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First Application of IFCB High-Frequency Imaging-in-Flow Cytometry to Investigate Bloom-Forming Filamentous Cyanobacteria in the Baltic Sea
Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as...
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Published in: | Frontiers in Marine Science 2021-03, Vol.8 |
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creator | Kraft, Kaisa Seppälä, Jukka Hällfors, Heidi Suikkanen, Sanna Ylöstalo, Pasi Anglès, Sílvia Kielosto, Sami Kuosa, Harri Laakso, Lauri Honkanen, Martti Lehtinen, Sirpa Oja, Johanna Tamminen, Timo |
description | Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea,
Aphanizomenon flosaquae
and
Dolichospermum
spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of
Dolichospermum
.
Aphanizomenon
biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms. |
doi_str_mv | 10.3389/fmars.2021.594144 |
format | article |
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Aphanizomenon flosaquae
and
Dolichospermum
spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of
Dolichospermum
.
Aphanizomenon
biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms.</description><identifier>ISSN: 2296-7745</identifier><identifier>EISSN: 2296-7745</identifier><identifier>DOI: 10.3389/fmars.2021.594144</identifier><language>eng</language><publisher>Lausanne: Frontiers Research Foundation</publisher><subject>Aquatic ecosystems ; Automation ; Biomass ; bloom dynamics ; Blooms ; Climate change ; Community composition ; Continuous flow ; Cyanobacteria ; cyanophyte ; Dolichospermum ; Driving ability ; Dynamics ; Ecological function ; Environmental changes ; Environmental factors ; Eutrophication ; Flow cytometry ; high-frequency observations ; IFCB ; Imaging FlowCytobot ; Imaging techniques ; Microscopy ; Monitoring methods ; Nitrogen ; Optical properties ; Oscillatoriales ; Phytoplankton ; Plankton ; Remote sensing ; Surface water ; Water analysis ; Water masses ; Water quality ; Water sampling ; Water temperature ; Wind ; Wind speed</subject><ispartof>Frontiers in Marine Science, 2021-03, Vol.8</ispartof><rights>2021. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c382t-ec2bf8a570dd9927b41ba551a5e973f70847d0af3d5d60b369eebd77596840673</citedby><cites>FETCH-LOGICAL-c382t-ec2bf8a570dd9927b41ba551a5e973f70847d0af3d5d60b369eebd77596840673</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2505021727/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2505021727?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Kraft, Kaisa</creatorcontrib><creatorcontrib>Seppälä, Jukka</creatorcontrib><creatorcontrib>Hällfors, Heidi</creatorcontrib><creatorcontrib>Suikkanen, Sanna</creatorcontrib><creatorcontrib>Ylöstalo, Pasi</creatorcontrib><creatorcontrib>Anglès, Sílvia</creatorcontrib><creatorcontrib>Kielosto, Sami</creatorcontrib><creatorcontrib>Kuosa, Harri</creatorcontrib><creatorcontrib>Laakso, Lauri</creatorcontrib><creatorcontrib>Honkanen, Martti</creatorcontrib><creatorcontrib>Lehtinen, Sirpa</creatorcontrib><creatorcontrib>Oja, Johanna</creatorcontrib><creatorcontrib>Tamminen, Timo</creatorcontrib><title>First Application of IFCB High-Frequency Imaging-in-Flow Cytometry to Investigate Bloom-Forming Filamentous Cyanobacteria in the Baltic Sea</title><title>Frontiers in Marine Science</title><description>Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea,
Aphanizomenon flosaquae
and
Dolichospermum
spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of
Dolichospermum
.
Aphanizomenon
biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms.</description><subject>Aquatic ecosystems</subject><subject>Automation</subject><subject>Biomass</subject><subject>bloom dynamics</subject><subject>Blooms</subject><subject>Climate change</subject><subject>Community composition</subject><subject>Continuous flow</subject><subject>Cyanobacteria</subject><subject>cyanophyte</subject><subject>Dolichospermum</subject><subject>Driving ability</subject><subject>Dynamics</subject><subject>Ecological function</subject><subject>Environmental changes</subject><subject>Environmental factors</subject><subject>Eutrophication</subject><subject>Flow cytometry</subject><subject>high-frequency observations</subject><subject>IFCB</subject><subject>Imaging FlowCytobot</subject><subject>Imaging techniques</subject><subject>Microscopy</subject><subject>Monitoring methods</subject><subject>Nitrogen</subject><subject>Optical properties</subject><subject>Oscillatoriales</subject><subject>Phytoplankton</subject><subject>Plankton</subject><subject>Remote sensing</subject><subject>Surface water</subject><subject>Water analysis</subject><subject>Water masses</subject><subject>Water quality</subject><subject>Water sampling</subject><subject>Water temperature</subject><subject>Wind</subject><subject>Wind speed</subject><issn>2296-7745</issn><issn>2296-7745</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpNkc9u1DAQxiMEElXpA3CzxDmL_8bxsV0RGqkSB-BsjWMn9SqxF9sL2mfgpfF2EeI0o9E333yaX9O8J3jHWK8-zhukvKOYkp1QnHD-qrmhVHWtlFy8_q9_29zlfMAYE8ax4Oqm-T34lAu6Px5XP0HxMaA4o3HYP6BHvzy3Q3I_Ti5MZzRusPiwtD60wxp_of25xM2VdEYlojH8dLn4BYpDD2uMWzvEtFU5GvwKmwslnnJdgRANTMUlD8gHVJ6rHNbiJ_TVwbvmzQxrdnd_623zffj0bf_YPn35PO7vn9qJ9bS0bqJm7kFIbK1SVBpODAhBQDgl2Sxxz6XFMDMrbIcN65RzxkopVNdz3El224xXXxvhoI_J1_eddQSvXwYxLRpSzbQ6ba3BUk7SGHDc2s5g64QCogjMhvOuen24eh1TrI_KRR_iKYUaX1OBRUUi6eUiuaqmFHNObv53lWB9QahfEOoLQn1FyP4AsKSRUg</recordid><startdate>20210325</startdate><enddate>20210325</enddate><creator>Kraft, Kaisa</creator><creator>Seppälä, Jukka</creator><creator>Hällfors, Heidi</creator><creator>Suikkanen, Sanna</creator><creator>Ylöstalo, Pasi</creator><creator>Anglès, Sílvia</creator><creator>Kielosto, Sami</creator><creator>Kuosa, Harri</creator><creator>Laakso, Lauri</creator><creator>Honkanen, Martti</creator><creator>Lehtinen, Sirpa</creator><creator>Oja, Johanna</creator><creator>Tamminen, Timo</creator><general>Frontiers Research Foundation</general><general>Frontiers Media S.A</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TN</scope><scope>7XB</scope><scope>88I</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M2P</scope><scope>M7P</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>DOA</scope></search><sort><creationdate>20210325</creationdate><title>First Application of IFCB High-Frequency Imaging-in-Flow Cytometry to Investigate Bloom-Forming Filamentous Cyanobacteria in the Baltic Sea</title><author>Kraft, Kaisa ; Seppälä, Jukka ; Hällfors, Heidi ; Suikkanen, Sanna ; Ylöstalo, Pasi ; Anglès, Sílvia ; Kielosto, Sami ; Kuosa, Harri ; Laakso, Lauri ; Honkanen, Martti ; Lehtinen, Sirpa ; Oja, Johanna ; Tamminen, Timo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c382t-ec2bf8a570dd9927b41ba551a5e973f70847d0af3d5d60b369eebd77596840673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aquatic ecosystems</topic><topic>Automation</topic><topic>Biomass</topic><topic>bloom dynamics</topic><topic>Blooms</topic><topic>Climate change</topic><topic>Community composition</topic><topic>Continuous flow</topic><topic>Cyanobacteria</topic><topic>cyanophyte</topic><topic>Dolichospermum</topic><topic>Driving ability</topic><topic>Dynamics</topic><topic>Ecological function</topic><topic>Environmental changes</topic><topic>Environmental factors</topic><topic>Eutrophication</topic><topic>Flow cytometry</topic><topic>high-frequency observations</topic><topic>IFCB</topic><topic>Imaging FlowCytobot</topic><topic>Imaging techniques</topic><topic>Microscopy</topic><topic>Monitoring methods</topic><topic>Nitrogen</topic><topic>Optical properties</topic><topic>Oscillatoriales</topic><topic>Phytoplankton</topic><topic>Plankton</topic><topic>Remote sensing</topic><topic>Surface water</topic><topic>Water analysis</topic><topic>Water masses</topic><topic>Water quality</topic><topic>Water sampling</topic><topic>Water temperature</topic><topic>Wind</topic><topic>Wind speed</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kraft, Kaisa</creatorcontrib><creatorcontrib>Seppälä, Jukka</creatorcontrib><creatorcontrib>Hällfors, Heidi</creatorcontrib><creatorcontrib>Suikkanen, Sanna</creatorcontrib><creatorcontrib>Ylöstalo, Pasi</creatorcontrib><creatorcontrib>Anglès, Sílvia</creatorcontrib><creatorcontrib>Kielosto, Sami</creatorcontrib><creatorcontrib>Kuosa, Harri</creatorcontrib><creatorcontrib>Laakso, Lauri</creatorcontrib><creatorcontrib>Honkanen, Martti</creatorcontrib><creatorcontrib>Lehtinen, Sirpa</creatorcontrib><creatorcontrib>Oja, Johanna</creatorcontrib><creatorcontrib>Tamminen, Timo</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Oceanic Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>Biological Sciences</collection><collection>ProQuest Science Journals</collection><collection>Biological Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content (ProQuest)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Directory of Open Access Journals</collection><jtitle>Frontiers in Marine Science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kraft, Kaisa</au><au>Seppälä, Jukka</au><au>Hällfors, Heidi</au><au>Suikkanen, Sanna</au><au>Ylöstalo, Pasi</au><au>Anglès, Sílvia</au><au>Kielosto, Sami</au><au>Kuosa, Harri</au><au>Laakso, Lauri</au><au>Honkanen, Martti</au><au>Lehtinen, Sirpa</au><au>Oja, Johanna</au><au>Tamminen, Timo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>First Application of IFCB High-Frequency Imaging-in-Flow Cytometry to Investigate Bloom-Forming Filamentous Cyanobacteria in the Baltic Sea</atitle><jtitle>Frontiers in Marine Science</jtitle><date>2021-03-25</date><risdate>2021</risdate><volume>8</volume><issn>2296-7745</issn><eissn>2296-7745</eissn><abstract>Cyanobacteria are an important part of phytoplankton communities, however, they are also known for forming massive blooms with potentially deleterious effects on recreational use, human and animal health, and ecosystem functioning. Emerging high-frequency imaging flow cytometry applications, such as Imaging FlowCytobot (IFCB), are crucial in furthering our understanding of the factors driving bloom dynamics, since these applications provide community composition information at frequencies impossible to attain using conventional monitoring methods. However, the proof of applicability of automated imaging applications for studying dynamics of filamentous cyanobacteria is still scarce. In this study we present the first results of IFCB applied to a Baltic Sea cyanobacterial bloom community using a continuous flow-through setup. Our main aim was to demonstrate the pros and cons of the IFCB in identifying filamentous cyanobacterial taxa and in estimating their biomass. Selected environmental parameters (water temperature, wind speed and salinity) were included, in order to demonstrate the dynamics of the system the cyanobacteria occur in and the possibilities for analyzing high-frequency phytoplankton observations against changes in the environment. In order to compare the IFCB results with conventional monitoring methods, filamentous cyanobacteria were enumerated from water samples using light microscopical analysis. Two common bloom forming filamentous cyanobacteria in the Baltic Sea,
Aphanizomenon flosaquae
and
Dolichospermum
spp. dominated the bloom, followed by an increase in Oscillatoriales abundance. The IFCB results compared well with the results of the light microscopical analysis, especially in the case of
Dolichospermum
.
Aphanizomenon
biomass varied slightly between the methods and the Oscillatoriales results deviated the most. Bloom formation was initiated as water temperature increased to over 15°C and terminated as the wind speed increased, dispersing the bloom. Community shifts were closely related to movements of the water mass. We demonstrate how using a high-frequency imaging flow cytometry application can help understand the development of cyanobacteria summer blooms.</abstract><cop>Lausanne</cop><pub>Frontiers Research Foundation</pub><doi>10.3389/fmars.2021.594144</doi><oa>free_for_read</oa></addata></record> |
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subjects | Aquatic ecosystems Automation Biomass bloom dynamics Blooms Climate change Community composition Continuous flow Cyanobacteria cyanophyte Dolichospermum Driving ability Dynamics Ecological function Environmental changes Environmental factors Eutrophication Flow cytometry high-frequency observations IFCB Imaging FlowCytobot Imaging techniques Microscopy Monitoring methods Nitrogen Optical properties Oscillatoriales Phytoplankton Plankton Remote sensing Surface water Water analysis Water masses Water quality Water sampling Water temperature Wind Wind speed |
title | First Application of IFCB High-Frequency Imaging-in-Flow Cytometry to Investigate Bloom-Forming Filamentous Cyanobacteria in the Baltic Sea |
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