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. 2022 Sep 12;28(5):477–491. doi: 10.1007/s12192-022-01295-9

Coping with harsh heat environments: molecular adaptation of metabolic depression in the intertidal snail Echinolittorina radiata

Jie Wang 1,2, Lin-Xuan Ma 1, Yun-Wei Dong 1,2,✉
PMCID: PMC10469152  PMID: 36094737

Abstract

Harsh thermal environments in the rocky intertidal zone pose serious physiological and molecular challenges to the inhabitants. Metabolic depression is regarded as an energy-conserving feature of intertidal species. To understand the molecular mechanism of metabolic depression, we investigated physiological and transcriptomic responses in the intertidal snail Echinolittorina radiata. The metabolic rate and expression of most genes were insensitive to temperatures ranging from 33 to 45 °C and then increased with further heating to 52 °C. Different from other genes, the genes involved in heat shock response (HSR) and oxidative stress response (OSR) (e.g., genes encoding heat shock protein 70 (HSP70) and cytochrome P450 protein (CYP450)) kept upregulating during metabolic depression. These high levels of HSR and OSR genes should be important for surviving the harsh thermal environments on the rocky shore. In the population experiencing more frequent moderate heat events, the depression breadth was larger, and the change in magnitude of upregulation was insensitive for HSR genes (e.g., HSP70s) but heat-sensitive for OSR genes (e.g., CYP450s) at the temperature of 37 to 45 °C. These findings indicate that both the thermal sensitivity of HSR and OSR genes and the insensitivity of metabolic genes are crucial for surviving extreme intertidal environments, and different populations of the same species rely on various physiological mechanisms to differing extents to deal with heat stress. The cellular stress response is not a “one size fits all” response across populations largely depending on local thermal regimes.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12192-022-01295-9.

Keywords: Heat stress, Heat shock response, Intertidal snail, Metabolic depression, Molecular adaptation, Thermal tolerance

Introduction

Depressed, temperature-insensitive metabolism has been widely observed in response to cold and heat stress in major animal phyla (Guppy and Withers 1999; Storey and Storey 2004; Navas and Carvalho 2010; Liao et al. 2021). At the molecular level, several cellular modifications occur during metabolic depression, including a decrease in pH, the presence of latent mRNA, an alteration in protein phosphorylation state, the maintenance of ion pumping, and downregulation of protein synthesis (Hand and Hardewig 1996; Guppy and Withers 1999). Metabolic depression is a well-known energy-conserving feature for many species living in harsh environments such as intertidal zone (Newell 1969; Marshall and McQuaid 1991, 2011; Sokolova and Pörtner 2001; Verberk et al. 2016). The conserved energy during metabolic depression might later be allocated into important functions (e.g., heat shock responses) to cope with further extreme conditions and increase the likelihood of survival. A recent study compared the response of heart rate to heat stress of 26 intertidal species and revealed the importance of metabolic depression to heat tolerance and species distribution (Liao et al. 2021). Understanding the molecular mechanisms for physiological responses to high thermal conditions is vital for predicting the fate of species under global warming (Somero 2010; Seebacher et al. 2015).

The cellular stress response (CSR) is a universal mechanism of physiological significance (Kültz 2005). Although CSR is pervasive in all lives on the earth, it is not a “one size fits all” reaction to thermal stress but a graded response (Kültz 2020; Somero 2020). The heat shock response (HSR) is a critical and early response in CSR (Feder and Hofmann 1999; Somero et al. 2017). Heat shock proteins (HSPs) are key components in the HSR and function as molecular chaperones, which help to restore the structure of unfolded proteins or facilitate the degradation of non-functional proteins (Sørensen et al. 2003; Pan et al. 2020), and stabilize cellular membranes (Maio and Hightower 2021; Somero 2022). Cytochrome P450 proteins (CYP450s) are recognized as another general molecular chaperone, belonging to evolutionarily conserved antioxidant proteins (Nelson and Strobel 1987; Snyder 2000; Zhang et al. 2012; Kültz 2020). The expression of genes encoding HSPs and CYP450s can be dramatically induced under thermal stress in intertidal species (Wang et al. 2016; Vergara-Amado et al. 2017; Dong et al. 2022). Given that these CSRs are energy-intensive (Kültz 2020; Somero 2020), when and to what extent these biological processes occur depend not only on the levels of thermal damage but also on the adaptive strategies in different levels of biological organization.

The rocky intertidal zone is one of the most variable and harshest environments on our planet (Gracey et al. 2008). Intertidal species are suggested to live close to their thermal limits (Stillman 2003; Stillman and Tagmount 2009) and are vulnerable to climate change (Helmuth et al. 2006; Hawkins et al. 2008). In the rocky intertidal zone, the degree and duration of thermal stress increase from the low shore to the splash zone (Raffaelli and Hawkins 1996). Much progress has been made in behavioral and physiological adaptations of intertidal ectotherms (Williams et al. 2005; Pörtner 2010; Somero 2020; Liao et al. 2021; Ng et al. 2021; Dong et al. 2022), especially for species living in the extreme thermal environments with high fluctuation (e.g., the splash zone). Marine ectotherms on the high shore to splash zone display obvious suppression and recovery of metabolic performance at high temperatures, such as snail Echinolittorina malaccana (Marshall et al. 2011) and oyster Isognomon nucleus (Hui et al. 2020). Some efforts have also been made in understanding the molecular response to stress during metabolic depression in some intertidal species. For example, the HSP70 expression was insensitive to heat stress during metabolic depression in snail E. malaccana (Marshall et al. 2011). Upregulation of several genes (e.g., ribosomal protein L26, ferritin heavy chain, cytochrome c oxidase subunit II, and KVN) has been detected in Littorina littorea under anoxia despite an overall suppression of transcription and translation (Larade and Storey 2002a, b; Storey and Storey 2004). As next-generation sequencing provides a much-needed tool for understanding thermal adaptation to heat stress in metazoans (Porcelli et al. 2015), we have an opportunity to gain insight into molecular mechanisms of metabolic depression. Answering this question is important for understanding how the organism survives the harsh thermal environment (López-Villalta 2008; Wethey et al. 2011).

The littorinid snail E. radiata is a keystone species on the high shore to splash zone in the Northwestern Pacific (NWP), and frequently encounters environmental temperatures over 55 °C in summer (Seuront and Ng 2016). The thermal environment in the rocky intertidal zone along the NWP coastline is a mosaic pattern with high variability and uncertainty (Dong et al. 2015, 2017). Different populations of E. radiata snails, therefore, face extreme and different thermal stresses along the species’ distribution range. Han et al. (2019) found that the E. radiata snails showed significant geographic variation in temperature sensitivity of HSP70 gene expression between two marine ecoregions along its range, the East China Sea Ecoregion (ECSE) and the South China Sea Ecoregion (SCSE). Here, we compared the physiological and transcriptomic responses to heat stress of two populations of the intertidal snail E. radiata along China’s coastline. We aimed to (1) examine the underlying molecular adaptation of metabolic depression of the intertidal snail, and (2) discern the molecular mechanisms that underlie physiological variation between populations. We postulate that adaptation or acclimation to local thermal regimes can lead to divergence in physiological traits and molecular responses that dictate thermal tolerance among populations.

Materials and methods

Body temperature estimation of E. radiata

Twenty-year estimates of the body temperature of E. radiata in sun-exposed habitats across study localities in summer (July to September) were calculated using a heat budget model modified from one developed to calculate body temperatures of snails (Marshall et al. 2015; Dong et al. 2017). The model was modified by changing partial parameters specific to the study species (i.e., shape, size, absorptivity, and the amount of contact area with the substratum). Environmental variables used in the model were hourly air temperature, wind speed, and solar radiation from 2001 to 2020. Environmental data were downloaded from the National Centers for Environmental Prediction Climate Forecast System Version 2 (CFSv2) (Saha et al. 2014). The Tide Model Driver (TMD) v2.5 (Padman and Erofeeva 2005) was used to estimate tides in MATLAB R2019b (MathWorks, Natick, Massachusetts).

Sample collection and acclimation

The E. radiata snails were collected from Wenzhou in the ECSE (WZ; 27°51′N, 121°11′E) and Xiamen in the SCSE (XM; 24°33′N, 118°09′E) (Fig. 1a). To avoid the potential effect of microhabitats (Dong et al. 2017), all snails (~ 8 mm in shell diameter) were sampled from sun-exposed rocky surfaces during the spring tides in July 2018. Following collection, snails were transported to the laboratory for a common garden acclimation. Snails from each locality were randomly allocated into three containers (~ 30 individuals in the 30 × 20 × 20-cm container) to simulate field densities of ~ 440 snails per m2 and acclimated for 2 months, a period likely to be adequate to remove past thermal history (Duffy et al. 2015). The acclimation temperature was 25.0 ± 1.0 °C, which was used to simulate the annual average seawater temperature (~ 25.5 °C) in the ECSE and SCSE (Wu et al. 2020). Snails were reared under a tidal cycle with 3 h of immersion and 9 h of emersion to model the condition in the upper intertidal zone. During acclimation, the snails were fed on biofilms on rocks. The mortality was less than 10% during the acclimation for each population.

Fig. 1.

Fig. 1

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a Sampling localities of intertidal snail Echinolittorina radiata in China. Wenzhou (WZ) is in the East China Sea Ecoregion (ECSE) and Xiamen (XM) is in the South China Sea Ecoregion (SCSE). b The total number of occurrences at each body temperature from 25 to 55 °C in summer (July to September) over the past 20 years (2001–2020) in both localities

Heart rate measurement

To understand changes in the physiological response to rising temperature in E. radiata, we measured the heart rate of snails using a noninvasive method (Dong and Williams 2011). The heartbeat of the snail was detected by an infrared sensor attached to the shell above the heart with the Blu-Tack adhesive (Bostik, Staffordshire, UK). After acclimation, snails (n = 17–18 per locality) were randomly selected, and each was positioned into a 20-mL glass container. The bottoms of the containers were immersed into water of 25 °C controlled by using a water bath (TXF 200; Grant, UK) for the ramping experiment. The heating rate was 0.1 °C/min to simulate the in situ average ramping rate in summer (Dong et al. 2017). Heart rate sensor signals were continuously monitored by PowerLab and analyzed by LabChart system v8.0 (ADInstruments, March-Hugstetten, Germany).

Three breakpoints and the depression breadth were determined from Arrhenius plots (ln rate against 1/T, where T is the temperature in Kelvin, K) by fitting two-phase regressions based on the minimum sum of squares using Origin v9.0 (OriginLab Corp., MA, USA). Three breakpoints included TBP1 (the temperature that initiated thermally insensitive metabolism), TBP2 (the temperature where the heart rate increased again), and the Arrhenius breakpoint temperature (ABT) (the temperature where the heart rate shapely decreased with further heating) (Fig. 2a). The depression breadth was the temperature difference between TBP1 and TBP2. In addition, the flatline temperature (FLT) was determined when the heart rate was zero beats per min.

Fig. 2.

Fig. 2

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a An example of Arrhenius plot of heart rate data that are used to determine breakpoint temperatures. Filled red squares represent three breakpoint temperatures (TBP1, TBP2, Arrhenius breakpoint temperature (ABT)) that are determined by fitting two-phase regressions based on the minimum sum of squares, and the flatline temperature (FLT) that is determined when the heart rate is zero beats per min. TBP1 is the temperature when thermally insensitive metabolism is initiated; TBP2 is the temperature when the heart rate increases again; the ABT is the temperature when the heart rate reduces rapidly. The depression breadth represents a temperature range between TBP1 and TBP2. b Heart rate performance curves of the snails from Wenzhou (WZ) and Xiamen (XM), depicting the trajectory of heart rate as temperature increases using a generalized additive mixed model (GAMM). The solid line is a smoothing spline, and the shaded area represents 2 × SE uncertainty for a regression fit. c, d The ABTs and the FLTs of heart rate in the snails from XM and WZ. A significant difference between the two localities, as determined by the t-test, is highlighted *P < 0.05

Heat stress exposures for transcriptome sequencing

To understand molecular responses in E. radiata, we examined their transcriptomic responses to heat stress. Three temperature treatments (37 °C, 45 °C, and 52 °C) were designed based on the heart rate performance curve, where 37 °C and 45 °C represented the temperature near the initiation and ending of metabolic depression, respectively, and 52 °C was the temperature near the ABT. After 2-month acclimation, ten snails were randomly selected (five individuals per locality) for each treatment. Each snail was transferred to a separate Petri dish (3 cm in diameter). The bottom of the dish was immersed into water of 25 °C controlled by using a water bath and heated at a rate of 0.1 °C/min to the designated temperatures (37 °C, 45 °C, and 52 °C). Then, the temperature decreased to 25 °C at a rate of 0.1 °C/min. During the period of heat treatment, five individuals from each locality were randomly selected and aerially exposed at 25 °C, as non-heated control samples. Finally, all the snails (heat-stressed and control samples) were immersed into 25 °C seawater for 2 h recovery, and then, the foot muscle of each individual was cut off immediately and stored at − 80 °C for further experiment.

Total RNA of foot muscle was extracted with Qiagen RNeasy Plus Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instructions. A total of 40 RNA-seq libraries (two populations × four treatments × five replicates) were constructed based on the following procedures. First, sequencing libraries were prepared using the NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) with DNase treatment, and index codes were added to attribute sequences to each sample. Second, the library quality was assessed using a 2100 Bioanalyzer (Agilent Technologies, Palo Alto, USA). Third, the clustering of the index-coded samples was performed on a cBot Cluster Generation System using HiSeq 4000 PE Cluster Kit (Illumina, San Diego, USA). Finally, the library preparations were sequenced in three lanes on an Illumina HiSeq 4000 platform, and 150 bp paired-end reads were generated.

Transcriptome analyses in response to heat stress

The quality of raw data was checked with FastQC v0.11.9 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Trimmomatic v0.33 (Bolger et al. 2014) was used to remove adapters and cut bases off the start (LEADING) and end (TRAILING) of reads (Q < 2), and reads shorter than 25 bp were removed. De novo transcriptome assembly was generated using Trinity v2.6.6 (Grabherr et al. 2011) with default parameters. To avoid potential population-specific mapping that might negatively affect comparison of differential gene expression between populations, we assembled a separate assembly for each population (Debiasse et al. 2018; Wang et al. 2022). In the population-specific assembly, four samples (one sample from each treatment) were selected for the assembly because these samples had the largest amount of data among all the samples in each treatment. After removing contigs sharing 95% sequence similarity in each transcriptome with CD-HIT-EST v4.6.8 (Fu et al. 2012), WZ and XM assemblies were prepared for gene expression and functional enrichment analysis. The quality and completeness of assemblies were checked using BUSCO v3.0.2 (Benchmarking Universal Single-Copy Orthologs) (Simão et al. 2015). BUSCO was run with the metazoan ortholog database of 978 genes.

To make a robust comparison of gene expression between populations, the present study detected orthologous transcripts present in both transcriptomes using the following procedures as adopted by Debiasse et al. (2018). First, transcriptomes were translated into protein sequences using TransDecoder v5.3.0 (Haas et al. 2013). Second, open reading frames (ORFs) were identified with homology to known proteins by running Diamond v0.9.22 (Buchfink et al. 2015) and Hmmer v3.1b2 (Eddy 2011) searches against the UniRef90 and Pfam-A v31.0 (Finn et al. 2016) databases, respectively. Third, we included the results of the homology searches in the final prediction of coding sequences (CDS) of TransDecoder. Finally, orthologous groups (orthogroups) were identified using OrthoFinder v2.2.6 (Emms and Kelly 2015) with default settings. The clean reads of each sample were mapped to the transcriptome of their own population using Salmon v0.8.2 (Patro et al. 2017) with default settings, and then, an orthogroup-level count matrix containing orthologous transcripts in both populations was created.

Differentially expressed orthogroups (DEOs) were identified with the orthogroup-level count matrix using R package DESeq2 v1.22.1 (Love et al. 2014). Low expressed orthogroups (i.e., the number of counts less than ten in more than five of the samples) were filtered out. Pairwise comparison between control (25 °C) and heat treatments (37 °C, 45 °C, and 52 °C) was performed with the Wald test for each population. An orthogroup was considered significant if the adjusted P value (Padj) was < 0.01 and |log2FoldChange| (|log2FC|) was ≥ 1. Principal coordinates analysis (PCoA) based on Manhattan distances of regularized logarithm (rlog) transformed counts was used to visualize the clustering of gene expression between temperature treatments and localities. Adonis was used to evaluate the significant effects of temperature treatments and population on global gene expression levels. PCoA and adonis were performed using R package vegan v2.5.7 (Anderson 2001).

To capture the relationship between orthogroups and temperature treatments, the weighted correlation network analysis (WGCNA) was performed with R package WGCNA v1.69 (Langfelder and Horvath 2008) according to the following procedures: (1) constructing a gene expression matrix by converting orthogroup-level count matrix with the “varianceStabilizingTransformation” function in DESeq2; (2) clustering samples to detect outliers with the “hclust” function; (3) determining the softpower value with R-square being 0.85 using the “pickSoftThreshold” function; (4) constructing a gene co-expression network and detecting modules with the “blockwiseModules” function (power = softpower, corType = pearson, minModuleSize = 30, mergeCutHeight = 0.25); (5) studying module relationships with module eigengenes (MEs), which represent the expression level for modules; (6) investigating correlations among gene expression modules and temperature treatments; and (7) investigating the hub genes of interesting modules that were most related with temperature treatment according to the calculated module membership (MM) and gene significance (GS) values.

Transcriptomes were annotated using the dammit pipeline (Scott 2016) with the Pfam-A v31.0 (Finn et al. 2016), Rfam v14.0 (Gardner et al. 2009), and OrthoDB v9.1 (Zdobnov et al. 2017) databases. In the case where there were multiple database hits, one protein name per contig was selected by choosing the name of the lowest e-value match (< 1e−05). Gene ontology (GO) terms for two translated transcriptomes were retrieved using InterProScan v5.30 (Jones et al. 2014). We used a custom script to match the GO terms assigned to contigs to the orthogroups containing those contigs. GO enrichment analysis was conducted with R package topGO v2.38.1 (Alexa et al. 2006). The minimum number of nodes was set to five, and terms with a P value below 0.01 were considered enriched in the classic Fisher exact test. Similar GO terms were collapsed with REVIGO (Supek et al. 2011) with default parameter settings. The enriched GO terms were visualized with GOChord using the R package GOplot v1.0.2 (Wencke et al. 2015). The GOChord shows the relationships between the selected genes and GO terms.

Results

Operative temperature

The body temperature of E. radiata estimated using the heat budget model showed that snails in WZ experienced higher frequencies of extreme weather events in summer than those in XM over the past 20 years (2001–2020). Among 17,476 h when body temperatures exceeded 25 °C in the WZ population, 2076 h (11.88%) were above 43 °C (Fig. 1b), while among 18,322 h when body temperatures were above 25 °C in the XM population, 1375 h (7.50%) were higher than 43 °C (Fig. 1b). The XM population (8841 h, 48.25%) experienced higher frequencies of moderate heat stress events between 33 and 43 °C, in comparison to WZ population (7460 h, 42.69%).

Cardiac performance curves and breakpoint temperatures

The cardiac performance curve of E. radiata was a bimodal pattern with temperature changes (Fig. 2b). The values of TBP1 and TBP2 of the XM population were 33.54 ± 3.32 °C (mean ± SD) and 45.45 ± 2.11 °C, respectively. For the WZ population, the TBP1 and TBP2 were 34.12 ± 2.99 °C and 43.52 ± 2.18 °C, respectively. The depression breadth of XM population (11.92 ± 2.71 °C) was significantly larger than that of WZ population (9.41 ± 3.21 °C) (t = 2.28, df = 29, P < 0.05).

The WZ population presented a higher thermal tolerance limit compared to the XM population. The average sublethal temperature (ABTs) of the WZ population (mean ± SD: 52.83 ± 0.76 °C) was similar to that of the XM population (52.43 ± 0.52 °C) (t = 1.76, df = 8.09, P = 0.09; Fig. 2c). There was significant difference in the lethal temperatures (FLTs) between WZ (mean ± SD: 54.16 ± 0.65 °C) and XM (53.44 ± 0.40 °C) (t = 3.79, df = 26.46, P < 0.01; Fig. 2d).

Transcriptomic data and orthogroup identification

The sequencing of 40 libraries resulted in an average of 24.3 million raw reads per library (range 19.4 million to 37.0 million; Supplementary Table 1). After removing redundancy with 95% similarity, the numbers of assembled transcripts were 494,257 and 617,052 in WZ and XM, respectively (Supplementary Table 2). The BUSCO result showed that WZ and XM assembly contained 87.8% and 96.2% complete conserved metazoan genes, respectively (Supplementary Table 2). There were 39,769 orthogroups containing transcripts from both transcriptomes, and 27,339 of them were identified as annotated orthogroups.

DEOs between populations

There were 33,835 orthogroups for differential gene expression analysis after filtering the low expressed orthogroups. The PCoA results showed that there were significant differences in gene expression between populations (adonis Ppop = 1e−6) and among heat treatments (adonis Ptreat = 0.0015) (Fig. 3a). For each population, samples under extreme thermal stress (52 °C) were clustered into a group, and there was overlapping among 25 °C, 37 °C, and 45 °C treatment groups.

Fig. 3.

Fig. 3

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a PCoA of the 40 Echinolittorina radiata individual samples’ global gene expression under different temperature treatments from Wenzhou (WZ) and Xiamen (XM) locality. The adonis method is used to determine the statistical significance of clustering. b The number of differentially expressed orthogroups (DEOs) under heat stress for the WZ (orange) and XM (blue) populations. The positive and negative values refer to the number of upregulated and downregulated DEOs (Padj < 0.01, |log2FoldChange|≥ 1), respectively, in response to 37 °C, 45 °C, and 52 °C as compared to the control 25 °C. c The ratio of up- and downregulated DEOs at 37 °C, 45 °C, and 52 °C for WZ (orange) and XM (blue) populations. Significant differences (P < 0.05) between different temperatures, as determined by Fisher’s exact test, are highlighted using asterisks

There were differences in the number of significantly differentially expressed orthogroups in response to rising heat stress. The number of DEOs (log2|FC|≥ 1 and Padj < 0.01) decreased from 37 °C (488) to 45 °C (214) and then increased at 52 °C (1427) in the WZ population, while the number increased with rising heat stress (37 °C, 314; 45 °C, 642; 52 °C, 2061) in XM (Fig. 3b). The ratio of up- and downregulated DEOs at 45 °C was significantly higher than that at 37 °C and 52 °C (P < 0.05) for each population (Fig. 3c), but nonsignificant differences were observed in the ratio at each temperature between populations.

Gene ontology enrichment of DEOs at 45 °C

Three biological process gene ontology (BP-GO) terms were significantly enriched for the DEOs at 45 °C in WZ, with two terms (protein polymerization and cytoplasmic microtubule organization) enriched for the upregulated DEOs and one term (DNA replication, synthesis of RNA prime) for the downregulated DEOs (Supplementary Fig. 1a). The significantly enriched 24 BP-GO terms at 45 °C in XM involved macromolecule metabolic process (e.g., proteolysis, protein modification by small protein conjugation, and DNA-dependent DNA replication), cellular metabolic process (e.g., citrate metabolic process, aerobic respiration, tricarboxylic acid metabolic process, antibiotic metabolic process, phosphatidylinositol phosphate biosynthetic process, and lipid phosphorylation), cellular component organization (e.g., microtubule polymerization or depolymerization, protein polymerization, supramolecular fiber organization, and cytoskeleton organization), developmental process (e.g., regulation of cell morphogenesis involved in differentiation, regulation of cell morphogenesis, cellular component morphogenesis, and anatomical structure morphogenesis), cell adhesion (e.g., substrate adhesion-dependent cell spreading regulation of cell adhesion, regulation of cell-substrate adhesion, and regulation of cell adhesion), and cellular localization (e.g., vesicle targeting trans-Golgi to endosome, and cytosolic transport) (Supplementary Fig. 1b).

There were 80 overlapping DEOs in the intersection of DEOs at 45 °C between the XM and WZ populations (71 upregulation and 9 downregulation). The average expression level (log2FC) of the upregulated DEOs in WZ (mean ± SE, 4.68 ± 0.25) was significantly higher than that in XM (3.70 ± 0.20). The upregulated DEOs contained multiple chaperones and co-chaperones, including HSP70 (9 accessions), HSP20 (5 accessions), HSP90AA1, AHA1, and CDC37 (2 accessions), USPA (3 accessions), UNC45A, and CYP450 (3 accessions) (Supplementary Fig. 2a; Supplementary Table 3). The downregulated DEOs included proteins containing the C-type lectin domain, SCP domain, CTCK domain, and chitin-binding domain (Supplementary Fig. 2a). GO enrichment analysis for the 80 overlapping DEOs showed that they were significantly enriched in 11 BP-GO terms (Supplementary Fig. 2b). The upregulated DEOs were significantly enriched in nine BP-GO terms, including cytoskeleton organization, cellular protein–containing complex assembly, protein polymerization, supramolecular fiber organization, protein peptidyl-prolyl isomerization, translational elongation, peptidyl-proline modification, cytoplasmic microtubule organization, and Golgi vesicle transport. Two BP-GO terms (DNA-dependent DNA replication and DNA replication, synthesis of RNA primer) were significantly enriched for the downregulated DEOs.

GO enrichment of hub genes in the WGCNA modules

To identify the relationship between orthogroups and heat treatments, WGCNA was used to do the clustering analysis and divided the 33,835 orthogroups into six co-expressed gene modules (Supplementary Fig. 3a). The MEturquoise was the largest module with 22,082 orthogroups. MEblue, MEbrown, MEyellow, and MEgreen contained 1873, 703, 362, and 130 orthogroups, respectively. According to the correlation (r-value) between module and treatment (Supplementary Fig. 3b), MEbrown was positively correlated with 37 °C (r = 0.50, P = 0.001) and 45 °C (r = 0.43, P = 0.006), and negatively correlated with 52 °C (r =  − 0.75, P = 2e−08). MEblue was negatively correlated with 37 °C (r =  − 0.47, P = 0.002) and positively correlated with 52 °C (r = 0.65, P = 5e−06).

We determined the hub genes in the module in relation to a specific heat treatment by setting |MM|> 0.8 and |GS|> 0.5. Most detected hub genes presented a similar expression trend between the WZ and XM populations. In the MEbrown at 37 °C (Fig. 4a), the difference in the average expression level (log2FC) of the 20 upregulated hub genes was nonsignificant between the WZ (mean ± SE, 2.17 ± 0.27) and XM populations (2.03 ± 0.38). In the MEbrown at 45 °C (Fig. 4b), the average level of the 18 upregulated hub genes in XM (4.82 ± 0.20) was significantly higher than that in WZ (2.24 ± 0.12) (P < 0.0001). The 18 hub genes belonged to the DEOs at 45 °C in XM, while only four of them were the DEOs in WZ. For the 120 downregulated hub genes in the MEbrown at 52 °C (Fig. 4c), the average expression level was significantly lower in WZ (− 2.17 ± 0.11) than that in XM (− 1.48 ± 0.09) (P < 0.0001); 52 out of them were DEOs at 52 °C in WZ, and 24 were DEOs in XM. In the MEblue at 37 °C (Fig. 4d), the difference in the average expression level of the 8 downregulated hub genes was nonsignificant between the populations (WZ, − 0.61 ± 0.15; XM, − 0.38 ± 0.06). In the MEblue at 52 °C (Fig. 4e), the 147 upregulated hub genes belonged to the DEOs in both populations; no significant difference in the average express level was observed between the two populations (WZ, 4.31 ± 0.25; XM, 4.39 ± 0.22). Multiple hub genes encoding chaperones and co-chaperones were highly expressed at 52 °C in both populations, including HSP20, DNAJB4 (2 accessions), HSP70 (16 accessions), AHSA1, HSP90AA1, HSP90, DNAJ, DNAJA1, FKBPPlase, CHORDC1, and TCP-1 (2 accessions), and IAP (2 accessions) (Supplementary Table 4).

Fig. 4.

Fig. 4

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Heatmap for the significantly expressed hub genes in the MEbrown related to 37 °C (a), 45 °C (b), and 52 °C (c), and in the MEblue related to 37 °C (d) and 52 °C (e) in the analysis of WGCNA. Heatmap color indicates log2 fold change in expression level (yellow and blue indicate up- or downregulation, respectively) relative to 25 °C control treatment. The number in the parentheses following the gene name indicates the accession number of the corresponding gene. A significant difference in the average expression level of hub genes between Wenzhou (WZ) and Xiamen (XM) populations, as determined by the t-test, is highlighted *P < 0.05

There were different enriched GO terms (P < 0.01) for MEbrown and MEblue at different thermal stresses. The hub genes in the MEbrown at 45 °C were significantly enriched in seven BP-GO terms, namely Golgi vesicle transport, cell morphogenesis involved in differentiation, regulation of cell morphogenesis involved in differentiation, regulation of cell morphogenesis, regulation of cell-substrate adhesion, regulation of cell adhesion, and response to stress (Fig. 5a). The hub genes in the MEbrown at 52 °C were significantly enriched by citrate metabolic process, aerobic respiration, tricarboxylic acid metabolic process, antibiotic metabolic process, lipid phosphorylation, and phosphatidylinositol phosphorylation (Fig. 5b). In the MEblue, the hub genes were significantly enriched by five BP-GO terms at 37 °C, including transport, localization, methionine biosynthetic process, sulfur amino acid metabolic process, and nucleotide excision repair (Fig. 5c); the hub genes at 52 °C were significantly enriched in neurotransmitter transport and intracellular protein transport (Fig. 5d).

Fig. 5.

Fig. 5

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The gene ontology (GO) enrichment analysis identified biological processes (P < 0.01) in the MEbrown related to 45 °C (a) and 52 °C (b), and the MEblue related to 37 °C (c) and 52 °C (d). The enriched biological processes of the identified hub genes were plotted with GOChord. The left half of GOChord shows whether the hub gene is upregulated (yellow) or downregulated (blue), and the right half displays different GO terms with different colors

Expression of HSP70 and CYP450 genes

Both the number and the expression level of HSP70 increased as heat stress increased (Fig. 6a). There was a significant increase in the average expression level of HSP70 from 37 to 45 °C in WZ (P < 0.05), while a significant increase from 45 to 52 °C was observed in XM (P < 0.01).

Fig. 6.

Fig. 6

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Effects of different heating temperatures on the expression levels of heat shock protein 70 (HSP70) (a) and cytochrome P450 protein (CYP450) (b) genes in the Wenzhou (WZ) and Xiamen (XM) populations of Echinolittorina radiata. Different letters indicate significant differences (one-way ANOVA followed by Tukey’s test, P < 0.05) in WZ (yellow letters) and XM (blue letters)

The expression levels of CYP450 genes were significantly upregulated at 37 °C and 45 °C but downregulated at 52 °C in both populations (Fig. 6b). There was a significant increase in the average level of CYP450 from 37 to 45 °C in XM (P < 0.01).

Discussion

The cellular stress response is not a “one size fits all” response across populations depending on their local thermal regimes. The present study revealed the physiological and transcriptional responses of the snail E. radiata that occupies the splash zone habitat, and various physiological mechanisms to deal with heat stress across different populations. Thermal insensitivity of metabolic rate and gene expression occurred in the face of moderate heat stress (~ 33–45 °C). However, expression of genes that were required in cells to resist heat and oxidative stress (e.g., HSPs and CYP450s) was significantly upregulated during the metabolic depression. The saved energy during metabolic depression should be important for the HSR activities under sublethal/lethal extreme heat stress. The population experiencing more frequent moderate heat events would display larger depression breadth and insensitive upregulation expression of HSR genes (e.g., HSP70s) but heat-sensitive expression of OSR genes (e.g., CYP450s) at the temperature of 37 to 45 °C.

Temperature-insensitive metabolism is an adaptation to harsh environments

Metabolic depression of intertidal species reflects their physiological adaptation to local thermal conditions. The splash zone E. radiata snails displayed thermal insensitivity of metabolic rate at 33–45 °C, a temperature range that they frequently encountered in summer (~ 5 h per day on average; Fig. 1b). High shore to splash zone species also faces the challenge of reduced opportunities to gain energy from feeding (Williams and Little 2007). Metabolic depression is suggested as an adaptive strategy that organisms adopt to avoid energetic demands and consumption under certain stressful conditions (Guppy and Withers 1999; Storey and Storey 2004). This conservation strategy is crucial for coping with lifelong temporal and thermal constraints on foraging and energy gain (Marshall and McQuaid 2011; Marshall et al. 2011; Liao et al. 2021) in distantly related species inhabiting harsh environments, including E. malaccana (Marshall et al. 2011), Littorina brevicula (Liao et al. 2021), and I. nucleus (Hui et al. 2020), implying that metabolic depression might be a common strategy surviving extreme intertidal environments in a long term.

The present study reveals differences in the depression breadth and upper thermal limit between the two populations facing different thermal regimes. The XM population, which experienced more frequent moderate heat events at 33–43 °C (4.91 h and 4.14 h per day on average in summer in XM and WZ, respectively), displayed significantly larger depression breadth (11.92 ± 0.68 °C) in comparison to the WZ population (9.41 ± 0.89 °C). These results indicate that the duration of metabolic depression is potentially closely related to the local thermal regimes. Snails might prolong the duration of metabolic depression if they have higher odds of being exposed to moderate heat events inducing metabolic depression.

Larger metabolic depression breadth does not mean higher upper thermal limit. In the present study, the XM population that owned a larger metabolic depression breadth had lower thermotolerance than the WZ population. Although metabolic depression allows conservation of energy and is suggested as an important strategy for determining heat tolerance of intertidal species (Liao et al. 2021), it also can potentially induce negative impacts, e.g., accumulation of waste metabolites (Chen et al. 2021) and impairment of protein biosynthesis (Marshall et al. 2011), that potentially impair the heat tolerance in the face of extreme heat stress.

Molecular adaptation of metabolic depression

The expression patterns of genes with divergent functions are different during metabolic depression. In the present study, the change in the number of differentially expressed genes from 37 to 45 °C was much smaller than that from 45 to 52 °C (Fig. 3b), indicating the insensitivity in gene expression to heat stress during metabolic depression. On the other hand, the ratio of up- and down-regulated genes at 45 °C was significantly higher than that at 37 °C and 52 °C, suggesting that the snails might induce the expression of essential genes to cope with immediate damage from heat stress after metabolic depression. Chaperones and co-chaperones were the main components of the upregulated DEOs at 45 °C, including HSP90AA1, HSP20, HSP70, UNC45A, USPA, CDC37, and AHA1 (Supplementary Fig. 2a). The upregulated genes at 45 °C were significantly enriched in the cellular macromolecule metabolic process (e.g., peptidyl-proline modification and translational elongation), cellular component organization (e.g., cytoskeleton organization, supramolecular fiber organization, protein-containing complex assembly), and Golgi vesicle transport (Supplementary Fig. 2b). In the CSR, chaperones not only function to restore and defend the integrity of macromolecular systems (Kültz 2020; Somero 2020) but also stabilize cellular membranes (Maio and Hightower 2021). Therefore, maintaining structural and functional homeostasis by using chaperones might still be the main task of snails during and after metabolic depression.

Divergence in gene expression during metabolic depression reflects population-specific molecular thermal responses. For the XM population, the expression levels of multiple genes involved in the OSR, including genes encoding CYP450 (38 accessions), glutathione S-transferase (GST) (4 accessions), and ATP-binding cassette (ABC) transporter (19 accessions) (Supplementary Table 5), were significantly upregulated at 45 °C, further supporting that the XM population owns higher thermal sensitivity in the face of moderate heat stress. Comparatively, the change in the number of DEOs was less sensitive to heat stress at 45 °C in the WZ population. Among these DEOs, there were few CYP450s (4 accessions) and no ABC transporter and GST. ROS productions (e.g., superoxide, hydrogen peroxide, and hydroxyl radical) accumulate as metabolic rates increase under warmer temperatures in marine species (Yao and Somero 2012; Wang et al. 2016; Harrington et al. 2020), and then, the OSR is activated (Thannickal and Fanburg 2000). CYP450s and GSTs are important components of the detoxification enzyme system in the OSR (Liska 1998), protecting cells against oxidative damage (Neve and Ingelman-Sundberg 2010). Firstly, in the phase I of detoxification, CYP450s use oxygen and NADH to add a reactive group (e.g., hydroxyl radical); secondly, the reactive molecules from phase I can be further metabolized by enzymes in the phase II conjugation reactions (Liska 1998). For example, GSTs catalyze the conjugation of glutathione with toxic oxidant compounds for detoxification (Sheehan et al. 2001). The upregulation of genes encoding detoxification enzymes has also been widely observed in marine invertebrates under heat stress, such as snail E. malaccana (Wang et al. 2016), snail Chlorostoma funebralis (Gleason and Burton 2015), sea urchin Loxechinus albus (Vergara-Amado et al. 2017), limpet Patella vulgata (Moreira et al. 2021), bivalve Mya truncata (Sleight et al. 2018), and oyster Crassostrea virginica (Rahman and Rahman 2021). Finally, ABC transporters can positively transport physiological wastes out of cells in the phase III excretion as observed in aquatic invertebrates (Jeong et al. 2017). Those molecular responses in the OSR are highly energy-consuming processes. In the present study, multiple biological processes involved in energy production were enriched in the XM population at 45 °C (e.g., aerobic respiration, tricarboxylic acid metabolic process, and lipid phosphorylation). It implies that the XM population needs to produce and consume more energy to resist heat and oxidative stress during metabolic depression.

Differences in molecular response under various heat stresses, however, need to be interpreted with caution due to the dynamic nature of the ramping methodology and the recovery from seawater in the present study. In addition to the effect of the intensity of heat stress, the duration of heat stress might cause differences in gene expression (Buckley and Hofmann 2004). Here, snails exposed to 45 °C would experience a much greater duration of metabolic depression than snails exposed to 37 °C due to the ramping methodology including the heat up and then cool down. We could not determine whether the difference in expression patterns between these two treatments was due to the differences in intensity or duration of heat exposure. Another noteworthy aspect is that snails were immersed into seawater for recovery prior to sampling, which means that the transcriptomic response might not directly reflect the effect of designed heat stress. Given that some genes (e.g., HSPs, HSF, and TCP-1) can show delayed and late expression relative to the timing of the stimulus (Hensen et al. 2013; Louis et al. 2017; Yusof et al. 2022), the experimental design of the present study, as many studies adopted (e.g., Tomanek and Somero 2000; Zhang et al. 2014; Li et al. 2018; Liu et al. 2019), could provide partial but not all information on the transcriptomic response during metabolic depression. Therefore, it is necessary to consider both immediate and delayed transcriptional responses in the experimental design for future studies.

HSR and OSR during metabolic depression

Molecular responses of HSR and OSR during metabolic depression are related to energy balance and heat tolerance. Although metabolic depression is suggested to potentially enhance species’ thermal tolerance and is beneficial for surviving extremely harsh intertidal habitats (Marshall et al. 2011; Liao et al. 2021), the present study finds that prolonged depression might negatively affect the upper thermal tolerance due to energy deficiency. Stress-related biomarkers (e.g., HSP70 and CYP450) can be used to determine the conditions of the HSR and OSR and thus predict the consequences of stress exposures (Sokolova et al. 2012). In the XM population, the upregulation expression was insensitive for HSP70s but sensitive for CYP450s under heat stresses at 37–45 °C, while the average expression level significantly increased for HSP70s and decreased for CYP450s from 45 to 52 °C, indicating that the XM population would consume more energy to deal with heat and oxidative stress during the prolonged depression. This response might limit their ability to deal with further extreme stress due to energy deficiency and may be associated with its reduced thermal tolerance. A similar situation has also been observed in another splash zone species, E. malaccana, in which severe energy deficiency due to higher gene expression of metabolic enzymes (including the CYP450 gene family) at 45 °C was suggested to be linked with reduced thermal tolerance of the XM population in comparison with the lower latitude populations (Wang et al. 2016).

In the WZ population, the average expression level of HSP70s significantly increased from 37 to 45 °C, and maintained at a high level during stress at 45–52 °C. This response pattern might correspond to a “preparative defense” strategy to cope with local frequent and short-term extreme heating events in the intertidal zone (Dong et al. 2008; Wang et al. 2020). Although maintaining a high level of HSPs is also expensive in energy cost, this strategy might be more efficient in energy utilization in the HSR for organisms in the habitats where extreme stress occurs more frequently (Somero 2020). Therefore, we suggest that sufficient energy supply from conserved energy by metabolic depression and efficient energy use under extreme heat stress might be associated with higher upper thermal limits of the WZ population.

The downregulation of CYP450s at 52 °C in both populations reflects an inability of the snail to respond to oxidative damage and suggests redistribution of energy towards the HSR under extreme heat stress. This result aligns with the findings in other marine species, e.g., rock goby Gobius paganellus (Vinagre et al. 2014) and American lobsters Homarus americanus (Lopez-Anido et al. 2021). In addition to the downregulation of the OSR, the snail also shuts down most biological processes with general housekeeping functions to cells (Fig. 5b) during periods of extreme stress. This response might ensure that sufficient energy is allocated into the intracellular processes directly to deal with extremely stressful conditions (e.g., repairing unfolded proteins and intracellular protein transport). Our data provide new evidence for the idea that CSR is not a “one size fits all” reaction to thermal stress (Kültz 2020; Somero 2020). Therefore, it is necessary to consider the interpopulation variation of CSR for predicting species’ future fate under global warming (Dong et al. 2015, 2022).

Concluding remarks

The present study is intended to reveal the molecular adaptation of metabolic depression for species with high thermal tolerance living in harsh intertidal environments. During metabolic depression, repression of the number of differentially expressed genes could minimize energy expenditures, and limited energy was mainly used for HSR and OSR. This might be an important molecular mechanism of high thermotolerance for the animals in the splash zone. Different populations rely on various physiological and molecular mechanisms to differing extents to deal with heat stress, potentially reflecting adaptation to local thermal regimes. Our study highlights that the CSR is not a “one size fits all” response but instead varies across populations depending on local thermal regimes.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 1039 KB) (1MB, docx)

Author contribution

Y.-W.D. designed research, J.W. and L.-X. M performed research, J.W. analyzed data, and J.W. and Y.-W.D. wrote the paper. All authors contributed to the interpretation of the results and approved the final manuscript.

Funding

This work was supported by grants from the National Natural Science Foundation of China (41976142, 42025604) and the Fundamental Research Funds for the Central Universities.

Declarations

Consent for publication

All authors have consented to publication.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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