Literature DB >> 27223402

Imaging flow cytometry for phytoplankton analysis.

Veronika Dashkova1, Dmitry Malashenkov2, Nicole Poulton3, Ivan Vorobjev4, Natasha S Barteneva5.   

Abstract

This review highlights the concepts and instrumentation of imaging flow cytometry technology and in particular its use for phytoplankton analysis. Imaging flow cytometry, a hybrid technology combining speed and statistical capabilities of flow cytometry with imaging features of microscopy, is rapidly advancing as a cell imaging platform that overcomes many of the limitations of current techniques and contributed significantly to the advancement of phytoplankton analysis in recent years. This review presents the various instrumentation relevant to the field and currently used for assessment of complex phytoplankton communities' composition and abundance, size structure determination, biovolume estimation, detection of harmful algal bloom species, evaluation of viability and metabolic activity and other applications. Also we present our data on viability and metabolic assessment of Aphanizomenon sp. cyanobacteria using Imagestream X Mark II imaging cytometer. Herein, we highlight the immense potential of imaging flow cytometry for microalgal research, but also discuss limitations and future developments.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Imaging flow cytometry; Metabolic activity; Microalgae; Phytoplankton; Viability

Mesh:

Substances:

Year:  2016        PMID: 27223402     DOI: 10.1016/j.ymeth.2016.05.007

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  15 in total

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3.  Effects of pre-ozonation on the cell characteristics and N-nitrosodimethylamine formation at three growth phases of Microcystis aeruginosa.

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4.  The Application of Nanopore Sequencing Technology to the Study of Dinoflagellates: A Proof of Concept Study for Rapid Sequence-Based Discrimination of Potentially Harmful Algae.

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Review 5.  Microfluidic Based Optical Microscopes on Chip.

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Journal:  Microbes Environ       Date:  2018-06-16       Impact factor: 2.912

7.  Combining high-throughput imaging flow cytometry and deep learning for efficient species and life-cycle stage identification of phytoplankton.

Authors:  Susanne Dunker; David Boho; Jana Wäldchen; Patrick Mäder
Journal:  BMC Ecol       Date:  2018-12-03       Impact factor: 2.964

8.  Sizing biological cells using a microfluidic acoustic flow cytometer.

Authors:  Eric M Strohm; Vaskar Gnyawali; Joseph A Sebastian; Robert Ngunjiri; Michael J Moore; Scott S H Tsai; Michael C Kolios
Journal:  Sci Rep       Date:  2019-03-18       Impact factor: 4.379

9.  A deep learning-enabled portable imaging flow cytometer for cost-effective, high-throughput, and label-free analysis of natural water samples.

Authors:  Zoltán Gӧrӧcs; Miu Tamamitsu; Vittorio Bianco; Patrick Wolf; Shounak Roy; Koyoshi Shindo; Kyrollos Yanny; Yichen Wu; Hatice Ceylan Koydemir; Yair Rivenson; Aydogan Ozcan
Journal:  Light Sci Appl       Date:  2018-09-19       Impact factor: 17.782

10.  A new method for isolating and analysing coccospheres within sediment.

Authors:  Beth Langley; Paul R Halloran; Ann Power; Rosalind E M Rickaby; Prabhjoat Chana; Poppy Diver; David Thornalley; Christian Hacker; John Love
Journal:  Sci Rep       Date:  2020-11-26       Impact factor: 4.379

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