Assisted reproductive technologies lead to abnormalities in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy and implantation in mouse blastocysts

Assisted reproductive technologies lead to abnormalities in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy and implantation in mouse blastocysts | 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 Assisted reproductive technologies lead to abnormalities in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy and implantation in mouse blastocysts Jinzhu Song, Yiwen Zhang, Xiaoyu Yin, Xueqi Dong, Hao Tian, Wanting You, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7421421/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Journal of Ovarian Research → Version 1 posted 11 You are reading this latest preprint version Abstract Background Assisted reproductive technology (ART), especially in vitro fertilization (IVF), has become an important means of addressing infertility issues. Compared with natural conception (in vivo fertilization, IVO), IVF embryos are completely dependent on in vitro culture, and the in vitro environment may interfere with early embryo gene expression, thereby affecting embryo development potential. However, various adverse outcomes in offspring have been reported to be associated with ART, whereas limited research has been conducted on its effects during the early stages of embryonic development. Results This study aims to investigate the specific mechanisms by which ART affects blastocysts. Proteomics and metabolomics analyses were conducted to identify differentially expressed proteins and metabolites between IVO and IVF blastocyst stages, and enrichment analysis was performed on the differentially expressed proteins (DEPs). Proteomic analysis revealed 745 DEPs between the two groups, with 257 upregulated and 488 downregulated in IVF-derived blastocysts. Gene ontology (GO) enrichment analysis demonstrated that these DEPs were primarily enriched in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy, and implantation-related pathways. Conclusions In conclusion, we identified considerable DEPs and discussed how they agreed with previous researches illustrating altered protein expression associated with the quality of blastocysts. These findings provide valuable insights for improving ART success rates and reducing health risks in IVF-conceived offspring, highlighting their significant clinical translational potential. Assisted reproduction technology In vitro fertilization Embryo development Proteomics Offspring safety Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Infertility has been recognized as a major global public health concern threatening population health. Assisted reproductive technologies, including IVF and intracytoplasmic sperm injection (ICSI), have revolutionized infertility treatment, resulting in the birth of over 8 million ART-conceived children born worldwide [ 1 ]. Although the vast majority of ART offspring are reported to be healthy [ 2 ], accumulating evidence suggests that potential perinatal and long-term risks should not be overlooked [ 3 ]. Several studies have indicated that ART-conceived children are associated with increased hospitalization rates during early childhood [ 2 , 4 , 5 ], elevated risks of cerebral palsy [ 6 ], and higher incidences of carotid intima-media thickening [ 7 ], asthma [ 8 , 9 ], and childhood cancers [ 10 ] compared to naturally conceived offspring. Therefore, comprehensive health assessments of ART progeny and thorough evaluations of ART safety are considered essential. During ART procedures, the intrafallopian microenvironment cannot be fully replicated by non-physiological culture conditions including medium composition, temperature, humidity, gas environment, light exposure, and biomechanical stimuli. These discrepancies have been suggested to interfere with early embryonic development. Previous researches revealed that the normal function of multiple molecules during embryonic development is affected by ART. At the metabolic level, ART-generated embryos have been demonstrated to exhibit significantly reduced pyruvate content accompanied by elevated lactate accumulation, resulting in disrupted lactate metabolism. This metabolic imbalance has been closely associated with aberrant epigenetic modifications and embryonic developmental arrest [ 11 , 12 ]. Oxidative stress is considered to be one of the key contributing factors, and higher partial pressure of oxygen in in vitro culture leads to increased levels of ROS, which causes mitochondrial damage and induces apoptosis in embryos [ 13 ]. Epigenetic reprogramming abnormalities have also been demonstrated. The activity of DNA methyltransferases (DNMTs) is altered by ART, leading to aberrant differential methylation regions (DMRs) in imprinted genes[ 14 ]. In mouse embryos subjected to in vitro culture, aberrant H3K4me3 modifications have been demonstrated to be associated with the activation of epiblast (Epi) lineage-specific genes in IVF-derived extraembryonic ectoderm (ExE) tissues[ 15 ]. Embryonic aneuploidy is attributed to ART-induced spindle abnormalities, altered chromatin accessibility, and defective cell cycle checkpoints[ 16 ]. Furthermore, embryo implantation may be compromised by ART-mediated modifications of placental morphology and endometrial receptivity[ 17 ]. However, the precise molecular mechanisms underlying these ART-associated developmental perturbations remain to be fully elucidated. As proteins serve as the primary executors of biological processes, alterations in protein abundance are known to play pivotal roles in embryonic development[ 18 ]. With rapid advancements in biotechnology, proteomic technologies have been widely applied to diverse cell types, tissues, and organs to characterize protein expression profiles under specific physiological conditions. However, proteomic analysis of early embryos has long been hindered by limited biological material availability, until recent breakthroughs in microcellular proteomics were achieved[ 19 ]. Microscale proteomic approaches now enable comprehensive proteome profiling of individual cells with improved reliability and precision[ 19 ]. Nevertheless, this cutting-edge technology has not yet been systematically applied in studies investigating ART-induced embryonic developmental alterations. The proteomic landscape of ART-derived blastocysts has been reported to be extensively perturbed [ 11 ]. To elucidate the molecular mechanisms through which ART affects embryonic development, systematic profiling of protein expression patterns has become an essential research focus. In this study, state-of-the-art microcellular proteomics coupled with high-resolution untargeted metabolomics were employed to investigate ART-associated embryonic developmental perturbations, aiming to reveal dynamic protein changes during ART procedures. Our findings provide novel insights into the molecular mechanisms underlying ART-mediated effects on embryonic development. Materials and Methods Ethics The current study was carried out with the approval of the Ethic Committee of Reproductive Medicine of Reproductive Hospital of Shandong University (2022 − 138), and all experiments performed were as per relevant regulations and guidelines of the committees. In vivo blastocyst collection Mice of Institute of Cancer Research (ICR) mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. and maintained under standard conditions (12-hour light/dark cycle with free access to food and water). Female ICR mice aged 6–8 weeks were injected intraperitoneally with 5 IU pregnant mare serum gonadotropin (PMSG) (110,914,564, Ningbo Sansheng Biological Technology Co., Ltd.) at 15:00–17:00, followed by 5 IU human chorionic gonadotropin (hCG) (110,911,282, Ningbo Sansheng Biological Technology Co., Ltd.) 46–48 hours later. The presence of a vaginal plug was checked the following morning and the day of plug detection was designated as E0.5. Plug-positive females were housed individually. At E3.5, mice were euthanized and the uteri were excised. Blastocysts were rinsed from the uteri with M2 medium, washed three to five times with G-1 PLUS medium and cultured in pre-equilibrated G-1 PLUS medium under 5% CO₂ and 6% O₂ in a tabletop incubator. In vitro blastocyst collection Female ICR mice (6–8 weeks old) were injected with 5 IU PMSG at 15:00–17:00, followed by 5 IU hCG 46–48 hours later. At 14–16 hours post-hCG injection, the mice were euthanized, and the oviducts were collected and placed in M2 medium. MII oocytes were released from the ampulla under a stereomicroscope, washed with G-IVF PLUS medium, and transferred to pre-equilibrated G-IVF PLUS medium for fertilization. Sperm from adult male ICR mice (≥ 12 weeks old) were collected from the cauda epididymis and capacitated in G-IVF PLUS medium for 30 minutes to 1 hour. Capacitated sperm were added to the oocytes and fertilization was allowed to proceed for 4–6 hours. Fertilized zygotes were washed with G1-PLUS medium to remove residual sperm and cumulus cells, then transferred to pre-equilibrated G1-PLUS medium and cultured under 5% CO₂ and 6% O₂. Blastocysts were obtained approximately 96 hours post-fertilization. Protein extraction and trypsin digestion Protein extraction and trypsin digestion The zona pellucida of in vivo and in vitro blastocysts was removed using acid Table’s solution, followed washes with PBS. The blastocysts were transferred to microcentrifuge tubes, flash-frozen in liquid nitrogen, and stored at − 80°C. For protein extraction, 10 blastocysts per replicate (three replicates per group) were lysed in a buffer containing 8 M urea and 1% protease inhibitor using a high-intensity ultrasonic processor (Scientz) on ice. The lysates were centrifuged at 12,000 g for 10 minutes at 4°C, and the supernatants were collected for protein quantification using a BCA assay. For digestion, proteins were reduced with 5 mM dithiothreitol at 56°C for 30 minutes, alkylated with 11 mM iodoacetamide in the dark for 15 minutes, and diluted with 100 mM TEAB (Sigma-Aldrich, USA) to reduce urea concentration below 2 M. Trypsin was added at a 1:50 (w/w) ratio for overnight digestion, followed by a second digestion with trypsin (1:100) for 4 hours. Peptides were purified using C18 solid-phase extraction columns. Liquid chromatography-mass spectrometry analysis and database search Peptides were dissolved in mobile phase A (0.1% formic acid and 2% acetonitrile in water) and separated using an EASY-nLC 1000 ultra-high-performance liquid chromatography system. Mobile phase B consisted of 0.1% formic acid in 100% acetonitrile. The gradient elution program was as follows: 0–4 minutes, 7–16% B; 4–12 minutes, 16–26% B; 12–15 minutes, 26–40% B; 15–17 minutes, 40–80% B; 17–20 minutes, 80% B; 20–23 minutes, 80–30% B; 23–26 minutes, 30% B; 26–28 minutes, 30–80% B; 28–30 minutes, 80% B, at a flow rate of 100 nL/min. Peptides were ionized using a capillary ion source at 1.75 kV and analyzed using a timsTOF Pro mass spectrometer. Data were acquired in parallel accumulation-serial fragmentation (PASEF) mode, with a dynamic exclusion time of 30 seconds. The DIA-NN software (v1.8) was used for data analysis, with a false discovery rate (FDR) set to 1% for peptide identification. Differentially expressed proteins (DEPs) were defined as those with a fold change > 1.5 and p ≤ 0.05. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were performed using adjusted p < 0.05 as the significance threshold. High-resolution off-target metabolomics Blastocysts derived from in vivo and in vitro sources were collected (100 per group, with three biological replicates). The zona pellucida was removed using acid Table’s solution, followed by extensive washing with PBS. The blastocysts were transferred to 1.5 mL low-adsorption microcentrifuge tubes, flash-frozen in liquid nitrogen, and stored at − 80°C. For metabolite extraction, thawed samples were mixed with pre-chilled methanol/acetonitrile/water (2:2:1, v/v), vortexed, and subjected to low-temperature ultrasonication for 30 minutes. After incubation at − 20°C for 10 minutes, the samples were centrifuged at 14,000 g for 20 minutes at 4°C. The supernatant was vacuum-dried, reconstituted in 100 µL of acetonitrile/water (1:1, v/v), vortexed, and centrifuged at 14,000 g for 15 minutes at 4°C. The resulting supernatant was used for liquid chromatography-mass spectrometry (LC-MS) analysis. Metabolite separation was performed using an Agilent 1290 Infinity LC system equipped with a HILIC column. The chromatographic conditions were as follows: column temperature, 25°C; flow rate, 0.5 mL/min; injection volume, 2 µL. Mobile phase A consisted of water containing 25 mM ammonium acetate and 25 mM ammonia, while mobile phase B was acetonitrile. The gradient elution program was as follows: 0–0.5 minutes, 95% B; 0.5–7 minutes, 95–65% B; 7–8 minutes, 65–40% B; 8–9 minutes, 40% B; 9–9.1 minutes, 40–95% B; 9.1–12 minutes, 95% B. Samples were maintained at 4°C in the autosampler throughout the analysis. To minimize instrumental variability, samples were analyzed in random order, and quality control (QC) samples were interspersed to monitor system stability. Mass spectrometry was performed using an AB Triple TOF 6600 instrument in both positive and negative electrospray ionization (ESI) modes. ESI source parameters were set as follows: nebulizing gas (Gas1 and Gas2), 60; curtain gas (CUR), 30 psi; ion source temperature, 600°C; ion spray voltage (ISVF), ± 5500 V. The mass range for MS1 was 60–1000 Da, and for MS2, it was 25–1000 Da. Accumulation times were 0.20 s/spectra for MS1 and 0.05 s/spectra for MS2. Data-dependent acquisition (DDA) mode was used for MS2, with a dynamic exclusion window of 4 Da and the collection of 10 fragment ion spectra per cycle. Raw data were converted to mzXML format using ProteoWizard and processed with XCMS software for peak alignment, retention time correction, and peak area extraction. Data preprocessing included filtering out features with > 50% missing values, imputation using K-nearest neighbors (KNN), and removal of features with a relative standard deviation (RSD) > 50%. Data quality was assessed, and statistical analyses, including univariate and multivariate approaches, were performed to identify and interpret significantly altered metabolites between in vivo and in vitro blastocysts. Immunofluorescence microscopy Blastocysts were fixed in 4% paraformaldehyde at room temperature for 30 minutes, permeabilized with MPS for 20 minutes, and blocked with blocking buffer for 30 minutes. Subsequently, the blastocysts were incubated with primary antibodies diluted in blocking buffer for 1 hour. The primary antibodies used were as follows: FBP1 (1:50 dilution, ab109732, Abcam), EZHIP (1:500 dilution, ab313392, Abcam), SOD1 (1:100 dilution, ab51254, Abcam), and NLRP5 (1:100 dilution, sc-514998, Santa Cruz Biotechnology). After incubation, the blastocysts were washed three times with washing buffer (5 minutes per wash) and then incubated with secondary antibodies diluted in washing buffer for 30 minutes in the dark. The secondary antibodies included goat anti-rabbit IgG H&L (Alexa Fluor 488, 1:500 dilution, ab150081, Abcam), goat anti-rabbit IgG H&L (Alexa Fluor 647, 1:500 dilution, ab150083, Abcam), and DAPI (1:500 dilution, D3571, Life Technologies). Following three additional washes with washing buffer, the blastocysts were mounted on glass slides using 1 µL of 80% glycerol or antifade mounting medium and imaged using a laser-scanning confocal microscope (Dragonfly, Andor Technology, UK). Statistical analysis Images of blastocysts labeled with the same antibodies were captured under identical scanning settings. The average fluorescence intensity within each blastocyst was quantified using ImageJ software (National Institutes of Health, Bethesda, MD, USA). Data are presented as mean ± SEM (standard error of the mean). Statistical comparisons were performed using a two-tailed Student’s t-test, with a p-value < 0.05 considered statistically significant. Results Global proteomics characteristics between in vivo and in vitro mouse blastocysts In order to determine the differences in protein expression between in vivo blastocysts and in vitro blastocysts, the latest microcellular proteomics technology was used to perform proteomic analysis. First, two statistical methods, Pearson's Correlation Coefficient (PCC) and Principal Component Analysis (PCA), were utilized to examine the analytical approach and evaluate the statistical reproducibility of biological and technical replicates. The correlation coefficients among the biological replicates within both in vivo and in vitro blastocyst groups were greater than those between groups, and all correlation coefficients exceeded 0.9, indicating a strong inter-sample consistency (Fig. 1 A). PCA results showed that in vivo and in vitro blastocysts can be divided into two separate clusters (Fig. 1 B). A total of 54,395 peptides were identified, corresponding to 6403 proteins, of which 6,294 proteins were quantitatively comparable based on specifically resolved peptides (Fig. 1 C). Subsequently, a total of 745 DEPs were screened by a log 2 (fold change) threshold greater than 1.5, of which 257 were up-regulated and 488 were down-regulated (Fig. 1 D and 1 E). Thus, we found that in vitro blastocysts exhibited significantly altered protein expression patterns compared to in vivo blastocysts. GO and KEGG analysis of DEPs for in vivo and in vitro blastocysts To better understand the functions of the DEPs between in vivo and in vitro blastocysts, GO and KEGG enrichment analyses were performed for the screened differential proteins. GO analysis showed that altered protein expression was associated with a variety of biological processes, cellular components and molecular functions. Biological process categories with significant enrichment included “Regulation of biological process”, “organic substance metabolic process”, “cellular metabolic process”, “primary metabolic process” and “nitrogen compound metabolic process”, which involved 479, 417, 414, 390, and 350 DEPs, respectively. In the cellular component category, “Intracellular anatomical structure”, “cytoplasm”, “organelle”, “cytosol” and “membrane” showed significantly enriched representation, involving 658, 606, 573, 356, and 322 DEPs, respectively. In the molecular function category, terms such as “protein binding”, “ion binding”, “organic cyclic compound binding”, “heterocyclic compound binding” and“hydrolase activity” were significantly enriched with 409, 180, 151, 150, 133 DEPs, respectively(Fig. 2 A). In relation to the biological process, the most abundant terms pertained to inorganic ion homeostasis, metal ion homeostasis and cellular metal ion homeostasis (Fig. 2 B). With regard to cellular components, the most enriched terms were extracellular space (Fig. 2 C). Oxidoreductase activity was the most enriched term for molecular function (Fig. 2 D). KEGG classification system serves as an alternative functional annotation for proteins based on their associated biochemical pathways. All samples were annotated to six functional categories at the KEGG primary classification level, including metabolism, cellular processes, organismal systems, genetic information processing, human diseases and environmental information processing. The metabolism category in the primary classification level had the highest proportion in all samples and contained 12 second-level pathways, including carbohydrate metabolism, lipid metabolism, amino acid metabolism, metabolism of cofactors and vitamin and metabolism of other amino acids, etc. (Fig. 2 E). Among the top 20 pathways, in vivo and in vitro blastocyst differential proteins were significantly enriched in fluid shear stress and atherosclerosis, as well as glutathione metabolism pathways (Fig. 2 F). Altered glucose metabolism and pyruvate metabolism due to ART To ensure accurate and timely functionality, metabolic processes are tightly regulated by the blastocyst to meet specific metabolite requirements at distinct developmental stages. To further investigate the key proteins involved in the blastocyst development in vivo and in vitro , DEPs related to glucose metabolism as well as pyruvate metabolism were specifically analyzed. Figure 3 A represents differential proteins associated with glucose metabolism and Fig. 3 B corresponds to differential proteins linked to pyruvate metabolism. We found that more than 18 proteins, including HK1 and PGK, were differentially expressed among glucose metabolism-related proteins in in vitro blastocysts compared to in vivo blastocysts. Over 13 pyruvate metabolism-related proteins exhibited differential expression, including PKM, ODGH, etc. The proteomics data were used to identify differential expressed proteins involved in glycolysis and the TCA cycle, which are key pathways essential for embryonic development(Fig. 3 C). The expression of HK, PGK, PKM and LDHB proteins involved in the glycolysis pathway, as well as MDH and ODGH proteins involved in the TCA cycle process were decreased in in vitro blastocysts. This suggests that a large number of proteins involved in the glycometabolism are abnormally expressed in in vitro blastocysts, and that several metabolic pathways, including glycolysis and the TCA cycle, are indeed affected. Disruption of lipid metabolism due to ART Next, we studied the proteins associated with lipid metabolism. The heatmap showed that more than 87 proteins related to lipid metabolism such as GK, DAGLB, etc., showed different expression levels (Fig. 4 A). The proteomics data showed that several metabolic pathways were affected in blastocysts in vitro . To elucidate these metabolic perturbations systematically, for the first time, we performed high-resolution non-target metabolomics on mouse blastocysts in vivo and in vitro . A total of 341 metabolites were detected by high-resolution non-target metabolomics., with comparative analysis revealing nine differentially regulated metabolites. These nine differential metabolites were closely related to lipid metabolic processes. Specially, Hexanoyl-l-carnitine, Octanoylcarnitine, Acetylcarnitine, Isobutyryl-l-carnitine, Creatine, Sarcosine, Carnitine and Myristamine oxide demonstrated decreased abundance in in vitro blastocysts, whereas Palmitic acid showed increased abundance (Fig. 4 B). ART disrupts blastocyst epigenetic modification and oxidative phosphorylation The establishment of epigenetic modifications is essential for normal development after fertilization. DNA methylation and histone modifications undergo extensive reprogramming during early embryonic development. The establishment of epigenetic modifications is sensitive to variations between the in vivo and in vitro environments, as well as to various assisted reproductive manipulations. In our study, seven DNA methylation-related proteins were identified as differentially expressed between in vivo and in vitro blastocysts, among which notable differences were observed in regulatory proteins related to DNA methylation modification, such as DNMT1, UHRF1 and DNMT3B, in mouse in vivo and in vitro blastocysts (Fig. 5 A). In addition, ten histone modification-associated proteins were differentially expressed, with the H3K4me3-specific demethylase KDM2B, the histone deacetylase HDAC7 and the EZH repressor protein EZHIP showing significant downregulation in in vitro blastocysts (Fig. 5 B). During assisted reproduction, in vitro cultures and various manipulations are frequently exposed to a hyperoxic environment, which may lead to oxidative stress and impaired ATP synthesis. In the proteomics data, we identified differentially expressed proteins associated with oxidative stress. As shown in Fig. 5 C, the expression levels of antioxidant proteins such as SOD1, GSTP1, PRDX1, GSTA4, MGST3, GSTT2, PRDX2, PRDX5, GPX3 and ALB we re decreased in in vitro blastocysts, while the expression levels of GSTO1 and PRXL2B were increased, suggesting the presence of oxidative stress in in vitro blastocysts. As shown in Fig. 5 D, a total of 27 proteins related to ATP synthesis, including ATP5IFL, ATP1B1 and DNAJA1, exhibited differential expression between in vivo and in vitro blastocysts, indicating that a large number of regulatory molecules related to ATP synthesis were abnormally expressed. We further validated the results using immunofluorescence to demonstrate the differences in histone modification and ATP synthesis between in vivo and in vitro blastocysts (Fig. 5 E-H). ART disrupts blastocyst chromosomal stability and implantation competence Previous studies have shown that in vitro culture is associated with an increase incidence of aneuploid embryos, but the exact molecular mechanisms are unclear. As shown in Figs. 6 A and B, analysis of mouse in vivo and in vitro blastocyst proteomics data revealed 11 aberrantly expressed proteins related to spindle localization, including AURKB and COPS3, as well as 7 differentially expressed proteins involved in chromosome segregation, including BECN1 and RDX. These findings led us to hypothesize that in vitro culture may contribute to increased aneuploidy through dysregulation of the expression of these key molecules. Although many early embryos developed in vitro can successfully reach the blastocyst stage, their placental development potential and implantation capacity may be compromised compared to embryos naturally fertilized in vivo , resulting in a lower pregnancy rate for ART than for natural conception. As shown in Fig. 6 C, the proteomic analysis revealed aberrant expression levels of proteins associated with placental development,, including SOD1, CTSB, SPP1, KRT8, CCN1, GJA1, GJB3, CEBPA, ADA, ERF, NSDHL, ETNK1, PALLD and EOMES. Furthermore, genes involved in embryo implantation were also dysregulated. As illustrated in Fig. 6 D, a total of eight differentially expressed proteins, such as NLRP5 and SPP1, were linked to embryo implantation, of which three showed increased expression patterns and five exhibited decreased expression levels. This findings suggest that potential impairments in the implantation capacity of in vitro -derived blastocysts. Immunofluorescence staining further validated the expression patterns of these proteins (Figs. 6 E-H). Discussion The widespread use of assisted reproductive technology globally has led to increased focus on its safety and potential risks. Recent studies suggest that in vitro fertilization may contribute to a higher incidence of perinatal complications and chronic diseases in offspring [ 10 ]. These adverse outcomes are thought to arise from differences in embryonic development conditions. While in vivo fertilization occurs in an optimal physiological environment, embryos conceived through IVF are cultured in a suboptimal artificial environment, potentially compromising their developmental potential and predisposing them to long-term health risks. Given that proteins serve as the ultimate executors of molecular functions, the impact of assisted reproductive technology on embryonic development was investigated using microcellular proteomics. A total of 6,294 quantifiable proteins were identified through specific peptide analysis, among which 745 were differentially expressed. Notably, 257 proteins were up-regulated in IVF blastocysts, while 488 were up-regulated in IVO blastocysts. These differentially expressed proteins were primarily enriched in metabolic pathways, epigenetic modifications, oxidative stress, chromatin aneuploidy, and embryo implantation. The findings of Lee et al in a mouse model, including IVF-induced Warburg effect and epigenetic alterations, were highly consistent with the present study[ 11 ]. The role of metabolism in early embryonic development has garnered significant research interest in recent years. However, studies investigating metabolic perturbations induced by IVF remain limited. Nie et al. conducted proteomic analyses of mouse embryonic, fetal and placental tissues at E7.5 and E10.5 stages, demonstrating that energy and amino acid metabolism-related pathways were significantly affected in IVF-derived specimens [ 20 ]. In the current study, multiple proteins involved in glucose metabolism, pyruvate metabolism, and lipid metabolism pathways were found to be dysregulated in IVF blastocysts. Furthermore, high-resolution untargeted metabolomic analysis revealed elevated palmitic acid levels in IVF blastocysts. Since elevated palmitic acid has been previously reported to impaired embryonic development [ 21 ] [ 22 , 23 ], our findings suggest that reduced developmental potential in IVF blastocysts may be mediated by the excessive accumulation of palmitic acid. The potential therapeutic strategy of adding oleic acid to culture media to counteract the detrimental effects of palmitic acid warrants further investigation. Over recent decades, substantial evidence has demonstrated that ART procedures can disrupt normal epigenetic reprogramming during fertilization and early development, consequently affecting the embryonic epigenome and subsequent development [ 24 ] [ 25 ]. DNA methylation and histone modifications represent two pivotal epigenetic regulatory mechanisms. Aberrant genome-wide DNA methylation reprogramming has been frequently reported in human ART-derived embryos [ 26 ]. Gao et al.'s clinical trial employing preimplantation methylation screening (PIMS) revealed that embryos with whole-genome DNA methylation levels around 0.26 exhibited the highest developmental potential, with increasing deviation from this value correlating with reduced developmental competence [ 27 ]. Significant alterations in DNA methylation-related regulatory proteins, including DNMT1, UHRF1, and DNMT3B, were identified at the global proteome level in the current study, providing further evidence for epigenetic disturbances induced by assisted reproductive technology. Histone modifications, another critical epigenetic mechanism during early embryogenesis, are known to dynamically regulate chromatin structure, gene expression, and genomic stability. However, research addressing histone modification changes caused by IVF remains limited. In a previous study by Huang et al., it was demonstrated that H3K4me3 levels were significantly reduced in in vitro cultured embryos compared to in vivo derived embryos, as assessed by immunofluorescence staining[ 28 ]. Our findings further revealed that Kdm2b, a specific eraser of H3K36me2, and EZHIP, a regulator of H3K27me3 deposition, were downregulated in IVF blastocysts [ 29 , 30 ]. These observations suggest that widespread disturbances in histone modification patterns may arise as a consequence of IVF. Oxidative stress induced by IVF remains a persistent concern in the field, as various IVF procedures are frequently conducted under hyperoxic conditions that readily trigger oxidative stress. Previous studies have demonstrated that the supplementation of antioxidants such as melatonin, astaxanthin, and resveratrol in culture media can effectively improve embryonic developmental rates [ 12 ]. However, the molecular mechanisms by which IVF affects embryonic development through oxidative stress remain poorly understood. In the present study, it was found that SOD1, PRDX1, and GPX3, key enzymes involved in superoxide anion scavenging, were significantly downregulated in IVF-derived blastocysts, indicating that these embryos were subjected to oxidative stress [ 31 , 32 ]. Furthermore, GSTA4 and MGST3, critical factors in maintaining lipid metabolic homeostasis, were also downregulated in IVF blastocysts, potentially leading to the accumulation of lipid peroxidation products, disruption of cell membrane integrity, and subsequent apoptosis [ 33 , 34 ]. Oxidative stress was observed to impair mitochondrial electron transport chain function, not only exacerbating reactive oxygen species (ROS) generation but also directly interfering with proton gradient formation, thereby significantly reducing ATP synthesis efficiency [ 35 ]. Notably, STIP1, which facilitates the proper folding and assembly of mitochondrial respiratory chain complexes, was downregulated in IVF embryos, suggesting that assisted reproductive technologies may adversely affect ATP production in developing embryos [ 36 , 37 ]. Various ART-related factors may increase the risk of embryonic aneuploidy [ 16 ]. For instance, ovulation induction drugs might induce chromosome segregation errors during oocyte maturation, while in vitro culture conditions could impose stresses that promote chromosomal missegregation - though the underlying molecular mechanisms remain unclear. Our proteomic analysis identified aberrant expression of spindle-associated proteins such as AURKB and SKP1 [ 38 ] [ 39 ] and chromosome segregation regulators including PSPC1 and HNRNPUL1 [ 40 , 41 ]in IVF blastocysts compared to IVO controls. The effects of assisted reproductive technologies on placental development have been extensively studied. Aberrant DNA methylation of multiple genes in several imprinted genes, such as PEG10 and L3MBTL1, has been reported in human ART placentas [ 42 , 43 ]. Tan et al. identified disruptions in hematopoietic and angiogenic pathways along with metabolic disturbances in ART placentas, which may contribute to placental dysfunction and subsequent embryonic growth retardation or death [ 44 ]. Although many IVF-derived embryos can develop to the blastocyst stage, their implantation potential appears to be compromised compared to IVO embryos, resulting in lower post-transfer pregnancy rates [ 45 ]. We identified 19 DEPs involved in placental development and embryo implantation regulation, including several critical molecular mediators. Notably, CTSB, which promotes implantation and decidualization through pyroptosis activation, was significantly downregulated in IVF blastocysts [ 46 ]. CEBPA, a critical regulator of syncytiotrophoblast differentiation, was found to be upregulated in IVF-derived blastocysts. Elevated CEBPA expression has been associated with aberrant proliferation and apoptosis of placental trophoblasts, a phenomenon similarly observed under hyperglycemic conditions during pregnancy [ 47 ]. Abnormal expression of laminins, such as LAMB1 and LAMB2 was also detected in IVF blastocysts [ 48 ]. These findings provide valuable direction for future studies of the mechanisms underlying the effects of ART on embryo implantation. Our study demonstrates that ART procedures significantly impact multiple biological processes including metabolic pathways, epigenetic regulation, oxidative stress and ATP synthesis, placental development and embryo implantation, as well as chromosomal stability. However, certain limitations must be acknowledged. The functional validation of identified differentially expressed proteins through gene knockdown in fresh mouse blastocysts remains to be conducted. The current analysis was restricted to mouse blastocysts due to ethical considerations and limited access to human research specimens. Furthermore, potential interspecies variations between murine and human proteomes should be considered when interpreting these results. Additional investigations are warranted to further validate these findings. Abbreviations ART assisted reproductive technology ADA Adenosine Deaminase ALB Albumin ATP1B1 ATPase Na⁺/K⁺ Transporting Subunit Beta 1 ATP5IFL ATP synthase inhibitory factor subunit 1 AURKB Aurora Kinase B BECN1 Beclin-1 CCN1 Cellular Communication Network 1 CEBPA CCAAT/Enhancer Binding Protein Alpha COPS3 COP9 Signalosome Subunit 3 CTSB Cathespin B CUR curtain gas DAGLB Diacylglycerol lipase beta DDA Data-dependent acquisition DEPs differentially expressed proteins DMRs differential methylation regions DNAJA1 DnaJ homolog subfamily A member 1 DNMT1 DNA methyltransferase 1 DNMT3B DNA methyltransferase 3B DNMTs DNA methyltransferases EOMES Eomesodermin Epi epiblast ERF ETS2 Repressive Factor ESI electrospray ionization ETNK1 Ethanolamine Kinase 1 ExE extraembryonic ectoderm EZH Enhancer of Zeste Homolog EZHIP Enhancer of Zeste Homolog 2 Inhibitory Protein FDR false discovery rate GJA1 Gap Junction Protein Alpha 1 GJB3 Gap Junction Protein Beta 3 GK Glycerol kinase GO Gene ontology GPX3 Glutathione peroxidase 3 GSTA4 Glutathione S-transferase A4 GSTO1 Glutathione S-transferase omega 1 GSTP1 Glutathione S-transferase P1 GSTT2 Glutathione S-transferase T2 hCG human chorionic gonadotropin HDAC7 Histone Deacetylase 7 HK1 Hexokinase 1 HNRNPUL1 Heterogeneous Nuclear Ribonucleoprotein U-Like 1 ICR Mice of Institute of Cancer Research ICSI intracytoplasmic sperm injection ISVF ion spray voltage IVF in vitro fertilization IVO in vivo fertilization KDM2B Lysine (K) Demethylase 2B KEGG Kyoto Encyclopedia of Genes and Genomes KNN K-nearest neighbors KRT8 Keratin 8 L3MBTL1 Paternally Expressed Gene L3MBTL1 LAMB1 Laminin subunit beta-1 LAMB2 Laminin subunit beta-2 LC-MS liquid chromatography-mass spectrometry LDHB Lactate Dehydrogenase B MDH Malate Dehydrogenase MGST3 Microglutathione S-transferase 3 NLRP5 NOD-like receptor family pyrin domain containing 5 NSDHL NAD(P)H Steroid Dehydrogenase-Like ODGH Oxoglutarate Dehydrogenase Complex PALLD Palladin, Cytoskeletal Associated Protein PASEF parallel accumulation-serial fragmentation PCA Principal Component Analysis PCC Pearson's Correlation Coefficient PEG10 Paternally Expressed 10 PGK Phosphoglycerate Kinase PIMS preimplantation methylation screening PKM Pyruvate Kinase muscle PMSG pregnant mare serum gonadotropin PRDX1 Peroxiredoxin 1 PRDX2 Peroxiredoxin 2 PRDX5 Peroxiredoxin 5 PRXL2B Peroxiredoxin like 2B PSPC1 Paraspeckle Component 1 QC quality control RDX Radixin ROS Reactive Oxygen Species RSD relative standard deviation SKP1 S-phase Kinase-Associated Protein 1 SOD1 Superoxide dismutase 1 SPP1 Secreted Phosphoprotein 1 STIP1 Stress-Induced Phosphoprotein 1 TCA tricarboxylic acid cycle UHRF1 Ubiquitin-like with PHD and RING finger domains 1 Declarations Ethics approval and consent to participate The current study was carried out with the approval of the Ethic Committee of Reproductive Medicine of Reproductive Hospital of Shandong University (2022-138), and all experiments performed were as per relevant regulations and guidelines of the committees. Consent for publication Not applicable Availability of data and materials The authors are amenable to providing data upon reasonable request to the corresponding author. Competing interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This research was supported by the National Natural Science Foundation of China (323B2027), National Key R&D Program of China (2023YFA1801803) and The Fundamental Research Funds of Shandong University (2023QNTD004). Authors' contributions CZ designed the study, JS and YZ carried out the analysis and interpretation of data and wrote the manuscript, XY, XD, HT, and WY performed the experiments. CZ, KW and BL supervised the project. All the authors approved the final version of manuscript. Acknowledgements Not applicable References Rienzi L, Gracia C, Maggiulli R, LaBarbera A R, Kaser D J, Ubaldi F M, et al. Oocyte, embryo and blastocyst cryopreservation in ART: systematic review and meta-analysis comparing slow-freezing versus vitrification to produce evidence for the development of global guidance . Hum Reprod Update. 2017;23(2):139-155. Pinborg A, Wennerholm U B, and Bergh C. Long-term outcomes for children conceived by assisted reproductive technology . Fertil Steril. 2023;120(3 Pt 1):449-456. Pelkonen S, Gissler M, Koivurova S, Lehtinen S, Martikainen H, Hartikainen A L, et al. Physical health of singleton children born after frozen embryo transfer using slow freezing: a 3-year follow-up study . Hum Reprod. 2015;30(10):2411-8. Šljivančanin T and Kontić-Vučinić O. Perinatal Outcomes of Pregnancies Conceived by Assisted Reproductive Technologies . Srp Arh Celok Lek. 2015;143(9-10):632-8. De Geyter C, Calhaz-Jorge C, Kupka M S, Wyns C, Mocanu E, Motrenko T, et al. ART in Europe, 2015: results generated from European registries by ESHRE . Hum Reprod Open. 2020;2020(1):hoz038. Sullivan-Pyke C S, Senapati S, Mainigi M A, and Barnhart K T. In Vitro fertilization and adverse obstetric and perinatal outcomes . Semin Perinatol. 2017;41(6):345-353. Basatemur E, Shevlin M, and Sutcliffe A. Growth of children conceived by IVF and ICSI up to 12years of age . Reprod Biomed Online. 2010;20(1):144-9. Belva F, Henriet S, Liebaers I, Van Steirteghem A, Celestin-Westreich S, and Bonduelle M. Medical outcome of 8-year-old singleton ICSI children (born >or=32 weeks' gestation) and a spontaneously conceived comparison group . Hum Reprod. 2007;22(2):506-15. Carson C, Sacker A, Kelly Y, Redshaw M, Kurinczuk J J, and Quigley M A. Asthma in children born after infertility treatment: findings from the UK Millennium Cohort Study . Hum Reprod. 2013;28(2):471-9. Chen M and Heilbronn L K. The health outcomes of human offspring conceived by assisted reproductive technologies (ART) . J Dev Orig Health Dis. 2017;8(4):388-402. Lee S H, Liu X, Jimenez-Morales D, and Rinaudo P F. Murine blastocysts generated by in vitro fertilization show increased Warburg metabolism and altered lactate production . Elife. 2022;11( Yang W, Wang P, Cao P, Wang S, Yang Y, Su H, et al. Hypoxic in vitro culture reduces histone lactylation and impairs pre-implantation embryonic development in mice . Epigenetics Chromatin. 2021;14(1):57. Agarwal A, Maldonado Rosas I, Anagnostopoulou C, Cannarella R, Boitrelle F, Munoz L V, et al. Oxidative Stress and Assisted Reproduction: A Comprehensive Review of Its Pathophysiological Role and Strategies for Optimizing Embryo Culture Environment . Antioxidants (Basel). 2022;11(3): Canovas S, Ross P J, Kelsey G, and Coy P. DNA Methylation in Embryo Development: Epigenetic Impact of ART (Assisted Reproductive Technologies) . Bioessays. 2017;39(11): Bai D, Sun J, Chen C, Jia Y, Li Y, Liu K, et al. Aberrant H3K4me3 modification of epiblast genes of extraembryonic tissue causes placental defects and implantation failure in mouse IVF embryos . Cell Rep. 2022;39(5):110784. Vitagliano A, Paffoni A, and Viganò P. Does maternal age affect assisted reproduction technology success rates after euploid embryo transfer? A systematic review and meta-analysis . Fertil Steril. 2023;120(2):251-265. Raunig J M, Yamauchi Y, Ward M A, and Collier A C. Placental inflammation and oxidative stress in the mouse model of assisted reproduction . Placenta. 2011;32(11):852-8. Gao Y, Liu X, Tang B, Li C, Kou Z, Li L, et al. Protein Expression Landscape of Mouse Embryos during Pre-implantation Development . Cell Rep. 2017;21(13):3957-3969. Wu Q, Sui X, and Tian R. [Advances in high-throughput proteomic analysis] . Se Pu. 2021;39(2):112-117. Nie J, An L, Miao K, Hou Z, Yu Y, Tan K, et al. Comparative analysis of dynamic proteomic profiles between in vivo and in vitro produced mouse embryos during postimplantation period . J Proteome Res. 2013;12(9):3843-56. Calder M D, Chen R, MacDonald A, MacNeily Z, Leung Z C L, Adus S, et al. Effects of palmitic acid on localization of embryo cell fate and blastocyst formation gene products . Reproduction. 2022;163(3):133-143. Yousif M D, Calder M D, Du J T, Ruetz K N, Crocker K, Urquhart B L, et al. Oleic Acid Counters Impaired Blastocyst Development Induced by Palmitic Acid During Mouse Preimplantation Development: Understanding Obesity-Related Declines in Fertility . Reprod Sci. 2020;27(11):2038-2051. Wang Y, Pope I, Brennan-Craddock H, Poole E, Langbein W, Borri P, et al. A primary effect of palmitic acid on mouse oocytes is the disruption of the structure of the endoplasmic reticulum . Reproduction. 2021;163(1):45-56. Ghimire S, Mantziou V, Moris N, and Martinez Arias A. Human gastrulation: The embryo and its models . Dev Biol. 2021;474(100-108. Graham M E, Jelin A, Hoon A H, Jr., Wilms Floet A M, Levey E, and Graham E M. Assisted reproductive technology: Short- and long-term outcomes . Dev Med Child Neurol. 2023;65(1):38-49. Li G, Yu Y, Fan Y, Li C, Xu X, Duan J, et al. Genome wide abnormal DNA methylome of human blastocyst in assisted reproductive technology . J Genet Genomics. 2017;44(10):475-481. Gao Y, Yi L, Zhan J, Wang L, Yao X, Yan J, et al. A clinical study of preimplantation DNA methylation screening in assisted reproductive technology . Cell Res. 2023;33(6):483-485. Huang J C, Lei Z L, Shi L H, Miao Y L, Yang J W, Ouyang Y C, et al. Comparison of histone modifications in in vivo and in vitro fertilization mouse embryos . Biochem Biophys Res Commun. 2007;354(1):77-83. Vacík T, Lađinović D, and Raška I. KDM2A/B lysine demethylases and their alternative isoforms in development and disease . Nucleus. 2018;9(1):431-441. Richard Albert J, Urli T, Monteagudo-Sánchez A, Le Breton A, Sultanova A, David A, et al. DNA methylation shapes the Polycomb landscape during the exit from naive pluripotency . Nat Struct Mol Biol. 2025;32(2):346-357. Zhu T, Guan S, Lv D, Zhao M, Yan L, Shi L, et al. Melatonin Modulates Lipid Metabolism in Porcine Cumulus-Oocyte Complex via Its Receptors . Front Cell Dev Biol. 2021;9(648209. Leyens G, Knoops B, and Donnay I. Expression of peroxiredoxins in bovine oocytes and embryos produced in vitro . Mol Reprod Dev. 2004;69(3):243-51. Tatone C, Di Emidio G, Battaglia R, and Di Pietro C. Building a Human Ovarian Antioxidant ceRNA Network "OvAnOx": A Bioinformatic Perspective for Research on Redox-Related Ovarian Functions and Dysfunctions . Antioxidants (Basel). 2024;13(9): Lam B K. Leukotriene C(4) synthase . Prostaglandins Leukot Essent Fatty Acids. 2003;69(2-3):111-6. Marei W F A, Van den Bosch L, Pintelon I, Mohey-Elsaeed O, Bols P E J, and Leroy J. Mitochondria-targeted therapy rescues development and quality of embryos derived from oocytes matured under oxidative stress conditions: a bovine in vitro model . Hum Reprod. 2019;34(10):1984-1998. Juszkiewicz S, Peak-Chew S Y, and Hegde R S. Mechanism of chaperone recruitment and retention on mitochondrial precursors . Mol Biol Cell. 2025;36(4):ar39. Demant M, Deutsch D R, Fröhlich T, Wolf E, and Arnold G J. Proteome analysis of early lineage specification in bovine embryos . Proteomics. 2015;15(4):688-701. Xu L, Liu T, Han F, Zong Z, Wang G, Yu B, et al. AURKB and MAPK involvement in the regulation of the early stages of mouse zygote development . Sci China Life Sci. 2012;55(1):47-56. Guan Y, Leu N A, Ma J, Chmátal L, Ruthel G, Bloom J C, et al. SKP1 drives the prophase I to metaphase I transition during male meiosis . Sci Adv. 2020;6(13):eaaz2129. Shao W, Bi X, Pan Y, Gao B, Wu J, Yin Y, et al. Phase separation of RNA-binding protein promotes polymerase binding and transcription . Nat Chem Biol. 2022;18(1):70-80. Vivori C, Papasaikas P, Stadhouders R, Di Stefano B, Rubio A R, Balaguer C B, et al. Dynamics of alternative splicing during somatic cell reprogramming reveals functions for RNA-binding proteins CPSF3, hnRNP UL1, and TIA1 . Genome Biol. 2021;22(1):171. Lu L, Lv B, Huang K, Xue Z, Zhu X, and Fan G. Recent advances in preimplantation genetic diagnosis and screening . J Assist Reprod Genet. 2016;33(9):1129-34. Katari S, Turan N, Bibikova M, Erinle O, Chalian R, Foster M, et al. DNA methylation and gene expression differences in children conceived in vitro or in vivo . Hum Mol Genet. 2009;18(20):3769-78. Tan K, Zhang Z, Miao K, Yu Y, Sui L, Tian J, et al. Dynamic integrated analysis of DNA methylation and gene expression profiles in in vivo and in vitro fertilized mouse post-implantation extraembryonic and placental tissues . Mol Hum Reprod. 2016;22(7):485-98. Grädel F, von Wolff M, Kohl Schwartz A S, and Mitter V R. Low-dose clomiphene citrate does not reduce implantation and live birth rates in otherwise unstimulated modified natural cycle IVF-retrospective cohort study . Arch Gynecol Obstet. 2023;307(4):1073-1081. Li M Y, Wu Y, Tang H L, Wang Y, Li B, He Y Y, et al. Embryo-Derived Cathepsin B Promotes Implantation and Decidualization by Activating Pyroptosis . Adv Sci (Weinh). 2024;11(43):e2402299. Chu Q, Zhong X, Lu Y, and Xu Y. miR-942-5p Regulates Proliferation, Invasion and EMT of Trophoblast Cells in Gestational Diabetes by Targeting the CEBPA . Altern Ther Health Med. 2024;30(9):312-318. Roediger M, Miosge N, and Gersdorff N. Tissue distribution of the laminin beta1 and beta2 chain during embryonic and fetal human development . J Mol Histol. 2010;41(2-3):177-84. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 03 Dec, 2025 Read the published version in Journal of Ovarian Research → Version 1 posted Editorial decision: Revision requested 19 Sep, 2025 Reviews received at journal 18 Sep, 2025 Reviews received at journal 18 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviewers agreed at journal 29 Aug, 2025 Reviewers invited by journal 27 Aug, 2025 Editor assigned by journal 22 Aug, 2025 Submission checks completed at journal 22 Aug, 2025 First submitted to journal 20 Aug, 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-7421421","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":507471342,"identity":"5aefc39e-0dd3-4d57-9847-411c27074aed","order_by":0,"name":"Jinzhu Song","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Jinzhu","middleName":"","lastName":"Song","suffix":""},{"id":507471343,"identity":"6bf57fce-e40e-44bd-a998-7f03ee9c06d7","order_by":1,"name":"Yiwen Zhang","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Yiwen","middleName":"","lastName":"Zhang","suffix":""},{"id":507471344,"identity":"cbd73178-b9c9-4d1d-a0a0-a19e8247abb3","order_by":2,"name":"Xiaoyu Yin","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyu","middleName":"","lastName":"Yin","suffix":""},{"id":507471345,"identity":"ae564848-2359-49c5-b0f9-bec2877e65a9","order_by":3,"name":"Xueqi Dong","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Xueqi","middleName":"","lastName":"Dong","suffix":""},{"id":507471346,"identity":"903d76a1-1a6b-4139-b1bd-aa95f63e5503","order_by":4,"name":"Hao Tian","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"Tian","suffix":""},{"id":507471347,"identity":"44b95786-d70e-47ce-b046-f68e9e558543","order_by":5,"name":"Wanting You","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Wanting","middleName":"","lastName":"You","suffix":""},{"id":507471348,"identity":"d91262cc-57fa-46b7-909c-dfd80da54a39","order_by":6,"name":"Boyang Liu","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Boyang","middleName":"","lastName":"Liu","suffix":""},{"id":507471349,"identity":"99d68b7e-68e1-4dfc-9d3e-6f95c2559b6f","order_by":7,"name":"Keliang Wu","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Keliang","middleName":"","lastName":"Wu","suffix":""},{"id":507471350,"identity":"e988d7e1-fa9f-4683-82a4-8262e1dcd4e8","order_by":8,"name":"Chuanxin Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9UlEQVRIie2QsQrCMBCGUwKdIlkTrPgKBcEiiL5KgqBLZyeHQKGra0XRV9BFHCOFTqJrQQddnFsQ0U1tXRtxE8w33HHwfxx3AGg0vwjJqswHBpoIY/Gd0rVoIL9RAAibtmBqozr2zqfL4MCHY2GS02qHbCCNJHWLFWMSOTUrOvPgIKHNN3vkQAHpaFmsQMLqZSpCLmJmHLm/Rw0hTVhSKCbpXTNlFjMgub9FtmRqBRG3TtOnMs+3yM8KIW6/DKKwtojZ8xa/g2iw9pS3VIPekt4GYWUaM5Pe/VYbY2+dpAolewHKGk7esyHU+Vfk9jGi0Wg0f80DUG5VZZ4auMUAAAAASUVORK5CYII=","orcid":"","institution":"Shandong University","correspondingAuthor":true,"prefix":"","firstName":"Chuanxin","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2025-08-21 02:23:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7421421/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7421421/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13048-025-01892-z","type":"published","date":"2025-12-03T15:58:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90528759,"identity":"3c2edd7d-9fbc-41c0-8580-d17f4b86858b","added_by":"auto","created_at":"2025-09-03 17:41:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2137493,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic analysis of mouse IVO and IVF blastocysts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) PCC analysis of mouse IVO and IVF blastocyst proteomics. (B) PCA analysis of mouse IVO and IVF blastocyst proteomics. (C) The number of peptides and proteins identified by mouse IVO and IVF blastocyst proteomics. (D) Volcano maps of mouse IVO and IVF blastocyst DEPs. (E) Heat map of mouse IVO and IVF blastocyst DEPs.\u003c/p\u003e","description":"","filename":"FIG1.png","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/ad73ed49d8a28f4853fe8f10.png"},{"id":90528762,"identity":"1cd76423-d820-46d7-a15d-71353019feaa","added_by":"auto","created_at":"2025-09-03 17:41:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2955287,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGO and KEGG enrichment analysis of mouse IVO and IVF blastocyst proteomics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Mouse IVO and IVF blastocyst proteomics GO enrichment analysis. (B) Top 20 GO terms related to biological processes presented in the enrichment analysis of DEP within IVO and IVF blastocysts. (C) Top 20 GO terms related to cellular components presented in the enrichment analysis of DEP within IVO and IVF blastocysts. (D) Top 20 GO terms related to molecular function presented in the enrichment analysis of DEP within IVO and IVF blastocysts. (E) KEGG enrichment analysis of mouse IVO and IVF blastocyst proteomics. (F) Top 20 KEGG pathways presented in the enrichment analysis of DEP within IVO and IVF blastocysts.\u003c/p\u003e","description":"","filename":"FIG2.png","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/eea2ec0ef7a076fc2f2f7e5c.png"},{"id":90528987,"identity":"b776ead0-0b30-464f-ac21-a4f49d1893bb","added_by":"auto","created_at":"2025-09-03 17:49:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1926902,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDEPs associated with glucose metabolism, pyruvate metabolism\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) DEPs associated with glucose metabolism. (B) DEPs associated with pyruvate metabolism. (C) Glycolytic TCA Schematic diagram of the TCAs, this figure was drawn online by BioRender.\u003c/p\u003e","description":"","filename":"FIG3.png","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/e01e5d85db5a06044dee360f.png"},{"id":90529808,"identity":"24bc8e0d-8962-4df3-a8b7-82134fb81b64","added_by":"auto","created_at":"2025-09-03 17:57:38","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1667248,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferential analysis of lipid metabolism in mouse IVO and IVF blastocysts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Lipid metabolism-related DEPs. (B) Differential metabolites in IVO and IVF blastocysts.\u003c/p\u003e","description":"","filename":"FIG4.png","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/24e7392d77d5ae00c6075832.png"},{"id":90528989,"identity":"902dd4b9-9c98-4e44-b1c5-31d3befd37a1","added_by":"auto","created_at":"2025-09-03 17:49:38","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3649159,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInterference of Assisted Reproductive Technology with Epigenetic Modifications and Oxidative Phosphorylation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmap of DEPs associated with DNA methylation. (B) Heatmap of DEPs associated with histone modifications. (C) Heatmap of DEPs associated with oxidative stress. (D) Heatmap of DEPs associated with ATP synthesis. (E) Immunofluorescence staining of mouse IVO and IVF blastocysts for FBP1. FBP1 in purple and DAPI-labeled nuclei in blue, scale bar is 10 µm. (F) Statistics of FBP1 immunofluorescence staining results in mouse IVO and IVF blastocysts. (G) Immunofluorescence staining of mouse IVO and IVF blastocysts with EZHIP. EZHIP in green and DAPI-labeled nuclei in blue, scale bar is 10 µm. (H) Statistics of EZHIP immunofluorescence staining results of mouse IVO and IVF blastocysts.\u003c/p\u003e","description":"","filename":"FIG5.png","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/f804788267f19918cef2a704.png"},{"id":90528766,"identity":"9d4cc114-3416-4398-8c7b-9d1576d1f3f1","added_by":"auto","created_at":"2025-09-03 17:41:38","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":3685528,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDisruption of aneuploidy and embryo implantation by assisted reproductive technologies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Heatmap of DEPs associated with spindle localization. (B) Heatmap of DEPs associated with chromatin segregation. (C) Heatmap of DEPs associated with embryo bedding. (D) Heatmap of DEPs associated with placental development. (E) Immunofluorescence staining of mouse IVO and IVF blastocysts for SOD1. SOD1 in green and DAPI-labeled nuclei in blue, scale bar is 10 µm. (F) Statistics of SOD1 immunofluorescence staining results in mouse IVO and IVF blastocysts. (G) Immunofluorescence staining of mouse IVO and IVF blastocysts for NLRP5. NLRP5 in green and DAPI-labeled nuclei in blue, scale bar is 10 µm. (H) Statistics of immunofluorescence staining results of mouse IVO and IVF blastocyst NLRP5.\u003c/p\u003e","description":"","filename":"FIG6.png","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/0dca97006169c68e808ae415.png"},{"id":97724592,"identity":"0a7f500e-91f3-4202-983e-5d8f4027f624","added_by":"auto","created_at":"2025-12-08 16:12:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15587659,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7421421/v1/131c3ef2-8f78-4e2e-8eff-42680c10804c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assisted reproductive technologies lead to abnormalities in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy and implantation in mouse blastocysts","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInfertility has been recognized as a major global public health concern threatening population health. Assisted reproductive technologies, including IVF and intracytoplasmic sperm injection (ICSI), have revolutionized infertility treatment, resulting in the birth of over 8\u0026nbsp;million ART-conceived children born worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Although the vast majority of ART offspring are reported to be healthy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], accumulating evidence suggests that potential perinatal and long-term risks should not be overlooked [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Several studies have indicated that ART-conceived children are associated with increased hospitalization rates during early childhood [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], elevated risks of cerebral palsy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and higher incidences of carotid intima-media thickening [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], asthma [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and childhood cancers [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] compared to naturally conceived offspring. Therefore, comprehensive health assessments of ART progeny and thorough evaluations of ART safety are considered essential.\u003c/p\u003e\u003cp\u003eDuring ART procedures, the intrafallopian microenvironment cannot be fully replicated by non-physiological culture conditions including medium composition, temperature, humidity, gas environment, light exposure, and biomechanical stimuli. These discrepancies have been suggested to interfere with early embryonic development. Previous researches revealed that the normal function of multiple molecules during embryonic development is affected by ART. At the metabolic level, ART-generated embryos have been demonstrated to exhibit significantly reduced pyruvate content accompanied by elevated lactate accumulation, resulting in disrupted lactate metabolism. This metabolic imbalance has been closely associated with aberrant epigenetic modifications and embryonic developmental arrest [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Oxidative stress is considered to be one of the key contributing factors, and higher partial pressure of oxygen in \u003cem\u003ein vitro\u003c/em\u003e culture leads to increased levels of ROS, which causes mitochondrial damage and induces apoptosis in embryos [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Epigenetic reprogramming abnormalities have also been demonstrated. The activity of DNA methyltransferases (DNMTs) is altered by ART, leading to aberrant differential methylation regions (DMRs) in imprinted genes[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In mouse embryos subjected to \u003cem\u003ein vitro\u003c/em\u003e culture, aberrant H3K4me3 modifications have been demonstrated to be associated with the activation of epiblast (Epi) lineage-specific genes in IVF-derived extraembryonic ectoderm (ExE) tissues[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Embryonic aneuploidy is attributed to ART-induced spindle abnormalities, altered chromatin accessibility, and defective cell cycle checkpoints[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, embryo implantation may be compromised by ART-mediated modifications of placental morphology and endometrial receptivity[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. However, the precise molecular mechanisms underlying these ART-associated developmental perturbations remain to be fully elucidated.\u003c/p\u003e\u003cp\u003eAs proteins serve as the primary executors of biological processes, alterations in protein abundance are known to play pivotal roles in embryonic development[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. With rapid advancements in biotechnology, proteomic technologies have been widely applied to diverse cell types, tissues, and organs to characterize protein expression profiles under specific physiological conditions. However, proteomic analysis of early embryos has long been hindered by limited biological material availability, until recent breakthroughs in microcellular proteomics were achieved[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Microscale proteomic approaches now enable comprehensive proteome profiling of individual cells with improved reliability and precision[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Nevertheless, this cutting-edge technology has not yet been systematically applied in studies investigating ART-induced embryonic developmental alterations.\u003c/p\u003e\u003cp\u003eThe proteomic landscape of ART-derived blastocysts has been reported to be extensively perturbed [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. To elucidate the molecular mechanisms through which ART affects embryonic development, systematic profiling of protein expression patterns has become an essential research focus. In this study, state-of-the-art microcellular proteomics coupled with high-resolution untargeted metabolomics were employed to investigate ART-associated embryonic developmental perturbations, aiming to reveal dynamic protein changes during ART procedures. Our findings provide novel insights into the molecular mechanisms underlying ART-mediated effects on embryonic development.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eEthics\u003c/h2\u003e\u003cp\u003e The current study was carried out with the approval of the Ethic Committee of Reproductive Medicine of Reproductive Hospital of Shandong University (2022\u0026thinsp;\u0026minus;\u0026thinsp;138), and all experiments performed were as per relevant regulations and guidelines of the committees.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn vivo\u003c/b\u003e \u003cb\u003eblastocyst collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMice of Institute of Cancer Research (ICR) mice were purchased from Beijing Vital River Laboratory Animal Technology Co., Ltd. and maintained under standard conditions (12-hour light/dark cycle with free access to food and water). Female ICR mice aged 6\u0026ndash;8 weeks were injected intraperitoneally with 5 IU pregnant mare serum gonadotropin (PMSG) (110,914,564, Ningbo Sansheng Biological Technology Co., Ltd.) at 15:00\u0026ndash;17:00, followed by 5 IU human chorionic gonadotropin (hCG) (110,911,282, Ningbo Sansheng Biological Technology Co., Ltd.) 46\u0026ndash;48 hours later. The presence of a vaginal plug was checked the following morning and the day of plug detection was designated as E0.5. Plug-positive females were housed individually. At E3.5, mice were euthanized and the uteri were excised. Blastocysts were rinsed from the uteri with M2 medium, washed three to five times with G-1 PLUS medium and cultured in pre-equilibrated G-1 PLUS medium under 5% CO₂ and 6% O₂ in a tabletop incubator.\u003c/p\u003e\u003cp\u003e\u003cb\u003eIn vitro\u003c/b\u003e \u003cb\u003eblastocyst collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFemale ICR mice (6\u0026ndash;8 weeks old) were injected with 5 IU PMSG at 15:00\u0026ndash;17:00, followed by 5 IU hCG 46\u0026ndash;48 hours later. At 14\u0026ndash;16 hours post-hCG injection, the mice were euthanized, and the oviducts were collected and placed in M2 medium. MII oocytes were released from the ampulla under a stereomicroscope, washed with G-IVF PLUS medium, and transferred to pre-equilibrated G-IVF PLUS medium for fertilization. Sperm from adult male ICR mice (\u0026ge;\u0026thinsp;12 weeks old) were collected from the cauda epididymis and capacitated in G-IVF PLUS medium for 30 minutes to 1 hour. Capacitated sperm were added to the oocytes and fertilization was allowed to proceed for 4\u0026ndash;6 hours. Fertilized zygotes were washed with G1-PLUS medium to remove residual sperm and cumulus cells, then transferred to pre-equilibrated G1-PLUS medium and cultured under 5% CO₂ and 6% O₂. Blastocysts were obtained approximately 96 hours post-fertilization.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProtein extraction and trypsin digestion\u003c/h3\u003e\n\u003cdiv class=\"Heading\"\u003eProtein extraction and trypsin digestion\u003c/div\u003e\u003cp\u003eThe zona pellucida of \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts was removed using acid Table\u0026rsquo;s solution, followed washes with PBS. The blastocysts were transferred to microcentrifuge tubes, flash-frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. For protein extraction, 10 blastocysts per replicate (three replicates per group) were lysed in a buffer containing 8 M urea and 1% protease inhibitor using a high-intensity ultrasonic processor (Scientz) on ice. The lysates were centrifuged at 12,000 g for 10 minutes at 4\u0026deg;C, and the supernatants were collected for protein quantification using a BCA assay. For digestion, proteins were reduced with 5 mM dithiothreitol at 56\u0026deg;C for 30 minutes, alkylated with 11 mM iodoacetamide in the dark for 15 minutes, and diluted with 100 mM TEAB (Sigma-Aldrich, USA) to reduce urea concentration below 2 M. Trypsin was added at a 1:50 (w/w) ratio for overnight digestion, followed by a second digestion with trypsin (1:100) for 4 hours. Peptides were purified using C18 solid-phase extraction columns.\u003c/p\u003e\n\u003ch3\u003eLiquid chromatography-mass spectrometry analysis and database search\u003c/h3\u003e\n\u003cp\u003ePeptides were dissolved in mobile phase A (0.1% formic acid and 2% acetonitrile in water) and separated using an EASY-nLC 1000 ultra-high-performance liquid chromatography system. Mobile phase B consisted of 0.1% formic acid in 100% acetonitrile. The gradient elution program was as follows: 0\u0026ndash;4 minutes, 7\u0026ndash;16% B; 4\u0026ndash;12 minutes, 16\u0026ndash;26% B; 12\u0026ndash;15 minutes, 26\u0026ndash;40% B; 15\u0026ndash;17 minutes, 40\u0026ndash;80% B; 17\u0026ndash;20 minutes, 80% B; 20\u0026ndash;23 minutes, 80\u0026ndash;30% B; 23\u0026ndash;26 minutes, 30% B; 26\u0026ndash;28 minutes, 30\u0026ndash;80% B; 28\u0026ndash;30 minutes, 80% B, at a flow rate of 100 nL/min. Peptides were ionized using a capillary ion source at 1.75 kV and analyzed using a timsTOF Pro mass spectrometer. Data were acquired in parallel accumulation-serial fragmentation (PASEF) mode, with a dynamic exclusion time of 30 seconds. The DIA-NN software (v1.8) was used for data analysis, with a false discovery rate (FDR) set to 1% for peptide identification. Differentially expressed proteins (DEPs) were defined as those with a fold change\u0026thinsp;\u0026gt;\u0026thinsp;1.5 and p\u0026thinsp;\u0026le;\u0026thinsp;0.05. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were performed using adjusted p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the significance threshold.\u003c/p\u003e\n\u003ch3\u003eHigh-resolution off-target metabolomics\u003c/h3\u003e\n\u003cp\u003eBlastocysts derived from \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e sources were collected (100 per group, with three biological replicates). The zona pellucida was removed using acid Table\u0026rsquo;s solution, followed by extensive washing with PBS. The blastocysts were transferred to 1.5 mL low-adsorption microcentrifuge tubes, flash-frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. For metabolite extraction, thawed samples were mixed with pre-chilled methanol/acetonitrile/water (2:2:1, v/v), vortexed, and subjected to low-temperature ultrasonication for 30 minutes. After incubation at \u0026minus;\u0026thinsp;20\u0026deg;C for 10 minutes, the samples were centrifuged at 14,000 g for 20 minutes at 4\u0026deg;C. The supernatant was vacuum-dried, reconstituted in 100 \u0026micro;L of acetonitrile/water (1:1, v/v), vortexed, and centrifuged at 14,000 g for 15 minutes at 4\u0026deg;C. The resulting supernatant was used for liquid chromatography-mass spectrometry (LC-MS) analysis.\u003c/p\u003e\u003cp\u003eMetabolite separation was performed using an Agilent 1290 Infinity LC system equipped with a HILIC column. The chromatographic conditions were as follows: column temperature, 25\u0026deg;C; flow rate, 0.5 mL/min; injection volume, 2 \u0026micro;L. Mobile phase A consisted of water containing 25 mM ammonium acetate and 25 mM ammonia, while mobile phase B was acetonitrile. The gradient elution program was as follows: 0\u0026ndash;0.5 minutes, 95% B; 0.5\u0026ndash;7 minutes, 95\u0026ndash;65% B; 7\u0026ndash;8 minutes, 65\u0026ndash;40% B; 8\u0026ndash;9 minutes, 40% B; 9\u0026ndash;9.1 minutes, 40\u0026ndash;95% B; 9.1\u0026ndash;12 minutes, 95% B. Samples were maintained at 4\u0026deg;C in the autosampler throughout the analysis. To minimize instrumental variability, samples were analyzed in random order, and quality control (QC) samples were interspersed to monitor system stability. Mass spectrometry was performed using an AB Triple TOF 6600 instrument in both positive and negative electrospray ionization (ESI) modes. ESI source parameters were set as follows: nebulizing gas (Gas1 and Gas2), 60; curtain gas (CUR), 30 psi; ion source temperature, 600\u0026deg;C; ion spray voltage (ISVF), \u0026plusmn;\u0026thinsp;5500 V. The mass range for MS1 was 60\u0026ndash;1000 Da, and for MS2, it was 25\u0026ndash;1000 Da. Accumulation times were 0.20 s/spectra for MS1 and 0.05 s/spectra for MS2. Data-dependent acquisition (DDA) mode was used for MS2, with a dynamic exclusion window of 4 Da and the collection of 10 fragment ion spectra per cycle.\u003c/p\u003e\u003cp\u003eRaw data were converted to mzXML format using ProteoWizard and processed with XCMS software for peak alignment, retention time correction, and peak area extraction. Data preprocessing included filtering out features with \u0026gt;\u0026thinsp;50% missing values, imputation using K-nearest neighbors (KNN), and removal of features with a relative standard deviation (RSD)\u0026thinsp;\u0026gt;\u0026thinsp;50%. Data quality was assessed, and statistical analyses, including univariate and multivariate approaches, were performed to identify and interpret significantly altered metabolites between \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts.\u003c/p\u003e\n\u003ch3\u003eImmunofluorescence microscopy\u003c/h3\u003e\n\u003cp\u003eBlastocysts were fixed in 4% paraformaldehyde at room temperature for 30 minutes, permeabilized with MPS for 20 minutes, and blocked with blocking buffer for 30 minutes. Subsequently, the blastocysts were incubated with primary antibodies diluted in blocking buffer for 1 hour. The primary antibodies used were as follows: FBP1 (1:50 dilution, ab109732, Abcam), EZHIP (1:500 dilution, ab313392, Abcam), SOD1 (1:100 dilution, ab51254, Abcam), and NLRP5 (1:100 dilution, sc-514998, Santa Cruz Biotechnology). After incubation, the blastocysts were washed three times with washing buffer (5 minutes per wash) and then incubated with secondary antibodies diluted in washing buffer for 30 minutes in the dark. The secondary antibodies included goat anti-rabbit IgG H\u0026amp;L (Alexa Fluor 488, 1:500 dilution, ab150081, Abcam), goat anti-rabbit IgG H\u0026amp;L (Alexa Fluor 647, 1:500 dilution, ab150083, Abcam), and DAPI (1:500 dilution, D3571, Life Technologies). Following three additional washes with washing buffer, the blastocysts were mounted on glass slides using 1 \u0026micro;L of 80% glycerol or antifade mounting medium and imaged using a laser-scanning confocal microscope (Dragonfly, Andor Technology, UK).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eImages of blastocysts labeled with the same antibodies were captured under identical scanning settings. The average fluorescence intensity within each blastocyst was quantified using ImageJ software (National Institutes of Health, Bethesda, MD, USA). Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SEM (standard error of the mean). Statistical comparisons were performed using a two-tailed Student\u0026rsquo;s t-test, with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eGlobal proteomics characteristics between\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e \u003cb\u003emouse blastocysts\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to determine the differences in protein expression between \u003cem\u003ein vivo\u003c/em\u003e blastocysts and \u003cem\u003ein vitro\u003c/em\u003e blastocysts, the latest microcellular proteomics technology was used to perform proteomic analysis. First, two statistical methods, Pearson's Correlation Coefficient (PCC) and Principal Component Analysis (PCA), were utilized to examine the analytical approach and evaluate the statistical reproducibility of biological and technical replicates. The correlation coefficients among the biological replicates within both \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocyst groups were greater than those between groups, and all correlation coefficients exceeded 0.9, indicating a strong inter-sample consistency (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). PCA results showed that \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts can be divided into two separate clusters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). A total of 54,395 peptides were identified, corresponding to 6403 proteins, of which 6,294 proteins were quantitatively comparable based on specifically resolved peptides (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). Subsequently, a total of 745 DEPs were screened by a log 2 (fold change) threshold greater than 1.5, of which 257 were up-regulated and 488 were down-regulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE). Thus, we found that \u003cem\u003ein vitro\u003c/em\u003e blastocysts exhibited significantly altered protein expression patterns compared to \u003cem\u003ein vivo\u003c/em\u003e blastocysts.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eGO and KEGG analysis of DEPs for\u003c/b\u003e \u003cb\u003ein vivo\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003ein vitro\u003c/b\u003e \u003cb\u003eblastocysts\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo better understand the functions of the DEPs between \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts, GO and KEGG enrichment analyses were performed for the screened differential proteins. GO analysis showed that altered protein expression was associated with a variety of biological processes, cellular components and molecular functions. Biological process categories with significant enrichment included \u0026ldquo;Regulation of biological process\u0026rdquo;, \u0026ldquo;organic substance metabolic process\u0026rdquo;, \u0026ldquo;cellular metabolic process\u0026rdquo;, \u0026ldquo;primary metabolic process\u0026rdquo; and \u0026ldquo;nitrogen compound metabolic process\u0026rdquo;, which involved 479, 417, 414, 390, and 350 DEPs, respectively. In the cellular component category, \u0026ldquo;Intracellular anatomical structure\u0026rdquo;, \u0026ldquo;cytoplasm\u0026rdquo;, \u0026ldquo;organelle\u0026rdquo;, \u0026ldquo;cytosol\u0026rdquo; and \u0026ldquo;membrane\u0026rdquo; showed significantly enriched representation, involving 658, 606, 573, 356, and 322 DEPs, respectively. In the molecular function category, terms such as \u0026ldquo;protein binding\u0026rdquo;, \u0026ldquo;ion binding\u0026rdquo;, \u0026ldquo;organic cyclic compound binding\u0026rdquo;, \u0026ldquo;heterocyclic compound binding\u0026rdquo; and\u0026ldquo;hydrolase activity\u0026rdquo; were significantly enriched with 409, 180, 151, 150, 133 DEPs, respectively(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). In relation to the biological process, the most abundant terms pertained to inorganic ion homeostasis, metal ion homeostasis and cellular metal ion homeostasis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). With regard to cellular components, the most enriched terms were extracellular space (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Oxidoreductase activity was the most enriched term for molecular function (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eKEGG classification system serves as an alternative functional annotation for proteins based on their associated biochemical pathways. All samples were annotated to six functional categories at the KEGG primary classification level, including metabolism, cellular processes, organismal systems, genetic information processing, human diseases and environmental information processing. The metabolism category in the primary classification level had the highest proportion in all samples and contained 12 second-level pathways, including carbohydrate metabolism, lipid metabolism, amino acid metabolism, metabolism of cofactors and vitamin and metabolism of other amino acids, etc. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Among the top 20 pathways, \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocyst differential proteins were significantly enriched in fluid shear stress and atherosclerosis, as well as glutathione metabolism pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF).\u003c/p\u003e\n\u003ch3\u003eAltered glucose metabolism and pyruvate metabolism due to ART\u003c/h3\u003e\n\u003cp\u003eTo ensure accurate and timely functionality, metabolic processes are tightly regulated by the blastocyst to meet specific metabolite requirements at distinct developmental stages. To further investigate the key proteins involved in the blastocyst development \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e, DEPs related to glucose metabolism as well as pyruvate metabolism were specifically analyzed. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA represents differential proteins associated with glucose metabolism and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB corresponds to differential proteins linked to pyruvate metabolism. We found that more than 18 proteins, including HK1 and PGK, were differentially expressed among glucose metabolism-related proteins in \u003cem\u003ein vitro\u003c/em\u003e blastocysts compared to \u003cem\u003ein vivo\u003c/em\u003e blastocysts. Over 13 pyruvate metabolism-related proteins exhibited differential expression, including PKM, ODGH, etc. The proteomics data were used to identify differential expressed proteins involved in glycolysis and the TCA cycle, which are key pathways essential for embryonic development(Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The expression of HK, PGK, PKM and LDHB proteins involved in the glycolysis pathway, as well as MDH and ODGH proteins involved in the TCA cycle process were decreased in \u003cem\u003ein vitro\u003c/em\u003e blastocysts. This suggests that a large number of proteins involved in the glycometabolism are abnormally expressed in \u003cem\u003ein vitro\u003c/em\u003e blastocysts, and that several metabolic pathways, including glycolysis and the TCA cycle, are indeed affected.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eDisruption of lipid metabolism due to ART\u003c/h2\u003e\u003cp\u003eNext, we studied the proteins associated with lipid metabolism. The heatmap showed that more than 87 proteins related to lipid metabolism such as GK, DAGLB, etc., showed different expression levels (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The proteomics data showed that several metabolic pathways were affected in blastocysts \u003cem\u003ein vitro\u003c/em\u003e. To elucidate these metabolic perturbations systematically, for the first time, we performed high-resolution non-target metabolomics on mouse blastocysts \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e. A total of 341 metabolites were detected by high-resolution non-target metabolomics., with comparative analysis revealing nine differentially regulated metabolites. These nine differential metabolites were closely related to lipid metabolic processes. Specially, Hexanoyl-l-carnitine, Octanoylcarnitine, Acetylcarnitine, Isobutyryl-l-carnitine, Creatine, Sarcosine, Carnitine and Myristamine oxide demonstrated decreased abundance in \u003cem\u003ein vitro\u003c/em\u003e blastocysts, whereas Palmitic acid showed increased abundance (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eART disrupts blastocyst epigenetic modification and oxidative phosphorylation\u003c/h2\u003e\u003cp\u003eThe establishment of epigenetic modifications is essential for normal development after fertilization. DNA methylation and histone modifications undergo extensive reprogramming during early embryonic development. The establishment of epigenetic modifications is sensitive to variations between the \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e environments, as well as to various assisted reproductive manipulations. In our study, seven DNA methylation-related proteins were identified as differentially expressed between \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts, among which notable differences were observed in regulatory proteins related to DNA methylation modification, such as DNMT1, UHRF1 and DNMT3B, in mouse \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). In addition, ten histone modification-associated proteins were differentially expressed, with the H3K4me3-specific demethylase KDM2B, the histone deacetylase HDAC7 and the EZH repressor protein EZHIP showing significant downregulation in \u003cem\u003ein vitro\u003c/em\u003e blastocysts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eDuring assisted reproduction, \u003cem\u003ein vitro\u003c/em\u003e cultures and various manipulations are frequently exposed to a hyperoxic environment, which may lead to oxidative stress and impaired ATP synthesis. In the proteomics data, we identified differentially expressed proteins associated with oxidative stress. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC, the expression levels of antioxidant proteins such as SOD1, GSTP1, PRDX1, GSTA4, MGST3, GSTT2, PRDX2, PRDX5, GPX3 and ALB we\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003ere\u003c/span\u003e decreased in \u003cem\u003ein vitro\u003c/em\u003e blastocysts, while the expression levels of GSTO1 and PRXL2B were increased, suggesting the presence of oxidative stress in \u003cem\u003ein vitro\u003c/em\u003e blastocysts. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD, a total of 27 proteins related to ATP synthesis, including ATP5IFL, ATP1B1 and DNAJA1, exhibited differential expression between \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts, indicating that a large number of regulatory molecules related to ATP synthesis were abnormally expressed. We further validated the results using immunofluorescence to demonstrate the differences in histone modification and ATP synthesis between \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocysts (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE-H).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eART disrupts blastocyst chromosomal stability and implantation competence\u003c/h2\u003e\u003cp\u003ePrevious studies have shown that \u003cem\u003ein vitro\u003c/em\u003e culture is associated with an increase incidence of aneuploid embryos, but the exact molecular mechanisms are unclear. As shown in Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eA and B, analysis of mouse \u003cem\u003ein vivo\u003c/em\u003e and \u003cem\u003ein vitro\u003c/em\u003e blastocyst proteomics data revealed 11 aberrantly expressed proteins related to spindle localization, including AURKB and COPS3, as well as 7 differentially expressed proteins involved in chromosome segregation, including BECN1 and RDX. These findings led us to hypothesize that \u003cem\u003ein vitro\u003c/em\u003e culture may contribute to increased aneuploidy through dysregulation of the expression of these key molecules.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlthough many early embryos developed \u003cem\u003ein vitro\u003c/em\u003e can successfully reach the blastocyst stage, their placental development potential and implantation capacity may be compromised compared to embryos naturally fertilized \u003cem\u003ein vivo\u003c/em\u003e, resulting in a lower pregnancy rate for ART than for natural conception. As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eC, the proteomic analysis revealed aberrant expression levels of proteins associated with placental development,, including SOD1, CTSB, SPP1, KRT8, CCN1, GJA1, GJB3, CEBPA, ADA, ERF, NSDHL, ETNK1, PALLD and EOMES. Furthermore, genes involved in embryo implantation were also dysregulated. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eD, a total of eight differentially expressed proteins, such as NLRP5 and SPP1, were linked to embryo implantation, of which three showed increased expression patterns and five exhibited decreased expression levels. This findings suggest that potential impairments in the implantation capacity of \u003cem\u003ein vitro\u003c/em\u003e-derived blastocysts. Immunofluorescence staining further validated the expression patterns of these proteins (Figs.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003eE-H).\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe widespread use of assisted reproductive technology globally has led to increased focus on its safety and potential risks. Recent studies suggest that \u003cem\u003ein vitro\u003c/em\u003e fertilization may contribute to a higher incidence of perinatal complications and chronic diseases in offspring [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These adverse outcomes are thought to arise from differences in embryonic development conditions. While \u003cem\u003ein vivo\u003c/em\u003e fertilization occurs in an optimal physiological environment, embryos conceived through IVF are cultured in a suboptimal artificial environment, potentially compromising their developmental potential and predisposing them to long-term health risks.\u003c/p\u003e\u003cp\u003eGiven that proteins serve as the ultimate executors of molecular functions, the impact of assisted reproductive technology on embryonic development was investigated using microcellular proteomics. A total of 6,294 quantifiable proteins were identified through specific peptide analysis, among which 745 were differentially expressed. Notably, 257 proteins were up-regulated in IVF blastocysts, while 488 were up-regulated in IVO blastocysts. These differentially expressed proteins were primarily enriched in metabolic pathways, epigenetic modifications, oxidative stress, chromatin aneuploidy, and embryo implantation. The findings of Lee et al in a mouse model, including IVF-induced Warburg effect and epigenetic alterations, were highly consistent with the present study[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe role of metabolism in early embryonic development has garnered significant research interest in recent years. However, studies investigating metabolic perturbations induced by IVF remain limited. Nie et al. conducted proteomic analyses of mouse embryonic, fetal and placental tissues at E7.5 and E10.5 stages, demonstrating that energy and amino acid metabolism-related pathways were significantly affected in IVF-derived specimens [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In the current study, multiple proteins involved in glucose metabolism, pyruvate metabolism, and lipid metabolism pathways were found to be dysregulated in IVF blastocysts. Furthermore, high-resolution untargeted metabolomic analysis revealed elevated palmitic acid levels in IVF blastocysts. Since elevated palmitic acid has been previously reported to impaired embryonic development [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], our findings suggest that reduced developmental potential in IVF blastocysts may be mediated by the excessive accumulation of palmitic acid. The potential therapeutic strategy of adding oleic acid to culture media to counteract the detrimental effects of palmitic acid warrants further investigation.\u003c/p\u003e\u003cp\u003eOver recent decades, substantial evidence has demonstrated that ART procedures can disrupt normal epigenetic reprogramming during fertilization and early development, consequently affecting the embryonic epigenome and subsequent development [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. DNA methylation and histone modifications represent two pivotal epigenetic regulatory mechanisms. Aberrant genome-wide DNA methylation reprogramming has been frequently reported in human ART-derived embryos [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Gao et al.'s clinical trial employing preimplantation methylation screening (PIMS) revealed that embryos with whole-genome DNA methylation levels around 0.26 exhibited the highest developmental potential, with increasing deviation from this value correlating with reduced developmental competence [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Significant alterations in DNA methylation-related regulatory proteins, including DNMT1, UHRF1, and DNMT3B, were identified at the global proteome level in the current study, providing further evidence for epigenetic disturbances induced by assisted reproductive technology. Histone modifications, another critical epigenetic mechanism during early embryogenesis, are known to dynamically regulate chromatin structure, gene expression, and genomic stability. However, research addressing histone modification changes caused by IVF remains limited. In a previous study by Huang et al., it was demonstrated that H3K4me3 levels were significantly reduced in \u003cem\u003ein vitro\u003c/em\u003e cultured embryos compared to \u003cem\u003ein vivo\u003c/em\u003e derived embryos, as assessed by immunofluorescence staining[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Our findings further revealed that Kdm2b, a specific eraser of H3K36me2, and EZHIP, a regulator of H3K27me3 deposition, were downregulated in IVF blastocysts [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. These observations suggest that widespread disturbances in histone modification patterns may arise as a consequence of IVF.\u003c/p\u003e\u003cp\u003eOxidative stress induced by IVF remains a persistent concern in the field, as various IVF procedures are frequently conducted under hyperoxic conditions that readily trigger oxidative stress. Previous studies have demonstrated that the supplementation of antioxidants such as melatonin, astaxanthin, and resveratrol in culture media can effectively improve embryonic developmental rates [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, the molecular mechanisms by which IVF affects embryonic development through oxidative stress remain poorly understood. In the present study, it was found that SOD1, PRDX1, and GPX3, key enzymes involved in superoxide anion scavenging, were significantly downregulated in IVF-derived blastocysts, indicating that these embryos were subjected to oxidative stress [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Furthermore, GSTA4 and MGST3, critical factors in maintaining lipid metabolic homeostasis, were also downregulated in IVF blastocysts, potentially leading to the accumulation of lipid peroxidation products, disruption of cell membrane integrity, and subsequent apoptosis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Oxidative stress was observed to impair mitochondrial electron transport chain function, not only exacerbating reactive oxygen species (ROS) generation but also directly interfering with proton gradient formation, thereby significantly reducing ATP synthesis efficiency [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Notably, STIP1, which facilitates the proper folding and assembly of mitochondrial respiratory chain complexes, was downregulated in IVF embryos, suggesting that assisted reproductive technologies may adversely affect ATP production in developing embryos [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eVarious ART-related factors may increase the risk of embryonic aneuploidy [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. For instance, ovulation induction drugs might induce chromosome segregation errors during oocyte maturation, while \u003cem\u003ein vitro\u003c/em\u003e culture conditions could impose stresses that promote chromosomal missegregation - though the underlying molecular mechanisms remain unclear. Our proteomic analysis identified aberrant expression of spindle-associated proteins such as AURKB and SKP1 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] and chromosome segregation regulators including PSPC1 and HNRNPUL1 [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]in IVF blastocysts compared to IVO controls.\u003c/p\u003e\u003cp\u003eThe effects of assisted reproductive technologies on placental development have been extensively studied. Aberrant DNA methylation of multiple genes in several imprinted genes, such as PEG10 and L3MBTL1, has been reported in human ART placentas [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Tan et al. identified disruptions in hematopoietic and angiogenic pathways along with metabolic disturbances in ART placentas, which may contribute to placental dysfunction and subsequent embryonic growth retardation or death [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Although many IVF-derived embryos can develop to the blastocyst stage, their implantation potential appears to be compromised compared to IVO embryos, resulting in lower post-transfer pregnancy rates [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. We identified 19 DEPs involved in placental development and embryo implantation regulation, including several critical molecular mediators. Notably, CTSB, which promotes implantation and decidualization through pyroptosis activation, was significantly downregulated in IVF blastocysts [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. CEBPA, a critical regulator of syncytiotrophoblast differentiation, was found to be upregulated in IVF-derived blastocysts. Elevated CEBPA expression has been associated with aberrant proliferation and apoptosis of placental trophoblasts, a phenomenon similarly observed under hyperglycemic conditions during pregnancy [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Abnormal expression of laminins, such as LAMB1 and LAMB2 was also detected in IVF blastocysts [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. These findings provide valuable direction for future studies of the mechanisms underlying the effects of ART on embryo implantation.\u003c/p\u003e\u003cp\u003eOur study demonstrates that ART procedures significantly impact multiple biological processes including metabolic pathways, epigenetic regulation, oxidative stress and ATP synthesis, placental development and embryo implantation, as well as chromosomal stability. However, certain limitations must be acknowledged. The functional validation of identified differentially expressed proteins through gene knockdown in fresh mouse blastocysts remains to be conducted. The current analysis was restricted to mouse blastocysts due to ethical considerations and limited access to human research specimens. Furthermore, potential interspecies variations between murine and human proteomes should be considered when interpreting these results. Additional investigations are warranted to further validate these findings.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"757\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eART\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eassisted reproductive technology\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eADA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eAdenosine\u0026nbsp;Deaminase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eALB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eAlbumin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eATP1B1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eATPase\u0026nbsp;Na⁺/K⁺\u0026nbsp;Transporting\u0026nbsp;Subunit\u0026nbsp;Beta\u0026nbsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eATP5IFL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eATP synthase inhibitory factor subunit 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eAURKB\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eAurora Kinase B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eBECN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eBeclin-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eCCN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eCellular Communication Network 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eCEBPA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eCCAAT/Enhancer\u0026nbsp;Binding\u0026nbsp;Protein\u0026nbsp;Alpha\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eCOPS3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eCOP9\u0026nbsp;Signalosome\u0026nbsp;Subunit\u0026nbsp;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eCTSB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eCathespin B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eCUR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ecurtain gas\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDAGLB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eDiacylglycerol lipase beta\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eData-dependent acquisition\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDEPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003edifferentially expressed proteins\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDMRs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003edifferential methylation regions\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDNAJA1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eDnaJ homolog subfamily A member 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDNMT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eDNA methyltransferase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDNMT3B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eDNA methyltransferase 3B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eDNMTs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eDNA methyltransferases\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eEOMES\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eEomesodermin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eEpi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eepiblast\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eERF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eETS2\u0026nbsp;Repressive\u0026nbsp;Factor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eESI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eelectrospray ionization\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eETNK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eEthanolamine\u0026nbsp;Kinase\u0026nbsp;1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eExE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eextraembryonic ectoderm\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eEZH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eEnhancer of Zeste Homolog\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eEZHIP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eEnhancer of Zeste Homolog 2 Inhibitory Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eFDR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003efalse discovery rate\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGJA1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGap Junction Protein Alpha 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGJB3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGap Junction Protein Beta 3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGlycerol kinase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGene ontology\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGPX3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGlutathione peroxidase 3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGSTA4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGlutathione S-transferase A4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGSTO1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGlutathione S-transferase omega 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGSTP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGlutathione S-transferase P1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eGSTT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eGlutathione S-transferase T2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ehCG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ehuman chorionic gonadotropin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eHDAC7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eHistone Deacetylase 7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eHK1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eHexokinase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eHNRNPUL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eHeterogeneous Nuclear Ribonucleoprotein U-Like 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eICR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eMice of Institute of Cancer Research\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eICSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eintracytoplasmic sperm injection\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eISVF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eion spray voltage\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eIVF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ein vitro fertilization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eIVO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ein vivo fertilization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eKDM2B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003e\u0026nbsp;Lysine (K) Demethylase 2B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eKEGG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eKNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eK-nearest neighbors\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eKRT8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eKeratin\u0026nbsp;8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eL3MBTL1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePaternally Expressed Gene L3MBTL1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eLAMB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eLaminin subunit beta-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eLAMB2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eLaminin subunit beta-2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eLC-MS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eliquid chromatography-mass spectrometry\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eLDHB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eLactate Dehydrogenase B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eMDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eMalate Dehydrogenase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eMGST3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eMicroglutathione S-transferase 3\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eNLRP5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eNOD-like receptor family pyrin domain containing 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eNSDHL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eNAD(P)H\u0026nbsp;Steroid\u0026nbsp;Dehydrogenase-Like\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eODGH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eOxoglutarate\u0026nbsp;Dehydrogenase\u0026nbsp;Complex\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePALLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePalladin,\u0026nbsp;Cytoskeletal\u0026nbsp;Associated\u0026nbsp;Protein\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePASEF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eparallel accumulation-serial fragmentation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePrincipal Component Analysis\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePCC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePearson\u0026apos;s Correlation Coefficient\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePEG10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePaternally Expressed 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePGK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePhosphoglycerate Kinase\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePIMS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003epreimplantation methylation screening\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePKM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePyruvate Kinase muscle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePMSG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003epregnant mare serum gonadotropin\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePRDX1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePeroxiredoxin 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePRDX2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePeroxiredoxin 2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePRDX5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003ePeroxiredoxin 5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePRXL2B\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003e\u0026nbsp;Peroxiredoxin like 2B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003ePSPC1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eParaspeckle Component 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eQC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003equality control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eRDX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eRadixin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eROS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eReactive Oxygen Species\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eRSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003erelative standard deviation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eSKP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eS-phase Kinase-Associated Protein 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eSOD1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eSuperoxide dismutase 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eSPP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eSecreted Phosphoprotein 1\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eSTIP1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eStress-Induced Phosphoprotein 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eTCA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003etricarboxylic acid cycle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 43.3289%;\"\u003e\n \u003cp\u003eUHRF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 56.6711%;\"\u003e\n \u003cp\u003eUbiquitin-like with PHD and RING finger domains 1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current study was carried out with the approval of the Ethic Committee of Reproductive Medicine of Reproductive Hospital of Shandong University (2022-138), and all experiments performed were as per relevant regulations and guidelines of the committees.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are amenable to providing data upon reasonable request to the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Natural Science Foundation of China (323B2027), National Key R\u0026amp;D Program of China (2023YFA1801803) and The Fundamental Research Funds of Shandong University (2023QNTD004).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCZ designed the study, JS and YZ carried out the analysis and interpretation of data and wrote the manuscript, XY, XD, HT, and WY performed the experiments. CZ, KW and BL supervised the project. All the authors approved the final version of manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRienzi L, Gracia C, Maggiulli R, LaBarbera A R, Kaser D J, Ubaldi F M, et al. Oocyte, embryo and blastocyst cryopreservation in ART: systematic review and meta-analysis comparing slow-freezing versus vitrification to produce evidence for the development of global guidance\u003cem\u003e.\u003c/em\u003e Hum Reprod Update. 2017;23(2):139-155.\u003c/li\u003e\n\u003cli\u003ePinborg A, Wennerholm U B, and Bergh C. Long-term outcomes for children conceived by assisted reproductive technology\u003cem\u003e.\u003c/em\u003e Fertil Steril. 2023;120(3 Pt 1):449-456.\u003c/li\u003e\n\u003cli\u003ePelkonen S, Gissler M, Koivurova S, Lehtinen S, Martikainen H, Hartikainen A L, et al. Physical health of singleton children born after frozen embryo transfer using slow freezing: a 3-year follow-up study\u003cem\u003e.\u003c/em\u003e Hum Reprod. 2015;30(10):2411-8.\u003c/li\u003e\n\u003cli\u003e\u0026Scaron;ljivančanin T and Kontić-Vučinić O. Perinatal Outcomes of Pregnancies Conceived by Assisted Reproductive Technologies\u003cem\u003e.\u003c/em\u003e Srp Arh Celok Lek. 2015;143(9-10):632-8.\u003c/li\u003e\n\u003cli\u003eDe Geyter C, Calhaz-Jorge C, Kupka M S, Wyns C, Mocanu E, Motrenko T, et al. ART in Europe, 2015: results generated from European registries by ESHRE\u003cem\u003e.\u003c/em\u003e Hum Reprod Open. 2020;2020(1):hoz038.\u003c/li\u003e\n\u003cli\u003eSullivan-Pyke C S, Senapati S, Mainigi M A, and Barnhart K T. In Vitro fertilization and adverse obstetric and perinatal outcomes\u003cem\u003e.\u003c/em\u003e Semin Perinatol. 2017;41(6):345-353.\u003c/li\u003e\n\u003cli\u003eBasatemur E, Shevlin M, and Sutcliffe A. Growth of children conceived by IVF and ICSI up to 12years of age\u003cem\u003e.\u003c/em\u003e Reprod Biomed Online. 2010;20(1):144-9.\u003c/li\u003e\n\u003cli\u003eBelva F, Henriet S, Liebaers I, Van Steirteghem A, Celestin-Westreich S, and Bonduelle M. Medical outcome of 8-year-old singleton ICSI children (born \u0026gt;or=32 weeks\u0026apos; gestation) and a spontaneously conceived comparison group\u003cem\u003e.\u003c/em\u003e Hum Reprod. 2007;22(2):506-15.\u003c/li\u003e\n\u003cli\u003eCarson C, Sacker A, Kelly Y, Redshaw M, Kurinczuk J J, and Quigley M A. Asthma in children born after infertility treatment: findings from the UK Millennium Cohort Study\u003cem\u003e.\u003c/em\u003e Hum Reprod. 2013;28(2):471-9.\u003c/li\u003e\n\u003cli\u003eChen M and Heilbronn L K. The health outcomes of human offspring conceived by assisted reproductive technologies (ART)\u003cem\u003e.\u003c/em\u003e J Dev Orig Health Dis. 2017;8(4):388-402.\u003c/li\u003e\n\u003cli\u003eLee S H, Liu X, Jimenez-Morales D, and Rinaudo P F. Murine blastocysts generated by in vitro fertilization show increased Warburg metabolism and altered lactate production\u003cem\u003e.\u003c/em\u003e Elife. 2022;11(\u003c/li\u003e\n\u003cli\u003eYang W, Wang P, Cao P, Wang S, Yang Y, Su H, et al. Hypoxic in vitro culture reduces histone lactylation and impairs pre-implantation embryonic development in mice\u003cem\u003e.\u003c/em\u003e Epigenetics Chromatin. 2021;14(1):57.\u003c/li\u003e\n\u003cli\u003eAgarwal A, Maldonado Rosas I, Anagnostopoulou C, Cannarella R, Boitrelle F, Munoz L V, et al. Oxidative Stress and Assisted Reproduction: A Comprehensive Review of Its Pathophysiological Role and Strategies for Optimizing Embryo Culture Environment\u003cem\u003e.\u003c/em\u003e Antioxidants (Basel). 2022;11(3):\u003c/li\u003e\n\u003cli\u003eCanovas S, Ross P J, Kelsey G, and Coy P. DNA Methylation in Embryo Development: Epigenetic Impact of ART (Assisted Reproductive Technologies)\u003cem\u003e.\u003c/em\u003e Bioessays. 2017;39(11):\u003c/li\u003e\n\u003cli\u003eBai D, Sun J, Chen C, Jia Y, Li Y, Liu K, et al. Aberrant H3K4me3 modification of epiblast genes of extraembryonic tissue causes placental defects and implantation failure in mouse IVF embryos\u003cem\u003e.\u003c/em\u003e Cell Rep. 2022;39(5):110784.\u003c/li\u003e\n\u003cli\u003eVitagliano A, Paffoni A, and Vigan\u0026ograve; P. Does maternal age affect assisted reproduction technology success rates after euploid embryo transfer? A systematic review and meta-analysis\u003cem\u003e.\u003c/em\u003e Fertil Steril. 2023;120(2):251-265.\u003c/li\u003e\n\u003cli\u003eRaunig J M, Yamauchi Y, Ward M A, and Collier A C. Placental inflammation and oxidative stress in the mouse model of assisted reproduction\u003cem\u003e.\u003c/em\u003e Placenta. 2011;32(11):852-8.\u003c/li\u003e\n\u003cli\u003eGao Y, Liu X, Tang B, Li C, Kou Z, Li L, et al. Protein Expression Landscape of Mouse Embryos during Pre-implantation Development\u003cem\u003e.\u003c/em\u003e Cell Rep. 2017;21(13):3957-3969.\u003c/li\u003e\n\u003cli\u003eWu Q, Sui X, and Tian R. [Advances in high-throughput proteomic analysis]\u003cem\u003e.\u003c/em\u003e Se Pu. 2021;39(2):112-117.\u003c/li\u003e\n\u003cli\u003eNie J, An L, Miao K, Hou Z, Yu Y, Tan K, et al. Comparative analysis of dynamic proteomic profiles between in vivo and in vitro produced mouse embryos during postimplantation period\u003cem\u003e.\u003c/em\u003e J Proteome Res. 2013;12(9):3843-56.\u003c/li\u003e\n\u003cli\u003eCalder M D, Chen R, MacDonald A, MacNeily Z, Leung Z C L, Adus S, et al. Effects of palmitic acid on localization of embryo cell fate and blastocyst formation gene products\u003cem\u003e.\u003c/em\u003e Reproduction. 2022;163(3):133-143.\u003c/li\u003e\n\u003cli\u003eYousif M D, Calder M D, Du J T, Ruetz K N, Crocker K, Urquhart B L, et al. Oleic Acid Counters Impaired Blastocyst Development Induced by Palmitic Acid During Mouse Preimplantation Development: Understanding Obesity-Related Declines in Fertility\u003cem\u003e.\u003c/em\u003e Reprod Sci. 2020;27(11):2038-2051.\u003c/li\u003e\n\u003cli\u003eWang Y, Pope I, Brennan-Craddock H, Poole E, Langbein W, Borri P, et al. A primary effect of palmitic acid on mouse oocytes is the disruption of the structure of the endoplasmic reticulum\u003cem\u003e.\u003c/em\u003e Reproduction. 2021;163(1):45-56.\u003c/li\u003e\n\u003cli\u003eGhimire S, Mantziou V, Moris N, and Martinez Arias A. Human gastrulation: The embryo and its models\u003cem\u003e.\u003c/em\u003e Dev Biol. 2021;474(100-108.\u003c/li\u003e\n\u003cli\u003eGraham M E, Jelin A, Hoon A H, Jr., Wilms Floet A M, Levey E, and Graham E M. Assisted reproductive technology: Short- and long-term outcomes\u003cem\u003e.\u003c/em\u003e Dev Med Child Neurol. 2023;65(1):38-49.\u003c/li\u003e\n\u003cli\u003eLi G, Yu Y, Fan Y, Li C, Xu X, Duan J, et al. Genome wide abnormal DNA methylome of human blastocyst in assisted reproductive technology\u003cem\u003e.\u003c/em\u003e J Genet Genomics. 2017;44(10):475-481.\u003c/li\u003e\n\u003cli\u003eGao Y, Yi L, Zhan J, Wang L, Yao X, Yan J, et al. A clinical study of preimplantation DNA methylation screening in assisted reproductive technology\u003cem\u003e.\u003c/em\u003e Cell Res. 2023;33(6):483-485.\u003c/li\u003e\n\u003cli\u003eHuang J C, Lei Z L, Shi L H, Miao Y L, Yang J W, Ouyang Y C, et al. Comparison of histone modifications in in vivo and in vitro fertilization mouse embryos\u003cem\u003e.\u003c/em\u003e Biochem Biophys Res Commun. 2007;354(1):77-83.\u003c/li\u003e\n\u003cli\u003eVac\u0026iacute;k T, Lađinović D, and Ra\u0026scaron;ka I. KDM2A/B lysine demethylases and their alternative isoforms in development and disease\u003cem\u003e.\u003c/em\u003e Nucleus. 2018;9(1):431-441.\u003c/li\u003e\n\u003cli\u003eRichard Albert J, Urli T, Monteagudo-S\u0026aacute;nchez A, Le Breton A, Sultanova A, David A, et al. DNA methylation shapes the Polycomb landscape during the exit from naive pluripotency\u003cem\u003e.\u003c/em\u003e Nat Struct Mol Biol. 2025;32(2):346-357.\u003c/li\u003e\n\u003cli\u003eZhu T, Guan S, Lv D, Zhao M, Yan L, Shi L, et al. Melatonin Modulates Lipid Metabolism in Porcine Cumulus-Oocyte Complex via Its Receptors\u003cem\u003e.\u003c/em\u003e Front Cell Dev Biol. 2021;9(648209.\u003c/li\u003e\n\u003cli\u003eLeyens G, Knoops B, and Donnay I. Expression of peroxiredoxins in bovine oocytes and embryos produced in vitro\u003cem\u003e.\u003c/em\u003e Mol Reprod Dev. 2004;69(3):243-51.\u003c/li\u003e\n\u003cli\u003eTatone C, Di Emidio G, Battaglia R, and Di Pietro C. Building a Human Ovarian Antioxidant ceRNA Network \u0026quot;OvAnOx\u0026quot;: A Bioinformatic Perspective for Research on Redox-Related Ovarian Functions and Dysfunctions\u003cem\u003e.\u003c/em\u003e Antioxidants (Basel). 2024;13(9):\u003c/li\u003e\n\u003cli\u003eLam B K. Leukotriene C(4) synthase\u003cem\u003e.\u003c/em\u003e Prostaglandins Leukot Essent Fatty Acids. 2003;69(2-3):111-6.\u003c/li\u003e\n\u003cli\u003eMarei W F A, Van den Bosch L, Pintelon I, Mohey-Elsaeed O, Bols P E J, and Leroy J. Mitochondria-targeted therapy rescues development and quality of embryos derived from oocytes matured under oxidative stress conditions: a bovine in vitro model\u003cem\u003e.\u003c/em\u003e Hum Reprod. 2019;34(10):1984-1998.\u003c/li\u003e\n\u003cli\u003eJuszkiewicz S, Peak-Chew S Y, and Hegde R S. Mechanism of chaperone recruitment and retention on mitochondrial precursors\u003cem\u003e.\u003c/em\u003e Mol Biol Cell. 2025;36(4):ar39.\u003c/li\u003e\n\u003cli\u003eDemant M, Deutsch D R, Fr\u0026ouml;hlich T, Wolf E, and Arnold G J. Proteome analysis of early lineage specification in bovine embryos\u003cem\u003e.\u003c/em\u003e Proteomics. 2015;15(4):688-701.\u003c/li\u003e\n\u003cli\u003eXu L, Liu T, Han F, Zong Z, Wang G, Yu B, et al. AURKB and MAPK involvement in the regulation of the early stages of mouse zygote development\u003cem\u003e.\u003c/em\u003e Sci China Life Sci. 2012;55(1):47-56.\u003c/li\u003e\n\u003cli\u003eGuan Y, Leu N A, Ma J, Chm\u0026aacute;tal L, Ruthel G, Bloom J C, et al. SKP1 drives the prophase I to metaphase I transition during male meiosis\u003cem\u003e.\u003c/em\u003e Sci Adv. 2020;6(13):eaaz2129.\u003c/li\u003e\n\u003cli\u003eShao W, Bi X, Pan Y, Gao B, Wu J, Yin Y, et al. Phase separation of RNA-binding protein promotes polymerase binding and transcription\u003cem\u003e.\u003c/em\u003e Nat Chem Biol. 2022;18(1):70-80.\u003c/li\u003e\n\u003cli\u003eVivori C, Papasaikas P, Stadhouders R, Di Stefano B, Rubio A R, Balaguer C B, et al. Dynamics of alternative splicing during somatic cell reprogramming reveals functions for RNA-binding proteins CPSF3, hnRNP UL1, and TIA1\u003cem\u003e.\u003c/em\u003e Genome Biol. 2021;22(1):171.\u003c/li\u003e\n\u003cli\u003eLu L, Lv B, Huang K, Xue Z, Zhu X, and Fan G. Recent advances in preimplantation genetic diagnosis and screening\u003cem\u003e.\u003c/em\u003e J Assist Reprod Genet. 2016;33(9):1129-34.\u003c/li\u003e\n\u003cli\u003eKatari S, Turan N, Bibikova M, Erinle O, Chalian R, Foster M, et al. DNA methylation and gene expression differences in children conceived in vitro or in vivo\u003cem\u003e.\u003c/em\u003e Hum Mol Genet. 2009;18(20):3769-78.\u003c/li\u003e\n\u003cli\u003eTan K, Zhang Z, Miao K, Yu Y, Sui L, Tian J, et al. Dynamic integrated analysis of DNA methylation and gene expression profiles in in vivo and in vitro fertilized mouse post-implantation extraembryonic and placental tissues\u003cem\u003e.\u003c/em\u003e Mol Hum Reprod. 2016;22(7):485-98.\u003c/li\u003e\n\u003cli\u003eGr\u0026auml;del F, von Wolff M, Kohl Schwartz A S, and Mitter V R. Low-dose clomiphene citrate does not reduce implantation and live birth rates in otherwise unstimulated modified natural cycle IVF-retrospective cohort study\u003cem\u003e.\u003c/em\u003e Arch Gynecol Obstet. 2023;307(4):1073-1081.\u003c/li\u003e\n\u003cli\u003eLi M Y, Wu Y, Tang H L, Wang Y, Li B, He Y Y, et al. Embryo-Derived Cathepsin B Promotes Implantation and Decidualization by Activating Pyroptosis\u003cem\u003e.\u003c/em\u003e Adv Sci (Weinh). 2024;11(43):e2402299.\u003c/li\u003e\n\u003cli\u003eChu Q, Zhong X, Lu Y, and Xu Y. miR-942-5p Regulates Proliferation, Invasion and EMT of Trophoblast Cells in Gestational Diabetes by Targeting the CEBPA\u003cem\u003e.\u003c/em\u003e Altern Ther Health Med. 2024;30(9):312-318.\u003c/li\u003e\n\u003cli\u003eRoediger M, Miosge N, and Gersdorff N. Tissue distribution of the laminin beta1 and beta2 chain during embryonic and fetal human development\u003cem\u003e.\u003c/em\u003e J Mol Histol. 2010;41(2-3):177-84.\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":"journal-of-ovarian-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jovr","sideBox":"Learn more about [Journal of Ovarian Research](http://ovarianresearch.biomedcentral.com)","snPcode":"13048","submissionUrl":"https://submission.nature.com/new-submission/13048/3","title":"Journal of Ovarian Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Assisted reproduction technology, In vitro fertilization, Embryo development, Proteomics, Offspring safety","lastPublishedDoi":"10.21203/rs.3.rs-7421421/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7421421/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAssisted reproductive technology (ART), especially in vitro fertilization (IVF), has become an important means of addressing infertility issues. Compared with natural conception (in vivo fertilization, IVO), IVF embryos are completely dependent on in vitro culture, and the in vitro environment may interfere with early embryo gene expression, thereby affecting embryo development potential. However, various adverse outcomes in offspring have been reported to be associated with ART, whereas limited research has been conducted on its effects during the early stages of embryonic development.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThis study aims to investigate the specific mechanisms by which ART affects blastocysts. Proteomics and metabolomics analyses were conducted to identify differentially expressed proteins and metabolites between IVO and IVF blastocyst stages, and enrichment analysis was performed on the differentially expressed proteins (DEPs). Proteomic analysis revealed 745 DEPs between the two groups, with 257 upregulated and 488 downregulated in IVF-derived blastocysts. Gene ontology (GO) enrichment analysis demonstrated that these DEPs were primarily enriched in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy, and implantation-related pathways.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eIn conclusion, we identified considerable DEPs and discussed how they agreed with previous researches illustrating altered protein expression associated with the quality of blastocysts. These findings provide valuable insights for improving ART success rates and reducing health risks in IVF-conceived offspring, highlighting their significant clinical translational potential.\u003c/p\u003e","manuscriptTitle":"Assisted reproductive technologies lead to abnormalities in metabolic processes, epigenetic modifications, oxidative stress, embryonic aneuploidy and implantation in mouse blastocysts","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 17:41:34","doi":"10.21203/rs.3.rs-7421421/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-19T08:15:19+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T14:43:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T08:30:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95641102194549588280825973643281317968","date":"2025-09-15T21:04:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300728950969093010873978405669764426793","date":"2025-09-15T10:28:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-12T19:41:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"48896345855511599371734991193540299698","date":"2025-08-29T12:57:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-27T10:24:26+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-23T01:52:04+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-22T07:52:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Ovarian Research","date":"2025-08-21T02:14:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-ovarian-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jovr","sideBox":"Learn more about [Journal of Ovarian Research](http://ovarianresearch.biomedcentral.com)","snPcode":"13048","submissionUrl":"https://submission.nature.com/new-submission/13048/3","title":"Journal of Ovarian Research","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"5d79aae2-24b5-415c-a233-70fcaa7d6c51","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-08T16:09:25+00:00","versionOfRecord":{"articleIdentity":"rs-7421421","link":"https://doi.org/10.1186/s13048-025-01892-z","journal":{"identity":"journal-of-ovarian-research","isVorOnly":false,"title":"Journal of Ovarian Research"},"publishedOn":"2025-12-03 15:58:03","publishedOnDateReadable":"December 3rd, 2025"},"versionCreatedAt":"2025-09-03 17:41:34","video":"","vorDoi":"10.1186/s13048-025-01892-z","vorDoiUrl":"https://doi.org/10.1186/s13048-025-01892-z","workflowStages":[]},"version":"v1","identity":"rs-7421421","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7421421","identity":"rs-7421421","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}