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Engelsen, S. B.

Publications and source records attributed to Engelsen, S. B..

5 recordsLinked to original sources

Untargeted metabolomics reveals farming practice- and cultivar-driven modulations of pea (Pisum sativum L.) seed metabolome

This work presents untargeted LC-MS-based metabolome of ten cultivars of peas grown at three field sites following different agricultural practices. More than 1,200 metabolite features were detected in methanolic extracts of pea seed flours. Of these, nearly 300 features were identified using mass spectral libraries and advanced computational tools. Approximately 40 metabolites were found to be associated with location effect, independent of cultivar type. Organically grown pea samples showed lower level of the main pea triterpene glycoside soyasaponin I and higher levels of nitrogen-abundant amino acids indicating increased nitrogen availability in soil. More than 100 metabolites were associated with the location-independent cultivar effect. Two cultivars resistant to downy mildew and pea wilt, Akooma and Greenway, showed the most distinct metabolome with greater levels of polyunsaturated fatty acids and lipid oxidation products known to give beany off-flavors. The most commonly cultivated pea variety, Ingrid, had significantly lower levels or was completely devoid of hydroxycinnamic acid amides such as caffeoyl, feruloyl, and coumaroyl aspartates that were present in all other cultivars. Three chloroauxin metabolites, reported here for the first time, were identified through molecular networking within GNPS platform and propagation of annotation from a computationally predicted indole-3-acetic acid catabolite. Overall, the results indicate biochemical adaptation of pea plants to location or agricultural practice as reflected in their seed metabolome.

plant biology↗

Gut microbiome and its cofactors are linked tolipoprotein distribution profiles

Increasing evidence indicates that the gut microbiome (GM) plays an important role in the etiology of dyslipidemia. To date, however, no in-depth characterization of the associations between GM and its metabolic attributes with deep profiling of lipoproteins distributions (LPD) among healthy individuals has been conducted. To determine associations and contributions of GM composition and its cofactors with distribution profiles of lipoprotein subfractions, we studied blood plasma LPD, fecal short-chain fatty acids (SCFA) and GM of 262 healthy Danish subjects aged 19-89 years. Stratification of LPD segregated subjects into three clusters of profiles that reflected differences in the lipoprotein subclasses, corresponded well with limits of recommended levels of main lipoprotein fractions and were largely explained by host characteristics such as age and body mass index. Higher levels of HDL, particularly driven by large subfractions (HDL2a and HDL2b), were associated with a higher relative abundance of Ruminococcaceae and Christensenellaceae. Increasing levels of total cholesterol and LDL, which were primarily associated with large 1 and 2 subclasses, were positively associated with Lachnospiraceae and Coriobacteriaceae, and negatively with Bacteroidaceae and Bifidobacteriaceae. Metagenome sequencing showed a higher abundance of genes involved in the biosynthesis of multiple B-vitamins and SCFA metabolism among subjects with healthier LPD profiles. Metagenomic assembled genomes (MAGs) affiliated mainly to Eggerthellaceae and Clostridiales were identified as the contributors of these genes and whose relative abundance correlated positively with larger subfractions of HDL. The results of this study demonstrate that remarkable differences in composition and metabolic traits of the GM are associated with variations in LPD among healthy subjects. Findings from this study provide evidence for GM considerations in future research aiming to shade light on mechanisms of the GM - dyslipidemia axis.

systems biology↗

Human blood lipoprotein predictions from 1H NMR spectra: protocol, model performances and cage of covariance

Lipoprotein subfractions are biomarkers for early diagnosis of cardiovascular diseases. The reference method, ultracentrifugation, for measuring lipoproteins is time consuming and there is a need to develop a rapid method for cohort screenings. Here we present partial least squares regression models developed using 1H-NMR spectra and concentrations of lipoproteins as measured by ultracentrifugation on 316 healthy Danes. Different regions of the 1H-NMR spectra representing signals of the lipoproteins and different lipid species were investigated to develop parsimonious, reliable and best performing prediction models. 65 LP main and subfractions were predictable with an accuracy Q2 of > 0.6 on test set samples. The models were tested on an independent cohort of 290 healthy Swedes with predicted and reference values matching by up to 85-95%. The software was developed to predict lipoproteins in human blood using 1H-NMR spectra and made freely available to be applied for future cohort screenings.

systems biology↗

Gut Mycobiome Dysbiosis Is Linked to Hypertriglyceridemia among Home Dwelling Elderly Danes

Gut microbial dysbiosis have been linked to frailty in elderly, yet the presence of fungal communities and their possible association with host health are little understood. This study attempts to identify gut microbial fungal associations with the progression of atherogenic dyslipidemia in a population of older adults by investigating the interplay between dietary intake, gut mycobiome composition, plasma and fecal metabolome and anthropometric/body-composition measurements of 99 Danes aged 65 to 81 (69.57 {+/-} 3.64) years. The gut mycobiome composition were determined by high-throughput sequencing of internal transcribed spacer (ITS2) gene amplicons, while the plasma and fecal metabolome was determined by GC-MS. The gut microbiome of the subjects investigated is home to three main eukaryotic phyla, namely Ascomyco-ta, Basidiomycota and Zygomycota, with genera Penicillium, Candida, and Aspergillus being particularly common. Hypertriglyceridemia was associated with fewer observed fungal species, and Bray-Curtis dissimilarity matrix-based analysis showed significant (p < 0.05) clustering according to fasting levels of circulating plasma triglycerides (Tg) and very low-density lipoprotein (VLDL) cholesterol fasting levels, respectively. Higher levels of Tg and VLDL cholesterol significantly associates with increased relative abundance of genus Penicillium, and Saccha:ramyces likely mediated by a higher dietary fatty acids intake (p < 0.05), and Sac-charomyces, Debaryomyces, Candida, Agaricus and Starmerella were moderately associated with SCF As groups. Collectively, these findings suggest that gut mycobiome dysbiosis on older adults is associated with hypertriglyceridemia, a known risk factor for development of cardiovascular disease.

microbiology↗

Physical fitness in community dwelling older adults is linked to dietary intake, gut microbiota and metabolomic signatures

When humans age, changes in body composition arise along with lifestyle-associated disorders influencing fitness and physical decline. Here we provide a comprehensive view of dietary intake, physical activity, gut microbiota (GM) and host metabolome in relation to physical fitness of 207 community dwelling subjects aged +65 years. Stratification on anthropometric/body-composition/physical-performance measurements (ABPm) variables identified two phenotypes (high/low-fitness) clearly linked to dietary intake, physical activity, GM and host metabolome patterns. Strikingly, despite a higher energy intake high-fitness subjects were characterized by leaner bodies and lower fasting proinsulin-C-peptide/blood glucose levels in a mechanism likely driven by higher dietary-fiber intake, physical activity and increased abundance of Bifidobacteriales and Clostridiales species in GM and associated metabolites (i.e. enterolactone). These factors explained 50.1% of the individual variation in physical fitness. We propose that targeting dietary strategies for modulation of GM and host metabolome interactions may allow establishing therapeutic approaches to delay and possibly revert comorbidities of aging.

cell biology↗