LAUSR

Microbiomes convoy human life in countless ways. They are an essential part of the human body and interact with its host in countless ways. Currently, extensive microbiome analyses assessing the microbiomes' composition and functions based on sequencing information are still far away from being routine analyses due to the complexity of applied techniques and data analysis, their time demand as well as high costs. With the growing demand for on-time community assessment and monitoring of its dynamic behavior with high resolution, alternative high-throughput methods such as microbial community flow cytometry come into focus. Our flow cytometric approach provides single-cell based high-dimensional data by using only three parameters but for every cell in a system which is enough to characterize whole communities' attributes with high acuity over time. To interpret such complex cytometric time-series data, novel concepts are required. We provide a workflow which is applicable for easy-to-use handling and measurement of microbiomes. Drawing inspiration from macro-ecology, in which a rich set of concepts has been developed for describing population dynamics, we interpret huge sets of community single cell data in an intuitive and actionable way using a series of bioinformatics tools which we either developed or adapted from sequence based evaluation approaches for the interpretation of single cell data. The developed evaluation pipeline tests for e.g. ecological measures such as community assembly, functioning, and evolution. We also addressed the meta-community-concept which is a well acknowledged idea in macro-ecology on how interconnected communities perform. The last concept discusses stability which is a metrics of paramount importance. A fast quantification of stability properties may not only detect disturbances and their impact on the organisms but also allow for on-time microbiome treatment. The workflow's immanent ability to support high temporal sample densities below bacterial generation times provides new insight into the ecology of microbiomes and may also provide access to community control for microbiome based health management. The future developments will facilitate cytometric fingerprinting for human routine diagnostics to be as simple and meaningful as a blood count today.