Expression pattern of potential heat stress genes under warm and cold episodes in scleractinian coral ‘Dipsastraea matthaii’ in the hottest sea, ‘the Persian Gulf’

doi:10.21203/rs.3.rs-2736473/v1

Shallow water reefs are widely threatened by anthropogenic ocean warming which sometimes exceeds their thermal tolerance limit. However, certain hard coral species are thermally resilient and can quickly adapt to anomalous thermal stress events by altering the expression of their heat stress-related genes. A comparative analysis of microarray data was undertaken to identify candidate genes involved in temperature stress. Finally, to validate the results of the analysis, four genes, including [i.e., Cell Division Cycle 16 (CDC16), Ubiquitin C (UBC), Heat Shock Protein 90 Beta Family Member 1 (HSP90B1), Histone acetyltransferase p300 (EP300)] as genes responding to temperature stress in the scleractinian coral “Dipsastera matthaii” collected from the Persian Gulf were selected for real-time PCR during warm and cold periods. Expression changes of them highly confirmed the results of the meta-analysis. So that a significant increase in expression was observed for UBC, HSP90B1, and EP300 in response to heat stress. The EP300 enhancement was triggered by transcription activation through binding to transcription factors. An important feature of this response was the expression of molecular chaperones such as HSP90B1 as a result of activation of the Heat Shock Factor 1 (HSF1). In addition, HSF1 activates UBC, which removes critically digested proteins along the path of the ubiquitin proteolysis system. The outcome of this study could help introduce candidate genes that may be beneficial as biomarkers for selection.

Thermal stress

gene expression

reef-building coral

thermally resilient coral

the Persian Gulf

The coral Dipsastera matthaii responds to thermal stress by changing the expression of its genes
The expression of UBC, HSP90B1, and EP300 was upregulated in response to heat stress
The EP300 enhancement was triggered by activation through binding to transcription factors

The thermal history of corals, or stress memory, appears to be an influential protective factor when they are exposed to extreme heat stress (Barshis et al. 2010; Weis 2010; Seveso et al. 2020). It is believed that the response of corals to thermal stress is partly determined by their heat exposure history (Roche et al. 2018). Although certain coral species (e.g., shallow water corals) have undergone extreme and persistent warming episodes in different hot seas (e.g., the Gulf of Aqaba, the Kimberley coastal area, Ofu Island, the Persian Gulf), they have successfully survived (Barshis et al. 2010; Grottoli et al. 2017; McCulloch et al. 2017; Burt et al. 2019). Such superior thermal-tolerant species are capable of adapting to unusual thermal stresses which are fatal for other species (Camp et al. 2018). Coral species with the highest recognized bleaching thermal threshold occur in the Persian Gulf (Howells et al., 2016; Riegl et al., 2011; Smith et al., 2017). This sea is characterized by an arid subtropical climate with the excess of evaporation over precipitation and river runoff in the northwestern sector (Sheppard et al., 2010). Despite harsh environmental conditions concerning high salinity (45 ppt) and remarkably large SST annual cycle (i.e., approximately 12.8 °C in winter and 36.8 °C in summer) (Reynolds 1993), several coral species have surprisingly survived and adapted to these conditions (Hume et al., 2013). In boreal summer, these corals are exposed to long-lasting thermal stresses (>34 °C) (Riegl et al., 2011). However, several widespread mass coral die-off episodes (i.e., 1996, 1998, 2017) have affected the corals in the Persian Gulf leading to 80% disappearance of corals with the entire elimination of Acropora spp. corals (Burt et al., 2019; Riegl et al., 2018; Riegl & Purkis, 2015; Shokri & Mohammadi, 2021; Shuail et al., 2016). Over the past decades, the warming trend across the Persian Gulf was higher than the globally averaged (Oliver et al. 2018). Such severely warm conditions are predicted for Indo-Pacific corals in the late twenty-first century and under strong greenhouse emission scenarios (Heron et al. 2016). Given the sensitivity of coral symbionts and their rapid response to thermal stress, early detection of any disorder in their health and other performance factors, before the occurrence of visible symptoms, is very beneficial for the protection and restoration of these delicate ecosystems (Kenkel et al. 2011, 2014; Traylor-Knowles and Palumbi 2014; Wright et al. 2017; Parkinson et al. 2020). Over the past recent decades, a molecular approach, termed Gene Expression Biomarkers (GEB), has been successfully developed and implemented in the early detection and quantification of stress in corals (Louis et al. 2017). Such molecular toolkits, which are widely used in biomedical research and clinical practices, measure the resilience of species and enhance the possibility of restoration (Parkinson et al. 2020; Rivera et al. 2021).

A gene expression biomarker should represent the expression, function, and regulation of a gene. Such genes are rapidly expressed in response to external factors and then their expression is reduced. For example, antioxidant genes, Cytochrome P450 isoforms, and heat shock proteins can act as biomarkers of optimal gene expression for early detection of whitening (Louis et al. 2017).

In transcriptomic responses of corals and their coexisting algae to heat stress, the most genes evaluated are heat shock proteins (Rosic et al. 2011; Meyer et al. 2011; Leggat et al. 2011; Kenkel et al. 2011; Zhang et al. 2017; Seveso et al. 2020). Heat shock proteins are molecular chaperones and play key roles in protein metabolism. Chaperones are protected proteins that are widely expressed in the presence of stress (Whitley et al. 1999). Heat shock proteins, which act as molecular protectors, are expressed in a wide range of stressors (Schmitt et al. 2007). During a stress event, for example, heat stress, incorrect protein folding, accumulation, or disruption of the regulation and separation of multiple protein complexes can lead to the activation of signaling pathways (Li 2004).

In general, corals exposed to heat stress or other stresses that lead to bleaching increase the expression level of heat shock proteins as a defense mechanism (Louis et al. 2017; Traylor-Knowles et al. 2017; Seveso et al. 2020). These proteins are the core of balancing cell death and life and also protect cells against apoptosis and stress (Nollen and Morimoto 2002; Das et al. 2019). The expression of heat shock proteins is regulated by the response to heat stress. An HSF1 transcription factor is lost or suppressed when activated. HSF1 eventually binds to promoters of heat stress genes (Jolly and Morimoto 2000; Pirkkala et al. 2001). Thermal stress proteins are named according to their molecular weight and function (e.g., HSP60, HSP70, HSP90) (Dubey et al. 2015).

Using the real-time-PCR technique, the increase in HSP90 expression in Montastraea cavernosa coral was explored as an indicator for protein denaturation (based on renaturing function) (Skutnik et al. 2020). Skutnik et al. (2020) further argued that this might be considered an indicator of host stress and immediate response to control negative consequences and control homeostasis.

In adult Porites astreoides colonies under laboratory heat and light stress, HSP90 expression increased 6-fold after 3 hours of exposure to 36-35 ° C, which is (7-8 °Cwarmer than control conditions and 10 times more light intensity of control medium) (Kenkel et al. 2011). In another study, an increase in the expression of molecular chaperones from the HSP90b1 family, HSP26 / 42, and DNAJ in Montipora aequituberculata corals were recorded under thermal stress of 29.5 and 32 ° C compared to controls at 27 ° C (van de Water et al. 2018).

Ubiquitin C (UBC) is one of the four genes encoding ubiquitin in the mammalian genome. The UBC gene is a stress-protecting gene that is overexpressed under a variety of stressful conditions, including exposure to UV radiation, heat shock, oxidative stress, and translational disorders.

Using Western blotting, certain protein biomarkers including Hsp70, Ubiquitin-conjugate, and MnSOD were selected in Porites lobata in Ofu Island, Samoa (USA), among which Ubiquitin-conjugates had higher levels in the colonies in back reefs than in the colonies in the fore reef (Barshis et al. 2010).

The histone acetyltransferase p300 (EP300) gene is a transcriptional inhibitor with endogenous lysine acetyltransferase activity that can regulate gene transcription and expression in a variety of ways. The histone acetyltransferase p300 controls the stability of many transcription factors through acetylation, activating them and ultimately activating heat shock and stress response proteins (Raychaudhuri et al. 2014).

The Persian Gulf as a semi-enclosed sea surrounded by dry landmasses is characterized by relatively harsh environmental conditions concerning high temperature and salinity (Sheppard et al., 2010). The coral communities in this sea have been formed under harsh environmental conditions that kill conspecifics elsewhere (Hume et al., 2013; Price et al., 1993). As such, these unique coral communities are attracting attention for their ability to inform how coral reefs globally are adapting to projected increases in water temperatures over the next century (Burt et al., 2012; Hume et al., 2015; Ziegler et al., 2017).

Despite the progress that has been made in understanding the causes and implications of coral bleaching across the northern Persian Gulf, it remains unclear, as a direct indication of adaptability, how the expression of thermal stress-related genes in native corals change under severe heat stress. In the present study, the changes in the expression of potential heat stress genes [i.e., Cell Division Cycle 16 (CDC16), Ubiquitin C (UBC), Heat Shock Protein 90 Beta Family Member 1 (HSP90B1), Histone acetyltransferase p300 (EP300)] in scleractinian massive coral “Dipsastera matthaii”, as a heat stress tolerator (Edinger and Risk 2000) collected off Hengam Island, in the northeastern Persian Gulf, were investigated. In doing so, the seasonal pattern of change in the expression of selected genes was explored between warm and cold periods in both shallow and deep waters. Accordingly, structural analysis of the cognate network was used to select the most important genes involved in the temperature stress pathway. In this study, four series of microarray transcriptome and RNA-SEQ data were analyzed. The aim was to use gene expression studies related to molecular processes involved in temperature stress conditions and genes involved in responding to the organism's thermal stress to construct a gene network and subsequent analyzes. Likewise, according to the results of co-expression network analysis, the expression of four genes (i.e., 12 CDC16, UBC, HSP90B1, EP300) with the highest rank was investigated as important genes of temperature stress path in D. matthaii corals.

2.1 Study area and sampling

The specimens of scleractinian coral, Dipsastraea matthaii (Vaughan, 1918) (Merulinidae), were collected off Hengam Island located in the Strait of Hormuz in the northeast of the Persian Gulf (Fig. 1). Coral specimens were collected from shallow depth (~2.5 m, 15 m from the shore, 26˚36.707' N, 55˚51.441' E) and intermediate-depth (~9 m, 250 meters from the shore, 26˚37.055 'N, 55˚ 50.725' E). These sites were referred to as shallow and deep corals, respectively.

Three colonies of the same size were selected and marked at each sampling site (i.e., shallow and deep sites). Sampling was performed by SCUBA diving during midday (14:00–16:00 local time) on the 17^th of August as a warm period and on the 3^rd of December 2018 as a cold period.

Using a hammer and chisel, three small fragments with an approximate size of 5 cm were collected from each colony providing a total of nine replicates for each site at each warm and cold period. By fragmenting single colonies unwanted sources of genetic and biological variability derived from colony size, shapes, and thermal/light life histories were eliminated (Granados-Cifuentes et al. 2013; Hemond et al. 2014; Parkinson et al. 2015). The coral fragments were immediately frozen in liquid nitrogen and kept at -80 °C in the laboratory until the RNA extraction. Two HOBO Pendant data loggers were lodged at each shallow and deep site and the water temperature was recorded from August 17, 2018, to December 31, 2018, with a 30-minute interval in both shallow and deep waters.

2.2 Identification and selection of appropriate expression stress experiments in D. matthaii

Using the keyword “Heat stress”, the expression data of coral transcripts on the NCBI were examined in the GEO DataSets section and the Array Express section of the EBI. Finally, to identify the genes responding to temperature stress, three sets of microarray data and one set of RNA-Seq data in the NCBI database were obtained from the GEO section. The data set used in this study with access codes GSE41435, GSE47779, GSE16151, and PRJNA177515 were obtained in the GEO section of the NCBI database (Table 1S). The various datasets were examined from various aspects, including the number of samples, and by considering these factors, the appropriate data set was selected. Based on the analysis of transcripts data, candidate genes were selected to the expression pattern of these genes was explored within warm and cold periods.

2.3 RNA extraction and cDNA synthesis

RNA extraction was carried out according to the RNeasy Mini kit (Qiagen), by following the manufacturer’s instructions. RNA quantity was assessed using a NanoDrop spectrophotometer (Thermo Scientific NanoDrop 2000). RNA integrity was checked through agarose gel electrophoresis and evaluated based on clear 28S and 18S ribosomal RNA bands. cDNA synthesis was carried out using the QuantiTect reverse transcription kit (Qiagen).

2.4 Primer design

Since no genomic/transcriptomic data for D. matthaii were available, the RNAseq data of Dipsastraea favus and Dipsastraea sp. as close species to D. matthaii, were utilized. In doing so, the BlastStation2 software (https://www.blaststation.com/ intl/en/blaststation2.php) was used. The local database was created from the assembled file of D. favus and D. sp. The sequences of genes were blasted against the database and sequences with the highest identity and the lowest E-Value as the best hit for each gene were considered. Additionally, selected sequences were blasted with other species of Porites corals by using the database provided at http://reefgenomics.org/ blast. Sequences were aligned using Clustal W of MEGA. Primers were designed based on conserved regions. For coral’s algal symbiont, the sequences of the genes in the Symbiodiniaceae were blasted against the database in Santos Lab (http://webhome.auburn.edu/*santosr/ symblast.htm). Primers were designed based on conserved regions using MEGA. The selection of genes was based on the analysis of macroarray data. The genes involved in responding to the organism's thermal stress were selected as candidate genes.

The primers were designed based on protected areas between the two species, and the best pair of primers were selected for PCR analysis. The properties of the designed primers such as melting temperature, GC percentage, and the possibility of forming secondary structures were investigated using OligoAnalyzer online tools. Finally, the specificity of the primers was checked using the Primer-BLAST program. PCR efficiency and coefficient of determination (r²) for each primer pair were determined using LinRegPCR software. The sequence of designed primers is presented in Table 1.

2.5 Quantitative real-time PCR

The quantitative real-time PCR was carried out in a total volume of 10.0 µl, containing 5 µl of 2x SYBR Green Master Mix (Amplicon), 1.0 µl of the cDNA, 0.5 µl of each primer (10 PM), and 3 µl of DEPC-water for 35 cycles. Three technical replicates for each colony were performed within each run. Reactions were run in standard mode on a Real-Time PCR System (Rotor gene- RG6000).

2.6 Data analysis

The samples collected in December from the deep site, termed as Deep-December, were considered control samples. The relative fold changes in other groups were evaluated concerning the control samples. Given the fact that variation in water temperature tends to be smaller for the deep corals, therefore, samples from the control group were not exposed to the environmental thermal stress when sample collection was carried out (T \ 26 °C; see Fig. 4). First Ct values of the target genes were normalized by using the reference gene. In all sample groups, this value was compared with the control group as the reference group. Gene expression values were computed according to the fold change (2-DDCt). Besides, the ANOVA statistical test was implemented to estimate the statistical confidence level of the gene expression differences for warm versus cold periods, shallow versus deep sites, acclimation experiments, and deep-recovery fragments (Table S1). This analysis was done using Genex v. 6 and SPSS v. 21. Results were visualized using GraphPad Prism 8.

2.6.1 Differential expression analysis and observation of sample distribution

When samples understudy has been extracted from independent biological sources, the variability of their variables is usually modeled by associated statistical distributions. Limma is a widely used software package that uses an application model to analyze microarray results. In this linear model, the normal distribution is used as the (distribution) basis to model the microarray test expressions.

2.6.2 Statistical test of hypothesis using an R programming language

In the first part of the present study, using the expression matrix created from the results of the previous step (preprocessing and expression calculation step) and by knowing the information about the content of the samples, an object in a special R class was created. In the expression matrix of each row representing an ENSEMBL gene identifier or any other identifier ID, each column displays the samples tested in the experiment and each score represents the expression of the genes.

3.1 Changes in water temperature

Water temperature in the deep site in August ranged from ~29 °C to ~33 °C. The water temperature declined notably right after the high tide suggesting that the corals had remarkably (~1.8 °C) cooled down by the displacement of cold subsurface water associated with tidal motion, as previously noted in the study area (Vajed Samiei et al. 2014). In the same period, shallow corals experienced a high temperature, typically warmer than 33 °C. Unlike the deep site, the temperature drop accompanied by the tidal cycle was not observed in the shallow site (Fig. 2a). During the sampling on August 17, 2018, between 14:00 and 16:00, the water temperature in the shallow and deep sites was 34.2 °C and 32.7 °C, respectively (Fig. 2a). During the in situ sampling in August, the sunshine was very intense and the sky was clear with almost no cloud coverage. The water was also clear. Thus, the observed thermal stress in the shallow site seems to be closely related to high light intensity. The severe heat stress conditions remained for several consecutive days (Fig. 2a). During the sampling on December 3, 2018, between 14:00 and 16:00, the water temperature was about 25.7 °C in both shallow and deep sites. In December 2018, the daily cycle of temperature was much smaller than that measured in the summer (Fig. 2b). The temperature difference between deep and shallow sites was minimal compared with summertime (Fig. 2a, b) indicating that the stratification was very minimal and the mixed layer depth reached the deep site. The connection between deep site temperature and tidal motion, as observed in August, was broken down (Fig. 2b).

3.2 Changes in the expression of thermal stress-related genes

The data set used in this study with access codes GSE41435, GSE47779, GSE16151, and PRJNA177515 were obtained in the GEO section of the NCBI database (Table 1S). The results of the preprocessing process can be examined by various diagrams. For example, a box diagram shows the possibility of evaluating the distribution of data in different arrays. Usually, the difference in the shape and center of the boxes in the diagram indicates that the specimens need to be normalized. In this section, we show examples of the GSE41435 dataset before and after normalization by the Quantile method. Graphing was done by ggplot bundle. It should be noted that this section uses the raw data for each experiment as input. As can be seen from the graphs, the samples became more comparable after the normalization process (Fig. 3a and Fig. 3b). The normalization processing was done for each sample (Data not shown).

3.3 Differential expression analysis

Differential expression analysis, in general, involves estimating the distribution value of each gene and developing a generalized linear model to examine the overall expression of genes. Calling the results using the corresponding function in the R programming provides different estimates with different criteria for analysis. Of different genes, only the candidate genes with the highest percentage difference are listed (Table 2). The log2FoldChange factor represents information about the candidate genes based on the base 2 logarithms. This factor is a criterion for confirming the candidate genes identified in the samples.

Normally in statistics, the final results of such analyzes are reported by the p-value criterion. It should be noted that this criterion indicates how logically the results of log2FoldChange analysis can be statistically significant under the conditions of the hypothesis test. The main criterion for identifying candidate genes is the modified p-value, and genes with a q-value or so-called FDR of less than 0.05 will be considered genes with expressive differentiation. Some 191 genes showed significant expression differences (Fig. 3c). Out of 191 genes, the key genes (CDS16, UBC, HSP9031, and EP300) were selected in the pathway of response to stress (Fig. 3c).

The results related to the analysis of DEG genes revealed that the changes in the expression of candidate genes were significant. One of the advantages of these diagrams is the visual review of the results of the hypothesis test. The M.A. plot diagram generally shows the logarithm of the expression ratio versus the logarithm of the mean expression. This diagram shows the expressive differences measured between the samples. The X-axis represents the average of the expressions in the whole samples and the Y-axis shows their expressive differences. The candidate genes are marked with a marked difference in expression in red and blue (Fig. 3d).

Given the minimized rate of gene sharing, the significant genes were combined according to a suite of criteria inducing (1) all genes with different and significant expression were obtained from the analysis of the previous step, but only genes with a log2FC value greater than 1 or less than -1 were used to plot the network. In other words, the criterion for combining the rate of change was more than 2 times (either in the case of increase or decrease).

3.4 Gene enrichment analysis and network mapping

3.4.1 Gene network

In this study, the STRING database contains a great deal of information on protein-protein interactions which, by submitting genes identified as DEGs in it, the protein-protein interaction network was drawn (Fig. 4). Due to the relative size of the constructed network, the PPI network was divided into smaller modules using the MCL algorithm and each of them was examined and interpreted separately. Figure 4 illustrates the constructed PPI network.

The output file containing protein interactions was then entered into Cytoscape 3.8.2 software. Using the CytoHubba plug-in in addition to the MNC algorithm, highly connected genes were introduced as hubs. In the Cytoscape, the values of the above parameter were obtained for all nodes and the genes that contained the maximum values for this parameter were considered effective genes (CDS16, UBC, HSP9031, and EP300 proteins were indicated by arrows in Fig 4). Figure 5 shows the degree of genes being studied. In addition, the genes (CDS16, UBC, HSP9031, and EP300) that had the most interaction (degree) in the network have been demonstrated in the expression change diagram. Accordingly, only hub genes and genes with a log FC greater than 1 or less than -1 have been combined in various studies and used in the network.

3.4.2 Functional review of modules

The employed algorithm resulted in the formation of about 32 modules for the PPI network. Here, Module 1 was chosen, because it had the most important and largest number of genes. An overview of the network and its available communications for this module in the STRING database are presented in Fig. 6. Some of the most important processes involved for the components in this module are listed in the table below (Table 3). Module 2 also had a high genetic diversity and is second in terms of the number of genes (Table 4).

3.4.3 Selection of the most important genes involved in thermal stress based on cognate network analysis

According to the results of co-expression and PPi network analysis, in this study, the expression of four genes, such as CDC16 UBC, HSP90B1, and EP300 with the highest ranking, was selected as important genes of temperature stress path in D. matthaii corals. The EF1a gene was identified as the reference gene for data analysis in this experiment. During different stages of the experiment and in all samples, the expression of this gene was almost constant and the standard deviation of the internal control gene was calculated to be 0.92. Samples taken in December from the Deep site (Deep-December) were considered as a control group in this study.

The expression of UBC (1.8), HSP90B1 (3.48), and EP300 (5.6) genes was upregulated in shallow samples in August (P> 0.05). Yet, no significant change was recorded in the expression of the CDC16 gene in the shallow samples in August (Fig. 7) (Tables S1, S2, and S3 in supplementary).

Though the corals appear to have adapted to the relatively harsh environmental conditions (e.g., long extreme warming episodes) in the Persian Gulf, however, they have increasingly experienced bleaching over the past decades. This indicates that they may have been exposed to high temperatures and intense light intensities close to their upper thermal limits for several hours per day during warm periods (July–August) of the year. In the present study, coral samples were collected in the natural environment and under intense sunlight.

In D. matthaii coral, structural analysis of the cognate network was used to select the most important genes involved in the temperature stress pathway. In this study, four series of microarray transcriptome and RNA-SEQ data were analyzed. The aim was to use gene expression studies related to molecular processes involved in temperature stress conditions and genes involved in responding to the organism's thermal stress to construct a network and subsequent analyzes. The main goal was to build a network based on the knowledge-based method, which was eventually achieved by using various processes of preprocessing, normalization, and other related calculations. Data were analyzed using Cytoscape software and network centrality criteria were identified to identify genes and important connections in the path of temperature stress. In this study, proteins that have important topological properties in the network were introduced as candidate markers. Likewise, according to the results of co-expression network analysis, the expression of four genes (i.e., CDC16, UBC, HSP90B1, EP300) with the highest rank was investigated as important genes of temperature stress path in D. matthaii corals. Among the studied genes, two genes, UBC and CDC16, play important roles in protein ubiquitination/protein degradation. The polybiobicotin C gene is a stress-protective gene under various stressful conditions, including exposure to UV radiation, heat shock, oxidative stress, and translational disorders. The UBC gene has also been reported to help maintain stable ubiquitin levels under physiological conditions. This is probably due to the increased demand for ubiquitin to remove critically folded proteins (Radici et al. 2013).

Consistent with the results of previous studies (Downs et al. 2000; Barshis et al. 2010, 2018; Maor-Landaw et al. 2014), the expression UBC gene was upregulated in corals collected from the shallow site in August and in tidal conditions and at the same time with the maximum daily temperature. This response may be due to increased stress levels due to protein damage. However, non-injury-related functions related to the transport and maintenance of cellular protein homeostasis may also lead to similar increases in gene expression (Hawkins 1991; Welchman et al. 2005).

The increase in ubiquitin in the corals of the shallow site compared to the deep site indicates higher stress levels, which are caused by fluctuations in the environmental conditions of the shallow site. Corals that are exposed to high circadian temperature changes are often more heat tolerant and more resistant to bleaching than their counterparts that live in stable environments (Barshis et al. 2018). Ubiquitin expression levels have been established as a cellular marker for protein health and response to cellular heat stress (Downs et al. 2000; Downs 2003). According to Barshis et al. (2010, 2018), the increase in ubiquitin concentration observed in the back reef corals indicates higher stress levels resulting from dynamic fluctuations in the environmental conditions in the front reef. The UBC gene, on the other hand, has so far been identified as a gene responding the heat shock and therefore may be used as the target gene for HSF1. Increased transcription under prototoxic conditions (as a result of heat stress or proteasome inhibition) is mainly due to the binding of HSF1 to known HSEs in the UBC gene promoter. UBC gene transcription occurs during stress and provides the extra ubiquitin needed to destroy unwrapped proteins (Ryu et al. 2007; Bianchi et al. 2018). Heat shock elements within the UBC gene promoter have been identified that induce the UBC gene as a result of heat shock factor transcription and are activated by proteotoxic stress (Bianchi et al. 2018). Therefore, this gene can be reliable as a candidate gene (Vihervaara et al. 2013; Crinelli et al. 2015). The CDC16 protein belongs to the anaphase complex (APC), which controls cell progression through mitosis.

In the present study, no significant changes were observed in the expression of the CDC16 gene. Zhou and Rigaud (2001) suggested that decreased expression of the CDC16 gene after oxidative stress may delay the progression of damaged cells in mitosis, leading to a delay in mitotic phase progression. This delay occurs in adapted cells and allows them to repair faster and more efficiently, which increases tolerance to stressful conditions (Zhou and Rigaud 2001). The high association of the CDC16 gene with other genes in the interaction network and the role of ubiquitin ligase protein, make this gene a key gene and can be used as an important candidate for gene studies and mechanisms of susceptibility of corals under stress.

HSP90 is a chaperone protein that, like other HSPs, plays an important role in the coral's response to heat shock and protein folding. HSP90 also plays a vital role in the cell cycle, signal transduction, and maintenance of cellular homeostasis. In the present study, at low tide conditions with maximum daily temperature, the shallow samples in August show increased expression of HSP90B1 heat shock protein. Previous studies have also reported that under temperature stress conditions, HSP90 mRNA expression was significantly higher than under control conditions (Desalvo et al. 2008; Meyer et al. 2011; Leggat et al. 2011; Kenkel et al. 2011; van de Water et al. 2018; Skutnik et al. 2020).

In the early stages of heat stress, HSP90 gene expression increases due to increased cell damage, which translates to HSP90 adapting to environmental stress (Hao and Gu 2014). In corals exposed to heat stress, it is beneficial for HSP90 to stimulate the mitochondria to produce more ATP, thereby helping to regulate cellular metabolism (Skutnik et al. 2020). Similarly, the presence of protective HSP90 during stressful conditions Chloroplasts, possibly associated with symbiosis, allow corals to achieve a steady state of energy until environmental stress subsides (Skutnik et al. 2020). Along with the production and transport of proteins and carbohydrates, an increase in HSP90 maintains the function of the endoplasmic reticulum during heat tolerance by the Holobiont (Skutnik et al. 2020). According to Skutnik et al. (2020), increasing the concentration of HSP90 is to maintain homeostasis, which indicates the normal functioning of the cell despite the presence of stress. On the other hand, an increase in HSP90 in this study could indicate the occurrence of cell degradation and protein denaturation based on HSP90 renature function (Skutnik et al. 2020).

In the present study, the expression of the EP300 transcription coagulator gene was also increased in shallow samples in August, which could be the response of this gene to severe environmental stress at noon. This increase is related to transcriptional activation by connecting to transcription factors and the transcription system. Important features of this response are the expression of molecular chaperones as a result of activation of the transcription factor HSF1. This involves the acetylation of vital functional lysines during stress, which leads to the activation of HSF1 (Raychaudhuri et al. 2014).

In summary, in corals sampled under midday environmental stress and tidal conditions, the cytosolic response to stress is commonly known as the heat shock response. This response is one of the main mechanisms of cell defense by cells to maintain protein stability (proteostasis) when exposed to prototoxic conditions against heat shock, which activates the HSF1 transcription factor by increasing EP300. HSF1, on the other hand, activates heat shock proteins such as HSP90B1, which are mainly molecular chaperones that prevent the accumulation of malleable proteins and cause them to re-fold or be destroyed. HSF1, on the other hand, activates UBC, which removes badly digested proteins along the path of the ubiquitin proteolysis system. Finally, the nuclear proteasome system, activated by HSF1 degradation, reduces the stress response in a way related to the removal of defective proteins by the ubiquitin-proteasome system.

In addition to the similarity in the communication pattern, the modules tend to have genes with similar functions. The results of the functional analysis confirmed to a large extent that each of the modules that make up the network had similar functional and path patterns between their genes. For example, module 1 in the PPI network constructed is often involved in the Ubiquitin mediated proteolysis process. Most of the terms used in GO for this module are biological processes related to ubiquitin. The results of the GO analysis also confirmed the fact that the different modules each have specific functions and are somehow functionally in separate groups.

It should be noted that corals in the deep site face fewer thermal and light changes in hot periods than shallow water corals. In addition, the displacement of subsurface waters during high tide causes a significant cooling and decrease in water temperature at this depth. Therefore, this part of the Persian Gulf seems to be a favorable habitat for corals under normal and stable temperature conditions. In the coming decades, heat waves are predicted to be more intense, more frequent, and more continuous than those observed in previous decades (IPCC 2014), a phenomenon that could cause corals to experience environmental stresses that exceed their heat threshold.

The reefs across the northern Persian Gulf live in better environmental conditions including lower temperature, lower salinity, better aragonite saturation, and greater depth that has led to increasing species richness towards the Straits of Hormuz (Riegl & Purkis, 2015). There might be further intrinsic mechanisms that have been developed by each scleractinian coral species to successfully thrive in the less optimal condition of the Gulf. The present study investigated the changes in expression of candidate genes [i.e., Cell Division Cycle 16 (CDC16), Ubiquitin C (UBC), Heat Shock Protein 90 Beta Family Member 1 (HSP90B1), Histone acetyltransferase p300 (EP300)] in a thermally resilient scleractinian coral ‘Dipsastraea matthaii’ as a conceivable tool for adapting anomalous thermal stress events. The results demonstrated a significant increase in the expression of UBC, HSP90B1, and EP300 genes in response to rising water temperature. The expression of molecular chaperones such as HSP90B1 occurred as a result of activation of the transcription factor HSF1 leading to UBC activation. Ubiquitin C removes critically digested proteins along the path of the ubiquitin proteolysis system.

Importantly, these findings suggest that gains in the heat tolerance of the studied coral species have a genetic basis. This may further indicate that the thermally resilient scleractinian corals living in the Persian Gulf can facilitate the evolution of coral populations to rapid climate warming. This can be accomplished by interspecific hybridization between the corals from the Gulf with those elsewhere in the world to produce genotypes with enhanced climate resilience.

ACKNOWLEDGEMENT

We thank Dr. Mohammad Javidkar for his guidance and valuable comments. The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article. This work was supported by the Iran National Science Foundation (INSF) [Grant Number 96015230].

Conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest.

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Table 1- The sequence of designed primers for the selected genes.

Gene	Primer sequence (5′–3′)	Size (bp)	Biological process
EP300	F-TCAAGAATACGGAAGCGAATGTG R-GGAGGACAAGCCCAAATATGAG	186	transcriptional co-activator
HSP90B1	F- AGGTTGCTGTAGAGGTGTTAGG R- GCACAAACCCTGGAGAAACATC	126	Heat Shock Protein
UBC	F- AGGATGGGATGTCACGTTTGG R- GCTGAGCCTGTCTATGGATTG	158	ubiquitination
CDC16	F -GCAAGCACGGAGGTATTTCAG R- GTGACATCGAGGCATCAGTTTG	154	ubiquitination
EF1A	F- CAGCATCACCCGACTTCAC R -ATATGCTCCTGTGTTGGATTGC	131	Control gene

Table 2. The final parts of the differential expression test.

ID	log2FoldChange	padj
UBC	2.61	0.005
CDC16	-2.64	0.0006
EP300	7.99	0.0001

Table 3. Interpretations related to the contents of module 1.

ID for the interpretation provided in the relevant database	Brief explanation for the proposed interpretation	Proposed interpretation category
GO:0016567	Protein ubiquitination	BP
GO:0000209	Protein polyubiquitination	BP
GO:0000151	Ubiquitin ligase complex	CC
GO:0004842	Ubiquitin-protein transferase activity	MF
GO:0061630	Ubiquitin protein ligase activity	MF
hsa04120	Ubiquitin mediated proteolysis	KEGG

Table 4. Suggested interpretations for the contents of Module 2.

ID for the interpretation provided in the relevant database	Brief explanation for the proposed interpretation	Proposed interpretation category
GO:0016567	Protein ubiquitination	BP
GO:0000209	Protein polyubiquitination	BP
GO:0000151	Ubiquitin ligase complex	CC
GO:0004842	Ubiquitin-protein transferase activity	MF
GO:0061630	Ubiquitin protein ligase activity	MF
hsa04120	Ubiquitin mediated proteolysis	KEGG

Supplementary.docx

Expression pattern of potential heat stress genes under warm and cold episodes in scleractinian coral ‘Dipsastraea matthaii’ in the hottest sea, ‘the Persian Gulf’

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Abstract

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1 Introduction

2 Materials And Methods

3 Results

4 Discussion

5 Conclusion

Declarations

References

Tables

Supplementary Files

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