14,974 research outputs found

    Toward a Census of Bacteria in Soil

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    For more than a century, microbiologists have sought to determine the species richness of bacteria in soil, but the extreme complexity and unknown structure of soil microbial communities have obscured the answer. We developed a statistical model that makes the problem of estimating richness statistically accessible by evaluating the characteristics of samples drawn from simulated communities with parametric community distributions. We identified simulated communities with rank-abundance distributions that followed a truncated lognormal distribution whose samples resembled the structure of 16S rRNA gene sequence collections made using Alaskan and Minnesotan soils. The simulated communities constructed based on the distribution of 16S rRNA gene sequences sampled from the Alaskan and Minnesotan soils had a richness of 5,000 and 2,000 operational taxonomic units (OTUs), respectively, where an OTU represents a collection of sequences not more than 3% distant from each other. To sample each of these OTUs in the Alaskan 16S rRNA gene library at least twice, 480,000 sequences would be required; however, to estimate the richness of the simulated communities using nonparametric richness estimators would require only 18,000 sequences. Quantifying the richness of complex environments such as soil is an important step in building an ecological framework. We have shown that generating sufficient sequence data to do so requires less sequencing effort than completely sequencing a bacterial genome

    Geogenomic segregation and temporal trends of human pathogenic Escherichia coli o157:H7, Washington, USA, 2005-2014

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    The often-noted and persistent increased incidence of Escherichia coli O157:H7 infections in rural areas is not well understood. We used a cohort of E. coli O157:H7 cases reported in Washington, USA, during 2005–2014, along with phylogenomic characterization of the infecting isolates, to identify geographic segregation of and temporal trends in specific phylogenetic lineages of E. coli O157:H7. Kernel estimation and generalized additive models demonstrated that pathogen lineages were spatially segregated during the period of analysis and identified a focus of segregation spanning multiple, predominantly rural, counties for each of the main clinical lineages, Ib, IIa, and IIb. These results suggest the existence of local reservoirs from which humans are infected. We also noted a secular increase in the proportion of lineage IIa and IIb isolates. Spatial segregation by phylogenetic lineage offers the potential to identify local reservoirs and intervene to prevent continued transmission

    Global marine bacterial diversity peaks at high latitudes in winter.

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    Genomic approaches to characterizing bacterial communities are revealing significant differences in diversity and composition between environments. But bacterial distributions have not been mapped at a global scale. Although current community surveys are way too sparse to map global diversity patterns directly, there is now sufficient data to fit accurate models of how bacterial distributions vary across different environments and to make global scale maps from these models. We apply this approach to map the global distributions of bacteria in marine surface waters. Our spatially and temporally explicit predictions suggest that bacterial diversity peaks in temperate latitudes across the world's oceans. These global peaks are seasonal, occurring 6 months apart in the two hemispheres, in the boreal and austral winters. This pattern is quite different from the tropical, seasonally consistent diversity patterns observed for most macroorganisms. However, like other marine organisms, surface water bacteria are particularly diverse in regions of high human environmental impacts on the oceans. Our maps provide the first picture of bacterial distributions at a global scale and suggest important differences between the diversity patterns of bacteria compared with other organisms

    Drought Stress Results in a Compartment-Specific Restructuring of the Rice Root-Associated Microbiomes.

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    Plant roots support complex microbial communities that can influence plant growth, nutrition, and health. While extensive characterizations of the composition and spatial compartmentalization of these communities have been performed in different plant species, there is relatively little known about the impact of abiotic stresses on the root microbiota. Here, we have used rice as a model to explore the responses of root microbiomes to drought stress. Using four distinct genotypes, grown in soils from three different fields, we tracked the drought-induced changes in microbial composition in the rhizosphere (the soil immediately surrounding the root), the endosphere (the root interior), and unplanted soils. Drought significantly altered the overall bacterial and fungal compositions of all three communities, with the endosphere and rhizosphere compartments showing the greatest divergence from well-watered controls. The overall response of the bacterial microbiota to drought stress was taxonomically consistent across soils and cultivars and was primarily driven by an enrichment of multiple Actinobacteria and Chloroflexi, as well as a depletion of several Acidobacteria and Deltaproteobacteria While there was some overlap in the changes observed in the rhizosphere and endosphere communities, several drought-responsive taxa were compartment specific, a pattern likely arising from preexisting compositional differences, as well as plant-mediated processes affecting individual compartments. These results reveal that drought stress, in addition to its well-characterized effects on plant physiology, also results in restructuring of root microbial communities and suggest the possibility that constituents of the altered plant microbiota might contribute to plant survival under extreme environmental conditions.IMPORTANCE With the likelihood that changes in global climate will adversely affect crop yields, the potential role of microbial communities in enhancing plant performance makes it important to elucidate the responses of plant microbiomes to environmental variation. By detailed characterization of the effect of drought stress on the root-associated microbiota of the crop plant rice, we show that the rhizosphere and endosphere communities undergo major compositional changes that involve shifts in the relative abundances of a taxonomically diverse set of bacteria in response to drought. These drought-responsive microbes, in particular those enriched under water deficit conditions, could potentially benefit the plant as they could contribute to tolerance to drought and other abiotic stresses, as well as provide protection from opportunistic infection by pathogenic microbes. The identification and future isolation of microbes that promote plant tolerance to drought could potentially be used to mitigate crop losses arising from adverse shifts in climate

    Robust estimation of microbial diversity in theory and in practice

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    Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity.Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figure

    Recovery of Agricultural Nutrients from Biorefineries

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    This review lays the foundation for why nutrient recovery must be a key consideration in design and operation of biorefineries and comprehensively reviews technologies that can be used to recover an array of nitrogen, phosphorus, and/or potassium-rich products of relevance to agricultural applications. Recovery of these products using combinations of physical, chemical, and biological operations will promote sustainability at biorefineries by converting low-value biomass (particularly waste material) into a portfolio of higher-value products. These products can include a natural partnering of traditional biorefinery outputs such as biofuels and chemicals together with nutrient-rich fertilizers. Nutrient recovery not only adds an additional marketable biorefinery product, but also avoids the negative consequences of eutrophication, and helps to close anthropogenic nutrient cycles, thereby providing an alternative to current unsustainable approaches to fertilizer production, which are energy-intensive and reliant on nonrenewable natural resource extraction

    Spartan Daily, February 26, 1980

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    Volume 74, Issue 18https://scholarworks.sjsu.edu/spartandaily/6585/thumbnail.jp
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