Identification of cypermethrin induced protein changes in green algae by iTRAQ quantitative proteomics

    Identification of cypermethrin induced proteins changes in green algae by iTRAQ quantitative proteomics Yan Gao, Teck Kwang Lim, Qingsong Lin, Sam Fong Yau Li PII: DOI: Reference:

S1874-3919(16)30066-5 doi: 10.1016/j.jprot.2016.03.012 JPROT 2451

To appear in:

Journal of Proteomics

Received date: Revised date: Accepted date:

25 November 2015 1 March 2016 2 March 2016

Please cite this article as: Gao Yan, Lim Teck Kwang, Lin Qingsong, Li Sam Fong Yau, Identification of cypermethrin induced proteins changes in green algae by iTRAQ quantitative proteomics, Journal of Proteomics (2016), doi: 10.1016/j.jprot.2016.03.012

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Identification of Cypermethrin Induced Proteins Changes in Green Algae by iTRAQ

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Quantitative Proteomics

Department of Chemistry, Faculty of Science, National University of Singapore,

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Yan GAO1, Teck Kwang LIM2, Qingsong LIN*2,3, Sam Fong Yau LI*1,3

Singapore 117543, Singapore

Department of Biological Science, Faculty of Science, National University of Singapore,

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NUS Environmental Research Institute, National University of Singapore, Singapore

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117411, Singapore

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Singapore 117543, Singapore

Corresponding authors

Tel.: +65 65167769; Fax: +65 67792486 E-mail address: [email protected] (Q. Lin). Tel.: +65 65162681; Fax: +65 67791691. E-mail address: [email protected] (S.F.Y. Li).

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ACCEPTED MANUSCRIPT Abstract Cypermethrin (CYP) is one of the most widely used pesticides in large scale for

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agricultural and domestic purpose and the residue often seriously affects aquatic system.

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Environmental pollutants induced protein changes in organisms could be detected by proteomics, leading to discovery of potential biomarkers and understanding of mode of

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action. While proteomics investigations of CYP stress in some animal models have been

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well studied, few reports about the effects of exposure to CYP on algae proteome were published. To determine CYP effect in algae, the impact of various dosages (0.001 µg/L,

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0.01 µg/L and 1 µg/L) of CYP on green algae Chlorella Vulgaris for 24h and 96h were investigated by using iTRAQ quantitative proteomics technique. A total of 162 and 198

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proteins were significantly altered after CYP exposure for 24h and 96h, respectively. Overview of iTRAQ results indicated that the influence of CYP on algae protein might be

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dosage-dependent. Functional analysis of differentially expressed proteins showed that CYP could induce protein alterations related to photosynthesis, stress responses and carbohydrates metabolism. This study provides a comprehensive view of complex mode of action of algae under CYP stress and highlights several potential biomarkers for further investigation of pesticides exposed plant and algae. Key words: Algae, iTRAQ, cypermethrin, photosynthesis, carbohydrate metabolism, stress responsive Significance The effect of cypermethrin on algae proteome in term of exposure concentrations and durations has been determined using quantitative iTRAQ technique. The

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ACCEPTED MANUSCRIPT results showed that cypermethrin affects proteins related with photosynthesis, stress responsive and carbohydrate metabolism. Overall, this study provides

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comprehensive analysis of green algae protein profiles in response to cypermethrin

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exposure and presents some new information about plant and algae exposure to

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pesticide.

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1. Introduction

Pesticides are widely used for agricultural and domestic purposes but their residues often

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seriously affect aquatic ecosystem. They can be consumed by primary reproducers in aquatic ecosystem and ultimately accumulate in humans. Therefore, it was expected that

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the presence of these pesticides residuals could be detected at an early stage in ecosystem.

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Synthetic pyrethroid pesticides became popular as a replacement for organophosphate

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and organochlorine pesticides in the last decade for environmental and human health consideration and account for over 30% of pesticide use globally[1]. Although pyrethroid pesticides are not persistent chemicals in environment, they are highly toxic to aquatic organisms[2]. They could affect the sodium channels of nerve cells as neurotoxins, resulting in repetitive firing of neuron[3]. The lipophilicity property of pyrethroid pesticides makes them readily absorbed by biological membranes and tissues, leading to high toxicity in non-target organism[4]. Cypermethrin (CYP) is one of the most widely used pyrethroid pesticides in large scale. Several studies reported that the concentrations of cypermethrin were around 0.01- 0.1 µg/L in water system[5, 6] and it has been found in surface waters on a worldwide scale, entering the system from runoff[7]. It was reported that CYP is correlated with oxidative stress, DNA damage and ion channels modulation mechanism, and may induce neurotoxicity and motor deficits in animal 3

ACCEPTED MANUSCRIPT models[8]. These findings have attracted increasing public concerns considering its toxicity associated with environmental and human health.

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It’s challenging to assess the potential risk of exposure to low dosage of chemical

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contaminants, because usually no obvious clinical symptoms can be observed after

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exposure, and information obtained from chemical analysis is not adequate for the understanding of the health risk of these pollutants since chemical analysis only provides

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information at the time of sampling. Proteomics analysis is one possible way to

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investigate molecular changes resulting from exposure before the development of apparent diseases[9], so this technique can provide useful information for toxicity

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assessment and early clinical diagnosis. It was expected that proteomics could detect

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adverse effects at early stage with improved sensitivity when organisms were exposed at

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low dose, resulting in improved risk assessments[10]. Proteomics may provide a comprehensive insight into protein changes upon stresses and reveal the mode of action, and identify potential biomarkers[11, 12]. Quantitative proteomics provides an effective way to identify and quantify proteome of an organism. Two-dimensional gel electrophoresis (2DE) was commonly used for protein quantitation prior to mass spectrometry identification[13]. However, it’s difficult to separate hydrophobic proteins using 2DE method, and the low sensitivity of protein staining significantly affects protein quantification[14]. iTRAQ (isobaric tags for relative and absolute quantitation) is a widely utilized quantitative proteomics approach to obtain relative quantification information of peptides in up to eight samples simultaneously. This method uses several isobaric tags to label peptides from various samples followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis to perform 4

ACCEPTED MANUSCRIPT protein identification and quantitation. Since iTRAQ can quantify proteins from up to eight samples simultaneously, it’s an appropriate method to investigate altered protein

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expression level from control and diseased or treated samples and determine the effect of

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exposure or treatment time on affected organism since it can provide relative quantitation

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information[11, 12, 14].

Previous studies showed that CYP could induce oxidative stress[8] and alteration of

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carbohydrates metabolism[15, 16] in studied organisms. Clinical, occupational or

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environmental exposure to this pesticide may cause serious risks for environment and human. Therefore, it was expected that the presence of CYP residues could be detected at

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an early stage in environment, providing early warnings for potential risks. However,

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most of these studies focused on animal models and no global approach providing insights into altered proteins induced by CYP in green algae has ever been reported.

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Using green algae, a primary reproducer in environment, as a model organism for the proteomics investigation can detect the pollutant hazards as early as possible as compared with other animal models because they are the beginning of the food chain for many other organisms. Once algae consumed the pollutants in water, these harmful pollutants enter food chain and ultimately accumulate in human body, which may have serious threaten to human health. In this context, a quantitative proteomics technique, iTRAQ, was applied to systematically reveal protein changes in algae associated with CYP toxicity. This study indicates that CYP significantly changed the protein expression levels in green algae Chlorella Vulgaris compared with the control samples. The significantly altered proteins were mainly involved in photosynthesis, stimulus response and carbohydrates metabolism. 5

ACCEPTED MANUSCRIPT 2. Materials and Methods

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2.1 Algae culture and CYP treatment Chlorella Vulgaris (ATCC 9765) was cultivated in 2L glass bottles at room temperature

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with 12/12 light-dark cycle and aerated with 0.4 µm filter-sterilized air. Bold modified

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basal freshwater nutrient solution (Sigma-Aldrich, Singapore) was used as culture

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medium with 50 times dilution. The algae growth was monitored by recording the cell density values (using optical density at 685 nm) at daily intervals until a constant reading

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was obtained, which represented an early stationary growth phase. During exponential phase of algae growth, 12 bottles of green algae were randomly assigned to one control

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group and three CYP treated groups (low dosage, medium dosage and high dosage), each

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group containing 3 biological replicates. The concentrations of CYP used in three treated

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groups were 0.001 µg/L as low dosage, 0.01 µg/L as medium dosage and 1 µg/L as high dosage. These algae samples were exposed to CYP for 24h and 96h, respectively. Harvest of algae was done by centrifugation and lyophilization. Freeze-dried algae samples were stored at -80 °C freezer prior to protein extraction. 2.2 Protein extraction Protein extraction of green algae was performed using phenol/TCA-acetone method based on Wang et al [17] with modifications. Briefly, 100 mg algae sample was suspended in 1 ml pre-chilled extraction buffer I and sonicated on ice for 30 min. After centrifugation at 16 000 × g for 5 min under 4 ◦C, the supernatant was removed and the pellet was rinsed with 0.1 M ammonium acetate in 80% methanol and acetone with 0.07% 2-mercaptoethanol(2-ME), respectively. Equal volumes of Tris-buffered phenol solution 6

ACCEPTED MANUSCRIPT and extraction buffer II were added and the mixture was well mixed followed by 5 min incubation. The sample was centrifuged at 16 000 × g for 5 min under 4 ◦C and the upper

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phenolic phase was collected. This step was repeated on the residual pellet for two more

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times and the phenolic phases collected were combined. Then the solution was precipitated with about five volumes of 0.1 M ammonium acetate in 80% methanol at -20

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◦C overnight. The mixture was centrifuged and the resulting pellet was rinsed with

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methanol and acetone. The pellet was re-suspended in appropriate volume of lysis buffer and incubated at room temperature for 60 min. After centrifugation at 18 000 × g for 60

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min, the supernatant was collected and kept at -80 ◦C until use. Final protein

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manufacturer’s instruction.

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concentrations were determined using BCA kits (Bio-Rad, Singapore) according to

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2.3 Protein Digestion and iTRAQ labeling iTRAQ Reagent 8-Plex kit (SCIEX, Foster City, CA, USA) was used for iTRAQ labeling according to the manufacturer’s protocol with some modifications. iTRAQ labeling reagents 113 and 114 were used to label two biological replicates from control group, and similarly, 115 and 116 (low dosage group), 117 and 118 (medium dosage group), 119 and 121 (high dosage group) were used to label two biological replicates from each group, respectively (Figure 1). Briefly, about 100 µg proteins from each sample were reduced and alkylated using tris-(2-carboxyethyl) phosphine (TCEP) and methyl methanethiosulfonate (MMTS). For digestion, the samples were diluted 10 times using 0.5 M triethylammonium bicarbonate (TEAB) firstly and 10 µL trypsin (w/CaCl2, SCIEX) in water was added to each tube and incubated at 37 ºC for 16h. The next step involved was drying digested peptides sample and reconstituting using 0.5 M TEAB. These samples 7

ACCEPTED MANUSCRIPT were then labeled with iTRAQ labeling reagents and incubated at room temperature for 2h. The eight iTRAQ-labeled peptide samples were then pooled and cleaned up using a

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strong-cation exchange column based on manufacturer’s protocol (SCIEX) to remove

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interfering substance such as excess iTRAQ reagents, organic solvent and sodium dodecyl sulfate (SDS). The sample after clean-up was desalted using a C18 Sep-Pak

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cartridge (Waters, Milford, Massachusetts, USA) and lyophilized. The dried sample was

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reconstituted in 20 mM ammonium formate in water, pH 10 for 2D-LC separation.

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2.4 LC-MS/MS Analysis

Prominence high performance liquid chromatography (HPLC) system (Shimadzu, Kyoto,

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Japan) connected to a reversed-phase column was used to perform the first dimension of

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peptide separation. Around 100 µg of the pooled peptide mixture (via 8 times) was

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injected into an Xbridge C18 column (WATERS Xbridge C18, 3.5 µm, 3.0 mm ×150 mm). Mobile phase A was 20 mM ammonium formate in water, pH 10 and mobile phase B was 20 mM ammonium formate in 80% acetonitrile, pH 10. The flow rate was set to 0.2 ml/min. A total of 79 fractions were collected at 1 minute intervals using the following gradient of mobile phase B: 0% for 5 min, 0-15% for 15 min, 15-40% for 40 min, 40-80% for 1 min, held at 80% for 5 min and 80-0% for 1 min and continued at 0% for another 17min. The eluted fractions were subsequently pooled to 10 fractions and reconstituted with 95% water, 5% acetonitrile with 0.1% formic acid after lyophillzation. The second dimension of peptide separation was performed on an Eksigent nanoLC Ultra and ChiPLC-nanoflex (Eksigent, Dublin, CA, USA) in Trap Elute configuration. The samples were loaded on a 200 µm ×0.5 mm column (ChromXP C18-CL, 3 µm) and eluted on an analytical 75 µm × 15 cm column (ChromXP C18-CL, 3 µm). Peptides were 8

ACCEPTED MANUSCRIPT separated by a gradient formed by mobile phase A (2% acetonitrile, 0.1% formic acid) and mobile phase B (98% acetonitrile, 0.1% formic acid) at a flow rate of 3 µL/min. The

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following gradient elution was used for peptide separation: 5 to 5% of mobile phase B in

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1 min, 5 to 12% of mobile phase B in 19 min, 12 to 30% of mobile phase B in 120 min, 30 to 70% of mobile phase B in 10 min, 70 to 90% of mobile phase B in 2 min, 90 to 90%

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in 7min, 90 to 5% in 6 min and held at 5% of mobile phase B for 10 min.

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The tandem MS analysis was achieved using a 5600 TripleTOF system (SCIEX) under

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Information Dependent Mode. The mass range of 400-1800 m/z and accumulation times of 250 ms per spectrum were applied for precursor ions selections. MS/MS analysis was

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performed on the 20 most abundant precursors (accumulation time: 100 ms) per cycle

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with 15s dynamic exclusion. The recording of MS/MS was acquired under high

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sensitivity mode using rolling collision energy. 2.5 Identification and Quantification of Peptides and Proteins The MS/MS data were searched against a protein sequence database derived from the transcriptome sequencing of Chlorella Vulgaris (total 43410 entries) using PorteinPilot™ software 4.2 (SCIEX) for peptide identification and quantification. The Paragon Algorithm (SCIEX) and ProGroup (SCIEX) were used to eliminate any redundant hits because of sharing peptides between proteins. The MS/MS spectra obtained were searched using the following user-defined search parameters: Sample Type: iTRAQ 8 plex (Peptide Labeled); Cysteine Alkylation: MMTS; Digestion: Trypsin; Instrument: TripleTOF5600; Special Factors: None; Species: None; ID Focus: Biological Modification; Database: Algae Transcriptome.fasta; Search Effort: Thorough; FDR Analysis: Yes; User Modified Parameter Files: Yes. 9

ACCEPTED MANUSCRIPT The MS/MS spectra were searched against a decoy database to estimate the false discovery rate (FDR) for peptide identification. The decoy database consisted of reversed

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protein sequences from the Chlorella Vulgaris database and 5% FDR was set as the

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cutoff threshold. For iTRAQ studies, an unused confidence score ≥1.3 (corresponding to 95% protein confidence level) was used as the identification criterion. The unused score

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is a measurement of all the peptide evidence for a protein that is not better explained by a

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higher ranking protein and it the true indicator of protein confidence. The equation below shows the basic formula to convert percentage confidence to confidence in unused

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protein score[18]. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [19] partner repository with the dataset

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identifier PXD003521.

3. Results and Discussion

3.1 Effect of CYP on the growth of Chlorella Vulgaris The growth of Chlorella Vulgaris in the presence of 0, 0.001µg/L, 0.01 µg/L, 0.1 µg/L and 1 µg/L CYP was assessed during exponential phase using optical density to determine the effect of this pesticide (Figure 2). The presence of CYP in culture medium seemed to decrease the growth rate and the inhibition of 1 µg/L on algae growth was most obvious, resulting in almost 50% decrease in growth rate after 96 hours exposure. According to United States Environment Protection Agency [20], the estimated acute drinking water CYP concentration in surface water is 1.04 µg/L and the chronic drinking water CYP concentration in surface water is 0.013 µg/L. To investigate whether these 10

ACCEPTED MANUSCRIPT mentioned CYP concentrations will affect algae proteome and the possibility of using the altered proteins as biomarkers for the presence of cypermethrin in water, 0.001 µg/L,

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0.01 µg/L and 1 µg/L CYP were added to algae culture media to investigate the dosage

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effect of CYP on algae growth in the following proteomics analysis. The addition of 0.001 µg/L cypermethrin in algae culture medium is to determine whether proteomics

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technique could detect protein level changes induced by a very low concentration of

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cypermethrin. The effect of exposure duration was also investigated in this study: 24h

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exposure as short term study and 96h exposure as long term study. 3.2 Overview of iTRAQ proteomics result

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iTRAQ quantitative proteomics technique was used to determine algae protein samples

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from control group and three CYP-treated groups (after 24h or 96h treatment),

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respectively, to investigate altered proteins related to CYP exposure. Proteomics results were correlated to explain molecular changes due to CYP exposure. Data analysis was performed with cross comparison among two treated samples and two control samples (treated 1/control: 115/113, 115/114, 116/113, 116/114). A cutoff of unused protein score ≥1.3 (corresponding to 95% confidence level in protein identification) and proteins identified by more than a single peptide were subjected to further analysis. A total of 2766 proteins for 24h CYP exposure set and 2099 proteins for 96h CYP exposure set (Table S1 and S2) were identified, respectively. A population statistic was applied to these proteins to determine the ratio of significantly changed proteins between treated group and control group[21]. Briefly, the variation between the average of four replicates (the average of 115/113, 115/114, 116/113 and 116/115 in the low dosage treatment group case) and one was calculated and converted to corresponding percentage variation. 11

ACCEPTED MANUSCRIPT These percentage variations were then plotted against the cumulative percentage coverage (Figure 3). The results showed that most variation falls below the range of 90%

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and therefore the population beyond 90% was considered as significantly altered.

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Applying this criteria to iTRAQ datasets, about 30% variation corresponds to ≥90% coverage of data (Figure 3). Therefore, the cutoff of significantly changed proteins was

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set to >1.30 for up-regulation and <0.77 (1/1.30) for down-regulation. A total of 162 and

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198 proteins were determined as significantly changed proteins after applying the above

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criteria and p value <0.05 (Table S3 and S4).

The Venn diagram[22] (Figure 4) of CYP dosage dependent altered proteins showed that

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medium dosage of CYP induced the most differentially expressed proteins at 24h and 96h,

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and the significantly changed protein lists from various CYP dosages exposure groups is quite different, indicating that the influence of CYP exposure on algae proteins is dosage-

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dependent. Surprisingly, medium CYP dosage-exposure groups had more differentially expressed proteins than high-dosage groups and more up-regulated proteins than downregulated proteins were detected as compared with other groups. One possible explanation is that medium CYP dosage induced algae defense system to enhance its tolerance to CYP stress, but high CYP dosage inhibited most algae biological processes, disabling some responses related to algae defense functions. 3.3 Proteins related to photosynthesis and Calvin cycle Photosynthesis plays an important role as the energy source for algae metabolism, and its efficiency may be drastically affected by environmental stress. Photoreaction system includes photosystem II (PS II), photosystem I (PS I), light harvesting system, cytochrome b6f and ATP synthase[23]. Light harvesting complexes, including 12

ACCEPTED MANUSCRIPT chlorophyll and proteins, harvest light energy and regulate energy flow to reaction center. The light energy is ultimately converted to chemical energy, in the form of nicotinamide

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adenine dinucleotide phosphate (NADPH) and adenosine triphosphate (ATP) after

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flowing through PS II and PS I. The light-independent Calvin cycle and other cellular metabolism could use NADPH and ATP as energy source[23]. In our study, the

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expression levels of several proteins involved in photosynthesis varied between the

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control group and treatment group. Upon exposure to CYP, the expression patterns for

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most proteins related to photosynthesis are complicated. PS II includes reaction center (D1, D2), main antenna proteins (CP43, CP47), oxygen

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evolving complexes (OEE1, OEE2, OEE3) and other small subunits. PS II use light

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energy to channel an electron through acceptors which pump protons to generate ATP before transferring the electron to PS I. PS II reaction center binds to chlorophylls which

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play a role in transferring energy from proximal antenna complexes (CP43, CP47) to reaction center. The antenna proteins also bind to these chlorophylls and transfer excitation energy from PS II antenna towards reaction center. Thus down-regulation of PS II core proteins (D2, CP47 and CP43) upon exposure to CYP might affect the efficiency of PS II energy transfer, which may subsequently affect PS I efficiency and lead to decreased expression of PS I reaction center protein (P700). During short term CYP exposure, the expression level of CP43 was down-regulated at medium dosage exposure while CP47 was decreased at high dosage exposure. It has been reported that the association of CP43 with PS II reaction center is weaker than that of CP47[24, 25]. The alteration of CP43 at medium dosage exposure could be attributed to this loose association and thus this protein is easily affected by CYP stress compared with CP47. 13

ACCEPTED MANUSCRIPT During long term exposure, the expression levels of both CP43 and CP47 were decreased at medium dosage exposure and this could be due to prolonged CYP stress.

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Oxygen evolving complexes are associated with PS II reaction center and act as active

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sites of water oxidation. It was shown that OEE1 and OEE2 are necessary components

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for photosynthetic oxygen evolution [26, 27] and maintaining PS II stability. OEE1 is responsible for oxygen evolution by catalyzing water splitting and provides binding sites

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for OEE2[28]. The function of OEE2 can be replaced by Ca2+ and Cl- while OEE1 cannot

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be. Sugihara et al[28] concluded that OEE1 is the most vital protein for oxygen evolution and PS II stability. The expression levels of two oxygen evolving enhancer proteins

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(OEE1 and OEE2) were increased compared with control samples after short term

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exposure to CYP, but long term exposure led to down-regulation of OEE2. Upregulations of OEE1 and OEE2 might be required to repair protein damage and stabilize

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PS II caused by short term CYP stress. Decreased expression of OEE2 might be due to reduced photosynthesis efficiency after long term exposure of CYP. Limited OEE1 is susceptible to degrade PS II reaction center proteins, but excess OEE1 does not affect reaction-center protein accumulation[29]. Therefore, the observation that PS II core proteins (D2, CP43, and CP47) were down-regulated while oxygen evolving complexes (OEE1, OEE2) were overexpressed was reasonable. Comparing CYP treated algae protein samples with control samples, the most dramatic change observed was ribulose bisphosphate carboxylase (RuBisCO). This enzyme was decreased after short term exposure, followed by overexpression after long term exposure. RuBisCO is a key enzyme in Calvin cycle and catalyzes the transfer of carbon from carbon dioxide to organic sugars [30]. Decreased RuBisCO might indicate that CYP 14

ACCEPTED MANUSCRIPT causes disruption of Calvin cycle and thus disturb PS II. Prolonged exposure to CYP resulted in overexpression of RuBisCO, possibly because this enzyme plays an important

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role in stress adaption. It was proposed that increased amount of RuBisCO can be

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beneficial for the survival of plants under certain environment stress[31].

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3.4 Stress responsive proteins

Altered proteins involved in response to stimulus was expected after exposure to CYP, as

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reviewed by Singh et al [8]. As exposure to CYP represents environmental stress to green

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algae, the common responses cells used to manage stress was expected [32]. The quantitative iTRAQ proteomics analysis showed several proteins related to stress

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response significantly altered between CYP treated and control conditions. The result of

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altered proteins during CYP stress in Chlorella Vulgaris revealed that two chaperone proteins (20 kDa chaperonin and chaperone protein dnaJ1) were up-regulated after 24h.

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These proteins have been intensively investigated and are known to be changed under diverse stress conditions [33-35]. It was shown that these proteins are responsible for protein synthesis and their overexpression might suggest that novel protein synthesis was needed under CYP stress [33]. The finding that chaperone protein dnaJ1 was upregulated during short term CYP exposure in spite of exposure dosages makes it a potential biomarker for CYP stress, because it is not only sensitive to low dosage of CYP exposure (0.001µg/L) but could also predict high CYP dosage exposure. Our study found that elongation factor receptor was up-regulated after 24h and down-regulated after 96h by CYP stress. This protein responds to elongation factor Tu with the induction of defense and increased resistance and elongation factor Tu protein is capable of activating innate immune responses and induce resistance in plant[36]. The increased level of 15

ACCEPTED MANUSCRIPT elongation factor receptor might enhance algae CYP tolerance in a short term exposure, but long term exposure (96h) might seriously disturb algae immune system, resulting in

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decreased expression level. Heat shock proteins (HSP) are the most commonly detected

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proteins in response to stressful conditions and can stabilize new proteins to ensure correct folding to prevent further damage[12]. Heat shock proteins can be divided into

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five sub-families based on molecular weight: HSP100, HSP90, HSP70, HSP60 and small

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HSP [37]. One small heat shock protein (18.1 kDa class I heat shock protein) showed increased abundance under long term exposure to CYP. Many reports revealed that plant

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small heat shock proteins are induced under diverse stress conditions[37, 38] and Heckathorn et al[39] reported that small heat shock proteins can decrease the reactive

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oxygen species level and thereby protect PS II reaction under stress condition possibly by stabilizing the oxygen evolving complexes. Therefore, the increased abundance of 18.1

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kDa heat shock protein might play a role in restoring OEE1 abundance to normal level under long term CYP exposure. The reactive oxygen species (ROS) production in cells is low under normal growth condition, but environmental stress usually induces excessive production of ROS and the balance between ROS production and antioxidant quenching activity is disrupted, resulting in oxidative damage[40]. Excessive ROS can damage many cellular targets, including proteins, DNA and lipids[41]. Oxidative stress responses have been described for cell under CYP stress as it induces production of highly ROS[12]. The overexpression of antioxidant enzymes could result in organism’s tolerance to oxidative stress[42]. Our proteomics results showed that CYP also induces oxidative stress in Chlorella Vulgaris after long term exposure and these differentially expressed antioxidant proteins were up16

ACCEPTED MANUSCRIPT regulated. Peroxiredoxin belongs to antioxidant enzymes and is a component in antioxidant defense network[43]. Various stresses could induce changes in peroxiredoxin

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abundance[43-45]. Up-regulation of peroxiredoxin might be the cause of excessive ROS production due to CYP stress. Superoxide dismutase (SOD) catalyzes dismutation of

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superoxide O2- into oxygen molecular and hydrogen peroxide. SODs are found in three

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isoenzymes characterized by their metal cofactors, which are manganese (MnSOD),

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copper-zinc (Cu/ZnSOD) and iron (FeSOD) and they are considered as the first line in plant defense response to ROS[42]. In our case, overproduction of FeSOD improved

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algae tolerance to ROS damage caused by CYP stress and might play a role in algae survival[41, 46]. Glutathione S-transferases (GST) can detoxify organic pollutants and

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natural toxins in addition to general stress tolerance[47]. Up-regulation of glutathione Stransferase DHAR3 contributes to the protection against oxidative stress induced by CYP

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and protects algae cells [48]. Methionine sulfoxide reductase B (MSR) is an enzyme that repair oxidative damage proteins because it is capable of specifically reducing methionine-R-sulfoxide to methionine [49]. Several studies showed that MSRs play important roles in protein protection from oxidative stress [49, 50]. Increased abundance of MSR in our proteomics study might be a response of algae to CYP stress. 3.5 Proteins involved in carbohydrates metabolism Previous studies showed that CYP could induce alterations in carbohydrate metabolism [15, 16]. Algae growth can be achieved under photoautotrophic (CO2), heterotrophic (acetate) and mixotrophic (CO2 and acetate) conditions using different carbon sources, which are usually the most critical factors for algae growth [51]. Most plants and microorganisms can use acetate as sole carbon source by glyoxylate cycle [52]. The key 17

ACCEPTED MANUSCRIPT enzymes involved in this cycle are isocitrate lyase (ICL) and malate synthase. This cycle is essential for cell growth and plays an important role for gluconeogenesis as it utilizes

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three of the five enzymes associated with tricarboxylic acid (TCA) cycle in which CO2 is

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evolved [51]. ICL catalyzes the conversion of isocitrate to succinate and glyoxylate. Succinate enters the TCA cycle while glyoxylate and acetyl-CoA condensates to malate

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catalyzed by MS. Isocitrate is a branch point metabolite between the TCA cycle and the

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glyoxylate cycle [53]. Overexpression of ICL at 24h CYP exposure might be a strategy for algae survival under CYP stress [54]. However, long term CYP exposure led to

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decreased expression level of ICL. Plancke et al.[51] revealed that lack of ICL results in decreased rate of acetate assimilation, finally enabling adaption to oxidative stress,

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corresponding to oxidative stress related protein alterations at 96h CYP exposure. Surprisingly, malate synthase was up-regulated at 96h CYP exposure, which might be

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correlated with overexpression of malate dehydrogenase (MDH). MDH catalyzes the conversion of malate into oxaloacetate, which is a key step in TCA cycle, which plays a central role in ATP production [55]. MDH overexpression might lead to up-regulation of TCA cycle, indicating that algae might start adaption to CYP stress at 96h and more energy production is needed for photosynthesis. Since malate is produced by canalization of malate synthase, up-regulation of malate synthase is expected. Moreover, the upregulation of malate synthase despite CYP dosages under long term exposure makes it a candidate biomarker for CYP stress. Glycolysis, an important metabolic pathway found in nearly all organisms, provides substrates for energy production in living cells [56]. It metabolizes glucose to pyruvate, which is an important intermediate compound to TCA cycle to obtain ATP. 18

ACCEPTED MANUSCRIPT Phosphofructokinase (PFK), pyruvate kinase (PK) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) play important roles in plant glycolysis. PFK catalyzes the

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reversibly conversion of fructose-6-phosphate and fructose-1,6-bisphosphate. GAPDH

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reversibly converts glyveraldehyde-3-phospate to 1,3-bisphosphoglycerate. PK, the final enzyme of glycolysis, converts phosphoenolpyruvate into pyruvate with the concomitant

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production of ATP, occupying one of the most connected nodes in the plant metabolic

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network. Mutuku et al.[57] provided evidence that PFK plays an adaptive role under stress condition within a short time. This finding supports our observation that PFK was

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up-regulated after short term exposure. Apart from catalytic activity as part of glycolysis, GAPDH is also involved in cellular redox regulation [58]. Increased ROS level might

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lead to down-regulation of GADPH upon long term CYP exposure. When photosynthesis is inhibited, ATP produced by glycolysis could be an important source of energy. As the

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final enzyme of glycolysis, overexpression of PK might be due to energy demand of algae. In addition, the expression level of PK was increased upon long term CYP exposure and thus more investigation could be conducted on this protein to explore its potential for acting as a CYP stress biomarker. 4. Conclusion This study investigated the effect of CYP on the protein expression level of green algae Chlorella Vulgaris by a high throughput iTRAQ quantitative proteomics technique. A total of 162 and 198 proteins were significantly altered upon exposed to CYP for 24h and 96h, respectively. Analysis of differentially expressed proteins from algae samples treated with various CYP concentrations (0.001 µg/L, 0.01 µg/L and 1 µg/L) implicated that the influence of CYP on algae protein might be dosage-dependent since most of the 19

ACCEPTED MANUSCRIPT changed proteins from these treated groups were unique. Proteins involved with photosynthesis, response to stimulus and carbohydrates metabolism were discussed in

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details. Based on the results obtained, we proposed that CYP exposure might lead to

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photosynthesis inhibition in green algae and long term CYP exposure induces oxidative stress while short term CYP exposure only induces common stress response. Moreover,

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most stress responsive proteins were altered at medium dosage exposure after 24h and

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96h, indicating that medium CYP dosage induced algae defense system to enhance its tolerance to CYP stress, but high CYP dosage inhibited most algae biological processes,

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disabling some responses related to algae defense functions. Investigation into carbohydrate metabolism related proteins revealed that CYP mainly affects glycolysis

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and glyoxylate cycle, and might subsequently disturb energy production in algae. Among these significantly altered proteins, more investigation could be conducted on chaperone

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protein dnaJ1, malate synthase and pyruvate acting as biomarkers since their expression levels were changed under different CYP exposure dosages. Overall, this study provides a comprehensive view of complex mode of action of algae under CYP stress and also highlights several potential biomarkers for further investigation of pesticides exposed plant and algae.

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20 kDa chaperonin

1.40±0.09

P12853

1.94±0.26

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P13869 P37255

0.74±0.13

0.76±0.06

0.68±0.04

0.67±0.10

0.64±0.05

0.74±0.03

Q1KVW6

0.76±0.13

Q1XDD1

0.73±0.11

P08475 O65282

0.61±0.09

0.67±0.18

Q1KVV0

0.64±0.07

0.75±0.27

0.67±0.12 0.60±0.09 1.63±0.32

response to stimulus 1.45±0.13

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96h_high 0.76±0.01

1.41±0.17

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O82660

P14273

96h_med

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P11471

Q1KVY3

fold changes 24h_high 96h_low

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24h_low 24h_med photosynthesis

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Oxygen-evolving enhancer protein 2 Oxygen-evolving enhancer protein 1 Photosystem II stability/assembly factor HCF136 Chlorophyll a-b binding protein Photosystem II CP47 reaction center protein Photosystem I P700 chlorophyll a apoprotein A1 Chlorophyll a-b binding protein of LHCII type I Ribulose bisphosphate carboxylase large chain Photosystem II D2 protein Photosystem II CP43 reaction center protein Ribulose bisphosphate carboxylase small chain 2

accession no.

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protein name

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Table 1. Important proteins induced by CYP stress

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Q38813

1.62±0.52

1.32±0.45

1.33±0.40 1.46±0.11 1.55±0.10

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P22302 Q949U7

0.72±0.08

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1.80±0.67

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C0LGT6

P19037

1.65±0.33 1.50±0.18

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Q9C8M2 Q8LE52

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LRR receptor-like serine/threonine-protein kinase EFR (EF Tu receptor) Chaperone protein dnaJ 1 (heat shock protein 40 kDa) Superoxide dismutase [Fe] Peroxiredoxin-2E 18.1 kDa class I heat shock protein Peptide methionine sulfoxide reductase B1 Glutathione S-transferase DHAR3

1.41±0.04

carbohydrates metabolism

P93110 Q9FLW9 P13244 P83373

1.48±0.14 1.79±0.31

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Q8VYN6

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ATP-dependent 6phosphofructokinase 5 Isocitrate lyase Plastidial pyruvate kinase 2 Malate synthase Malate dehydrogenase Glyceraldehyde-3-phosphate dehydrogenase

Q8VXQ8

1.35±0.10 0.73±0.03 1.49±0.37 1.65±0.12

1.66±0.42 1.76±0.36 1.43±0.27

1.31±0.34 1.38±0.59 0.73±0.02

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ACCEPTED MANUSCRIPT FIGURE CAPTIONS Figure 1 Figure Experimental design for iTRAQ labeling showing biological replicates.

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Two biological replicates from control, low dosage, medium dosage and high dosage

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were labeled with iTRAQ labeling reagents 113 and 114, 115 and 116, 117 and 118, 119

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and 121 respectively.

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Figure 2. Growth curve of Chlorella Vulgaris strain without or with different concentrations of cypermethrin.

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Figure 3. Determination of experimental variation using identified proteins (unused protein score ≥1.3 and protein identified by more than single peptide) in both biological

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replicates: the horizontal axis represents % variation of average iTRAQ ratios of same protein from different biological replicate samples from one; the left vertical axis

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represents corresponding number of proteins (columns) with different % variation range; the right vertical axis represents the cumulative % of counted proteins (lines). Figure 4. Venn diagram showing significantly altered proteins from various concentrations of CYP exposure for 24h and 96h. A, up-regulated proteins after 24h CYP exposure; B, down-regulated proteins after 24h CYP exposure; C, up-regulated proteins after 96h CYP exposure; D, down-regulated proteins after 96h CYP exposure. Figure 5. Schematic representation of photosynthetic network. Photoreaction system consists of PS II, PS I, light harvesting system, cytochrome b6f and ATP synthase. Light harvesting complexes gather light energy and control the flow of energy to reaction center. PS II transfers electrons to cytochrome b6f by plastoquinol molecules. Then electrons are transferred by plastocyanin to PS I, followed by ferredoxin (Fd) and 27

ACCEPTED MANUSCRIPT Ferredoxin-NADP reductase (FNR).The light energy is ultimately converted to chemical energy, NADPH and ATP. The chemical energy could be used in light-independent

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proteins associated with the systems were highlighted in red.

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Calvin cycle for CO2 assimilation and other cellular metabolism. The relevant altered

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Figure 6. Schematic representation of glyoxylate cycle. Key enzyme involved were highlighted in red. This cycle centers on the conversion of acetyl-CoA for carbohydrates

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synthesis.

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Figure 7. Schematic representation of glycolysis pathway. The free energy released in this process is used to form high energy compounds, ATP and NADH. Key enzymes

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regulated under CYP stress were highlighted in red.

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Figure 2

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Figure 6

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Graphical abstract

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Effects of exposure to cypermethrin on algae proteome were assessed Exposure durations and concentrations were investigated Cypermethrin induced protein alterations were attributable to several mechanisms Mechanisms affected included photosynthesis, stress response and carbohydrate metabolism Potential protein biomarkers were identified

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