scholarly journals Microbial Community Ecology & Insect Nutrition

2000 ◽  
Vol 46 (3) ◽  
pp. 173-185 ◽  
Author(s):  
Michael G. Kaufman ◽  
Edward D. Walker ◽  
David A. Odelson ◽  
Michael J. Klug
Author(s):  
Chi Liu ◽  
Yaoming Cui ◽  
Xiangzhen Li ◽  
Minjie Yao

Abstract A large amount of sequencing data is produced in microbial community ecology studies using the high-throughput sequencing technique, especially amplicon-sequencing-based community data. After conducting the initial bioinformatic analysis of amplicon sequencing data, performing the subsequent statistics and data mining based on the operational taxonomic unit and taxonomic assignment tables is still complicated and time-consuming. To address this problem, we present an integrated R package-‘microeco’ as an analysis pipeline for treating microbial community and environmental data. This package was developed based on the R6 class system and combines a series of commonly used and advanced approaches in microbial community ecology research. The package includes classes for data preprocessing, taxa abundance plotting, venn diagram, alpha diversity analysis, beta diversity analysis, differential abundance test and indicator taxon analysis, environmental data analysis, null model analysis, network analysis and functional analysis. Each class is designed to provide a set of approaches that can be easily accessible to users. Compared with other R packages in the microbial ecology field, the microeco package is fast, flexible and modularized to use, and provides powerful and convenient tools for researchers. The microeco package can be installed from CRAN (The Comprehensive R Archive Network) or github (https://github.com/ChiLiubio/microeco).


2020 ◽  
Vol 11 ◽  
Author(s):  
Els van der Goot ◽  
Francjan J. van Spronsen ◽  
Joana Falcão Salles ◽  
Eddy A. van der Zee

2019 ◽  
Vol 79 (2) ◽  
pp. 342-356
Author(s):  
Yushi Tang ◽  
Tianjiao Dai ◽  
Zhiguo Su ◽  
Kohei Hasegawa ◽  
Jinping Tian ◽  
...  

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Sylvie Estrela ◽  
Alicia Sanchez-Gorostiaga ◽  
Jean CC Vila ◽  
Alvaro Sanchez

A major open question in microbial community ecology is whether we can predict how the components of a diet collectively determine the taxonomic composition of microbial communities. Motivated by this challenge, we investigate whether communities assembled in pairs of nutrients can be predicted from those assembled in every single nutrient alone. We find that although the null, naturally additive model generally predicts well the family-level community composition, there exist systematic deviations from the additive predictions that reflect generic patterns of nutrient dominance at the family level. Pairs of more-similar nutrients (e.g. two sugars) are on average more additive than pairs of more dissimilar nutrients (one sugar–one organic acid). Furthermore, sugar–acid communities are generally more similar to the sugar than the acid community, which may be explained by family-level asymmetries in nutrient benefits. Overall, our results suggest that regularities in how nutrients interact may help predict community responses to dietary changes.


Sign in / Sign up

Export Citation Format

Share Document