Identifying genes and regulatory pathways associated with the scleractinian coral calcification process

Coral collection

Scleractinian coral colonies of Stylophora pistillata were collected by SCUBA diving from 3–6 m depth at the coral reef near the Inter-University Institute (IUI) in Eilat, Aqaba Gulf, Red Sea. The branching coral colonies were fragmented to 5–10 cm long nubbins and transferred to an outdoor shaded running seawater table at the IUI for a month acclimation and recovery before the experiment started. The Israeli Nature and National Parks Protection Authority approved the collection of corals in this study (permit No. 2009-35556).

Calcification rates measurements under different seawater calcium concentrations

High calcium seawater was prepared by adding either 100 mg/L or 200 mg/L calcium (added as CaCl₂⋅2H₂O) to filtered seawater (0.45 µm).

Four coral fragments of S. pistillata, for each treatment (Fig. 1), were incubated in running seawater tables for 1.5 h for two time points: midday (11:00) and night-time (23:00). The fragments were incubated separately in three seawater calcium concentrations: natural calcium concentration (SW), natural calcium concentration added with 100 mg/L (SW + 100) and natural calcium concentration added with 200 mg/L (SW + 200).

The calcification rate values (µmol CaCO₃ h⁻¹ cm⁻²) were calculated according to the equation: ${\displaystyle \frac{\frac{\Delta A_T}{2}\ast \left(V_{\mathrm{chamber}}-V_{\mathrm{coral}}\right)}{T^{\ast }{A}_{\mathrm{coral}}}}$ where ΔA_T is the difference in Total Alkalinity (A_T) measured between the beginning and the end the incubation period, V is the volume of the chamber or the coral fragment, T is the duration of the incubation and A is the coral surface area. The coral’s surface area (A) was calculated by considering the branched fragments as perfect cylinders, hence the height and diameter were measured and used for the cylinder-coral fragment surface area calculation (Mass et al., 2007). Such short period incubation was already been successful for distinguishing differences of calcification rates between treatments (Cohen, Dubinsky & Erez, 2016; Gutner-Hoch et al., 2016).

Microarray experiment set-up and coral fragments sampling

Four coral fragments of S. pistillata were incubated for 1.5 h in each of the two different calcium concentrations (SW, SW + 100), and for two time points: in the mid-day (11:00) and at night-time (23:00). After incubation, coral fragments were sampled, snap froze in liquid nitrogen and stored in −80 C until further handled.

The coral fragments that have been subjected to SW + 200, were removed from gene expression analysis because no statistically significant was found between the calcification rates of SW + 100 and SW + 200 treatments (Fig. 2).

RNA extraction and microarray design

Total RNA was isolated from the S. pistillata fragments by using TRIzol^® reagent (Invitrogen, Carlsbad, CA, USA) according to manufacturer’s instructions. RNA quantity and integrity were assessed with a NanoDrop ND-1000 spectrophotometer and an Agilent 2100 Bioanalyzer, respectively. Total RNA was labeled and hybridized against custom S. pistillata microarray; an Agilent two-color gene expression microarray platform with 8 × 15 K probe per slide; microarray samples included four SW+100 and four SW (control) samples for each time point (11:00 and 23:00). Each treatment was combined with a differently labeled control sample from the same time point for hybridization to each compartment of the microarray slide. Oligonucleotide probes (60-mers) were designed based on approximately 12,000 genes predicted to encode proteins retrieved from a recent de novo assembly of 454-sequenced EST libraries of S. pistillata (Karako-Lampert et al., 2014). Labeling and hybridization were conducted using the Agilent Low Input Quick Amp Labeling Kit according to the manufacturer’s instructions. The intensity of the emitted fluorescence from a target spot on the array was detected using an Agilent G2565BA microarray scanner. The raw data as well as the processed data of the microarray were deposited under Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo) accession number GSE87159. Stylophora pistillata EST data are also stored at the Cnidarian Database of Centre Scientifique de Monaco: http://data.centrescientifique.mc/CSMdata-home.html.

Microarray results analysis

The data from all arrays were first subjected to background correction and LOESS within-array normalization using Agilent Feature Extraction software (version 9.5.1.1; Agilent Technologies, Santa Clara, CA, USA). The remaining analyses were performed in Partek^® Genomics Suite software (version 6.6; Partek Inc., St. Louis, MO, USA). Data from three biological replicates were used to perform a one-way ANOVA. The quintile normalized data were analyzed to identify genes with significantly up- or down-regulated expression (FDR p-value < 0.05) with an arbitrary cutoff of at least a two-fold change. As the microarray contains a diversity of genes originated from different organisms, all genes were transformed to Homo sapiens ones. Networks of highly interconnected proteins were generated using the STRING (Search Tool for the Retrieval of Interacting Genes, Heidelberg, Germany) 9.0 database (Szklarczyk et al., 2011) and GeneMania (Warde-Farley et al., 2010). The gene function clustering in GeneMania was predicted by using the Gaussian field label propagation algorithm. For this study the Homo sapiens dataset of functional association network was used in a network-weighting method of ‘Gene-Ontology (GO) based weighting, biological process based. The names of samples within the microarray analysis were labeled C11 and T11 as for control (reference) and treatment at daytime (11:00), respectively. The samples C23 and T23 were labeled as for control (reference) and treatment for night-time (23:00), respectively.

Semi-quantitive real time PCR

The relative expression of genes was analyzed through Qiagen Corbett machine, using a two step real-time PCR. The gene expression from every sample was amplified in triplicates, with a single volume of 10 µl containing: 3 µl of diluted cNDA with 0.5 µl of primer set (see Table 1 for primer sequences), 1.5 µl double distilled water (DDW) and 5 µl of GoTaq qpcr Master Mix Kit (Promega, USA). Cycle threshold values for each time point were compared to the internal reference genes, according the 2^−ΔΔCT method (Livak & Schmittgen, 2001). The gene β-actin was used for normalization in all RT-PCR analyses (Levy et al., 2007).

Statistical analyses

For statistical analyses, one-way ANOVA was used and followed by Tukey HSD (honestly significant differences) to assess the differences in experimental treatments of calcification rates and genes’ real-time PCR results. All statistical analyses were conducted using SPSS 20.0 (IBM, USA), and the results were considered statistically significant at p < 0.05.

Calcification rates of S. pistillata under increased seawater calcium concentration

Calcification rates of the Red Sea scleractinian coral Stylophora pistillata during daytime (11:00) were enhanced by 54% and 104% when the seawater calcium concentration was increased by adding 100 mg/L and 200 mg/L (of CaCl₂⋅2H₂O), respectively. During night-time (23:00), calcification rates were not influenced by the calcium concentration additions (Fig. 2 and File S1). Statistically significant differences were found during the daytime between calcification in natural seawater and calcification with additional calcium concentration (one-way ANOVA F(2, 9) = 5.277, p = 0.03; n = 4), while during night-time no difference was found (one-way ANOVA F(2, 9) = 1.052, p = 0.39; n = 4).

Microarray expression analysis

The Stylophora pistillata gene expression profile was analyzed with Partek Genomics Suite™ software (Fig. 3A) in a principal component analysis (PCA). The analysis showed that experiment replicates were profiled in the 3D PCA plot into two different groups—treated coral fragments (T11 and T23, which are fragments that were incubated in SW+100 mg/L at 11:00 and at 23:00) and second group—reference coral fragments (C11 and C23, which are fragments that were incubated in natural SW at 11:00 and at 23:00).

The microarray analysis revealed that 2,768 transcripts were differentially expressed (fold > 2) across all of the treatment groups. Among the differentially expressed gene targets, 1924 were found comparing treatment corals versus reference corals from night-time (T23 vs. C23). Comparing treatment corals with reference coral from daytime (T11 vs. C11) revealed 1,957 differentially expressed genes. In addition, comparing both lists of treatments corals with reference corals from night-time (T23 vs. C23) and daytime (T11 vs. C11) 1,113 common genes were identified (Fig. 3B). Within the 811 unique differentially expressed genes during night-time (which did not overlap with daytime) 267 genes were up-regulated and 544 were down-regulated. Within the 844 unique differentially expressed genes during daytime (which did not overlap with night-time) 437 genes were up-regulated and 407 were down-regulated.

In order to focus on genes that share similar biological processes and correlate with the calcification process, the analysis continued for unique up-regulated gene transcripts and total up-regulated gene transcripts that were differentially expressed during daytime (437 genes for unique and 1,333 for total), and during night-time (267 genes for unique and 1,171 for total). The total (found also to be up-regulated during the “opposite” time point) and unique genes were clustered into biological processes descriptions with GeneMania website analysis portal.

Among the total gene transcripts that were differentially expressed during daytime six biological processes were found: Wnt signaling pathway, cell junction organization, SMAD binding, regulation of cell morphogenesis, TGF-β signaling pathway, and amino acid synthesis (Fig. 4A). From the unique genes during daytime four biological processes were found: amino acid synthesis, metabolism, Smad signaling, and cartilage and bone biogenesis (Fig. 4A and Tables 2 and 3). All biological processes that were analyzed from total and unique genes were found with high significance of FDR p-value <0.05, except of “connective tissue development” cluster within the biological process cartilage and bone biogenesis, with FDR p-value of 0.068.

Among the total gene transcripts that were differentially expressed during night-time four biological processes were found: protein folding, mitochondrial membrane, innate immune system, and protein targeting (Fig. 4B). From the unique genes during night-time three biological processes were found to be associated with ribosomal metabolism, peptide synthesis/modification/processing, and ATP synthesis and oxidative phosphorylation. (Fig. 4B and Tables 2 and 3). All night-time biological processes were found with high significance of FDR p-value <0.05.

(List of total genes for C11 vs. C23, T11 vs. C11, T23 vs. C23, and T11 vs. T23 can be found in File S2; Biological processes of these total gene transcripts analyses can be found in File S3).

In order to expand the analysis of calcification associated genes, the gene expressions of S. pistillata’s orthologs of galaxin and galaxin-like were analyzed through semi-quantitative real-time PCR (Figs. 5A–5B and File S1). The galaxin gene has displayed a high relative expression during midday (relative expression of 59.76 ± 0.89 at 11:00, C11 in Fig. 5A) with statistically significant of p < 0.0005 (one-way ANOVA). While in treatment with addition of 100 mg/L calcium, relative expression of galaxin was dropped to expression level similar to expression during night-time (relative expression of 17.72 ± 2.61 at 23:00, C23 in Fig. 5A). The expression of gene galaxin-like was enhanced when treated with addition of 100 mg/L of calcium with relative expression of 14.14 ± 4.83 compared to relative expression of 3.48 ±  0.96 of the expression in the control corals at 11:00 (statistically significant p < 0.005, one-way ANOVA, n = 3). During night-time an addition of 100 mg/L calcium did not change galaxin-like gene expression (Fig. 5B).

Following the microarray analysis, the gene smad1, which was identified to be up-regulated during daytime and associated with the Smad signaling pathway was used to validate the microarray results (Fig. 5C). Semi-quantitative real-time PCR results of smad1 displayed that its expression was elevated during the day to 3.00 ± 0.48 (T11 in Fig. 5C) when seawater had added calcium, compared to relative expression of 1.56 ± 0.2 in control corals (C11 in Fig. 5C; statistical significance p < 0.05, one-way ANOVA, n =3). However, there was no difference in the relative expression of the gene during the night-time (C23 and T23 in Fig. 5C).