Prevalence of Shiga Toxin-Producing Escherichia coli O157 in Wild Scottish Deer with High Human Pathogenic Potential

Autor: Stephen F. Fitzgerald, Mairi C. Mitchell, Anne Holmes, Lesley Allison, Margo Chase-Topping, Nadejda Lupolova, Beth Wells, David L. Gally, Tom N. McNeilly

Publikováno v: Animals, Vol 13, Iss 17, p 2795 (2023)

Shiga toxin-producing E. coli (STEC) infections associated with wildlife are increasing globally, highlighting many ‘spillover’ species as important reservoirs for these zoonotic pathogens. A human outbreak of STEC serogroup O157 in 2015 in Scotl

Externí odkaz: https://doaj.org/article/baae74794d504346a7589463fc82fae1

Genome structural variation in

Autor: Stephen F, Fitzgerald, Nadejda, Lupolova, Sharif, Shaaban, Timothy J, Dallman, David, Greig, Lesley, Allison, Sue C, Tongue, Judith, Evans, Madeleine K, Henry, Tom N, McNeilly, James L, Bono, David L, Gally

Publikováno v: Microbial Genomics

The human zoonotic pathogen Escherichia coli O157:H7 is defined by its extensive prophage repertoire including those that encode Shiga toxin, the factor responsible for inducing life-threatening pathology in humans. As well as introducing genes that

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::08ac60a812a084a913ed3b4918ea4cd5
https://pubmed.ncbi.nlm.nih.gov/34751643

Predicting Host Association for Shiga Toxin-Producing E. coli Serogroups by Machine Learning

Autor: David L. Gally, Antonia Chalka, Nadejda Lupolova

Publikováno v: Methods in Molecular Biology ISBN: 9781071613382

Escherichia coli is a species of bacteria that can be present in a wide variety of mammalian hosts and potentially soil environments. E. coli has an open genome and can show considerable diversity in gene content between isolates. It is a reasonable

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5c463185f5e493bf4e1b8b09dda872b8
https://doi.org/10.1007/978-1-0716-1339-9_4

A guide to machine learning for bacterial host attribution using genome sequence data

Autor: David L. Gally, Samantha Lycett, Nadejda Lupolova

Publikováno v: Lupolova, N, Lycett, S & Gally, D 2019, ' A guide to machine learning for bacterial host attribution using genome sequence data ', Microbial Genomics . https://doi.org/10.1099/mgen.0.000317
Microbial Genomics

With the ever-expanding number of available sequences from bacterial genomes, and the expectation that this data type will be the primary one generated from both diagnostic and research laboratories for the foreseeable future, then there is both an o

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b496dea9cbb6002b196d7098f478c2f6
https://hdl.handle.net/20.500.11820/b587fac3-aaad-4c9d-bacb-960d1eebe81f

Patchy promiscuity: machine learning applied to predict the host specificity of Salmonella enterica and Escherichia coli

Autor: Timothy J. Dallman, David L. Gally, Nicola Holden, Nadejda Lupolova

Publikováno v: Lupolova, N, Dallman, T, Holden, N & Gally, D 2017, ' Patchy promiscuity: machine learning applied to predict the host specificity of Salmonella enterica and Escherichia coli ', Microbial Genomics, vol. 3, no. 10, 2017;3 . https://doi.org/10.1099/mgen.0.000135

Salmonella enterica and Escherichia coli are bacterial species that colonize different animal hosts with sub-types that can cause life-threatening infections in humans. Source attribution of zoonoses is an important goal for infection control as is i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4268d01e592840c3cc06f5f32db506a6
https://www.pure.ed.ac.uk/ws/files/44481099/mgen000135.pdf