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Thinking like a bacterium can improve water quality

Researchers show that mathematical models based on cell biology can help lake managers reduce toxic algal blooms and improve the quality of our drinking water.


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Image Credit: Harmful Algal Bloom in Western Basin of Lake Erie, from NOAA Great Lakes Environmental Research Laboratory. Photo by Zachary Haslick, Aerial Associates Photography, Inc.

Have you ever planned a trip to swim at your local lake only to find it closed due to poor water quality? The problem may have been a harmful bloom of blue-green algae, an increasing issue for freshwater bodies around the world. 

Blue-green algae are not actually algae, but a widespread type of photosynthesizing bacteria called cyanobacteria. They provide benefits to our environment, like making oxygen, but they can also harm water quality by making toxins that contaminate ponds and lakes. 

When cyanobacteria cells rapidly multiply in water sources they can create a harmful bloom, releasing toxins and diminishing water quality. Drinking toxin-contaminated water can result in illness or death. For example, in 2014 the residents of Toledo, Ohio, were unable to consume water from their faucets for two days due to this type of contamination. 

Despite many efforts, lake water quality managers in Toledo and elsewhere have not been able to successfully reduce cyanobacterial blooms. One way researchers have tried to stop harmful blooms is by taking away elements that cyanobacteria need to grow, like phosphorus. Phosphorus is used in DNA and other biomolecules in all living things. 

Thus, one approach to stop cyanobacteria from growing in lakes and other water supplies is to limit how much phosphorus flows into them. In 2018, the USA and Canada agreed to reduce phosphorus going into Lake Erie by 40% in an attempt to reduce the growth of cyanobacteria. Lake Erie is the main source of drinking water for Toledo. But will phosphorus reduction alone be enough to prevent toxin contamination?

Researchers led by Dr. Ferdi Hellweger from the Technical University of Berlin created a new type of computer model to predict water contamination by algal blooms in Lake Erie. Models use mathematical equations and computer simulations to predict real-world scenarios. Using their model, the researchers tested whether reducing phosphorus would help stop cyanobacteria from growing and producing toxins in the lake. 

They built their model specifically to simulate the biochemical activities of a cyanobacterial cell. In addition to the amount of phosphorus in the lake, the researchers used their model to test other conditions that affect cell growth, like nitrogen, temperature, light, and the amount of reactive compounds called peroxides. These compounds are naturally created when dissolved oxygen interacts with sunlight. They are also generated as a byproduct of cellular energy production. But peroxides can also cause damage to cells.

To test how accurate their model was, the researchers compiled data from more than 700 experiments conducted over the last 50 years. The historical experiments had all tested the impact of different combinations of temperature, light, and nutrients on cyanobacterial cell growth and toxin production. They then compared predictions made by their model to the experimental results, to see if they matched. The researchers confirmed that their model was able to reproduce the experimental results nearly 90% of the time.

The team then used their model to see how different conditions in the lake could impact cyanobacterial growth and toxin production. They found that general cell growth responded to phosphorus content in their models, because phosphorus is widely found in biomolecules. Toxin production responded most strongly to nitrogen content in their models, since toxins contain nitrogen. They also found that peroxide concentrations impacted both cell growth and toxin production in their models, since peroxides can damage cells but they can also stick to other toxins.

The researchers next used the model to simulate the phosphorus and nitrogen concentrations in Lake Erie that led to the contamination of Toledo drinking water. The Toledo-like model predicted that lake managers would need to decrease both phosphorus and nitrogen in the lake waters to slow cell growth and toxin production. Their model also showed that predicted temperature increases of up to 3oC could actually reduce toxin concentrations in the lake.

The researchers concluded that the current management plan for Lake Erie, a reduction in phosphorus alone, will make harmful blooms worse rather than better. They argued that ongoing water quality issues are caused by past attempts to lower phosphorus in the lake. To improve water quality, the researchers recommended reducing the flows of both phosphorus and nitrogen into Lake Erie. They proposed that lake managers should use models based on cell biology to help predict biological responses of cyanobacteria and improve the quality of drinking water.

Study Information

Original study: Models predict planned phosphorus load reduction will make Lake Erie more toxic

Study was published on: May 27, 2022

Study author(s): Ferdi Hellweger, Robbie Martin, Falk Eigemann, Derek Smith, Gregory Dick, Steven Wilhelm

The study was done at: Technical University of Berlin (Germany), University of Tennessee (USA), University of Michigan (USA)

The study was funded by: National Oceanographic and Atmospheric Administration, National Institute of Environmental Health Sciences, National Science Foundation

Raw data availability: Not available

Featured image credit: Harmful Algal Bloom in Western Basin of Lake Erie, from NOAA Great Lakes Environmental Research Laboratory. Photo by Zachary Haslick, Aerial Associates Photography, Inc.

This summary was edited by: Erica Curles and Aubrey Zerkle