Irune Calzado

Human infertility affects approximately 17.5% of the global population, with male factors accounting for nearly half of all cases. Identifying reliable molecular biomarkers is crucial for improving the diagnosis and assessment of male fertility. This study established and refined an untargeted high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC-ESI-MS/MS) protocol for a comprehensive lipidomic and metabolomic analysis of human spermatozoa, using only 1.25 million cells per sample. Compared with previous reports, our optimized method achieved an unparalleled level of analytical depth, identifying 473 lipid species and 955 structurally annotated metabolites. This corresponds to nearly a 7600-fold improvement in detection efficiency per cell compared with previously published approaches. Lipidomic analysis revealed that the most abundant lipid classes were glycerophospholipids (39%), cholesterol (20%) and fatty acids (19%), with cholesterol representing the single most abundant compound. This observation is consistent with the structural complexity of the sperm plasma membrane. Metabolomic profiling similarly identified glycerophospholipids (44%), eicosanoids (14%) and N-acyl amino acids (12%) as the major metabolite classes. The integration of lipidomic and metabolomic data highlighted functionally interconnected pathways related to membrane dynamics, energy metabolism, and hormone biosynthesis. Overall, this work establishes a robust, sensitive, and scalable analytical framework that enables the high-coverage molecular characterization of spermatozoa from limited sample material, laying the groundwork for future biomarker discovery and clinical applications in male infertility research.

Epigenetic memory ensures stable inheritance of gene expression patterns critical for embryonic development. Environmental exposures can disrupt this memory, yet the mechanisms remain unclear. Here we demonstrate that chronic morphine exposure induces a persistent transcriptomic and epigenetic memory by repressing Smchd1, a key chromatin regulator, in mouse embryonic stem cells, preimplantation embryos, and human induced pluripotent stem cells. This repression compromises maintenance of X-chromosome inactivation and genomic imprinting, leading to sustained dysregulation of developmentally important gene clusters. Morphine-induced epigenetic alterations also involve changes in DNA methylation and histone modifications along the X chromosome and notably increased H3K27me3 at the Smchd1 locus. These findings reveal a conserved mechanism by which opioid exposure disrupts higher-order chromatin architecture and epigenetic memory during early development, potentially contributing to long-term developmental and clinical outcomes.

Despite the improvements in tool development for DNA methylation analysis, there is a lack of a consensus on computational and statistical models used for differentially methylated cytosine (DMC) identification. This variability complicates the interpretation of findings and raises concerns about the reproducibility and biological significance of the detected results. In this regard, here we conducted a comparative evaluation of edgeR and methylKit tools to assess their performance, concordance, and biological relevance in detecting DMCs following a morphine exposure model in mouse embryonic stem cells (mESCs). Both pipelines were applied to the same WGBS dataset (GEO accession number: GSE292082), and concordance was calculated at both single-base and gene levels. Although the total number of DMCs identified differed between tools, both pipelines detected a global hypomethylation pattern. Genomic distribution analysis revealed that DMCs predominantly localized to intergenic and intronic regions, as well as to open sea regions. Despite differences in sensitivity, both pipelines demonstrated moderate concordance at the DMC level (~56%) and high concordance at the gene level (~90%), identifying largely overlapping sets of differentially methylated genes (DMGs). Comparative assessments further showed that the choice of statistical metric can influence the perceived magnitude of biological effects. Sensitivity analyses indicated that threshold selection and normalization methods influence DMC detection, whereas aggregation at gene level reduces discrepancies. Overall, our findings underscore the complementary strengths of methylKit and edgeR and highlight the importance of careful tool selection for epigenetic studies. As a conclusion, we recommend integrating both pipelines to ensure a balanced interpretation of effect sizes, particularly in studies with complex experimental designs.

1. Background: Human infertility affects approximately 17.5% of the global population, with male factors accounting for nearly half of all cases. The identification of reliable molecular biomarkers is crucial for improving the diagnosis and assessment of male fertility. In this study, we developed and optimized an untargeted high-performance liquid chromatography–electrospray ionization–tandem mass spectrometry (HPLC-ESI-MS/MS) workflow for comprehensive lipidomic and metabolomic profiling of human spermatozoa using only 1.25 million cells per sample. Results: Compared to previous reports, our optimized method achieved unprecedented analytical depth, identifying 473 lipid species and 955 structurally annotated metabolites, corresponding to nearly 7.600-fold improvements in detection efficiency per cell over published approaches. Lipidomic analysis revealed cholesterol, fatty acids, phosphatidylcholines, and phosphatidylethanolamine plasmalogens as the most abundant lipid classes, consistent with the structural complexity of the sperm plasma membrane. Metabolomic profiling showed strong enrichment of lipid-related and steroidogenic pathways, including phospholipid biosynthesis, glycerolipid metabolism and androgen and estrogen metabolism. The integration of lipidomic and metabolomic data highlighted functionally interconnected pathways related to membrane dynamics, energy metabolism, and hormone biosynthesis. Conclusions: Overall, this work establishes a robust, sensitive, and scalable analytical framework enabling high-coverage molecular characterization of spermatozoa from limited sample material, laying the groundwork for future biomarker discovery and clinical applications in male infertility research. One Sentence Summary: Development of a highly sensitive untargeted HPLC-ESI–MS/MS lipidomic and metabolomic workflow that achieves unprecedented molecular coverage from only 1.25 million human spermatozoa, revealing interconnected lipid and metabolic pathways and providing a robust foundation for biomarker discovery in male infertility. Graphical

Epigenetic regulation, particularly DNA methylation, plays a crucial role in embryonic development by controlling gene expression patterns. The disruption of this regulation by environmental factors can have long-lasting consequences. Opioid drugs, such as morphine, are known to cross the placental barrier and affect the developing central nervous system, yet their precise epigenetic effects during early development remain unclear. This study aimed to elucidate the impact of chronic morphine exposure on the DNA methylation landscape and gene expression in mouse embryonic stem cells (mESCs). mESCs were chronically exposed to morphine (10 μM for 24 h). Genome-wide bisulfite sequencing was performed to identify DNA methylation changes, while RNA sequencing (RNA-Seq) assessed corresponding gene expression alterations. Global levels of 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) were quantified using mass spectrometry. Morphine exposure induced global DNA hypomethylation and identified 16,808 differentially methylated genes (DMGs) related to development, cell signalling, metabolism, and transcriptional regulation. Integrative transcriptomic analysis with RNA-Seq data revealed 651 overlapping genes, including alterations in key epigenetic regulators involved on DNA methylation machinery. Specifically, Tet1 was upregulated with promoter hypomethylation, while Dnmt1 was downregulated, without changes in promoter methylation after morphine exposiure. Mass spectrometry results confirmed a global decrease in 5mC levels alongside increased 5hmC, indicating the involvement of both passive and active demethylation pathways. These findings demonstrate for the first time that morphine disrupts the epigenetic homeostasis of mESCs by promoting global and gene-specific DNA demethylation, which might be key to the phenotypic changes that occur in adulthood. This work provides novel mechanistic insights into how opioid exposure during early development may lead to persistent epigenetic alterations, with potential long-term implications for neurodevelopment and disease susceptibility.

Despite the improvements in tool development for DNA methylation analysis, there is a lack of a consensus on computational and statistical models used for differentially methylated cytosine (DMC) identification. This variability complicates the interpretation of findings and raises concerns about the reproducibility and biological significance of the detected results. In this regard, the primary objective of this study was to compare the performance, concordance, and biological relevance of edgeR and methylKit tools in detecting DMCs (the first one based on fold change and the second one based on percentage), following morphine exposure model in mouse embryonic stem cells (mESCs). While a different number of total DMCs was identified by each tool, both pipelines detected a global hypomethylation as a result. Genomic analysis revealed a predominant distribution of DMCs in intergenic and intronic regions on one hand, and in open sea regions on the other hand. Despite the differences in sensitivity, both tools demonstrated moderate concordance in DMCs detection (∼56%) and high concordance in gene level analysis (∼90%), identifying similar differentially methylated genes (DMGs). Overall, the results underscore the complementary strengths of methylKit and edgeR and highlight the importance of tool selection for epigenetic studies. As a conclusion, integrating both pipelines is recommended for comprehensive analysis, particularly in studies with complex experimental designs.

Epigenetic changes are essential for normal development and ageing, but there is still limited understanding of how environmental factors can cause epigenetic changes that leads to health problems or diseases. Morphine is known to pass through the placental barrier and impact normal embryo development by affecting the neural tube, frontal cortex and spinal cord development, and, as a consequence, delaying nervous system development. In fact, in-utero morphine exposure has shown alterations in anxiety-like behaviours, analgesic tolerance, synaptic plasticity and the neuronal structure of offspring. However, how morphine leads to abnormal neurogenesis and other physiological consequences during embryo development is still unknown. Considering that DNA methylation is a key epigenetic factor crucial for embryo development, our aim is to elucidate the role of methylation in response to morphine. Chronic morphine treatment (24h, 10μM) induces a global hypomethylation in mESC. WGBSeq identifies 16,808 sensitive to morphine which are involved in embryo development, signalling pathways, metabolism and/or gene expression, suggesting that morphine might impact methylation levels at developmental genes. Integrative analyses between WGBSeq and RNASeq identified Tet1 as morphine-sensitive gene. Morphine increased the gene expression of Tet1 , modifying the methylation levels at the promoter. On the other hand, RNASeq and qRT-PCR analyses revealed that Dnmt1 gene expression decreased after morphine treatment, without altering the methylation patter at its promoters. By MS/MS approaches confirms a decrease in DNA methylation after chronic morphine treatment, together with an increase in hydroxymethylation global levels in mESCs. In conclusion, morphine induces a global hypomethylation in mESC through different mechanisms that involves passive demethylation and a self-regulatory mechanism via active demethylation. One Sentence Summary: Understanding how environmental epigenetics impact on embryo development aids to unravel changes that leads to health problems or diseases in the adulthood. Graphical Chronic morphine treatment induces a global hypomethylation in mESC through different mechanisms that involves passive demethylation and a self-regulatory mechanism via active demethylation in genes involved in embryo development.

Alterazio kromosomikoak dituzten espermatozoideak identifikatzeko biomarkatzaileen hautaketa produkzioaren informazio-fitxa

Morfinak hipometilazio globala eragiten du mES zeluletan autoerregulazioa daukan demetilazio aktibo baten bidez produkzioaren informazio-fitxa