Identifying Metabolically Active Microbial Populations in Anaerobic Digestion Through Bioorthogonal Non-Canonical Amino Acid Tagging and Affinity-Based Cell Separation

Our understanding of microbial communities associated with anaerobic digestion (AD) currently relies strongly on metagenomic sequencing, which can reveal phylogenetic diversity, but does not provide information concerning microbial activity or the close associations that may form between syntrophic organisms. Approaches that facilitate charting of process-targeted variation in microbial community activities are important for understanding how the microbiology of AD functions as a single biological machine. Here I identify subsets of metabolically specialised microbes as they respond to substrate availability in AD systems using bioorthogonal non-canonical amino acid tagging (BONCAT) and affinity-based cell separation (ABCS). The results demonstrate the specific labelling, visualisation and separation of microbes that actively participate in volatile fatty acid (VFA) degradation and suggest a differential response to octanoic acid by specialists within the microbial community. Analysis of metagenomic sequences from a time series of BONCAT-ABCS samples reveals that this method enriched a distinct microbial community with genetically-derived metabolisms consistent with and changing according to the observed metabolic outcomes. Proteomic data generated from BONCAT-ABCS help to resolve the functional landscape of enriched microbial community and give better resolution of identified translationally/metabolically active taxa. This enrichment approach allows us to determine the temporal response of those microbes most likely to engage in octanoic acid degradation in AD sludge. This method can be applied to the identification of specialist microbes with a role in degradation of a range of other compounds in AD, enhancing our understanding of microbial community interactions and facilitating the development of strategies for process optimisation.