51. Additional file 2 of Large-scale genomic analysis of antimicrobial resistance in the zoonotic pathogen Streptococcus suis
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Hadjirin, Nazreen F., Miller, Eric L., Murray, Gemma G. R., Yen, Phung L. K., Phuc, Ho D., Wileman, Thomas M., Hernandez-Garcia, Juan, Williamson, Susanna M., Parkhill, Julian, Maskell, Duncan J., Zhou, Rui, Fittipaldi, Nahuel, Gottschalk, Marcelo, Tucker, A. W. ( Dan), Hoa, Ngo Thi, Welch, John J., and Weinert, Lucy A.
- Abstract
Additional file 2: Figures S1-S13 and Table S2. Fig S1 – Phylogenetic tree. Fig S2 – MICs in Canada & the UK. Fig S3 - The effects of candidate determinants on MIC for beta-lactams Fig S4 - The effects of candidate determinants on MIC for MLSB. Fig S5 - The effects of candidate alleles on MIC for tetracyclines. Fig S6 - The effects of candidate alleles on MIC for fluoroquinolone. Fig S7 - The effects of candidate alleles on MIC for the aminoglycoside, spectinomycin. Fig S8 - The effects of candidate alleles on MIC for the pleuromutilin, tiamulin. Fig S9 - The effects of candidate alleles on MIC for trimethoprim (TMP). Fig S10 - Variation in the presence of candidate AMR determinants explains consistent differences between genetic clusters. Fig S11 - Methods of using candidate determinants to predict MIC. Fig S12 - Allelic variation in ermB and unidentified sources of epistasis. Fig S13 -High levels of ‘nestedness’ suggest that resistance determinants to beta-lactams are acquired in a particular order. Table S2 - Binomial tests showing that novel AMR variants are independently associated with MIC in different genetic clusters.
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- 2021
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