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Ziegler, T. R.

Publications and source records attributed to Ziegler, T. R..

2 recordsLinked to original sources

Diet-Microbiome Analysis in a Healthy Cohort Reveals Potential Role of Intestinal Microbiota in Metabolism

Both preclinical and clinical studies have revealed the indisputable importance of intestinal bacterial community composition in pathogenesis of various disease states, from obesity to neurodegeneration. Diet remains one of the most important factors shaping human intestinal microbiota composition. In this study, we investigated diet-microbiome interactions in a healthy cohort of 88 participants from Atlanta and Calgary. We examine microbial composition (16S rRNA sequencing) with dietary records using Spearman Correlation tests with Benjamini-Hochberg multiple hypothesis correction to make community-level comparisons between dietary scores and microbial diversity index scores. Predictive models were used for molecular-level comparisons between microbial gene pathways and molecules. Among generalized dietary and microbial indices, we identified a negative association between dietary whole grain consumption and a microbial dysbiosis score. Comparisons between dietary food groups and bacterial family abundance reveal significant associations between dairy consumption and Lactobacillaceae abundance, dietary unsaturated to saturated fatty acid ratio and Clostridia Cluster Family XIII, salt intake and Lachnospiraceae, and consumption of greens and beans and Veillonellaceae. Predictive models of microbial gene pathways and molecules reveal significant positive associations between several dietary fatty acids and microbial short-chain fatty acid fermentation pathways, and between dietary lignans and archaeal methanogenesis pathways. Overall, these associations may inform future explorations on specific dietary interventions to impact the gut microbiome. IMPORTANCEIn this study, we compare dietary records and composition of intestinal microbes in a cohort of 88 participants. We identified associations between dietary consumption of dairy and the presence of dairy-consuming bacteria called Lactobacteriaceae and between consumption of dietary fats and the presence of fat-consuming bacteria called Clostridia. Using predictive analysis, we identify specific fatty acids associated with specific biochemical pathways found in Clostridia that might underlie these associations, in addition to an association between archaeal microbes and dietary consumption of estrogen-binding molecules called lignans, which are commonly found in whole grains and vegetables. Overall, our study generates useful associations between diet and intestinal microbes that can be tested in experiments that may help scientists use diet to control intestinal microbes in order to improve human health.

microbiology↗

Metabolic Trajectories During Surgical Stress in Patients Undergoing Cardiac Surgery

Stress hyperglycemia (SH) during acute illness is linked to adverse surgical outcomes, yet the accompanying metabolic perturbations are incompletely characterized. We profiled longitudinal metabolic changes in adults without diabetes undergoing cardiac surgery to identify pathways associated with perioperative SH (defined as point-of-care glucose [≥]140 mg/dL on [≥]3 readings or [≥]180 mg/dL once). Blood was collected at baseline before surgery (T0) and at 2 h (T1), 24-48 h (T2), and 72-96 h (T3) after surgical initiation. High-resolution metabolomics (LC-MS) was integrated with continuous glucose monitoring and inflammatory/cardiac biomarkers. At T0, several pathways were associated with subsequent SH, including bile acid metabolism, the carnitine shuttle, and fatty-acid oxidation, suggesting preoperative metabolic susceptibility. In longitudinal analyses, participants who developed SH showed coordinated postoperative changes with significant enrichment of pathways not evident at baseline, C21-steroid hormone biosynthesis, glycerophospholipid metabolism, and glycosphingolipid (ceramide) metabolism, consistent with lipid remodeling and inflammatory signaling during surgical stress. Individuals with SH also exhibited higher inflammatory biomarker levels (high-sensitivity C-reactive protein and soluble urokinase plasminogen activator receptor). A machine-learning model using early metabolomic features predicted SH with an area under the receiver operating characteristic curve of 0.86. These findings highlight distinct preoperative and perioperative metabolic trajectories associated with SH and implicate established dysglycemia-related pathways, as well as stress-induced pathways in perioperative metabolic dysregulation. Pathway enrichment analyses were exploratory and hypothesis-generating; validation in larger cohorts and assessment of implications for clinical outcomes are warranted.

biochemistry↗