scholarly journals MPA_Pathway_Tool: User-Friendly, Automatic Assignment of Microbial Community Data on Metabolic Pathways

2021 ◽  
Vol 22 (20) ◽  
pp. 10992
Author(s):  
Daniel Walke ◽  
Kay Schallert ◽  
Prasanna Ramesh ◽  
Dirk Benndorf ◽  
Emanuel Lange ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Web Application ◽  
Functional Characterization ◽  
Single Species ◽  
Central Carbon Metabolism ◽  
Biological Pathways ◽  
Community Data ◽  
Set Up ◽  
User Friendly

Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versality of microbial metabolism and a still-increasing number of newly biological pathways, linkage to standard pathway maps such as the KEGG central carbon metabolism is often problematic. We successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called ‘Pathway-Creator’ and ‘Pathway-Calculator’. The ‘Pathway-Creator’ enables an easy set-up of user-defined pathways with specific taxonomic constraints. The ‘Pathway-Calculator’ automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. The MPA_Pathway_Tool is implemented in Java and ReactJS.

scholarly journals MPA_Pathway_Tool: User-friendly, automatic assignment of microbial community data on metabolic pathways

2021 ◽  
Author(s):  
Daniel Walke ◽  
Kay Schallert ◽  
Prasanna Ramesh ◽  
Dirk Benndorf ◽  
Emanuel Lange ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Web Application ◽  
Functional Characterization ◽  
Single Species ◽  
Central Carbon Metabolism ◽  
Biological Pathways ◽  
Biogas Plants ◽  
Community Data ◽  
User Friendly

Motivation: Taxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versatility of microbial metabolism and a still increasing number of new biological pathways, linkage to standard pathway maps such as the KEGG (Kyoto Encyclopedia of Genes and Genomes) central carbon metabolism is often problematic. Results: We successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called Pathway-Creator and Pathway-Calculator. The Pathway-Creator enables an easy setup of user-defined pathways with specific taxonomic constraints. The Pathway-Calculator automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. Availability and Implementation: The MPA_Pathway_Tool is implemented in Java and ReactJS. It is freely available on http://mpa-pathwaymapper.ovgu.de/. Further documentation and the complete source code are available on GitHub (https://github.com/danielwalke/MPA_Pathway_Tool). Contact: [email protected], [email protected]

scholarly journals Formation of Phage Lysis Patterns and Implications on Co-Propagation of Phages and Motile Host Bacteria

2019 ◽  
Author(s):  
Xiaochu Li ◽  
Floricel Gonzalez ◽  
Nathaniel Esteves ◽  
Birgit E. Scharf ◽  
Jing Chen
Keyword(s):  
Mathematical Model ◽  
Microbial Community ◽  
Microbial Communities ◽  
Biological Properties ◽  
Scientific Basis ◽  
Nutrient Level ◽  
Natural Environments ◽  
Extrinsic Factors ◽  
Inhibition Of Proliferation ◽  
Set Up

AbstractCoexistence of bacteriophages, or phages, and their host bacteria plays an important role in maintaining the microbial communities. In natural environments with limited nutrients, motile bacteria can actively migrate towards locations of richer resources. Although phages are not motile themselves, they can infect motile bacterial hosts and spread in space via the hosts. Therefore, in a migrating microbial community coexistence of bacteria and phages implies their co-propagation in space. Here, we combine an experimental approach and mathematical modeling to explore how phages and their motile host bacteria coexist and co-propagate. When lytic phages encountered motile host bacteria in our experimental set up, a sector-shaped lysis zone formed. Our mathematical model indicates that local nutrient depletion and the resulting inhibition of proliferation and motility of bacteria and phages are the key to formation of the observed lysis pattern. The model further reveals the straight radial boundaries in the lysis pattern as a tell-tale sign for coexistence and co-propagation of bacteria and phages. Emergence of such a pattern, albeit insensitive to extrinsic factors, requires a balance between intrinsic biological properties of phages and bacteria, which likely results from co-evolution of phages and bacteria.Author summaryCoexistence of phages and their bacterial hosts is important for maintaining the microbial communities. In a migrating microbial community, coexistence between phages and host bacteria implies that they co-propagate in space. Here we report a novel phage lysis pattern that is indicative of this co-propagation. The corresponding mathematical model we developed highlights a crucial dependence of the lysis pattern and implied phage-bacteria co-propagation on intrinsic properties allowing proliferation and spreading of the microbes in space. Remarkably, extrinsic factors, such as overall nutrient level, do not influence phage-bacteria coexistence and co-propagation. Findings from this work have strong implications for dispersal of phages mediated by motile bacterial communities, which will provide scientific basis for the fast-growing applications of phages.

scholarly journals Fast automated reconstruction of genome-scale metabolic models for microbial species and communities

2018 ◽  
Author(s):  
Daniel Machado ◽  
Sergej Andrejev ◽  
Melanie Tramontano ◽  
Kiran Raosaheb Patil
Keyword(s):  
Microbial Communities ◽  
Single Species ◽  
Model Organisms ◽  
Universal Model ◽  
Microbial Species ◽  
Scale Models ◽  
Metabolic Models ◽  
User Friendly ◽  
Genome Scale ◽  
Automated Tool

AbstractGenome-scale metabolic models are instrumental in uncovering operating principles of cellular metabolism and model-guided re-engineering. Recent applications of metabolic models have also demonstrated their usefulness in unraveling cross-feeding within microbial communities. Yet, the application of genome-scale models, especially to microbial communities, is lagging far behind the availability of sequenced genomes. This is largely due to the time-consuming steps of manual cura-tion required to obtain good quality models and thus physiologically meaningful simulation results. Here, we present an automated tool – CarveMe – for reconstruction of species and community level metabolic models. We introduce the concept of a universal model, which is manually curated and simulation-ready. Starting with this universal model and annotated genome sequences, CarveMe uses a top-down approach to build single-species and community models in a fast and scalable manner. We build reconstructions for two model organisms, Escherichia coli and Bacillus subtillis, as well as a collection of human gut bacteria, and show that CarveMe models perform similarly to manually curated models in reproducing experimental phenotypes. Finally, we demonstrate the scalability of CarveMe through reconstructing 5587 bacterial models. Overall, CarveMe provides an open-source and user-friendly tool towards broadening the use of metabolic modeling in studying microbial species and communities.

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.

scholarly journals GREIN: An Interactive Web Platform for Reanalyzing GEO RNA-seq Data

2018 ◽  
Author(s):  
Naim Al Mahi ◽  
Mehdi Fazel Najafabadi ◽  
Marcin Pilarczyk ◽  
Michal Kouril ◽  
Mario Medvedovic
Keyword(s):  
Gene Expression ◽  
User Interfaces ◽  
Web Application ◽  
Statistical Power ◽  
Functional Characterization ◽  
Gene Expression Omnibus ◽  
Rna Seq ◽  
Link Type ◽  
Front End ◽  
User Friendly

ABSTRACTThe vast amount of RNA-seq data deposited in Gene Expression Omnibus (GEO) and Sequence Read Archive (SRA) is still a grossly underutilized resource for biomedical research. To remove technical roadblocks for reusing these data, we have developed a web-application GREIN (GEO RNA-seq Experiments Interactive Navigator) which provides user-friendly interfaces to manipulate and analyze GEO RNA-seq data. GREIN is powered by the back-end computational pipeline for uniform processing of RNA-seq data and the large number (>6,500) of already processed datasets. The front-end user interfaces provide a wealth of user-analytics options including sub-setting and downloading processed data, interactive visualization, statistical power analyses, construction of differential gene expression signatures and their comprehensive functional characterization, and connectivity analysis with LINCS L1000 data. The combination of the massive amount of back-end data and front-end analytics options driven by user-friendly interfaces makes GREIN a unique open-source resource for re-using GEO RNA-seq data. GREIN is accessible at: https://shiny.ilincs.org/grein, the source code at: https://github.com/uc-bd2k/grein, and the Docker container at: https://hub.docker.com/r/ucbd2k/grein.

scholarly journals Microbial predictors of environmental perturbations in coral reef ecosystems

2019 ◽  
Author(s):  
Bettina Glasl ◽  
David G. Bourne ◽  
Pedro R. Frade ◽  
Torsten Thomas ◽  
Britta Schaffelke ◽  
...  
Keyword(s):  
Coral Reef ◽  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Environmental Parameters ◽  
Diagnostic Value ◽  
Free Living ◽  
Environmental Pressures ◽  
Coral Reef Ecosystems ◽  
Community Data

AbstractIncorporation of microbial community data into environmental monitoring programs could improve prediction and management of environmental pressures. Coral reefs have experienced dramatic declines due to cumulative impacts of local and global stressors. Here we assess the utility of free-living (i.e. seawater and sediment) and host-associated (i.e. corals, sponges and macroalgae) microbiomes for diagnosing environmental perturbation based on their habitat-specificity, environmental sensitivity and uniformity. We show that the seawater microbiome has the greatest diagnostic value, with environmental parameters explaining 56% of the observed compositional variation and temporal successions being dominated by uniform community assembly patterns. Host-associated microbiomes, in contrast, were five-times less affected by the environment and their community assembly patterns were generally less uniform. Further, seawater microbial community data provided an accurate prediction on the environmental state, highlighting the diagnostic value of microorganisms and illustrating how long-term coral reef monitoring initiatives could be enhanced by incorporating assessments of microbial communities in seawater.ImportanceThe recent success in disease diagnostics based on the human microbiome has highlighted the utility of this approach for model systems. However, despite improved prediction and management of environmental pressures from the inclusion of microbial community data in monitoring programs, this approach has not previously been applied to coral reef ecosystems. Coral reefs are facing unprecedented pressure on a local and global scale, and sensitive and rapid markers for ecosystem stress are urgently needed to underpin effective management and restoration strategies. In this study, we performed the first assessment of the diagnostic value of multiple free-living and host-associated reef microbiomes to infer the environmental state of coral reef ecosystems. Our results reveal that free-living microbial communities have a higher potential to infer environmental parameters than host-associated microbial communities due to their higher determinacy and environmental sensitivity. We therefore recommend timely integration of microbial sampling into current coral reef monitoring initiatives.

scholarly journals Seed: a user-friendly tool for exploring and visualizing microbial community data

2014 ◽  
Vol 31 (4) ◽  
pp. 602-603 ◽  
Author(s):  
Daniel Beck ◽  
Christopher Dennis ◽  
James A. Foster
Keyword(s):  
Microbial Community ◽  
Community Data ◽  
User Friendly

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 CaptureSeq: Hybridization-Based Enrichment of cpn60 Gene Fragments Reveals the Community Structures of Synthetic and Natural Microbial Ecosystems

2021 ◽  
Vol 9 (4) ◽  
pp. 816
Author(s):  
Matthew G. Links ◽  
Tim J. Dumonceaux ◽  
E. Luke McCarthy ◽  
Sean M. Hemmingsen ◽  
Edward Topp ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Dna Sequences ◽  
Pcr Amplification ◽  
Shotgun Sequencing ◽  
Natural Ecosystems ◽  
Gene Markers ◽  
Microbial Profile ◽  
Microbial Ecosystems ◽  
Pcr Targeting

Background. The molecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with “universal” PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics. Methods. We present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir. Results. The CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health. Conclusions: cpn60-based hybridization enriched for taxonomically informative DNA sequences from complex mixtures. In synthetic and natural microbial ecosystems, CaptureSeq provided sequences from prokaryotes and eukaryotes simultaneously, with quantitatively reliable read abundances. CaptureSeq provides an alternative to PCR amplification of taxonomic markers with deep community coverage while minimizing amplification biases.

scholarly journals Pollutant-Removing Biofilter Strains Associated with High Ammonia and Hydrogen Sulfide Removal Rate in a Livestock Wastewater Treatment Facility

2021 ◽  
Vol 13 (13) ◽  
pp. 7358
Author(s):  
Dong-Hyun Kim ◽  
Hyun-Sik Yun ◽  
Young-Saeng Kim ◽  
Jong-Guk Kim
Keyword(s):  
Wastewater Treatment ◽  
Hydrogen Sulfide ◽  
Microbial Community ◽  
Microbial Communities ◽  
Illumina Miseq ◽  
Illumina Miseq Sequencing ◽  
Miseq Sequencing ◽  
Treatment Facility ◽  
Livestock Wastewater ◽  
Wastewater Treatment Facility

This study analyzed the microbial community metagenomically to determine the cause of the functionality of a livestock wastewater treatment facility that can effectively remove pollutants, such as ammonia and hydrogen sulfide. Illumina MiSeq sequencing was used in analyzing the composition and structure of the microbial community, and the 16S rRNA gene was used. Through Illumina MiSeq sequencing, information such as diversity indicators as well as the composition and structure of microbial communities present in the livestock wastewater treatment facility were obtained, and differences between microbial communities present in the investigated samples were compared. The number of reads, operational taxonomic units, and species richness were lower in influent sample (NLF), where the wastewater enters, than in effluent sample (NL), in which treated wastewater is found. This difference was greater in June 2019 than in January 2020, and the removal rates of ammonia (86.93%) and hydrogen sulfide (99.72%) were also higher in June 2019. In both areas, the community composition was similar in January 2020, whereas the influent sample (NLF) and effluent sample (NL) areas in June 2019 were dominated by Proteobacteria (76.23%) and Firmicutes (67.13%), respectively. Oleiphilaceae (40.89%) and Thioalkalibacteraceae (12.91%), which are related to ammonia and hydrogen sulfide removal, respectively, were identified in influent sample (NLF) in June 2019. They were more abundant in June 2019 than in January 2020. Therefore, the functionality of the livestock wastewater treatment facility was affected by characteristics, including the composition of the microbial community. Compared to Illumina MiSeq sequencing, fewer species were isolated and identified in both areas using culture-based methods, suggesting Illumina MiSeq sequencing as a powerful tool to determine the relevance of microbial communities for pollutant removal.

Sign in / Sign up

Export Citation Format

Share Document