Detection of carbapenems resistant k-mer sequences in bacteria of critical priority by the world health organization (pseudomonas aeruginosa and acinetobacter baumannii) Academic Article in Scopus uri icon

abstract

  • © 2020 IEEE.Antimicrobial resistance (AMR) (or drug resistance) is a natural phenomenon where microorganisms change their molecular, physical, or chemical structures to resist the drugs created by infections. The World Health Organization (WHO) had released for the first time a list of Multidrug-Resistant Bacteria (MRB) that pose the greatest threat to human health, and for which new antibiotics are desperately needed. Acinetobacter baumannii and Pseudomonas aeruginosa resistant to carbapenems are part of the Gramnegative group non-fermenting bacilli with critical priority according to the WHO. For this, the research final purpose was to create and train a bioinformatic study capable of finding critical k-mers that could differentiate those strains of P. aeruginosa and A. baumannii resistant to carbapenems. At the end, two sets of k-mers for both pathogens were obtained. Three Machine Learning algorithms were performed to prove the use of these k-mers in antimicrobial prediction Random Forest, Adaboost, and Xgboost. For Pseudomonas aeruginosa, an accuracy of 0.8 was obtained using Random Forest, an accuracy of 0.92 using Adaboost, and an accuracy of 0.84 when using Xgboost. In the case of Acinetobacter baumannii, an accuracy of 0.98 was obtained when using Random Forest and an accuracy of 0.99 when using Adaboost or Xgboost. To investigate the sequences of the k-mers obtained, the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool BLAST was used. Twenty sequences built with the k-mers were investigated for each bacteria. For A. baumannii, 18 out of 20 sequences represented a key sequence in antibiotic resistance. In the case of P. aeruginosa, 16 out of 20 sequences represented a key sequence. Further investigation over these sequences can be applied in creating new directed antibiotics or detecting easily resistant strains of Pseudomona aeruginosa or Acinetobacter baumannii resistant to carbapenems.

publication date

  • December 14, 2020