Hydrogen peroxide influence on toxicity of cyanobacterial harmful algal blooms (CHABs) in Lake Erie and other eutrophic waters from 2017 - 2019

Website: https://www.bco-dmo.org/dataset/944935
Data Type: experimental, Cruise Results
Version: 1
Version Date: 2025-02-03

Project
» The role of heterotrophic bacteria in protecting cyanobacteria from hydrogen peroxide in coastal ecosystems (Lake Erie H2O2 )
ContributorsAffiliationRole
Dick, Gregory J.University of MichiganPrincipal Investigator, Contact
Cory, RoseUniversity of MichiganCo-Principal Investigator, Contact
Kling, GeorgeUniversity of MichiganCo-Principal Investigator
Smith, DerekUniversity of MichiganStudent
Merchant, Lynne M.Woods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
Hydrogen peroxide is an oxidative stressor that may influence aquatic microbial community composition and function. It has been hypothesized that hydrogen peroxide may influence the toxicity of cyanobacterial harmful algal blooms (CHABs) in Lake Erie and other eutrophic waters, yet the sources and sinks of hydrogen peroxide are not fully understood. We assessed the relationship between hydrogen peroxide concentrations and CHABs by measuring production and decay of hydrogen peroxide in filtered and unfiltered waters from western Lake Erie with and without UV-visible light. Absolute H2O2 production rates and H2O2 decay rate constants were quantified in the western basin of Lake Erie before, during, and after Microcystis blooms from June – September, 2017-2019 and 2021. Experiments were conducted in whole and filtered waters with natural sunlight or visible light and in the dark to assess relative contributions of major microbial and photochemical processes to production and decay of H2O2. Absolute rates of H2O2 production depended on visible light and were significantly, positively correlated with concentration of chlorophyll a, chromophoric dissolved organic matter (CDOM), and rates of whole-water respiration and primary production. Rate constants for H2O2 decay were highest in waters containing high bloom biomass, and were significantly, positively correlated with whole-water respiration rates and with a proxy for labile dissolved organic nitrogen. Microcystis abundance was not a significant predictor of absolute H2O2 production rates, and microbial production and decay of H2O2 were primarily controlled by microorganisms smaller than 105 µm. Light-dependent production of H2O2 by microorganisms smaller than 105 µm suggests that photosynthesizing organisms other than Microcystis are responsible for H2O2 production. High microbial production and decay of H2O2 are favored by Microcystis bloom conditions (e.g., high light, high biomass) but are not directly due to Microcystis.


Coverage

Location: western basin of Lake Erie
Temporal Extent: 2017-05-30 - 2019-09-19

Methods & Sampling

Water samples were collected in the western basin of Lake Erie during the summer and fall of 2017, 2018, and 2019.  In 2017, water was collected approximately weekly from NOAA station WE2 in conjunction with the NOAA Great Lakes Environmental Research Lab (GLERL) harmful algal bloom monitoring program.  During August and October 2017, lake water was also collected by Environment and Climate Change Canada’s monitoring program.  In 2018 and 2019, lake water was collected at several stages of bloom development (pre-bloom, early bloom, late bloom, and post bloom).  In 2018, lake water was collected at NOAA’s monitoring stations WE2 and WE12 and at the drinking water intake for the City of Toledo (TWI).  During summer 2019, the goal was to sample lake waters containing high bloom biomass as predicted by the NOAA HAB forecast model and HAB tracker bulletins (Wynne et al. 2013).  Sampling sites were chosen based on the presence of surface scums comprised of dense cyanobacterial colonies (i.e., “bloom chase” sites).

For all sites, a depth-integrated water sample was collected in acid-washed carboys.  Water samples were collected from the NOAA stations using a peristaltic pump.  The pump hose was moved down the water column from the surface to 1 meter above the bottom.  For the TWI, bloom chase, and Environment Canada cruise sites, a depth-integrated sample was collected by pooling water collected at 1 m intervals from surface to 1 meter above the lake bottom using a Niskin (Environment Canada) or Van Dorn (TWI and bloom chase sites) bottle.  Integrated water samples were stored in carboys in an outdoor aquaculture tank until the start of the bottle experiments the following morning.  The water temperature in the aquaculture tank was controlled using copper piping attached to a NESLAB RTE refrigerated water bath (Thermo Scientific, Newington, NH) and maintained at the lake temperature measured at the time of sample collection.  During the Environment Canada cruises, bottles and carboys were stored in a plexiglass tank continuously circulated with fresh lake water.

Subsamples for supporting water quality analyses were taken from each carboy.  Upon arrival in the laboratory at the University of Michigan, a subsample of whole (unfiltered) water was taken for analysis of total phosphorus.  During 2017, pH of the water from each site was obtained from NOAA monitoring buoys.  For samples collected in 2018-2019, pH of the whole water was measured upon arrival in the laboratory.   Subsamples of the whole water were filtered through a 0.22 μm polyethersulfone (PES) filter for subsequent analysis of total dissolved phosphorus (TDP), soluble reactive phosphorous, nitrate and ammonium, dissolved organic carbon (DOC), and chromophoric and fluorescent dissolved organic matter (CDOM and FDOM, respectively).  DOC samples were preserved by addition of 6N trace metal grade hydrochloric acid to pH 3.   TDP, SRP, DOC, CDOM and FDOM were stored in the dark at 4 °C until analysis.  Nitrate and ammonium samples were stored at -20 °C until analysis at GLERL.

Subsamples for H2O2 and DNA were collected by filtering 100-200 mL of water from each bottle through a 0.22 μm pore size PES filter and collecting the last 50 mL of filtrate into a centrifuge tube.  The filtered water for H2O2 analysis was stored in the dark at 4 °C until analysis within 4 hours of collection.  H2O2 concentrations were measured on an FeLume by flow injection analysis using standard additions as previously described (King et al. 2007, as applied to Lake Erie waters in Cory et al. 2017; Pandey et al. 2022).  The filter was saved for DNA extraction by freezing in a cryovial containing 1 mL RNAlater at -80 °C. 


BCO-DMO Processing Description

Processed the submitted file Environmental data BCO-DMO.xlsx with the BCO-DMO processing tool Laminar.

- Imported the submitted file into Laminar

- Renamed the parameters to conform with the BCO-DMO naming convention by replacing spaces with underscores, replacing % symbols with the word 'percent', and remove parenthesis.

- Converted dates from the format %d-%b-%y into the ISO 8601 format of %Y-%m-%d


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Related Publications

Cory, R. M., Davis, T. W., Dick, G. J., Johengen, T., Denef, V. J., Berry, M. A., Page, S. E., Watson, S. B., Yuhas, K., & Kling, G. W. (2016). Seasonal Dynamics in Dissolved Organic Matter, Hydrogen Peroxide, and Cyanobacterial Blooms in Lake Erie. Frontiers in Marine Science, 3. https://doi.org/10.3389/fmars.2016.00054
Related Research
Cory, R. M., Davis, T. W., Dick, G. J., Johengen, T., Denef, V. J., Berry, M., Page, S. E., Watson, S. B., Yuhas, K., & Kling, G. W. (2017). Corrigendum: Seasonal Dynamics in Dissolved Organic Matter, Hydrogen Peroxide, and Cyanobacterial Blooms in Lake Erie. Frontiers in Marine Science, 4. https://doi.org/10.3389/fmars.2017.00377
Related Research
King, D. W., Cooper, W. J., Rusak, S. A., Peake, B. M., Kiddle, J. J., O’Sullivan, D. W., Melamed, M. L., Morgan, C. R., & Theberge, S. M. (2007). Flow Injection Analysis of H2O2 in Natural Waters Using Acridinium Ester Chemiluminescence:  Method Development and Optimization Using a Kinetic Model. Analytical Chemistry, 79(11), 4169–4176. https://doi.org/10.1021/ac062228w
Methods
Pandey, D. R., Polik, C., & Cory, R. M. (2022). Controls on the photochemical production of hydrogen peroxide in Lake Erie. Environmental Science: Processes & Impacts, 24(11), 2108–2118. https://doi.org/10.1039/d2em00327a
Related Research
Wynne, T. T., Stumpf, R. P., Tomlinson, M. C., Fahnenstiel, G. L., Dyble, J., Schwab, D. J., & Joshi, S. J. (2013). Evolution of a cyanobacterial bloom forecast system in western Lake Erie: Development and initial evaluation. Journal of Great Lakes Research, 39, 90–99. https://doi.org/10.1016/j.jglr.2012.10.003
Methods

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Related Datasets

IsRelatedTo
Dick, G. J., Cory, R., Kling, G. (2025) RNA-Seq and NCBI accessions of microbial communities in the western basin of Lake Erie during summer-fall from 2017-2019. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-02-03 http://lod.bco-dmo.org/id/dataset/945401 [view at BCO-DMO]

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Parameters

ParameterDescriptionUnits
Collection_Date

Collection date

unitless
Experiment_Date

Experiment date

unitless
Incubation_Type

Incubation conditions

unitless
Site

Sampling site

unitless
Latitude

latitude, South is negative

decimal degrees
Longitude

Longitude, West is negative

decimal degrees
Chlorophyll_a

Chlorophyll a

microgram/Liter (ug/L)
Chlorophyll_a_95percent_CI

Chlorophyll a 95% Confidence Interval

microgram/Liter (ug/L)
Dissolved_Inorganic_Carbon

dissolved inorganic Carbon

micrometer (uM)
Dissolved_Inorganic_Carbon_95percent_CI

Chlorophyll a 95% Confidence Interval

micrometer (uM)
H2CO3_star

H2CO3* (the total dissolved inorganic cabon including aqueous carbon dioxide)

micrometer (uM)
H2CO3_star_95percent_CI

H2CO3* 95% Confidence Interval

micrometer (uM)
Bicarbonate

Bicarbonate

micrometer (uM)
Bicarbonate_95percent_CI

Bicarbonate 95% Confidence Interval

micrometer (uM)
Carbonate

Carbonate

micrometer (uM)
Carbonate_95percent_CI

Carbonate 95% Confidence Interval

micrometer (uM)
Dissolved_Organic_Carbon

dissolved organic Carbon

micrometer (uM)
Respiration_Rate

Respiration Rate

micrometer O2 / day (uM O2 / day)
Respiration_Rate_95percent_CI

Respiration Rate 95% Confidence Interval

micrometer O2 / day (uM O2 / day)
Primary_Production_Rate

Primary Production Rate

micrometer C / hour (uM C / hr)
Primary_Production_Rate_95percent_CI

Primary Production Rate 95% Confidence Interval

micrometer C / hour (uM C / hr)
CDOM_a305

CDOM (a305)

per meter (m-1)
CDOM_95percent_CI

CDOM 95% Confidence Interval

per meter (m-1)
Day_Integrated_UV_A

total amount of UV-A that the experimental bottles were exposed to during the 9 hour experiments

joules per meter squared (J/m^2)
Day_Integrated_UV_B

total amount of UV-B that the experimental bottles were exposed to during the 9 hour experiments

joules per meter squared (J/m^2)
Day_Integrated_UV

sum of UV-A and UV-B that the experimental bottles were exposed to during the 9 hour experiments

joules per meter squared (J/m^2)
pH

pH

unitless
Total_Phosphorus

Total Phosphorus

microgram/Liter (ug/L)
Total_Phosphorus_95percent_CI

Total Phosphorus 95% Confidence Interval

microgram/Liter (ug/L)
Total_Dissolved_Phosphorus

Total Dissolved Phosphorus

microgram/Liter (ug/L)
Total_Dissolved_Phosphorus_95percent_CI

Total Dissolved Phosphorus 95% Confidence Interval

microgram/Liter (ug/L)
Nitrate

Nitrate

miligram/Liter (mg/L)
Nitrate_95percent_CI

Nitrate 95% Confidence Interval

miligram/Liter (mg/L)
Ammonium

Ammonium

microgram/Liter (ug/L)
Ammonium_95percent_CI

Ammonium 95% Confidence Interval

microgram/Liter (ug/L)
Soluble_Reactive_Phosphorus

Soluble Reactive Phosphorus

microgram/Liter (ug/L)
Soluble_Reactive_Phosphorus_95percent_CI

Soluble Reactive Phosphorus 95% Confidence Interval

microgram/Liter (ug/L)
Average_Incubation_Temperature

Average Incubation Temperature

degrees Celsius (°C)
Incubation_Temperature_Standard_Deviation

Incubation Temperature Standard Deviation

degrees Celsius (°C)
peak_A

Peak A is the fluorescence intensity of FDOM at excitation (ex) of 250 nm and emission (em) at 450 nm

Raman units (RU)
peak_A_95percent_CI

fDOM peak A 95% Confidence Interval

Raman units (RU)
peak_C

Peak C is the fluorescence intensity at ex and em of 350 and 450 nm, respectively

Raman units (RU)
peak_C_95percent_CI

fDOM peak C 95% Confidence Interval

Raman units (RU)
peak_T

Peak T is the fluorescence intensity at ex and em of 275 and 340 nm, respectively

Raman units (RU)
peak_T_95percent_CI

fDOM peak T 95% Confidence Interval

Raman units (RU)
peak_C_peak_A_ratio

fDOM peak C/peak A ratio

unitless
peak_C_peak_A_ratio_95percent_CI

fDOM peak C/peak A ratio 95% Confidence Interval

unitless
peak_T_peak_A_ratio

fDOM peak T/peak A ratio

unitless
peak_T_peak_A_ratio_95percent_CI

fDOM peak T/peak A ratio 95% Confidence Interval

unitless
Integrated_Fluorescence

Integrated Fluorescence

unitless
Integrated_Fluorescence_95percent_CI

Integrated Fluorescence 95% Confidence Interval

unitless
Fluorescence_Index

Fluorescence Index

unitless
Fluorescence_Index_95percent_CI

Fluorescence Index 95% Confidence Interval

unitless
Slope_Ratio

The Slope Ratio is the spectral slope ratio of the absorption curve of chromophoric dissolved organic matter (CDOM). The slope ratio is a unitless proxy for the average molecular weight of DOM

unitless
Slope_Ratio_95percent_CI

Slope Ratio 95% Confidence Interval

unitless


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Instruments

Dataset-specific Instrument Name
NESLAB RTE refrigerated water bath
Generic Instrument Name
circulating water bath
Dataset-specific Description
NESLAB RTE refrigerated water bath made by Thermo Scientific, Newington, NH
Generic Instrument Description
A device designed to regulate the temperature of a vessel by bathing it in water held at the desired temperature. [Definition Source: NCI] 

Dataset-specific Instrument Name
FeLume
Generic Instrument Name
Flow Injection Analyzer
Dataset-specific Description
FeLume, Waterville Analytical, purchased 2011 The description from the company website of Waterville Analytical, http://watervilleanalytical.com/products.html The FeLume(II) is a general purpose, FIA-based, analytical system for the analysis of Fe(II), Fe(III), Cu(II), Co(II), hydrogen peroxide, and superoxide. 
Generic Instrument Description
An instrument that performs flow injection analysis. Flow injection analysis (FIA) is an approach to chemical analysis that is accomplished by injecting a plug of sample into a flowing carrier stream. FIA is an automated method in which a sample is injected into a continuous flow of a carrier solution that mixes with other continuously flowing solutions before reaching a detector. Precision is dramatically increased when FIA is used instead of manual injections and as a result very specific FIA systems have been developed for a wide array of analytical techniques.

Dataset-specific Instrument Name
Aqualog fluorometer
Generic Instrument Name
Fluorometer
Dataset-specific Description
Aqualog fluorometer made by Horiba Scientific
Generic Instrument Description
A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ.

Dataset-specific Instrument Name
Generic Instrument Name
Niskin bottle
Generic Instrument Description
A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.

Dataset-specific Instrument Name
peristaltic pump
Generic Instrument Name
Pump
Generic Instrument Description
A pump is a device that moves fluids (liquids or gases), or sometimes slurries, by mechanical action. Pumps can be classified into three major groups according to the method they use to move the fluid: direct lift, displacement, and gravity pumps


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Project Information

The role of heterotrophic bacteria in protecting cyanobacteria from hydrogen peroxide in coastal ecosystems (Lake Erie H2O2 )

Coverage: Western Basin of Lake Erie (41N, 83W)


NSF Award Abstract:
Toxic cyanobacterial harmful algal blooms (CHABs) are now a worldwide problem that poses dangers for humans and aquatic organisms including life-threatening sickness, beach closures, health alerts, and drinking water treatment plant closures. This project focuses on the basic science needed to understand interactions between the microorganisms present in CHABs and the chemistry of the lakes they inhabit. In particular, it will study the sources, fate, and effects of hydrogen peroxide, which is a potentially important control on the toxicity and species present within these blooms. This research will be conducted in Lake Erie, a source of drinking water for 11 million people that is threatened by CHABs annually. Results will be directly integrated into two water quality models that are widely used by water managers and other stakeholders. This project will support the training of two PhD students, including a first-generation college attendee, and undergraduate students from backgrounds that are underrepresented in the earth sciences. Research will also be integrated into outreach aimed at increasing diversity in the earth sciences by involving women and underrepresented minorities in K-12 as well as college and adult educational settings.

The overall goal of this project is to determine the influence of hydrogen peroxide (H2O2) on cyanobacterial community composition and function in nearshore ecosystems. Preliminary results from Lake Erie show that dominant primary producers rely on heterotrophic bacteria to draw down H2O2 from transiently high environmental levels that are likely inhibitory to members of the cyanobacterial community. This suggests that H2O2 plays important and still poorly understood roles in aquatic microbial ecology. A combination of field sampling, experiments, and state-of-the art "-omics" will be used to test the overall hypothesis that H2O2 decomposition by heterotrophic "helpers" is an important determinant of microbial interactions and community structure and function. Lake Erie will be studied because (i) it is a model system for shallow coastal areas receiving high terrestrial nutrient runoff, (ii) it offers strong inshore-offshore gradients of light and nutrients for comparative studies, and (iii) existing sampling infrastructure, archived samples, and preliminary data can be leveraged. Field and laboratory experiments and measurements will be integrated to answer the following questions: Q1: What drives the temporal dynamics of H2O2 concentrations? Q2: Which enzymes and organisms are responsible for protecting the community via biological H2O2 decay? Q3: How does protection from H2O2 by helpers influence the composition and function of the community? The study will perform controlled lab experiments on cultures and on natural waters during different points of the bloom. Measures of H2O2 concentrations and rates of production and decay, along with supporting chemical and biological measurements, will be used to assess the major sources and sinks of H2O2. Molecular tools will be used to determine the pathways underpinning H2O2 decay and the effect of H2O2 on cyanobacterial community composition function. In parallel, impacts of varying H2O2 concentrations on growth rates of major cyanobacteria will be assessed experimentally. These experimental results will be placed into context through comparisons with the structure and function of microbial communities from field samples across spatial, temporal, and chemical gradients in this coastal ecosystem. The approach of integrating studies of H2O2 with "-omics" in natural systems is novel, and will advance our fundamental knowledge and understanding of the relationship between microbial community composition and function.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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