Biology subjects

Faust, K.

Publications and source records attributed to Faust, K..

21 records · Page 2Linked to original sources

bioRxiv2020

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↗

bioRxiv2019

manta - a clustering algorithm for weighted ecological networks

Microbial network inference and analysis has become a successful approach to generate biological hypotheses from microbial sequencing data. Network clustering is a crucial step in this analysis. Here, we present a novel heuristic flow-based network clustering algorithm, which equals or outperforms existing algorithms on noise-free synthetic data. manta comes with unique strengths such as the ability to identify nodes that represent an intermediate between clusters, to exploit negative edges and to assess the robustness of cluster membership. manta does not require parameter tuning, is straightforward to install and run, and can easily be combined with existing microbial network inference tools.

bioinformatics↗

bioRxiv2018

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a synthetic gut community

Whereas the composition of the human gut microbiome is relatively well resolved, predictive understanding of its response to perturbations such as diet shifts is still lacking. Here, we followed a bottom-up strategy to explore human gut community dynamics. We established a synthetic community composed of three representative human gut isolates in well-controlled conditions in vitro. We then explored species interactions by performing all mono- and pair-wise fermentation experiments and quantified with a mechanistic community model how well tri-culture dynamics was predicted from mono-culture data. With the model as a reference, we demonstrated that species grown in co-culture behaved differently than in mono-culture and confirmed their altered behavior at the transcriptional level. In addition, we showed with replicate tri-cultures and in simulations that dominance in tri-culture sensitively depends on initial conditions. Our work has important implications for gut microbial community modeling as well as ecological interaction detection from batch cultures.

bioinformatics↗