Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers

Clémentine Gallot; Zéline Hubert; Lumi Haraguchi; Hedy Aardema; Luis Felipe Artigas; Amel Bellaaj Zouari; Arnaud Cauvin; Raffaella Casotti; Véronique Créach; Georges Dubelaar; Alexandre Epinoux; Gérald Grégori; Oliver Grosso; Joanna Kolasinki; Harrie Kools; Rob Lievaart; Arnaud P. Louchart; Glaucia Moreira Fragoso; Maialen Palazot; Machteld Rijkeboer; Kévin Robache; Joseph Rolland; Thomas Rutten; Melilotus Thyssen

doi:10.1002/cyto.a.24964

Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers

Clémentine Gallot^* (Corresponding author), Zéline Hubert, Lumi Haraguchi, Hedy Aardema, Luis Felipe Artigas, Amel Bellaaj Zouari, Arnaud Cauvin, Raffaella Casotti, Véronique Créach, Georges Dubelaar, Alexandre Epinoux, Gérald Grégori, Oliver Grosso, Joanna Kolasinki, Harrie Kools, Rob Lievaart, Arnaud P. Louchart, Glaucia Moreira Fragoso, Maialen Palazot, Machteld RijkeboerKévin Robache, Joseph Rolland, Thomas Rutten, Melilotus Thyssen^* (Corresponding author)

^*Corresponding author for this work

NIOO - Aquatic Ecology (AqE)

Research output: Contribution to journal/periodical › Article › Scientific › peer-review

Abstract

The use of flow cytometry to investigate phytoplankton functional groups is rapidly expanding worldwide, using lab- or ship-based instruments or autonomous environmental monitoring platforms. Automation, coupled with greater autonomy, allows for higher spatial and temporal resolution of phytoplankton groups, enhancing understanding of their dynamics and patterns, generating large datasets. The level of resolution is determined by both instrumental capabilities and optimization of its acquisition settings. Sharing these datasets with the scientific community, whether to improve global phytoplankton distribution resolution or facilitate the intercomparison of environmental indicators among monitoring laboratories, strongly relies on quality-controlled instruments and standardized data acquisition and analysis. This article focuses on CytoSense-type (CytoBuoy, NL) flow cytometers, which operate by recording the optical pulse shapes of particles as they pass through a laser beam. Different configurations such as laser wavelength and power, sheath fluid management, sample inlet design, and dataset output format were not considered, in order to focus on optimization and protocol standardization to resolve the whole phytoplankton size spectrum, from the smallest autofluorescing prokaryotes to colonies and chain-forming species. In this study, coincidence, PMT voltage, trigger threshold optimization, and regular quality control procedures are considered and discussed, using datasets from three types of instruments and two contrasted marine coastal waters as case studies. The primary goal of this study is to establish a framework to guide and support the exploration and application of this type of flow cytometer, ultimately achieving a reliable and optimal resolution for sample acquisition of natural waters.

Original language	English
Journal	Cytometry Part A
DOIs	https://doi.org/10.1002/cyto.a.24964
Publication status	E-pub ahead of print - 16 Oct 2025

Keywords

best practices
coincidence risk
CytoSense
detection optimization
flow cytometry
phytoplankton
quality control
regular maintenance

Access to Document

10.1002/cyto.a.24964Licence: CC BY

Cite this

Gallot, C., Hubert, Z., Haraguchi, L., Aardema, H., Artigas, L. F., Bellaaj Zouari, A., Cauvin, A., Casotti, R., Créach, V., Dubelaar, G., Epinoux, A., Grégori, G., Grosso, O., Kolasinki, J., Kools, H., Lievaart, R., Louchart, A. P., Moreira Fragoso, G., Palazot, M., ... Thyssen, M. (2025). Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers. Cytometry Part A. Advance online publication. https://doi.org/10.1002/cyto.a.24964

@article{e57d5af63a63464487af7b0c0e83a205,

title = "Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers",

abstract = "The use of flow cytometry to investigate phytoplankton functional groups is rapidly expanding worldwide, using lab- or ship-based instruments or autonomous environmental monitoring platforms. Automation, coupled with greater autonomy, allows for higher spatial and temporal resolution of phytoplankton groups, enhancing understanding of their dynamics and patterns, generating large datasets. The level of resolution is determined by both instrumental capabilities and optimization of its acquisition settings. Sharing these datasets with the scientific community, whether to improve global phytoplankton distribution resolution or facilitate the intercomparison of environmental indicators among monitoring laboratories, strongly relies on quality-controlled instruments and standardized data acquisition and analysis. This article focuses on CytoSense-type (CytoBuoy, NL) flow cytometers, which operate by recording the optical pulse shapes of particles as they pass through a laser beam. Different configurations such as laser wavelength and power, sheath fluid management, sample inlet design, and dataset output format were not considered, in order to focus on optimization and protocol standardization to resolve the whole phytoplankton size spectrum, from the smallest autofluorescing prokaryotes to colonies and chain-forming species. In this study, coincidence, PMT voltage, trigger threshold optimization, and regular quality control procedures are considered and discussed, using datasets from three types of instruments and two contrasted marine coastal waters as case studies. The primary goal of this study is to establish a framework to guide and support the exploration and application of this type of flow cytometer, ultimately achieving a reliable and optimal resolution for sample acquisition of natural waters.",

keywords = "best practices, coincidence risk, CytoSense, detection optimization, flow cytometry, phytoplankton, quality control, regular maintenance",

author = "Cl{\'e}mentine Gallot and Z{\'e}line Hubert and Lumi Haraguchi and Hedy Aardema and Artigas, {Luis Felipe} and {Bellaaj Zouari}, Amel and Arnaud Cauvin and Raffaella Casotti and V{\'e}ronique Cr{\'e}ach and Georges Dubelaar and Alexandre Epinoux and G{\'e}rald Gr{\'e}gori and Oliver Grosso and Joanna Kolasinki and Harrie Kools and Rob Lievaart and Louchart, {Arnaud P.} and {Moreira Fragoso}, Glaucia and Maialen Palazot and Machteld Rijkeboer and K{\'e}vin Robache and Joseph Rolland and Thomas Rutten and Melilotus Thyssen",

note = "Publisher Copyright: {\textcopyright} 2025 The Author(s). Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry.",

year = "2025",

month = oct,

day = "16",

doi = "10.1002/cyto.a.24964",

language = "English",

journal = "Cytometry Part A",

issn = "1552-4922",

publisher = "John Wiley and Sons Inc.",

}

Gallot, C, Hubert, Z, Haraguchi, L, Aardema, H, Artigas, LF, Bellaaj Zouari, A, Cauvin, A, Casotti, R, Créach, V, Dubelaar, G, Epinoux, A, Grégori, G, Grosso, O, Kolasinki, J, Kools, H, Lievaart, R, Louchart, AP, Moreira Fragoso, G, Palazot, M, Rijkeboer, M, Robache, K, Rolland, J, Rutten, T & Thyssen, M 2025, 'Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers', Cytometry Part A. https://doi.org/10.1002/cyto.a.24964

TY - JOUR

T1 - Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers

AU - Gallot, Clémentine

AU - Hubert, Zéline

AU - Haraguchi, Lumi

AU - Aardema, Hedy

AU - Artigas, Luis Felipe

AU - Bellaaj Zouari, Amel

AU - Cauvin, Arnaud

AU - Casotti, Raffaella

AU - Créach, Véronique

AU - Dubelaar, Georges

AU - Epinoux, Alexandre

AU - Grégori, Gérald

AU - Grosso, Oliver

AU - Kolasinki, Joanna

AU - Kools, Harrie

AU - Lievaart, Rob

AU - Louchart, Arnaud P.

AU - Moreira Fragoso, Glaucia

AU - Palazot, Maialen

AU - Rijkeboer, Machteld

AU - Robache, Kévin

AU - Rolland, Joseph

AU - Rutten, Thomas

AU - Thyssen, Melilotus

PY - 2025/10/16

Y1 - 2025/10/16

N2 - The use of flow cytometry to investigate phytoplankton functional groups is rapidly expanding worldwide, using lab- or ship-based instruments or autonomous environmental monitoring platforms. Automation, coupled with greater autonomy, allows for higher spatial and temporal resolution of phytoplankton groups, enhancing understanding of their dynamics and patterns, generating large datasets. The level of resolution is determined by both instrumental capabilities and optimization of its acquisition settings. Sharing these datasets with the scientific community, whether to improve global phytoplankton distribution resolution or facilitate the intercomparison of environmental indicators among monitoring laboratories, strongly relies on quality-controlled instruments and standardized data acquisition and analysis. This article focuses on CytoSense-type (CytoBuoy, NL) flow cytometers, which operate by recording the optical pulse shapes of particles as they pass through a laser beam. Different configurations such as laser wavelength and power, sheath fluid management, sample inlet design, and dataset output format were not considered, in order to focus on optimization and protocol standardization to resolve the whole phytoplankton size spectrum, from the smallest autofluorescing prokaryotes to colonies and chain-forming species. In this study, coincidence, PMT voltage, trigger threshold optimization, and regular quality control procedures are considered and discussed, using datasets from three types of instruments and two contrasted marine coastal waters as case studies. The primary goal of this study is to establish a framework to guide and support the exploration and application of this type of flow cytometer, ultimately achieving a reliable and optimal resolution for sample acquisition of natural waters.

AB - The use of flow cytometry to investigate phytoplankton functional groups is rapidly expanding worldwide, using lab- or ship-based instruments or autonomous environmental monitoring platforms. Automation, coupled with greater autonomy, allows for higher spatial and temporal resolution of phytoplankton groups, enhancing understanding of their dynamics and patterns, generating large datasets. The level of resolution is determined by both instrumental capabilities and optimization of its acquisition settings. Sharing these datasets with the scientific community, whether to improve global phytoplankton distribution resolution or facilitate the intercomparison of environmental indicators among monitoring laboratories, strongly relies on quality-controlled instruments and standardized data acquisition and analysis. This article focuses on CytoSense-type (CytoBuoy, NL) flow cytometers, which operate by recording the optical pulse shapes of particles as they pass through a laser beam. Different configurations such as laser wavelength and power, sheath fluid management, sample inlet design, and dataset output format were not considered, in order to focus on optimization and protocol standardization to resolve the whole phytoplankton size spectrum, from the smallest autofluorescing prokaryotes to colonies and chain-forming species. In this study, coincidence, PMT voltage, trigger threshold optimization, and regular quality control procedures are considered and discussed, using datasets from three types of instruments and two contrasted marine coastal waters as case studies. The primary goal of this study is to establish a framework to guide and support the exploration and application of this type of flow cytometer, ultimately achieving a reliable and optimal resolution for sample acquisition of natural waters.

KW - best practices

KW - coincidence risk

KW - CytoSense

KW - detection optimization

KW - flow cytometry

KW - phytoplankton

KW - quality control

KW - regular maintenance

U2 - 10.1002/cyto.a.24964

DO - 10.1002/cyto.a.24964

M3 - Article

AN - SCOPUS:105019210324

SN - 1552-4922

JO - Cytometry Part A

JF - Cytometry Part A

ER -

Best Practices for Optimization of Phytoplankton Analysis in Natural Waters Using CytoSense Flow Cytometers

Abstract

Keywords

Access to Document

Fingerprint

Cite this