High resolution single cell analytics to follow microbial community dynamics in anaerobic ecosystems

Analyzing natural anaerobic microbial communities is a challenge and interpretation of the respective members' performances arduous. Strict anaerobes are often slow-growing and difficult to cultivate due to their unknown physiological capacities. Additionally, abiotic micro-environmental data are difficult to assess, limiting the information on the eco-chemical background in natural environments. This review describes how qualitative and quantitative data can be obtained on anaerobic microbial communities isolated from anoxic environments and treated under laboratory conditions. It gives information on how community composition ('phylogenetic fingerprint') and community structure ('cytometric fingerprint') can be described by PCR-based and single cell-based techniques, respectively. A cell sorting step combined both approaches and enabled quantitative and more precise community resolution. The community dynamics found were swift and strong, despite low and slow changes in measured abiotic parameters. Therefore, the community structure itself mirrored variation in the constructed long term (6years) ecosystem in a most sensitive way and can be used as sensor for the ecosystems situation. New statistical tools are presented allowing suddenly changing performances of complex communities to be detected and community (in) stabilities to be monitored and/or predicted.