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Progressive Microbial Community Networks with Incremental Organic Loading Rates Underlie Higher Anaerobic Digestion Performance.

ABSTRACT: Although biotic interactions among members of microbial communities have been conceived to be crucial for community assembly, it remains unclear how changes in environmental conditions affect microbial interaction and consequently system performance. Here, we adopted a random matrix theory-based network analysis to explore microbial interactions in triplicate anaerobic digestion (AD) systems, which is widely applied for organic pollutant treatments. The digesters were operated with incremental organic loading rates (OLRs) from 1.0 g volatile solids (VS)/liter/day to 1.3 g VS/liter/day and then to 1.5 g VS/liter/day, which increased VS removal and methane production proportionally. Higher resource availability led to networks with higher connectivity and shorter harmonic geodesic distance, suggestive of more intense microbial interactions and quicker responses to environmental changes. Strikingly, a number of topological properties of microbial network showed significant (P < 0.05) correlation with AD performance (i.e., methane production, biogas production, and VS removal). When controlling for environmental parameters (e.g., total ammonia, pH, and the VS load), node connectivity, especially that of the methanogenic archaeal network, still correlated with AD performance. Last, we identified the Methanothermus, Methanobacterium, Chlorobium, and Haloarcula taxa and an unclassified Thaumarchaeota taxon as keystone nodes of the network.IMPORTANCE AD is a biological process widely used for effective waste treatment throughout the world. Biotic interactions among microbes are critical to the assembly and functioning of the microbial community, but the response of microbial interactions to environmental changes and their influence on AD performance are still poorly understood. Using well-replicated time series data of 16S rRNA gene amplicons and functional gene arrays, we constructed random matrix theory-based association networks to characterize potential microbial interactions with incremental OLRs. We demonstrated striking linkage between network topological features of methanogenic archaea and AD functioning independent of environmental parameters. As the intricate balance of multiple microbial functional groups is responsible for methane production, our results suggest that microbial interaction may be an important, previously unrecognized mechanism in determining AD performance.

SUBMITTER: Wu L

PROVIDER: S-EPMC6946792 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Progressive Microbial Community Networks with Incremental Organic Loading Rates Underlie Higher Anaerobic Digestion Performance.

Wu Linwei L Shan Xiaoyu X Chen Si S Zhang Qiuting Q Qi Qi Q Qin Ziyan Z Yin Huaqun H Zhou Jizhong J He Qiang Q Yang Yunfeng Y

mSystems 20200107 1

Although biotic interactions among members of microbial communities have been conceived to be crucial for community assembly, it remains unclear how changes in environmental conditions affect microbial interaction and consequently system performance. Here, we adopted a random matrix theory-based network analysis to explore microbial interactions in triplicate anaerobic digestion (AD) systems, which is widely applied for organic pollutant treatments. The digesters were operated with incremental o ...[more]

PMID: 31911462

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Project description:BackgroundVolatile fatty acid intoxication (acidosis), a common process failure recorded in anaerobic reactors, leads to drastic losses in methane production. Unfortunately, little is known about the microbial mechanisms underlining acidosis and the potential to recover the process. In this study, triplicate mesophilic anaerobic reactors of 100 L were exposed to acidosis resulting from an excessive feeding with sugar beet pulp and were compared to a steady-state reactor.ResultsStable operational conditions at the beginning of the experiment initially led to similar microbial populations in the four reactors, as revealed by 16S rRNA gene T-RFLP and high-throughput amplicon sequencing. Bacteroidetes and Firmicutes were the two dominant phyla, and although they were represented by a high number of operational taxonomic units, only a few were dominant. Once the environment became deterministic (selective pressure from an increased substrate feeding), microbial populations started to diverge between the overfed reactors. Interestingly, most of bacteria and archaea showed redundant functional adaptation to the changing environmental conditions. However, the dominant Bacteroidales were resistant to high volatile fatty acids content and low pH. The severe acidosis did not eradicate archaea and a clear shift in archaeal populations from acetotrophic to hydrogenotrophic methanogenesis occurred in the overfed reactors. After 11 days of severe acidosis (pH 5.2 ± 0.4), the process was quickly recovered (restoration of the biogas production with methane content above 50 %) in the overfed reactors, by adjusting the pH to around 7 using NaOH and NaHCO3.ConclusionsIn this study we show that once the replicate reactors are confronted with sub-optimal conditions, their microbial populations start to evolve differentially. Furthermore the alterations of commonly used microbial parameters to monitor the process, such as richness, evenness and diversity indices were unsuccessful to predict the process failure. At the same time, we tentatively propose the replacement of the dominant Methanosaeta sp. in this case by Methanoculleus sp., to be a potential warning indicator of acidosis.

Dataset Information

Progressive Microbial Community Networks with Incremental Organic Loading Rates Underlie Higher Anaerobic Digestion Performance.

Publications

Progressive Microbial Community Networks with Incremental Organic Loading Rates Underlie Higher Anaerobic Digestion Performance.

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