Scheda di dettaglio – i prodotti della ricerca
| Dato | Valore |
|---|---|
| Title | Deconvolution model to resolve cytometric microbial community patterns in flowing waters |
| Abstract | Flow cytometry is suitable to discriminate and quantify aquatic microbial cells within a spectrum of fluorescence and light scatter signals. Using fixed gating and operational settings, we developed a finite distribution mixture model, followed by the Voronoi tessellation, to resolve bivariate cytometric profiles into cohesive subgroups of events. This procedure was applied to outline recurrent patterns and quantitative changes of the aquatic microbial community along a river hydrologic continuum. We found five major subgroups within each of the commonly retrieved populations of cells with Low and High content of Nucleic Acids (namely, LNA, and HNA cells). Moreover, the advanced analysis allowed assessing changes of community patterns perturbed by a wastewater feed. Our approach for cytometric data deconvolution confirmed that flow cytometry could represent a prime candidate technology for assessing microbial community patterns in flowing waters. (c) 2017 International Society for Advancement of Cytometry |
| Source | Cytometry. Part A 93A (2), pp. 194–200 |
| Keywords | flow cytometryriver continuumprokaryotesbacteriacytometric fingerprinting |
| Journal | Cytometry. Part A |
| Editor | Wiley-Liss,, Hoboken, N.J., Stati Uniti d'America |
| Year | 2018 |
| Type | Articolo in rivista |
| DOI | 10.1002/cyto.a.23304 |
| Authors | Amalfitano, Stefano; Fazi, Stefano; Ejarque, Elisabet; Freixa, Anna; Romani, Anna M.; Butturini, Andrea |
| Text | 398622 2018 10.1002/cyto.a.23304 ISI Web of Science WOS 000426061500009 Scopus 2 s2.0 85042388425 flow cytometry river continuum prokaryotes bacteria cytometric fingerprinting Deconvolution model to resolve cytometric microbial community patterns in flowing waters Amalfitano, Stefano; Fazi, Stefano; Ejarque, Elisabet; Freixa, Anna; Romani, Anna M.; Butturini, Andrea IRSA CNR; WasserCluster Lunz Biol Stn; Catalan Inst Water Res ICRA; Univ Girona; Univ Barcelona Flow cytometry is suitable to discriminate and quantify aquatic microbial cells within a spectrum of fluorescence and light scatter signals. Using fixed gating and operational settings, we developed a finite distribution mixture model, followed by the Voronoi tessellation, to resolve bivariate cytometric profiles into cohesive subgroups of events. This procedure was applied to outline recurrent patterns and quantitative changes of the aquatic microbial community along a river hydrologic continuum. We found five major subgroups within each of the commonly retrieved populations of cells with Low and High content of Nucleic Acids namely, LNA, and HNA cells . Moreover, the advanced analysis allowed assessing changes of community patterns perturbed by a wastewater feed. Our approach for cytometric data deconvolution confirmed that flow cytometry could represent a prime candidate technology for assessing microbial community patterns in flowing waters. c 2017 International Society for Advancement of Cytometry 93A Published version Deconvolution model to resolve cytometric microbial community patterns in flowing waters Versione allegata Amalfitano_2018_CytometryA_Deconvolution model.pdf Articolo in rivista Wiley Liss, 1552 4922 Cytometry. Part A Cytometry. Part A Cytometry, Part A Cytometry. stefano.fazi FAZI STEFANO stefano.amalfitano AMALFITANO STEFANO |