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Background: Microbiome recruitment is influenced by plant host, but how host plant impacts the assembly, functions, and interactions of perennial plant root microbiomes is poorly understood. Here we examined prokaryotic and fungal communities between rhizosphere soils and the root endophytic compartment in two native Miscanthus species (Miscanthus sinensis and Miscanthus floridulus) of Taiwan and further explored the roles of host plant on root-associated microbiomes., Results: Our results suggest that host plant genetic variation, edaphic factors, and site had effects on the root endophytic and rhizosphere soil microbial community compositions in both Miscanthus sinensis and Miscanthus floridulus, with a greater effect of plant genetic variation observed for the root endophytic communities. Host plant genetic variation also exerted a stronger effect on core prokaryotic communities than on non-core prokaryotic communities in each microhabitat of two Miscanthus species. From rhizosphere soils to root endophytes, prokaryotic co-occurrence network stability increased, but fungal co-occurrence network stability decreased. Furthermore, we found root endophytic microbial communities in two Miscanthus species were more strongly driven by deterministic processes rather than stochastic processes. Root-enriched prokaryotic OTUs belong to Gammaproteobacteria, Alphaproteobacteria, Betaproteobacteria, Sphingobacteriia, and [Saprospirae] both in two Miscanthus species, while prokaryotic taxa enriched in the rhizosphere soil are widely distributed among different phyla., Conclusions: We provide empirical evidence that host genetic variation plays important roles in root-associated microbiome in Miscanthus. The results of this study have implications for future bioenergy crop management by providing baseline data to inform translational research to harness the plant microbiome to sustainably increase agriculture productivity. Video Abstract., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Variations in microbial communities promoted by alterations in environmental conditions are reflected in similarities/differences both at taxonomic and functional levels. Here we used a natural gradient within mangroves from seashore to upland, to contrast the natural variability in bacteria, cyanobacteria and diazotroph assemblages in a pristine area compared to an oil polluted area along a timespan of three years, based on ARISA (bacteria and cyanobacteria) and nifH T-RFLP (diazotrophs) fingerprinting. The data presented herein indicated that changes in all the communities evaluated were mainly driven by the temporal effect in the contaminated area, while local effects were dominant on the pristine mangrove. A positive correlation of community structure between diazotrophs and cyanobacteria was observed, suggesting the functional importance of this phylum as nitrogen fixers in mangroves soils. Different ecological patterns explained the microbial behavior in the pristine and polluted mangroves. Stochastic models in the pristine mangrove indicate that there is not a specific environmental factor that determines the bacterial distribution, while cyanobacteria and diazotrophs better fitted in deterministic model in the same area. For the contaminated mangrove site, deterministic models better represented the variations in the communities, suggesting that the presence of oil might change the microbial ecological structures over time. Mangroves represent a unique environment threatened by global change, and this study contributed to the knowledge of the microbial distribution in such areas and its response on persistent contamination historic events., (Copyright © 2017 Sociedade Brasileira de Microbiologia. Published by Elsevier Editora Ltda. All rights reserved.)

We established a four-biofilter setup to examine the effects of moisture content (MC) on biofilter performance, including NH3 removal and N2O generation. We hypothesized that MC increase can improve NH3 removal, stimulate N2O generation and alter the composition and function of microbial communities. We found that NH3 removal efficiency was greatly improved when MC increased from 35 to 55%, but further increasing MC to 63% did not help much; while N2O concentration was low at 35-55% MC, but dramatically increased at 63% MC. Decreasing MC from 63 to 55% restored N2O concentration. Examination of amoA communities using T-RFLP and real-time qPCR showed that the composition and abundance of ammonia oxidizers were not significantly changed in a "moisture disturbance-disturbance relief" process in which MC was increased from 55 to 63% and then reduced to 55%. This observation supported the changes of NH3 removal efficiency. The composition of nosZ community was altered at 63% MC and then was recovered at 55% MC, which indicates resilience to moisture disturbance. The abundance of nosZ community was negatively correlated with moisture content in this process, and the decreased nosZ abundance at 63% MC explained the observation of increased N2O concentration at that condition., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Denitrifying biofilters can remove agricultural nitrates from subsurface drainage, reducing nitrate pollution that contributes to coastal hypoxic zones. The performance and reliability of natural and engineered systems dependent upon microbially mediated processes, such as the denitrifying biofilters, can be affected by the spatial structure of their microbial communities. Furthermore, our understanding of the relationship between microbial community composition and function is influenced by the spatial distribution of samples.In this study we characterized the spatial structure of bacterial communities in a denitrifying biofilter in central Illinois. Bacterial communities were assessed using automated ribosomal intergenic spacer analysis for bacteria and terminal restriction fragment length polymorphism of nosZ for denitrifying bacteria.Non-metric multidimensional scaling and analysis of similarity (ANOSIM) analyses indicated that bacteria showed statistically significant spatial structure by depth and transect,while denitrifying bacteria did not exhibit significant spatial structure. For determination of spatial patterns, we developed a package of automated functions for the R statistical environment that allows directional analysis of microbial community composition data using either ANOSIM or Mantel statistics.Applying this package to the biofilter data, the flow path correlation range for the bacterial community was 6.4 m at the shallower, periodically in undated depth and 10.7 m at the deeper, continually submerged depth. These spatial structures suggest a strong influence of hydrology on the microbial community composition in these denitrifying biofilters. Understanding such spatial structure can also guide optimal sample collection strategies for microbial community analyses.

Shifts in the composition of dissolved organic matter (DOM) may be a principal factor effecting changes in bacterial community composition. Emerald Lake, a high-elevation lake with DOM dominated by terrestrial sources in the spring with increasing phytoplankton-derived inputs throughout the ice-free season, provided a natural experiment with which to investigate the importance of resource-mediated drivers. Glycolate-utilizing bacteria, a subset of the bacterial community able to use algal exudates, were characterized using DNA analysis of glycolate oxidase subunit D (glcD) genes from Emerald Lake samples collected approximately biweekly from ice-cover (June) through fall turnover (September). glcD genes were not detected in early-season samples when the lake was ice-covered and phytoplankton-derived resources were scarce. Following this period, glcD gene composition exhibited significant changes through time, which were strongly correlated with the combination of fluorescence index, an indicator of the proportion of lake vs. terrestrially derived DOM, and dissolved inorganic nitrate + nitrite. These results suggest that seasonal shifts in DOM source and environmental variables that affect the composition of algal-derived dissolved resources drive changes in the relative abundance and composition of putative glycolate-utilizing bacteria. These findings strengthen the evidence for shifts in DOM structuring bacterial communities., (© 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.)

Wetland mitigation is implemented to replace ecosystem functions provided by wetlands; however, restoration efforts frequently fail to establish equivalent levels of ecosystem services. Delivery of microbially mediated ecosystem functions, such as denitrification, is influenced by both the structure and activity of the microbial community. The objective of this study was to compare the relationship between soil and vegetation factors and microbial community structure and function in restored and reference wetlands within a mitigation bank. Microbial community composition was assessed using terminal restriction fragment length polymorphism targeting the 16S rRNA gene (total bacteria) and the nosZ gene (denitrifiers). Comparisons of microbial function were based on potential denitrification rates. Bacterial community structures differed significantly between restored and reference wetlands; denitrifier community assemblages were similar among reference sites but highly variable among restored sites throughout the mitigation bank. Potential denitrification was highest in the reference wetland sites. These data demonstrate that wetland restoration efforts in this mitigation bank have not successfully restored denitrification and that differences in potential denitrification rates may be due to distinct microbial assemblages observed in restored and reference (natural) wetlands. Further, we have identified gradients in soil moisture and soil fertility that were associated with differences in microbial community structure. Microbial function was influenced by bacterial community composition and soil fertility. Identifying soil factors that are primary ecological drivers of soil bacterial communities, especially denitrifying populations, can potentially aid the development of predictive models for restoration of biogeochemical transformations and enhance the success of wetland restoration efforts.

Two primer sets for automated ribosomal intergenic spacer analysis (ARISA) were used to assess the bacterial community composition (BCC) in Lake Mendota, Wisconsin, over 3 years. Correspondence analysis revealed differences in community profiles generated by different primer sets, but overall ecological patterns were conserved in each case. ARISA is a powerful tool for evaluating BCC change through space and time, regardless of the specific primer set used.

A previous multiyear study observed correlations between bacterioplankton community composition (BCC) and abundance and the dynamics of phytoplankton populations and bacterivorous grazers in a humic lake. These observations generated hypotheses about the importance of trophic interactions (both top-down and bottom-up) for structuring bacterial communities in this lake, which were tested using two multifactorial food web manipulation experiments that separately manipulated the intensity of grazing and the composition of the phytoplankton community. Our results, combined with field observations, suggest that a hierarchy of drivers structures bacterial communities in this lake. While other studies have noted links between aggregate measures of phytoplankton and bacterioplankton communities, we demonstrate here correlations between succession of phytoplankton assemblages and BCC as assessed by automated ribosomal intergenic spacer analysis (ARISA). We used a novel approach linking community ARISA data to phylogenetic assignments from sequence analysis of 16S rRNA gene clone libraries to examine the responses of specific bacterial phylotypes to the experimental manipulations. The synchronous dynamics of these populations suggests that primary producers may mediate BCC and diversity through labile organic matter production, which evolves in quality and quantity during phytoplankton succession. Superimposed on this resource-mediated control of BCC are brief periods of intense bacterivory that impact bacterial abundance and composition.

In an effort to better understand the factors contributing to patterns in freshwater bacterioplankton community composition and diversity, we coupled automated ribosomal intergenic spacer analysis (ARISA) to analysis of 16S ribosomal RNA (rRNA) gene sequences to follow the persistence patterns of 46 individual phylotypes over 3 years in Crystal Bog Lake. Additionally, we sought to identify linkages between the observed phylotype variations and known chemical and biological drivers. Sequencing of 16S rRNA genes obtained from the water column indicated the presence of phylotypes associated with the Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, TM7 and Verrucomicrobia phyla, as well as phylotypes with unknown affiliation. Employment of the 16S rRNA gene/ARISA method revealed that specific phylotypes varied independently of the entire bacterial community dynamics. Actinobacteria, which were present on greater than 95% of sampling dates, did not share the large temporal variability of the other identified phyla. Examination of phylotype relative abundance patterns (inferred using ARISA fragment relative fluorescence) revealed a strong correlation between the dominant phytoplankton succession and the relative abundance patterns of the majority of individual phylotypes. Further analysis revealed covariation among unique phylotypes, which formed several distinct bacterial assemblages correlated with particular phytoplankton communities. These data indicate the existence of unique persistence patterns for different common freshwater phylotypes, which may be linked to the presence of dominant phytoplankton species.

Despite considerable attention in recent years, the composition and dynamics of lake bacterial communities over annual time scales are poorly understood. This study used automated ribosomal intergenic spacer analysis (ARISA) to explore the patterns of change in lake bacterial communities in three temperate lakes over 2 consecutive years. The study lakes included a humic lake, an oligotrophic lake, and a eutrophic lake, and the epilimnetic bacterial communities were sampled every 2 weeks. The patterns of change in bacterial communities indicated that seasonal forces were important in structuring the behavior of the bacterial communities in each lake. All three lakes had relatively stable community composition in spring and fall, but summer changes were dramatic. Summertime variability was often characterized by recurrent drops in bacterial diversity. Specific ARISA fragments derived from these lakes were not constant among lakes or from year to year, and those fragments that did recur in lakes in different years did not exhibit the same seasonal pattern of recurrence. Nonetheless, seasonal patterns observed in 2000 were fairly successful predictors of the rate of change in bacterial communities and in the degree of autocorrelation of bacterial communities in 2001. Thus, seasonal forces may be important structuring elements of these systems as a whole even if they are uncoupled from the dynamics of the individual system components.

Culture-independent DNA fingerprints are commonly used to assess the diversity of a microbial community. However, relating species composition to community profiles produced by community fingerprint methods is not straightforward. Terminal restriction fragment length polymorphism (T-RFLP) is a community fingerprint method in which phylogenetic assignments may be inferred from the terminal restriction fragment (T-RF) sizes through the use of web-based resources that predict T-RF sizes for known bacteria. The process quickly becomes computationally intensive due to the need to analyze profiles produced by multiple restriction digests and the complexity of profiles generated by natural microbial communities. A web-based tool is described here that rapidly generates phylogenetic assignments from submitted community T-RFLP profiles based on a database of fragments produced by known 16S rRNA gene sequences. Users have the option of submitting a customized database generated from unpublished sequences or from a gene other than the 16S rRNA gene. This phylogenetic assignment tool allows users to employ T-RFLP to simultaneously analyze microbial community diversity and species composition. An analysis of the variability of bacterial species composition throughout the water column in a humic lake was carried out to demonstrate the functionality of the phylogenetic assignment tool. This method was validated by comparing the results generated by this program with results from a 16S rRNA gene clone library.

Since the first estimate of prokaryotic abundance in soil was published, researchers have attempted to assess the abundance and distribution of species and relate this information on community structure to ecosystem function. Culture-based methods were found to be inadequate to the task, and as a consequence a number of culture-independent approaches have been applied to the study of microbial diversity in soil. Applications of various culture-independent methods to descriptions of soil and rhizosphere microbial communities are reviewed. Culture-independent analyses have been used to catalog the species present in various environmental samples and also to assess the impact of human activity and interactions with plants or other microbes on natural microbial communities. Recent work has investigated the linkage of specific organisms to ecosystem function. Prospects for increased understanding of the ecological significance of particular populations through the use of genomics and microarrays are discussed.