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Development of a biofilm inhibitor molecule against multidrug resistant Staphylococcus aureus associated with gestational urinary tract infections.

ABSTRACT: Urinary Tract Infection (UTI) is a globally widespread human infection caused by an infestation of uropathogens. Eventhough, Escherichia coli is often quoted as being the chief among them, Staphylococcus aureus involvement in UTI especially in gestational UTI is often understated. Staphylococcal accessory regulator A (SarA) is a quorum regulator of S. aureus that controls the expression of various virulence and biofilm phenotypes. Since SarA had been a focussed target for antibiofilm agent development, the study aims to develop a potential drug molecule targeting the SarA of S. aureus to combat biofilm associated infections in which it is involved. In our previous studies, we have reported the antibiofilm activity of SarA based biofilm inhibitor, (SarABI) with a 50% minimum biofilm inhibitory concentration (MBIC50) value of 200 ?g/mL against S. aureus associated with vascular graft infections and also the antibiofilm activity of the root ethanolic extracts of Melia dubia against uropathogenic E. coli. In the present study, in silico design of a hybrid molecule composed of a molecule screened from M. dubia root ethanolic extracts and a modified SarA based inhibitor (SarABI(M)) was undertaken. SarABI(M) is a modified form of SarABI where the fluorine groups are absent in SarABI(M). Chemical synthesis of the hybrid molecule, 4-(Benzylamino)cyclohexyl 2-hydroxycinnamate (henceforth referred to as UTI Quorum-Quencher, UTI(QQ)) was then performed, followed by in vitro and in vivo validation. The MBIC50 and MBIC90 of UTI(QQ) were found to be 15 and 65 ?g/mL, respectively. Confocal laser scanning microscopy (CLSM) images witnessed biofilm reduction and bacterial killing in either UTI(QQ) or in combined use of antibiotic gentamicin and UTI (QQ) . Similar results were observed with in vivo studies of experimental UTI in rat model. So, we propose that the drug UTI(QQ) would be a promising candidate when used alone or, in combination with an antibiotic for staphylococcal associated UTI.

SUBMITTER: Balamurugan P

PROVIDER: S-EPMC4531255 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Development of a biofilm inhibitor molecule against multidrug resistant Staphylococcus aureus associated with gestational urinary tract infections.

Balamurugan P P Hema M M Kaur Gurmeet G Sridharan V V Prabu P C PC Sumana M N MN Princy S Adline SA

Frontiers in microbiology 20150811

Urinary Tract Infection (UTI) is a globally widespread human infection caused by an infestation of uropathogens. Eventhough, Escherichia coli is often quoted as being the chief among them, Staphylococcus aureus involvement in UTI especially in gestational UTI is often understated. Staphylococcal accessory regulator A (SarA) is a quorum regulator of S. aureus that controls the expression of various virulence and biofilm phenotypes. Since SarA had been a focussed target for antibiofilm agent devel ...[more]

PMID: 26322037

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Project description:BACKGROUND:The scope of this work is to build a Machine Learning model able to predict patients risk to contract a multidrug resistant urinary tract infection (MDR UTI) after hospitalization. To achieve this goal, we used different popular Machine Learning tools. Moreover, we integrated an easy-to-use cloud platform, called DSaaS (Data Science as a Service), well suited for hospital structures, where healthcare operators might not have specific competences in using programming languages but still, they do need to analyze data as a continuous process. Moreover, DSaaS allows the validation of data analysis models based on supervised Machine Learning regression and classification algorithms. RESULTS:We used DSaaS on a real antibiotic stewardship dataset to make predictions about antibiotic resistance in the Clinical Pathology Operative Unit of the Principe di Piemonte Hospital in Senigallia, Marche, Italy. Data related to a total of 1486 hospitalized patients with nosocomial urinary tract infection (UTI). Sex, age, age class, ward and time period, were used to predict the onset of a MDR UTI. Machine Learning methods such as Catboost, Support Vector Machine and Neural Networks were utilized to build predictive models. Among the performance evaluators, already implemented in DSaaS, we used accuracy (ACC), area under receiver operating characteristic curve (AUC-ROC), area under Precision-Recall curve (AUC-PRC), F1 score, sensitivity (SEN), specificity and Matthews correlation coefficient (MCC). Catboost exhibited the best predictive results (MCC 0.909; SEN 0.904; F1 score 0.809; AUC-PRC 0.853, AUC-ROC 0.739; ACC 0.717) with the highest value in every metric. CONCLUSIONS:the predictive model built with DSaaS may serve as a useful support tool for physicians treating hospitalized patients with a high risk to acquire MDR UTIs. We obtained these results using only five easy and fast predictors accessible for each patient hospitalization. In future, DSaaS will be enriched with more features like unsupervised Machine Learning techniques, streaming data analysis, distributed calculation and big data storage and management to allow researchers to perform a complete data analysis pipeline. The DSaaS prototype is available as a demo at the following address: https://dsaas-demo.shinyapps.io/Server/.

Project description:Urinary tract infection (UTI) is one of the most common infectious conditions affecting people in the United States and around the world. Our knowledge of the host-pathogen interaction during UTI caused by Gram-positive bacterial uropathogens is limited compared to that for Gram-negative pathogens. Here, we investigated whether copper and the primary copper-containing protein, ceruloplasmin, are mobilized to urine during naturally occurring UTI caused by Gram-positive uropathogens in patients. Next, we probed the role of copper resistance in the fitness of methicillin-resistant Staphylococcus aureus (MRSA) during experimental UTI in a murine model. Our findings demonstrate that urinary copper and ceruloplasmin content are elevated during UTI caused by Enterococcus faecalis, S. aureus, S. epidermidis, and S. saprophyticus. MRSA strains successfully colonize the urinary tract of female CBA mice with selective induction of inflammation in the kidneys but not the bladder. MRSA mutants lacking CopL, a copper-binding cell surface lipoprotein, and the ACME genomic region containing copL, exhibit decreased fitness in the mouse urinary tract compared to parental strains. Copper sensitivity assays, cell-associated copper and iron content, and bioavailability of iron during copper stress demonstrate that homeostasis of copper and iron is interlinked in S. aureus. Importantly, relative fitness of the MRSA mutant lacking the ACME region is further decreased in mice that receive supplemental copper compared to the parental strain. In summary, copper is mobilized to the urinary tract during UTI caused by Gram-positive pathogens, and copper resistance is a fitness factor for MRSA during UTI. IMPORTANCE Urinary tract infection (UTI) is an extremely common infectious condition affecting people throughout the world. Increasing antibiotic resistance in pathogens causing UTI threatens our ability to continue to treat patients in the clinics. Better understanding of the host-pathogen interface is critical for development of novel interventional strategies. Here, we sought to elucidate the role of copper in host-Staphylococcus aureus interaction during UTI. Our results reveal that copper is mobilized to the urine as a host response in patients with UTI. Our findings from the murine model of UTI demonstrate that copper resistance is involved in the fitness of methicillin-resistant S. aureus (MRSA) during interaction with the host. We also establish a critical link between adaptation to copper stress and iron homeostasis in S. aureus.

Dataset Information

Development of a biofilm inhibitor molecule against multidrug resistant Staphylococcus aureus associated with gestational urinary tract infections.

Publications

Development of a biofilm inhibitor molecule against multidrug resistant Staphylococcus aureus associated with gestational urinary tract infections.

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