Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 108, Issue 10, Pages 4158-4163Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1015676108
Keywords
community dynamics; UniFrac; community function; digester; sludge
Categories
Funding
- National Research Initiative of the Department of Agriculture (USDA) National Institutes for Food and Agriculture (NIFA) [2004-35504-14896]
- Cornell University Agricultural Experiment Station, USDA NIFA [NYC-123444]
- DOE [DE-FC26-08NT05870]
- Colorado Center for Biofuels and Biorefining [C2B2]
- Howard Hughes Medical Institute
- National Institutes of Health [NIDDK020579, NIDDK05634, NCRR000954]
Ask authors/readers for more resources
Anaerobic digestion is the most successful bioenergy technology worldwide with, at its core, undefined microbial communities that have poorly understood dynamics. Here, we investigated the relationships of bacterial community structure (> 400,000 16S rRNA gene sequences for 112 samples) with function (i.e., bioreactor performance) and environment (i.e., operating conditions) in a year-long monthly time series of nine full-scale bioreactor facilities treating brewery wastewater (> 20,000 measurements). Each of the nine facilities had a unique community structure with an unprecedented level of stability. Using machine learning, we identified a small subset of operational taxonomic units (OTUs; 145 out of 4,962), which predicted the location of the facility of origin for almost every sample (96.4% accuracy). Of these 145 OTUs, syntrophic bacteria were systematically overrepresented, demonstrating that syntrophs rebounded following disturbances. This indicates that resilience, rather than dynamic competition, played an important role in maintaining the necessary syntrophic populations. In addition, we explained the observed phylogenetic differences between all samples on the basis of a subset of environmental gradients (using constrained ordination) and found stronger relationships between community structure and its function rather than its environment. These relationships were strongest for two performance variables-methanogenic activity and substrate removal efficiency-both of which were also affected by microbial ecology because these variables were correlated with community evenness (at any given time) and variability in phylogenetic structure (over time), respectively. Thus, we quantified relationships between community structure and function, which opens the door to engineer communities with superior functions.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available