Rapid bacteria selection using Aquaphotomics and near infrared spectroscopy
Author(s) -
Zoltán Kovács,
Aleksandar Slavchev,
George Bázár,
Bernhard Pollner,
Roumiana Tsenkova
Publication year - 2019
Publication title -
im publications open llp ebooks
Language(s) - English
Resource type - Book series
DOI - 10.1255/nir2017.065
Subject(s) - selection (genetic algorithm) , bacteria , spectroscopy , infrared spectroscopy , infrared , materials science , computer science , biology , chemistry , physics , artificial intelligence , optics , astronomy , genetics , organic chemistry
Author Summary: Efficient, quick and inexpensive screening methods, which provide rapid, in vivo comprehensive probiotic bacteria evaluation, are highly desired in contemporary microbiology. Aquaphotomics is a novel scientific approach for the exploration of aqueous systems through rapid and comprehensive analysis of water–light interaction as a potential source of information for better understanding of the biological world using spectroscopy. The water spectral pattern of the solution as a molecular fingerprint of the cell culture system can be used for quick determination of biological systems. Our objectives are to use near infrared (NIR) spectroscopy with the Aquaphotomics evaluation technique for in vivo discrimination of resistant and non-resistant Lactobacillus strains, and to predict their low pH and bile resistances using different growth stages and different wavelength ranges. Therefore, NIR spectroscopy with Aquaphotomics was applied to monitor the growth of Lactobacillus bulgaricus, Lactobacillus pentosus and Lactobacillus gasseri bacteria strains. Their growth rate, maximal optical density, low pH and bile tolerances were measured and used as a reference data for the analysis of the simultaneously acquired spectral data. The acquired NIR spectra were subjected to various multivariate data analyses to build different qualitative and quantitative models to classify the bacteria strains with different probiotic strength and to determine their phenotypic characteristics. The results of the in vivo evaluation of probiotic and non-probiotic bacteria strains provided accurate, fast and non-invasive identification of probiotic bacteria strains based on spectral monitoring of their bacterial growth. Results also proved that the prediction of the main phenotypic characteristics of probiotic candidates is also possible with NIR spectroscopy and Aquaphotomics.
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