Dineshram et al. GCB Page No. 1

Data S1. Materials and Methods

Protein extraction and iTRAQ labelling

A portion of this pediveliger larvae from each treatment replicate tanks were frozen with 2Dlysis buffer (7 M urea, 2 M thiourea, 4% CHAPS, 40 mM DTT, 2% Bio-Lyte 3/10 ampholyte with protease inhibitor) and stored at -80oC for proteomics analysis. The larval samples were thawed and lysed using a sonicator (Branson Sonifier 150) (30 sec continuous pulse at a power setting of 3 followed by 2 min on ice). Supernatant containing solubilized larval proteins was collected after centrifugation at 14000 rpm for 20 min at 15oC and quantified using RC-DC kit (Bio-Rad, USA). Equal amounts of proteins from each of three biological replicate for individual treatment were pooled and purified by adding cold (-20oC) acetone four times the sample volume. Biologically independent replicate samples were mixed to minimize the random biological variation (Gan et al., 2007). However, three independent mass spectrometry iTRAQ analysis was performed for statistical evaluation of the proteomics results. The mixture was vortexed followed by incubation for 10 to 12 h at -20oC and centrifuged at 12000 rpm for 15 min at 4oC. Subsequently, the precipitated proteins were re-suspended in HEPES buffer (8 M urea, 40 mM HEPES (pH 8.0) and quantified using RC-DC kit (Bio-Rad, USA). Acetone precipitated aliquots containing 100 µg of protein were dissolved in 20 µl of iTRAQ dissolution buffer. The samples were subjected to reduction followed by alkylation using 5 mM triscarboxyethyl phosphine hydrochloride (TCEP) for 60 min at 37°C and 10 mM methylethanethiosulfonate (MMTS) for 10 min. The samples were digested with sequencing grade Trypsin (Promega, Madison, WI, USA) with enzyme-protein ratio of 1:40 at 37°C for 16 h. The tryptic digests were desalted using Sep-Pak C18 cartridges (Waters, Milford, USA). The peptide solution was vacuum dried (SpeedVac, Thermo Electron, Waltham, USA) and resuspended in 30 µl of 50 mM triethylammonium bicarbonate (TEAB) prior to labeling with iTRAQ reagents according to the manufacturer’s guidelines (Applied Biosystems, MA, USA). Peptides derived from treatments C, S, P, T, SP, TS, TP and TSP were labeled with isobaric tags 113, 114, 115, 116, 117, 118, 119 and 121, respectively, for 2 hat room temperature followed which reaction was quenched by adding equal volume of deionised water as that of sample reaction mixture (Fig. 1). The iTRAQ labeled samples were pooled and dried in a SpeedVac.

SCX fractionation and LC-MS/MS analysis

The dried iTRAQ labeled samples were reconstituted in 100 µl of SCX buffer A (10 mM KH2PO4, acetonitrile (ACN)/H2O 25/75 (v/v), pH 3.0) and then loaded onto a strong cation exchange PolySULFOETHY A column (200 mm × 4.6 mm, 200-Å pore size, 5 μm particle size, PolyLC, USA) and fractionated using a Waters Delta 600 HPLC unit (Waters). The peptides were eluted using a 60-min gradient comprised of 100% buffer A for 10 min, 25 min of 0–30% SCX buffer B (10 mM KH2PO4, 500 mM KCl, ACN/H2O 25/75 (v/v), pH 3.0), 5 min of 30–100% buffer B and 10 min of 100% buffer B, at a flow rate of 1 mL/min. Absorbance at 214 nm was monitored during the peptide elution. Concessive fractions with low intensity were combined to obtain a total of fifteen fractions. The peptides were desalted using Sep-Pak C18 cartridges (Waters, Milford, MA, USA) and dried in a SpeedVac.

The dried peptide fractions were reconstituted in 20 µL mobile phase (0.1% formic acid). The samples were analyzed using LTQ-OrbitrapVelos (Thermo Scientific, Bremen, Germany) coupled to Easy-nLC (Thermo Scientific, Bremen, Germany). Exactly 5 µL of the sample was injected for each analysis and concentrated in a preconditioned column (0.3 × 50 mm) packed with C18 AQ (5 µm particles, 200 Å pore size) (Bruker-Michrom, Auburn, CA, USA). The peptide separation was performed in a preconditioned capillary column (0.1 × 150 mm, with C18 AQ of 3 µm particles and 200 Å pore size (Bruker-Michrom). The peptides were separated using a 75-min gradient comprised of 45 min of 0-35% mobile phase B (0.1% formic acid in ACN, 15 min of 35-80% B, and 15 min of 80% B. The total flow rate of the gradient was set at 400nL/min. The sample was subjected into LTQ-Orbitrap through a Nanospray Flex (Thermo Scientific, Bremen, Germany) with an electrospray potential of 1.5 kV. The ion transfer tube temperature was set at 160°C. The LTQ-Orbitrap was set to perform data acquisition in the positive ion mode. A full MS scan (350-1600 m/z range) was acquired in the Orbitrap at a resolution of 30,000 (at 400 m/z) in a profile mode, a maximum ion accumulation time of 1 s and a target value of 1 × e6. Charge state screening for precursor ion was activated. The six most intense ions above a 1000-count threshold and carrying multiple charges were selected for a paralleled fragmentation (MS/MS) in the collision-induced dissociation (CID) in the linear ion trap and the higher energy collision dissociation (HCD). Dynamic exclusion for both CID and HCD fragmentation was activated with a repeat count of 2, repeat duration of 30 s, exclusion duration of 45 s, and ±5 ppm mass tolerance (Sun et al., 2013). Additionally, the settings for CID included a maximum ion accumulation time of 200 ms for MS/MS spectrum collection, a target value of 1 × e4, a normalized collision energy at 35%, an activation Q at 0.25, isolation width of 3.0 and activation time of 10 ms. For HCD, the settings included a full scan at a resolution of 7,500 (at 400 m/z) in a centroid mode, a maximum ion accumulation time of 200 ms for MS/MS spectrum collection, a target value of 5 × e4, a normalized collision energy at 40%, an activation Q at 0.35, isolation width of 3.0 and activation time of 0.1 ms(Han et al., 2013).

Protein identification and proteome analyses

The RAW files from Orbitrap velos were processed using the Proteome Discoverer software (version 1.4, Thermo Fisher Scientific, Germany). The workflow consisted of a spectrum selector and a reporter ion quantifier. MS/MS search was carried out using Sequest HT search algorithm against a concatenated target-decoy C. gigas annotated proteome containing 27,900 protein sequences (version 9) and common contaminant sequences such as keratins and trypsin(Zhang et al., 2012). Search parameters included full tryptic cleavage with allowance of one missed cleavage; oxidation of methionine was set as a dynamic modification while alkylation at cysteine and iTRAQ modification (8-plex) at N-terminus of the peptide and lysine were set as static modifications. Precursor mass tolerance were set to 10 ppm and for all HCD spectra and the high resolution CID spectra fragment ion tolerances were set.to 0.5.Da (Han et al., 2013). The search results were normalized based on total intensity and the False Discovery Rate (FDR) was calculated by enabling the peptide sequence analysis using a decoy database. High confidence peptide identifications were obtained by setting a target FDR threshold of 1% at the peptide level. Relative intensities of the two reporter ions for each of the peptide identifiers for a protein were used for averaging and assessing percentage variability to determine relative quantity of a protein in different stressor treatment compared to control.

To visualize differential expression pattern of proteins across treatments, tools such as Genesis 1.7.6 (Sturn et al., 2002) and DAnTE R statistical package were used(Polpitiya et al., 2008). Hierarchical clustering analysis was performed on the log2 fold change differentially expressed proteins using Genesis 1.7.6 (Sturn et al., 2002). A heat map displaying the expression matrix showing the similarity among treatments was calculated by Euclidean distance method and average linkage clustering. Box and whisker plot of log2 transformed data using DAnTE R statistical package (Polpitiya et al., 2008) was used to evaluate the variability and providing a different view for visualizing the expression trend between the treatments (Fig. 2). The line within the box plot corresponds to the median value, the box length to the interquartile range, the outliers are depicted as circles, and the lines emanating from the box (whiskers) extend to the smallest and largest observations. Correlation matrix/non-clustering heat map of Pearson correlation coefficients values from all pair wise comparisons of the log2 transformed protein intensity data of treatments was calculated using a colorimetric scale ranging from black (no correlation) to red, orange, yellow and white (high correlation).

An enrichment analysis was performed using CIMminer tool (http://discover.nci.nih.gov) to organize the list of proteins for interpretation in the context of the Gene Ontology (GO) which can be statistically significant or not. The enrichment results 2-dimensional visualization of heat map with columns correspond to treatments; rows correspond to GO level/module and with a scale indicating a colour gradient based on the number of enriched proteins from zero to high. Clustering was done by Euclidean distance measure and average linkage clustering method both at GO level and treatments to identify patterns showing treatments that are strongly altered by the GO classifications.