Project description:Background - Prepregnancy overweight and obesity promote deleterious health impacts on both mothers during pregnancy and the offspring. Significant changes in the maternal peripheral blood mononuclear cells (PBMCs) gene expression due to obesity are well-known. However, during pregnancy the impact of overweight on immune cell gene expression and its association with maternal and infant outcomes is not well explored. Methods – Blood samples were collected from healthy normal weight (NW, BMI 18.5-24.9) or overweight (OW, BMI 25-29.9) 2nd parity pregnant women at 12, 24 and 36 weeks of pregnancy. PBMCs were isolated from the blood and subjected to mRNA sequencing. Maternal and infant microbiota were analyzed by 16S rRNA gene sequencing. Integrative multi-omics data analysis was performed to evaluate the association of gene expression with maternal diet, gut microbiota, milk composition, and infant gut microbiota. Results - Gene expression analysis revealed that 453 genes were differentially expressed in the OW women compared to NW women at 12 weeks of pregnancy, out of which 354 were upregulated and 99 were downregulated. Several up-regulated genes in the OW group were enriched in inflammatory, chemokine-mediated signaling and regulation of interleukin-8 production-related pathways. At 36 weeks of pregnancy healthy eating index score was positively associated with several genes that include, DTD1, ELOC, GALNT8, ITGA6-AS1, KRT17P2, NPW, POT1-AS1 and RPL26. In addition, at 36 weeks of pregnancy, genes involved in adipocyte functions, such as NG2 and SMTNL1, were negatively correlated to human milk 2’FL and total fucosylated oligosaccharides content collected at 1 month postnatally. Furthermore, infant Akkermansia was positively associated with maternal PBMC anti-inflammatory genes that include CPS1 and RAB7B, at 12 and 36 weeks of pregnancy. Conclusions – These findings suggest that prepregnancy overweight impacts the immune cell gene expression profile, particularly at 12 weeks of pregnancy. Further, deciphering the complex association of PBMC’s gene expression levels with maternal gut microbiome and milk composition and infant gut microbiome may aid in developing strategies to mitigate obesity-mediated effects.
Project description:The human gut is colonized by trillions of microorganisms that influence human health and disease through the metabolism of xenobiotics, including therapeutic drugs and antibiotics. The diversity and metabolic potential of the human gut microbiome have been extensively characterized, but it remains unclear which microorganisms are active and which perturbations can influence this activity. Here, we use flow cytometry, 16S rRNA gene sequencing, and metatranscriptomics to demonstrate that the human gut contains distinctive subsets of active and damaged microorganisms, primarily composed of Firmicutes, which display marked temporal variation. Short-term exposure to a panel of xenobiotics resulted in significant changes in the physiology and gene expression of this active microbiome. Xenobiotic-responsive genes were found across multiple bacterial phyla, encoding novel candidate proteins for antibiotic resistance, drug metabolism, and stress response. These results demonstrate the power of moving beyond DNA-based measurements of microbial communities to better understand their physiology and metabolism. RNA-Seq analysis of the human gut microbiome during exposure to antibiotics and therapeutic drugs.
Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.
Project description:In a prior report, we observed two distinct lung microbiomes in healthy subjects that we termed â??pneumotypesâ??: pneumotypeSPT, characterized by high bacterial load and supraglottic predominant taxa (SPT) such as the anaerobes Prevotella and Veillonella; and pneumotypeBPT, with low bacterial burden and background predominant taxa (BPT) found in the saline lavage and bronchoscope. Here, we determined the prevalence of these two contrasting lung microbiome types, in a multi-center study of healthy subjects. We confirmed that a lower airway microbiome enriched with upper airway microbes (pneumotypeSPT) was present in ~45% of healthy individuals. Cross-sectional Multicenter cohort. BAL of 49 healthy subjects from three cohort had their lower airway microbiome assessed by 16S rDNA sequencing and microbial gene content (metagenome) was computationally inferred from taxonomic assignments. The amplicons from total 100 samples are barcoded; the barcode and other clinical characteristics (e.g. inflammatory biomarkers and metabolome data) for each sample are provided in the 'Pneumotype.sep.Map.A1.txt' file.
Project description:The objectives of this study were to establish a microbiome profile for oral epithelial dysplasia using archival lesion swab samples to characterize the community variations and the functional potential of the microbiome using 16S rRNA gene sequencing
Project description:In this paper, we first report that EC smoking significantly increases the odds of gingival inflammation. Then, we seek to identify and explain the mechanism that underlies the relationship between EC smoking and gingival inflammation via the oral microbiome. We performed mediation analyses to assess if EC smoking affects the oral microbiome, which in turn affects gingival inflammation. For this, we collected saliva and subgingival samples from EC users and non-users and profiled their microbial compositions via 16S rRNA amplicon sequencing. We then performed α-diversity, β-diversity, and taxonomic differential analyses to survey the disparity in microbial composition between EC users and non-users. We found significant increases in α-diversity in EC users and disparities in β-diversity between EC users and non-users.
Project description:Breastfeeding is vital for reducing morbidity and mortality, yet exclusive breastfeeding rates are low, with insufficient milk supply being a major weaning factor whose molecular causes remain largely unknown. In this study, we collected fresh milk samples from 30 lactating individuals, classified as low, normal, or high milk producers at multiple postpartum stages, and conducted extensive genomic and microbiome analysis. Using bulk RNA sequencing on human milk fat globules (MFG), milk cells, and breast tissue, we found that MFG-derived RNA closely resembles RNA from milk luminal cells. Furthermore, bulk and single-cell RNA-seq revealed changes in the transcriptome and cellular content linked to milk production. We identified specific genes and cell-type proportions differing in low and high milk production. Infant microbiome diversity was affected by feeding type, but not by maternal milk supply. This study provides a comprehensive human milk transcriptomic catalog, identifies genes associated with milk production, and highlights MFG as a useful biomarker for milk transcriptome analysis.
Project description:Breastfeeding is vital for reducing morbidity and mortality, yet exclusive breastfeeding rates are low, with insufficient milk supply being a major weaning factor whose molecular causes remain largely unknown. In this study, we collected fresh milk samples from 30 lactating individuals, classified as low, normal, or high milk producers at multiple postpartum stages, and conducted extensive genomic and microbiome analysis. Using bulk RNA sequencing on human milk fat globules (MFG), milk cells, and breast tissue, we found that MFG-derived RNA closely resembles RNA from milk luminal cells. Furthermore, bulk and single-cell RNA-seq revealed changes in the transcriptome and cellular content linked to milk production. We identified specific genes and cell-type proportions differing in low and high milk production. Infant microbiome diversity was affected by feeding type, but not by maternal milk supply. This study provides a comprehensive human milk transcriptomic catalog, identifies genes associated with milk production, and highlights MFG as a useful biomarker for milk transcriptome analysis.