Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

High-resolution ISR amplicon sequencing reveals personalized oral microbiome

Background:Sequencing of the 16S rRNA gene has been the standard for studying the composition of microbial communities. While it allows identification of bacteria at the level of species, it does not usually provide sufficient information to resolve at the sub-species level. Species-level resolution is not adequate for studies of transmission or stability, or for exploring subspecies variation in disease association. Current approaches using whole metagenome shotgun sequencing require very high coverage that can be cost-prohibitive and computationally challenging for diverse communities. Thus there is a need for high-resolution, yet cost-effective, high-throughput methods for characterizing microbial communities.Results:Significant improvement in resolution for amplicon-based bacterial community analysis was achieved by combining amplicon sequencing of a high-diversity marker gene, the ribosomal operon ISR, with a probabilistic error modeling algorithm, DADA2. The resolving power of this new approach was compared to that of both standard and high-resolution 16S-based approaches using a set of longitudinal subgingival plaque samples. The ISR strategy achieved a 5.2-fold increase in community richness compared to reference-based 16S rRNA gene analysis, and showed 100% accuracy in predicting the correct source of a clinical sample. Individuals’ microbial communities were highly personalized, and although they exhibited some drift in membership and levels over time, that difference was always smaller than the differences between any two subjects, even after one year. The construction of an ISR database from publicly available genomic sequences allowed us to explore genomic variationwithinspecies, resulting in the identification of multiple variants of the ISR for most species.Conclusions:The ISR approach resulted in significantly improved resolution of communities, and revealed a highly personalized, stable human oral microbiota. Multiple ISR types were observed for all species examined, demonstrating a high level of subspecies variation in the oral microbiota. The approach is high-throughput, high-resolution yet cost-effective, allowing subspecies-level community fingerprinting at a cost comparable to that of 16S rRNA gene amplicon sequencing. It will be useful for a range of applications that require high-resolution identification of organisms, including microbial tracking, community fingerprinting, and potentially for identification of virulence-associated strains.