterial diversity through high-throughput sequencing of 16S rRNA gene amplicons and recorded the nutrient status of multiple (5-10) soil samples from our milpa plots. We estimated microbial diversity from a total of 90 samples and constructed co-occurrence networks. Although we did not find significant changes in diversity or composition of bacterial communities across time, we identified significant rearrangements in their co-occurrence network structure. We found particularly drastic changes between the first and second time points. Co-occurrence analyses showed that the bacterial community changed from a less structured network at (t1) into modules with a non-random composition of taxonomic groups at (t2). We conclude that changes in bacterial communities undetected by standard diversity analyses can become evident when performing co-occurrence network analyses. We also postulate possible functional associations among keystone groups suggested by biogeochemical processes. This study represents the first contribution on soil microbial diversity of a maize-based polyculture and shows its dynamic nature in short-term scales.
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Project description:Microorganisms are crucial components of the aquatic ecosystem due to their immense diversity and abundance. They are vital in sustaining ecological services, especially in maintaining essential biogeochemical cycles. Recent years have seen a substantial increase in surplus nitrogenous pollutants in aquatic ecosystems due to the heightened occurrence of anthropogenic activities. Elevated levels of free ammonia (FA, NH3), stemming from the discharge of excess nitrogenous pollutants, have caused notable fluctuations in aquatic ecosystems, leading to water eutrophication and various ecological challenges. The impact of these oscillations on microbial communities in aquatic ecosystems has not been extensively studied. This study employed 16S rRNA gene amplicon sequencing to systematically investigate the dynamics, co-occurrence networks, and assembly processes of microbial communities and their subcommunities (abundant, moderate, and rare) in the Luanhe River Diversion Project in China. Our findings indicate that NH3 concentration significantly influences the dynamics of microbial communities, with a notable decrease in community Richness and Phylogenetic Distance alongside increased community dissimilarity under higher NH3 conditions. The analysis revealed that certain microbial groups, particularly Actinobacteriaota, were notably more prevalent in environments with elevated NH3 levels, suggesting their potential resilience or adaptive responses to NH3 stress. Additionally, through co-occurrence network analysis, we observed dynamic changes in network topology and increased connectedness under NH3 stress. Key nodes, identified as connectors and module hubs, played crucial roles in maintaining network structure, particularly Cyanobacteria and Actinobacteriaota. Furthermore, stochastic processes, particularly drift and dispersal limitation, predominantly shaped the microbial communities. Within the three subcommunities, the impact of drift became more pronounced as the effect of dispersal limitation diminished. Overall, elucidating the dynamics of microbial communities in aquatic ecosystems exposed to NH3 can enhance our comprehension of the ecological mechanisms of microbial communities and provide new insights into the conservation of microbial community diversity and ecological functions.ImportanceThe research presented in this paper explores how varying concentrations of free ammonia impact microbial communities in aquatic ecosystems. By employing advanced gene sequencing techniques, the study reveals significant changes in microbial diversity and network structures in response to increased ammonia levels. Key findings indicate that high ammonia concentrations lead to a decrease in microbial richness and diversity while increasing community dissimilarity. Notably, certain microbial groups, like Actinobacteria, show resilience to ammonia stress. This research enhances our understanding of how pollution affects microbial ecosystems and underscores the importance of maintaining balanced ammonia levels to preserve microbial diversity and ecosystem health.
| S-EPMC11370247 | biostudies-literature
Project description:Recent studies highlight linkages among the architecture of ecological networks, their persistence facing environmental disturbance, and the related patterns of biodiversity. A hitherto unresolved question is whether the structure of the landscape inhabited by organisms leaves an imprint on their ecological networks. We analyzed, based on pyrosequencing profiling of the biofilm communities in 114 streams, how features inherent to fluvial networks affect the co-occurrence networks that the microorganisms form in these biofilms. Our findings suggest that hydrology and metacommunity dynamics, both changing predictably across fluvial networks, affect the fragmentation of the microbial co-occurrence networks throughout the fluvial network. The loss of taxa from co-occurrence networks demonstrates that the removal of gatekeepers disproportionately contributed to network fragmentation, which has potential implications for the functions biofilms fulfill in stream ecosystems. Our findings are critical because of increased anthropogenic pressures deteriorating stream ecosystem integrity and biodiversity.
| S-EPMC4156742 | biostudies-literature
Project description:BackgroundMicrobial interactions shape the structure and function of microbial communities; microbial co-occurrence networks in specific environments have been widely developed to explore these complex systems, but their interconnection pattern across microbiomes in various environments at the global scale remains unexplored. Here, we have inferred an Earth microbial co-occurrence network from a communal catalog with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset.ResultsThis non-random scale-free Earth microbial co-occurrence network consisted of 8 taxonomy distinct modules linked with different environments, which featured environment specific microbial co-occurrence relationships. Different topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct co-occurrence patterns in the microbiomes of various environments. The high number of specialist edges highlights that environmental specific co-occurrence relationships are essential features across microbiomes. The microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identified as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche differentiation. Video abstract CONCLUSION: This investigation highlights the interconnection patterns across microbiomes in various environments and emphasizes the importance of understanding co-occurrence feature of microbiomes from a network perspective.
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Project description:Soil microbial community is a complex blackbox that requires a multi-conceptual approach (Hultman et al., 2015; Bastida et al., 2016). Most methods focus on evaluating total microbial community and fail to determine its active fraction (Blagodatskaya & Kuzyakov 2013). This issue has ecological consequences since the behavior of the active community is more important (or even essential) and can be different to that of the total community. The sensitivity of the active microbial community can be considered as a biological mechanism that regulates the functional responses of soil against direct (i.e. forest management) and indirect (i.e. climate change) human-induced alterations. Indeed, it has been highglihted that the diversity of the active community (analyzed by metaproteomics) is more connected to soil functionality than the that of the total community (analyzed by 16S rRNA gene and ITS sequencing) (Bastida et al., 2016). Recently, the increasing application of soil metaproteomics is providing unprecedented, in-depth characterisation of the composition and functionality of active microbial communities and overall, allowing deeper insights into terrestrial microbial ecology (Chourey et al., 2012; Bastida et al., 2015, 2016; Keiblinger et al., 2016). Here, we predict the responsiveness of the soil microbial community to forest management in a climate change scenario. Particularly, we aim: i) to evaluate the impacts of 6-years of induced drought on the diversity, biomass and activity of the microbial community in a semiarid forest ecocosystem; and ii) to discriminate if forest management (thinning) influences the resistance of the microbial community against induced drought. Furthermore, we aim to ascertain if the functional diversity of each phylum is a trait that can be used to predict changes in microbial abundance and ecosystem functioning.
2021-02-02 | PXD005447 | Pride
Project description:Compost and biochar are beneficial soil amendments which derived from agricultural waste, and their application was proven to be effective practices for promoting soil fertility. Arbuscular mycorrhizal (AM) fungi form symbiotic associations with most crop plant species, and are recognized as one group of the most important soil microorganisms to increase food security in sustainable agriculture. To understand the legacy effects of compost and biochar addition on AM fungal communities, a field study was conducted on the Songnen Plain, Northeast China. Two years after application, compost addition improved soil aggregate stability, but we did not detect a legacy effect of compost addition on AM fungal community. Our results indicated that AM fungal Shannon diversity and Pielou evenness indices were significantly increased by one-time biochar addition, but unaffected by compost addition after two year's application. PERMANOVA analysis also revealed a legacy effect of biochar addition on AM fungal community. Network analysis revealed a dramatically simplified AM fungal co-occurrence network and small network size in biochar added soils, demonstrated by their topological properties (e.g., low connectedness and betweenness). However, AM fungal community did not differ among aggregate fractions, as confirmed by the PERMANOVA analysis as well as the fact that only a small number of AM fungal OTUs were shared among aggregate fractions. Consequently, the current study highlights a stronger legacy effect of biochar than compost addition on AM fungi, and have implications for agricultural practices.
| S-EPMC9692858 | biostudies-literature