Rapid detection of multidrug-resistant gram-negative rod-shaped bacteria

Multi-drug-resistant Gram-negative rod-shaped bacteria (MRGN) have become increasingly widespread in recent years as a cause of nosocomial infections worldwide. Antibiotics used for standard therapy are largely ineffective in the case of MRGN infections. This is why infections with multi-drug-resistant pathogens have to be identified very early on in order to initiate the right therapy with one of the few reserve antibiotics still available as soon as possible. MRGN bacteria can also survive on inanimate surfaces and spread via contaminated objects. Early detection is important so as to be able to take special hygienic measures and prevent these problematic pathogens from spreading. A Fraunhofer EMFT research team is collaborating with the SME GBN Systems GmbH, the Institute of Microbiology and Hygiene at Regensburg University Hospital and Asklepios Kliniken GmbH to develop a compact, comprehensive system that will enable rapid on-site detection of MRGN bacteria.

Multiresistant Bacteria
© David Dorward; National Institute of Allergy and Infectious Diseases.
Multiresistant Bacteria

The detection system is to be fluorescence-based and capable of being carried out on the sample material without elaborate sample preparation. Smears from potentially contaminated surfaces and objects serve as test material, in addition to human samples. Using a highly sensitive measuring system combined with a fluorescence-based detection reaction, the aim is to achieve an enormous reduction in time between sample collection and test result.

Unlike conventional, time-consuming methods using microbiological cultures, rapid on-site detection will provide feedback on the existence of MRGN bacteria in the sample material within a short period of time. In contrast to PCR-based methods, this phenotypic detection will be independent of the genetic variability of the MRGN bacteria, also allowing the pathogens to be detected where PCR-based methods would not be capable of identification. This constitutes a major step forward as compared to the methods currently in use.

The project is funded by the Bavarian Research Foundation (BFS).



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