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Biochips for Direct Detection and Identification of Bacteria in Blood Culture-Like Conditions

Bloodstream bacterial infections are life-threatening conditions necessitating prompt medical care. Rapid pathogen identification is essential for early setting of the best anti-infectious therapy. However, the bacterial load in blood samples from patients with bacteremia is too low and under the li...

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Detalles Bibliográficos
Autores principales: Templier, V., Livache, T., Boisset, S., Maurin, M., Slimani, S., Mathey, R., Roupioz, Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5572712/
https://www.ncbi.nlm.nih.gov/pubmed/28842712
http://dx.doi.org/10.1038/s41598-017-10072-z
Descripción
Sumario:Bloodstream bacterial infections are life-threatening conditions necessitating prompt medical care. Rapid pathogen identification is essential for early setting of the best anti-infectious therapy. However, the bacterial load in blood samples from patients with bacteremia is too low and under the limit of detection of most methods for direct identification of bacteria. Therefore, a preliminary step enabling the bacterial multiplication is required. To do so, blood cultures still remain the gold standard before bacteremia diagnosis. Bacterial identification is then usually obtained within 24 to 48 hours -at least- after blood sampling. In the present work, the fast and direct identification of bacteria present in blood cultures is completed in less than 12 hours, during bacterial growth, using an antibody microarray coupled to a Surface Plasmon Resonance imager (SPRi). Less than one bacterium (Salmonella enterica serovar Enteritidis) per milliliter of blood sample is successfully detected and identified in blood volumes similar to blood tests collected in clinics (i.e. several milliliters). This proof of concept demonstrates the workability of our method for human samples, despite the highly complex intrinsic nature of unprocessed blood. Our label-free method then opens new perspectives for direct and faster bacterial identification in a larger range of clinical samples.