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A systematic approach re-analyzing the effects of temperature disturbance on the microbial community of mesophilic anaerobic digestion.

ABSTRACT: Microbial communities are key drivers of ecosystem processes, but their behavior in disturbed environments is difficult to measure. How microbial community composition and function respond disturbances is a common challenge in biomedical, environmental, agricultural, and bioenergy research. A novel way to solve this problem is to use a systems-level perspective and describe microbial communities as networks. Based on a mesophilic anaerobic digestion system of swine manure as a tool, we propose a simple framework to investigate changes in microbial communities via compositions, metabolic pathways, genomic properties and interspecies relationships in response to a long-term temperature disturbance. After temperature disturbance, microbial communities tend towards a competitive interaction network with higher GC content and larger genome size. Based on microbial interaction networks, communities responded to the disturbance by showing a transition from acetotrophic (Methanotrichaceae and Methanosarcinaceae) to methylotrophic methanogens (Methanomassiliicoccaceae and Methanobacteriaceae) and a fluctuation in rare biosphere taxa. To conclude, this study may be important for exploring the dynamic relationships between disturbance and microbial communities as a whole, as well as for providing researchers with a better understanding of how changes in microbial communities relate to ecological processes.

SUBMITTER: Shaw GT

PROVIDER: S-EPMC6484075 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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A systematic approach re-analyzing the effects of temperature disturbance on the microbial community of mesophilic anaerobic digestion.

Shaw Grace Tzun-Wen GT Weng Chieh-Yin CY Chen Cheng-Yu CY Weng Francis Cheng-Hsuan FC Wang Daryi D

Scientific reports 20190425 1

Microbial communities are key drivers of ecosystem processes, but their behavior in disturbed environments is difficult to measure. How microbial community composition and function respond disturbances is a common challenge in biomedical, environmental, agricultural, and bioenergy research. A novel way to solve this problem is to use a systems-level perspective and describe microbial communities as networks. Based on a mesophilic anaerobic digestion system of swine manure as a tool, we propose a ...[more]

PMID: 31024021

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Project description:BackgroundMonitoring and providing early warning are essential operations in the anaerobic digestion (AD) process. However, there are still several challenges for identifying the early warning indicators and their thresholds. One particular challenge is that proposed strategies are only valid under certain conditions. Another is the feasibility and universality of the detailed threshold values obtained from different AD systems. In this article, we report a novel strategy for identifying early warning indicators and defining threshold values via a combined experimental and simulation approach.ResultsThe AD of corn stalk (CS) was conducted using mesophilic, completely stirred anaerobic reactors. Two overload modes (organic and hydraulic) and overload types (sudden and gradual) were applied in order to identify early warning indicators of the process and determine their threshold values. To verify the selection of experimental indicators, a combined experimental and simulation approach was adopted, using a modified anaerobic bioconversion mathematical model (BioModel). Results revealed that the model simulations agreed well with the experimental data. Furthermore, the ratio of intermediate alkalinity to bicarbonate alkalinity (IA/BA) and volatile fatty acids (VFAs) were selected as the most potent early warning indicators, with warning times of 7 days and 5-8 days, respectively. In addition, IA, BA, and VFA/BA were identified as potential auxiliary indicators for diagnosing imbalances in the AD system. The relative variations for indicators based on that of steady state were observed instead of the absolute threshold values, which make the early warning more feasible and universal.ConclusionThe strategy of a combined approach presented that the model is promising tool for selecting and monitoring early warning indicators in various corn stalk AD scenarios. This study may offer insight into industrial application of early warning in AD system with mathematical model.

Project description:Harvesting valuable bioproducts from various renewable feedstocks is necessary for the critical development of a sustainable bioeconomy. Anaerobic digestion is a well-established technology for the conversion of wastewater and solid feedstocks to energy with the additional potential for production of process intermediates of high market values (e.g., carboxylates). In recent years, first-generation biofuels typically derived from food crops have been widely utilized as a renewable source of energy. The environmental and socioeconomic limitations of such strategy, however, have led to the development of second-generation biofuels utilizing, amongst other feedstocks, lignocellulosic biomass. In this context, the anaerobic digestion of perennial grass holds great promise for the conversion of sustainable renewable feedstock to energy and other process intermediates. The advancement of this technology however, and its implementation for industrial applications, relies on a greater understanding of the microbiome underpinning the process. To this end, microbial communities recovered from replicated anaerobic bioreactors digesting grass were analyzed. The bioreactors leachates were not buffered and acidic pH (between 5.5 and 6.3) prevailed at the time of sampling as a result of microbial activities. Community composition and transcriptionally active taxa were examined using 16S rRNA sequencing and microbial functions were investigated using metaproteomics. Bioreactor fraction, i.e., grass or leachate, was found to be the main discriminator of community analysis across the three molecular level of investigation (DNA, RNA, and proteins). Six taxa, namely Bacteroidia, Betaproteobacteria, Clostridia, Gammaproteobacteria, Methanomicrobia, and Negativicutes accounted for the large majority of the three datasets. The initial stages of grass hydrolysis were carried out by Bacteroidia, Gammaproteobacteria, and Negativicutes in the grass biofilms, in addition to Clostridia in the bioreactor leachates. Numerous glycolytic enzymes and carbohydrate transporters were detected throughout the bioreactors in addition to proteins involved in butanol and lactate production. Finally, evidence of the prevalence of stressful conditions within the bioreactors and particularly impacting Clostridia was observed in the metaproteomes. Taken together, this study highlights the functional importance of Clostridia during the anaerobic digestion of grass and thus research avenues allowing members of this taxon to thrive should be explored.

Project description:Anaerobic co-digestion (Co-AD) is used to increase the effectiveness of anaerobic digestion (AD) using local "wastes", adding economic and environmental benefits. Since system stability is of existential importance for the operation of wastewater treatment plants, thorough testing of potential co-substrates and their effects on the respective community and system performance is crucial for understanding and utilizing Co-AD to its best capacity. Food waste (FW) and canola lecithin (CL) were tested in mesophilic, lab-scale, semi-continuous reactors over a duration of 120 days with stepwise increased substrate addition. Key performance indicators (biogas, total/volatile solids, fatty acids) were monitored and combined with 16S-rRNA amplicon sequencing to assess the impact of co-substrate addition on reactor performance and microbial community composition (MCC). Additionally, the latter was then compared with natural shifts occurring in the wastewater treatment plant (WWTP, source) at the same time. An almost linear increase in biogas production with both co-substrates at an approximate 1:1 ratio with the organic loading rate (OLR) was observed. The MCCs in both experiments were mostly stable, but also prone to drift over time. The FW experiment MCC more closely resembled the original WWTP community and the observed shifts indicated high levels of functional redundancy. Exclusive to the CL co-substrate, a clear selection for a few operational taxonomic units (OTUs) was observed. There was little evidence for a persistent invasion and establishment of microorganisms from typical primary substrates into the stable resident community of the reactors, which is in line with earlier findings that suggested that the inoculum and history mostly define the MCC. However, external factors may still tip the scales in favor of a few r-strategists (e.g., Prolixibacter) in an environment that otherwise favors K-strategists, which may in fact also be recruited from the primary substrate (Trichococcus). In our study, specialization and diversity loss were also observed in response to the addition of the highly specialized CL, which in turn, may have adverse effects on the system's stability and reduced resilience and recovery.

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A systematic approach re-analyzing the effects of temperature disturbance on the microbial community of mesophilic anaerobic digestion.

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A systematic approach re-analyzing the effects of temperature disturbance on the microbial community of mesophilic anaerobic digestion.

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