Abstract
BackgroundThe rise of antibiotic resistance in pathogenic bacteria is a significant problem for the treatment of infectious diseases. Resistance is usually selected by the antibiotic itself; however, biocides might also co-select for resistance to antibiotics. Although resistance to biocides is poorly defined, different in vitro studies have shown that mutants presenting low susceptibility to biocides also have reduced susceptibility to antibiotics. However, studies with natural bacterial isolates are more limited and there are no clear conclusions as to whether the use of biocides results in the development of multidrug resistant bacteria.MethodsThe main goal is to perform an unbiased blind-based evaluation of the relationship between antibiotic and biocide reduced susceptibility in natural isolates of Staphylococcus aureus. One of the largest data sets ever studied comprising 1632 human clinical isolates of S. aureus originated worldwide was analysed. The phenotypic characterization of 13 antibiotics and 4 biocides was performed for all the strains. Complex links between reduced susceptibility to biocides and antibiotics are difficult to elucidate using the standard statistical approaches in phenotypic data. Therefore, machine learning techniques were applied to explore the data.ResultsIn this pioneer study, we demonstrated that reduced susceptibility to two common biocides, chlorhexidine and benzalkonium chloride, which belong to different structural families, is associated to multidrug resistance. We have consistently found that a minimum inhibitory concentration greater than 2 mg/L for both biocides is related to antibiotic non-susceptibility in S. aureus.ConclusionsTwo important results emerged from our work, one methodological and one other with relevance in the field of antibiotic resistance. We could not conclude on whether the use of antibiotics selects for biocide resistance or vice versa. However, the observation of association between multiple resistance and two biocides commonly used may be of concern for the treatment of infectious diseases in the future.
Highlights
Antibiotics are among the most successful therapeutic agents so far developed by humankind
The authors do not conclude whether there is an association or not, but with the data and tools used in the analysis it is hard to conclude if increased biocide resistance is a cause of increased antibiotic resistance. All of these studies deal with small data sets and the results present no evidence of statistical correlation between those antimicrobials, either antibiotics or biocides
We propose this new framework, based on machine learning methodologies, to analyse the scale and complexity of molecular epidemiology data and its application to study the potential linkage between antibiotic resistance and biocide reduced susceptibility
Summary
Antibiotics are among the most successful therapeutic agents so far developed by humankind. The widespread use of these compounds has led to the selection of resistant microorganisms, and to a loss of efficacy for this family of drugs [1,2] This problem is further increased by the circulation of microorganisms among humans, animals and agricultural hosts creating the opportunity for the exchange of resistance genes/mechanisms directing the spread of resistance [3]. The problem is compounded by the fact that the pace of introduction of new chemotherapeutic drugs in the market and in clinical practice has slowed in the last few years [6] The consequence of this slowdown is that many antibiotics lose their treatment effect against organisms that have developed antibiotic resistance and the use of other drugs, which are often reserved for last line treatment, is required. Studies with natural bacterial isolates are more limited and there are no clear conclusions as to whether the use of biocides results in the development of multidrug resistant bacteria
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
