Anaerobic Digester Bioaugmentation Influences Quasi Steady State Performance and Microbial Community

Nine anaerobic digesters, each seeded with biomass from a different source, were operated identically and their quasi steady state function was compared. Subsequently, digesters were bioaugmented with a methanogenic culture previously shown to increase specific methanogenic activity. Before bioaugmentation, different seed biomass resulted in different quasi steady state function, with digesters clustering into three groups distinguished by methane (CH4) production. Digesters with similar functional performance contained similar archaeal communities based on clustering of Illumina sequence data of the V4V5 region of the 16S rRNA gene. High CH4 production correlated with neutral pH and high Methanosarcina abundance, whereas low CH4production correlated to low pH as well as high Methanobacterium and DHVEG 6 family abundance. After bioaugmentation, CH4 production from the high CH4 producing digesters transiently increased by 11 ± 3% relative to non-bioaugmented controls (p \u3c 0.05, n = 3), whereas no functional changes were observed for medium and low CH4producing digesters that all had pH higher than 6.7. The CH4 production increase after bioaugmentation was correlated to increased relative abundance of Methanosaeta and Methaospirillum originating from the bioaugment culture. In conclusion, different anaerobic digester seed biomass can result in different quasi steady state CH4production, SCOD removal, pH and effluent VFA concentration in the timeframe studied. The bioaugmentation employed can result in a period of increased methane production. Future research should address extending the period of increased CH4 production by employing pH and VFA control concomitant with bioaugmentation, developing improved bioaugments, or employing a membrane bioreactor to retain the bioaugment

Biofilm engineering: linking biofilm development at different length and time scales

Biofilms are heterogeneous and dynamic systems. Evaluation of biofilm structure and function at the microscale has been greatly advanced through the application of multidimensional imaging, in-situ identification of the microbial community composition, function, and genetic regulation. Biofilm reactors are being applied for advanced biological treatment processes and their overall (macroscale) operation is well understood and controlled. What is missing is the link between micro and macroscale. In this horizon paper we suggest how understanding the overall biofilm ecosystem will require an integrated evaluation of the different length and time scale

Correlating Methane Production to Microbiota in Anaerobic Digesters Fed Synthetic Wastewater

A quantitative structure activity relationship (QSAR) between relative abundance values and digester methane production rate was developed. For this, 50 triplicate anaerobic digester sets (150 total digesters) were each seeded with different methanogenic biomass samples obtained from full-scale, engineered methanogenic systems. Although all digesters were operated identically for at least 5 solids retention times (SRTs), their quasi steady-state function varied significantly, with average daily methane production rates ranging from 0.09 ± 0.004 to 1 ± 0.05 L-CH4/LR-day (LR = Liter of reactor volume) (average ± standard deviation). Digester microbial community structure was analyzed using more than 4.1 million partial 16S rRNA gene sequences of Archaea and Bacteria. At the genus level, 1300 operational taxonomic units (OTUs) were observed across all digesters, whereas each digester contained 158 ± 27 OTUs. Digester function did not correlate with typical biomass descriptors such as volatile suspended solids (VSS) concentration, microbial richness, diversity or evenness indices. However, methane production rate did correlate notably with relative abundances of one Archaeal and nine Bacterial OTUs. These relative abundances were used as descriptors to develop a multiple linear regression (MLR) QSAR equation to predict methane production rates solely based on microbial community data. The model explained over 66% of the variance in the experimental data set based on 149 anaerobic digesters with a standard error of 0.12 L-CH4/LR-day. This study provides a framework to relate engineered process function and microbial community composition which can be further expanded to include different feed stocks and digester operating conditions in order to develop a more robust QSAR model

Advancing microbial sciences by individual-based modelling

Remarkable technological advances have revealed ever more properties and behaviours of individual microorganisms, but the novel data generated by these techniques have not yet been fully exploited. In this Opinion article, we explain how individual-based models (IBMs) can be constructed based on the findings of such techniques and how they help to explore competitive and cooperative microbial interactions. Furthermore, we describe how IBMs have provided insights into self-organized spatial patterns from biofilms to the oceans of the world, phage-CRISPR dynamics and other emergent phenomena. Finally, we discuss how combining individual-based observations with IBMs can advance our understanding at both the individual and population levels, leading to the new approach of microbial individual-based ecology (μIBE)

Challenges in microbial ecology: building predictive understanding of community function and dynamics.

The importance of microbial communities (MCs) cannot be overstated. MCs underpin the biogeochemical cycles of the earth's soil, oceans and the atmosphere, and perform ecosystem functions that impact plants, animals and humans. Yet our ability to predict and manage the function of these highly complex, dynamically changing communities is limited. Building predictive models that link MC composition to function is a key emerging challenge in microbial ecology. Here, we argue that addressing this challenge requires close coordination of experimental data collection and method development with mathematical model building. We discuss specific examples where model-experiment integration has already resulted in important insights into MC function and structure. We also highlight key research questions that still demand better integration of experiments and models. We argue that such integration is needed to achieve significant progress in our understanding of MC dynamics and function, and we make specific practical suggestions as to how this could be achieved

Biofilm engineering: Linking biofilm development at different length and time scales

ISSN:1569-1705ISSN:1572-982

Conservation of acquired morphology and community structure in aged biofilms after facing environmental stress

International audienceThe influence of growth history on biofilm morphology and microbial community structure is poorly studied despite its important role for biofilm development. Here, biofilms were exposed to a change in hydrodynamic conditions at different growth stages and we observed how biofilm age affected the change in morphology and bacterial community structure. Biofilms were developed in two bubble column reactors, one operated under constant shear stress and one under variable shear stress. Biofilms were transferred from one reactor to the other at different stages in their development by withdrawing and inserting the support medium from one reactor to the other. The developments of morphology and microbial community structure were followed by image analysis and molecular tools. When transferred early in biofilm development, biofilms adapted to the new hydrodynamic conditions and adopted features of the biofilm already developed in the receiving reactor. Biofilms transferred at a late state of biofilm development continued their initial trajectories of morphology and community development even in a new environment. These biofilms did not immediately adapt to their new environment and kept features acquired during their early growth phase, a property we called memory effect