Environmental Engineering Research

Korean Society of Environmental Engineers (대한환경공학회)
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A novel method for cell counting of Microcystis colonies in water resources using a digital imaging flow cytometer and microscope

  • Park, Jungsu (Water Quality Research Center, Korea Water Resources Corporation) ;
  • Kim, Yongje (Department of Civil, Environmental and Construction Engineering, University of Central Florida) ;
  • Kim, Minjae (School of Life Science, Kyungbook National University) ;
  • Lee, Woo Hyoung (Department of Civil, Environmental and Construction Engineering, University of Central Florida)
  • Received : 2018.07.31
  • Accepted : 2018.09.30
  • Published : 2019.09.30
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Abstract

Microcystis sp. is one of the most common harmful cyanobacteria that release toxic substances. Counting algal cells is often used for effective control of harmful algal blooms. However, Microcystis sp. is commonly observed as a colony, so counting individual cells is challenging, as it requires significant time and labor. It is urgent to develop an accurate, simple, and rapid method for counting algal cells for regulatory purposes, estimating the status of blooms, and practicing proper management of water resources. The flow cytometer and microscope (FlowCAM), which is a dynamic imaging particle analyzer, can provide a promising alternative for rapid and simple cell counting. However, there is no accurate method for counting individual cells within a Microcystis colony. Furthermore, cell counting based on two-dimensional images may yield inaccurate results and underestimate the number of algal cells in a colony. In this study, a three-dimensional cell counting approach using a novel model algorithm was developed for counting individual cells in a Microcystis colony using a FlowCAM. The developed model algorithm showed satisfactory performance for Microcystis sp. cell counting in water samples collected from two rivers, and can be used for algal management in fresh water systems.

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References

  1. Cao J, Chu Z, Du Y, Hou Z, Wang S. Phytoplankton dynamics and their relationship with environmental variables of Lake Poyang. Hydrol. Res. 2016;47:249-260. https://doi.org/10.2166/nh.2016.224
  2. Cui YJ, Liu DF, Zhang JL, et al. Diel migration of Microcystis during an algal bloom event in the three Gorges Reservoir, China. Environ. Earth Sci. 2016;75:616. https://doi.org/10.1007/s12665-015-5124-x
  3. Lehman P, Kurobe T, Lesmeister S, Baxa D, Tung A, Teh S. Impacts of the 2014 severe drought on the Microcystis bloom in San Francisco Estuary. Harmful Algae 2017;63:94-108. https://doi.org/10.1016/j.hal.2017.01.011
  4. Rowe M, Anderson E, Wynne T, et al. Vertical distribution of buoyant Microcystis blooms in a Lagrangian particle tracking model for short-term forecasts in Lake Erie. J. Geophys. Res. Oceans 2016;121:5296-5314. https://doi.org/10.1002/2016JC011720
  5. Hyun B, Ju SJ, Ko AR, et al. Thermal effects on the growth and fatty acid composition of four harmful algal bloom species: Possible implications for ichthyotoxicity. Ocean Sci. J. 2016;51:333-342. https://doi.org/10.1007/s12601-016-0029-5
  6. Banares-Espana E, Del Mar Fernandez-Arjona M, Garcia-Sanchez MJ, et al. Sulphide resistance in the cyanobacterium Microcystis aeruginosa: A comparative study of morphology and photosynthetic performance between the sulphide-resistant mutant and the wild-type strain. Microb. Ecol. 2016;71:860-872. https://doi.org/10.1007/s00248-015-0715-3
  7. Otten TG, Crosswell JR, Mackey S, Dreher TW. Application of molecular tools for microbial source tracking and public health risk assessment of a Microcystis bloom traversing 300 km of the Klamath River. Harmful Algae 2015;46:71-81. https://doi.org/10.1016/j.hal.2015.05.007
  8. Falconer IR. Algal toxins and human health. In: Hrubec J, ed. Quality and treatment of drinking water II. Berlin: Springer-Verlag; 1998. p. 57-73.
  9. Codd GA, Morrison LF, Metcalf JS. Cyanobacterial toxins: Risk management for health protection. Toxicol. Appl. Pharmacol. 2005;203:264-272. https://doi.org/10.1016/j.taap.2004.02.016
  10. Carmichael WW, Azevedo S, An JS, et al. Human fatalities from cyanobacteria: Chemical and biological evidence for cyanotoxins. Environ. Health Perspect. 2001;109:663-668. https://doi.org/10.1289/ehp.01109663
  11. Taranu ZE, Gregory-Eaves I, Steele RJ, Beaulieu M, Legendre P. Predicting microcystin concentrations in lakes and reservoirs at a continental scale: A new framework for modelling an important health risk factor. Global Ecol. Biogeogr. 2017;26:625-637. https://doi.org/10.1111/geb.12569
  12. Oberholster PJ, Botha AM, Cloete TE. An overview of toxic freshwater cyanobacteria in South Africa with special reference to risk, impact and detection by molecular marker tools. Biokemistri 2005;17:57-71.
  13. Dove A, Chapra SC. Long-term trends of nutrients and trophic response variables for the Great Lakes. Limnol. Oceanogr. 2015;60:696-721. https://doi.org/10.1002/lno.10055
  14. Wang C, Wu X, Tian C, et al. A quantitative protocol for rapid analysis of cell density and size distribution of pelagic and benthic Microcystis colonies by FlowCAM. J. Appl. Phycol. 2015;27:711-720. https://doi.org/10.1007/s10811-014-0352-0
  15. Garmendia M, Revilla M, Zarauz L. Testing the usefulness of a simple automatic method for particles abundance and size determination to derive cost-effective biological indicators in large monitoring networks. Hydrobiologia 2013;704:231-252. https://doi.org/10.1007/s10750-012-1400-x
  16. Paerl HW, Valdes LM, Pinckney JL, Piehler MF, Dyble J, Moisander PH. Phytoplankton photopigments as indicators of estuarine and coastal eutrophication. BioScience 2003;53:953-964. https://doi.org/10.1641/0006-3568(2003)053[0953:PPAIOE]2.0.CO;2
  17. Mouillot D, Spatharis S, Reizopoulou S, et al. Alternatives to taxonomic-based approaches to assess changes in transitional water communities. Aquat. Conserv. 2006;16:469-482. https://doi.org/10.1002/aqc.769
  18. National Health and Medical Research Council (NHMRC). Guidelines for managing risks in recreational water. Australian Government, Canberra, Australia. 2008. p. 91-116.
  19. Chorus I, Bartram J. Toxic cyanobacteria in water: A guide to their public health consequences, monitoring and management. 1st ed. New York: World Health Organization; 1999. p. 334-361.
  20. Wood SA, Hamilton DP, Paul WJ, Safi KA, Williamson WM. New Zealand guidelines for cyanobacteria in recreational fresh waters. Wellington, New Zealand: Ministry for the Environment and Ministry of Health; 2009. p. 9-20.
  21. Romero-Martinez L, Van Slooten C, Nebot E, Acevedo-Merino A, Peperzak L. Assessment of imaging-in-flow system (FlowCAM) for systematic ballast water management. Sci. Total Environ. 2017;603:550-561. https://doi.org/10.1016/j.scitotenv.2017.06.070
  22. Sieracki CK, Sieracki ME, Yentsch CS. An imaging-in-flow system for automated analysis of marine microplankton. Mar. Ecol. Prog. Ser. 1998;168:285-296. https://doi.org/10.3354/meps168285
  23. Dashkova V, Malashenkov D, Poulton N, Vorobjev I, Barteneva NS. Imaging flow cytometry for phytoplankton analysis. Methods 2017;112:188-200. https://doi.org/10.1016/j.ymeth.2016.05.007
  24. Poulton NJ, Martin JL. Imaging flow cytometry for quantitative phytoplankton analysis-FlowCAM. Microscopic and molecular methods for quantitative phytoplankton analysis. Intergovernmental Oceanographic Commission Manuals and Guides of UNESCO. 2010. p. 47-54.
  25. Poulton NJ. FlowCAM: Quantification and classification of phytoplankton by imaging flow cytometry. In: Barteneva N, Vorobjev I, eds. Imaging flow cytometry: Methods and protocols in molecular biology. New York: Springer; 2016. p. 237-247.
  26. Wong E, Sastri AR, Lin FS, Hsieh CH. Modified FlowCAM procedure for quantifying size distribution of zooplankton with sample recycling capacity. PloS One 2017;12:e0175235. https://doi.org/10.1371/journal.pone.0175235
  27. Milde AS, Richardson WB, Strauss EA, Larson JH, Vallazza J, Knights BC. Spatial and temporal dynamics of suspended particle characteristics and composition in navigation Pool 19 of the upper Mississippi River. River Res. Appl. 2017;33:740-752. https://doi.org/10.1002/rra.3131
  28. Le Bourg B, Cornet-Barthaux V, Pagano M, Blanchot J. FlowCAM as a tool for studying small ($80-1000{\mu}m$) metazooplankton communities. J. Plankton Res. 2015;37:666-670. https://doi.org/10.1093/plankt/fbv025
  29. Park J, Wang D, Lee WH. Evaluation of weir construction on water quality related to algal blooms in the Nakdong River. Environ. Earth Sci. 2018;77:408. https://doi.org/10.1007/s12665-018-7590-4
  30. Briand E, Escoffier N, Straub C, Sabart M, Quiblier C, Humbert JF. Spatiotemporal changes in the genetic diversity of a bloom-forming Microcystis aeruginosa (cyanobacteria) population. ISME J. 2009;3:419-429. https://doi.org/10.1038/ismej.2008.121
  31. Kurmayer R, Christiansen G, Chorus I. The abundance of microcystin- producing genotypes correlates positively with colony size in Microcystis sp. and determines its microcystin net production in Lake Wannsee. Appl. Environ. Microbiol. 2003;69:787-795. https://doi.org/10.1128/AEM.69.2.787-795.2003
  32. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. T. ASABE 2007;50:885-900. https://doi.org/10.13031/2013.23153
  33. Golmohammadi G, Prasher S, Madani A, Rudra R. Evaluating three hydrological distributed watershed models: MIKE-SHE, APEX, SWAT. Hydrology 2014;1:20-39. https://doi.org/10.3390/hydrology1010020

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