Working group 2: Microbiology

Successful AD requires long-term, stable and efficient metabolic conversions to be maintained, despite real-world process fluctuations. Further development and optimisation of AD requires better knowledge of the mechanisms occurring on a microscale, which should in turn be linked to the macroscale system performance and behaviour. Despite this, the relationship between the dynamic behaviour of microbial communities and environmental parameters in AD has hardly been studied . Indeed, there is a pressing need for more and better information on the biology, rates and limitations of microbially-mediated processes. Thus, the weakest component of many AD bioreactor operations is the available information on the structure, dynamics and functions of the microbial community underpinning digestion and biogas production. WG2 will focus on the microbial populations comprising AD biofilms and the impact of TMs, and of changing TM concentrations in bioreactors, on community structure; population dynamics; and the metabolism of individual trophic groups and the meta-community. An innovative and holistic approach is the basis for this task, integrating polyomics (genomics, transcriptomics, metabolomics and fluxomics), microfluidic cell counting and sorting, and ecological modelling will be explored.

System approaches such as this determine the DNA sequences of the meta-organism under study; the collectively-transcribed RNA; the translated proteins; and the metabolites resulting from cellular processes. Ultimately, the goal is to allow for in silico prediction of ecosystem attributes, which, in the AD context, should support process optimisation with reference to TM concentrations and bioavailabity, and the development of new applications. Metagenomic data accounts for the functional potential of the ecosystem, but does not provide many insights into microbial activity. Metatranscriptomics is one step closer to the identification of active metabolic pathways, but does not allow for translational regulation to be taken into consideration. Metaproteomics provides significant insights into microbial activity together with metabolomics, which is the study of the intermediate and end-product of cellular processes. The application of proteomics in conjunction with metabolomics has been demonstrated in an acid mine drainage ecosystem. In turn, the analysis of metabolites strengthens metaproteomics results with respect to the identification of active metabolic pathways, but it can also, through the application of labelled substrates, elucidate the metabolic fluxes of cells and interactions taking place within microbial populations. Finally, Flux Balance Analysis (FBA) is used to find a set of fluxes through the network that satisfy this stoichiometry. FBA is well established for single species but how best to extend these models to a multi-species community is still an active area of research. In AD, ecosystems biology models have great potential for predicting, and hence supporting optimisation and management of, microbial community function. Thus, the focus of WG2 represents a comprehensive strategy to understand the develop probabilistic models incorporating the stochasticity necessary to reflect the environmental conditions in bioreactors that can be used to identify functionally-important groups of microbial individuals in AD systems, and the impact of TM on those microbes. Finally, WG2 will focus on developing and commercializing quantitative, molecular diagnostics tools to monitor the metals-related ‘health’ of those functional groups.