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- 2019
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Journal article (peer-reviewed)
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| 2. |
- Liu, Zhigang, et al.
(author)
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Gut microbiota mediates intermittent-fasting alleviation of diabetes-induced cognitive impairment
- 2020
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In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723 .- 2041-1723. ; 11:1, s. 855-
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Journal article (peer-reviewed)abstract
- Cognitive decline is one of the complications of type 2 diabetes (T2D). Intermittent fasting (IF) is a promising dietary intervention for alleviating T2D symptoms, but its protective effect on diabetes-driven cognitive dysfunction remains elusive. Here, we find that a 28-day IF regimen for diabetic mice improves behavioral impairment via a microbiota-metabolites-brain axis: IF enhances mitochondrial biogenesis and energy metabolism gene expression in hippocampus, re-structures the gut microbiota, and improves microbial metabolites that are related to cognitive function. Moreover, strong connections are observed between IF affected genes, microbiota and metabolites, as assessed by integrative modelling. Removing gut microbiota with antibiotics partly abolishes the neuroprotective effects of IF. Administration of 3-indolepropionic acid, serotonin, short chain fatty acids or tauroursodeoxycholic acid shows a similar effect to IF in terms of improving cognitive function. Together, our study purports the microbiota-metabolites-brain axis as a mechanism that can enable therapeutic strategies against metabolism-implicated cognitive pathophysiologies.
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| 3. |
- He, Yafang, et al.
(author)
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Metabolomic Changes Upon Conjugated Linoleic Acid Supplementation and Predictions of Body Composition Responsiveness
- 2022
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In: Journal of Clinical Endocrinology and Metabolism. - : The Endocrine Society. - 1945-7197 .- 0021-972X. ; 107:9, s. 2606-2615
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Journal article (peer-reviewed)abstract
- Context Conjugated linoleic acid (CLA) may optimize body composition, yet mechanisms underlining its benefits are not clear in humans. Objective We aimed to reveal the CLA-induced changes in the plasma metabolome associated with body composition improvement and the predictive performance of baseline metabolome on intervention responsiveness. Methods Plasma metabolome from overnight fasted samples at pre- and post-intervention of 65 participants in a 12-week randomized, placebo-controlled trial (3.2 g/day CLA vs 3.2 g/day sunflower oil) were analyzed using untargeted LC-MS metabolomics. Mixed linear model and machine learning were applied to assess differential metabolites between treatments, and to identify optimal panel (based on baseline conventional variables vs metabolites) predicting responders of CLA-derived body composition improvement (increased muscle variables or decreased adiposity variables) based on dual-energy x-ray absorptiometry. Results Compared with placebo, CLA altered 57 metabolites (P
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| 4. |
- Nilsson, R. Henrik, 1976, et al.
(author)
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Improving ITS sequence data for identification of plant pathogenic fungi
- 2014
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In: Fungal Diversity. - : Springer Science and Business Media LLC. - 1560-2745 .- 1878-9129. ; 67:1, s. 11-19
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Journal article (peer-reviewed)abstract
- Plant pathogenic fungi are a large and diverse assemblage of eukaryotes with substantial impacts on natural ecosystems and human endeavours. These taxa often have complex and poorly understood life cycles, lack observable, discriminatory morphological characters, and may not be amenable to in vitro culturing. As a result, species identification is frequently difficult. Molecular (DNA sequence) data have emerged as crucial information for the taxonomic identification of plant pathogenic fungi, with the nuclear ribosomal internal transcribed spacer (ITS) region being the most popular marker. However, international nucleotide sequence databases are accumulating numerous sequences of compromised or low-resolution taxonomic annotations and substandard technical quality, making their use in the molecular identification of plant pathogenic fungi problematic. Here we report on a concerted effort to identify high-quality reference sequences for various plant pathogenic fungi and to re-annotate incorrectly or insufficiently annotated public ITS sequences from these fungal lineages. A third objective was to enrich the sequences with geographical and ecological metadata. The results – a total of 31,954 changes – are incorporated in and made available through the UNITE database for molecular identification of fungi (http://unite.ut.ee), including standalone FASTA files of sequence data for local BLAST searches, use in the next-generation sequencing analysis platforms QIIME and mothur, and related applications. The present initiative is just a beginning to cover the wide spectrum of plant pathogenic fungi, and we invite all researchers with pertinent expertise to join the annotation effort.
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