Heat shock protein 70 in Cynops orientalis: Bidirectional thermal regulation and metabolic optimization in amphibian climatic adaptation

Heat shock protein 70 in Cynops orientalis: Bidirectional thermal regulation and metabolic optimization in amphibian climatic adaptation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Heat shock protein 70 in Cynops orientalis: Bidirectional thermal regulation and metabolic optimization in amphibian climatic adaptation Junrong Liu, Yanqing Tang, Zhengyuan Fang, Zhiwen Wang, Haoyuan Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6990504/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jan, 2026 Read the published version in BMC Genomics → Version 1 posted 13 You are reading this latest preprint version Abstract This study investigates the molecular mechanisms underlying thermal resilience in the Cynops orientalis (Chinese fire-bellied newt) through functional characterization of CoHsp70 , a cytosolic heat shock protein 70 homolog. Comparative genomic analysis revealed conserved structural domains (ATPase, substrate-binding domain, and EEVD motif) and > 80% sequence identity with amphibian orthologs. Tissue-specific profiling identified adipose tissue as the predominant site of CoHsp70 expression. Temperature-dependent transcriptional regulation exhibited bidirectional dynamics: rapid induction under acute heat stress versus progressive suppression during chronic cold exposure. CoHsp70 overexpression enhanced hyperthermic survival while reducing metabolic expenditure (SMR, REE) and oxygen consumption rate (OCR). Taken together, these results suggest that CoHsp70 is a critical modulator of amphibian temperature resilience, balancing proteostatic fidelity with energy conservation under thermal extremes. CoHsp70 Cynops orientalis metabolic efficiency overexpression stress response Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Climate change, characterized by rising thermal extremes and altering hydrological cycles, imposes multidimensional pressures on amphibian populations globally [ 1 ]. These perturbations destabilize amphibian habitats while disrupting their physiological equilibrium, ultimately manifesting as behavioral modifications, reproductive impairments, and elevated mortality thresholds [ 2 – 4 ]. Prolonged thermal stress activates conserved molecular defenses, particularly through heat shock protein (HSP) cascades, which mitigate proteotoxic damage during cellular denaturation [ 5 – 7 ]. Amphibians' constrained thermal tolerance thresholds amplify vulnerability to metabolic dysfunction, developmental anomalies, and population declines in climate-sensitive ecosystems [ 8 – 11 ]. Cynops orientalis (Chinese fire-bellied newt), a caudate amphibian endemic to freshwater systems in China [ 12 ], thrives in ecologically variable habitats including agricultural wetlands, ephemeral ponds, and montane streams, demonstrating adaptive plasticity to microenvironmental heterogeneity [ 13 ]. This species exhibits exceptional thermal resilience, tolerating natural fluctuations from 5°C to 35°C and transient exposure to > 40°C in thermally buffered microhabitats during summer stratification [ 14 , 15 ]. This exceptional thermal resilience — combined with an established captive breeding system enabling controlled thermal stress exposure — positions C. orientalis as a model organism for ectotherm adaptation studies [ 16 ]. Mechanistic research on stress-responsive pathways — including HSP-mediated proteostasis, redox regulation, and epigenetic modifications — is critical for modeling adaptive potential and guiding conservation strategies amid accelerating environmental change. Elucidating these molecular-ecological interfaces will enhance predictive frameworks for species resilience under escalating climatic volatility [ 17 , 18 ]. Heat shock proteins (HSPs), a phylogenetically conserved class of molecular chaperones, are transcriptionally upregulated under diverse stress conditions beyond thermal exposure, including cold shock, hypoxia, pathogenic invasion, nutritional deprivation, physical injury, and xenobiotic toxicity [ 19 – 21 ]. The HSP superfamily is phylogenetically categorized by molecular weight into distinct subgroups: HSP100, HSP90, HSP70, HSP60, HSP40, and small heat shock proteins (sHSPs), each exhibiting specialized roles in cellular stress adaptation [ 22 ]. HSP70 family encompasses both constitutively expressed isoforms (e.g., Hsc70 / HSPA8 ) functioning in basal proteostasis and stress-inducible variants (e.g., Hsp72 / HSPA1A ), which are dynamically upregulated during proteotoxic crises [ 22 ]. As a central node in cellular stress defense, HSP70 orchestrates nascent polypeptide folding, facilitates the disaggregation and renaturation of denatured proteins, and targets irreversibly damaged substrates for proteasomal degradation, thereby preserving proteostatic integrity under thermal extremes [ 23 , 24 ]. Empirical studies about amphibian taxa reveal conserved HSP70 induction patterns during hyperthermic challenges. In Xenopus laevis A6 kidney epithelial cells, proteasome inhibitors (e.g., celastrol or MG132) suppress chymotrypsin-like activity, triggering HSF1 binding to heat shock elements and dose/time-dependent HSP70 induction. As a critical chaperone, HSP70 prevents aggregation and maintains client protein solubility/folding capacity during stress, contrasting with HSP30 prolonged stability [ 25 , 69 ]. Studies in Rana temporaria tadpoles revealed that HSP70 levels increased during late developmental stages (Gosner 39–42), with northern populations exhibiting higher constitutive expression at 13°C compared to southern counterparts, a difference abolished at 19°C, highlighting temperature-dependent adaptation [ 26 ]. In Rana lessonae , Hsp70 was strictly heat-inducible (33°C), contrasting with constitutive Hsc70 expression, and both localized to neuroectoderm and somites during organogenesis, suggesting dual roles in stress response and developmental regulation [ 27 ]. These results demonstrate that the evolutionarily conserved HSP70 molecular chaperone coordinates amphibian thermotolerance and developmental fidelity through a heat-shock-responsive regulatory mechanism. However, systematic characterization of HSP70 across amphibian lineages remains constrained by interspecific genomic heterogeneity, ecological niche-driven adaptation dynamics, and technical limitations in resolving paralogous gene clusters. These challenges underscore the need for advanced phylogenomic approaches to elucidate HSP70 functional diversification in this ecologically vulnerable clade. In ectotherms, energy budget allocation efficiency is a central metric for evaluating climatic adaptation. Resting energy expenditure (REE), quantified through gas exchange rates ( V O₂ / V CO₂ ), directly reflects the basal metabolic load of organisms under quiescent conditions and their energy economy during stress [ 28 ]. Standard metabolic rate (SMR) characterizes the baseline energy demand required for fundamental processes such as cellular homeostasis under minimized environmental interference [ 29 ], while oxygen consumption rate (OCR) reveals mitochondrial respiratory chain activity and oxidative phosphorylation efficiency via oxygen utilization per unit time [ 30 ]. These three metabolic phenotypes collectively establish an analytical framework for bioenergetic budgeting: SMR defines survival thresholds, REE captures stress-induced metabolic trajectories, and OCR deciphers mitochondrial functional plasticity. Recent studies indicate that energy expenditure influences the efficiency of Hsp70 chaperones in correctly refolding misfolded proteins [ 31 ]. However, empirical research directly linking HSP70 activity to metabolic phenotypes such as SMR, REE, and OCR remains scarce, particularly in non-model amphibians facing climate-driven thermal oscillations. This knowledge gap severely constrains a comprehensive understanding of the ecological adaptive value of HSP70. Functioning as an evolutionarily conserved molecular chaperone, HSP70 coordinates thermal stress adaptation with systemic metabolic regulation in animal organisms. In this study, we report the molecular cloning and stress-inducible expression profiling of CoHsp70 , a heat shock protein 70 homolog from C. orientalis . Tissue-specific expression analysis revealed differential CoHsp70 mRNA abundance across organ systems, exhibiting temperature-dependent expression dynamics. Transgenic overexpression of CoHsp70 conferred enhanced thermotolerance in newts during thermal challenge. Mechanistic investigation demonstrated time-temperature superposition effects on metabolic remodeling, as evidenced by significant alterations in SMR, REE and OCR profiles. Our findings bridge molecular chaperone biology with conservation physiology, demonstrating how CoHsp70 balances proteostatic resilience with energy economy — a framework critical for predicting ectotherm adaptability to anthropogenic thermal shifts. Materials and Methods Animal acquisition and controlled housing conditions All experimental procedures involving animals were conducted in strict compliance with the ethical guidelines and regulations governing animal welfare and scientific research in China. The protocol was reviewed and approved by the Animal Research Ethical Committee of Hangzhou Normal University (Approval Number: 2023049). Adult newts ( n = 300) were procured from Shengsheng Hatchery (Hangzhou, China) and acclimated in standardized polypropylene containers (100 × 100 × 80 mm) with ventilation holes. Precise mass determination (± 1 mg) was performed using a calibrated electronic balance (AB135-S; Mettler Toledo, Switzerland) prior to housing. Each container contained a peat-moss substrate and filtered water (40 mm depth, pH 5.1 ± 0.2) to simulate natural microhabitat conditions. Specimens were maintained in temperature-controlled incubators (Panasonic, Higashi, Japan) at 18.0 ± 0.5°C under a 12 h:12 h light-dark cycle with automated illumination (06:00 − 18:00). The newts were fed at 48-hour intervals using thawed Limnodrilus spp. earthworms, with residual food particles and fecal matter systematically removed via sterile forceps within 30 minutes post-feeding. Molecular cloning and structural characterization of CoHsp70 Part of CoHsp70 sequence was obtained by PCR from newt liver DNA using the primers CAU70-F1 and CAU70-R1 (Table 1 ) based on the conserved region sequence of Pleurodeles waltl , Ambystoma mexicanum , Rana amurensis and Rana lessonae (GenBank accession nos. X71951, AY029210, MZ736885, MZ736884). Partial genomic sequences were obtained using the Genome Walking Kit (Takara, Dalian, China), followed by acquisition of the complete open reading frame (ORF) sequence via the SMARTer RACE 5’/3’ Kit (Takara, Dalian, China). The ORF sequence was submitted to GenBank under accession number PQ323562. Sequence homology was verified using NCBI BLAST, while physicochemical properties were analyzed via ExPASy ProtParam. Secondary structure prediction employed SOPMA (NPS@ server), and domain architecture was resolved using SMART v4.0. The tertiary structure was predicted via homology modeling using SWISS-MODEL. Phylogenetic analysis To construct a meaningful phylogenetic tree, NCBI was used to search for 6 classes of CoHsp70 homologous proteins in Chordata : Mammalia , Aves , Reptilia , Amphibia , Chondrichthyes , and Osteichthyes . Ten proteins with > 80% homology to CoHSP70 in each class, with a total of 60 species. Multiple sequence alignment was performed using MUSCLE v3.8 with default gap penalties. Phylogenetic analysis was performed using MEGA11 with neighbor-joining method [ 32 – 34 ]. Table 1 Primers used in polymerase chain reaction. Primer name Primer sequence (5' to 3') CAU70-F1 CATGGCAAGGTGGAGATCATC CAU70-R1 TTAAAATGGAAACATCAAAGGT RT70-F1 GAGGATCATCAATGAGCCAACAG RT70-R1 GTGTCTCCAGCTGTAGCCTTGAC GAPDH-F1 CTGTCCATGCTGTGACTGCT GAPDH-R1 CACATTGGCGACAGGTACAC IRES70-F1 CGAGCTCAAGCTTCGAATTCGATATC ATGTCTGCACCCAAGGGCGTCGC IRES70-R1 CAATGGTGATGGTGATGATGGATATC ATCGACTTCTTCGATAGTGG IRG-F1 CTACTTGGCAGTACATCTACGT IRG-RI GACGGCAATATGGTGGAAAAT *The underlined region represents the partial sequence of the ligated plasmid, with the restriction enzyme sites indicated at the emphasized positions. Constitutive CoHsp70 expression in newt tissues ​ Tissues or organs from newts ( n = 5) were collected, flash-frozen in liquid nitrogen, and stored at − 80°C for subsequent experiments. The tissues collected included liver, fat, lung, heart, kidney, stomach, muscle, and intestine. Total RNA was extracted by using an RNA extraction kit (Takara, Dalian, China). One microgram of total RNA was treated with a gDNA Eraser Kit (Takara, Dalian, China) and used for cDNA synthesis with a PrimeScript™ RT Reagent Kit (Perfect Real Time) (Takara, Dalian, China). Quantitative real-time reverse transcription-PCR (qRT-PCR) was performed using a C1000™ thermal cycler (Bio-Rad, Hercules, CA, USA) with an iTaq Universal SYBR Green Supermix Kit (Bio-Rad, Hercules, CA, USA). Each assay was performed in triplicate and programmed as follows: 95°C for 30 s, followed by 40 cycles of 95°C for 5 s and 60°C for 30 s for 30 s, finally 95°C for 10 s. A negative control without template was included in each assay. Melt curve analysis of amplification products was performed at the end of each PCR to confirm amplification specificity. The housekeeping gene was amplified using primers GAPDH-F1 and GAPDH-R1 , which were designed according published newt sequence. The primers, RT70-F1 and RT70-R1 , used to amplify CoHsp70 were designed according to the sequence obtained in our study (Table 1 ). CoHsp70 expression in response to temperature challenges Adult newts ( n = 60) were divided into two groups (30 specimens/group) and acclimated at 4°C (hypothermic stress) or 32°C (hyperthermic stress). Hepatic tissues were harvested at defined intervals: 4°C-exposed specimens at 0, 8, 24, 48, 72, and 96 h; 32°C-exposed specimens at 0, 2, 8, 16, 24, and 48 h. All excised tissues were immediately flash-frozen in liquid nitrogen and stored at − 80°C until RNA extraction. RNA extraction, cDNA synthesis, and qRT-PCR protocols followed the methods described in Section 2.4. CoHsp70 overexpression and metabolic phenotyping ​ (i) Plasmid construction The open reading frame of CoHsp70 was amplified by PCR using primers IRES70-F1 and IRES70-R1 (Table 1 ). The 1941-bp fragment was ligated into the pIRES2-EGFP vector (Clontech, Mountain View, CA, USA) using a one-step PCR cloning kit (Novoprotein, Shanghai, China). pIRES2-CoHsp70 was generated to express an EGFP tagged CoHsp70 in newts. (ii) Thermal stress response in CoHsp70 -overexpressed newts​ Adult newts ( n = 80) were divided into two groups (40 newts/group) for plasmid intramuscular plasmid injection. Forty newts were injected with 60 µL PBS containing 600 ng pIRES2-EGFP at caudal musculature, while 40 newts were injected with 60 µL PBS containing 600 ng pIRESPs-CoHsp70 . Post-injection, cohorts were acclimated in controlled thermal environments programmed for gradual thermal shifts: one group transitioned from 18°C to 36°C (+ 2.25°C/d), the other from 18°C to 2°C (− 2°C/d), reaching target temperatures within 8 days (Fig. 1 A). Each thermal cohort consisted of 20 pIRES2-EGFP -injected newts and 20 pIRESPs-CoHsp70 -injected counterparts. Newts were monitored daily during the 10-day exposure at stabilized extreme temperature (36°C or 2°C). Mortality was defined by cessation of opercular movement and righting reflex loss. (iii) Respirometric measurement of SMR and OCR in newts Ninety adult newts were allocated to three thermal regimens (30 newts/group), each comprising 15 pIRES2-EGFP -injected and 15 pIRESPs-CoHsp70 -injected individuals: (1) hypothermic adaptation (18°C to 4°C, − 0.8°C/day), (2) hyperthermic acclimation (18°C to 32°C, + 1.5°C/day), and (3) isothermal maintenance at 18°C. All cohorts were stabilized at their respective target temperatures for 21 days prior to metabolic evaluation (Fig. 1 B). Metabolic profiling utilized an FMS portable respirometry system (Ecotech, Beijing, China) with eight RM8-switched microchambers (30 mL/min standardized airflow). SMR (mL O₂ g⁻¹ h⁻¹) was quantified after 10 min dark acclimation in partially vented chambers, followed by 30 min continuous V O₂ /V CO₂ monitoring via ExpeData software (baseline-corrected against channel 1 blanks). Measurements were repeated five times (Days 0, 7, 14, 21, 28) under low-light conditions (12:00–22:00), preceded by 24 h fasting and mass recording. Respiratory measurements were conducted quintuply at Days 0, 7, 14, 21, and 28 under low-light conditions (12:00–22:00 h), with 24-hour fasting and mass documentation preceding each trial. This protocol adheres to ectotherm metabolic research standards for environmental stress minimization and data reproducibility. OCR (mg g⁻¹ h⁻¹) was measured under identical temperature acclimation conditions as SMR, with matching time points, sample sizes, and temperature parameters. OCR measurements were conducted at five intervals (Days 0, 7, 14, 21, 28) using 250 mL glass respirometry chambers containing 24-hour aerated water. Initial dissolved oxygen ( DO 0 , mg L⁻¹) was measured with a JPBJ-610L meter (Leici, Wuxi, China) at ± 0.3 mg L⁻¹ accuracy. After 1 h incubation, final dissolved oxygen ( DO₁ ; mg L⁻¹) was recorded, followed by blot-drying and volumetric displacement-based mass ( M ; g) determination. OCR was calculated as [( DO₀ − DO₁ ) × (chamber volume − newt volume)] / ( M × t ), with chamber volume = 250 mL and t = 1 h. All protocols aligned with ectotherm respirometry methodologies for minimizing handling stress and ensuring thermal consistency. (iv) Detection of plasmid expression in newt tissues Muscle and liver tissues were harvested from newts after 28 days of culture for DNA/RNA extraction. cDNA synthesis followed the protocol described in Section 2.4. The primer pair RT70-F1 / IRG-R1 were used to detect pIRES2-CoHsp70 , while IRG-F1 / IRG-R1 amplified pIRES2-EGFP (Table 1 ). Amplification products were electrophoresed on 2% agarose gels using SYBR Safe DNA Gel Stain (Thermo Fisher, Waltham, United States), confirming target-specific bands. Data analyses The expression levels of CoHsp70 were analyzed using the 2 −ΔΔCT method, with relative mRNA levels expressed as mean ± SE [ 35 ]. Chi-square test was performed using Graphpad Prism 9.5 software to assess the differences in mortality. SMR in newts was quantified via closed-chamber respirometry with ExpeData software (Sable Systems International), applying automated MACRO routines to exclude activity-associated oxygen consumption. REE (kcal g⁻¹ h⁻¹) was calculated using the Weir equation [ 70 ]: REE = 3.941 × V O₂ + 1.106 × V CO₂ , where V O₂ and V CO₂ represent mass-specific oxygen and carbon dioxide exchange rates, respectively. Within-subject effect tests were performed using repeated measures ANOVA in SPSS 26 software ( α = 0.05). Significant differences among treatment groups were determined using Duncan's multiple range test in SPSS 26 software ( p < 0.05). Results Sequence characterisation of CoHsp70 The ORF sequence of CoHsp70 comprises 1,941 nucleotides encoding a 646-residue polypeptide with a predicted molecular mass of 71.05 kDa (Fig. S1 A and B). Amino acid composition analysis revealed alanine (8.2%) and lysine (8.0%) as predominant residues (Fig. 2 A). Computational analysis using ExPASy identified CoHsp70 as a hydrophilic acidic protein ( pI 5.52) with high structural stability (stability index 33.48), exhibiting an aliphatic index of 84.24 and average hydrophilicity of − 0.431 (Fig. 2 B). Secondary structure prediction via SOPMA demonstrated α-helices (42.41%) as the dominant conformation, followed by random coils (39.01%) and extended strands (18.58%) (Fig. S1 C). Three conserved HSP70 family signatures were identified through ProSite analysis: signature 1 (11–18 aa, IDLGTTYS), signature 2 (200–213 aa, IFDLGGGTFDVSIL), and signature 3 (337–351 aa, VVLVGGSTRIPKIQK) (Fig. S1 B). Domain architecture analysis revealed an actin-like ATPase domain spanning residues 7–189 and 194–385, a peptide-binding domain (388–546 aa), and a C-terminal subdomain (541–620 aa), with tertiary structural modeling confirming these functional regions (Fig. 3 ). Phylogenetic reconstruction using NCBI BLAST identified > 80% sequence identity across six phyla, demonstrating CoHSP70 evolutionary conservation. Phylogenetic analysis (Fig. S2) revealed CoHsp70 clustered within the amphibian clade, showing closest homology to Pleurodeles waltl (Amphibia). Unexpected proximity to Osteichthyes sequences may reflect conserved stress-response mechanisms across aquatic vertebrates. Quantitative reverse transcription-PCR (qRT-PCR) analysis of CoHsp70 expression across eight tissues revealed a distinct hierarchical pattern when normalized to hepatic expression levels (Fig. 4 ). Adipose tissue exhibited the highest basal expression, with CoHsp70 transcript abundance measuring 9.4-times that of the liver reference value. Pulmonary expression ranked second at 5.7-fold relative to liver, followed by gastric (3.5-fold) and renal (3.1-fold) tissues. Notably, muscular CoHsp70 levels closely mirrored hepatic baselines (1.1-fold), while intestinal expression demonstrated a marked reduction, registering only 10% of the hepatic reference value. This tissue-specific hierarchy (adipose > lung > stomach > kidney > muscle ≈ liver > intestine) was observed under physiological steady-state conditions. Expression of CoHsp70 in response to temperature change Quantitative analysis of hepatic CoHsp70 transcript levels under thermal stress demonstrated temperature-specific regulatory patterns (Fig. 5 ). Newts exposed to 4°C exhibited rapid transcriptional suppression (Fig. 5 A), with CoHsp70 expression declining to 10% of control levels (18°C) within 8 h. Partial recovery occurred at 24 h (25% of baseline), followed by stabilization at this reduced expression plateau through 96 h ( F 5, 30 = 160.0, p < 0.0001). In contrast, acute 32°C challenge triggered rapid transcriptional activation (Fig. 5 B), achieving peak induction (3.15-fold vs . control) at 2 h before returning to baseline by 8 h. Sustained hyperthermia beyond this phase maintained transcript levels near control conditions ( F 5, 30 = 177.4, p < 0.0001). CoHsp70 overexpression in tissues pIRES2-EGFP is a eukaryotic expression vector carrying CoHsp70 for overexpression in newts. The presence and expression of vectors pIRES2-EGFP and pIRES2-CoHsp70 in tissues were verified at both DNA and mRNA levels by PCR. In the gel image, clear electrophoresis bands of both plasmids were observed under high temperature and low temperature conditions, and the band sizes were accurate (Fig. 6 C and D). This indicates that both the empty vector and the recombinant plasmid are present in the liver and muscles of the newts and undergo normal transcription and translation. CoHsp70 enhances newt survival under heat stress​ Survival analysis of newts subjected to thermal extremes revealed plasmid-dependent viability patterns (Fig. 7 ). Following intramuscular injection with either pIRES2-EGFP ( n = 20) or pIRES2-CoHsp70 ( n = 20), newts were acclimated to thermal challenges (36°C vs . 2°C) over 10 days. Under hyper (36°C), the pIRES2-CoHsp70 cohort exhibited 40% survival, significantly surpassing the 10% viability in pIRES2-EGFP -injected counterparts ( df = 1, χ 2 = 5.562 > 5.024, p < 0.03). Mortality in the pIRES2-EGFP group commenced at 72 h post-induction, escalating linearly through day 10. In contrast, hypothermia (2°C) elicited 100% survival in both groups, demonstrating temperature-specific plasmid effects. CoHsp70 modulates temperature-dependent metabolism The repeated-measures ANOVA (Table 2 ) indicated no significant effects of Time ( F 4, 348 = 1.438, p = 0.227 > 0.05, partial η² = 0.016), Temperature ( F 2, 87 = 0.203, p = 0.816 > 0.05, partial η² = 0.005), or Time×Temperature interaction ( F 8, 348 = 0.322, p = 0.944 > 0.05, partial η² = 0.007) on body mass trajectories. Prior to thermal acclimation under standard 18°C conditions, newts injected with pIRES2-CoHsp70 or pIRES2-EGFP showed no significant differences in SMR or REE at Day 0 ( p > 0.05; Fig. 8 A and B). Following temperature acclimation (4°C, 18°C, 32°C), distinct thermal response patterns emerged (Fig. 8 A and B, Fig. 9 A and B). At 32°C, both SMR and REE measurements consistently exceeded those at 18°C and 4°C throughout the 28-day period, peaking on day 14 before gradual decline while maintaining elevated levels compared to lower temperatures. Temperature-dependent plasmid effects became apparent from day 14 onward across all thermal regimes, with pIRES2-CoHsp70 -injected newts demonstrating significantly lower metabolic parameters than pIRES2-EGFP controls. Specifically, at 4°C, delayed divergence emerged on day 21, accompanied by progressive metabolic decline from days 7–28. At day 21 under 4°C, pIRES2-CoHsp70 -injected newts exhibited significantly reduced metabolic rates compared to pIRES2-EGFP controls, SMR and REE reaching 75.7% and 76.5% of control values, respectively ( p < 0.05). In 18°C and 32 ℃ conditions, stable baseline metabolic levels contrasted with plasmid-specific differences from day 14 onward. At day 14 under 18°C, pIRES2-CoHsp70 -injected newts showed SMR at 96.1% and REE at 95.9% of pIRES2-EGFP controls ( p < 0.05). At 32°C, SMR and REE values were 95.9% and 96.0%, respectively, compared to controls ( p < 0.05). The reduced SMR and REE in pIRES2-CoHsp70 -injected newts suggest enhanced proteostatic efficiency, which lowersATP expenditure for protein refolding under stress conditions. Table 2 Within-agent effect test. Source Type III Sum of Squares Mean Square F Statistic ( p -value)​ Partial η² Time 0.692 0.198 F 4, 348 = 1.438, p = 0.227 0.016 Temperature 0.132 0.066 F 2, 87 = 0.203, p = 0.816 0.005 Time × Temperature 0.310 0.044 F 8, 348 = 0.322, p = 0.944 0.007 *All analyses utilized Type III sum of squares ( α = 0.05) . CoHsp70 attenuates thermal stress-induced oxygen demand As detailed in Table 2 , the repeated-measures ANOVA correction revealed no statistically significant impact of temporal variation, thermal exposure or their interaction on body mass trajectories in newts under the implemented experimental paradigm. Prior to thermal acclimation under standard 18°C conditions (Day 0), newts injected with pIRES2-CoHsp70 or pIRES2-EGFP plasmids exhibited no significant differences in OCR ( p > 0.05; Fig. 8 C). Thermal acclimation to 4°C, 18°C, and 32°C induced distinct OCR response patterns over the 28-day experimental period (Fig. 8 C, 9 C). In contrast to SMR and REE, OCR measurements at 32°C consistently exceeded values at lower temperatures, peaking on Day 7 followed by a gradual decline. Plasmid-specific OCR divergence emerged from day 14, with pIRES2-CoHsp70 -injected newts exhibiting 94.7% of pIRES2-EGFP control values ( p < 0.05), demonstrating sustained OCR suppression. At 4°C, plasmid-mediated differentiation became apparent by day 21, pIRES2-CoHsp70 groups showing 87.9% of control OCR levels ( p < 0.05), alongside progressive attenuation from days 7–28. Despite inter-plasmid differences from day 14 in the 18°C group, baseline OCR stability persisted, pIRES2-CoHsp70 reaching 92.4% of control values ( p < 0.05), emphasizing temperature-dependent modulation of oxygen metabolism. Discussion HSP70 is one of the most evolutionarily conserved and widely studied members of the heat shock protein family [ 36 – 38 ]. It is expressed in both prokaryotes and eukaryotes, with amino acid sequences exhibiting high similarity across diverse biological sources [ 23 , 39 – 42 ]. For instance, goat HSP70-1 shares 96–99% sequence similarity with sheep (partial), cattle, and buffalo, while amino acid-level similarity ranges from 95–100% [ 43 ]. Similarly, murine and human HSP70 display 95% amino acid homology and 91% nucleotide homology [ 44 ], suggesting conserved biological roles across species. Although multiple Hsp70 family members have been identified in animals and plants, amphibian studies remain limited to a few model species, including Xenopus laevis , X. tropicalis , and Rana lessonae [ 25 , 27 , 45 ]. Our study addresses this knowledge gap through successful cloning and functional characterization of CoHsp70 from C. orientalis . These findings not only establish an amphibian-specific framework for molecular chaperone research but also provide crucial evolutionary insights into stress adaptation mechanisms across tetrapod lineages. Structural basis of CoHsp70 functional plasticity Sequence analysis confirms that CoHsp70 exhibits the canonical eukaryotic HSP70 architecture, characterized by three signature motifs and three conserved functional domains. The N-terminal region contains two highly conserved sequences (41 kDa) encompassing the ATPase active site, which drives ATP hydrolysis to facilitate substrate protein folding and translocation. Adjacent to this lies a conserved 17.4 kDa substrate-binding domain that recognizes hydrophobic client peptides. The C-terminal region (9.4 kDa) displays structural variability and terminates with the cytoplasmic-specific EEVD motif, a hallmark of cytosolic HSP70 isoforms that mediates co-chaperone interactions [ 46 – 48 , 68 ]. Phylogenetic comparisons reveal striking conservation of these structural features across diverse taxa, including Macrobrachium rosenbergii , Pleurodeles waltl , and Xenopus laevis [ 25 , 49 , 67 ], underscoring the evolutionary constraint on HSP70 core machinery. Notably, the acidic isoelectric point ( pI 5.52) of CoHsp70 closely resembles that of mammalian HSPA1A ( pI 5.3–5.8). However, its lower hydrophobicity (GRAVY: – 0.431) compared to human HSPA8 (GRAVY: – 0.38) suggests a potential mechanism for stabilizing higher-molecular-weight client protein complexes through enhanced surface charge distribution [ 50 ]. These structural features collectively underpin the functional plasticity of CoHsp70 in adapting to amphibian ecological pressures. Adipose Hsp70 drives stress adaptation This study reveals that baseline expression of CoHsp70 in adipose tissue (9.4-fold higher than hepatic levels) challenges the liver/spleen-centric paradigm of Hsp70 expression [ 51 , 52 ]. This phenomenon likely reflects newts' unique reliance on adipose tissue as an energy reservoir during hibernation [ 53 ], where elevated free fatty acids in adipocytes induce endoplasmic reticulum stress (ERS) and mitochondrial lipid peroxidation [ 54 ]. Sustained CoHsp70 overexpression may maintain adipocyte homeostasis via dual mechanisms: (1) collaborative repair of misfolded fatty acid synthases with HSP40 co-chaperones [ 55 ], and (2) suppression of IRE1α-XBP1 signaling to block ERS-driven lipolysis [ 56 ]. The comparatively low intestinal CoHsp70 expression (10% of hepatic levels) suggests a risk-aversion strategy, limiting misfolded protein accumulation and premature UPR activation [ 57 ]. This tissue hierarchy (adipose > lung > stomach > kidney) implies spatial Hsp70 reprogramming balances organ-specific stress defense with metabolic economy. Thermal bidirectionality of Hsp70 stress adaptation CoHsp70 exhibits marked asymmetric dynamics in response to thermal challenges: acute heat stress (32°C) triggers rapid yet self-limited transcriptional activation (peaking at 2 h and returning to baseline by 8 h), while chronic cold exposure (4°C) causes progressive and irreversible transcriptional suppression (25% baseline retention at 96 h). This divergence likely stems from hierarchical temperature-sensing pathways — heat stress directly activates the Hsp70 promoter via HSF1 trimerization [ 58 ], whereas cold stress suppresses mTORC1-S6K signaling to reduce translational elongation efficiency, inducing negative feedback [ 59 ]. Partial CoHsp70 recovery at 24 h of cold exposure may involve cold shock proteins [ 60 ]. Functional assays reveal that CoHsp70 overexpression enhances hyperthermic survival (36°C; 40% vs . 10% controls) but not cold survival (2°C). This temperature-dependent survival trade-off suggests distinct mechanisms: under heat stress, CoHsp70 stabilizes thermosensitive kinases to sustain energy sensing [ 61 ], whereas under cold stress, its ATP-dependent activity exacerbates energy deficits, driving metabolic suppression [ 62 ]. These findings underscore that Hsp70 adaptive value is tightly modulated by environmental thermal amplitude. Hsp70 optimizes energy budgets under stress While canonical models posit that HSP70 overexpression exacerbates energy burdens [ 63 ], this study demonstrates CoHsp70 overexpression reduces SMR and REE under hyperthermia (32°C). These effects may occur through reduced energy waste in protein repair and improved mitochondrial energy efficiency. This paradox aligns with the chaperone efficiency hypothesis: CoHsp70 enhances substrate recognition precision (e.g., via strengthened Hsp40 co-chaperone affinity) to minimize ATP expenditure on futile folding cycles [ 64 ], while concurrently suppressing energy-draining non-selective autophagy by disrupting p62-LC3 interactions [ 65 ]. In cold-adapted cohorts, CoHsp70 -mediated declines in OCR likely involve stabilization of mitochondrial respiratory assemblies (e.g., I-III2-IVn) [ 66 ], which optimize electron transfer efficiency. These findings redefine Hsp70 metabolic role — not merely as a stress defense executor but as a systemic energy budget optimizer, reconciling proteostatic demands with bioenergetic constraints under thermal extremes. Conclusion This study delineates the structural and functional attributes of CoHsp70 in Cynops orientalis , revealing its conserved HSP70 architecture — three signature motifs (IDLGTTYS, IFDLGGGTFDVSIL, VVLVGGSTRIPKIQK) and domains (ATPase, substrate-binding, C-terminal EEVD) — with > 80% sequence identity to amphibian homologs such as Pleurodeles waltl. Tissue-specific profiling identified adipose tissue as the primary site of CoHsp70 expression (9.4-fold higher than liver), contrasting sharply with suppressed intestinal levels (10% of hepatic baseline). Thermal challenges induced bidirectional transcriptional dynamics: rapid but transient activation under acute heat stress (32°C, peaking at 2 h) versus progressive suppression during chronic cold exposure (4°C, declining to 10% baseline within 8 h). Plasmid-driven CoHsp70 overexpression enhanced hyperthermic survival (40% vs . 10% in at 36°C) while reducing standard metabolic rate (SMR), resting energy expenditure (REE), and oxygen consumption (OCR), corroborating its role in energy-efficient stress adaptation. Successful validation of tissue-specific plasmid expression confirmed the functional relevance of these findings. Collectively, CoHsp70 emerges as a molecular linchpin balancing proteostatic resilience with metabolic economy in amphibian thermal adaptation. Abbreviations ATPase – Adenosine triphosphatase CoHsp70 – Cynops orientalis Heat shock protein 70 DO – Dissolved oxygen DO₀ – Initial dissolved oxygen DOₜ – Final dissolved oxygen after time t EEVD – Glutamate-glutamate-valine-aspartate (C-terminal motif of cytosolic HSP70) EGFP – Enhanced green fluorescent protein ERS – Endoplasmic reticulum stress GAPDH – Glyceraldehyde-3-phosphate dehydrogenase (housekeeping gene) Hsc70 – Heat shock cognate 70 (constitutive isoform) HSP – Heat shock protein HSP40 – Heat shock protein 40 (co-chaperone) HSP70 – Heat shock protein 70 HSP90 – Heat shock protein 90 HSPA1A – Heat shock protein family A member 1A (inducible Hsp70) HSPA8 – Heat shock protein family A member 8 (constitutive Hsc70) HSF1 – Heat shock factor 1 IRE1α – Inositol-requiring enzyme 1α (ERS sensor) mTORC1 – Mechanistic target of rapamycin complex 1 OCR – Oxygen consumption rate ORF – Open reading frame pIRES2 – Plasmid with internal ribosome entry site PBS – Phosphate-Buffered Saline qRT-PCR – Quantitative real-time reverse transcription polymerase chain reaction REE – Resting energy expenditure S6K – Ribosomal protein S6 kinase SMR – Standard metabolic rate sHSPs – Small heat shock proteins UPR – Unfolded protein response VO 2 – Oxygen consumption rate VCO 2 – Carbon dioxide production rate XBP1 – X-box binding protein 1 (UPR transcription factor) Declarations Acknowledgments The authors extend their gratitude to all members of the L.H.L. research group for their insightful discussions, dedicated animal care, and technical support during experimental procedures. Author contributions J.R.L. contributed to writing the original draft, methodology, data curation, formal analysis, and validation. Y.Q.T. reviewed and edited the manuscript and developed the software. Z.Y.F. implemented the software and conducted formal analysis. Z.W.W., H.Y.Z., and S.C.G. performed investigations and created visualizations. L.H.L. acquired funding, managed the project, and provided resources. W.D. conceptualized the study, designed the methodology, and supervised the research. All authors approved the final version for publication and agree to be accountable for the work. Funding This work was supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LY23C030003). Data availability The open reading frame sequence of CoHsp70 has been deposited in GenBank under accession number PQ323562. Ethics and consent to participate Experimental animals ( Cynops orientalis , n=300) were obtained from Shengsheng Hatchery (Hangzhou, China) with informed consent for the study. All experimental procedures involving animals were conducted in strict compliance with the ARRIVE guidelines and the National Research Council's Guide for the Care and Use of Laboratory Animals (China) . The protocol was reviewed and approved by the Animal Research Ethical Committee of Hangzhou Normal University (Approval Number: 2023049). All surgeries were performed under anesthesia with 0.1% Tricaine methanesulfonate (MS-222, Sigma-Aldrich, USA), and every effort was made to minimize suffering. References Parmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 2003; 421 (6918), 37–42. (doi: 10.1038/nature01286) Alan Pounds J, Bustamante MR, Coloma LA, Consuegra JA, Fogden MPL, Foster PN, La Marca E, Masters KL, Merino-Viteri A, Puschendorf R, et al. Widespread amphibian extinctions from epidemic disease driven by global warming. Nature. 2006; 439 (7073), 161–167. (doi: 10.1038/nature04246) Bickford D, Lohman DJ, Sodhi NS, Ng PKL, Meier R, Winker K, Ingram KK, Das I. Cryptic species as a window on diversity and conservation. Trends Ecol. Evol. 2007; 22 (3), 148–155. (doi: 10.1016/j.tree.2006.11.004) Walther GR, Post E, Convey P, Menzel A, Parmesan C, Beebee TJC, Fromentin JM, Guldberg OH, Bairlein F. Ecological responses to recent climate change. Nature. 2002; 416, 389–395. (doi: 10.1038/416389a) Abdelnour SA, Abd El-Hack ME, Khafaga AF, Arif M, Taha AE, Noreldin AE. Stress biomarkers and proteomics alteration to thermal stress in ruminants: A review. J. Therm. Biol. 2019; 79, 120–134. (doi: 10.1016/j.jtherbio.2018.12.013) Feder ME, Krebs RA. Ecological and evolutionary physiology of heat shock proteins and the stress response in Drosophila: Complementary insights from genetic engineering and natural variation. EXS. 1997; 83, 155–173. (doi: 10.1007/978-3-0348-8882-0_9) Sleadd IM, Lee M, Hassumani DO, Stecyk TMA, Zeitz OK, Buckley BA. Sub-lethal heat stress causes apoptosis in an Antarctic fish that lacks an inducible heat shock response. J. Therm. Biol. 2014; 44, 119-125. (doi: 10.1016/j.jtherbio.2014.06.007) Cooper RD, Shaffer HB. Allele‐specific expression and gene regulation help explain transgressive thermal tolerance in non‐native hybrids of the endangered California tiger salamander ( Ambystoma californiense ). Mol. Ecol. 2021; 30 (4), 987–1004. (doi: 10.1111/mec.15779) Li Y, Cohen JM, Rohr JR. Review and synthesis of the effects of climate change on amphibians. Integr. Zool. 2013; 8 (2), 145–161. (doi: 10.1111/1749-4877.12001) Pottier P, Lin HY, Oh RRY, Pollo P, Rivera-Villanueva AN, Valdebenito JO, Yang Y, Amano T, Burke S, Drobniak SM, et al. A comprehensive database of amphibian heat tolerance. Sci. Data. 2022; 9 (1), 600. (doi: 10.1038/s41597-022-01704-9) Ruthsatz K, Dausmann KH, Peck MA, Glos J. Thermal tolerance and acclimation capacity in the European common frog ( Rana temporaria ) change throughout ontogeny. J. Exp. Zool. A Ecol. Integr. Physiol. 2022; 337 (5), 477–490. (doi: 10.1002/jez.2582) Guo K, Yuan S, Wang H, Zhong J, Wu Y, Chen W, Hu C, Chang Q. Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt Cynops orientalis under climate change. Ecol. Evol. 2021; 11 (15), 10147–10154. (doi: 10.1002/ece3.7822) Weng L, Wong WP, Chew SF, Ip YK. Excretory nitrogen metabolism in the Chinese fire-belly newt Cynops orientalis in water, on land, or in high concentrations of environmental ammonia. J. Comp. Physiol. B Biochem. Syst. Environ. Physiol. 2004; 174 (2), 113–120. (doi: 10.1007/s00360-003-0395-z) Ando N, Barquera B, Bartlett DH, Boyd E, Burnim AA, Byer AS, Colman D, Gillilan RE, Gruebele M, Makhatadze G, et al. The Molecular Basis for Life in Extreme Environments. Annual review of biophysics. 2021; 50, 343–372. (doi: 10.1146/annurev-biophys-100120-072804) Biscotti MA, Carducci F, Barucca M, Gerdol M, Pallavicini A, Schartl M, Canapa A, Adolfi MC, The transcriptome of the newt Cynops orientalis provides new insights into evolution and function of sexual gene networks in sarcopterygians. Sci. Rep. 2020; 10 (1), 5445. (doi: 10.1038/s41598-020-62408-x) Mebs D, Yotsu-Yamashita M. Acquiring toxicity of a newt, Cynops orientalis . Toxicon. 2021; 198, 32–35. (doi: 10.1016/j.toxicon.2021.04.025) Oborová V, Šugerková M, Gvoždík L. Sensitivity of amphibian embryos to timing and magnitude of present and future thermal extremes. J. Exp. Zool. A Ecol. Integr. Physiol. 2024; 341 (4), 377–388. (doi: 10.1002/jez.2791) Von May R, Catenazzi A, Santa-Cruz R, Gutierrez AS, Moritz C, Rabosky DL. Thermal physiological traits in tropical lowland amphibians: Vulnerability to climate warming and cooling. PLoS ONE. 2019; 14 (8), e0219759. (doi: 10.1371/journal.pone.0219759) Lévesque M, Guimond JC, Pilote M, Leclerc S, Moldovan F, Roy S. Expression of heat‐shock protein 70 during limb development and regeneration in the axolotl. Dev. Dyn. 2005; 233 (4), 1525–1534. (doi: 10.1002/dvdy.20458) Ninomiya H, Ohgami N, Oshino R, Kato M, Ohgami K, Li X, Shen D, Iida M, Yajima I, Angelidis CE, et al. Increased expression level of Hsp70 in the inner ears of mice by exposure to low frequency noise. Hear. Res. 2018; 363, 49-54. (doi: 10.1016/j.heares.2018.02.006) Qian SB, McDonough H, Boellmann F, Cyr DM, Patterson C. CHIP-mediated stress recovery by sequential ubiquitination of substrates and Hsp70 . Nature. 2006; 440 (7083), 551–555. (doi: 10.1038/nature04600) Hagymasi AT, Dempsey JP, Srivastava PK. Heat‐Shock Proteins. Curr. Protoc. 2022; 2 (11), e592. (doi: 10.1002/cpz1.592) Mayer MP, Bukau B. Hsp70 chaperones: Cellular functions and molecular mechanism. Cell. Mol. Life Sci. 2005; 62 (6), 670–684. (doi: 10.1007/s00018-004-4464-6) Rosenzweig R, Nillegoda NB, Mayer MP, Bukau B. The Hsp70 chaperone network. Mol. Cell Biol. 2019; 20 (11), 665–680. (doi: 10.1038/s41580-019-0133-3) Khan S, Heikkila JJ. Distinct patterns of HSP30 and HSP70 degradation in Xenopus laevis A6 cells recovering from thermal stress. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 2014; 168, 1–10. (doi: 10.1016/j.cbpa.2013.10.026) Nikinmaa M, Leveelahti L, Dahl E, Rissanen E, Rytkönen KT, Laurila A. Population origin, development and temperature of development affect the amounts of HSP70, HSP90 and the putative hypoxia-inducible factor in the tadpoles of the common frog Rana temporaria . J. Exp. Biol. 2008; 211 (Pt 12), 1999–2004. (doi:10.1242/jeb.016816) Simoncelli F, Morosi L, Di Rosa I, Pascolini R, Fagotti A. Molecular characterization and expression of a heat-shock cognate 70 (Hsc70) and a heat-shock protein 70 (Hsp70) cDNAs in Rana (Pelophylax) lessonae embryos. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 2010; 156 (4), 552–560. doi.org/10.1016/j.cbpa.2010.04.016) Blasco Redondo R. Resting energy expenditure; assessment methods and applications. Nutr. Hosp. 31 (Suppl 3), 2015; 245–254. (doi: 10.3305/nh.2015.31.sup3.8772) Bech C, Christiansen MT, Kvernland P, Nygård RM, Rypdal E, Sneltorp SK, Trondrud LM, Tvedten ØG. The standard metabolic rate of a land snail ( Cepaea hortensis ) is a repeatable trait and influences winter survival. Comp Biochem Physiol A Mol Integr Physiol. 2020; 249: 110773. (doi: 10.1016/j.cbpa.2020.110773) Ezgeta-Balić D, Rinaldi A, Peharda M, Prusina I, Montalto V, Niceta N, Sarà G. An energy budget for the subtidal bivalve Modiolus barbatus (Mollusca) at different temperatures. Mar. Environ. Res. 2011; 71 (1), 79–85. (doi: 10.1016/j.marenvres.2010.10.005) Chauhan R, Sharma AK. Speed-Energy-Efficiency Trade-off in Hsp70 Chaperone System. J. Phys. Chem. B. 2024; 128 (49), 12101–12113. (doi: 10.1021/acs.jpcb.4c06594) Felsenstein J. Confidence Limits on Phylogenies: An Approach Using the Bootstrap. Evolution. 1985; 39 (4), 783–791. (doi: 10.1111/j.1558-5646.1985.tb00420.x) Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 1987; 4 (4), 406–425. (doi: 10.1093/oxfordjournals.molbev.a040454) Tamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0. Mol. Biol. Evol. 2013; 30 (12), 2725–2729. (doi: 10.1093/molbev/mst197) Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001; 25 (4), 402–408. (doi: 10.1006/meth.2001.1262) De Maio A. Heat Shock Proteins: Facts, Thoughts, and Dreams. Shock. 1999; 11 (1), 1–12. (doi: 10.1097/00024382-199901000-00001) Junprung W, Norouzitallab P, De Vos S, Tassanakajon A, Nguyen Viet D, Van Stappen G, Bossier P. Sequence and expression analysis of HSP70 family genes in Artemia franciscana . Sci. Rep. 2019; 9 (1), 8391. (doi:10.1038/s41598-019-44884-y) Yu A, Li P, Tang T, Wang J, Chen Y, Liu L. Roles of Hsp70s in Stress Responses of Microorganisms, Plants, and Animals. Biomed. Res. Int. 2015; 2015, 510319. (doi: 10.1155/2015/510319) Cui Z, Liu Y, Luan W, Li Q, Wu D, Wang S. Molecular cloning and characterization of a heat shock protein 70 gene in swimming crab ( Portunus trituberculatus ). Fish Shellfish Immunol. 2010; 28 (1), 56–64. (doi: 10.1016/j.fsi.2009.09.018) Karlin S, Brocchieri L. Heat Shock Protein 70 Family: Multiple Sequence Comparisons, Function, and Evolution. J. Mol. Evol. 1998; 47 (5), 565–577. (doi: 10.1007/pl00006413) Tang T, Yu A, Li P, Yang H, Liu G, Liu L. Sequence analysis of the Hsp70 family in moss and evaluation of their functions in abiotic stress responses. Sci. Rep. 2016; 6, 33650. (doi: 10.1038/srep33650) Von Plehwe U, Berndt U, Conz C, Chiabudini M, Fitzke E, Sickmann A, Petersen A, Pfeifer D, Rospert S. The Hsp70 homolog Ssb is essential for glucose sensing via the SNF1 kinase network. Genes Dev. 2009; 23 (17), 2102–2115. (doi: 10.1101/gad.529409) Gade N, Mahapatra RK, Sonawane A, Singh VK, Doreswamy R, Saini M. Molecular Characterization of Heat Shock Protein 70-1 Gene of Goat ( Capra hircus ). Mol. Biol. Int. 2010; 2010, 108429. (doi: 10.4061/2010/108429) Hunt C, Calderwood S. Characterization and sequence of a mouse hsp70 gene and its expression in mouse cell lines. Gene. 1990; 87 (2), 199–204. (doi: 10.1016/0378-1119(90)90302-8) Klein SL, Strausberg RL, Wagner L, Pontius J, Clifton SW, Richardson P. Genetic and genomic tools for Xenopus research: The NIH Xenopus initiative. Dev. Dyn. 2002; 225 (4), 384–391. (doi: 10.1002/dvdy.10174) Boorstein W, Ziegelhoffer T, Craig E. Molecular evolution of the HSP70 multigene family. J. Mol. Evol. 1994; 38 (1), 1–17. (doi: 10.1007/BF00175490) Han YL, Hou CC, Du C, Zhu JQ. Molecular cloning and expression analysis of five heat shock protein 70 (HSP70) family members in Lateolabrax maculatus with Vibrio harveyi infection. Fish Shellfish Immun. 2017; 60, 299–310. (doi: 10.1016/j.fsi.2016.11.056) Onuoha SC, Coulstock ET, Grossmann JG, Jackson SE. Structural Studies on the Co-chaperone Hop and Its Complexes with Hsp90. J. Mol. Biol. 2008; 379 (4), 732–744. (doi: 10.1016/j.jmb.2008.02.013) Liu J, Yang WJ, Zhu XJ, Karouna Renier NK, Rao RK. Molecular cloning and expression of two HSP70 genes in the prawn, Macrobrachium rosenbergii . Cell Stress Chaperones. 2004; 9 (3), 313–323. (doi: 10.1379/csc-40r.1) Kiraga J, Mackiewicz P, Mackiewicz D, Kowalczuk M, Biecek P, Polak N, Smolarczyk K, Dudek MR, Cebrat S. The relationships between the isoelectric point and: length of proteins, taxonomy and ecology of organisms. BMC genomics. 2007; 8, 163. (doi: 10.1186/1471-2164-8-163) Rout PK, Kaushik R, Ramachandran N. Differential expression pattern of heat shock protein 70 gene in tissues and heat stress phenotypes in goats during peak heat stress period. Cell Stress Chaperones. 2016; 21 (4), 645–651. (doi: 10.1007/s12192-016-0689-1) Zhang C, Lu K, Wang J, qian Q, Yuan X, Pu C. Molecular cloning, expression HSP70 and its response to bacterial challenge and heat stress in Microptenus salmoides . Fish Physiol. Biochem. 2020; 46 (6), 2389–2402. (doi: 10.1007/s10695-020-00883-9) Costanzo JP. Overwintering adaptations and extreme freeze tolerance in a subarctic population of the wood frog, Rana sylvatica . J. Comp. Physiol. B. 2019; 189 (1), 1–15. (doi: 10.1007/s00360-018-1189-7) Ayala A, Muñoz MF, Argüelles S. Lipid peroxidation: production, metabolism, and signaling mechanisms of malondialdehyde and 4-hydroxy-2-nonenal. Oxidative medicine and cellular longevity. 2014; 2014, 360438. (doi: 10.1155/2014/360438) Alderson TR, Kim JH, Markley JL. Dynamical Structures of Hsp70 and Hsp70-Hsp40 Complexes. Structure . 2016; 24 (7): 1014–1030. (doi: 10.1016/j.str.2016.05.011) Lin TT, Qu J, Wang CY, Yang X, Hu F, Hu L, Wu XF, Jiang CY, Liu WT, Han Y. Rescue of HSP70 in Spinal Neurons Alleviates Opioids-Induced Hyperalgesia via the Suppression of Endoplasmic Reticulum Stress in Rodents. Front. Cell Dev. Biol. 2020; 8, 269. (doi: 10.3389/fcell.2020.00269) Roybal CN, Marmorstein LY, Vander Jagt DL, Abcouwer SF. Aberrant accumulation of fibulin-3 in the endoplasmic reticulum leads to activation of the unfolded protein response and VEGF expression. Invest. Ophthalmol. Vis. Sci. 2005; 46 (11), 3973–3979. (doi: 10.1167/iovs.05-0070) Pincus D. Regulation of Hsf1 and the Heat Shock Response. Advances in experimental medicine and biology. 2020; 1243, 41–50. (doi: 10.1007/978-3-030-40204-4_3) Ye T, Yan Z, Chen C, Wang D, Wang A, Li T, Yang B, Ding X, Shen C. Lactoferrin attenuates cardiac fibrosis and cardiac remodeling after myocardial infarction via inhibiting mTORC1/S6K signaling pathway. Theranostics. 2023; 13 (10), 3419–3433. (doi: 10.7150/thno.85361) Corre M, Lebreton A. Regulation of cold-inducible RNA-binding protein (CIRBP) in response to cellular stresses. Biochimie. 2024; 217, 3–9. (doi: 10.1016/j.biochi.2023.04.003) Kaya ST. Effects of diazoxide on streptozotocin induced β cell damage via HSP70/HSP90/TLR4/AMPK signaling pathways. Biotech. Histochem. 2023; 98 (3), 210–219. (doi: 10.1080/10520295.2023.2168757) Trcka F, Durech M, Vankova P, Chmelik J, Martinkova V, Hausner J, Kadek A, Marcoux J, Klumpler T, Vojtesek B, et al. Human Stress-inducible Hsp70 Has a High Propensity to Form ATP-dependent Antiparallel Dimers That Are Differentially Regulated by Cochaperone Binding. Mol. Cell. Proteomics. 2019; 18 (2), 320–337. (doi: 10.1074/mcp.RA118.001044) Boudesco C, Cause S, Jego G, Garrido C. Hsp70: A Cancer Target Inside and Outside the Cell. Methods in molecular biology (Clifton, N.J.). 2018; 1709, 371–396. (doi: 10.1007/978-1-4939-7477-1_27) Kabakov AE, Budagova KR, Latchman DS, Kampinga HH. Stressful preconditioning and HSP70 overexpression attenuate proteotoxicity of cellular ATP depletion. Am. J. Physiol. Cell Physiol. 2002; 283 (2), C521–C534. (doi: 10.1152/ajpcell.00503.2001) Kong E, Li Y, Geng X, Wang J, He Y, Feng X. Ischemic preconditioning attenuates endoplasmic reticulum stress-dependent apoptosis of hepatocytes by regulating autophagy in hepatic ischemia-reperfusion injury. Int. Immunopharmacol. 2023; 122, 110637. (doi: 10.1016/j.intimp.2023.110637) Ikeda K, Shiba S, Horie-Inoue K, Shimokata K, Inoue S. A stabilizing factor for mitochondrial respiratory supercomplex assembly regulates energy metabolism in muscle. Nat. Commun. 2013; 4, 2147. (doi: 10.1038/ncomms3147) Avdonin PP, Markitantova YV, Poplinskaya VA, Grigoryan EN. Determination of mRNA-transcripts and heat shock proteins HSP70 and HSP90 in retina of the adult Spanish Ribbed Newt Pleurodeles waltl . Biol Bull Russ Acad Sci. 2013; 40, 343–350. (doi:10.1134/S106235901304002X) Li HB, Du YZ. Molecular cloning and characterization of an Hsp90/70 organizing protein gene from Frankliniella occidentalis (Insecta: Thysanoptera, Thripidae). Gene. 2013; 520 (2), 148–155. (doi: 10.1016/j.gene.2013.02.026) Walcott SE, Heikkila JJ. Celastrol can inhibit proteasome activity and upregulate the expression of heat shock protein genes, hsp30 and hsp70 , in Xenopus laevis A6 cells. Comp. Biochem. Physiol. A Mol. Integr. Physiol. 2010; 156 (2), 285–293. (doi: 10.1016/j.cbpa.2010.02.015) Weir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J. Physiol. 1949; 109 (1-2), 1–9. (doi: 10.1113/jphysiol.1949.sp004363) Additional Declarations No competing interests reported. Supplementary Files Fig.S.docx Cite Share Download PDF Status: Published Journal Publication published 05 Jan, 2026 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 06 Nov, 2025 Reviews received at journal 14 Sep, 2025 Reviews received at journal 08 Sep, 2025 Reviewers agreed at journal 07 Sep, 2025 Reviewers agreed at journal 03 Sep, 2025 Reviews received at journal 31 Aug, 2025 Reviewers agreed at journal 17 Aug, 2025 Reviewers agreed at journal 15 Aug, 2025 Reviewers invited by journal 11 Aug, 2025 Editor invited by journal 30 Jul, 2025 Editor assigned by journal 07 Jul, 2025 Submission checks completed at journal 05 Jul, 2025 First submitted to journal 05 Jul, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6990504","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502205093,"identity":"b46a0fc2-b42e-4ab0-9efc-9d016fdf3575","order_by":0,"name":"Junrong Liu","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Junrong","middleName":"","lastName":"Liu","suffix":""},{"id":502205094,"identity":"9094b109-23d2-4e8e-911b-894cd41f3377","order_by":1,"name":"Yanqing Tang","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Yanqing","middleName":"","lastName":"Tang","suffix":""},{"id":502205095,"identity":"2bf39dc5-6f1e-4f15-bc09-4215c135dd5a","order_by":2,"name":"Zhengyuan Fang","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Zhengyuan","middleName":"","lastName":"Fang","suffix":""},{"id":502205096,"identity":"799f6deb-0d71-4c42-87c3-c8db7bdfe34a","order_by":3,"name":"Zhiwen Wang","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Zhiwen","middleName":"","lastName":"Wang","suffix":""},{"id":502205097,"identity":"855d3e7d-ec05-4038-93c7-c4806d2e77e5","order_by":4,"name":"Haoyuan Zhang","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Haoyuan","middleName":"","lastName":"Zhang","suffix":""},{"id":502205098,"identity":"6a4d8d8a-39d0-4d45-ab76-ef21afb7c6ee","order_by":5,"name":"Songchen Guo","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Songchen","middleName":"","lastName":"Guo","suffix":""},{"id":502205099,"identity":"8ec2b00b-af9c-499b-85f8-f77ed11ae801","order_by":6,"name":"Longhui Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYBACPmYGxsMMFQcgPB5itLAxMzAcZjhDkhYgPszYRpIWdt4Dhwvn3bE3l0hgfPC2jUHenLDD+BIOz9z2jNlyRgKz4dw2BsOdDQS18Bgc5t12mM3gRgKbNG8bQ4LBAaK0zDnMA9TC/psELQ2HJUC2MBOvhefYYQODMw+bJeeckzDcQEgLP/8Zw8c8NYftDY4nH/zwpsxGnqAtSICxAUhIEK9+FIyCUTAKRgFuAAC4Pznx7Z3JzAAAAABJRU5ErkJggg==","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":true,"prefix":"","firstName":"Longhui","middleName":"","lastName":"Lin","suffix":""},{"id":502205102,"identity":"edcf09a6-5b62-4df9-b92c-7828fbde8efb","order_by":7,"name":"Wei Dang","email":"","orcid":"","institution":"Hangzhou Normal University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Dang","suffix":""}],"badges":[],"createdAt":"2025-06-27 10:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6990504/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6990504/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-025-12501-0","type":"published","date":"2026-01-05T15:57:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":89390673,"identity":"c2b397f0-e7b6-4e55-92b2-326b7c81550b","added_by":"auto","created_at":"2025-08-19 12:57:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116344,"visible":true,"origin":"","legend":"\u003cp\u003eMonitoring of culture temperature. (A) Monitoring temperature for newts injected with plasmids in two incubators (high: 36 °C; low: 2 °C). (B) Monitoring temperature for newts injected with plasmids in three incubators (high: 32 °C; room:18 °C; low: 4 °C).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/5389710a9538b8d9afbb6cc4.png"},{"id":89390674,"identity":"c4f5decb-9e76-485a-8cb5-41f592ea735f","added_by":"auto","created_at":"2025-08-19 12:57:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":192658,"visible":true,"origin":"","legend":"\u003cp\u003eStructural analysis of CoHSP70. (A) Amino acid composition of CoHSP70 ordered by molecular size. (B) Hydrophobicity plot of CoHSP70. Positive and negative values indicate hydrophobic and hydrophilic regions, respectively.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/c96fb9a9582f5967bc3841c9.png"},{"id":89391213,"identity":"8e8a5ade-a578-40a1-96ce-fcf657345ca5","added_by":"auto","created_at":"2025-08-19 13:05:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":327682,"visible":true,"origin":"","legend":"\u003cp\u003eThree-dimensional structure of CoHSP70 deduced by using SWISS-MODEL.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/be8ba3b86ad11c40f3ecd0c0.png"},{"id":89391212,"identity":"dee2969e-8d9e-4b1e-a73b-9321090b714e","added_by":"auto","created_at":"2025-08-19 13:05:18","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":39678,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of \u003cem\u003eCoHsp70\u003c/em\u003e in different tissues or organs of newts detected by quantitative real time reverse transcriptase PCR . \u003cem\u003eCoHsp70\u003c/em\u003e expression levels in heart, kidney, stomach, lung, fat, muscle, intestine are normalized to that of GAPDH mRNA. The normalized \u003cstrong\u003eCoHsp70\u003c/strong\u003e mRNA level in liver was set as 1. The vertical bars represent the means ±SE (n = 6).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/4769e203b7682f1688bfe1bc.png"},{"id":89390685,"identity":"5801459f-3df4-43b2-b6bc-78e6847a8337","added_by":"auto","created_at":"2025-08-19 12:57:19","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":65031,"visible":true,"origin":"","legend":"\u003cp\u003eExpression of \u003cem\u003eCoHsp70\u003c/em\u003e in newts under different incubation temperatures determined by quantitative real time reverse transcriptase PCR at various times. The mRNA level of \u003cem\u003eCoHsp70\u003c/em\u003e was normalized to that of GADPH. The vertical bars represent the means ± SE (\u003cem\u003en\u003c/em\u003e = 6). Different letters indicate significant differences (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, a \u0026gt; b \u0026gt; c). (A)\u003cem\u003e CoHsp70 \u003c/em\u003eexpression levels in newts incubated at 4 °C for different times. (B) \u003cem\u003eCoHsp70\u003c/em\u003e expression levels in newts incubated at 32 °C for different times.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/4224b02245e9d19e1b70fcc7.png"},{"id":89390686,"identity":"faa75beb-2c56-4682-ab27-d2f6db179f24","added_by":"auto","created_at":"2025-08-19 12:57:19","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":194873,"visible":true,"origin":"","legend":"\u003cp\u003eDetection of plasmid \u003cem\u003epIRES2\u003c/em\u003e-\u003cem\u003eCoHsp70\u003c/em\u003e and expression of the plasmid-encoded \u003cem\u003eCoHsp70 \u003c/em\u003ein injected newts. (A) DNA of injected newts was attracted as the PCR template to determine the existence of plasmids. (B) mRNA of injected newts was obtained as the PCR template to confirm \u003cem\u003eCoHsp70 \u003c/em\u003ewas overexpressed by plasmids. Lane M: DNA marker. Lane 1: Newts injected with \u003cem\u003epIRES2-EGFP\u003c/em\u003ewere incubated at 32 °C/36 °C. Primers specific to \u003cem\u003epIRES2-EGFP\u003c/em\u003e was used. Lane 2: Newts injected with \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e were incubated at 32 °C/36 °C. Primers specific to \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e was used. Lane 3: Newts injected with \u003cem\u003epIRES2-EGFP\u003c/em\u003e were incubated at 2 °C/4 °C. Primers specific to \u003cem\u003epIRES2-EGFP\u003c/em\u003ewas used. Lane 4: Newts injected with pIRES2-CoHsp70 were incubated at 2 °C/4 °C. Primers specific to \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e was used.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/d7f86a4c7036eabb013cd3dd.png"},{"id":89391214,"identity":"974f5119-4bed-45c3-9829-b62e2a664392","added_by":"auto","created_at":"2025-08-19 13:05:18","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":53402,"visible":true,"origin":"","legend":"\u003cp\u003eThe survival rates of injected newts incubated at 36 °C and 2 °C within 10 days. *\u003cem\u003e p \u003c/em\u003e\u0026lt; 0.05.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/c437621af43157af159b12be.png"},{"id":89391215,"identity":"db6fa27c-597c-4ecc-a541-5374329ac094","added_by":"auto","created_at":"2025-08-19 13:05:19","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":159880,"visible":true,"origin":"","legend":"\u003cp\u003eStandard metabolic rate (SMR, A), resting energy expenditure (REE, B), and oxygen consumption rate (OCR, C) in newts injected with \u003cem\u003epIRES2-EGFP\u003c/em\u003e or \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e measured at five time points over 28 days under 4 °C, 18 °C (control), or 32 °C. The vertical bars represent the means ± SE (\u003cem\u003en\u003c/em\u003e = 15). Different letters indicate significant differences (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, a \u0026gt; b \u0026gt; c \u0026gt; d \u0026gt; e \u0026gt; f).\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/f0b56e169016fca417f51346.png"},{"id":89391220,"identity":"0f296192-0a59-4556-8227-980d3afc07da","added_by":"auto","created_at":"2025-08-19 13:05:19","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":194093,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal profiles of SMR (A), REE (B), and OCR (C) across temperature regimens (4 °C/18 °C/32 °C) and plasmid treatments (\u003cem\u003epIRES2-EGFP\u003c/em\u003e/\u003cem\u003epIRES2-CoHsp70\u003c/em\u003e). The vertical bars represent the means ± SE (\u003cem\u003en\u003c/em\u003e = 15). Different letters indicate significant differences (\u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05, a \u0026gt; b \u0026gt; c \u0026gt; d \u0026gt; e \u0026gt; f).\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/2de351c8e2baa25b2dba9a8f.png"},{"id":100070008,"identity":"86f9c200-a8b0-48e0-9826-131de638e592","added_by":"auto","created_at":"2026-01-12 16:15:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1979276,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/fea792c8-bfe3-45a3-be5c-7a22319da6a0.pdf"},{"id":89390678,"identity":"57de15d5-c87f-4079-a9e7-1778b7203301","added_by":"auto","created_at":"2025-08-19 12:57:18","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1305354,"visible":true,"origin":"","legend":"","description":"","filename":"Fig.S.docx","url":"https://assets-eu.researchsquare.com/files/rs-6990504/v1/cd9b313acf9f573567a91269.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Heat shock protein 70 in Cynops orientalis: Bidirectional thermal regulation and metabolic optimization in amphibian climatic adaptation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eClimate change, characterized by rising thermal extremes and altering hydrological cycles, imposes multidimensional pressures on amphibian populations globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These perturbations destabilize amphibian habitats while disrupting their physiological equilibrium, ultimately manifesting as behavioral modifications, reproductive impairments, and elevated mortality thresholds [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Prolonged thermal stress activates conserved molecular defenses, particularly through heat shock protein (HSP) cascades, which mitigate proteotoxic damage during cellular denaturation [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Amphibians' constrained thermal tolerance thresholds amplify vulnerability to metabolic dysfunction, developmental anomalies, and population declines in climate-sensitive ecosystems [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. \u003cem\u003eCynops orientalis\u003c/em\u003e (Chinese fire-bellied newt), a caudate amphibian endemic to freshwater systems in China [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], thrives in ecologically variable habitats including agricultural wetlands, ephemeral ponds, and montane streams, demonstrating adaptive plasticity to microenvironmental heterogeneity [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. This species exhibits exceptional thermal resilience, tolerating natural fluctuations from 5\u0026deg;C to 35\u0026deg;C and transient exposure to \u0026gt;\u0026thinsp;40\u0026deg;C in thermally buffered microhabitats during summer stratification [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This exceptional thermal resilience \u0026mdash; combined with an established captive breeding system enabling controlled thermal stress exposure \u0026mdash; positions \u003cem\u003eC. orientalis\u003c/em\u003e as a model organism for ectotherm adaptation studies [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Mechanistic research on stress-responsive pathways \u0026mdash; including HSP-mediated proteostasis, redox regulation, and epigenetic modifications \u0026mdash; is critical for modeling adaptive potential and guiding conservation strategies amid accelerating environmental change. Elucidating these molecular-ecological interfaces will enhance predictive frameworks for species resilience under escalating climatic volatility [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHeat shock proteins (HSPs), a phylogenetically conserved class of molecular chaperones, are transcriptionally upregulated under diverse stress conditions beyond thermal exposure, including cold shock, hypoxia, pathogenic invasion, nutritional deprivation, physical injury, and xenobiotic toxicity [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The HSP superfamily is phylogenetically categorized by molecular weight into distinct subgroups: HSP100, HSP90, HSP70, HSP60, HSP40, and small heat shock proteins (sHSPs), each exhibiting specialized roles in cellular stress adaptation [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. HSP70 family encompasses both constitutively expressed isoforms (e.g., \u003cem\u003eHsc70\u003c/em\u003e/\u003cem\u003eHSPA8\u003c/em\u003e) functioning in basal proteostasis and stress-inducible variants (e.g., \u003cem\u003eHsp72\u003c/em\u003e/\u003cem\u003eHSPA1A\u003c/em\u003e), which are dynamically upregulated during proteotoxic crises [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. As a central node in cellular stress defense, HSP70 orchestrates nascent polypeptide folding, facilitates the disaggregation and renaturation of denatured proteins, and targets irreversibly damaged substrates for proteasomal degradation, thereby preserving proteostatic integrity under thermal extremes [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Empirical studies about amphibian taxa reveal conserved HSP70 induction patterns during hyperthermic challenges. In \u003cem\u003eXenopus laevis\u003c/em\u003e A6 kidney epithelial cells, proteasome inhibitors (e.g., celastrol or MG132) suppress chymotrypsin-like activity, triggering HSF1 binding to heat shock elements and dose/time-dependent HSP70 induction. As a critical chaperone, HSP70 prevents aggregation and maintains client protein solubility/folding capacity during stress, contrasting with HSP30 prolonged stability [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Studies in \u003cem\u003eRana temporaria\u003c/em\u003e tadpoles revealed that HSP70 levels increased during late developmental stages (Gosner 39\u0026ndash;42), with northern populations exhibiting higher constitutive expression at 13\u0026deg;C compared to southern counterparts, a difference abolished at 19\u0026deg;C, highlighting temperature-dependent adaptation [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In \u003cem\u003eRana lessonae\u003c/em\u003e, \u003cem\u003eHsp70\u003c/em\u003e was strictly heat-inducible (33\u0026deg;C), contrasting with constitutive \u003cem\u003eHsc70\u003c/em\u003e expression, and both localized to neuroectoderm and somites during organogenesis, suggesting dual roles in stress response and developmental regulation [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These results demonstrate that the evolutionarily conserved HSP70 molecular chaperone coordinates amphibian thermotolerance and developmental fidelity through a heat-shock-responsive regulatory mechanism. However, systematic characterization of HSP70 across amphibian lineages remains constrained by interspecific genomic heterogeneity, ecological niche-driven adaptation dynamics, and technical limitations in resolving paralogous gene clusters. These challenges underscore the need for advanced phylogenomic approaches to elucidate HSP70 functional diversification in this ecologically vulnerable clade.\u003c/p\u003e\u003cp\u003eIn ectotherms, energy budget allocation efficiency is a central metric for evaluating climatic adaptation. Resting energy expenditure (REE), quantified through gas exchange rates (\u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003eO₂\u003c/em\u003e\u003c/sub\u003e/\u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003eCO₂\u003c/em\u003e\u003c/sub\u003e), directly reflects the basal metabolic load of organisms under quiescent conditions and their energy economy during stress [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Standard metabolic rate (SMR) characterizes the baseline energy demand required for fundamental processes such as cellular homeostasis under minimized environmental interference [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], while oxygen consumption rate (OCR) reveals mitochondrial respiratory chain activity and oxidative phosphorylation efficiency via oxygen utilization per unit time [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These three metabolic phenotypes collectively establish an analytical framework for bioenergetic budgeting: SMR defines survival thresholds, REE captures stress-induced metabolic trajectories, and OCR deciphers mitochondrial functional plasticity. Recent studies indicate that energy expenditure influences the efficiency of \u003cem\u003eHsp70\u003c/em\u003e chaperones in correctly refolding misfolded proteins [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. However, empirical research directly linking HSP70 activity to metabolic phenotypes such as SMR, REE, and OCR remains scarce, particularly in non-model amphibians facing climate-driven thermal oscillations. This knowledge gap severely constrains a comprehensive understanding of the ecological adaptive value of HSP70.\u003c/p\u003e\u003cp\u003eFunctioning as an evolutionarily conserved molecular chaperone, HSP70 coordinates thermal stress adaptation with systemic metabolic regulation in animal organisms. In this study, we report the molecular cloning and stress-inducible expression profiling of \u003cem\u003eCoHsp70\u003c/em\u003e, a heat shock protein 70 homolog from \u003cem\u003eC. orientalis\u003c/em\u003e. Tissue-specific expression analysis revealed differential \u003cem\u003eCoHsp70\u003c/em\u003e mRNA abundance across organ systems, exhibiting temperature-dependent expression dynamics. Transgenic overexpression of \u003cem\u003eCoHsp70\u003c/em\u003e conferred enhanced thermotolerance in newts during thermal challenge. Mechanistic investigation demonstrated time-temperature superposition effects on metabolic remodeling, as evidenced by significant alterations in SMR, REE and OCR profiles. Our findings bridge molecular chaperone biology with conservation physiology, demonstrating how \u003cem\u003eCoHsp70\u003c/em\u003e balances proteostatic resilience with energy economy \u0026mdash; a framework critical for predicting ectotherm adaptability to anthropogenic thermal shifts.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eAnimal acquisition and controlled housing conditions\u003c/p\u003e\u003cp\u003e All experimental procedures involving animals were conducted in strict compliance with the ethical guidelines and regulations governing animal welfare and scientific research in China. The protocol was reviewed and approved by the Animal Research Ethical Committee of Hangzhou Normal University (Approval Number: 2023049). Adult newts (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;300) were procured from Shengsheng Hatchery (Hangzhou, China) and acclimated in standardized polypropylene containers (100 \u0026times; 100 \u0026times; 80 mm) with ventilation holes. Precise mass determination (\u0026plusmn;\u0026thinsp;1 mg) was performed using a calibrated electronic balance (AB135-S; Mettler Toledo, Switzerland) prior to housing. Each container contained a peat-moss substrate and filtered water (40 mm depth, pH 5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2) to simulate natural microhabitat conditions. Specimens were maintained in temperature-controlled incubators (Panasonic, Higashi, Japan) at 18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C under a 12 h:12 h light-dark cycle with automated illumination (06:00\u0026thinsp;\u0026minus;\u0026thinsp;18:00). The newts were fed at 48-hour intervals using thawed \u003cem\u003eLimnodrilus\u003c/em\u003e spp. earthworms, with residual food particles and fecal matter systematically removed via sterile forceps within 30 minutes post-feeding.\u003c/p\u003e\u003cp\u003eMolecular cloning and structural characterization of \u003cem\u003eCoHsp70\u003c/em\u003e\u003c/p\u003e\u003cp\u003ePart of \u003cem\u003eCoHsp70\u003c/em\u003e sequence was obtained by PCR from newt liver DNA using the primers \u003cem\u003eCAU70-F1\u003c/em\u003e and \u003cem\u003eCAU70-R1\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) based on the conserved region sequence of \u003cem\u003ePleurodeles waltl\u003c/em\u003e, \u003cem\u003eAmbystoma mexicanum\u003c/em\u003e, \u003cem\u003eRana amurensis\u003c/em\u003e and \u003cem\u003eRana lessonae\u003c/em\u003e (GenBank accession nos. X71951, AY029210, MZ736885, MZ736884). Partial genomic sequences were obtained using the Genome Walking Kit (Takara, Dalian, China), followed by acquisition of the complete open reading frame (ORF) sequence via the SMARTer RACE 5\u0026rsquo;/3\u0026rsquo; Kit (Takara, Dalian, China). The ORF sequence was submitted to GenBank under accession number PQ323562. Sequence homology was verified using NCBI BLAST, while physicochemical properties were analyzed via ExPASy ProtParam. Secondary structure prediction employed SOPMA (NPS@ server), and domain architecture was resolved using SMART v4.0. The tertiary structure was predicted via homology modeling using SWISS-MODEL.\u003c/p\u003e\u003cp\u003ePhylogenetic analysis\u003c/p\u003e\u003cp\u003eTo construct a meaningful phylogenetic tree, NCBI was used to search for 6 classes of \u003cem\u003eCoHsp70\u003c/em\u003e homologous proteins in \u003cem\u003eChordata\u003c/em\u003e: \u003cem\u003eMammalia\u003c/em\u003e, \u003cem\u003eAves\u003c/em\u003e, \u003cem\u003eReptilia\u003c/em\u003e, \u003cem\u003eAmphibia\u003c/em\u003e, \u003cem\u003eChondrichthyes\u003c/em\u003e, and \u003cem\u003eOsteichthyes\u003c/em\u003e. Ten proteins with \u0026gt;\u0026thinsp;80% homology to CoHSP70 in each class, with a total of 60 species. Multiple sequence alignment was performed using MUSCLE v3.8 with default gap penalties. Phylogenetic analysis was performed using MEGA11 with neighbor-joining method [\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePrimers used in polymerase chain reaction.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimer name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimer sequence (5' to 3')\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAU70-F1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCATGGCAAGGTGGAGATCATC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCAU70-R1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTTAAAATGGAAACATCAAAGGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRT70-F1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGAGGATCATCAATGAGCCAACAG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRT70-R1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGTGTCTCCAGCTGTAGCCTTGAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGAPDH-F1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCTGTCCATGCTGTGACTGCT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGAPDH-R1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCACATTGGCGACAGGTACAC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIRES70-F1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCGAGCTCAAGCTTCGAATTCGATATC\u003c/span\u003eATGTCTGCACCCAAGGGCGTCGC\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIRES70-R1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eCAATGGTGATGGTGATGATGGATATC\u003c/span\u003eATCGACTTCTTCGATAGTGG\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIRG-F1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCTACTTGGCAGTACATCTACGT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIRG-RI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGACGGCAATATGGTGGAAAAT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*The underlined region represents the partial sequence of the ligated plasmid, with the restriction enzyme sites indicated at the emphasized positions.\u003c/p\u003e\u003cp\u003eConstitutive \u003cem\u003eCoHsp70\u003c/em\u003e expression in newt tissues\u003cem\u003e​\u003c/em\u003e\u003c/p\u003e\u003cp\u003eTissues or organs from newts (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5) were collected, flash-frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C for subsequent experiments. The tissues collected included liver, fat, lung, heart, kidney, stomach, muscle, and intestine. Total RNA was extracted by using an RNA extraction kit (Takara, Dalian, China). One microgram of total RNA was treated with a gDNA Eraser Kit (Takara, Dalian, China) and used for cDNA synthesis with a PrimeScript\u0026trade; RT Reagent Kit (Perfect Real Time) (Takara, Dalian, China). Quantitative real-time reverse transcription-PCR (qRT-PCR) was performed using a C1000\u0026trade; thermal cycler (Bio-Rad, Hercules, CA, USA) with an iTaq Universal SYBR Green Supermix Kit (Bio-Rad, Hercules, CA, USA). Each assay was performed in triplicate and programmed as follows: 95\u0026deg;C for 30 s, followed by 40 cycles of 95\u0026deg;C for 5 s and 60\u0026deg;C for 30 s for 30 s, finally 95\u0026deg;C for 10 s. A negative control without template was included in each assay. Melt curve analysis of amplification products was performed at the end of each PCR to confirm amplification specificity. The housekeeping gene was amplified using primers \u003cem\u003eGAPDH-F1\u003c/em\u003e and \u003cem\u003eGAPDH-R1\u003c/em\u003e, which were designed according published newt sequence. The primers, \u003cem\u003eRT70-F1\u003c/em\u003e and \u003cem\u003eRT70-R1\u003c/em\u003e, used to amplify \u003cem\u003eCoHsp70\u003c/em\u003e were designed according to the sequence obtained in our study (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70\u003c/em\u003e expression in response to temperature challenges\u003c/p\u003e\u003cp\u003eAdult newts (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;60) were divided into two groups (30 specimens/group) and acclimated at 4\u0026deg;C (hypothermic stress) or 32\u0026deg;C (hyperthermic stress). Hepatic tissues were harvested at defined intervals: 4\u0026deg;C-exposed specimens at 0, 8, 24, 48, 72, and 96 h; 32\u0026deg;C-exposed specimens at 0, 2, 8, 16, 24, and 48 h. All excised tissues were immediately flash-frozen in liquid nitrogen and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until RNA extraction. RNA extraction, cDNA synthesis, and qRT-PCR protocols followed the methods described in Section 2.4.\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70\u003c/em\u003e overexpression and metabolic phenotyping\u003cb\u003e​\u003c/b\u003e\u003c/p\u003e\u003cp\u003e(i) Plasmid construction\u003c/p\u003e\u003cp\u003eThe open reading frame of \u003cem\u003eCoHsp70\u003c/em\u003e was amplified by PCR using primers \u003cem\u003eIRES70-F1\u003c/em\u003e and \u003cem\u003eIRES70-R1\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The 1941-bp fragment was ligated into the \u003cem\u003epIRES2-EGFP\u003c/em\u003e vector (Clontech, Mountain View, CA, USA) using a one-step PCR cloning kit (Novoprotein, Shanghai, China). \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e was generated to express an EGFP tagged \u003cem\u003eCoHsp70\u003c/em\u003e in newts.\u003c/p\u003e\u003cp\u003e(ii) Thermal stress response in \u003cem\u003eCoHsp70\u003c/em\u003e-overexpressed newts​\u003c/p\u003e\u003cp\u003eAdult newts (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;80) were divided into two groups (40 newts/group) for plasmid intramuscular plasmid injection. Forty newts were injected with 60 \u0026micro;L PBS containing 600 ng \u003cem\u003epIRES2-EGFP\u003c/em\u003e at caudal musculature, while 40 newts were injected with 60 \u0026micro;L PBS containing 600 ng \u003cem\u003epIRESPs-CoHsp70\u003c/em\u003e. Post-injection, cohorts were acclimated in controlled thermal environments programmed for gradual thermal shifts: one group transitioned from 18\u0026deg;C to 36\u0026deg;C (+\u0026thinsp;2.25\u0026deg;C/d), the other from 18\u0026deg;C to 2\u0026deg;C (\u0026minus;\u0026thinsp;2\u0026deg;C/d), reaching target temperatures within 8 days (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). Each thermal cohort consisted of 20 \u003cem\u003epIRES2-EGFP\u003c/em\u003e-injected newts and 20 \u003cem\u003epIRESPs-CoHsp70\u003c/em\u003e-injected counterparts.\u003c/p\u003e\u003cp\u003eNewts were monitored daily during the 10-day exposure at stabilized extreme temperature (36\u0026deg;C or 2\u0026deg;C). Mortality was defined by cessation of opercular movement and righting reflex loss.\u003c/p\u003e\u003cp\u003e(iii) Respirometric measurement of SMR and OCR in newts\u003c/p\u003e\u003cp\u003eNinety adult newts were allocated to three thermal regimens (30 newts/group), each comprising 15 \u003cem\u003epIRES2-EGFP\u003c/em\u003e-injected and 15 \u003cem\u003epIRESPs-CoHsp70\u003c/em\u003e-injected individuals: (1) hypothermic adaptation (18\u0026deg;C to 4\u0026deg;C, \u0026minus; 0.8\u0026deg;C/day), (2) hyperthermic acclimation (18\u0026deg;C to 32\u0026deg;C, + 1.5\u0026deg;C/day), and (3) isothermal maintenance at 18\u0026deg;C. All cohorts were stabilized at their respective target temperatures for 21 days prior to metabolic evaluation (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Metabolic profiling utilized an FMS portable respirometry system (Ecotech, Beijing, China) with eight RM8-switched microchambers (30 mL/min standardized airflow). SMR (mL O₂ g⁻\u0026sup1; h⁻\u0026sup1;) was quantified after 10 min dark acclimation in partially vented chambers, followed by 30 min continuous V\u003csub\u003eO₂\u003c/sub\u003e/V\u003csub\u003eCO₂\u003c/sub\u003e monitoring via ExpeData software (baseline-corrected against channel 1 blanks). Measurements were repeated five times (Days 0, 7, 14, 21, 28) under low-light conditions (12:00\u0026ndash;22:00), preceded by 24 h fasting and mass recording. Respiratory measurements were conducted quintuply at Days 0, 7, 14, 21, and 28 under low-light conditions (12:00\u0026ndash;22:00 h), with 24-hour fasting and mass documentation preceding each trial. This protocol adheres to ectotherm metabolic research standards for environmental stress minimization and data reproducibility.\u003c/p\u003e\u003cp\u003eOCR (mg g⁻\u0026sup1; h⁻\u0026sup1;) was measured under identical temperature acclimation conditions as SMR, with matching time points, sample sizes, and temperature parameters. OCR measurements were conducted at five intervals (Days 0, 7, 14, 21, 28) using 250 mL glass respirometry chambers containing 24-hour aerated water. Initial dissolved oxygen (\u003cem\u003eDO\u003c/em\u003e\u003csub\u003e\u003cem\u003e0\u003c/em\u003e\u003c/sub\u003e, mg L⁻\u0026sup1;) was measured with a JPBJ-610L meter (Leici, Wuxi, China) at \u0026plusmn;\u0026thinsp;0.3 mg L⁻\u0026sup1; accuracy. After 1 h incubation, final dissolved oxygen (\u003cem\u003eDO₁\u003c/em\u003e; mg L⁻\u0026sup1;) was recorded, followed by blot-drying and volumetric displacement-based mass (\u003cem\u003eM\u003c/em\u003e; g) determination. OCR was calculated as [(\u003cem\u003eDO₀\u003c/em\u003e \u0026minus; \u003cem\u003eDO₁\u003c/em\u003e) \u0026times; (chamber volume\u0026thinsp;\u0026minus;\u0026thinsp;newt volume)] / (\u003cem\u003eM\u003c/em\u003e \u0026times; \u003cem\u003et\u003c/em\u003e), with chamber volume\u0026thinsp;=\u0026thinsp;250 mL and \u003cem\u003et\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1 h. All protocols aligned with ectotherm respirometry methodologies for minimizing handling stress and ensuring thermal consistency.\u003c/p\u003e\u003cp\u003e(iv) Detection of plasmid expression in newt tissues\u003c/p\u003e\u003cp\u003eMuscle and liver tissues were harvested from newts after 28 days of culture for DNA/RNA extraction. cDNA synthesis followed the protocol described in Section 2.4. The primer pair \u003cem\u003eRT70-F1\u003c/em\u003e/\u003cem\u003eIRG-R1\u003c/em\u003e were used to detect \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e, while \u003cem\u003eIRG-F1\u003c/em\u003e/\u003cem\u003eIRG-R1\u003c/em\u003e amplified \u003cem\u003epIRES2-EGFP\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Amplification products were electrophoresed on 2% agarose gels using SYBR Safe DNA Gel Stain (Thermo Fisher, Waltham, United States), confirming target-specific bands.\u003c/p\u003e\u003cp\u003eData analyses\u003c/p\u003e\u003cp\u003eThe expression levels of \u003cem\u003eCoHsp70\u003c/em\u003e were analyzed using the 2\u003csup\u003e\u0026minus;ΔΔCT\u003c/sup\u003e method, with relative mRNA levels expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SE [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Chi-square test was performed using Graphpad Prism 9.5 software to assess the differences in mortality. SMR in newts was quantified via closed-chamber respirometry with ExpeData software (Sable Systems International), applying automated MACRO routines to exclude activity-associated oxygen consumption. REE (kcal g⁻\u0026sup1; h⁻\u0026sup1;) was calculated using the Weir equation [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e]: REE\u0026thinsp;=\u0026thinsp;3.941 \u0026times; \u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003eO₂\u003c/em\u003e\u003c/sub\u003e + 1.106 \u0026times; \u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003eCO₂\u003c/em\u003e\u003c/sub\u003e, where \u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003eO₂\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003eV\u003c/em\u003e\u003csub\u003e\u003cem\u003eCO₂\u003c/em\u003e\u003c/sub\u003e represent mass-specific oxygen and carbon dioxide exchange rates, respectively. Within-subject effect tests were performed using repeated measures ANOVA in SPSS 26 software (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05). Significant differences among treatment groups were determined using Duncan's multiple range test in SPSS 26 software (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eSequence characterisation of \u003cem\u003eCoHsp70\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe ORF sequence of \u003cem\u003eCoHsp70\u003c/em\u003e comprises 1,941 nucleotides encoding a 646-residue polypeptide with a predicted molecular mass of 71.05 kDa (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA and B). Amino acid composition analysis revealed alanine (8.2%) and lysine (8.0%) as predominant residues (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Computational analysis using ExPASy identified \u003cem\u003eCoHsp70\u003c/em\u003e as a hydrophilic acidic protein (\u003cem\u003epI\u003c/em\u003e 5.52) with high structural stability (stability index 33.48), exhibiting an aliphatic index of 84.24 and average hydrophilicity of \u0026minus;\u0026thinsp;0.431 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Secondary structure prediction via SOPMA demonstrated α-helices (42.41%) as the dominant conformation, followed by random coils (39.01%) and extended strands (18.58%) (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC). Three conserved HSP70 family signatures were identified through ProSite analysis: signature 1 (11\u0026ndash;18 aa, IDLGTTYS), signature 2 (200\u0026ndash;213 aa, IFDLGGGTFDVSIL), and signature 3 (337\u0026ndash;351 aa, VVLVGGSTRIPKIQK) (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB). Domain architecture analysis revealed an actin-like ATPase domain spanning residues 7\u0026ndash;189 and 194\u0026ndash;385, a peptide-binding domain (388\u0026ndash;546 aa), and a C-terminal subdomain (541\u0026ndash;620 aa), with tertiary structural modeling confirming these functional regions (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePhylogenetic reconstruction using NCBI BLAST identified\u0026thinsp;\u0026gt;\u0026thinsp;80% sequence identity across six phyla, demonstrating \u003cem\u003eCoHSP70\u003c/em\u003e evolutionary conservation. Phylogenetic analysis (Fig. S2) revealed \u003cem\u003eCoHsp70\u003c/em\u003e clustered within the amphibian clade, showing closest homology to \u003cem\u003ePleurodeles waltl\u003c/em\u003e (Amphibia). Unexpected proximity to Osteichthyes sequences may reflect conserved stress-response mechanisms across aquatic vertebrates.\u003c/p\u003e\u003cp\u003eQuantitative reverse transcription-PCR (qRT-PCR) analysis of \u003cem\u003eCoHsp70\u003c/em\u003e expression across eight tissues revealed a distinct hierarchical pattern when normalized to hepatic expression levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Adipose tissue exhibited the highest basal expression, with \u003cem\u003eCoHsp70\u003c/em\u003e transcript abundance measuring 9.4-times that of the liver reference value. Pulmonary expression ranked second at 5.7-fold relative to liver, followed by gastric (3.5-fold) and renal (3.1-fold) tissues. Notably, muscular \u003cem\u003eCoHsp70\u003c/em\u003e levels closely mirrored hepatic baselines (1.1-fold), while intestinal expression demonstrated a marked reduction, registering only 10% of the hepatic reference value. This tissue-specific hierarchy (adipose\u0026thinsp;\u0026gt;\u0026thinsp;lung\u0026thinsp;\u0026gt;\u0026thinsp;stomach\u0026thinsp;\u0026gt;\u0026thinsp;kidney\u0026thinsp;\u0026gt;\u0026thinsp;muscle\u0026thinsp;\u0026asymp;\u0026thinsp;liver\u0026thinsp;\u0026gt;\u0026thinsp;intestine) was observed under physiological steady-state conditions.\u003c/p\u003e\u003cp\u003eExpression of \u003cem\u003eCoHsp70\u003c/em\u003e in response to temperature change\u003c/p\u003e\u003cp\u003eQuantitative analysis of hepatic \u003cem\u003eCoHsp70\u003c/em\u003e transcript levels under thermal stress demonstrated temperature-specific regulatory patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Newts exposed to 4\u0026deg;C exhibited rapid transcriptional suppression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA), with \u003cem\u003eCoHsp70\u003c/em\u003e expression declining to 10% of control levels (18\u0026deg;C) within 8 h. Partial recovery occurred at 24 h (25% of baseline), followed by stabilization at this reduced expression plateau through 96 h (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e5, 30\u003c/sub\u003e = 160.0, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). In contrast, acute 32\u0026deg;C challenge triggered rapid transcriptional activation (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB), achieving peak induction (3.15-fold \u003cem\u003evs\u003c/em\u003e. control) at 2 h before returning to baseline by 8 h. Sustained hyperthermia beyond this phase maintained transcript levels near control conditions (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e5, 30\u003c/sub\u003e = 177.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70\u003c/em\u003e overexpression in tissues\u003c/p\u003e\u003cp\u003e\u003cem\u003epIRES2-EGFP\u003c/em\u003e is a eukaryotic expression vector carrying \u003cem\u003eCoHsp70\u003c/em\u003e for overexpression in newts. The presence and expression of vectors \u003cem\u003epIRES2-EGFP\u003c/em\u003e and \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e in tissues were verified at both DNA and mRNA levels by PCR. In the gel image, clear electrophoresis bands of both plasmids were observed under high temperature and low temperature conditions, and the band sizes were accurate (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC and D). This indicates that both the empty vector and the recombinant plasmid are present in the liver and muscles of the newts and undergo normal transcription and translation.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70 enhances newt survival under heat stress​\u003c/em\u003e\u003c/p\u003e\u003cp\u003eSurvival analysis of newts subjected to thermal extremes revealed plasmid-dependent viability patterns (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Following intramuscular injection with either \u003cem\u003epIRES2-EGFP\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20) or \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;20), newts were acclimated to thermal challenges (36\u0026deg;C \u003cem\u003evs\u003c/em\u003e. 2\u0026deg;C) over 10 days. Under hyper (36\u0026deg;C), the \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e cohort exhibited 40% survival, significantly surpassing the 10% viability in \u003cem\u003epIRES2-EGFP\u003c/em\u003e-injected counterparts (\u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1, \u003cem\u003eχ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;5.562\u0026thinsp;\u0026gt;\u0026thinsp;5.024, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.03). Mortality in the \u003cem\u003epIRES2-EGFP\u003c/em\u003e group commenced at 72 h post-induction, escalating linearly through day 10. In contrast, hypothermia (2\u0026deg;C) elicited 100% survival in both groups, demonstrating temperature-specific plasmid effects.\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70\u003c/em\u003e modulates temperature-dependent metabolism\u003c/p\u003e\u003cp\u003eThe repeated-measures ANOVA (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) indicated no significant effects of Time (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e4, 348\u003c/em\u003e\u003c/sub\u003e = 1.438, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.227\u0026thinsp;\u0026gt;\u0026thinsp;0.05, partial η\u0026sup2; = 0.016), Temperature (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e2, 87\u003c/em\u003e\u003c/sub\u003e = 0.203, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.816\u0026thinsp;\u0026gt;\u0026thinsp;0.05, partial η\u0026sup2; = 0.005), or Time\u0026times;Temperature interaction (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e8, 348\u003c/em\u003e\u003c/sub\u003e = 0.322, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.944\u0026thinsp;\u0026gt;\u0026thinsp;0.05, partial η\u0026sup2; = 0.007) on body mass trajectories. Prior to thermal acclimation under standard 18\u0026deg;C conditions, newts injected with \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e or \u003cem\u003epIRES2-EGFP\u003c/em\u003e showed no significant differences in SMR or REE at Day 0 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA and B). Following temperature acclimation (4\u0026deg;C, 18\u0026deg;C, 32\u0026deg;C), distinct thermal response patterns emerged (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA and B, Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA and B). At 32\u0026deg;C, both SMR and REE measurements consistently exceeded those at 18\u0026deg;C and 4\u0026deg;C throughout the 28-day period, peaking on day 14 before gradual decline while maintaining elevated levels compared to lower temperatures. Temperature-dependent plasmid effects became apparent from day 14 onward across all thermal regimes, with \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e-injected newts demonstrating significantly lower metabolic parameters than \u003cem\u003epIRES2-EGFP\u003c/em\u003e controls. Specifically, at 4\u0026deg;C, delayed divergence emerged on day 21, accompanied by progressive metabolic decline from days 7\u0026ndash;28. At day 21 under 4\u0026deg;C, \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e-injected newts exhibited significantly reduced metabolic rates compared to \u003cem\u003epIRES2-EGFP\u003c/em\u003e controls, SMR and REE reaching 75.7% and 76.5% of control values, respectively (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In 18\u0026deg;C and 32 ℃ conditions, stable baseline metabolic levels contrasted with plasmid-specific differences from day 14 onward. At day 14 under 18\u0026deg;C, \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e-injected newts showed SMR at 96.1% and REE at 95.9% of \u003cem\u003epIRES2-EGFP\u003c/em\u003e controls (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). At 32\u0026deg;C, SMR and REE values were 95.9% and 96.0%, respectively, compared to controls (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The reduced SMR and REE in \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e-injected newts suggest enhanced proteostatic efficiency, which lowersATP expenditure for protein refolding under stress conditions.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWithin-agent effect test.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eType III Sum of Squares\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003cp\u003eSquare\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e Statistic\u003c/p\u003e\u003cp\u003e(\u003cem\u003ep\u003c/em\u003e-value)​\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePartial\u003c/p\u003e\u003cp\u003eη\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.692\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e4, 348\u003c/em\u003e\u003c/sub\u003e = 1.438, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.227\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTemperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.066\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e2, 87\u003c/em\u003e\u003c/sub\u003e = 0.203, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.816\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTime \u0026times; Temperature\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003csub\u003e\u003cem\u003e8, 348\u003c/em\u003e\u003c/sub\u003e = 0.322, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e*All analyses utilized Type III sum of squares (\u003cem\u003eα\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05) .\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70\u003c/em\u003e attenuates thermal stress-induced oxygen demand\u003c/p\u003e\u003cp\u003eAs detailed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the repeated-measures ANOVA correction revealed no statistically significant impact of temporal variation, thermal exposure or their interaction on body mass trajectories in newts under the implemented experimental paradigm. Prior to thermal acclimation under standard 18\u0026deg;C conditions (Day 0), newts injected with \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e or \u003cem\u003epIRES2-EGFP\u003c/em\u003e plasmids exhibited no significant differences in OCR (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). Thermal acclimation to 4\u0026deg;C, 18\u0026deg;C, and 32\u0026deg;C induced distinct OCR response patterns over the 28-day experimental period (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC, \u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). In contrast to SMR and REE, OCR measurements at 32\u0026deg;C consistently exceeded values at lower temperatures, peaking on Day 7 followed by a gradual decline. Plasmid-specific OCR divergence emerged from day 14, with \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e-injected newts exhibiting 94.7% of \u003cem\u003epIRES2-EGFP\u003c/em\u003e control values (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), demonstrating sustained OCR suppression. At 4\u0026deg;C, plasmid-mediated differentiation became apparent by day 21, \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e groups showing 87.9% of control OCR levels (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), alongside progressive attenuation from days 7\u0026ndash;28. Despite inter-plasmid differences from day 14 in the 18\u0026deg;C group, baseline OCR stability persisted, \u003cem\u003epIRES2-CoHsp70\u003c/em\u003e reaching 92.4% of control values (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), emphasizing temperature-dependent modulation of oxygen metabolism.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHSP70 is one of the most evolutionarily conserved and widely studied members of the heat shock protein family [\u003cspan additionalcitationids=\"CR37\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. It is expressed in both prokaryotes and eukaryotes, with amino acid sequences exhibiting high similarity across diverse biological sources [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan additionalcitationids=\"CR40 CR41\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. For instance, goat HSP70-1 shares 96\u0026ndash;99% sequence similarity with sheep (partial), cattle, and buffalo, while amino acid-level similarity ranges from 95\u0026ndash;100% [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Similarly, murine and human HSP70 display 95% amino acid homology and 91% nucleotide homology [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e], suggesting conserved biological roles across species. Although multiple \u003cem\u003eHsp70\u003c/em\u003e family members have been identified in animals and plants, amphibian studies remain limited to a few model species, including \u003cem\u003eXenopus laevis\u003c/em\u003e, \u003cem\u003eX. tropicalis\u003c/em\u003e, and \u003cem\u003eRana lessonae\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Our study addresses this knowledge gap through successful cloning and functional characterization of \u003cem\u003eCoHsp70\u003c/em\u003e from \u003cem\u003eC. orientalis\u003c/em\u003e. These findings not only establish an amphibian-specific framework for molecular chaperone research but also provide crucial evolutionary insights into stress adaptation mechanisms across tetrapod lineages.\u003c/p\u003e\u003cp\u003eStructural basis of \u003cem\u003eCoHsp70\u003c/em\u003e functional plasticity\u003c/p\u003e\u003cp\u003eSequence analysis confirms that \u003cem\u003eCoHsp70\u003c/em\u003e exhibits the canonical eukaryotic HSP70 architecture, characterized by three signature motifs and three conserved functional domains. The N-terminal region contains two highly conserved sequences (41 kDa) encompassing the ATPase active site, which drives ATP hydrolysis to facilitate substrate protein folding and translocation. Adjacent to this lies a conserved 17.4 kDa substrate-binding domain that recognizes hydrophobic client peptides. The C-terminal region (9.4 kDa) displays structural variability and terminates with the cytoplasmic-specific EEVD motif, a hallmark of cytosolic HSP70 isoforms that mediates co-chaperone interactions [\u003cspan additionalcitationids=\"CR47\" citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Phylogenetic comparisons reveal striking conservation of these structural features across diverse taxa, including \u003cem\u003eMacrobrachium rosenbergii\u003c/em\u003e, \u003cem\u003ePleurodeles waltl\u003c/em\u003e, and \u003cem\u003eXenopus laevis\u003c/em\u003e [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], underscoring the evolutionary constraint on HSP70 core machinery. Notably, the acidic isoelectric point (\u003cem\u003epI\u003c/em\u003e 5.52) of \u003cem\u003eCoHsp70\u003c/em\u003e closely resembles that of mammalian HSPA1A (\u003cem\u003epI\u003c/em\u003e 5.3\u0026ndash;5.8). However, its lower hydrophobicity (GRAVY: \u0026ndash; 0.431) compared to human HSPA8 (GRAVY: \u0026ndash; 0.38) suggests a potential mechanism for stabilizing higher-molecular-weight client protein complexes through enhanced surface charge distribution [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These structural features collectively underpin the functional plasticity of \u003cem\u003eCoHsp70\u003c/em\u003e in adapting to amphibian ecological pressures.\u003c/p\u003e\u003cp\u003eAdipose \u003cem\u003eHsp70\u003c/em\u003e drives stress adaptation\u003c/p\u003e\u003cp\u003eThis study reveals that baseline expression of \u003cem\u003eCoHsp70\u003c/em\u003e in adipose tissue (9.4-fold higher than hepatic levels) challenges the liver/spleen-centric paradigm of \u003cem\u003eHsp70\u003c/em\u003e expression [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. This phenomenon likely reflects newts' unique reliance on adipose tissue as an energy reservoir during hibernation [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], where elevated free fatty acids in adipocytes induce endoplasmic reticulum stress (ERS) and mitochondrial lipid peroxidation [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Sustained \u003cem\u003eCoHsp70\u003c/em\u003e overexpression may maintain adipocyte homeostasis via dual mechanisms: (1) collaborative repair of misfolded fatty acid synthases with HSP40 co-chaperones [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], and (2) suppression of IRE1α-XBP1 signaling to block ERS-driven lipolysis [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. The comparatively low intestinal \u003cem\u003eCoHsp70\u003c/em\u003e expression (10% of hepatic levels) suggests a risk-aversion strategy, limiting misfolded protein accumulation and premature UPR activation [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This tissue hierarchy (adipose\u0026thinsp;\u0026gt;\u0026thinsp;lung\u0026thinsp;\u0026gt;\u0026thinsp;stomach\u0026thinsp;\u0026gt;\u0026thinsp;kidney) implies spatial \u003cem\u003eHsp70\u003c/em\u003e reprogramming balances organ-specific stress defense with metabolic economy.\u003c/p\u003e\u003cp\u003eThermal bidirectionality of \u003cem\u003eHsp70\u003c/em\u003e stress adaptation\u003c/p\u003e\u003cp\u003e\u003cem\u003eCoHsp70\u003c/em\u003e exhibits marked asymmetric dynamics in response to thermal challenges: acute heat stress (32\u0026deg;C) triggers rapid yet self-limited transcriptional activation (peaking at 2 h and returning to baseline by 8 h), while chronic cold exposure (4\u0026deg;C) causes progressive and irreversible transcriptional suppression (25% baseline retention at 96 h). This divergence likely stems from hierarchical temperature-sensing pathways \u0026mdash; heat stress directly activates the \u003cem\u003eHsp70\u003c/em\u003e promoter via HSF1 trimerization [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], whereas cold stress suppresses mTORC1-S6K signaling to reduce translational elongation efficiency, inducing negative feedback [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Partial \u003cem\u003eCoHsp70\u003c/em\u003e recovery at 24 h of cold exposure may involve cold shock proteins [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. Functional assays reveal that \u003cem\u003eCoHsp70\u003c/em\u003e overexpression enhances hyperthermic survival (36\u0026deg;C; 40% \u003cem\u003evs\u003c/em\u003e. 10% controls) but not cold survival (2\u0026deg;C). This temperature-dependent survival trade-off suggests distinct mechanisms: under heat stress, \u003cem\u003eCoHsp70\u003c/em\u003e stabilizes thermosensitive kinases to sustain energy sensing [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e], whereas under cold stress, its ATP-dependent activity exacerbates energy deficits, driving metabolic suppression [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. These findings underscore that \u003cem\u003eHsp70\u003c/em\u003e adaptive value is tightly modulated by environmental thermal amplitude.\u003c/p\u003e\u003cp\u003e\u003cem\u003eHsp70\u003c/em\u003e optimizes energy budgets under stress\u003c/p\u003e\u003cp\u003eWhile canonical models posit that HSP70 overexpression exacerbates energy burdens [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], this study demonstrates \u003cem\u003eCoHsp70\u003c/em\u003e overexpression reduces SMR and REE under hyperthermia (32\u0026deg;C). These effects may occur through reduced energy waste in protein repair and improved mitochondrial energy efficiency. This paradox aligns with the chaperone efficiency hypothesis: \u003cem\u003eCoHsp70\u003c/em\u003e enhances substrate recognition precision (e.g., via strengthened Hsp40 co-chaperone affinity) to minimize ATP expenditure on futile folding cycles [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], while concurrently suppressing energy-draining non-selective autophagy by disrupting p62-LC3 interactions [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. In cold-adapted cohorts, \u003cem\u003eCoHsp70\u003c/em\u003e-mediated declines in OCR likely involve stabilization of mitochondrial respiratory assemblies (e.g., I-III2-IVn) [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], which optimize electron transfer efficiency. These findings redefine \u003cem\u003eHsp70\u003c/em\u003e metabolic role \u0026mdash; not merely as a stress defense executor but as a systemic energy budget optimizer, reconciling proteostatic demands with bioenergetic constraints under thermal extremes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study delineates the structural and functional attributes of \u003cem\u003eCoHsp70\u003c/em\u003e in \u003cem\u003eCynops orientalis\u003c/em\u003e, revealing its conserved HSP70 architecture \u0026mdash; three signature motifs (IDLGTTYS, IFDLGGGTFDVSIL, VVLVGGSTRIPKIQK) and domains (ATPase, substrate-binding, C-terminal EEVD) \u0026mdash; with \u0026gt;\u0026thinsp;80% sequence identity to amphibian homologs such as Pleurodeles waltl. Tissue-specific profiling identified adipose tissue as the primary site of \u003cem\u003eCoHsp70\u003c/em\u003e expression (9.4-fold higher than liver), contrasting sharply with suppressed intestinal levels (10% of hepatic baseline). Thermal challenges induced bidirectional transcriptional dynamics: rapid but transient activation under acute heat stress (32\u0026deg;C, peaking at 2 h) versus progressive suppression during chronic cold exposure (4\u0026deg;C, declining to 10% baseline within 8 h). Plasmid-driven \u003cem\u003eCoHsp70\u003c/em\u003e overexpression enhanced hyperthermic survival (40% \u003cem\u003evs\u003c/em\u003e. 10% in at 36\u0026deg;C) while reducing standard metabolic rate (SMR), resting energy expenditure (REE), and oxygen consumption (OCR), corroborating its role in energy-efficient stress adaptation. Successful validation of tissue-specific plasmid expression confirmed the functional relevance of these findings. Collectively, \u003cem\u003eCoHsp70\u003c/em\u003e emerges as a molecular linchpin balancing proteostatic resilience with metabolic economy in amphibian thermal adaptation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eATPase \u0026ndash; Adenosine triphosphatase\u003c/p\u003e\n\u003cp\u003eCoHsp70 \u0026ndash; Cynops orientalis Heat shock protein 70\u003c/p\u003e\n\u003cp\u003eDO \u0026ndash; Dissolved oxygen\u003c/p\u003e\n\u003cp\u003eDO₀ \u0026ndash; Initial dissolved oxygen\u003c/p\u003e\n\u003cp\u003eDOₜ \u0026ndash; Final dissolved oxygen after time t\u003c/p\u003e\n\u003cp\u003eEEVD \u0026ndash; Glutamate-glutamate-valine-aspartate (C-terminal motif of cytosolic HSP70)\u003c/p\u003e\n\u003cp\u003eEGFP \u0026ndash; Enhanced green fluorescent protein\u003c/p\u003e\n\u003cp\u003eERS \u0026ndash; Endoplasmic reticulum stress\u003c/p\u003e\n\u003cp\u003eGAPDH \u0026ndash; Glyceraldehyde-3-phosphate dehydrogenase (housekeeping gene)\u003c/p\u003e\n\u003cp\u003eHsc70 \u0026ndash; Heat shock cognate 70 (constitutive isoform)\u003c/p\u003e\n\u003cp\u003eHSP \u0026ndash; Heat shock protein\u003c/p\u003e\n\u003cp\u003eHSP40 \u0026ndash; Heat shock protein 40 (co-chaperone)\u003c/p\u003e\n\u003cp\u003eHSP70 \u0026ndash; Heat shock protein 70\u003c/p\u003e\n\u003cp\u003eHSP90 \u0026ndash; Heat shock protein 90\u003c/p\u003e\n\u003cp\u003eHSPA1A \u0026ndash; Heat shock protein family A member 1A (inducible Hsp70)\u003c/p\u003e\n\u003cp\u003eHSPA8 \u0026ndash; Heat shock protein family A member 8 (constitutive Hsc70)\u003c/p\u003e\n\u003cp\u003eHSF1 \u0026ndash; Heat shock factor 1\u003c/p\u003e\n\u003cp\u003eIRE1\u0026alpha; \u0026ndash; Inositol-requiring enzyme 1\u0026alpha; (ERS sensor)\u003c/p\u003e\n\u003cp\u003emTORC1 \u0026ndash; Mechanistic target of rapamycin complex 1\u003c/p\u003e\n\u003cp\u003eOCR \u0026ndash; Oxygen consumption rate\u003c/p\u003e\n\u003cp\u003eORF \u0026ndash; Open reading frame\u003c/p\u003e\n\u003cp\u003epIRES2 \u0026ndash; Plasmid with internal ribosome entry site\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePBS \u0026ndash; Phosphate-Buffered Saline\u003c/p\u003e\n\u003cp\u003eqRT-PCR \u0026ndash; Quantitative real-time reverse transcription polymerase chain reaction\u003c/p\u003e\n\u003cp\u003eREE \u0026ndash; Resting energy expenditure\u003c/p\u003e\n\u003cp\u003eS6K \u0026ndash; Ribosomal protein S6 kinase\u003c/p\u003e\n\u003cp\u003eSMR \u0026ndash; Standard metabolic rate\u003c/p\u003e\n\u003cp\u003esHSPs \u0026ndash; Small heat shock proteins\u003c/p\u003e\n\u003cp\u003eUPR \u0026ndash; Unfolded protein response\u003c/p\u003e\n\u003cp\u003eVO\u003csub\u003e2\u003c/sub\u003e \u0026ndash; Oxygen consumption rate\u003c/p\u003e\n\u003cp\u003eVCO\u003csub\u003e2\u003c/sub\u003e \u0026ndash; Carbon dioxide production rate\u003c/p\u003e\n\u003cp\u003eXBP1 \u0026ndash; X-box binding protein 1 (UPR transcription factor)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their gratitude to all members of the L.H.L. research group for their insightful discussions, dedicated animal care, and technical support during experimental procedures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.R.L. contributed to writing the original draft, methodology, data curation, formal analysis, and validation. Y.Q.T. reviewed and edited the manuscript and developed the software. Z.Y.F. implemented the software and conducted formal analysis. Z.W.W., H.Y.Z., and S.C.G. performed investigations and created visualizations. L.H.L. acquired funding, managed the project, and provided resources. W.D. conceptualized the study, designed the methodology, and supervised the research. All authors approved the final version for publication and agree to be accountable for\u003cstrong\u003e\u0026nbsp;the work.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LY23C030003).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe open reading frame sequence of \u003cem\u003eCoHsp70\u003c/em\u003e has been deposited in GenBank under accession number PQ323562.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExperimental animals (\u003cem\u003eCynops orientalis\u003c/em\u003e, n=300) were obtained from Shengsheng Hatchery (Hangzhou, China) with informed consent for the study. All experimental procedures involving animals were conducted in strict compliance with the ARRIVE guidelines and the National Research Council\u0026apos;s \u003cem\u003eGuide for the Care and Use of Laboratory Animals\u0026nbsp;(China)\u003c/em\u003e. The protocol was reviewed and approved by the Animal Research Ethical Committee of Hangzhou Normal University (Approval Number: 2023049). All surgeries were performed under anesthesia with 0.1% Tricaine methanesulfonate (MS-222, Sigma-Aldrich, USA), and every effort was made to minimize suffering.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eParmesan C, Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. \u003cem\u003eNature.\u003c/em\u003e 2003; 421 (6918), 37\u0026ndash;42. (doi: 10.1038/nature01286)\u003c/li\u003e\n\u003cli\u003eAlan Pounds J, Bustamante MR, Coloma LA, Consuegra JA, Fogden MPL, Foster PN, La Marca E, Masters KL, Merino-Viteri A, Puschendorf R, et al. Widespread amphibian extinctions from epidemic disease driven by global warming. \u003cem\u003eNature.\u003c/em\u003e 2006; 439 (7073), 161\u0026ndash;167. (doi: 10.1038/nature04246)\u003c/li\u003e\n\u003cli\u003eBickford D, Lohman DJ, Sodhi NS, Ng PKL, Meier R, Winker K, Ingram KK, Das I. Cryptic species as a window on diversity and conservation. \u003cem\u003eTrends Ecol. Evol.\u003c/em\u003e 2007; 22 (3), 148\u0026ndash;155. (doi: 10.1016/j.tree.2006.11.004)\u003c/li\u003e\n\u003cli\u003eWalther GR, Post E, Convey P, Menzel A, Parmesan C, Beebee TJC, Fromentin JM, Guldberg OH, Bairlein F. Ecological responses to recent climate change. \u003cem\u003eNature.\u003c/em\u003e 2002; 416, 389\u0026ndash;395. (doi: 10.1038/416389a)\u003c/li\u003e\n\u003cli\u003eAbdelnour SA, Abd El-Hack ME, Khafaga AF, Arif M, Taha AE, Noreldin AE. Stress biomarkers and proteomics alteration to thermal stress in ruminants: A review.\u003cem\u003e J. Therm. Biol.\u003c/em\u003e 2019; 79, 120\u0026ndash;134. (doi: 10.1016/j.jtherbio.2018.12.013)\u003c/li\u003e\n\u003cli\u003eFeder ME, Krebs RA. Ecological and evolutionary physiology of heat shock proteins and the stress response in Drosophila: Complementary insights from genetic engineering and natural variation. EXS. 1997; 83, 155\u0026ndash;173. (doi: 10.1007/978-3-0348-8882-0_9) \u003c/li\u003e\n\u003cli\u003eSleadd IM, Lee M, Hassumani DO, Stecyk TMA, Zeitz OK, Buckley BA. Sub-lethal heat stress causes apoptosis in an Antarctic fish that lacks an inducible heat shock response. \u003cem\u003eJ. Therm. Biol.\u003c/em\u003e 2014; 44, 119-125. (doi: 10.1016/j.jtherbio.2014.06.007)\u003c/li\u003e\n\u003cli\u003eCooper RD, Shaffer HB. Allele‐specific expression and gene regulation help explain transgressive thermal tolerance in non‐native hybrids of the endangered California tiger salamander (\u003cem\u003eAmbystoma californiense\u003c/em\u003e). \u003cem\u003eMol. Ecol.\u003c/em\u003e 2021; 30 (4), 987\u0026ndash;1004. (doi: 10.1111/mec.15779)\u003c/li\u003e\n\u003cli\u003eLi Y, Cohen JM, Rohr JR. Review and synthesis of the effects of climate change on amphibians. \u003cem\u003eIntegr. Zool.\u003c/em\u003e 2013; 8 (2), 145\u0026ndash;161. (doi: 10.1111/1749-4877.12001)\u003c/li\u003e\n\u003cli\u003ePottier P, Lin HY, Oh RRY, Pollo P, Rivera-Villanueva AN, Valdebenito JO, Yang Y, Amano T, Burke S, Drobniak SM, et al. A comprehensive database of amphibian heat tolerance. \u003cem\u003eSci. Data.\u003c/em\u003e 2022; 9 (1), 600. (doi: 10.1038/s41597-022-01704-9)\u003c/li\u003e\n\u003cli\u003eRuthsatz K, Dausmann KH, Peck MA, Glos J. Thermal tolerance and acclimation capacity in the European common frog (\u003cem\u003eRana temporaria\u003c/em\u003e) change throughout ontogeny. \u003cem\u003eJ. Exp. Zool.\u003c/em\u003e A Ecol. Integr. Physiol. 2022; 337 (5), 477\u0026ndash;490. (doi: 10.1002/jez.2582)\u003c/li\u003e\n\u003cli\u003eGuo K, Yuan S, Wang H, Zhong J, Wu Y, Chen W, Hu C, Chang Q. Species distribution models for predicting the habitat suitability of Chinese fire‐bellied newt \u003cem\u003eCynops orientalis\u003c/em\u003e under climate change. \u003cem\u003eEcol. Evol.\u003c/em\u003e 2021; 11 (15), 10147\u0026ndash;10154. (doi: 10.1002/ece3.7822)\u003c/li\u003e\n\u003cli\u003eWeng L, Wong WP, Chew SF, Ip YK. Excretory nitrogen metabolism in the Chinese fire-belly newt \u003cem\u003eCynops orientalis\u003c/em\u003e in water, on land, or in high concentrations of environmental ammonia.\u003cem\u003e J. Comp. Physiol. B Biochem. Syst. Environ. Physiol.\u003c/em\u003e 2004; 174 (2), 113\u0026ndash;120. (doi: 10.1007/s00360-003-0395-z)\u003c/li\u003e\n\u003cli\u003eAndo N, Barquera B, Bartlett DH, Boyd E, Burnim AA, Byer AS, Colman D, Gillilan RE, Gruebele M, Makhatadze G, et al. The Molecular Basis for Life in Extreme Environments. \u003cem\u003eAnnual review of biophysics.\u003c/em\u003e 2021; 50, 343\u0026ndash;372. (doi: 10.1146/annurev-biophys-100120-072804)\u003c/li\u003e\n\u003cli\u003eBiscotti MA, Carducci F, Barucca M, Gerdol M, Pallavicini A, Schartl M, Canapa A, Adolfi MC, The transcriptome of the newt Cynops orientalis provides new insights into evolution and function of sexual gene networks in sarcopterygians. \u003cem\u003eSci. Rep.\u003c/em\u003e 2020; 10 (1), 5445. (doi: 10.1038/s41598-020-62408-x)\u003c/li\u003e\n\u003cli\u003eMebs D, Yotsu-Yamashita M. Acquiring toxicity of a newt, \u003cem\u003eCynops orientalis\u003c/em\u003e. \u003cem\u003eToxicon.\u003c/em\u003e 2021; 198, 32\u0026ndash;35. (doi: 10.1016/j.toxicon.2021.04.025)\u003c/li\u003e\n\u003cli\u003eOborov\u0026aacute; V, \u0026Scaron;ugerkov\u0026aacute; M, Gvožd\u0026iacute;k L. Sensitivity of amphibian embryos to timing and magnitude of present and future thermal extremes. \u003cem\u003eJ. Exp. Zool. A Ecol. Integr. Physiol.\u003c/em\u003e 2024; 341 (4), 377\u0026ndash;388. (doi: 10.1002/jez.2791)\u003c/li\u003e\n\u003cli\u003eVon May R, Catenazzi A, Santa-Cruz R, Gutierrez AS, Moritz C, Rabosky DL. Thermal physiological traits in tropical lowland amphibians: Vulnerability to climate warming and cooling. \u003cem\u003ePLoS ONE.\u003c/em\u003e 2019; 14 (8), e0219759. (doi: 10.1371/journal.pone.0219759)\u003c/li\u003e\n\u003cli\u003eL\u0026eacute;vesque M, Guimond JC, Pilote M, Leclerc S, Moldovan F, Roy S. Expression of heat‐shock protein 70 during limb development and regeneration in the axolotl. \u003cem\u003eDev. Dyn.\u003c/em\u003e 2005; 233 (4), 1525\u0026ndash;1534. (doi: 10.1002/dvdy.20458)\u003c/li\u003e\n\u003cli\u003eNinomiya H, Ohgami N, Oshino R, Kato M, Ohgami K, Li X, Shen D, Iida M, Yajima I, Angelidis CE, et al. Increased expression level of \u003cem\u003eHsp70\u003c/em\u003e in the inner ears of mice by exposure to low frequency noise. \u003cem\u003eHear. Res.\u003c/em\u003e 2018; 363, 49-54. (doi: 10.1016/j.heares.2018.02.006)\u003c/li\u003e\n\u003cli\u003eQian SB, McDonough H, Boellmann F, Cyr DM, Patterson C. CHIP-mediated stress recovery by sequential ubiquitination of substrates and \u003cem\u003eHsp70\u003c/em\u003e. \u003cem\u003eNature.\u003c/em\u003e 2006; 440 (7083), 551\u0026ndash;555. (doi: 10.1038/nature04600)\u003c/li\u003e\n\u003cli\u003eHagymasi AT, Dempsey JP, Srivastava PK. Heat‐Shock Proteins. \u003cem\u003eCurr. Protoc.\u003c/em\u003e 2022; 2 (11), e592. (doi: 10.1002/cpz1.592)\u003c/li\u003e\n\u003cli\u003eMayer MP, Bukau B. Hsp70 chaperones: Cellular functions and molecular mechanism. \u003cem\u003eCell. Mol. Life Sci.\u003c/em\u003e 2005; 62 (6), 670\u0026ndash;684. (doi: 10.1007/s00018-004-4464-6)\u003c/li\u003e\n\u003cli\u003eRosenzweig R, Nillegoda NB, Mayer MP, Bukau B. The Hsp70 chaperone network. \u003cem\u003eMol. Cell Biol.\u003c/em\u003e 2019; 20 (11), 665\u0026ndash;680. (doi: 10.1038/s41580-019-0133-3)\u003c/li\u003e\n\u003cli\u003eKhan S, Heikkila JJ. Distinct patterns of HSP30 and HSP70 degradation in \u003cem\u003eXenopus laevis\u003c/em\u003e A6 cells recovering from thermal stress. \u003cem\u003eComp. Biochem. Physiol. A Mol. Integr. Physiol.\u003c/em\u003e 2014; 168, 1\u0026ndash;10. (doi: 10.1016/j.cbpa.2013.10.026)\u003c/li\u003e\n\u003cli\u003eNikinmaa M, Leveelahti L, Dahl E, Rissanen E, Rytkönen KT, Laurila A. Population origin, development and temperature of development affect the amounts of HSP70, HSP90 and the putative hypoxia-inducible factor in the tadpoles of the common frog \u003cem\u003eRana temporaria\u003c/em\u003e. \u003cem\u003eJ. Exp. Biol.\u003c/em\u003e 2008; 211 (Pt 12), 1999\u0026ndash;2004. (doi:10.1242/jeb.016816)\u003c/li\u003e\n\u003cli\u003eSimoncelli F, Morosi L, Di Rosa I, Pascolini R, Fagotti A. Molecular characterization and expression of a heat-shock cognate 70 (Hsc70) and a heat-shock protein 70 (Hsp70) cDNAs in \u003cem\u003eRana (Pelophylax)\u003c/em\u003e lessonae embryos. \u003cem\u003eComp. Biochem. Physiol. A Mol. Integr. Physiol.\u003c/em\u003e 2010; 156 (4), 552\u0026ndash;560. doi.org/10.1016/j.cbpa.2010.04.016)\u003c/li\u003e\n\u003cli\u003eBlasco Redondo R. Resting energy expenditure; assessment methods and applications. \u003cem\u003eNutr. Hosp.\u003c/em\u003e 31 (Suppl 3), 2015; 245\u0026ndash;254. (doi: 10.3305/nh.2015.31.sup3.8772)\u003c/li\u003e\n\u003cli\u003eBech C, Christiansen MT, Kvernland P, Nyg\u0026aring;rd RM, Rypdal E, Sneltorp SK, Trondrud LM, Tvedten \u0026Oslash;G. The standard metabolic rate of a land snail (\u003cem\u003eCepaea hortensis\u003c/em\u003e) is a repeatable trait and influences winter survival. \u003cem\u003eComp Biochem Physiol A Mol Integr Physiol.\u003c/em\u003e 2020; 249: 110773. (doi: 10.1016/j.cbpa.2020.110773)\u003c/li\u003e\n\u003cli\u003eEzgeta-Balić D, Rinaldi A, Peharda M, Prusina I, Montalto V, Niceta N, Sar\u0026agrave; G. An energy budget for the subtidal bivalve \u003cem\u003eModiolus barbatus\u003c/em\u003e (Mollusca) at different temperatures. \u003cem\u003eMar. Environ. Res.\u003c/em\u003e 2011; 71 (1), 79\u0026ndash;85. (doi: 10.1016/j.marenvres.2010.10.005)\u003c/li\u003e\n\u003cli\u003eChauhan R, Sharma AK. Speed-Energy-Efficiency Trade-off in \u003cem\u003eHsp70\u003c/em\u003e Chaperone System.\u003cem\u003e J. Phys. Chem. B.\u003c/em\u003e 2024; 128 (49), 12101\u0026ndash;12113. (doi: 10.1021/acs.jpcb.4c06594)\u003c/li\u003e\n\u003cli\u003eFelsenstein J. Confidence Limits on Phylogenies: An Approach Using the Bootstrap. \u003cem\u003eEvolution.\u003c/em\u003e 1985; 39 (4), 783\u0026ndash;791. (doi: 10.1111/j.1558-5646.1985.tb00420.x)\u003c/li\u003e\n\u003cli\u003eSaitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. \u003cem\u003eMol. Biol. Evol.\u003c/em\u003e 1987; 4 (4), 406\u0026ndash;425. (doi: 10.1093/oxfordjournals.molbev.a040454)\u003c/li\u003e\n\u003cli\u003eTamura K, Stecher G, Peterson D, Filipski A, Kumar S. MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0. \u003cem\u003eMol. Biol. Evol.\u003c/em\u003e 2013; 30 (12), 2725\u0026ndash;2729. (doi: 10.1093/molbev/mst197)\u003c/li\u003e\n\u003cli\u003eLivak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. \u003cem\u003eMethods.\u003c/em\u003e 2001; 25 (4), 402\u0026ndash;408. (doi: 10.1006/meth.2001.1262)\u003c/li\u003e\n\u003cli\u003eDe Maio A. Heat Shock Proteins: Facts, Thoughts, and Dreams. \u003cem\u003eShock.\u003c/em\u003e 1999; 11 (1), 1\u0026ndash;12. (doi: 10.1097/00024382-199901000-00001)\u003c/li\u003e\n\u003cli\u003eJunprung W, Norouzitallab P, De Vos S, Tassanakajon A, Nguyen Viet D, Van Stappen G, Bossier P. Sequence and expression analysis of HSP70 family genes in \u003cem\u003eArtemia franciscana\u003c/em\u003e. \u003cem\u003eSci. Rep.\u003c/em\u003e 2019; 9 (1), 8391. (doi:10.1038/s41598-019-44884-y)\u003c/li\u003e\n\u003cli\u003eYu A, Li P, Tang T, Wang J, Chen Y, Liu L. Roles of Hsp70s in Stress Responses of Microorganisms, Plants, and Animals. \u003cem\u003eBiomed. Res. Int.\u003c/em\u003e 2015; 2015, 510319. (doi: 10.1155/2015/510319)\u003c/li\u003e\n\u003cli\u003eCui Z, Liu Y, Luan W, Li Q, Wu D, Wang S. Molecular cloning and characterization of a heat shock protein 70 gene in swimming crab (\u003cem\u003ePortunus trituberculatus\u003c/em\u003e). \u003cem\u003eFish Shellfish Immunol.\u003c/em\u003e 2010; 28 (1), 56\u0026ndash;64. (doi: 10.1016/j.fsi.2009.09.018)\u003c/li\u003e\n\u003cli\u003eKarlin S, Brocchieri L. Heat Shock Protein 70 Family: Multiple Sequence Comparisons, Function, and Evolution. \u003cem\u003eJ. Mol. Evol.\u003c/em\u003e 1998; 47 (5), 565\u0026ndash;577. (doi: 10.1007/pl00006413)\u003c/li\u003e\n\u003cli\u003eTang T, Yu A, Li P, Yang H, Liu G, Liu L. Sequence analysis of the Hsp70 family in moss and evaluation of their functions in abiotic stress responses. \u003cem\u003eSci. Rep.\u003c/em\u003e 2016; 6, 33650. (doi: 10.1038/srep33650)\u003c/li\u003e\n\u003cli\u003eVon Plehwe U, Berndt U, Conz C, Chiabudini M, Fitzke E, Sickmann A, Petersen A, Pfeifer D, Rospert S. The Hsp70 homolog Ssb is essential for glucose sensing via the SNF1 kinase network. \u003cem\u003eGenes Dev.\u003c/em\u003e 2009; 23 (17), 2102\u0026ndash;2115. (doi: 10.1101/gad.529409)\u003c/li\u003e\n\u003cli\u003eGade N, Mahapatra RK, Sonawane A, Singh VK, Doreswamy R, Saini M. Molecular Characterization of Heat Shock Protein 70-1 Gene of Goat (\u003cem\u003eCapra hircus\u003c/em\u003e). \u003cem\u003eMol. Biol. Int.\u003c/em\u003e 2010; 2010, 108429. (doi: 10.4061/2010/108429)\u003c/li\u003e\n\u003cli\u003eHunt C, Calderwood S. Characterization and sequence of a mouse hsp70 gene and its expression in mouse cell lines. \u003cem\u003eGene.\u003c/em\u003e 1990; 87 (2), 199\u0026ndash;204. (doi: 10.1016/0378-1119(90)90302-8)\u003c/li\u003e\n\u003cli\u003eKlein SL, Strausberg RL, Wagner L, Pontius J, Clifton SW, Richardson P. Genetic and genomic tools for Xenopus research: The NIH Xenopus initiative. \u003cem\u003eDev. Dyn.\u003c/em\u003e 2002; 225 (4), 384\u0026ndash;391. (doi: 10.1002/dvdy.10174)\u003c/li\u003e\n\u003cli\u003eBoorstein W, Ziegelhoffer T, Craig E. Molecular evolution of the HSP70 multigene family.\u003cem\u003e J. Mol. Evol.\u003c/em\u003e 1994; 38 (1), 1\u0026ndash;17. (doi: 10.1007/BF00175490)\u003c/li\u003e\n\u003cli\u003eHan YL, Hou CC, Du C, Zhu JQ. Molecular cloning and expression analysis of five heat shock protein 70 (HSP70) family members in \u003cem\u003eLateolabrax maculatus\u003c/em\u003e with \u003cem\u003eVibrio harveyi\u003c/em\u003e infection. \u003cem\u003eFish Shellfish Immun.\u003c/em\u003e 2017; 60, 299\u0026ndash;310. (doi: 10.1016/j.fsi.2016.11.056)\u003c/li\u003e\n\u003cli\u003eOnuoha SC, Coulstock ET, Grossmann JG, Jackson SE. Structural Studies on the Co-chaperone Hop and Its Complexes with Hsp90. \u003cem\u003eJ. Mol. Biol.\u003c/em\u003e 2008; 379 (4), 732\u0026ndash;744. (doi: 10.1016/j.jmb.2008.02.013)\u003c/li\u003e\n\u003cli\u003eLiu J, Yang WJ, Zhu XJ, Karouna Renier NK, Rao RK. Molecular cloning and expression of two HSP70 genes in the prawn, \u003cem\u003eMacrobrachium rosenbergii\u003c/em\u003e. \u003cem\u003eCell Stress Chaperones.\u003c/em\u003e 2004; 9 (3), 313\u0026ndash;323. (doi: 10.1379/csc-40r.1)\u003c/li\u003e\n\u003cli\u003eKiraga J, Mackiewicz P, Mackiewicz D, Kowalczuk M, Biecek P, Polak N, Smolarczyk K, Dudek MR, Cebrat S. The relationships between the isoelectric point and: length of proteins, taxonomy and ecology of organisms. \u003cem\u003eBMC genomics.\u003c/em\u003e 2007; 8, 163. (doi: 10.1186/1471-2164-8-163)\u003c/li\u003e\n\u003cli\u003eRout PK, Kaushik R, Ramachandran N. Differential expression pattern of heat shock protein 70 gene in tissues and heat stress phenotypes in goats during peak heat stress period. \u003cem\u003eCell Stress Chaperones.\u003c/em\u003e 2016; 21 (4), 645\u0026ndash;651. (doi: 10.1007/s12192-016-0689-1)\u003c/li\u003e\n\u003cli\u003eZhang C, Lu K, Wang J, qian Q, Yuan X, Pu C. Molecular cloning, expression \u003cem\u003eHSP70\u003c/em\u003e and its response to bacterial challenge and heat stress in \u003cem\u003eMicroptenus salmoides\u003c/em\u003e. \u003cem\u003eFish Physiol. Biochem.\u003c/em\u003e 2020; 46 (6), 2389\u0026ndash;2402. (doi: 10.1007/s10695-020-00883-9)\u003c/li\u003e\n\u003cli\u003eCostanzo JP. Overwintering adaptations and extreme freeze tolerance in a subarctic population of the wood frog, \u003cem\u003eRana sylvatica\u003c/em\u003e. \u003cem\u003eJ. Comp. Physiol. B.\u003c/em\u003e 2019; 189 (1), 1\u0026ndash;15. (doi: 10.1007/s00360-018-1189-7)\u003c/li\u003e\n\u003cli\u003eAyala A, Mu\u0026ntilde;oz MF, Arg\u0026uuml;elles S. Lipid peroxidation: production, metabolism, and signaling mechanisms of malondialdehyde and 4-hydroxy-2-nonenal. \u003cem\u003eOxidative medicine and cellular longevity.\u003c/em\u003e 2014; 2014, 360438. (doi: 10.1155/2014/360438)\u003c/li\u003e\n\u003cli\u003eAlderson TR, Kim JH, Markley JL. Dynamical Structures of Hsp70 and Hsp70-Hsp40 Complexes. \u003cem\u003eStructure\u003c/em\u003e. 2016; 24 (7): 1014\u0026ndash;1030. (doi: 10.1016/j.str.2016.05.011)\u003c/li\u003e\n\u003cli\u003eLin TT, Qu J, Wang CY, Yang X, Hu F, Hu L, Wu XF, Jiang CY, Liu WT, Han Y. Rescue of HSP70 in Spinal Neurons Alleviates Opioids-Induced Hyperalgesia via the Suppression of Endoplasmic Reticulum Stress in Rodents.\u003cem\u003e Front. Cell Dev. Biol. \u003c/em\u003e2020; 8, 269. (doi: 10.3389/fcell.2020.00269)\u003c/li\u003e\n\u003cli\u003eRoybal CN, Marmorstein LY, Vander Jagt DL, Abcouwer SF. Aberrant accumulation of fibulin-3 in the endoplasmic reticulum leads to activation of the unfolded protein response and VEGF expression. \u003cem\u003eInvest. Ophthalmol. Vis. Sci.\u003c/em\u003e 2005; 46 (11), 3973\u0026ndash;3979. (doi: 10.1167/iovs.05-0070)\u003c/li\u003e\n\u003cli\u003ePincus D. Regulation of Hsf1 and the Heat Shock Response. \u003cem\u003eAdvances in experimental medicine and biology.\u003c/em\u003e 2020; 1243, 41\u0026ndash;50. (doi: 10.1007/978-3-030-40204-4_3)\u003c/li\u003e\n\u003cli\u003eYe T, Yan Z, Chen C, Wang D, Wang A, Li T, Yang B, Ding X, Shen C. Lactoferrin attenuates cardiac fibrosis and cardiac remodeling after myocardial infarction via inhibiting mTORC1/S6K signaling pathway. \u003cem\u003eTheranostics.\u003c/em\u003e 2023; 13 (10), 3419\u0026ndash;3433. (doi: 10.7150/thno.85361)\u003c/li\u003e\n\u003cli\u003eCorre M, Lebreton A. Regulation of cold-inducible RNA-binding protein (CIRBP) in response to cellular stresses. \u003cem\u003eBiochimie.\u003c/em\u003e 2024; 217, 3\u0026ndash;9. (doi: 10.1016/j.biochi.2023.04.003)\u003c/li\u003e\n\u003cli\u003eKaya ST. Effects of diazoxide on streptozotocin induced \u0026beta; cell damage via HSP70/HSP90/TLR4/AMPK signaling pathways.\u003cem\u003e Biotech. Histochem. \u003c/em\u003e2023; 98 (3), 210\u0026ndash;219. (doi: 10.1080/10520295.2023.2168757)\u003c/li\u003e\n\u003cli\u003eTrcka F, Durech M, Vankova P, Chmelik J, Martinkova V, Hausner J, Kadek A, Marcoux J, Klumpler T, Vojtesek B, et al. Human Stress-inducible \u003cem\u003eHsp70\u003c/em\u003e Has a High Propensity to Form ATP-dependent Antiparallel Dimers That Are Differentially Regulated by Cochaperone Binding. \u003cem\u003eMol. Cell. Proteomics.\u003c/em\u003e 2019; 18 (2), 320\u0026ndash;337. (doi: 10.1074/mcp.RA118.001044)\u003c/li\u003e\n\u003cli\u003eBoudesco C, Cause S, Jego G, Garrido C. Hsp70: A Cancer Target Inside and Outside the Cell. \u003cem\u003eMethods in molecular biology (Clifton, N.J.).\u003c/em\u003e 2018; 1709, 371\u0026ndash;396. (doi: 10.1007/978-1-4939-7477-1_27)\u003c/li\u003e\n\u003cli\u003eKabakov AE, Budagova KR, Latchman DS, Kampinga HH. Stressful preconditioning and HSP70 overexpression attenuate proteotoxicity of cellular ATP depletion. \u003cem\u003eAm. J. Physiol. Cell Physiol.\u003c/em\u003e 2002; 283 (2), C521\u0026ndash;C534. (doi: 10.1152/ajpcell.00503.2001)\u003c/li\u003e\n\u003cli\u003eKong E, Li Y, Geng X, Wang J, He Y, Feng X. Ischemic preconditioning attenuates endoplasmic reticulum stress-dependent apoptosis of hepatocytes by regulating autophagy in hepatic ischemia-reperfusion injury. \u003cem\u003eInt. Immunopharmacol.\u003c/em\u003e 2023; 122, 110637. (doi: 10.1016/j.intimp.2023.110637)\u003c/li\u003e\n\u003cli\u003eIkeda K, Shiba S, Horie-Inoue K, Shimokata K, Inoue S. A stabilizing factor for mitochondrial respiratory supercomplex assembly regulates energy metabolism in muscle. \u003cem\u003eNat. Commun.\u003c/em\u003e 2013; 4, 2147. (doi: 10.1038/ncomms3147)\u003c/li\u003e\n\u003cli\u003eAvdonin PP, Markitantova YV, Poplinskaya VA, Grigoryan EN. Determination of mRNA-transcripts and heat shock proteins HSP70 and HSP90 in retina of the adult Spanish Ribbed Newt \u003cem\u003ePleurodeles waltl\u003c/em\u003e. \u003cem\u003eBiol Bull Russ Acad Sci.\u003c/em\u003e 2013; 40, 343\u0026ndash;350. (doi:10.1134/S106235901304002X)\u003c/li\u003e\n\u003cli\u003eLi HB, Du YZ. Molecular cloning and characterization of an Hsp90/70 organizing protein gene from \u003cem\u003eFrankliniella occidentalis\u003c/em\u003e (Insecta: Thysanoptera, Thripidae). Gene. 2013; 520 (2), 148\u0026ndash;155. (doi: 10.1016/j.gene.2013.02.026)\u003c/li\u003e\n\u003cli\u003eWalcott SE, Heikkila JJ. Celastrol can inhibit proteasome activity and upregulate the expression of heat shock protein genes, \u003cem\u003ehsp30\u003c/em\u003e and \u003cem\u003ehsp70\u003c/em\u003e, in \u003cem\u003eXenopus laevis\u003c/em\u003e A6 cells. \u003cem\u003eComp. Biochem. Physiol. A Mol. Integr. Physiol.\u003c/em\u003e 2010; 156 (2), 285\u0026ndash;293. (doi: 10.1016/j.cbpa.2010.02.015)\u003c/li\u003e\n\u003cli\u003eWeir JB. New methods for calculating metabolic rate with special reference to protein metabolism. J. Physiol. 1949; 109 (1-2), 1\u0026ndash;9. (doi: 10.1113/jphysiol.1949.sp004363)\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"CoHsp70, Cynops orientalis, metabolic efficiency, overexpression, stress response","lastPublishedDoi":"10.21203/rs.3.rs-6990504/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6990504/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study investigates the molecular mechanisms underlying thermal resilience in the \u003cem\u003eCynops orientalis\u003c/em\u003e (Chinese fire-bellied newt) through functional characterization of \u003cem\u003eCoHsp70\u003c/em\u003e, a cytosolic heat shock protein 70 homolog. Comparative genomic analysis revealed conserved structural domains (ATPase, substrate-binding domain, and EEVD motif) and \u0026gt;\u0026thinsp;80% sequence identity with amphibian orthologs. Tissue-specific profiling identified adipose tissue as the predominant site of \u003cem\u003eCoHsp70\u003c/em\u003e expression. Temperature-dependent transcriptional regulation exhibited bidirectional dynamics: rapid induction under acute heat stress versus progressive suppression during chronic cold exposure. \u003cem\u003eCoHsp70\u003c/em\u003e overexpression enhanced hyperthermic survival while reducing metabolic expenditure (SMR, REE) and oxygen consumption rate (OCR). Taken together, these results suggest that \u003cem\u003eCoHsp70\u003c/em\u003e is a critical modulator of amphibian temperature resilience, balancing proteostatic fidelity with energy conservation under thermal extremes.\u003c/p\u003e","manuscriptTitle":"Heat shock protein 70 in Cynops orientalis: Bidirectional thermal regulation and metabolic optimization in amphibian climatic adaptation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 12:57:14","doi":"10.21203/rs.3.rs-6990504/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-07T04:54:30+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-14T20:06:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T13:16:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"305930358824858662078160449976918517070","date":"2025-09-07T16:36:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"130459777834212930823356823841284057094","date":"2025-09-03T15:20:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-01T00:38:41+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137936899973343796329644152393241072092","date":"2025-08-18T00:51:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"316470907986854771651498533497864018433","date":"2025-08-15T11:56:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-11T13:33:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-30T08:57:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-07T08:18:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-05T07:36:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2025-07-05T07:33:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d0031592-493e-42a7-bfd0-47505d1833bf","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-12T16:09:01+00:00","versionOfRecord":{"articleIdentity":"rs-6990504","link":"https://doi.org/10.1186/s12864-025-12501-0","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2026-01-05 15:57:25","publishedOnDateReadable":"January 5th, 2026"},"versionCreatedAt":"2025-08-19 12:57:14","video":"","vorDoi":"10.1186/s12864-025-12501-0","vorDoiUrl":"https://doi.org/10.1186/s12864-025-12501-0","workflowStages":[]},"version":"v1","identity":"rs-6990504","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6990504","identity":"rs-6990504","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}