Insights into the Toxicity of Triclosan to Green Microalga

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Insights into the Toxicity of Triclosan to Green Microalga Chlorococcum sp. using Synchrotron-based Fourier Transform Infrared Spectromicroscopy: Biophysiological Analyses and Roles of Environmental Factors xiaying xin, guohe huang, Chunjiang An, charley huang, Harold Weger, shan zhao, yang zhou, and Scott M Rosendahl Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b05533 • Publication Date (Web): 29 Jan 2018 Downloaded from http://pubs.acs.org on January 29, 2018

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Environmental Science & Technology

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Insights into the Toxicity of Triclosan to Green Microalga Chlorococcum sp. using

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Synchrotron-based Fourier Transform Infrared Spectromicroscopy: Biophysiological

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Analyses and Roles of Environmental Factors

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Xiaying Xin,a Guohe Huang,a,* Chunjiang An,b Charley Huang,c Harold Weger,d Shan Zhao e,

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Yang Zhou a, Scott Rosendahlf

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a

Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina,

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Canada S4S 0A2

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b

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Canada H3G 1M8

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c

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Vancouver, Canada V6T 1Z3

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d

Department of Biology, University of Regina, Regina, Canada S4S 0A2

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e

Shandong Key Laboratory of Water Pollution Control and Resource Reuse, School of

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Environmental Science and Engineering, Shandong University, Jinan, China 250100

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f

Department of Building, Civil and Environmental Engineering, Concordia University, Montreal,

Department of Chemical and Biological Engineering, University of British Columbia,

Canadian Light Source, Saskatoon, Canada S7N 2V3

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*Corresponding author: Tel: +1-306-5854095; Fax: +1-306-5854855; E-mail:

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[email protected]

1 ACS Paragon Plus Environment


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Abstract

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This study investigated the toxicity of triclosan to the green microalga Chlorococcum sp. under

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multiple environmental stressors. The interactions between triclosan and environmental stressors

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were explored through full two-way factorial, synchrotron-based Fourier transform infrared

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spectromicroscopy, and principal component analyses. Phosphorus concentration, pH *

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phosphorus concentration, temperature * pH * NaCl concentration were the most statistically

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significant factors under triclosan exposure. The variation of those factors would have a huge

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impact on biophysiological performances. It is interesting to find Chlorococcum sp. may become

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more resistant against triclosan in phosphorus-enriched environment. Besides, particular

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significant factors from multiple environmental stressors showed the impacts of triclosan on the

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corresponding response of Chlorococcum sp. owing to the specific structure and performance of

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biomolecular components. Moreover, two high-order interactions of temperature * pH * NaCl

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concentration and temperature * pH * NaCl concentration * phosphorus concentration had more

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contributions than others at subcellular level, which could be attributed to the interactive

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complexity of biomolecular components. Due to cellular self-regulation mechanism and short

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exposure time, the biophysiological changes of Chlorococcum sp. were undramatic. These

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findings can help reveal the interactive complexity among triclosan and multiple environmental

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stressors. It is suggested that multiple environmental stressors should be considered during

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ecological risk assessment and management of emerging pollutants.

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Keywords: Toxicity, Triclosan, Multiple environmental stressors, Chlorococcum sp.,

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Biophysiological analyzes, Synchrotron-based Fourier Transform Infrared Spectromicroscopy


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1. Introduction

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Triclosan is widely used as an antimicrobial agent in soaps, detergents, shampoos, toothpastes

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and other household products.1 Although a reduction of triclosan concentration can be achieved

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in wastewater treatment plants, it is still frequently detected in aquatic ecosystems, with a

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reported concentration range of 0.0075 ‒ 2.3 ug/L.2 As primary producers, algae have been

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widely used to evaluate the impacts and bioavailability of xenobiotic contaminants in aquatic

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systems. Even at low concentrations, long-term exposure to triclosan can result in potential

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chronic effects over generations on aquatic biota, and thereby influence their productivity or

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enhance their resistance to triclosan.3, 4 This is a common concern, in general, for the negative

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effects of antimicrobials.

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The toxicity of triclosan to aquatic plants is influenced by changing environmental conditions.

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For example, triclosan toxicity to algae can increase with decreasing pH. Low pH is favorable

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for the formation of neutral triclosan, which is more able to diffuse across the plasma membrane

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to target sites.5 Results from experiments with the small vascular plant Lemna gibba suggested

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that site-specific nutrient concentrations should be taken into account in assessing the risk of

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triclosan exposure.4 When triclosan exposure occurs in a changing environment,

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biophysiological properties may be influenced in both the short- and long-term. Exposure to

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triclosan may result in the acclimation of species, or gradually cause metabolic dysfunction, e,g,

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a decline in photosynthesis.6 Previous efforts mainly focused on the toxicity of triclosan based on

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specific environmental conditions.7 Although the toxic effects of triclosan have been investigated



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considering single environmental factors, the toxicity based on the interactions among multiple

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environmental stressors has not yet been reported.

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Furthermore, common toxicity evaluation parameters for triclosan on algae include cell density,

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chlorophyll-a fluorescence, cell viability, photosynthesis and genotoxicity, which are usually at

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biomass level.8 Such bulk measurements need large amounts of biomass samples and are time

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consuming. They may result in insufficiency of samples, when continuous batch measurements

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are needed.9 Moreover, the specific toxic state may be hidden within the average values of those

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parameters, while the basic nature of interactions among cells can’t be revealed. On the other

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hand, at subcellular level, only a few studies focused on the determination of biochemical

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compositions of algae exposed to triclosan.10 The in vivo effect can be only estimated by

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extrapolating in vitro results, failing to present accurate cellular molecular nature.9 The

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extraction process needs hazardous organic solvents, making it environmentally unfriendly.

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Therefore, a fast and accurate approach for simultaneous quantification of various biochemical

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compositions of single cell in-vivo is also necessary for characterizing the toxicity of triclosan to

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algae during cultivation.

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In this study, interactive effects of environmental factors on biophysiological changes of green

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alga Chlorococcum sp. were comprehensively evaluated through a full two-way factorial

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experimental design. Simultaneous qualification and quantification of biophysiological changes

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of single cell were conducted in-vivo through synchrotron-based Fourier transform infrared (SR-

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FTIR) spectromicroscopy. The correlations of all biophysiological responses and treatment

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groups were explored separately through principle component analysis (PCA). These


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experiments represent a novel approach to examine compound interactions among multiple

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environmental stressors on aquatic toxicity of emerging pollutants, using triclosan as a

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representative molecule.

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2. Material and methods

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2.1. Cell cultivation

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The green microalga, Chlorococcum sp., was isolated from Pasqua Lake in the Qu’Appelle River

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system (in southern Saskatchewan, Canada). Chlorococcum is a cosmopolitan genus found in

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edaphic and aquatic environments, and this particular strain has a typical cell diameter of 8-17

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µm (Supporting Information (SI) Figure S1). It can grow at high biomass densities with high

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tolerance to the harsh conditions (temperature, pH).11

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Prior to the main experiment, Chlorococcum sp. were cultured in modified BG-11 medium to log

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growth phase.12, 13 The culture medium was sterilized at 121 °C, 15 psi for 45 min.14 To inoculate

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new cultures, algae were filtered through a 1 µm sterile filter membrane, washed in sterile

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deionized water, and re-suspended in sterile deionized water. An inoculum of 4.5 mL was then

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added to 125 mL Erlenmeyer flasks containing 45 mL of culture medium. The starting cell

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density was between 2.1 × 105 and 4.3 × 105 cells mL-1. Algal cells were propagated

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photoautotrophically and illuminated with cool-white fluorescent light (4000 lux), with a 12:12h

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light-dark photoperiod.

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2.2 Triclosan exposure tests based on a full two-way factorial design

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Triclosan (purity > 99 %) was purchased from Alfa Aesar (Ward Hill, USA). The chemical

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structure and property of triclosan are shown in Supporting Information (SI) Table S1. The green

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microalga Chlorococcum sp. was exposed to triclosan at 113 µg/L.15 After 48h, samples of algal

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cells were harvested for measurement of biophysiological responses. A 25 factorial design was

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used to run the triclosan exposure tests.16 This type of design can screen factors that have

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significant effects on responses. The five factors investigated in this study are temperature, pH,

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NaCl concentration, nitrogen concentration, and phosphorus concentration. The high and low

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levels for each variable are presented in SI Table S2. The experimental matrix design under

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different combinations is shown in SI Table S3. The order of the experimental runs was

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completely randomized within each set of experiments. The control experiments without

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triclosan exposure were performed under same factorial experimental design matrix.

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2.3 Cell densities and cell viability

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For cell counts, 400 µL of each algal culture was preserved with 40 µL of Lugol’s iodine before

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counting using a hemacytometer and light microscope. To observe cell viability, 20 µL of the

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medium-algae mixture was added to a slide, covered with a cover slip. Cell size was analyzed

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using a Zeiss Axio Observer Z1 microscope. The corresponding biovolume was calculated by

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approximating the cells to a sphere according to Hillebrand.17

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2.4 Biochemical measurement for single living cell through synchrotron-based FTIR

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spectromicroscopy 6 ACS Paragon Plus Environment

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Algal cells were harvested by centrifugation at 4500 rpm for 15 min. The biomass was re-

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suspended in distilled water and centrifuged again. This process was repeated three times.

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The final biomass were re-suspended in a small volume of D2O. 30 µL of cell suspension was

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loaded on the optical CaF2 window, and compressed by another CaF2 window, leaving a

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polymeric spacer between them. This was held in a sample holder, allowing the flow of an

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aqueous solution around the edge of the windows to compensate for evaporation from the

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sample.9 Synchrotron-based FTIR spectromicroscopy measurements were carried out at the

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beamline 01B1-01(MidIR) at the Canadian Light Source, Saskatoon, Canada. A Bruker Vertex

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70v interferometer coupled to a Hyperion 3000 IR confocal microscope equipped with a liquid

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nitrogen cooled mercury cadmium telluride (MCT) detector (Bruker Optics, USA) was used to

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acquire the data using synchrotron-based infrared light (SI Figure S2). The brilliant synchrotron

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source could maintain an adequate signal-to-noise ratio even with small apertures.18 A pair of

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36× objectives were used for spectra collection in transmission mode with a 10 × 10 µm point

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size on the sample, with 512 scan co-added scans, measured over a broad range of 4 000 - 800

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cm-1 wave-numbers. The data were collected using OPUS 7.2 software (Bruker Optics, USA). At

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least 10 cells for each sample were selected randomly to generate average spectra. Background

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spectra were taken for every sample to compensate for atmospheric alteration and synchrotron

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ring current changes. Raw spectra were baseline-corrected using the automatic baseline

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correction algorithm and were scaled to Amide II’, using Bruker OPUS 7.2 software.19

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2.5 Analytical methods

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All experiments were carried out in at least triplicate. The quantitative data were expressed as

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mean values. The data were subjected to ANOVA to test the main effects of different factors and 7 ACS Paragon Plus Environment


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their interactions (p≤0.05). The data of factorial experiments were processed using Design-

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Expert v8.0.6 (Stat-Ease Inc., Minneapolis, USA). PCA was performed to visualize the

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correlation of relevant responses and all of treatment groups using SPSS 18.0 (SPSS, Chicago,

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USA). The diagrams were generated by using OriginPro 8.0.

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3. Results and discussion

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In this study, statistical analysis was conducted for six responses: cell density, biovolume, Lipid

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(C-H)/Amide II’, Lipid (CH=CH)/Amide II’, Lipid (C=O)/Amide II’, and Amide I/Amide II’. As

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for the control experiments, there were no significant factors for cell density, biovolume, Lipid

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(CH=CH)/Amide II’, and Amide I/Amide II’ in such a short exposure test, as shown in SI Figure

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S3. However, for Lipid (C-H)/Amide II’, the significant factors involved were phosphorus

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concentration, temperature * salinity * phosphorus concentration, and temperature. For Lipid

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(C=O)/Amide II’, the significant factors involved were phosphorus concentration, temperature,

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salinity * phosphorus concentration, and temperature * salinity * phosphorus concentration. It

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might be due to the huge amount of neutral lipids stored in Chlorococcum sp., leading to the

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sensitive changes of lipids.20 For triclosan exposure experiments, significant main environmental

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factors and their interactions were investigated using a full two-way factorial design (SI Figure

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S4). Statistical analysis was conducted for the same six responses, and these biophysiological

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responses are shown in Figure 1. The assumptions underlying ANOVA including the

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independence of individual observations, normal distribution of random errors, and homogeneity

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of variance of random errors were verified (SI Figure S5). The contribution of each

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environmental factor is also shown in SI Table S4.

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3.1 Cell density analysis 8 ACS Paragon Plus Environment

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The use of populations allows a realistic assessment of community-level properties to explore the

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effects of perturbations from the environment. Changes in algal culture cell density is a

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commonly-measured parameter in aquatic toxicity testing. There were several significant

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interactions among experimental variables (SI Table S5). It is interesting to note there were

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positive effects for all interactions. In detail, nitrogen increase had a positive effect on algal

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density at 23 °C, and a negative effect at 15 °C (Figure 2A). This indicates nitrogen increase

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could stimulate cell division when the temperature approached the optimum level. Usually, an

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inhibition of cell division can be caused by salinity increase, associated with a depression of

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photosynthetic activity, including in Chlorococcum.21 The interactive effects of NaCl

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concentration and nitrogen concentration were more complex (Figure 2B). When the NaCl

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concentration was at its higher concentration (15 ‰), increased nitrogen showed a positive effect

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on algal growth in the presence of triclosan. The highest density (687 500 cells mL-1) was

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observed at 23 °C, 0.25 ‰ NaCl, and 150 µM phosphorus (SI Figure S6A). When exposed to

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triclosan, a significant increase in algal density occurred as phosphorus decreased. A similar

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trend was reported in a previous study, in which algal biomass significantly increased at the same

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time as phosphorus significantly decreased in a 22-years investigation of 13 lakes distributed all

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over Sweden18. At 23 °C, 15 ‰ NaCl, and 8 mM nitrogen concentration, the highest density was

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750 000 cells mL-1 (SI Figure S6B). As for Scenedesmus quadricauda, the algal density became

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highest at 23 °C, 12 ‰ NaCl, and 1.5 g/L NaNO3, while the value decreased under changing

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conditions.22 The highest density of 601 563 cells mL-1 occurred at 0.25 ‰ NaCl, 8 mM nitrogen,

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and 300 µM phosphorus (SI Figure S6C). It indicated that the optimal condition under the

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interaction of those factors and triclosan was consistent with the ordinary BG-11 media.



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3.2 Biovolume analysis

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Cell size is a fundamental characteristic of all organisms, which is related to cell cycle

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progression and influenced by internal and external stimuli.23 Biovolume has been considered as

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a life-history feature to analyze algal-chemical interaction and subsequent sensitivity.24 In the

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present study, biovolume was used to assess within-population effects influenced by triclosan

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exposure. Statistically significant factors are shown at 5 % level in SI Table S5. When

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temperature, pH and NaCl concentration reached 15 °C, 6.5 and 0.25 ‰, respectively, the largest

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cell volume was 2.55 mm3 (SI Figure S6D). The interaction of temperature, pH and NaCl

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concentration under triclosan exposure had the largest contribution to cell biovolume among all

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three-level negative interactions. The smallest cell volume was 1.36 mm3, with pH 6.5, 4 mM

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nitrogen and 150 µM phosphorus (SI Figure S6E). When pH, nitrogen concentration and

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phosphorus concentration were 6.5, 8 mM and 300 µM, respectively, the largest volume was

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2.50 mm3 (SI Figure S6E). It had the most significant difference in volume range under triclosan

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exposure among all three-level interactions. Figure 3A shows biovolume decrease as a result of

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phosphorus decrease. When cells are in a phosphorus-limited environment, RNA can be used as

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a main phosphorus reserve, inhibiting membrane build up and cell grow.25 At the same time,

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cells may also suffer from triclosan-induced membrane dysfunction.26 Elevated nitrogen had a

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positive effect on biovolume at 23 °C, and it had a negative effect at 15 °C (Figure 2A). It might

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be because nitrogen supplement can improve enzyme viability and enlarge cell size when

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approaching the optimal temperature under triclosan exposure.27 Increased phosphorus had a

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positive effect on biovolume when pH was 6.5, and had a negative effect at pH 8.0 (Figure 2C).


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In general, the neutral form of triclosan, which occurs in an acidic environment, is more toxic

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than its ionized form at higher pH.28 However, in this situation, the toxic effect could be hidden

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or modified by the interactive effects between pH and phosphorus concentration.

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3.3 Biochemical composition analysis

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SR-FTIR spectromicroscopy is an emerging bioanalytical tool. Synchrotron IR light is an ideal

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source with a high brightness, 100-1000× brighter than a conventional thermal IR source.29 This

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unique technique provides mid-IR spectra of specific subcellular compartments with high signal-

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to-noise at diffraction-limited spatial resolutions as fine as 3 to 10 microns.30 Mid-IR photons are

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low in energy (0.05-0.5 eV), which enables high-throughput noninvasive spectroscopic

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microanalysis.31 These provides SR-FTIR with high feasibility of in-vivo study of single cell.

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Moreover, the main cell components have distinct functional groups, such as lipids and proteins,

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which are featured by the corresponding absorbance characteristics in mid-IR spectra (SI Table

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S6).10, 32 Thus, the variation of macromolecular pools in response to environmental changes

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under triclosan exposure can be qualified and quantified simultaneously by SR-FTIR

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spectromicroscopy.33 To correct cell-to-cell variation in IR absorption spectra, an internal

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reference was chosen to evaluate the relative contents of lipids and proteins (SI Figure S7).10

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Amide II’ was used as a suitable band for normalization of SR-FTIR spectra and ratio

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determination due to its minimal variation among all targeted functional groups (Figure 4A).34, 35

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3.3.1 Lipid analysis

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Lipids in algae can be categorized into two groups: storage lipids and structural lipids.36, 37

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Storage lipids are primarily triacyglycerols composed of predominately saturated fatty acids and

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some unsaturated fatty acids. Structural lipids usually have a high content of polyunsaturated

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fatty acids. Phospholipids and sterols are essential structural constituents of biological

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membranes which act as a selectively permeable barrier for organelles and cells. These lipids can

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maintain membrane functions and provide a wide variety of metabolic lipids, which are key

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intermediates or their precursors in cell signaling pathways and important responses to

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environmental changes.38, 39

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Lipid (C-H)/Amide II’ is ideal for analyzing aliphatic groups of total lipids observed from 3000-

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2800 cm-1, which mainly originate from hydrocarbon chains. The related statistical factors are

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shown in SI Table S5. In the presence of triclosan, phosphorus had the largest positive effects,

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while temperature * pH * NaCl concentration, temperature * pH * NaCl concentration *

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phosphorus and nitrogen showed more negative effects than other factors.

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High phosphorus levels result in an increase in Lipid (C-H)/Amide II’ (Figure 3A). Other work

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indicated phosphorus did not influence lipid accumulation.40, 41 However, our study showed an

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increase in saturated lipids in Chlorococcum sp., when exposed to triclosan under phosphorus-

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replete conditions. Overall, it appears that the effects phosphate supply on algal lipid

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accumulation is variable and species-dependent, with some experiments suggesting only minor

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effects,36, 37 and other experiments suggesting either upregulation or downregulation depending

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on the algal group that is being tested.38 Moreover, the repletion of phosphorus favors the

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generation of phospholipids, contributing to increase the content of saturated lipid groups,38


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especially under the stimulation effect of low-level triclosan. As shown in Figure 2D, nitrogen

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reduction enhanced Lipid (C-H)/Amide II’ from 6.60 to 7.43 at pH 8.0. When pH was 6.5, the

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ratio increased more from 5.66655 to 18.8937. It indicated under the increase of nitrogen

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concentration, low pH made saturated lipid groups more sensitive to triclosan exposure. The

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interaction of above three factors during triclosan exposure was also significant (SI Table S5).

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Increasing nitrogen resulted in a rise of Lipid (C-H)/Amide II’ from 3.94 to 5.79 at 23 °C, and a

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reduction from 8.47 to 6.38 at 15 °C (Figure 2A). Fatty acids became more vulnerable to the

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damaging effect of triclosan. Low temperature could reduce enzyme activity, slowing down the

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metabolic rate and weakening the resistance to triclosan. Moreover, algal cells could absorb or

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assimilate less nitrogen to produce effective enzymes for lipid production. Figure 3B shows

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decreasing nitrogen resulted in an increase in Lipid (C-H)/Amide II. It was reported that lipid

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content of alga Nannochloropsis salina significantly increased by 56.1% in a low nitrogen

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medium.42 Even under triclosan exposure, nitrogen limitation could lead to lipid accumulation

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especially in the content of saturated fatty acids and monounsaturated fatty acids. As phosphorus

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increased with triclosan exposure, the ratios decreased from 10.15 to 6.33 when pH was 8.0, but

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the ratios slightly increased when pH was 6.5 (Figure 2C). Triclosan can affect algae primarily

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through inhibiting fatty acid synthesis.15 In an acidic environment, the neutral form of triclosan is

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more toxic than its ionized form when pH gets close to its pKa.28 However, algae can adapt to

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acidic conditions by increasing its saturated fatty acid content, which would reduce membrane

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fluidity and high proton concentrations.43 The results of this study suggested that the effects of

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algae acclimation had more influence than the effects of triclosan under the interaction of pH and

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phosphorus concentration. There was a less increase in Lipid (C-H)/Amide II with rising



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phosphorus at 23 °C than at 15 °C (Figure 2E). Triclosan may exhibit more significant effects on

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phosphorus uptake and assimilation at higher temperatures, owing to its active movement.44

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To assess the degree of unsaturation in lipids, Lipid (CH=CH)/Amide II’ was further used to

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represent unsaturated fatty acids within the algal cells. CH=CH vibration was observed around

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3010 cm-1 and the corresponding statistic significant factors are shown in SI Table S5. Nitrogen,

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temperature * phosphorus, pH * phosphorus, temperature * pH * NaCl concentration, and

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temperature * pH * NaCl concentration * phosphorus contribute negatively, while phosphorus,

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temperature * nitrogen, and pH * nitrogen contribute positively. These results are similar to those

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regarding Lipid (C-H)/Amide II’. Such similarity indicates two types of ratios are relative in a

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way and those common significant factors can be used to reflect the changes of unsaturated

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group from fatty acids/lipids upon triclosan exposure. In addition, temperature * pH * NaCl

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concentration exhibited the most negative effect with 16 % and temperature * pH * NaCl

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concentration * phosphorus showed less negative effect with 6.13 %. It suggests the significant

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contribution from high-order interactions. Generally, it’s not common to see significant high-

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order interactions, and it is difficult to interpret from a practical viewpoint.

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Furthermore, pH, temperature * pH * phosphorus, and temperature * NaCl concentration *

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phosphorus, only showed negative effects on Lipid (CH=CH)/Amide II’. As pH increased from

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low to high (Figure 3C), the amount of unsaturated groups decreased. This is corresponding with

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the interactive effects of phosphorus concentration and pH on Lipid (C-H)/Amide II’. It was

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reported that some species could adapt to acidic conditions by increasing levels of long-chain,


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mono-unsaturated fatty acids.45 Such adaptative response could also play an important role in the

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effect of environmental changes under triclosan exposure.

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In order to explore the variation of total lipids in algal cells, Lipid (C=O)/Amide II’ was used to

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represent C=O stretches of ester carbonyl group from lipid triglycerides and fatty acids at

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wavenumber around 1740 cm-1. Temperature * pH * phosphorus caused the most negative effect,

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with a contribution of 15.29 %. Increased pH resulted in the reduction of Lipid (C=O)/Amide II’,

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which also matched the above results (Figure 3C). Phosphorus contributed the most positive

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effect with 12.99 % (SI Table S5). Figure 3A shows phosphorus increase led to the rise of this

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ratio. Due to the close relationship with phospholipids production, phosphorus became the most

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significant factor for this ratio under trilosan exposure. In addition, phosphorus presented

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positive effects no matter at which pH level/temperature. This is also consistent with the

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significant effects caused by phosphorus (Figure 2C & E).

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3.3.2 Protein analysis

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Amide I/Amide II’ can display the relative content of Amide I, arising mainly from the C=O

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stretching vibration with minor contributions from the out-of-phase CN stretching vibration,

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CCN deformation and NH in-plane bend.46 The Amide I vibration depends on the secondary

342

structure of the protein backbone.46 Temperature * pH * NaCl concentration and temperature *

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pH * NaCl concentration * phosphorus showed the largest negative effects, contributing 6.77 %

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and 6.45 %, respectively (SI Table S5). Such high-level interactions indicated the complexity of

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the involved factors. Phosphorus had the largest positive effect contributing 7.76 %. Decreased



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phosphorus resulted in the reduction of Amide I/Amide II’ (Figure 3A). It seems lack of

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phosphorus can lead to the reduction of protein content, especially under triclosan exposure. This

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could be reflected in the change of secondary structure content.47 Nitrogen increase had a

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negative effect on Amide I content when pH was 6.5, and it had a slight positive effect when pH

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was 8.0 (Figure 2D). When pH interacted with nitrogen, the molecular state of triclosan in an

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acidic environment could be more toxic to Amide I. Negative effects were observed as nitrogen

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increased at both 15 and 23 °C, but the ratio decreased slightly at 23 °C (Figure 2A). It indicated

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the protein secondary structure of Chlorococcum sp. may be less sensitive to triclosan at higher

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temperatures, due to the higher metabolic rate and enhanced cellular repairing capability.

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Nitrogen increase resulted in a large decrease of the ratio (Figure 3B). Compared with triclosan,

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nitrogen increase had little or no positive effect on protein secondary structure. Nitrogen uptake

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capabilities might be inhibited by the presence of triclosan.44 As for phosphorus, its increase

358

showed positive effects on the ratio at 15 and 23 °C and pH 6.5 and 8.0 (Figure 2C&E). Such

359

ratio increases were more evident at higher temperature and pH under triclosan exposure.

360

Phosphorus is a component of DNA, RNA and ATP. The increase of phosphorus may facilitate

361

the synthesis of those cellular components and intensify the involvement of various enzymes in

362

this process.48

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363 364

Amide I vibration is most commonly used to analyze protein secondary structures.49 The Amide

365

I band can be decomposed into spectral bands that reveal structural characteristics, including α-

366

helix (1660 - 1647 cm-1), β-sheet (1634 - 1625 cm-1, 1694–1672), turns (1691–1653) and

367

unordered structure (1648 - 1637 cm-1) content. The related errors in the prediction are within 7%

368

based on secondary derivative spectra.49 Since there was overlap between antiparallel β-sheet


Page 17 of 34


369

and turns in spectra, this study focuses on α-helix, parallel β-sheet, and unordered structure

370

(Figure 4B&C). SI Table S7 shows the ratio of α-helix to parallel β-sheet structure content based

371

on the spectra intensity in factorial experiments, as well as some results for unordered /β-sheet.

372

The variation of ratio and the appearance of unordered structure indicates the change of protein

373

secondary structure depending on hydrogen bonding. The corresponding increase in

374

intermolecular β-sheet structure centered at 1630 cm-1 along with the decrease of α-helix

375

structure could be caused by protein oligomerization which would lead primarily to the

376

formation of octameric structures.50 Those changes may relate to protein aggregation when

377

exposed to triclosan and changing environmental stressors.

378 379

3.4 Principal Component Analysis

380 381

PCA can help reduce the dimensionality of the data and determine the key variables in a

382

multidimensional data set.51, 52 In the present study, PCA of cell density, biovolume, Lipid (C-

383

H)/Amide II’, Lipid (CH=CH)/Amide II’, Lipid (C=O)/Amide II’, and Amide I/Amide II’ was

384

conducted and a statistical distinction is shown through a biplot display in Figure 5A. PC1

385

describes 65 % of the variances, and PC2 describes 16 %. The biovolume, Lipid (C-H)/Amide

386

II’, Lipid (CH=CH)/Amide II’, Lipid (C=O)/Amide II’, and Amide I/Amide II’ are located at the

387

positive side of PC1, while only cell density is at the negative side. The cell density and

388

biovolume are located at the positive side of PC2, while Lipid (C-H)/Amide II’, Lipid

389

(CH=CH)/Amide II’, Lipid (C=O)/Amide II’, and Amide I/Amide II’ are at the negative side.

390

The cell density is farthest away from other variables, and the biovolume is less farther from

391

other molecular ratios. Four molecular ratios get closer with each other. Among them, Lipid (C-



392

H)/Amide II’ are nearest to Amide I/Amide II’, and Lipid (CH=CH)/Amide II’ is a little farther,

393

while Lipid (C=O)/Amide II’ is farthest.

394 395

As for the impact of environmental stressors under triclosan exposure, the relevance of saturated

396

groups of lipids to the protein backbone is the most abundant. Next are unsaturated groups, and

397

finally ester carbonyl groups from total lipids. It is consistent with the results of factorial analysis

398

above. The distinctions among six variables at community-, cell- and molecular-level profiles are

399

evident, and some correlations among four biochemical components are probably existent.

400 401

PCA of variances in factorial experiments were performed to further analyze the data

402

considering all groups. 100% of the variances (96.996 % and 3.004 %) were explained through a

403

biplot as shown in Figure 5B. Among all 32 groups, only group 12 is located at the negative side

404

of PC1 and at the positive side of PC2, while others are overlapped. It indicated that the short-

405

term toxicity with low-level triclosan did not demonstrate evident distinctions among all groups

406

based on six biophysiological responses.

407 408

In addition to differentiating the toxic effects of triclosan on lipids, multivariate analysis of

409

second derivative spectra for Lipid (C-H) was also conducted. The 3000-2800 cm-1 range

410

contains C-H stretching bands from different vibrational modes: nas(CH2) near 2920 cm-1, ns(CH2)

411

near 2850 cm-1, nas(CH3) near 2960 cm-1, and ns(CH3) near 2870 cm-1 (Figure 4D). These

412

vibrational modes are independent from lipid head group, and they are sensitive to the disordered

413

chain structure.53 The range of 3000-2800 cm-1 was further investigated using PCA to determine

414

what extent all groups could be differentiated (Figure 5C). The results showed PCA clearly


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415

resolved the data into two major components. PC1 accounted for 98.887 % of the variation and

416

PC2 accounted for 1.113 %. A clear separation of two big clusters can be seen in the plot. One

417

cluster includes group 4, 19, 11, 8, 9, 7, 15, 25, 18, 21, 26, 3, 5, 29, 10, 27, 2, 28, 12, 13 and 17.

418

The other one includes group 14, 24, 1, 23, 30, 22, 31, 32, 20, 16, and 6. The former groups are

419

located at the positive side of PC1 and the positive side of PC2. The latter groups are located at

420

the negative side of PC1 and the negative side of PC2. The groups in each cluster are close but

421

differently located, indicating they have a close relationship but still with a little difference.

422

Triclosan can affect algae primarily via inhibiting fatty acid synthesis.15 For short-term triclosan

423

exposure, 32 groups can be differentiated based on the changes in saturated fatty acids.

424 425

Green microalgal cell is an organic integrity. Its biochemical components are closely related to

426

physical properties, such as, cell size and cell structure.54 The inherent correlations of

427

biochemical components are closely associated with community performance, such as biomass

428

growth. SI Table S8 shows the linear regression coefficients between four molecular ratios and

429

corresponding cell density/biovolume. Biovolume presented a better simulation result with a

430

higher R value of 0.744, suggesting 74.4 percent of positive correlation between those

431

biochemical components and biovolume.55 It was reported that vesicles containing lipids and

432

proteins could fuse with the cell membrane to increase cell size.56 It indicated the interactive

433

relation between biomacromolecules and cell size. In comparison, cell density had no good

434

regression with a lower R value of 0.327, meaning only 32.7 percent of positive correlation

435

between those biochemical components and cell density. It might be due to the systematic

436

complexity of microalgal populations in the presence of the differences from individual cells.

437



438

3.5 Environmental significance

439 440

The toxicity of triclosan to algae in the aquatic environment is complex. It can be influenced by

441

various inherent and apparent factors. For example, when exposed to triclosan, the concentration

442

and physicochemical characteristics of triclosan, as well as exposure time and toxicity

443

mechanism play important roles. Otherwise, the prevailing environmental factors can also exert a

444

physiological background stress to influence the toxic effects of triclosan.57 It is still challenging

445

to clearly understand the toxicity of triclosan over micro- and mesocosms at cellular and

446

subcellular levels.

447 448

To address such challenges, this study provided an insight into the toxicity of triclosan to green

449

microalga Chlorococcum sp. under multiple environmental stressors using synchrotron-based

450

Fourier transform infrared spectromicroscopy. For different responses in factorial analysis, there

451

were some common significant main effects and interactions from environmental stressors. Such

452

significant factors had the consistent positive or negative effects, but their contributions to

453

specific responses were different. Phosphorus concentration, pH * phosphorus concentration,

454

temperature * pH * NaCl concentration were the most statistically significant factors for all

455

responses, except cell density. It demonstrated the variation of those factors would have a huge

456

impact on biophysiological performances under triclosan exposure. The involved organelles and

457

organic molecules within algal cells have their own particular structures and functions. They can

458

work not only independently but also cooperatively, which might be the reason for being

459

influenced simultaneously.

460


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461

Phosphorus concentration had positive effects in all conditions. When triclosan attacked fatty

462

acids of the green microalga, the supplement of phosphorus could alleviate this damage. In

463

reality, along with the discharge of triclosan, phosphorus from detergents, fertilizers and other

464

anthropogenic sources are widely distributed in water sources. It is interesting to find green

465

microalgae may become more resistant against triclosan in such phosphorus-enriched

466

environment. Similar effects were also observed in some previous studies. It was reported that

467

cyanobacteria became more tolerant to atrazine, particularly with increased phosphorus supply.

468

This further supported the hypothesis that the prevalence of cyanobacterial blooms in European

469

aquatic systems might arise from a combination of unbalanced nutrient enrichment and selective

470

pressures from multiple toxicants.58 Moreover, the tolerance induction of periphytic communities

471

to copper was probably related to the higher phosphorus availability. It verified that periphyton

472

from oligotrophic streams was more sensitive to copper than periphyton from fertilized streams

473

(mainly P).59 As a similar case, it was stated that phosphorus supplement could enhance the

474

resistance of algae Chlamydomonas geitleri Ettl and Chlorella vulgaris Beyerinck more to

475

copper toxicity than nitrogen supplement.60 The negative effects of the interaction of pH *

476

phosphorus concentration revealed that the toxicity of triclosan at acidic environment could be

477

hidden by specific environmental conditions such as nutrient availability. Furthermore,

478

temperature * pH * NaCl concentration contributed significantly, even though the involved

479

single effects were insignificant in some cases. It demonstrated the effects of high-order

480

interactions can obscure that of single effects. Even though the effect of each involved single

481

factor was trivial, there might be crossover interactions when combining them. It verified that the

482

effect of one factor depended on the level of the others. This finding is of particular interest to

483

assess triclosan toxicity in natural aquatic ecosystem with complex environmental conditions.



484

Moreover, interestingly, for the responses of lipid functional groups and Amide I, some common

485

significant factors were found. The reasons are as follows. On the one hand, the frequency of C-

486

H stretching of lipids also indicated C-H stretching of proteins, while lipids still made the major

487

contribution. On the other hand, it also indicated some inter-relations among lipids and proteins,

488

which may happen in microalgal structures (e.g. membrane proteins, and lipoproteins) or

489

functions (e.g. enzyme-involved lipid synthesis).47

490 491

In addition, the distinctions of significant factors between any two responses were also present.

492

Particular significant factors from multiple environmental stressors showed the impacts of

493

triclosan on the corresponding response of Chlorococcum sp. owing to the specific structure and

494

performance of biomolecular components. For cell density and biovolume, most of significant

495

factors were two-or three-order interactions. This suggested triclosan toxicity to living organisms

496

at community and individual-cell levels would be more complex than that at subcellular level.

497

Moreover, the high-order interactions of temperature * pH * NaCl concentration and temperature

498

* pH * NaCl concentration * phosphorus concentration had more contributions than others at

499

subcellular level, which might be due to the interactive complexity of biomolecular components.

500 501

Fatty acids within microalgae were the most sensitive targets in the exposure of triclosan.

502

Therefore, fatty acids can be potentially used as a fingerprint for future assessment of triclosan

503

toxicity to other algal species. However, it was noted there were some undistinguishable groups.

504

That can be attributed either to the existence of cellular self-regulation or short exposure time.

505

Cells are capable of acclimating to environmental stressors in a variety of ways to promote

506

survival and mitigate damage. As a response to environmental changes, such acclimation can


Page 22 of 34

Page 23 of 34


507

help cells defend against and recover from the stress.61 The presented biophysiological changes

508

of Chlorococcum sp. under triclosan exposure might involve the self-regulation mechanism, and

509

thereby the distinctions caused by multiple environmental stressors could be undramatic. Along

510

with the extension of exposure time, the toxicity of triclosan on green algae might be enhanced

511

and even amplified, which is more common in real-world problem.

512 513

The finding of this work can help examine the response of primary producers to triclosan from

514

biochemical view under multiple environmental stressors. It makes up for the deficiency in

515

previous studies regarding the interactive complexity among emerging pollutants and multiple

516

environmental stressors. This is also the first time to combine factorial and SR-FTIR analyses to

517

reveal interactive effects in response to biophysiological changes. The inter-correlations of all

518

biophysiological responses and treatment groups in the short-term toxicity test were explored.

519

These findings suggest that multiple environmental stressors should be considered during

520

ecological risk assessment and environmental management of emerging pollutants. Factorial

521

design is an effective and viable approach to help reveal such interactive relations. SR-FTIR

522

analysis could be applied to explore the in-vivo interactive effects at biophysiological level of a

523

single cell. For the future perspective, toxic effects of triclosan on higher trophic-level aquatic

524

organisms under multiple environmental stressors will be explored.

525 526

Supporting Information

527 528

The Supporting Information is available free of charge on the ACS Publications website at DOI:

529

***.



530

Figures showing the images of unicellular microalga Chlorococcum sp., Canadian light source

531

and Mid-IR equipment, half-normal probability plot of the effects, normal plot of residuals for

532

control experiments and triclosan exposure experiments, three-order interactions in toxicity

533

assessment, and average SR-FTIR absorption spectra. Tables showing the characteristics of

534

triclosan, the design matrix of the 25 full factorial design, significant factors and their

535

contributions in toxicity assessment, assignment of the major bands in SR-FTIR of

536

Chlorococcom sp., the average ratio of α-helix / β-sheet and unordered / β-sheet in toxicity

537

assessment, and calculated parameters of linear regression models for the simulation of cell

538

density and biovolume.

539 540

Acknowledgements

541 542

This research was supported by the Natural Science and Engineering Research Council of

543

Canada, the Canada Foundation for Innovation (CFI) and the Canada Research Chairs Program

544

(CRC). The authors are thankful to the Mid Infrared beamline at Canadian Light Source for

545

providing support in measurements and analysis. Research described in this paper was performed

546

at the Canadian Light Source, which is supported by the Canada Foundation for Innovation,

547

Natural Sciences and Engineering Research Council of Canada, the University of Saskatchewan,

548

the Government of Saskatchewan, Western Economic Diversification Canada, the National

549

Research Council Canada, and the Canadian Institutes of Health Research. The authors are

550

particularly grateful to the editors and the anonymous reviewers for their insightful comments

551

and suggestions.


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TOC



8

6

5

Cell density (10 cells/mL)

(A)10

4

2

0 1

(B)

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Run

4

3 Biovolume (mm )

3

2

1

0

Ratio of biochemical responses (%)

(C) 50

1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Run Lipid(CH=CH) / Amide II' × 10 Amide I / Amide II' Lipid(C=O) / Amide II' Lipid(C-H) / Amide II'

40

30

20

10

0

1

2

3

4

5

6

7

8

9

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32

Run

Figure 1. Biophysiological responses of green microalgae Chlorococcum sp. to triclosan in factorial experiments: (A) cell density, (B) biovolume and (C) ratio of biochemical responses.


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15 °C 23 °C

2.16

1.98

1.80

NaCl 0.25 ‰ NaCl 15 ‰

3.95

4

8

Nitrogen concentration (mM)

pH 6.5 pH 8.0

2.24

1.96

1.68

pH 6.5 pH 8.0

9.84

7.38

4.92

(E)

8.95

pH 6.5 pH 8.0

7.16 5.37

7.25

5.80 pH 6.5 pH 8.0 4.35

6.33 15 °C 23 °C

4.22

pH 6.5 pH 8.0

1.41

0.94

0.47

15 °C 23 °C

8.48 6.36 4.24

15 °C 23 °C

1.23

0.82

0.41

8

Nitrogen concentration (mM) Amide I/Amide II'

Lipid(C=O)/Amide II'

Lipid(C-H)/Amide II'

4

8.44


4.05

4.74


5.40

5.53

Amide I/Amide II'

15 °C 23 °C


6.75

(D)

(C) 3 Biovolume (mm )

(B) 5 Cell density (10 cells/mL)

3 Biovolume (mm ) Cell density (105 cells/mL)

(A)


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7.00

15 °C 23 °C

5.25

3.50

150

300

Amide I/Amide II'

Amide I/Amide II'

Phosphorus concentration (µM) 6.25

5.00 15 °C 23 °C

3.75

4

8

Nitrogen concentration (mM)

pH 6.5 pH 8.0

7.25

5.80

4.35

300

150

Phosphorus concentration (µM)

Figure 2. Two-order interactions of (A) temperature * nitrogen concentration, (B) NaCl concentration * nitrogen concentration, (C) pH * phosphorus concentration, (D) pH * nitrogen concentration, and (E) temperature * phosphorus concentration in toxicity assessment.



1.96

1.82

Lipid(CH=CH)/Amide II'


2.10

6.93

5.94

4.95

6.36

4.77

0.098

0.084

0.070


7.95

Amide I/Amide II'

3 Biovolume (mm ) Lipid(C-H)/Amide II'

(C)

(B)

(A)

Page 32 of 34

5.31

4.72

4.13

0.80

0.64

0.48

Amide I/Amide II'


4

8

Nitrogen content (g/L)

0.96

6.5

8.0

pH

0.72

0.48

5.74

4.92

4.10

150

300

Phosphorus concentration (µM)

Figure 3. Main effects of (A) pH, (B) nitrogen, and (C) phosphorus on biophysiological responses under triclosan exposure.


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(A)

(B)

0.30

d 2 (A )/d ( ν ) 2

A b so rb a n ce

0.45

Lipid(C-H) Amide I Lipid(C=C)

0.15

β-sheet

Amide II’

α-helix Lipid(C=O)

0.00 1300 1400 1500 1600 1700

1596 1608 1620 1632 1644 1656 1668 1680 1692 1704 1716

27502800285029002950300030503100 -1

(C)

-1

(D)

Wavenumber (cm )

Wavenumber (cm )

ns(CH2)

nas(CH2)

parallel β-sheet

d 2 (A )/d ( ν ) 2

d 2 (A )/d ( ν ) 2

nas(CH3)

unordered structure

ns(CH3)

α-helix

1596 1608 1620 1632 1644 1656 1668 1680 1692 1704 1716

2800

-1

2825

2850

2875

2900

2925

2950

2975

3000

-1

Wavenumber (cm )

Wavenumber (cm )

Figure 4. SR-FTIR spectra from the toxicity assessment of triclosan on green microalgae Chlorococcom sp.: (A) average SR-FTIR absorption spectra of Run 1, (B) the second derivative spectrum of SR-FTIR of Run 1 in the 1724-1585 cm-1 region, (C) the second derivative spectrum of SR-FTIR of Run 16 in the 1724-1585 cm-1 region, (D) the second derivative spectrum of SRFTIR of Run 1 in the 3000-2800 cm-1 region.



(A)

1

(B)

(C)

2 3 4 5 6 7 8 9 10 11

Figure 5. The principal component analysis (PCA) biplot: (A) Scatter diagrams of factor loads of six responses, (B) Scatter diagrams

12

of factor loads of 32 groups at all responses, (C) Scatter diagrams of factor loads of 32 groups at the range of 3000-2800 cm-1.


Page 34 of 34

Insights into the Toxicity of Triclosan to Green Microalga

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