Oral Presentation 20th Lancefield International Symposium on Streptococci and Streptococcal Diseases 2017

Prediction of antimicrobial resistance phenotype from whole genome sequences in streptococcus suis (#96)

Nazreen F Hadjirin 1 , Eric Miller 1 , Juan Hernandez-Garcia 1 , Jinghong Wang 1 , Sarah E Peters 1 , Tom M Wileman 1 , Julian Parkhill 2 , Stephen D Bentley 2 , Marcelo Gottschalk 3 , Nahuel Fittipald 3 4 , Duncan J Maskell 1 , Ngo Thi Hoa 5 , Alexander (Dan) W Tucker 1 , Lucy A Weinert 1
  1. University of Cambridge, Cambridge, United Kingdom
  2. The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
  3. Public Health Ontario Laboratory,, Toronto, ON, Canada
  4. Streptococcus suis Laboratory, Faculty of Veterinary Medicine, University of Montreal, Saint-Hyacinthe, QC , Canada
  5. Oxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme,, Hospital for Tropical Diseases, 190 Ben Ham Tu, District 5, Ho Chi Minh City , Vietnam

Streptococcus suis is an important zoonotic pathogen of pigs that has significant economic impact on the pig industry, animal welfare and human health. In UK pigs, it is the second largest cause of systemic disease. This, coupled with the lack of effective vaccines has resulted in the heavy use of antimicrobials within the industry, especially in the water or feed of piglets and, is likely to increase the selection pressure for the development of resistance against antimicrobials.


Development of antimicrobial resistance (AMR) is an increasingly global concern and as such, monitoring of antimicrobial resistance in zoonotic pathogens such as S. suis is of relevance to infection control. However, unlike other streptococcal pathogens, no systematic characterisation of AMR genes and their role in AMR phenotype has been carried out. The current study aims to determine the genetic basis of antimicrobial resistance in S. suis and to build a predictive tool of antimicrobial resistance phenotype from whole genome sequencing data.


Using whole genome sequences from 667 isolates from the UK and Canada, along with minimum inhibitory concentrations for 17 antibiotics widely used antibiotics in the agricultural industry, we show that rates of antimicrobial resistance in S. suis are high. However, in many cases, the resistance phenotypes could not be fully explained by the known resistance genotypes. Therefore we have used genome wide association studies and have uncovered novel resistance mechanisms, which subsequently increased the effectiveness of the prediction tool.