Minimum Inhibitory Concentrations (MICs) for β-lactam Antibiotics Predicted by Penicillin Binding Protein Gene Types

The CDC Streptococcus Laboratory has created procedures for using whole-genome sequencing data to predict phenotypic susceptibility results for a range of antibiotics. For beta-lactam antibiotics, the procedure uses newly-defined Penicillin Binding Protein (PBP) types, which are based on transpeptidase-encoding regions of PBP proteins 1a, 2b, and 2x. Using a machine learning algorithm an isolate’s PBP type sequence can predict a specific level of resistance to penicillin and other beta-lactam antibiotics.1, 2, 3, 4

Below are the MICs and the links to the algorithm and the most up to date PBP type sequence database.

SPN Pipeline

Strep Lab PBP sequence database



1Metcalf BJ, Gertz RE Jr, Gladstone RA, et al. Strain features and distributions in pneumococci from children with invasive disease before and after 13-valent conjugate vaccine implementation in the USA. Clin Microbiol Infect. 2016;22(1):60 e9–60.

2Metcalf BJ, Chochua S, Gertz RE Jr, et al. Using whole genome sequencing to identify resistance determinants and predict antimicrobial resistance phenotypes for year 2015 invasive pneumococcal disease isolates recovered in the United States. Clin Microbiol Infect. 2016;22(12):1002.e1–1002.e8.

3CDC Strep Lab GAS bioinformatic pipelines for S. agalactiae, S. pyogenes, and S. pneumoniae.

4Li Y, Metcalf BJ, Chochua S, et al. Penicillin-binding protein transpeptidase signatures for tracking and predicting β-lactam resistance levels in Streptococcus pneumoniae. mBio. 2016;7(3):60 pii:e00756–16.