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Author
Moles Matas, Gemma
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Abstract
Infectious diseases are one of the main worldwide causes of death mainly because of excessive use of antibiotics, the lack of development of them, and fast diagnostic methods for the detection of the pathogen. All these factors have caused an increase in the resistance of bacteria to antibiotics, leading to more difficulties to treat these types of diseases with conventional antibiotics.
The main bacteria which are getting these resistances are classified in the acronym called ESKAPE, where one of these bacteria is called Pseudomonas aeruginosa. This is a gram-negative bacterium that is considered opportunist and is multiresistant to treatments. It has presented great interest because of the high number of infections in which this bacterium is involved, a part of being one of the most common bacteria in cystic fibrosis.
This bacterium causes two types of infections: acute and chronic. The type of infection and the transition between them are regulated by a communication intraspecific and interspecific system called Quorum Sensing system (QS), this system does this function by controlling the genetic expression in response to signaling molecules called autoinducer (AI).
The fact that this system is so important for the pathology of Pseudomonas aeruginosa, promotes a great interest in the need of developing diagnostic and therapy tools (therapeutic target). Nowadays the diagnostic technics to identify which pathogen is the cause of infectious diseases can take too much time to obtain a reliable result for the diagnostic.
This work focuses on the optimization of an ELISA immunoassay for the diagnosis of this type of disease. These immunoassays are intended to be fast and efficient and are based on the detection of the molecules from the QS system of Pseudomonas aeruginosa as biomarkers of respiratory infections.
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