Ultrasensitive multiplex optical quantification of bacteria in large samples of biofluids

Efficient treatments in bacterial infections require the fast and accurate recognition of pathogens, with concentrations as low as one per milliliter in the case of septicemia. Detecting and quantifying bacteria in such low concentrations is challenging and typically demands cultures of large sample...

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Detalles Bibliográficos
Autores: Pazos-Perez, Nicolas, Pazos, Elena, Catala, Carme, Mir-Simon, Bernat|||0000-0002-7899-9577, Gómez-de Pedro, Sara|||0000-0002-3794-5820, Sagales, Juan, Villanueva, Carlos, Vila Estapé, Jordi|||0000-0002-8025-3926, Soriano Viladomiu, Alex|||0000-0002-9374-0811, García de Abajo, F. Javier, Álvarez Puebla, Ramon A.|||0000-0003-4770-5756
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:254170
Acceso en línea:https://ddd.uab.cat/record/254170
https://dx.doi.org/urn:doi:10.1038/srep29014
Access Level:acceso abierto
Descripción
Sumario:Efficient treatments in bacterial infections require the fast and accurate recognition of pathogens, with concentrations as low as one per milliliter in the case of septicemia. Detecting and quantifying bacteria in such low concentrations is challenging and typically demands cultures of large samples of blood (~1 milliliter) extending over 24-72 hours. This delay seriously compromises the health of patients. Here we demonstrate a fast microorganism optical detection system for the exhaustive identification and quantification of pathogens in volumes of biofluids with clinical relevance (~1 milliliter) in minutes. We drive each type of bacteria to accumulate antibody functionalized SERS-labelled silver nanoparticles. Particle aggregation on the bacteria membranes renders dense arrays of inter-particle gaps in which the Raman signal is exponentially amplified by several orders of magnitude relative to the dispersed particles. This enables a multiplex identification of the microorganisms through the molecule-specific spectral fingerprints.