Laura Wosinska

Mrs. Laura Wosinska


Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 September 2019 in Nutrients
Verified
Journal Article
Open access
PDF file
LWLaura Wosinska
Laura Wosinska
PCPaul Cotter
Paul Cotter
CGCaitriona Guinane
Caitriona Guinane
CGCaitriona Guinane
Caitriona Guinane
There is accumulating evidence that physical fitness influences the gut microbiome and as a result, promotes health. Indeed, exercise-induced alterations in the gut microbiome can influence health parameters crucial to athletic performance, specifically, immune function, lower susceptibility to infection, inflammatory response and tissue repair. Consequently, maintenance of a healthy gut microbiome is essential for an athlete’s health, training and performance. This review explores the effect of exercise on the microbiome while also investigating the effect of probiotics on various potential consequences associated with over-training in athletes, as well as their associated health benefits.

24 March 2022 in Microorganisms
Verified
Journal Article
Open access
PDF file
LWLaura Wosinska
Laura Wosinska
CWCalum J. Walsh
Calum J. Walsh
POPaula M. O'Connor
Paula M. O'Connor
ELElaine M. Lawton
Elaine M. Lawton
PCPaul Cotter
Paul Cotter
Orla O'sullivanOrla O'sullivan
Orla O'sullivan
Exercise reduces inflammation, fatigue, and aids overall health. Additionally, physical fitness has been associated with desirable changes in the community composition of the athlete gut microbiome, with health-associated taxa being shown to be increased in active individuals. Here, using a combination of in silico and in vitro methods, we investigate the antimicrobial activity of the athlete gut microbiome. In vitro approaches resulted in the generation of 284 gut isolates with inhibitory activity against Clostridioides difficile and/or Fusobacterium nucleatum, and the most potent isolates were further characterized, and potential bacteriocins were predicted using both MALDI-TOF MS and whole-genome sequencing. Additionally, metagenomic reads from the faecal samples were used to recover 770 Metagenome Assembled Genomes (MAGs), of which 148 were assigned to be high-quality MAGs and screened for the presence of putative bacteriocin gene clusters using BAGEL4 software, with 339 gene clusters of interest being identified. Class I was the most abundant bacteriocin class predicted, accounting for 91.3% of predictions, Class III had a predicted abundance of 7.5%, and Class II was represented by just 1% of all predictions.