Deconvolution models for a better understanding of natural microbial communities enumerated by flow‐cytometry

Deconvolution models for a better understanding of natural microbial communities enumerated by... 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Cytometry Wiley

Deconvolution models for a better understanding of natural microbial communities enumerated by flow‐cytometry

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018 International Society for Advancement of Cytometry
ISSN
1552-4922
eISSN
1552-4930
D.O.I.
10.1002/cyto.a.23330
Publisher site
See Article on Publisher Site

Abstract

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

Journal

CytometryWiley

Published: Jan 1, 2018

Keywords: ; ;

References

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