Single Cell Analysis
Virtually all microbial communities on our planet are dominated by a great diversity of uncultured microorganisms, which cannot be studied by traditional approaches in microbiology. In their habitats, microbes often coexist in spatially complex assemblies colonising sediments, soils, roots, teeth, the gut, and many other environments with an intricate three-dimensional architecture. Within these consortia, microbes are influenced by numerous abiotic factors (e.g., fluctuations in nutrient concentrations) and involved in a plethora of biotic interactions.
To understand this complex microbial life, we must look directly at single cells and the microscopically small niches where they thrive and interact with other organisms. Only then can we decipher the in situ metabolic activities and symbioses of uncultured microbes. However, single-cell microbiology is an enormous methodological challenge if we consider the tiny size of a microbial cell and the ultra-low amounts of substrates that are taken up, utilised, and exchanged by single cells.
Our methods, at a glance
- Single-cell chemical imaging using NanoSIMS, spontaneous Raman microspectroscopy and stimulated Raman scattering (SRS)
- Visualising and quantifying uncultured microbial cells by fluorescence in situ hybridisation (FISH) and confocal laser scanning microscopy (CLSM)
- 3D visualisation and image analysis software “daime” (developed in-house)
- Single cell manipulation and sorting by laser microdissection
- Flow cytometry and fluorescence activated cell sorting
- Raman-activated microfluidic cell sorting
CeMESS plays a leading role in the development and application of single-cell techniques to study uncultured microorganisms in situ. Our toolbox includes cutting-edge methods for labelling cells with isotope tracers, detecting metabolic activities at the single cell level, monitoring the flow of substrates through microbial communities, resolving 3D localisation patterns of microbial cells, and activity-based cell sorting for down-stream analyses and single-cell genomics. All our research projects make heavy use of these powerful approaches. We continually optimise and adapt our single-cell tools to address new research questions and push their limits of sensitivity, accuracy, and spatial resolution.