Anaerobic digestion (AD) involves a consortium of microorganisms that convert substrates into biogas containing methane for renewable energy. The technology has suffered from the perception of being periodically unstable due to limited understanding of the relationship between microbial community structure and function. The emphasis of this review is to describe microbial communities in digesters and quantitative and qualitative relationships between community structure and digester function. Progress has been made in the past few decades to identify key microorganisms influencing AD. Yet, more work is required to realize robust, quantitative relationships between microbial community structure and functions such as methane production rate and resilience after perturbations. Other promising areas of research for improved AD may include methods to increase/control (1) hydrolysis rate, (2) direct interspecies electron transfer to methanogens, (3) community structure–function relationships of methanogens, (4) methanogenesis via acetate oxidation, and (5) bioaugmentation to study community–activity relationships or improve engineered bioprocesses.

Upflow anaerobic sludge blanket (UASB) reactor has served as an effective process to treat industrial wastewater such as purified terephthalic acid (PTA) wastewater. For optimal UASB performance, balanced ecological interactions between syntrophs, methanogens, and fermenters are critical. However, much of the interactions remain unclear because UASB have been studied at a “macro”-level perspective of the reactor ecosystem. In reality, such reactors are composed of a suite of granules, each forming individual micro-ecosystems treating wastewater. Thus, typical approaches may be oversimplifying the complexity of the microbial ecology and granular development. To identify critical microbial interactions at both macro- and micro- level ecosystem ecology, we perform community and network analyses on 300 PTA–degrading granules from a lab-scale UASB reactor and two full-scale reactors. Based on MiSeq-based 16S rRNA gene sequencing of individual granules, different granule-types co-exist in both full-scale reactors regardless of granule size and reactor sampling depth, suggesting that distinct microbial interactions occur in different granules throughout the reactor. In addition, we identify novel networks of syntrophic metabolic interactions in different granules, perhaps caused by distinct thermodynamic conditions. Moreover, unseen methanogenic relationships (e.g. “Candidatus Aminicenantes” and Methanosaeta) are observed in UASB reactors. In total, we discover unexpected microbial interactions in granular micro-ecosystems supporting UASB ecology and treatment through a unique single-granule level approach.

Abstract:Much remains unknown about the relationships between microbial community structure and anaerobic digester function. However, knowledge of links between community structure and function, such as specific methanogenic activity (SMA) and COD removal rate, are valuable to improve anaerobic bioprocesses. In this work, quantitative structure-activity relationships (QSARs) were developed using multiple linear regression (MLR) to predict SMA using methanogen community structure descriptors for 49 cultures. Community descriptors were DGGE demeaned standardized band intensities for amplicons of a methanogen functional gene (mcrA). First, predictive accuracy of MLR QSARs was assessed using cross validation with training (n = 30) and test sets (n = 19) for glucose and propionate SMA data. MLR equations correlating band intensities and SMA demonstrated good predictability for glucose (q 2 = 0.54) and propionate (q 2 = 0.53). Subsequently, data from all 49 cultures were used to develop QSARs to predict SMA values. Higher intensities of two bands were correlated with higher SMA values; high abundance of methanogens associated with these two bands should be encouraged to attain high SMA values. QSARs are helpful tools to identify key microorganisms or to study and improve many bioprocesses. Development of new, more robust QSARs is encouraged for anaerobic digestion or other bioprocesses, including nitrification, nitritation, denitrification, anaerobic ammonium oxidation, and enhanced biological phosphorus removal. Graphical abstract

Background Ubiquitous in natural and engineered ecosystems, microbial immigration is one of the mechanisms shaping community assemblage. However, quantifying immigration impact remains challenging especially at individual population level. The activities of immigrants in the receiving community are often inadequately considered, leading to potential bias in identifying the relationship between community composition and environmental parameters. Results This study quantified microbial immigration from an upstream full-scale anaerobic reactor to downstream activated sludge reactors. A mass balance was applied to 16S rRNA gene amplicon sequencing data to calculate the net growth rates of individual populations in the activated sludge reactors. Among the 1178 observed operational taxonomic units (OTUs), 582 had a positive growth rate, including all the populations with abundance > 0.1%. These active populations collectively accounted for 99% of the total sequences in activated sludge. The remaining 596 OTUs with a growth rate ≤ 0 were classified as inactive populations. All the abundant populations in the upstream anaerobic reactor were inactive in the activated sludge process, indicating a negligible immigration impact. We used a supervised learning regressor to predict environmental parameters based on community composition and compared the prediction accuracy based on either the entire community or the active populations. Temperature was the most predictable parameter, and the prediction accuracy was improved when only active populations were used to train the regressor. Conclusions Calculating growth rate of individual microbial populations in the downstream system provides an effective approach to determine microbial activity and quantify immigration impact. For the studied biological process, a marginal immigration impact was observed, likely due to the significant differences in the growth environments between the upstream and downstream processes. Excluding inactive populations as a result of immigration further enhanced the prediction of key environmental parameters affecting process performance. Electronic supplementary material The online version of this article (10.1186/s40168-019-0682-x) contains supplementary material, which is available to authorized users.

Many beer breweries use high-rate anaerobic digestion (AD) systems to treat their soluble high-strength wastewater. Biogas from these AD systems is used to offset nonrenewable energy utilization in the brewery. With increasing nonrenewable energy costs, interest has mounted to also digest secondary residuals from the high-rate digester effluent, which consists of yeast cells, bacteria, methanogens, and small (hemi)cellulosic particles. Mesophilic (37 degrees C) and thermophilic (55 degrees C) lab-scale, low-rate continuously-stirred anaerobic digestion (CSAD) bioreactors were operated for 258 days by feeding secondary residuals at a volatile solids (VS) concentration of approximately 40 g l(-1). At a hydraulic retention time (HRT) of 15 days and a VS loading rate of 2.7 g VS l(-1) day(-1), the mesophilic bioreactor showed an average specific volumetric biogas production rate of 0.88 l CH4 l(-1) day(-1) and an effluent VS concentration of 22.2 g VS l(-1) (43.0% VS removal efficiency) while the thermophilic bioreactor displayed similar performances. The overall methane yield for both systems was 0.21 l CH4 g(-1) VS fed and 0.47-0.48 l CH4 g(-1) VS removed. A primary limitation of thermophilic digestion of this protein-rich waste is the inhibition of methanogens due to higher nondissociated (free) ammonia (NH3) concentrations under similar total ammonium (NH4+) concentrations at equilibrium. Since thermophilic AD did not result in advantageous methane production rates or yields, mesophilic AD was, therefore, superior in treating secondary residuals from high-rate AD effluent. An additional digester to convert secondary residuals to methane may increase the total biogas generation at the brewery by 8% compared to just conventional high-rate digestion of brewery wastewater alone.