Relevant bibliographies by topics / Microbial community structure

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Microbial community structure'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Microbial community structure"

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Peralta, Ariane L., Jeffrey W. Matthews, and Angela D. Kent. "Microbial Community Structure and Denitrification in a Wetland Mitigation Bank." Applied and Environmental Microbiology 76, no. 13 (May 7, 2010): 4207–15. http://dx.doi.org/10.1128/aem.02977-09.

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ABSTRACT 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.
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Okita, Noriko, Toshihiro Hoaki, Sinya Suzuki, and Masashi Hatamoto. "Characteristics of Microbial Community Structure at the Seafloor Surface of the Nankai Trough." Journal of Pure and Applied Microbiology 13, no. 4 (December 30, 2019): 1917–28. http://dx.doi.org/10.22207/jpam.13.4.04.

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Cheng, C., D. Zhao, D. Lv, S. Li, and G. Du. "Comparative study on microbial community structure across orchard soil, cropland soil, and unused soil." Soil and Water Research 12, No. 4 (October 9, 2017): 237–45. http://dx.doi.org/10.17221/177/2016-swr.

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We examined the effects of three different soil conditions (orchard soil, cropland soil, unused soil) on the functional diversity of soil microbial communities. The results first showed that orchard and cropland land use significantly changed the distribution and diversity of soil microbes, particularly at surface soil layers. The richness index (S) and Shannon diversity index (H) of orchard soil microbes were significantly higher than the indices of the cropland and unused soil treatments in the 0–10 cm soil layer, while the S and H indices of cropland soil microbes were the highest in 10–20 cm soil layers. Additionally, the Simpson dominance index of cropland soil microbial communities was the highest across all soil layers. Next, we found that carbon source differences in soil layers under the three land use conditions can mainly be attributed to their carbohydrate and polymer composition, indicating that they are the primary cause of the functional differences in microbial communities under different land uses. In conclusion, orchard and cropland soil probably affected microbial distribution and functional diversity due to differences in vegetation cover, cultivation, and management measures.
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Pérez-Brandán, C., J. Huidobro, M. Galván, S. Vargas-Gil, and Meriles JM. "Relationship between microbial functions and community structure following agricultural intensification in South American Chaco." Plant, Soil and Environment 62, No. 7 (July 24, 2016): 321–28. http://dx.doi.org/10.17221/19/2016-pse.

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Findlay, Robert H., Christine Yeates, Meredith A. J. Hullar, David A. Stahl, and Louis A. Kaplan. "Biome-Level Biogeography of Streambed Microbiota." Applied and Environmental Microbiology 74, no. 10 (March 31, 2008): 3014–21. http://dx.doi.org/10.1128/aem.01809-07.

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ABSTRACT A field study was conducted to determine the microbial community structures of streambed sediments across diverse geographic and climatic areas. Sediment samples were collected from three adjacent headwater forest streams within three biomes, eastern deciduous (Pennsylvania), southeastern coniferous (New Jersey), and tropical evergreen (Guanacaste, Costa Rica), to assess whether there is biome control of stream microbial community structure. Bacterial abundance, microbial biomass, and bacterial and microbial community structures were determined using classical, biochemical, and molecular methods. Microbial biomass, determined using phospholipid phosphate, was significantly greater in the southeastern coniferous biome, likely due to the smaller grain size, higher organic content, and lower levels of physical disturbance of these sediments. Microbial community structure was determined using phospholipid fatty acid (PLFA) profiles and bacterial community structure from terminal restriction fragment length polymorphism and edited (microeukaryotic PLFAs removed) PLFA profiles. Principal component analysis (PCA) was used to investigate patterns in total microbial community structure. The first principal component separated streams based on the importance of phototrophic microeukaryotes within the community, while the second separated southeastern coniferous streams from all others based on increased abundance of fungal PLFAs. PCA also indicated that within- and among-stream variations were small for tropical evergreen streams and large for southeastern coniferous streams. A similar analysis of bacterial community structure indicated that streams within biomes had similar community structures, while each biome possessed a unique streambed community, indicating strong within-biome control of stream bacterial community structure.
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Tankere, S. P. C., D. G. Bourne, F. L. L. Muller, and V. Torsvik. "Microenvironments and microbial community structure in sediments." Environmental Microbiology 4, no. 2 (February 2002): 97–105. http://dx.doi.org/10.1046/j.1462-2920.2002.00274.x.

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Bach, Lisbet Holm, John-Arvid Grytnes, Rune Halvorsen, and Mikael Ohlson. "Tree influence on soil microbial community structure." Soil Biology and Biochemistry 42, no. 11 (November 2010): 1934–43. http://dx.doi.org/10.1016/j.soilbio.2010.07.002.

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SCHIMEL, JOSHUA P., and JAY GULLEDGE. "Microbial community structure and global trace gases." Global Change Biology 4, no. 7 (October 1998): 745–58. http://dx.doi.org/10.1046/j.1365-2486.1998.00195.x.

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Fuhrman, Jed A. "Microbial community structure and its functional implications." Nature 459, no. 7244 (May 2009): 193–99. http://dx.doi.org/10.1038/nature08058.

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Gao, Yang, Xiuwei Wang, Zijun Mao, Liu Yang, Zhiyan Jiang, Xiangwei Chen, and Doug P. Aubrey. "Changes in Soil Microbial Community Structure Following Different Tree Species Functional Traits Afforestation." Forests 12, no. 8 (July 30, 2021): 1018. http://dx.doi.org/10.3390/f12081018.

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The soil microbial community structure is critical to the cycling of carbon and nitrogen in forest soils. As afforestation practices increasingly promote different functional traits of tree species, it has become critical to understand how they influence soil microbial community structures, which directly influence soil biogeochemical processes. We used fungi ITS and bacteria 16S rDNA to investigate soil microbial community structures in three monoculture plantations consisting of a non-native evergreen conifer (Pinus sibirica), a native deciduous conifer (Larix gmelinii), and a native deciduous angiosperm (Betula platyphylla) and compared them with two 1:1 mixed-species plantations (P. sibirica and L. gmelinii, P. sibirica and B. platyphylla). The fungal community structure of the conifer–angiosperm mixed plantation was similar to that of the non-native evergreen conifer, and the bacterial community structure was similar to that of the angiosperm monoculture plantation. Fungal communities were strongly related to tree species, but bacterial communities were strongly related to soil nitrogen. The co-occurrence networks were more robust in the mixed plantations, and the microbial structures associated with soil carbon and nitrogen were significantly increased. Our results provide a comparative study of the soil microbial ecology in response to afforestation of species with different functional traits and enhance the understanding of factors controlling the soil microbial community structure.
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Dissertations / Theses on the topic "Microbial community structure"

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Friedman, Jonathan Ph D. Massachusetts Institute of Technology. "Microbial adaptation, differentiation, and community structure." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81751.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Computational and Systems Biology Program, 2013.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 112-119).
Microbes play a central role in diverse processes ranging from global elemental cycles to human digestion. Understanding these complex processes requires a rm under- standing of the interplay between microbes and their environment. In this thesis, we utilize sequencing data to study how individual species adapt to different niches, and how species assemble to form communities. First, we study the potential temperature and salinity range of 16 marine Vibrio strains. We nd that salinity tolerance is at odds with the strains' natural habitats, and provide evidence that this incongruence may be explained by a molecular coupling between salinity and temperature tolerance. Next, we investigate the genetic basis of bacterial ecological differentiation by analyzing the genomes of two closely related, yet ecologically distinct populations of Vibrio splendidus. We nd that most loci recombine freely across habitats, and that ecological differentiation is likely driven by a small number of habitat-specic alle-les. We further present a model for bacterial sympatric speciation. Our simulations demonstrate that a small number of adaptive loci facilitates speciation, due to the op- posing roles horizontal gene transfer (HGT) plays throughout the speciation process: HGT initially promotes speciation by bringing together multiple adaptive alleles, but later hinders it by mixing alleles across habitats. Finally, we introduce two tools for analyzing genomic survey data: SparCC, which infers correlations between taxa from relative abundance data; and StrainFinder, which extracts strain-level information from metagenomic data. Employing these tools, we infer a rich ecological network connecting hundreds of interacting species across 18 sites on the human body, and show that 16S-defined groups are rarely composed of a single dominant strain.
by Jonathan Friedman.
Ph.D.
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2

Hagley, Karen Jane. "Microbial community structure in sports turf soils." Thesis, Royal Holloway, University of London, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.402548.

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Datta, Manoshi Sen. "Microbial community structure and dynamics on patchy landscapes." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/104464.

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Thesis: Ph. D., Massachusetts Institute of Technology, Computational and Systems Biology Program, 2016.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 139-156).
Microbes are tiny metabolic engines with large-scale effects on industry, the environment, and human health. Understanding how the micron-scale actions (and interactions) of individual microbes give rise to macro-scale consequences remains a major challenge in microbial ecology. However, for the most part, studies employ coarsegrained sampling schemes, which average over the heterogeneous microscopic structure of microbial communities. This has limited our ability to establish mechanistic links between dynamics occurring across these disparate spatial scales. However, such links are critical for (a) making sense of the tremendous extant microbial diversity on Earth, and (b) predicting how perturbations (e.g., global climate change) may influence microbial diversity and function. In this thesis, I characterize the structure and dynamics of wild bacterial populations in the ocean at spatial scales of tens of microns. I then employ a simple, two-strain laboratory model system to link (cooperative) inter-species interactions at local scales to emergent properties at larger scales, focusing on spatially connected meta-communities undergoing range expansions into new territory. This work encompasses diverse environments (ranging from well-mixed communities in the laboratory to individual crustaceans) and approaches (including mathematical modeling, highthroughput sequencing, and traditional microbiological experiments). Altogether, we find that the microscale environment inhabited by a microbe - that is, "what the neighborhood is like" and "who lives next to whom" - shapes the structure and dynamics of wild microbial populations at local scales. Moreover, these local interactions can drive patterns of biodiversity and function, even at spatial scales much larger than the length of an individual cell. Thus, our work represents a small step toward developing mechanistic theories for how microbes shape our planet's ecosystems.
by Manoshi Sen Datta.
Ph. D.
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Ries, Mackenzie Lynn. "The Effect of Salinity on Soil Microbial Community Structure." Thesis, North Dakota State University, 2020. https://hdl.handle.net/10365/31807.

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Soil salinity is a widespread problem that affects crop productivity. We expect that saline soils also have altered microbial community structure, soil food webs and related soil properties. To test this, we sampled field soils across four farms in eastern North Dakota that host salinity gradients. We evaluated microbial biomass carbon, phospholipid fatty acid analysis and nematode counts in moderately saline and low saline soils. Additionally, we measured soil properties that represent potential food sources and habitat characteristics that influence microbial communities. We found higher microbial group abundance in moderately saline soils than in the lower saline soils. In contrast, we found lower nematode abundances in the moderately saline soils. We also observed increased labile carbon, nitrogen, phosphorus, and water content in the moderately saline soils. Based on our results, saline soils appear to have unique soil biological characteristics, which have implications for overall soil function along salinity gradients.
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Sudini, Hari Kishan Huettel Robin Norton. "Soil microbial community structure and aflatoxin contamination of peanuts." Auburn, Ala., 2009. http://hdl.handle.net/10415/1875.

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Van, Blerk Gerhardus Nicolas. "Microbial community structure and dynamics within sulphate- removing bioreactors." Diss., Pretoria : [s.n.], 2009. http://upetd.up.ac.za/thesis/available/etd-08122009-132505.

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Higgins, Logan Massie. "Insights into microbial community structure from pairwise interaction networks." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/113465.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biology, 2017
Cataloged from PDF version of thesis.
Includes bibliographical references.
Microbial communities are typically incredibly diverse, with many species contributing to the overall function of the community. The structure of these communities is the result of many complex biotic and abiotic factors. In this thesis, my colleagues and I employ a bottom-up approach to investigate the role of interspecies interactions in determining the structure of multispecies communities. First, we investigate the network of pairwise competitive interactions in a model community consisting of 20 strains of naturally co-occurring soil bacteria. The resulting interaction network is strongly hierarchical and lacks significant non-transitive motifs, a result that is robust across multiple environments. Multispecies competitions resulted in extinction of all but the most highly competitive strains, indicating that higher order interactions do not play a major role in structuring this community.
Given the lack of non-transitivity and higher order interactions in vitro, we conclude that other factors such as temporal or spatial heterogeneity must be at play in determining the ability of these strains to coexist in nature. Next, we propose a simple, qualitative assembly rule that predicts community structure from the outcomes of competitions between small sets of species, and experimentally assess its predictive power using synthetic microbial communities composed of up to eight soil bacterial species. Nearly all competitions resulted in a unique, stable community, whose composition was independent of the initial species fractions. Survival in three-species competitions was predicted by the pairwise outcomes with an accuracy of ~90%. Obtaining a similar level of accuracy in competitions between sets of seven or all eight species required incorporating additional information regarding the outcomes of the three-species competitions.
These results demonstrate experimentally the ability of a simple bottom-up approach to predict the structure of communities and illuminate the factors that determine their composition.
by Logan Massie Higgins.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Biology
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Moynihan, Emma Louise. "Interactions between microbial community structure and pathogen survival in soil." Thesis, Cranfield University, 2012. http://dspace.lib.cranfield.ac.uk/handle/1826/7297.

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Manure and slurry are valuable resources that may enhance many soil properties. However, organic amendments can pose a significant health risk to both humans and livestock if not managed correctly due to pathogenic loads that may be carried within them. Therefore it is crucial to identify the factors that affect pathogen survival in soil, in order to gain maximum benefit from such resources, whilst minimising the threat to public and animal welfare. This research aimed to elucidate the impact of microbial community structure on pathogen decline following entry of such organisms into the soil. It was hypothesised that pathogen survival would be significantly influenced by both diversity and phenotypic configuration of the microbial community. This was experimentally investigated within three distinctly different biological contexts. Firstly, it was shown that the survival of Escherichia coli 0157 was significantly affected by the presence of an intact microbial community. Microcosms consisting of sterile and non-sterile sand and clay soils were inoculated with E. coli and destructively sampled over time. The pathogen remained stable at 4°C, irrespective of biological status. However at 18°C, the pathogen grew in sterile soil and declined in non-sterile soil. This result was attributed to microbial antagonism in non-sterile soil, which only became apparent at 18°C, due to increased metabolic activity of the native community. The next experiment was designed to investigate the impact of microbial diversity and community configuration on the survival of a suite of model pathogens. A gradient of community complexity was created by inoculation of gamma-irradiated soil mesocosms with a serial-dilution of a suspension of a field soil. Soils were incubated to allow biomass equilibration and the establishment of distinct community phenotypes. Sub-samples were then inoculated with Listeria, Salmonella and E. coli strains and survival was monitored over 160 days. Death rates were calculated and plotted as a function of dilution, which represented diversity, and of principal component (PC) scores from PLFA profiles, which represented the phenotypic community context. There was some evidence of a diversity effect as weak negative linear correlations were observed between death rate and dilution for S. Dublin and environmentally-persistent E. coli. However, a much stronger correlation was observed between death rate and certain PC scores for these organisms. No effect of diversity or phenotype was detected on either L. monocytogenes or E. coli 0157. These results suggest that pathogen survival was affected by diversity, but the phenotypic community context was apparently much more influential. Additionally, such community effects were specific to pathogen type. Pathogen survival was also investigated in the context of highly-contrasting communities within a range of naturally-derived field soils. PLFA analysis was used to determine phenotypic community structure and soils were also characterized for a range of physico-chemical properties. They were inoculated with Listeria, Salmonella and E. coli strains as above. Pathogen survival was monitored over 110 days and death rates were calculated. Physicochemical and biotic data, including PC scores derived from PLFA profiles, were used in stepwise regression analysis to determine the predominant factor influencing pathogen-specific death rates. PC scores were identified as the most significant factor in pathogen decay for all organisms tested, with the exception of an environmentally-persistent E. coli isolate. Overall, these results demonstrate the importance of soil biological quality, specifically the configuration of the microbial community, in pathogen suppression, and provide a possible means to assess the inherent potential of soils to regulate pathogen survival. This may lead to the identification of management strategies which will ultimately accelerate pathogen decay, and therefore improve the safety of agricultural practice.
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Durno, W. Evan. "Precise correlation and metagenomic binning uncovers fine microbial community structure." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62360.

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Bacteria and Archaea represent the invisible majority of living things on Earth with an estimated numerical abundance exceeding 10^30 cells. This estimate surpasses the number of grains of sand on Earth and stars in the known universe. Interdependent microbial communities drive fluxes of matter and energy underlying biogeochemical processes, and provide essential ecosystem functions and services that help create the operating conditions for life. Despite their abundance and functional imperative, the vast majority of microorganisms remain uncultivated in laboratory settings, and therefore remain extremely difficult to study. Recent advances in high-throughput sequencing are opening a multi-omic (DNA and RNA) window to the structure and function of microbial communities providing new insights into coupled biogeochemical cycling and the metabolic problem solving power of otherwise uncultivated microbial dark matter (MDM). These technological advances have created bottlenecks with respect to information processing, and innovative bioinformatics solutions are required to analyze immense biological data sets. This is particularly apparent when dealing with metagenome assembly, population genome binning, and network analysis. This work investigates combined use of single-cell amplifed genomes (SAGs) and metagenomes to more precisely construct population genome bins and evaluates the use of covariance matrix regularization methods to identify putative metabolic interdependencies at the population and community levels of organization. Applying dimensional reduction with principal components and a Gaussian mixture model to k-mer statistics from SAGs and metagenomes is shown to bin more precisely, and has been implemented as a novel pipeline, SAG Extrapolator (SAGEX). Also, correlation networks derived from small subunit ribosomal RNA gene sequences are shown to be more precisely inferred through regularization with factor analysis models applied via Gaussian copula. SAGEX and regularized correlation are applied toward 368 SAGs and 91 metagenomes, postulating populations’ metabolic capabilities via binning, and constraining interpretations via correlation. The application describes coupled biogeochemical cycling in low-oxygen waters. Use of SAGEX leverages SAGs’ deep taxonomic descriptions and metagenomes’ breadth, produces precise population genome bins, and enables metabolic reconstruction and analysis of population dynamics over time. Regularizing correlation networks overcomes a known analytic bottleneck based in precision limitations.
Science, Faculty of
Graduate
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Perez, Sarah Isa Esther. "Exploring microbial community structure and resilience through visualization and analysis of microbial co-occurrence networks." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/53928.

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Cultivation independent microbial ecology research relies on high throughput sequencing technologies and analytical methods to resolve the infinite diversity of microbial life on Earth. Microorganisms live in communities driven by genetic and metabolic processes as well as symbiotic relationships. Interconnected communities of microorganisms provide essential functions in natural and human engineered ecosystems. Modelling the community as an inter-connected system can give insight into the community's functional characteristics related to the biogeochemical processes it performs. Network science resolves associations between elements of structure to notions of function in a system and has been successfully applied to the study of microbial communities and other complex biological systems. Microbial co-occurrence networks are inferred from community composition data to resolve structural patterns related to ecological properties such as community resilience to disturbance and keystone species. However, the interpretation of global and local network properties from an ecological standpoint remains difficult due to the complexity of these systems creating a need for quantitative analytical methods and visualization techniques for co-occurrence networks. This thesis tackles the visualization and analytical challenges of modelling microbial community structure from a network science approach. First, Hive Panel Explorer, an interactive visualization tool, is developed to permit data driven exploration of topological and data association patterns in complex systems. The effectiveness of Hive Panel Explorer is validated by resolving known and novel patterns in a model biological network, the C. elegans connectome. Second, network structural robustness analysis methods are applied to study microbial communities from timber harvested forest soils from a North American longterm soil productivity study. Analyzing these geographically dispersed soils reveals biogeographic patterns of diversity and enables the discovery of conserved organizing principles shaping microbial community structure. The capacity of robustness analysis to identify key microbial community members as well as model shifts in community structure due to environmental change is demonstrated. Finally, this work provides insight into the relationship between microbes and their ecosystem, and characterizing this relationship can help us understand the organization of microbial communities, survey microbial diversity and harness its potential.
Science, Faculty of
Graduate
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Books on the topic "Microbial community structure"

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1959-, Allison D. G., and Society for General Microbiology, eds. Community structure and co-operation in biofilms. Cambridge, UK: Cambridge University Press, 2000.

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Edgerton, Deborah L. An investigation of the interrelationship between the microbial community and soil structure in soils disturbed by opencast mining.. London: University of East London, 1997.

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Nemergut, Diana Reid, Ashley Shade, and Cyrille Violle, eds. The causes and consequences of microbial community structure. Frontiers SA Media, 2015. http://dx.doi.org/10.3389/978-2-88919-361-5.

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Kirchman, David L. Community structure of microbes in natural environments. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789406.003.0004.

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Community structure refers to the taxonomic types of microbes and their relative abundance in an environment. This chapter focuses on bacteria with a few words about fungi; protists and viruses are discussed in Chapters 9 and 10. Traditional methods for identifying microbes rely on biochemical testing of phenotype observable in the laboratory. Even for cultivated microbes and larger organisms, the traditional, phenotype approach has been replaced by comparing sequences of specific genes, those for 16S rRNA (archaea and bacteria) or 18S rRNA (microbial eukaryotes). Cultivation-independent approaches based on 16S rRNA gene sequencing have revealed that natural microbial communities have a few abundant types and many rare ones. These organisms differ substantially from those that can be grown in the laboratory using cultivation-dependent approaches. The abundant types of microbes found in soils, freshwater lakes, and oceans all differ. Once thought to be confined to extreme habitats, Archaea are now known to occur everywhere, but are particularly abundant in the deep ocean, where they make up as much as 50% of the total microbial abundance. Dispersal of bacteria and other small microbes is thought to be easy, leading to the Bass Becking hypothesis that “everything is everywhere, but the environment selects.” Among several factors known to affect community structure, salinity and temperature are very important, as is pH especially in soils. In addition to bottom-up factors, both top-down factors, grazing and viral lysis, also shape community structure. According to the Kill the Winner hypothesis, viruses select for fast-growing types, allowing slower growing defensive specialists to survive. Cultivation-independent approaches indicate that fungi are more diverse than previously appreciated, but they are less diverse than bacteria, especially in aquatic habitats. The community structure of fungi is affected by many of the same factors shaping bacterial community structure, but the dispersal of fungi is more limited than that of bacteria. The chapter ends with a discussion about the relationship between community structure and biogeochemical processes. The value of community structure information varies with the process and the degree of metabolic redundancy among the community members for the process.
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Sutton, Susan Dee. Determinants of sedimentary microbial biomass and community structure in two temperate streams. 2000.

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Structure of Microbial Community in Soils Contaminated with Heavy Metals Assessed by Culture and Fatty Acid Approaches. Wydawnictwo Uniwersytetu Slaskiego, 2005.

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Book chapters on the topic "Microbial community structure"

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Garland, Jay L., K. L. Cook, C. A. Loader, and B. A. Hungate. "The Influence of Microbial Community Structure and Function on Community-Level Physiological Profiles." In Microbial Communities, 171–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60694-6_16.

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Schimel, J. "Ecosystem Consequences of Microbial Diversity and Community Structure." In Ecological Studies, 239–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-642-78966-3_17.

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Findlay, Robert H. "The use of phospholipid fatty acids to determine microbial community structure." In Molecular Microbial Ecology Manual, 77–93. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-009-0215-2_7.

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Nancy, Jaspreet Kaur Boparai, and Pushpender Kumar Sharma. "Metatranscriptomics: A Promising Tool to Depict Dynamics of Microbial Community Structure and Function." In Microbial Metatranscriptomics Belowground, 471–91. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-9758-9_22.

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Findlay, Robert H. "Section 4 update: Determination of microbial community structure using phospholipid fatty acid profiles." In Molecular Microbial Ecology Manual, 2885–906. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-2177-0_408.

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Rastogi, Gurdeep, and Rajesh K. Sani. "Molecular Techniques to Assess Microbial Community Structure, Function, and Dynamics in the Environment." In Microbes and Microbial Technology, 29–57. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-7931-5_2.

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Keegan, Kevin P., Elizabeth M. Glass, and Folker Meyer. "MG-RAST, a Metagenomics Service for Analysis of Microbial Community Structure and Function." In Microbial Environmental Genomics (MEG), 207–33. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3369-3_13.

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Ward, David M., Michael J. Ferris, Stephen C. Nold, Mary M. Bateson, Eric D. Kopczynski, and Alyson L. Ruff-Roberts. "Species diversity in hot spring microbial mats as revealed by both molecular and enrichment culture approaches — relationship between biodiversity and community structure." In Microbial Mats, 33–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-78991-5_3.

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van Nostrand, Joy D., Zhili He, and Jizhong Zhou. "GeoChip: A High-Throughput Metagenomics Technology for Dissecting Microbial Community Functional Structure." In Handbook of Molecular Microbial Ecology I, 507–19. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118010518.ch57.

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Artz, Rebekka R. E. "Microbial Community Structure and Carbon Substrate use in Northern Peatlands." In Carbon Cycling in Northern Peatlands, 111–29. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/2008gm000806.

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Conference papers on the topic "Microbial community structure"

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Davis, Madison C. "MICROBIAL COMMUNITY STRUCTURE OF A STRATIFIED ANCHIALINE SINKHOLE." In GSA Annual Meeting in Seattle, Washington, USA - 2017. Geological Society of America, 2017. http://dx.doi.org/10.1130/abs/2017am-300326.

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Sun, Juan, Ning Wang, Xiaoqing Yang, Xiuzhi Zheng, Zuxian Yu, and Tong Zhang. "Microbial Community Structure and Distribution Characteristics in Oil Contaminated Soil." In Goldschmidt2020. Geochemical Society, 2020. http://dx.doi.org/10.46427/gold2020.2500.

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He, Shuying, Jixiang Li, Yatong Xu, Erkun Hu, and Haizhen Yang. "Study on Microbial Community Structure of Immersed Biofilter in Urban River." In 2010 4th International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2010. http://dx.doi.org/10.1109/icbbe.2010.5515434.

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He, Shuying, Jixiang Li, and Yatong Xu. "Microbial Community Structure of Biological Contact Oxidation Process Used in Landscape River." In 2009 3rd International Conference on Bioinformatics and Biomedical Engineering (iCBBE). IEEE, 2009. http://dx.doi.org/10.1109/icbbe.2009.5163050.

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Shi, Xiang, Julia R. de Rezende, and Kenneth Sorbie. "Microbial Ecology Metrics to Assess the Effect of Biocide on Souring Control and Improve Souring Modelling." In SPE International Oilfield Corrosion Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205037-ms.

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Abstract Reservoir souring is a long-standing issue for the oil and gas industry caused by sulfate-reducing microorganisms (SRM) producing H2S from sulfate ions. In this work, we investigated the connections between the development of souring and the change in three key microbial ecology metrics: the abundance, alpha diversity and community structure of a souring microbiota under the biocide treatment of 100 ppm glutaraldehyde (henceforth referred to as GA). These are studied in sand-packed flow-through bioreactors during and after the biocide treatment using cutting-edge DNA assays. Our study suggests that the rebound of microbial sulfide production after the 100 ppm GA treatment is closely associated with the recovery in microbial abundance and microbial alpha diversity. The study also shows that 100 ppm GA treatment may lead to a measurable shift in the SRM community structure. By comparing the effluent microbial community with the sand microbial community, the study suggests that the change in alpha diversity of the produced water microbial community might be an early warning for the sulfide breakthrough due to souring recurrence in practice. This work explores the relationship between souring and the underlining microbial community behaviours in response to the 100 ppm GA treatment and, to characterise these changes, we propose measurable metrics. A conceptual model is also proposed describing the near-term biological process behind the biocide treatment-recovery cycle in a souring scenario. Finally, this work highlights the potential applications and caveats of harnessing the increasingly available field microbial community data for the improvement of souring modelling and field souring control strategies.
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Zhang, Qing, Guohua Chang, Tian-Peng Gao, Huyuan Zhang, and Haili Sun. "Microbial Community Structure Diversity in Different Sludge Used as Reducing Barrier for Tailings." In 2019 IEEE International Conference on Architecture, Construction, Environment and Hydraulics (ICACEH). IEEE, 2019. http://dx.doi.org/10.1109/icaceh48424.2019.9041841.

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Zhao, Wenjing, Qian Zhang, Zhongyu Du, Xiangyu Xu, and Zhenquan Li. "Variations in rhizosphere microbial community structure of bulrush in Wusong estuarine wetland, Shanghai." In 2018 7th International Conference on Energy, Environment and Sustainable Development (ICEESD 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/iceesd-18.2018.79.

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William C Rice, Amber M Mason, N Andy Cole, and R Nolan Clark. "The Influence of Feedlot Pen Surface Layers on Microbial Community Structure and Diversity." In International Symposium on Air Quality and Waste Management for Agriculture, 16-19 September 2007, Broomfield, Colorado. St. Joseph, MI: American Society of Agricultural and Biological Engineers, 2007. http://dx.doi.org/10.13031/2013.23907.

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"Novel archaeal metagenome assembled genomes from acidophilic microbial community of Parys Mountain copper mine (UK)." In Bioinformatics of Genome Regulation and Structure/ Systems Biology. institute of cytology and genetics siberian branch of the russian academy of science, Novosibirsk State University, 2020. http://dx.doi.org/10.18699/bgrs/sb-2020-136.

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Al-najjar, Mohammad, Artur Fink, Christopher Munday, Waleed Hamza, Ibrahim Al-ansari, Ismail Al-shaikh, Jan-berend Stuut, et al. "Effect Of Dust On The Microbial Community Structure And Function In The Arabian Gulf." In Qatar Foundation Annual Research Conference Proceedings. Hamad bin Khalifa University Press (HBKU Press), 2014. http://dx.doi.org/10.5339/qfarc.2014.eepp0541.

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Reports on the topic "Microbial community structure"

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Siebers, A., S. Singer, and M. Thelen. Analyzing the Structure and Function of Novel Cytochromes from a Natural Microbial Community. Office of Scientific and Technical Information (OSTI), August 2006. http://dx.doi.org/10.2172/900122.

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He, Zhili, Ye Deng, Joy Van Nostrand, Qichao Tu, Meiying Xu, Chris Hemme, Liyou Wu, et al. GeoChip 3.0: A High Throughput Tool for Analyzing Microbial Community, Composition, Structure, and Functional Activity. Office of Scientific and Technical Information (OSTI), May 2010. http://dx.doi.org/10.2172/986221.

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Balkwill, David L. Vadose zone microbial community structure and activity in metal/radionuclide contaminated sediments. Final technical report. Office of Scientific and Technical Information (OSTI), August 2002. http://dx.doi.org/10.2172/807073.

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Van Nostrand, Joy, P. Waldron, W. Wu, B. Zhou, Liyou Wu, Ye Deng, J. Carley, et al. Effects of Nitrate Exposure on the Functional Structure of a Microbial Community in a Uranium-contaminated Aquifer. Office of Scientific and Technical Information (OSTI), May 2010. http://dx.doi.org/10.2172/985928.

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Wong, S., C. Jeans, and M. Thelen. A Study of the Structure and Metabolic Processes of a Novel Membrane Cytochrome in an Extreme Microbial Community. Office of Scientific and Technical Information (OSTI), September 2006. http://dx.doi.org/10.2172/894351.

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Buckley, Daniel. Microbial food web mapping: linking carbon cycling and community structure in soils through pyrosequencing enabled stable isotope probing. Office of Scientific and Technical Information (OSTI), March 2015. http://dx.doi.org/10.2172/1172474.

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White, D. C., and D. B. Ringelberg. Signature lipid biomarkers for in situ microbial biomass, community structure and nutritional status of deep subsurface microbiota in relation to geochemical gradients. Final technical report. Office of Scientific and Technical Information (OSTI), February 1998. http://dx.doi.org/10.2172/578585.

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