Electrochemical label-free pathogen identification for bloodstream infections diagnosis: Towards a machine learning based smart blood culture bottle

• Published in: Sensors and actuators. B, Chemical Chemical, 2023-07, Vol.387, p.133748, Article 133748
• Main Authors: Babin, Thibaut C., Dedole, Tommy, Bouvet, Pierre, Marcoux, Pierre R., Gougis, Maxime, Mailley, Pascal
• Format: Article
• Language: English
• Subjects: Blood culture; Electrochemical fingerprint; Life Sciences; Machine learning; Multi-material electrode array
• ISSN: 0925-4005; 1873-3077
• DOI: 10.1016/j.snb.2023.133748

Bloodstream infections are a growing public health concern. Current pathogen identification systems are based on complex and expensive devices, intended for use in centralized laboratories. Subsequent identification requires harmful chemical reagents, specialized personnel and time. Here we describe a new approach for rapid and decentralized diagnosis of positive blood cultures using electrochemical sensors. By implementing a multi-material potentiometric platform in a blood culture bottle, we have developed a portable system for pathogen identification of Gram and of genus. Bacterial growth in human blood generates a specific label-free multiplex electrochemical fingerprint according to the detected species. Analysis of these fingerprints using homemade machine learning algorithms allow for rapid identification of the pathogen after detection (14 species and 9 genus) (GRAM= 99 % accuracy 5.75 h after detection, GENUS= 85 % accuracy 7.8 h after positivity) without further handling of the contaminated sample. •Blood culture bottles have been instrumented with a silver reference electrode and with 8 work electrodes from four types.•Time-lapse potentiometry of the electroactive fraction of the metabolome can bring in-situ label-free identification.•Gram, then later genus, then species, can be determined within a few hours of additional incubation after positivity.