The application of flow cytometry is well‐established for the characterization of aquatic microbial communities in natural systems . These microbial assemblages are of fundamental importance for the so called “Earth's Critical Zone” (the planet surface including rivers, lakes, and oceans) as they are the main drivers of all biochemical cycles in waters and are responsible for more than half of the global production of oxygen. In waters limited by nutrients (e.g., glaciers, pristine freshwaters, and open oceans), they control energy fluxes and the transport of organic compounds from the surface to the deeper layers, allowing life even in extreme conditions. Finally, they represent the largest part of the biodiversity of marine and freshwaters, having >99% of the aquatic species comprised between bacteria and microscopic organisms .The manuscript by Amalfitano et al. (this issue, page 194; DOI: cyto.a.23304) presents an attractive approach to dredge the cytometric fingerprinting of planktonic microorganisms. Though there are studies providing algorithms to differentiate more cytometric groups , the novel deconvolution model proposed by Amalfitano et al. (this issue) allows sorting out the recurrent cell subgroups within a complex microbial community, without a priori knowledge of the event nature. Deconvolution models have been mainly proposed for
Cytometry – Wiley
Published: Jan 1, 2018
Keywords: ; ;
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