Molecules, Vol. 24, Pages 4516: A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species

Molecules, Vol. 24, Pages 4516: A Machine Learning-Based Raman Spectroscopic Assay for the Identification of Burkholderia mallei and Related Species Molecules doi: 10.3390/molecules24244516 Authors: Amira A. Moawad Anja Silge Thomas Bocklitz Katja Fischer Petra Rösch Uwe Roesler Mandy C. Elschner Jürgen Popp Heinrich Neubauer Burkholderia (B.) mallei, the causative agent of glanders, and B. pseudomallei, the causative agent of melioidosis in humans and animals, are genetically closely related. The high infectious potential of both organisms, their serological cross-reactivity, and similar clinical symptoms in human and animals make the differentiation from each other and other Burkholderia species challenging. The increased resistance against many antibiotics implies the need for fast and robust identification methods. The use of Raman microspectroscopy in microbial diagnostic has the potential for rapid and reliable identification. Single bacterial cells are directly probed and a broad range of phenotypic information is recorded, which is subsequently analyzed by machine learning methods. Burkholderia were handled under biosafety level 1 (BSL 1) conditions after heat inactivation. The clusters of the spectral phenotypes and the diagnostic relevance of the Burkholderia spp. were considered for an advanced hierarchical machine learning approach. The strain panel for training involved 12 B. mallei, 13 B. pseudomallei and 11 other Burkholderia spp. type...
Source: Molecules - Category: Chemistry Authors: Tags: Article Source Type: research