| 1. |
- Carr, Victoria R., et al.
(författare)
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Abundance and diversity of resistomes differ between healthy human oral cavities and gut
- 2020
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The global threat of antimicrobial resistance has driven the use of high-throughput sequencing techniques to monitor the profile of resistance genes, known as the resistome, in microbial populations. The human oral cavity contains a poorly explored reservoir of these genes. Here we analyse and compare the resistome profiles of 788 oral cavities worldwide with paired stool metagenomes. We find country and body site-specific differences in the prevalence of antimicrobial resistance genes, classes and mechanisms in oral and stool samples. Within individuals, the highest abundances of antimicrobial resistance genes are found in the oral cavity, but the oral cavity contains a lower diversity of resistance genes compared to the gut. Additionally, co-occurrence analysis shows contrasting ARG-species associations between saliva and stool samples. Maintenance and persistence of antimicrobial resistance is likely to vary across different body sites. Thus, we highlight the importance of characterising the resistome across body sites to uncover the antimicrobial resistance potential in the human body. Antimicrobial resistance (AMR) represents a global health threat. Here, the authors analyse the oral and gut resistomes from metagenomes of diverse populations and find that the oral resistome harbours higher abundance but lower diversity of antimicrobial resistance genes than the gut resistome.
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| 2. |
- Chaudhury, Nayab M A, et al.
(författare)
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Reduced MUC7 mucin sialylation and altered saliva rheology in Sjogren's syndrome associated oral dryness.
- 2016
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Ingår i: Molecular & cellular proteomics : MCP. - 1535-9484. ; 15, s. 1048-1059
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Tidskriftsartikel (refereegranskat)abstract
- Sjogren 's syndrome is a chronic autoimmune disorder characterised by lymphocytic infiltration and hypofunction of salivary and lacrimal glands. This loss of salivary function leads to oral dryness, impaired swallowing and speech and increased infection and is associated with other autoimmune diseases and an increased risk of certain cancers. Despite the implications of this prevalent disease, diagnosis currently takes years, partly due to the diversity in patient presentation. Saliva is a complicated biological fluid with major constituents including heavily glycosylated mucins MUC5B and MUC7, important for its viscoelastic, hydrating and lubricating properties. This study investigated Sjogren 's patient 's perception of dryness (bother index questionnaires) along with the rheological, protein composition and glycan analysis of whole mouth saliva and the saliva on the mucosal surface (residual mucosal saliva) to understand the properties that most affect patient wellbeing. Sjogrenvs patients exhibited a statistically significant reduction in residual mucosal saliva, salivary flow rate and extensional rheology, spinnbarkeit (stringiness). Although the concentration of mucins MUC5B and MUC7 were similar between patients and controls, a comparison of protein Western blotting and glycan staining identified a reduction in mucin glycosylation in Sjogren 's, particularly on MUC7. LC-MS/MS analysis of O -glycans released from MUC7 by β-elimination revealed patients had an increase in core 1 sulfation and an overall reduction in sialylation resulting in a global decline of charged glycans. This was primarily due to the loss of the extended core 2 disialylated structure, with and without fucosylation. A decrease in the extended, fucosylated core 2 disialylated structure on MUC7, residual mucosal wetness and whole mouth saliva flow rate appeared to have a negative and cumulative effect on the perception of oral dryness. The observed changes in MUC7 glycosylation could be a potential diagnostic tool for saliva quality and taken into consideration for future therapies for this multifactorial syndrome.
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| 5. |
- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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| 6. |
- Rosario, Dorines, et al.
(författare)
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Systematic analysis of gut microbiome reveals the role of bacterial folate and homocysteine metabolism in Parkinson's disease
- 2021
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Ingår i: Cell Reports. - : CELL PRESS. - 2211-1247. ; 34:9
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Tidskriftsartikel (refereegranskat)abstract
- Parkinson's disease (PD) is the most common progressive neurological disorder compromising motor functions. However, nonmotor symptoms, such as gastrointestinal (GI) dysfunction, precede those affecting movement. Evidence of an early involvement of the GI tract and enteric nervous system highlights the need for better understanding of the role of gut microbiota in GI complications in PD. Here, we investigate the gut microbiome of patients with PD using metagenomics and serum metabolomics. We integrate these data using metabolic modeling and construct an integrative correlation network giving insight into key microbial species linked with disease severity, GI dysfunction, and age of patients with PD. Functional analysis reveals an increased microbial capability to degrade mucin and host glycans in PD. Personalized community-level metabolic modeling reveals the microbial contribution to folate deficiency and hyperhomo-cysteinemia observed in patients with PD. The metabolic modeling approach could be applied to uncover gut microbial metabolic contributions to PD pathophysiology.
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