Harnessing plant-microbiome interactions for bioremediation across a freshwater urbanization gradient
Graphical abstract
Introduction
Urban landscapes are expected to triple in area from the year 2000 to 2030 alone (Seto et al., 2012), and thus represent a new major type of ecosystem into which existing species assemble. Urban environments confront organisms with unique challenges and stressors, and in response, many organisms evolve along urban-to-rural gradients (Johnson and Munshi-South, 2017). The influx of highly complex mixtures of anthropogenic contaminants into aquatic systems via stormwater is one such unique pressure of urban environments that elicits ecological and evolutionary responses (Brans, De Meester, 2018, Hale, Scoggins, Smucker, Suchy, 2016, Kern, Langerhans, 2018, Masoner, Kolpin, Cozzarelli, Barber, Burden, Foreman, Forshay, Furlong, Groves, Hladik, et al., 2019, Nacci, Champlin, Jayaraman, 2010, Peter, Tian, Wu, Lin, White, Du, McIntyre, Scholz, Kolodziej, 2018, Tian, Zhao, Peter, Gonzalez, Wetzel, Wu, Hu, Prat, Mudrock, Hettinger, et al., 2021, Walsh, Roy, Feminella, Cottingham, Groffman, Morgan, 2005).
Interactions between organisms in systems receiving stormwater, such as ponds, wetlands, rivers, lakes, and marine environments, can simultaneously alter both biological consequences of contaminants and contaminant fate (e.g., Tondera et al., 2021). Contaminant transformation in receiving systems is particularly affected by resident “microbiomes” (assemblages of microbial species living together in a community). Host-associated microbiomes can comprise hundreds or thousands of species, each with unique metabolic capabilities and potentially distinct effects on contaminants. Because plant carbon increases microbial growth and metabolic rates, plant-microbe combinations often synergistically enhance contaminant transformation (Ashraf, Afzal, Rehman, Naveed, Zahir, 2018, Fester, Giebler, Wick, Schlosser, Kästner, 2014), and plant-associated microbiomes can often transform contaminants faster than environmental microbiomes (Chaudhry et al., 2005). Engineering microbiomes to improve human or plant health shows great promise (Busby, Soman, Wagner, Friesen, Kremer, Bennett, Morsy, Eisen, Leach, Dangl, 2017, Lawson, Harcombe, Hatzenpichler, Lindemann, Löffler, O’Malley, Martín, Pfleger, Raskin, Venturelli, et al., 2019). Likewise, engineered plant-microbe systems have been proposed as a way to manage stormwater contaminant influxes as part of constructed, wetland-mimicking infrastructure (Ashraf, Afzal, Rehman, Naveed, Zahir, 2018, Ishizawa, Kuroda, Inoue, Morikawa, Ike, 2020). Constructed wetlands demonstrate variable contaminant removal efficacy, and therefore opportunity for improvement (Brisson, Chazarenc, 2009, Varma, Gupta, Ghosal, Majumder, 2021).
One representative and widespread source of stormwater contaminants is the co-use of anti-corrosives, such as benzotriazole, and salt in temperate latitudes during winter. Benzotriazole is a common anti-corrosive agent in many applications, including de-icers for aircraft and cars, which may explain its higher abundance as a winter contaminant in more urban stormwater (Alvey, Hagedorn, Dotson, 2016, Kiss, Fries, 2012, Parajulee, Lei, De Silva, Cao, Mitchell, Wania, 2017). Environmental concentrations are generally well below effect concentrations (environmental in ng/L to low g/L, rarely 100 mg/L; effect 10 g/L for sensitive species, Cancilla, Martinez, Van Aggelen, 1998, Parajulee, Lei, De Silva, Cao, Mitchell, Wania, 2017, Tangtian, Bo, Wenhua, Shin, Wu, 2012). Yet, benzotriazole is relatively resistant to biodegradation, has a long half-life (100 days, Liu et al., 2011a), and its environmental fate is poorly understood. At the same time, winter salt application in many temperate-region urban areas has shifted salinities near the U.S. EPA aquatic life threshold criterion, and contributes to expanding freshwater salinization across North America (Dugan, Bartlett, Burke, Doubek, Krivak-Tetley, Skaff, Summers, et al., 2017, Kaushal, Likens, Pace, Utz, Haq, Gorman, Grese, 2018). Impacts of contaminant mixtures are often poorly predicted from components alone due to interactive effects (Cedergreen, 2014), and both occurrence in mixture and interactive effects are especially likely for salt and benzotriazole (Asheim, Vike-Jonas, Gonzalez, Lierhagen, Venkatraman, Veivåg, Snilsberg, Flaten, Asimakopoulos, 2019, Parajulee, Lei, De Silva, Cao, Mitchell, Wania, 2017, Rhodes-Dicker, Passeport, 2019).
Given the potential for contaminant responses or transformation to vary across plant genotypes, microbial community composition, and background environmental conditions (Hijosa-Valsero, Sidrach-Cardona, Bécares, 2012, Inui, Wakai, Gion, Kim, Eun, 2008, Rhodes-Dicker, Passeport, 2019, Tondera, Chazarenc, Chagnon, Brisson, 2021, Wu, Suchana, Flick, Kümmel, Richnow, Passeport, 2021), harnessing microbiomes for stormwater treatment requires understanding how these factors interact. Large experiments can simultaneously reveal more effective plant-microbe combinations for specific purposes (i.e. constructed wetlands) and develop tools for leveraging plant microbiomes across applications. Duckweeds (Lemna minor) are tiny plants common in stormwater ponds in northern temperate regions, foster biotransformation of benzotriazole even in the presence of salt, and have plant growth-promoting microbiomes that vary in composition (Ishizawa, Kuroda, Morikawa, Ike, 2017, O’Brien, Laurich, Lash, Frederickson, 2020, O’Brien, Yu, Luo, Laurich, Passeport, Frederickson, 2019). We used duckweed as a model wetland plant, leveraging these characteristics in high-throughput constructed microcosm experiments. Our objective was to identify how variation in co-applied salt, duckweed genotype, and interacting microbes across an urban-to-rural gradient may alter benzotriazole fate.
Section snippets
Materials and Methods
We conducted two microcosm experiments to reveal interactive effects between benzotriazole biotransformation and duckweed microbiomes. Combined, these experiments tested 100 differences in plant and microbiome manipulation (“biotypes”) in 2,500 independent microcosms.
Results
The vast majority of benzotriazole was transformed or otherwise removed in our microcosms during our 11-day experiment (73-99% across treatments, Fig. 1). Estimated half-lives of benzotriazole in our 21-day experiment reached as low as 3.9 days (95% confidence interval 3.2-5 days, Table S5, Fig. S2). However, transformation varied across microcosms depending on salt and biological context.
Discussion
Rapid, continued urbanization brings potentially harmful consequences, such as release of anthropogenic contaminants into stormwater (Masoner et al., 2019), and makes leveraging services that can be provided by urban ecosystems, such as bioremediation in wetlands, more critical than ever (Elmqvist, Setälä, Handel, Van Der Ploeg, Aronson, Blignaut, Gomez-Baggethun, Nowak, Kronenberg, De Groot, 2015, Johnson, Munshi-South, 2017). Here, we observed 73-99% of the common contaminant benzotriazole
Conclusions
Here, we quantified effects of physical and biotic context on biotransformation outcomes for a model stormwater contaminant, and demonstrated that these factors offer substantial variation to consider when constructing urban wetlands for bioremediation. In high-throughput microcosm scale experiments, our model plant (duckweed, Lemna minor) rapidly transformed our model contaminant (benzotriazole). Certain manipulations of variation in duckweed and its associated microbial communities increased
Data Accessibility
Data including raw sequence files and code are on figshare at https://doi.org/10.6084/m9.figshare.20311758. Code and some data are available at https://github.com/amob/benzotriazole-microcosms.
Author contributions
AMO, ZHY, MEF, and EP conceived of the idea and designed experiments. AMO, ZHY, and CP conducted experiments and collected data. GHL synthesized chemical standards. AMO and ZHY analyzed the data, with MEF, EP, and GHL advising. AMO and ZHY provided the first draft of the manuscript, and AMO, ZHY, MEF, EP, and GHL edited the manuscript. All authors approved the submitted manuscript.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This project was funded by NSERC Discovery Grants and a University of Toronto XSeed Grant to MEF and EP, NSERC Canada Research Chair program grants to EP (950-230892), and by the Gordon and Betty Moore Foundation grant GBMF9356 to MEF (https://doi.org/10.37807/GBMF9356). GHL acknowledges NSF CBET CAREER funding (1844720). We thank Hollis Dahn for collecting two duckweed sources, and Frederickson lab members for useful discussion.
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