Motivation New antimicrobial resistance mechanisms are emerging and spreading globally, threatening the ability to treat common infectious diseases. The long term goal of this project is to develop an automated procedure to identify and structurally characterise point mutations in bacterial genes that can lead to the rising of antibi- otic resistance. Streptococcus pneumoniae, a gram positive bacterium responsible for several community-acquired diseases (infections of the upper respiratory tract, pneumonia, meningitis), was chosen as case study to develop the long term strat- egy. S. pneumoniae has developed resistance to different classes of drugs including penicillin, macrolides and quinolones. Fluoroquinolones are a novel class of com- pound inhibiting the pathogen’s growth by targeting bacterial topoisomerase IV. Methods We collected the complete genome of 46 different strains of S. pneumoniae from a publicly available database (NCBI microbial genome) and developed a pipeline to retrieve the sequences of the subunit A (parC) of topoisomerase IV. These se- quences were translated into the respective amino acidic sequences and a multiple sequence alignment was generated. In order to identify single point mutations the parC gene from the R6 non-resistant strain was used as reference. In order to eval- uate how the identified amino acidic substitutions may affect the binding of the antibiotic to the topoisomerase IV, for each strain, we mapped them on the ParC protein structure and carried out a structural analysis. Results Here, we present the results of the S. pneumoniae case study. Using the parC gene from the R6 non-resistant strain as reference, we identified several single point mu- tations in the parC genes of other strains, some of which were already known from the literature to be related to antibiotic resistance.

Analysis of point mutations leading to antibiotic resistance in Streptococcus pneumoniae / Staid, DAVID SASAH; Gerda, Užubalytė; Via, Allegra. - (2018), pp. 243-243. (Intervento presentato al convegno 15th BITS Annual meeting tenutosi a Torino).

Analysis of point mutations leading to antibiotic resistance in Streptococcus pneumoniae

STAID, DAVID SASAH
Primo
Methodology
;
Allegra Via
Ultimo
Supervision
2018

Abstract

Motivation New antimicrobial resistance mechanisms are emerging and spreading globally, threatening the ability to treat common infectious diseases. The long term goal of this project is to develop an automated procedure to identify and structurally characterise point mutations in bacterial genes that can lead to the rising of antibi- otic resistance. Streptococcus pneumoniae, a gram positive bacterium responsible for several community-acquired diseases (infections of the upper respiratory tract, pneumonia, meningitis), was chosen as case study to develop the long term strat- egy. S. pneumoniae has developed resistance to different classes of drugs including penicillin, macrolides and quinolones. Fluoroquinolones are a novel class of com- pound inhibiting the pathogen’s growth by targeting bacterial topoisomerase IV. Methods We collected the complete genome of 46 different strains of S. pneumoniae from a publicly available database (NCBI microbial genome) and developed a pipeline to retrieve the sequences of the subunit A (parC) of topoisomerase IV. These se- quences were translated into the respective amino acidic sequences and a multiple sequence alignment was generated. In order to identify single point mutations the parC gene from the R6 non-resistant strain was used as reference. In order to eval- uate how the identified amino acidic substitutions may affect the binding of the antibiotic to the topoisomerase IV, for each strain, we mapped them on the ParC protein structure and carried out a structural analysis. Results Here, we present the results of the S. pneumoniae case study. Using the parC gene from the R6 non-resistant strain as reference, we identified several single point mu- tations in the parC genes of other strains, some of which were already known from the literature to be related to antibiotic resistance.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1181143
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