Effects of herbicide exposure on growth of the cyanobacteria Microcystis aeruginosa (Cyanophyta) (NESP 3.1.5, AIMS and JCU)

This dataset shows the effects of imazapic (detected in the Great Barrier Reef catchments) on the growth rate (from cell density data) on the cyanobacteria Microcystis aeruginosa over a 72 hour exposure period during laboratory experiments conducted in 2019. The aims of this project were to develop and apply standard ecotoxicology protocols to determine the effects of Photosystem II (PSII) and alternative herbicides on the growth of the cyanobacteria Microcystis aeruginosa. Growth bioassays were performed over 3-day exposures using imazapic which has been detected in the Great Barrier Reef catchment area (O’Brien et al. 2016). This toxicity data will enable improved assessment of the risks posed by the herbicide imazapic to cyanobacteria for both regulatory purposes and for comparison with other taxa. Methods: The cyanobacteria Microcystis aeruginosa (Kutzing) Kutzing 1846 (Cyanophyceae) (CS338/01) was purchased from the Australian National Algae Supply Service, Hobart (CSIRO). Cultures of M. aeruginosa were established in MLA medium (Bolch and Blackburn 1996). Cultures were maintained in sterile 250 mL Erlenmeyer flasks as batch cultures in exponential growth phase with weekly transfers of 1 - 3 mL of a 7 day-old M. aeruginosa suspension to 100 mL MLA medium under sterile conditions. Clean culture solutions were maintained at 26 ± 2°C, and under a 12:12 h light:dark cycle (91 ± 12 µmol photons m–2 s–1). Imazapic stock solution was prepared using PESTANAL (Sigma-Aldrich) analytical grade (HPLC greater than or equal to 98%) imazapic (CAS 104098-48-8). The selection of imazapic was based on application rates and detection in coastal waters of the GBR (Grant et al. 2017, O’Brien et al. 2016). Imazapic stock solution was prepared in 1 L volumetric flasks using milli-Q water. Imazapic was dissolved using analytical grade methanol (final concentration < 0.01% (v/v) in exposures). Cultures of M. aeruginosa were exposed to a range of herbicide concentrations over a period of 72 h. The inoculum was taken from cultures in the exponential growth phase (4 - 7-day-old cultures). A M. aeruginosa working suspension was prepared in a 100 mL volumetric flask. A 1:10 and 1:100 dilution was prepared and counted using a haemocytometer under a compound microscope to determine appropriate dilution volumes. The pre-determined inoculum was added to 50 mL of each test and control treatment replicates to the required dilution (3.1 x 104 cells / mL). A control (no herbicide) and solvent control treatment was added to support the validity of the test protocols and to monitor continued performance of the assays. All treatment concentrations were prepared in 0.5x strength MLA medium. Replicates were incubated at 26.6 ± 0.5 °C under a 12:12 h light:dark cycle (59 ± 9.7 µmol photons m–2 s–1). Sub-samples were taken from each replicate to measure cell densities of algal populations at 72 h using a haemocytometer under phase contrast conditions. Cell counts were done manually. Specific growth rates (SGR) were expressed as the logarithmic increase in cell density from day i (ti) to day j (tj) as per equation (1), where SGRi-j is the specific growth rate from time i to j; Xj is the cell density at day j and Xi is the cell density at day i (OECD 2011). SGR i-j = [(ln Xj - ln Xi )/(tj - ti )] (day-1) (1) SGR relative to the solvent control treatment was used to derive chronic effect values for growth inhibition. A test was considered valid if the SGR of solvent control replicates was ? 0.92 day-1 (OECD 2011). Physical and chemical characteristics (pH, electrical conductivity and temperature) of each treatment solution was measured at 0 hr and 72 hr. Growth cabinet temperature was logged in 15-min intervals over the total test duration. Analytical samples were taken at 0 hr and 72 hr. Mean percent inhibition in SGR of each treatment relative to the control treatment was calculated as per equation (2)(OECD 2011), where Xcontrol is the average SGR of solvent control and Xtreatment is the average SGR or Delta F/Fm’ of single treatments. % Inhibition = [(X control - X treatment )/X control] x 100 (2) Format: Microcystis aeruginosa herbicide toxicity data_eAtlas.xlsx Data Dictionary: There are two tabs in the spreadsheet. The first tab corresponds to the specific growth rate (SGR) data; the second tab shows the measured water quality (WQ) parameters (pH, electrical conductivity, and temperature) for the test. For the Imazapic_SGR tab: SGR = specific growth rate – the logarithmic increase from day 0 to day 3 Nominal (µg/L) = nominal herbicide concentrations used in the bioassays; SC denotes solvent control which is no herbicide and contains less than 0.01% v/v solvent carrier as per the treatments Measured (µg/L) = measured concentrations analysed by The University of Queensland Rep = Replicate: for SGR, notation is 1-3 T3_CellsPer_ml = cell density at day 3 ln(day3) = natural logarithm of cell density at day 3 Average T0_CellsPer_ml = average cell density at day 0 ln(Day0) = natural logarithm of cell density at day 0 References: Bolch, C. J. S. and Blackburn S. I. (1996). Isolation and purification of Australian isolates of the toxic cyanobacterium Microcystis aeruginosa Kütz. Journal of Applied Phycology 8, 5-13 Grant, S., Gallen, C., Thompson, K., Paxman, C., Tracey, D. and Mueller, J. (2017) Marine Monitoring Program: Annual Report for inshore pesticide monitoring 2015-2016. Report for the Great Barrier Reef Marine Park Authority, Great Barrier Reef Marine Park Authority, Townsville, Australia. 128 pp, http://dspace-prod.gbrmpa.go...017/13325 Kützing, F.T. (1846). Tabulae phycologicae; oder, Abbildungen der Tange. Vol. I, fasc. 1 pp. 1-8, pls 1-10. Nordhausen: Gedruckt auf kosten des Verfassers (in commission bei W. Köhne) Mercurio, P., Eaglesham, G., Parks, S., Kenway, M., Beltran, V., Flores, F., Mueller, J.F. and Negri, A.P. (2018) Contribution of transformation products towards the total herbicide toxicity to tropical marine organisms. Scientific Reports 8(1), 4808. O’Brien, D., Lewis, S., Davis, A., Gallen, C., Smith, R., Turner, R., Warne, M., Turner, S., Caswell, S. and Mueller, J.F. (2016) Spatial and temporal variability in pesticide exposure downstream of a heavily irrigated cropping area: application of different monitoring techniques. Journal of Agricultural and Food Chemistry 64(20), 3975-3989. OECD (2011) OECD guidelines for the testing of chemicals: freshwater alga and cyanobacteria, growth inhibition test, Test No. 201. https://search.oecd.org/env/...23-en.htm. Data Location: This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.5_Pesticide-guidelines-GBR

Principal Investigator
Templeman, Michelle TropWATER, James Cook University (JCU)
Co Investigator
Mueller, Jochen University of Queensland, Queensland Alliance for Environmental Health Science (QAEHS)
Co Investigator
Elisei, Gabriele University of Queensland, Queensland Alliance for Environmental Health Science (QAEHS)
Co Investigator
Sarit, Kaserzon University of Queensland, Queensland Alliance for Environmental Health Science (QAEHS)
Point Of Contact
Templeman, Michelle TropWATER, James Cook University (JCU) Shelley.Templeman@jcu.edu.au

Data collected from 28 Aug 2018 until 15 Dec 2019

Data Usage Constraints
  • Attribution 3.0 Australia