scholarly journals How sample heterogeneity can obscure the signal of microbial interactions

2019 ◽  
Author(s):  
David W. Armitage ◽  
Stuart E. Jones
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Species Interactions ◽  
Dynamic Models ◽  
Spatial Scales ◽  
Microbial Interactions ◽  
Vital Rates ◽  
Ecological Processes ◽  
Correlation Networks ◽  
Community Data

ABSTRACTMicrobial community data are commonly subjected to computational tools such as correlation networks, null models, and dynamic models, with the goal of identifying the ecological processes structuring microbial communities. Researchers applying these methods assume that the signs and magnitudes of species interactions and vital rates can be reliably parsed from observational data on species’ (relative) abundances. However, we contend that this assumption is violated when sample units contain any underlying spatial structure. Here, we show how three phenomena — Simpson’s paradox, context-dependence, and nonlinear averaging — can lead to erroneous conclusions about population parameters and species interactions when samples contain heterogeneous mixtures of populations or communities. At the root of this issue is the fundamental mismatch between the spatial scales of species interactions (micrometres) and those of typical microbial community samples (millimetres to centimetres). These issues can be overcome by measuring and accounting for spatial heterogeneity at very small scales, which will lead to more reliable inference of the ecological mechanisms structuring natural microbial communities.

A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Environmental Remediation ◽  
Real Life ◽  
Design Principles ◽  
Microbial Interactions ◽  
Potential Applications ◽  
New Gene ◽  
Global Biogeochemical Cycles ◽  
Synthetic Microbial Communities

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

scholarly journals Local versus site-level effects of algae on coral microbial communities

2021 ◽  
Vol 8 (9) ◽  
pp. 210035
Author(s):  
Amy A. Briggs ◽  
Anya L. Brown ◽  
Craig W. Osenberg
Keyword(s):  
Microbial Communities ◽  
Spatial Scales ◽  
French Polynesia ◽  
Negative Effects ◽  
Ecological Processes ◽  
Antagonistic Effects ◽  
Alpha And Beta Diversity ◽  
Macroalgal Cover ◽  
Coral Microbiome ◽  
Turf Algae

Microbes influence ecological processes, including the dynamics and health of macro-organisms and their interactions with other species. In coral reefs, microbes mediate negative effects of algae on corals when corals are in contact with algae. However, it is unknown whether these effects extend to larger spatial scales, such as at sites with high algal densities. We investigated how local algal contact and site-level macroalgal cover influenced coral microbial communities in a field study at two islands in French Polynesia, Mo'orea and Mangareva. At 5 sites at each island, we sampled prokaryotic microbial communities (microbiomes) associated with corals, macroalgae, turf algae and water, with coral samples taken from individuals that were isolated from or in contact with turf or macroalgae. Algal contact and macroalgal cover had antagonistic effects on coral microbiome alpha and beta diversity. Additionally, coral microbiomes shifted and became more similar to macroalgal microbiomes at sites with high macroalgal cover and with algal contact, although the microbial taxa that changed varied by island. Our results indicate that coral microbiomes can be affected by algae outside of the coral's immediate vicinity, and local- and site-level effects of algae can obscure each other's effects when both scales are not considered.

scholarly journals OrtSuite – from genomes to prediction of microbial interactions within targeted ecosystem processes

2021 ◽  
Author(s):  
João Pedro Saraiva ◽  
Alexandre Bartholomäus ◽  
René Kallies ◽  
Marta Gomes ◽  
Marcos Bicalho ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Open Source Software ◽  
Species Interactions ◽  
Functional Annotation ◽  
Ecosystem Processes ◽  
Independent Study ◽  
Microbial Interactions ◽  
High Complexity ◽  
Benzoate Degradation ◽  
User Friendly

Abstract The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96 % of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. We evaluated the identification of putative synergistic species interactions using the sequenced genomes of an independent study that had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy-to-use workflow that allows for rapid functional annotation based on a user-curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known. OrtSuite is an open-source software available at https://github.com/mdsufz/OrtSuite.

scholarly journals Regular Biochar and Bacteria-Inoculated Biochar Alter the Composition of the Microbial Community in the Soil of a Chinese Fir Plantation

Forests ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 951
Author(s):  
Liguo Song ◽  
Lingyu Hou ◽  
Yongqiang Zhang ◽  
Zhichao Li ◽  
Wenzheng Wang ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Rhizosphere Soil ◽  
Soil Microbial Communities ◽  
Principal Component ◽  
Nutrient Content ◽  
Chinese Fir ◽  
Bulk Soil ◽  
Ecological Processes ◽  
Chinese Fir Plantation

Biochar is a promising material for the improvement of soil quality. However, studies on biochar have mostly been carried out in laboratory conditions or have focused on agricultural aspects. The impacts of the application of biochar on soil characteristics and related ecological processes of the forest ecosystem have not been fully resolved. In this study, we investigated the effects of regular biochar and bacteria-loaded biochar on the microbial communities in the bulk soil and the rhizosphere soil of an annual Chinese fir plantation. In early spring (April), the two types of biochar were added to the soil at the rates of 2.22 t·ha−1, 4.44 t·ha−1, 6.67 t·ha−1, 8.89 t·ha−1, and 11.11 t·ha−1 by ring furrow application around the seedlings, and soil samples were collected at the end of autumn (November). The results showed that biochar addition increased the soil nutrient content and promoted the growth and diversity of soil microbial communities. The diversity of soil fungi was significantly increased, and the diversity of soil bacteria was significantly decreased. Principal component analysis under the different biochar types and application rates demonstrated that microbial communities differed significantly between the treatments and controls and that the effect of biochar on the microbial community of the bulk soil was more significant than that of the rhizosphere soil. Under the same dosage, the effect of bacteria-loaded biochar on soil was more significant than that of regular biochar.

scholarly journals Mechanism Across Scales: A Holistic Modeling Framework Integrating Laboratory and Field Studies for Microbial Ecology

2021 ◽  
Vol 12 ◽  
Author(s):  
Lauren M. Lui ◽  
Erica L.-W. Majumder ◽  
Heidi J. Smith ◽  
Hans K. Carlson ◽  
Frederick von Netzer ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Microbial Ecology ◽  
High Throughput Sequencing ◽  
Spatial Scales ◽  
Data Types ◽  
Modeling Framework ◽  
Rapid Acquisition ◽  
Mechanistic Understanding ◽  
And Function

Over the last century, leaps in technology for imaging, sampling, detection, high-throughput sequencing, and -omics analyses have revolutionized microbial ecology to enable rapid acquisition of extensive datasets for microbial communities across the ever-increasing temporal and spatial scales. The present challenge is capitalizing on our enhanced abilities of observation and integrating diverse data types from different scales, resolutions, and disciplines to reach a causal and mechanistic understanding of how microbial communities transform and respond to perturbations in the environment. This type of causal and mechanistic understanding will make predictions of microbial community behavior more robust and actionable in addressing microbially mediated global problems. To discern drivers of microbial community assembly and function, we recognize the need for a conceptual, quantitative framework that connects measurements of genomic potential, the environment, and ecological and physical forces to rates of microbial growth at specific locations. We describe the Framework for Integrated, Conceptual, and Systematic Microbial Ecology (FICSME), an experimental design framework for conducting process-focused microbial ecology studies that incorporates biological, chemical, and physical drivers of a microbial system into a conceptual model. Through iterative cycles that advance our understanding of the coupling across scales and processes, we can reliably predict how perturbations to microbial systems impact ecosystem-scale processes or vice versa. We describe an approach and potential applications for using the FICSME to elucidate the mechanisms of globally important ecological and physical processes, toward attaining the goal of predicting the structure and function of microbial communities in chemically complex natural environments.

scholarly journals Rewiring of peatland plant-microbe networks outpaces species turnover

2020 ◽  
Author(s):  
Bjorn J.M. Robroek ◽  
Magalí Martí ◽  
Bo H. Svensson ◽  
Marc G. Dumont ◽  
Annelies J. Veraart ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Species Turnover ◽  
Ecosystem Processes ◽  
Microbial Interactions ◽  
Ecosystem Dynamics ◽  
Bipartite Networks ◽  
Ecological Processes ◽  
Network Composition ◽  
The Impact ◽  
Network Rewiring

AbstractEnviro-climatological changes are thought to be causing alterations in ecosystem processes through shifts in plant and microbial communities; however, how links between plant and microbial communities change with enviro-climatological change is likely to be less straightforward but may be fundamental for many ecological processes. To address this, we assessed the composition of the plant community and the prokaryotic community –using amplicon-based sequencing– of three European peatlands that were distinct in enviro-climatological conditions. Bipartite networks were used to construct site-specific plant-prokaryote co-occurrence networks. Our data show that between sites, plant and prokaryotic communities differ and that turnover in interactions between the communities was complex. Essentially, turnover in plant-microbial interactions is much faster than turnover in the respective communities. Our findings suggest that network rewiring does largely result from novel associations between species that are common and shared across the networks. Turnover in network composition is largely driven by novel interactions between a core community of plants and microorganisms. Taken together our results indicate that plant-microbe associations are context dependent, and that changes in enviro-climatological conditions will likely lead to network rewiring. Integrating turnover in plant-microbe interactions into studies that assess the impact of enviro-climatological change on peatland ecosystems is essential to understand ecosystem dynamics and must be combined with studies on the impact of these changes on ecosystem processes.

scholarly journals METABOLIC: High-throughput Profiling of Microbial Genomes for Functional Traits, Biogeochemistry, and Community-scale Metabolic Networks

2020 ◽  
Author(s):  
Zhichao Zhou ◽  
Patricia Q Tran ◽  
Adam M Breister ◽  
Yang Liu ◽  
Kristopher Kieft ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Microbial Ecology ◽  
Single Cell ◽  
Metabolic Networks ◽  
Biogeochemical Cycling ◽  
Microbial Interactions ◽  
Microbial Genomes ◽  
Biogeochemical Models ◽  
Genome Scale

Abstract Background: Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent, however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and contributions to biogeochemical cycling. Results: We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, identification of metabolism markers, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the community, potential microbial metabolic handoffs and metabolite exchange, and calculation of microbial community contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or from single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, and community-scale metabolic networks using a newly defined metric ‘MN-score’ (metabolic network score). METABOLIC takes ~3 hours with 40 CPU threads to process ~100 genomes and metagenomic reads within which the most compute-demanding part of hmmsearch takes ~45 mins, while it takes ~5 hours to complete hmmsearch for ~3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut.Conclusion: METABOLIC enables consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available at https://github.com/AnantharamanLab/METABOLIC under GPLv3.

scholarly journals OrtSuite – from genomes to prediction of microbial interactions within targeted ecosystem processes

2021 ◽  
Author(s):  
Joao Pedro Saraiva ◽  
Alexandre Bartholomäus ◽  
René Kallies ◽  
Marta Gomes ◽  
Marcos Vinicios Fleming Bicalho ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Open Source Software ◽  
Species Interactions ◽  
Functional Annotation ◽  
Ecosystem Processes ◽  
Independent Study ◽  
Microbial Interactions ◽  
High Complexity ◽  
Benzoate Degradation ◽  
User Friendly

The high complexity found in microbial communities makes the identification of microbial interactions challenging. To address this challenge, we present OrtSuite, a flexible workflow to predict putative microbial interactions based on genomic content of microbial communities and targeted to specific ecosystem processes. The pipeline is composed of three user-friendly bash commands. OrtSuite combines ortholog clustering with genome annotation strategies limited to user-defined sets of functions allowing for hypothesis-driven data analysis such as assessing microbial interactions in specific ecosystems. OrtSuite matched, on average, 96 % of experimentally verified KEGG orthologs involved in benzoate degradation in a known group of benzoate degraders. Identification of putative synergistic species interactions was evaluated using the sequenced genomes of an independent study which had previously proposed potential species interactions in benzoate degradation. OrtSuite is an easy to use workflow that allows for rapid functional annotation based on a user curated database and can easily be extended to ecosystem processes where connections between genes and reactions are known. OrtSuite is an open-source software available at https://github.com/mdsufz/OrtSuite.

scholarly journals The microbial exometabolome: ecological resource and architect of microbial communities

2020 ◽  
Vol 375 (1798) ◽  
pp. 20190250 ◽  
Author(s):  
Angela E. Douglas
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Priority Effects ◽  
Future Research ◽  
Metabolic Efficiency ◽  
Total Biomass ◽  
Ecological Processes ◽  
Evolutionary Diversification ◽  
Metabolite Exchange ◽  
Starting Conditions

All microorganisms release many metabolites, collectively known as the exometabolome. The resultant multi-way cross-feeding of metabolites among microorganisms distributes resources, thereby increasing total biomass of the microbial community, and promotes the recruitment and persistence of phylogenetically and functionally diverse taxa in microbial communities. Metabolite transfer can also select for evolutionary diversification, yielding multiple closely related but functionally distinct strains. Depending on starting conditions, the evolved strains may be auxotrophs requiring metabolic outputs from producer cells or, alternatively, display loss of complementary reactions in metabolic pathways, with increased metabolic efficiency. Metabolite cross-feeding is widespread in many microbial communities associated with animals and plants, including the animal gut microbiome, and these metabolic interactions can yield products valuable to the host. However, metabolite exchange between pairs of intracellular microbial taxa that share the same host cell or organ can be very limited compared to pairs of free-living microorganisms, perhaps as a consequence of host controls over the metabolic function of intracellular microorganisms. Priorities for future research include the development of tools for improved quantification of metabolite exchange in complex communities and greater integration of the roles of metabolic cross-feeding and other ecological processes, including priority effects and antagonistic interactions, in shaping microbial communities. This article is part of the theme issue ‘Conceptual challenges in microbial community ecology’.

Rhizosphere Microbial Community Dynamics in Glyphosate-Treated Susceptible and Resistant Biotypes of Giant Ragweed (Ambrosia trifida)

Weed Science ◽  
2014 ◽  
Vol 62 (2) ◽  
pp. 370-381 ◽  
Author(s):  
Jessica R. Schafer ◽  
Steven G. Hallett ◽  
William G. Johnson
Keyword(s):  
Microbial Community ◽  
Next Generation Sequencing ◽  
Microbial Communities ◽  
Soil Microbial Communities ◽  
Microbial Interactions ◽  
Field Soil ◽  
Next Generation ◽  
Giant Ragweed ◽  
Generation Sequencing ◽  
Rhizosphere Microbial Community

In a previous study, glyphosate-susceptible and -resistant giant ragweed biotypes grown in sterile field soil survived a higher rate of glyphosate than those grown in unsterile field soil, and the roots of the susceptible biotype were colonized by a larger number of soil microorganisms than those of the resistant biotype when treated with 1.6 kg ae ha−1glyphosate. Thus, we concluded that soil-borne microbes play a role in glyphosate activity and now hypothesize that the ability of the resistant biotype to tolerate glyphosate may involve microbial interactions in the rhizosphere. The objective of this study was to evaluate differences in the rhizosphere microbial communities of glyphosate-susceptible and -resistant giant ragweed biotypes 3 d after a glyphosate treatment. Giant ragweed biotypes were grown in the greenhouse in unsterile field soil and glyphosate was applied at either 0 or 1.6 kg ha−1. Rhizosphere soil was sampled 3 d after the glyphosate treatment, and DNA was extracted, purified, and sequenced with the use of Illumina Genome Analyzer next-generation sequencing. The taxonomic distribution of the microbial community, diversity, genera abundance, and community structure within the rhizosphere of the two giant ragweed biotypes in response to a glyphosate application was evaluated by metagenomics analysis. Bacteria comprised approximately 96% of the total microbial community in both biotypes, and differences in the distribution of some microbes at the phyla level were observed. Select soil-borne plant pathogens (VerticilliumandXanthomonas) and plant-growth–promoting rhizobacteria (Burkholderia) present in the rhizosphere were influenced by either biotype or glyphosate application. We did not, however, observe large differences in the diversity or structure of soil microbial communities among our treatments. The results of this study indicate that challenging giant ragweed biotypes with glyphosate causes perturbations in rhizosphere microbial communities and that the perturbations differ between the susceptible and resistant biotypes. However, biological relevance of the rhizosphere microbial community data that we obtained by next-generation sequencing remains unclear.

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