Effects of herbicide exposure on growth and photosynthetic efficiency of the microalgae Chlorella sp. (Chlorophyta) (NESP TWQ 3.1.5, AIMS and JCU)

This dataset shows the effects of herbicides (detected in the Great Barrier Reef catchments) on the growth rates (from cell density data) and photosynthesis (effective quantum yield) on the microalgae Chlorella sp. during laboratory experiments conducted from 2017-2019.

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 and photosynthetic efficiency of the microalgae Chlorella sp. Growth bioassays were performed over 3-day exposures using herbicides that have been detected in the Great Barrier Reef catchment area (O’Brien et al. 2016). Effects of herbicides on the photophysiology of Chlorella sp., measured by chlorophyll fluorescence as the effective quantum yield (Delta F/Fm’) were investigated using mini-PAM fluorometry after 72 h herbicide exposure. These toxicity data will enable improved assessment of the risks posed by PSII and alternative herbicides to microalgae for both regulatory purposes and for comparison with other taxa.

Methods:

The chlorophyte Chlorella sp. was sourced from the Supervising Scientist, Department Energy and Environment, Darwin. Cultures of Chlorella sp. were established in MBL medium (Riethmuller et al 2003, Pease et al 2016). 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 Chlorella sp. suspension to 100 mL MBL 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).

Herbicide stock solutions were prepared using PESTANAL (Sigma-Aldrich) analytical grade products (HPLC greater than or equal to 98%): bromacil (CAS 314-40-9), diuron (CAS 330-54-1), haloxyfop-p-methyl (CAS 72619-32-0), hexazinone (CAS 51235-04-2), imazapic (CAS 104098-48-8), isoxaflutole (CAS 141112-29-0), prometryn (CAS 7287-19-6) and propazine (CAS 139-40-2). The selection of herbicides was based on application rates and detection in coastal waters of the GBR (Grant et al. 2017, O’Brien et al. 2016). Stock solutions were prepared in sterile 1 L glass Schott bottles using milli-Q water. Diuron, haloxyfop-p-methyl, hexazinone, isoxaflutole and prometryn were dissolved using analytical grade acetone (< 0.01% (v/v) in exposures). Imazapic was dissolved in methanol (less than or equal to 0.01% (v/v) in exposure). No solvent carrier was used for the preparation of the remaining herbicide stock solutions.

Cultures of Chlorella sp. were exposed to a range of herbicide concentrations over a period of 72 h. Inoculum was taken from cultures in exponential growth phase (4 – 7 day-old cultures). A Chlorella sp. 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 – 3.1 x 104 cells/ mL). In each toxicity test, a control (no herbicide) and solvent control (if used) treatments were added to support the validity of the test protocols and to monitor continued performance of the assays. All treatment solutions were prepared in 0.5x strength MBL medium. Replicates were incubated at 26.6 ± 0.5 °C under a 12:12 h light:dark cycle (190 ± 14 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 and photographed under phase contrast conditions. Cell counts were done either manually or using imageJ from microscope photographs (Rueden et al 2017). 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 control treatment was used to derive chronic effect values for growth inhibition. A test was considered valid, if the SGR of control replicates was greater than or equal to 0.92 day-1 (OECD 2011). Physical and chemical characteristics of each treatment were measured at 0 h and 72 h including pH, electrical conductivity and temperature. Chamber temperature was also logged in 15-min intervals over the total test duration. Analytical samples were taken at 0 h and 72 h.

Effects of herbicides on the photophysiology of Chlorella sp., measured by chlorophyll fluorescence as the effective quantum yield (Delta F/Fm’ ), were investigated at 72 h using mini-PAM fluorometry (mini-PAM, Walz, Germany). Light adapted minimum fluorescence (F) and maximum fluorescence (Fm’) were determined and effective quantum yield was calculated for each treatment as per equation (2)(Schreiber et al. 2002).

Delta F/Fm’ = (Fm’-F)/Fm’ (2)

Mini- PAM settings were set to ETR-F = 0.84, F-Offset = 92, measuring light frequency = 3, measuring intensity = 4, gain = 3; damp = 3. Saturation pulse settings: intensity = 6, width = 0.6.
Mean percent inhibition in SGR and Delta F/Fm’ of each treatment relative to the control treatment was calculated as per equation (3)(OECD 2011), where Xcontrol is the average SGR or Delta F/Fm’ of control and Xtreatment is the average SGR or Delta F/Fm’ of single treatments.

% Inhibition = [(X control - X treatment )/X control] x 100 (3)

Format:
Chlorella sp.herbicide toxicity data_eAtlas.xlsx

Data Dictionary:

There are two tabs for each herbicide in the spreadsheet. The first tab corresponds to the specific growth rate (SGR) data; the second tab is the pulse amplitude modulation (PAM) fluorometry data. The last tab of the dataset shows the measured water quality (WQ) parameters (pH, electrical conductivity and temperature) of each herbicide test.

Brom - Bromacil
Diu – Diuron
Halo – Haloxyfop
Hex - Hexazinone
Imaz – Imazapic
Isox - Isoxaflutole
Prom - Prometryn
Prop - Propazine

For each ‘herbicide’_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; for PAM data, notation is 1-3
T3_CellsPerMl = cell density at day 3
ln(day3) = natural logarithm of cell density at day 3
Average T0_CellsPerMl = average cell density at day 0
ln(Day0) = natural logarithm of cell density at day 0

For each ‘herbicide’_PAM tab:
PAM = pulse amplitude modulated fluorometry to calculate effective quantum yield (light adapted)
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; for PAM data, notation is 1-3
Delta F/Fm’ = effective quantum (light adapted) yield measured by a Pulse Amplitude Modulation (PAM) fluorometer

References:

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.gov.au/jspui/handle/11017/13325

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/test-no-201-alga-growth-inhibition-test-9789... (accessed 28 August 2019).

Pease C, Mooney T, Trenfield M, Costello C & Harford A (2016). Updated procedure for the 72 hour algal growth inhibition toxicity test using Chlorella sp. Internal Report 645, September, Supervising Scientist, Darwin

Riethmuller, N., Camilleri, C., Franklin, N., Hogan, A., King, A., Koch, A., Markich, S.J., Turley, C. and van Dam, R. (2003) Ecotoxicological testing protocols for Australian tropical freshwater ecosystems. Supervising Scientist Report 173, Supervising Scientist, Darwin NT.

Rueden, C.T., Schindelin, J., Hiner, M.C. et al. (2017) ImageJ2: ImageJ for the next generation of scientific image data. BMC Bioinformatics 18:529, PMID 29187165, doi:10.1186/s12859-017-1934-z

Data Location:

This dataset is filed in the eAtlas enduring data repository at: data\nesp3\3.1.5_Pesticide-guidelines-GBR