11 research outputs found

    Soil bacterial diversity is associated with human population density in urban greenspaces

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    Author Posting. © The Author(s), 2018. This is the author's version of the work. It is posted here by permission of American Chemical Society for personal use, not for redistribution. The definitive version was published in Environmental Science and Technology 52 (2018): 5115–5124, doi:10.1021/acs.est.7b06417.Urban greenspaces provide extensive ecosystem services, including pollutant remediation, water management, carbon maintenance, and nutrient cycling. However, while the urban soil microbiota underpin these services, we still have limited understanding of the factors that influence their distribution. We characterized soil bacterial communities from turf-grasses associated with urban parks, streets and residential sites across a major urban environment, including a gradient of human population density. Bacterial diversity was significantly positively correlated with the population density; and species diversity was greater in park and street soils, compared to residential soils. Population density and greenspace type also led to significant differences in the microbial community composition that was also significantly correlated with soil pH, moisture and texture. Co-occurrence network analysis revealed that microbial guilds in urban soils were well correlated. Abundant soil microbes in high density population areas had fewer interactions, while abundant bacteria in high moisture soils had more interactions. These results indicate the significant influence of changes in urban demographics and land-use on soil microbial communities. As urbanization is rapidly growing across the planet, it is important to improve our understanding of the consequences of urban zoning on the soil microbiota.This study is supported by the Earth Microbiome Project (http://www.earthmicrobiome.org/) and the China Scholarship Council (http://en.csc.edu.cn/).2019-04-0

    Wheat rhizosphere harbors a less complex and more stable microbial co-occurrence pattern than bulk soil

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    © The Author(s), 2018. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Soil Biology and Biochemistry 125 (2018): 251-260, doi:10.1016/j.soilbio.2018.07.022.The rhizosphere harbors complex microbial communities, whose dynamic associations are considered critical for plant growth and health but remain poorly understood. We constructed co-occurrence networks for archaeal, bacterial and fungal communities associated with the rhizosphere and bulk soil of wheat fields on the North China Plain. Rhizosphere co-occurrence networks had fewer nodes, edges, modules and lower density, but maintained more robust structure compared with bulk soil, suggesting that a less complex topology and more stable co-occurrence pattern is a feature for wheat rhizosphere. Bacterial and fungal communities followed a power-law distribution, while the archaeal community did not. Soil pH and microbial diversity were significantly correlated with network size and connectivity in both rhizosphere and bulk soils. Keystone species that played essential roles in network structure were predicted to maintain a flexible generalist metabolism, and had fewer significant correlations with environmental variables, especially in the rhizosphere. These results indicate that distinct microbial co-occurrence patterns exist in wheat rhizosphere, which could be associated with variable agricultural ecosystem properties.This work was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB15010101) and the National Program on Key Basic Research Project (2014CB954002).2020-07-2

    Computing and applying atomic regulons to understand gene expression and regulation

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    The Supplementary Material for this article can be found online at: http://journal.frontiersin.org/article/10.3389/fmicb.2016.01819/full#supplementary-materialUnderstanding gene function and regulation is essential for the interpretation prediction and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets Atomic Regulons ARs represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here we describe an approach for inferring ARs that leverages large-scale expression data sets gene context and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness CLR analysis finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms we computed ARs for Shewanella oneidensis Pseudomonas aeruginosa Thermus thermophilus and Staphylococcus aureus each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain.JF acknowledges funding from [SFRH/BD/70824/2010] of the FCT (Portuguese Foundation for Science and Technology) PhD program. CH and PW were supported by the National Science Foundation under grant number EFRI-MIKS-1137089. RT was supported by the Genomic Science Program (GSP), Office of Biological and Environmental Research (OBER), U.S. Department of Energy(DOE),and his work is a contribution of the Pacific North west National Laboratory (PNNL) Foundational Scientific Focus Area. This work was partially supported by an award from the National Science Foundation to MD, AB, NT, and RO (NSFABI-0850546). This work was also supported by the United States National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Service [Contract No. HHSN272201400027C]

    Representing the function and sensitivity of coastal interfaces in earth system models

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    © The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ward, N. D., Megonigal, J. P., Bond-Lamberty, B., Bailey, V. L., Butman, D., Canuel, E. A., Diefenderfer, H., Ganju, N. K., Goni, M. A., Graham, E. B., Hopkinson, C. S., Khangaonkar, T., Langley, J. A., McDowell, N. G., Myers-Pigg, A. N., Neumann, R. B., Osburn, C. L., Price, R. M., Rowland, J., Sengupta, A., Simard, M., Thornton, P. E., Tzortziou, M., Vargas, R., Weisenhorn, P. B., & Windham-Myers, L. Representing the function and sensitivity of coastal interfaces in earth system models. Nature Communications, 11(1), (2020): 2458, doi:10.1038/s41467-020-16236-2.Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth’s climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface.Funding for this work was provided by Pacific Northwest National Laboratory (PNNL) Laboratory Directed Research & Development (LDRD) as part of the Predicting Ecosystem Resilience through Multiscale Integrative Science (PREMIS) Initiative. PNNL is operated by Battelle for the U.S. Department of Energy under Contract DE-AC05-76RL01830. Additional support to J.P.M. was provided by the NSF-LTREB program (DEB-0950080, DEB-1457100, DEB-1557009), DOE-TES Program (DE-SC0008339), and the Smithsonian Institution. This manuscript was motivated by discussions held by co-authors during a three-day workshop at PNNL in Richland, WA: The System for Terrestrial Aquatic Research (STAR) Workshop: Terrestrial-Aquatic Research in Coastal Systems. The authors thank PNNL artist Nathan Johnson for preparing the figures in this manuscript and Terry Clark, Dr. Charlette Geffen, and Dr. Nancy Hess for their aid in organizing the STAR workshop. The authors thank all workshop participants not listed as authors for their valuable insight: Lihini Aluwihare (contributed to biogeochemistry discussions and development of concept for Fig. 3), Gautam Bisht (contributed to modeling discussion), Emmett Duffy (contributed to observational network discussions), Yilin Fang (contributed to modeling discussion), Jeremy Jones (contributed to biogeochemistry discussions), Roser Matamala (contributed to biogeochemistry discussions), James Morris (contributed to biogeochemistry discussions), Robert Twilley (contributed to biogeochemistry discussions), and Jesse Vance (contributed to observational network discussions). A full report on the workshop discussions can be found at https://www.pnnl.gov/publications/star-workshop-terrestrial-aquatic-research-coastal-systems

    A communal catalogue reveals Earth’s multiscale microbial diversity

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    Our growing awareness of the microbial world’s importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth’s microbial diversity

    A communal catalogue reveals Earth's multiscale microbial diversity

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    Our growing awareness of the microbial world's importance and diversity contrasts starkly with our limited understanding of its fundamental structure. Despite recent advances in DNA sequencing, a lack of standardized protocols and common analytical frameworks impedes comparisons among studies, hindering the development of global inferences about microbial life on Earth. Here we present a meta-analysis of microbial community samples collected by hundreds of researchers for the Earth Microbiome Project. Coordinated protocols and new analytical methods, particularly the use of exact sequences instead of clustered operational taxonomic units, enable bacterial and archaeal ribosomal RNA gene sequences to be followed across multiple studies and allow us to explore patterns of diversity at an unprecedented scale. The result is both a reference database giving global context to DNA sequence data and a framework for incorporating data from future studies, fostering increasingly complete characterization of Earth's microbial diversity.Peer reviewe

    Substrate Utilization by Micrococcus Luteus: Biodegradation of Pyridine for Metabolic Modeling

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    The bacterium Micrococcus luteus was grown on three substrates: glucose, acetate, and pyridine; all maintained at a molar C: N ratio of 5:1 Optical density, pH measurements, substrate, and ammonium concentrations were monitored at regular intervals. The N-heterocycle pyridine is a by-product of coal gasification and oil shale that has high water solubility and mobility through the soil; leading to surface and groundwater contamination. M. luteus was able to grow on all substrates and riboflavin production was apparent in all treatments. Glucose, the most widely used energy reserve, produced acidic conditions during log phase growth, and supported the most biomass production. Acetate surprisingly produced alkaline conditions during log phase growth. Pyridine was oxidized for energy by M luteus and as the pyridine concentration decreased, the ammonium concentration increased. The ring N was released to the medium as ammonium or incorporated into biomass. M luteus utilized pyridine as a carbon, nitrogen, and energy source similar to glucose and acetate treatments amended with ammonium. The metabolism of N-heterocycles remains poorly understood, but with transcriptomic analysis and metabolic modeling, more information on the metabolic pathways of pyridine degradation can be obtained. More studies of this organism will be necessary to elucidate the degradative pathways for pyridine; which can lead to a better understanding of N-heterocycle-degrading microorganisms

    Responses of Microbial Communities to Hydrocarbon Exposures

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    The responses of microbial communities to hydrocarbon exposures are complex and variable, driven to a large extent by the nature of hydrocarbon infusion, local environmental conditions, and factors that regulate microbial physiology (e.g., substrate and nutrient availability). Although present at low abundance in the ocean, hydrocarbon-degrading seed populations are widely distributed, and they respond rapidly to hydrocarbon inputs at natural and anthropogenic sources. Microbiomes from environments impacted by hydrocarbon discharge may appear similar at a higher taxonomic rank (e.g., genus level) but diverge at increasing phylogenetic resolution (e.g., sub-OTU [operational taxonomic unit] levels). Such subtle changes are detectable by computational methods such as oligotyping or by genome reconstruction from metagenomic sequence data. The ability to reconstruct these genomes, and to characterize their transcriptional activities in different environmental contexts through metatranscriptomic mapping, is revolutionizing our ability to understand the diverse and adaptable microbial communities in marine ecosystems. Our knowledge of the environmental factors that regulate microbial hydrocarbon degradation and the efficiency with which marine hydrocarbon-degrading microbial communities bioremediate hydrocarbon contamination is incomplete. Moreover, detailed baseline descriptions of naturally occurring hydrocarbon-degrading microbial communities and a more robust understanding of the factors that regulate their activity are needed

    Responses of Microbial Communities to Hydrocarbon Exposures

    No full text
    The responses of microbial communities to hydrocarbon exposures are complex and variable, driven to a large extent by the nature of hydrocarbon infusion, local environmental conditions, and factors that regulate microbial physiology (e.g., substrate and nutrient availability). Although present at low abundance in the ocean, hydrocarbon-degrading seed populations are widely distributed, and they respond rapidly to hydrocarbon inputs at natural and anthropogenic sources. Microbiomes from environments impacted by hydrocarbon discharge may appear similar at a higher taxonomic rank (e.g., genus level) but diverge at increasing phylogenetic resolution (e.g., sub-OTU [operational taxonomic unit] levels). Such subtle changes are detectable by computational methods such as oligotyping or by genome reconstruction from metagenomic sequence data. The ability to reconstruct these genomes, and to characterize their transcriptional activities in different environmental contexts through metatranscriptomic mapping, is revolutionizing our ability to understand the diverse and adaptable microbial communities in marine ecosystems. Our knowledge of the environmental factors that regulate microbial hydrocarbon degradation and the efficiency with which marine hydrocarbon-degrading microbial communities bioremediate hydrocarbon contamination is incomplete. Moreover, detailed baseline descriptions of naturally occurring hydrocarbon-degrading microbial communities and a more robust understanding of the factors that regulate their activity are needed

    Metabolic Reconstruction and Modeling Microbial Electrosynthesis.

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    Microbial electrosynthesis is a renewable energy and chemical production platform that relies on microbial cells to capture electrons from a cathode and fix carbon. Yet despite the promise of this technology, the metabolic capacity of the microbes that inhabit the electrode surface and catalyze electron transfer in these systems remains largely unknown. We assembled thirteen draft genomes from a microbial electrosynthesis system producing primarily acetate from carbon dioxide, and their transcriptional activity was mapped to genomes from cells on the electrode surface and in the supernatant. This allowed us to create a metabolic model of the predominant community members belonging to Acetobacterium, Sulfurospirillum, and Desulfovibrio. According to the model, the Acetobacterium was the primary carbon fixer, and a keystone member of the community. Transcripts of soluble hydrogenases and ferredoxins from Acetobacterium and hydrogenases, formate dehydrogenase, and cytochromes of Desulfovibrio were found in high abundance near the electrode surface. Cytochrome c oxidases of facultative members of the community were highly expressed in the supernatant despite completely sealed reactors and constant flushing with anaerobic gases. These molecular discoveries and metabolic modeling now serve as a foundation for future examination and development of electrosynthetic microbial communities
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