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Single Cell Multimodal Analyses Reveal Epigenomic and Transcriptomic Basis for Birth Defects in Maternal Diabetes.

ABSTRACT: Maternal diabetes mellitus is among the most frequent environmental contributors to congenital birth defects, including heart defects and craniofacial anomalies, yet the cell types affected and mechanisms of disruption are largely unknown. Using multi-modal single cell analyses, here we show that maternal diabetes affects the epigenomic landscape of specific subsets of cardiac and craniofacial progenitors during embryogenesis. A previously unrecognized cardiac progenitor subpopulation expressing the homeodomain-containing protein ALX3 showed prominent chromatin accessibility changes and acquired a more posterior identity. Similarly, a subpopulation of neural crest-derived cells in the second pharyngeal arch, which contributes to craniofacial structures, displayed abnormalities in the epigenetic landscape and axial patterning defects. Chromatin accessibility changes in both populations were associated with increased retinoic acid signaling, known to establish anterior-posterior identity. This work highlights how an environmental insult can have highly selective epigenomic consequences on discrete cell types leading to developmental patterning defects.

SUBMITTER: Nishino T

PROVIDER: S-EPMC11343316 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Single Cell Multimodal Analyses Reveal Epigenomic and Transcriptomic Basis for Birth Defects in Maternal Diabetes.

Nishino Tomohiro T Ranade Sanjeev S SS Pelonero Angelo A van Soldt Benjamin J BJ Ye Lin L Alexanian Michael M Koback Frances F Huang Yu Y Sadagopan Nandhini N Lam Adrienne A Zholudeva Lyandysha V LV Li Feiya F Padmanabhan Arun A Thomas Reuben R van Bemmel Joke G JG Gifford Casey A CA Costa Mauro W MW Srivastava Deepak D

Nature cardiovascular research 20231130 12

Maternal diabetes mellitus is among the most frequent environmental contributors to congenital birth defects, including heart defects and craniofacial anomalies, yet the cell types affected and mechanisms of disruption are largely unknown. Using multi-modal single cell analyses, here we show that maternal diabetes affects the epigenomic landscape of specific subsets of cardiac and craniofacial progenitors during embryogenesis. A previously unrecognized cardiac progenitor subpopulation expressing ...[more]

PMID: 39183978

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Project description:BackgroundThere has been a significant surge in the global prevalence of diabetes mellitus (DM), which increases the susceptibility of individuals to ovarian cancer (OC). However, the relationship between DM and OC remains largely unexplored. The objective of this study is to provide preliminary insights into the shared molecular regulatory mechanisms and potential biomarkers between DM and OC.MethodsMultiple datasets from the GEO database were utilized for bioinformatics analysis. Single cell datasets from the GEO database were analysed. Subsequently, immune cell infiltration analysis was performed on mRNA expression data. The intersection of these datasets yielded a set of common genes associated with both OC and DM. Using these overlapping genes and Cytoscape, a protein‒protein interaction (PPI) network was constructed, and 10 core targets were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then conducted on these core targets. Additionally, advanced bioinformatics analyses were conducted to construct a TF-mRNA-miRNA coregulatory network based on identified core targets. Furthermore, immunohistochemistry staining (IHC) and real-time quantitative PCR (RT-qPCR) were employed for the validation of the expression and biological functions of core proteins, including HSPAA1, HSPA8, SOD1, and transcription factors SREBF2 and GTAT2, in ovarian tumors.ResultsThe immune cell infiltration analysis based on mRNA expression data for both DM and OC, as well as analysis using single-cell datasets, reveals significant differences in mononuclear cell levels. By intersecting the single-cell datasets, a total of 119 targets related to mononuclear cells in both OC and DM were identified. PPI network analysis further identified 10 hub genesincludingHSP90AA1, HSPA8, SNRPD2, UBA52, SOD1, RPL13A, RPSA, ITGAM, PPP1CC, and PSMA5, as potential targets of OC and DM. Enrichment analysis indicated that these genes are primarily associated with neutrophil degranulation, GDP-dissociation inhibitor activity, and the IL-17 signaling pathway, suggesting their involvement in the regulation of the tumor microenvironment. Furthermore, the TF-gene and miRNA-gene regulatory networks were validated using NetworkAnalyst. The identified TFs included SREBF2, GATA2, and SRF, while the miRNAs included miR-320a, miR-378a-3p, and miR-26a-5p. Simultaneously, IHC and RT-qPCR reveal differential expression of core targets in ovarian tumors after the onset of diabetes. RT-qPCR further revealed that SREBF2 and GATA2 may influence the expression of core proteins, including HSP90AA1, HSPA8, and SOD1.ConclusionThis study revealed the shared gene interaction network between OC and DM and predicted the TFs and miRNAs associated with core genes in monocytes. Our research findings contribute to identifying potential biological mechanisms underlying the relationship between OC and DM.

Dataset Information

Single Cell Multimodal Analyses Reveal Epigenomic and Transcriptomic Basis for Birth Defects in Maternal Diabetes.

Publications

Single Cell Multimodal Analyses Reveal Epigenomic and Transcriptomic Basis for Birth Defects in Maternal Diabetes.

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