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Scientific Reports Jun 2024The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated...
The benefits of breastfeeding for the health and wellbeing of both infants and mothers are well documented, yet global breastfeeding rates are low. One factor associated with low breast feeding is maternal body mass index (BMI), which is used as a measure of obesity. The negative relationship between maternal obesity and breastfeeding is likely caused by a variety of social, psychological, and physiological factors. Maternal obesity may also have a direct biological association with breastfeeding through changes in maternal DNA methylation. Here, we investigate this potential biological association using data from a UK-based cohort study, the Avon Longitudinal Study of Parents and Children (ALSPAC). We find that pre-pregnancy body mass index (BMI) is associated with lower initiation to breastfeed and shorter breastfeeding duration. We conduct epigenome-wide association studies (EWAS) of pre-pregnancy BMI and breastfeeding outcomes, and run candidate-gene analysis of methylation sites associated with BMI identified via previous meta-EWAS. We find that DNA methylation at cg11453712, annotated to PHTP1, is associated with pre-pregnancy BMI. From our results, neither this association nor those at candidate-gene sites are likely to mediate the link between pre-pregnancy BMI and breastfeeding.
Topics: Humans; DNA Methylation; Breast Feeding; Body Mass Index; Female; Pregnancy; Adult; Longitudinal Studies; Genome-Wide Association Study; United Kingdom; Obesity; Epigenesis, Genetic
PubMed: 38918574
DOI: 10.1038/s41598-024-65605-0 -
Scientific Reports Jun 2024Engineered mammalian cells are key for biotechnology by enabling broad applications ranging from in vitro model systems to therapeutic biofactories. Engineered cell...
Engineered mammalian cells are key for biotechnology by enabling broad applications ranging from in vitro model systems to therapeutic biofactories. Engineered cell lines exist as a population containing sub-lineages of cell clones that exhibit substantial genetic and phenotypic heterogeneity. There is still a limited understanding of the source of this inter-clonal heterogeneity as well as its implications for biotechnological applications. Here, we developed a genomic barcoding strategy for a targeted integration (TI)-based CHO antibody producer cell line development process. This technology provided novel insights about clone diversity during stable cell line selection on pool level, enabled an imaging-independent monoclonality assessment after single cell cloning, and eventually improved hit-picking of antibody producer clones by monitoring of cellular lineages during the cell line development (CLD) process. Specifically, we observed that CHO producer pools generated by TI of two plasmids at a single genomic site displayed a low diversity (< 0.1% RMCE efficiency), which further depends on the expressed molecules, and underwent rapid population skewing towards dominant clones during routine cultivation. Clonal cell lines from one individual TI event demonstrated a significantly lower variance regarding production-relevant and phenotypic parameters as compared to cell lines from distinct TI events. This implies that the observed cellular diversity lies within pre-existing cell-intrinsic factors and that the majority of clonal variation did not develop during the CLD process, especially during single cell cloning. Using cellular barcodes as a proxy for cellular diversity, we improved our CLD screening workflow and enriched diversity of production-relevant parameters substantially. This work, by enabling clonal diversity monitoring and control, paves the way for an economically valuable and data-driven CLD process.
Topics: CHO Cells; Cricetulus; Animals; DNA Barcoding, Taxonomic; Clone Cells; Genomics; Antibodies, Monoclonal
PubMed: 38918509
DOI: 10.1038/s41598-024-65323-7 -
Scientific Reports Jun 2024A previous study suggested that fetal inheritance of chromosomally integrated human herpesvirus 6 (ici-HHV6) is associated with the hypertensive pregnancy disorder... (Observational Study)
Observational Study
A previous study suggested that fetal inheritance of chromosomally integrated human herpesvirus 6 (ici-HHV6) is associated with the hypertensive pregnancy disorder preeclampsia (PE). We aimed to study this question utilizing cord plasma samples (n = 1276) of the Finnish Genetics of Preeclampsia Consortium (FINNPEC) cohort: 539 from a pregnancy with PE and 737 without. We studied these samples and 30 placentas from PE pregnancies by a multiplex qPCR for the DNAs of all nine human herpesviruses. To assess the population prevalence of iciHHV-6, we studied whole-genome sequencing data from blood-derived DNA of 3421 biobank subjects. Any herpes viral DNA was detected in only two (0.37%) PE and one (0.14%) control sample (OR 2.74, 95% CI 0.25-30.4). One PE sample contained iciHHV-6B and another HHV-7 DNA. The control's DNA was of iciHHV-6B; the fetus having growth restriction and preterm birth without PE diagnosis. Placentas showed no herpesviruses. In the biobank data, 3 of 3421 subjects (0.08%) had low level HHV-6B but no iciHHV-6. While iciHHV-6 proved extremely rare, both fetuses with iciHHV-6B were growth-restricted, preterm, and from a pregnancy with maternal hypertension. Our findings suggest that human herpesviruses are not a significant cause of PE, whereas iciHHV-6 may pose some fetal risk.
Topics: Humans; Female; Pregnancy; Pre-Eclampsia; Adult; Herpesvirus 6, Human; Cohort Studies; Fetal Blood; Finland; DNA, Viral; Placenta; Herpesviridae
PubMed: 38918446
DOI: 10.1038/s41598-024-65386-6 -
Scientific Reports Jun 2024Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the...
Type 2 diabetes (T2D) is the fastest growing non-infectious disease worldwide. Impaired insulin secretion from pancreatic beta-cells is a hallmark of T2D, but the mechanisms behind this defect are insufficiently characterized. Integrating multiple layers of biomedical information, such as different Omics, may allow more accurate understanding of complex diseases such as T2D. Our aim was to explore and use Machine Learning to integrate multiple sources of biological/molecular information (multiOmics), in our case RNA-sequening, DNA methylation, SNP and phenotypic data from islet donors with T2D and non-diabetic controls. We exploited Machine Learning to perform multiOmics integration of DNA methylation, expression, SNPs, and phenotypes from pancreatic islets of 110 individuals, with ~ 30% being T2D cases. DNA methylation was analyzed using Infinium MethylationEPIC array, expression was analyzed using RNA-sequencing, and SNPs were analyzed using HumanOmniExpress arrays. Supervised linear multiOmics integration via DIABLO based on Partial Least Squares (PLS) achieved an accuracy of 91 ± 15% of T2D prediction with an area under the curve of 0.96 ± 0.08 on the test dataset after cross-validation. Biomarkers identified by this multiOmics integration, including SACS and TXNIP DNA methylation, OPRD1 and RHOT1 expression and a SNP annotated to ANO1, provide novel insights into the interplay between different biological mechanisms contributing to T2D. This Machine Learning approach of multiOmics cross-sectional data from human pancreatic islets achieved a promising accuracy of T2D prediction, which may potentially find broad applications in clinical diagnostics. In addition, it delivered novel candidate biomarkers for T2D and links between them across the different Omics.
Topics: Humans; Diabetes Mellitus, Type 2; Machine Learning; DNA Methylation; Islets of Langerhans; Polymorphism, Single Nucleotide; Male; Female; Middle Aged; Biomarkers; Adult; Aged
PubMed: 38918439
DOI: 10.1038/s41598-024-64846-3 -
Cell Genomics Jun 2024Alterations in the structure and location of telomeres are pivotal in cancer genome evolution. Here, we applied both long-read and short-read genome sequencing to assess...
Alterations in the structure and location of telomeres are pivotal in cancer genome evolution. Here, we applied both long-read and short-read genome sequencing to assess telomere repeat-containing structures in cancers and cancer cell lines. Using long-read genome sequences that span telomeric repeats, we defined four types of telomere repeat variations in cancer cells: neotelomeres where telomere addition heals chromosome breaks, chromosomal arm fusions spanning telomere repeats, fusions of neotelomeres, and peri-centromeric fusions with adjoined telomere and centromere repeats. These results provide a framework for the systematic study of telomeric repeats in cancer genomes, which could serve as a model for understanding the somatic evolution of other repetitive genomic elements.
PubMed: 38917803
DOI: 10.1016/j.xgen.2024.100588 -
Poultry Science Apr 2024Magang geese are typical short-day breeders whose reproductive behaviors are significantly influenced by photoperiod. Exposure to a long-day photoperiod results in...
Magang geese are typical short-day breeders whose reproductive behaviors are significantly influenced by photoperiod. Exposure to a long-day photoperiod results in testicular regression and spermatogenesis arrest in Magang geese. To investigate the epigenetic influence of DNA methylation on the seasonal testicular regression in Magang geese, we conducted whole-genome bisulfite sequencing and transcriptome sequencing of testes across 3 reproductive phases during a long-day photoperiod. A total of 250,326 differentially methylated regions (DMR) were identified among the 3 comparison groups, with a significant number showing hypermethylation, especially in intronic regions of the genome. Integrating bisulfite sequencing with transcriptome sequencing data revealed that DMR-associated genes tend to be differentially expressed in the testes, highlighting a potential regulatory role for DNA methylation in gene expression. Furthermore, there was a significant negative correlation between changes in the methylation of CG DMRs and changes in the expression of their associated genes in the testes. A total of 3,359 DMR-associated differentially expressed genes (DEG) were identified; functional enrichment analyses revealed that motor proteins, MAPK signaling pathway, ECM-receptor interaction, phagosome, TGF-beta signaling pathway, and calcium signaling might contribute to the testicular regression process. GSEA revealed that the significantly enriched activated hallmark gene set was associated with apoptosis and estrogen response during testicular regression, while the repressed hallmark gene set was involved in spermatogenesis. Our study also revealed that methylation changes significantly impacted the expression level of vitamin A metabolism-related genes during testicular degeneration, with hypermethylation of STRA6 and increased calmodulin levels indicating vitamin A efflux during the testicular regression. These findings were corroborated by pyrosequencing and real-time qPCR, which revealed that the vitamin A metabolic pathway plays a pivotal role in testicular degeneration under long-day conditions. Additionally, metabolomics analysis revealed an insufficiency of vitamin A and an abnormally high level of oxysterols accumulated in the testes during testicular regression. In conclusion, our study demonstrated that testicular degeneration in Magang geese induced by a long-day photoperiod is linked to vitamin A homeostasis disruption, which manifests as the hypermethylation status of STRA6, vitamin A efflux, and a high level of oxysterol accumulation. These findings offer new insights into the effects of DNA methylation on the seasonal testicular regression that occurs during long-day photoperiods in Magang geese.
PubMed: 38917605
DOI: 10.1016/j.psj.2024.103769 -
Database : the Journal of Biological... Jun 2024Major depressive disorder (MDD) is a pressing global health issue. Its pathogenesis remains elusive, but numerous studies have revealed its intricate associations with...
Major depressive disorder (MDD) is a pressing global health issue. Its pathogenesis remains elusive, but numerous studies have revealed its intricate associations with various biological factors. Consequently, there is an urgent need for a comprehensive multi-omics resource to help researchers in conducting multi-omics data analysis for MDD. To address this issue, we constructed the MDDOmics database (Major Depressive Disorder Omics, (https://www.csuligroup.com/MDDOmics/), which integrates an extensive collection of published multi-omics data related to MDD. The database contains 41 222 entries of MDD research results and several original datasets, including Single Nucleotide Polymorphisms, genes, non-coding RNAs, DNA methylations, metabolites and proteins, and offers various interfaces for searching and visualization. We also provide extensive downstream analyses of the collected MDD data, including differential analysis, enrichment analysis and disease-gene prediction. Moreover, the database also incorporates multi-omics data for bipolar disorder, schizophrenia and anxiety disorder, due to the challenge in differentiating MDD from similar psychiatric disorders. In conclusion, by leveraging the rich content and online interfaces from MDDOmics, researchers can conduct more comprehensive analyses of MDD and its similar disorders from various perspectives, thereby gaining a deeper understanding of potential MDD biomarkers and intricate disease pathogenesis. Database URL: https://www.csuligroup.com/MDDOmics/.
Topics: Depressive Disorder, Major; Humans; Databases, Genetic; Polymorphism, Single Nucleotide; Genomics; DNA Methylation; Multiomics
PubMed: 38917209
DOI: 10.1093/database/baae042 -
BioRxiv : the Preprint Server For... Jun 2024The ability to deliver large transgenes to a single genomic sequence with high efficiency would accelerate biomedical interventions. Current methods suffer from low...
The ability to deliver large transgenes to a single genomic sequence with high efficiency would accelerate biomedical interventions. Current methods suffer from low insertion efficiency and most rely on undesired double-strand DNA breaks. Serine integrases catalyze the insertion of large DNA cargos at attachment (att) sites. By targeting att sites to the genome using technologies such as prime editing, integrases can target safe loci while avoiding double-strand breaks. We developed a method of phage-assisted continuous evolution we call IntePACE, that we used to rapidly perform hundreds of rounds of mutagenesis to systematically improve activity of PhiC31 and Bxb1 serine integrases. Novel hyperactive mutants were generated by combining synergistic mutations resulting in integration of a multi-gene cargo at rates as high as 80% of target chromosomes. Hyperactive integrases inserted a 15.7 kb therapeutic DNA cargo containing Von Willebrand Factor. This technology could accelerate gene delivery therapeutics and our directed evolution strategy can easily be adapted to improve novel integrases from nature.
PubMed: 38915697
DOI: 10.1101/2024.06.10.598370 -
BioRxiv : the Preprint Server For... Jun 2024DNA nanotechnology relies on programmable anchoring of regions of single-stranded DNA through base pair hybridization to create nanoscale objects such as polyhedra,...
DNA nanotechnology relies on programmable anchoring of regions of single-stranded DNA through base pair hybridization to create nanoscale objects such as polyhedra, tubes, sheets, and other desired shapes. Recent work from our lab measured energetics of base-stacking interactions and suggested that terminal stacking interactions between two adjacent strands could be an additional design parameter for DNA nanotechnology. Here, we explore that idea by creating DNA tetrahedra held together with sticky ends which contain identical base pairing interactions but different terminal stacking interactions. Testing all 16 possible combinations, we found that the melting temperature of DNA tetrahedra varied by up to 10 °C from altering a single base stack in the design while retaining a common sequence in a 6-nt sticky end. This work clearly shows that stacking design influences DNA tetrahedra stability in a substantial and predictable way. The results likely apply to other types of DNA nanostructures and suggest that terminal stacking interactions play an integral role in formation and stability of DNA nanostructures.
PubMed: 38915531
DOI: 10.1101/2024.06.10.598265 -
BioRxiv : the Preprint Server For... Jun 2024Understanding how the number, placement and affinity of transcription factor binding sites dictates gene regulatory programs remains a major unsolved challenge in...
Understanding how the number, placement and affinity of transcription factor binding sites dictates gene regulatory programs remains a major unsolved challenge in biology, particularly in the context of multicellular organisms. To uncover these rules, it is first necessary to find the binding sites within a regulatory region with high precision, and then to systematically modulate this binding site arrangement while simultaneously measuring the effect of this modulation on output gene expression. Massively parallel reporter assays (MPRAs), where the gene expression stemming from 10,000s of in vitro-generated regulatory sequences is measured, have made this feat possible in high-throughput in single cells in culture. However, because of lack of technologies to incorporate DNA libraries, MPRAs are limited in whole organisms. To enable MPRAs in multicellular organisms, we generated tools to create a high degree of mutagenesis in specific genomic loci using base editing. Targeting GFP integrated in genome of cell culture and whole animals as a case study, we show that the base editor AID stemming from sea lamprey fused to nCas9 is highly mutagenic. Surprisingly, longer gRNAs increase mutation efficiency and expand the mutating window, which can allow the introduction of mutations in previously untargetable sequences. Finally, we demonstrate arrays of >20 gRNAs that can efficiently introduce mutations along a 200bp sequence, making it a promising tool to test enhancer function in a high throughput manner.
PubMed: 38915503
DOI: 10.1101/2024.06.10.598328