利用水光组学和近红外光谱快速筛选细菌

Z. Kovács, A. Slavchev, G. Bázár, Bernhard Pollner, R. Tsenkova
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引用次数: 4

摘要

作者简介:高效、快速和廉价的筛选方法,提供快速、全面的体内益生菌评价,是当代微生物学非常需要的。水光组学是一种新的科学方法,通过对水-光相互作用的快速和全面的分析来探索水系统,作为利用光谱学更好地了解生物世界的潜在信息来源。该溶液的水谱图可作为细胞培养体系的分子指纹图谱,用于生物体系的快速测定。我们的目的是利用近红外(NIR)光谱结合水光学评价技术在体内鉴别耐药和非耐药乳杆菌菌株,并在不同生长阶段和不同波长范围内预测其低pH值和胆汁耐药性。因此,采用近红外光谱法对保加利亚乳杆菌、戊酸乳杆菌和干酪乳杆菌菌株的生长进行了监测。测量它们的生长速率、最大光密度、低pH值和胆汁耐受性,作为分析同时获得的光谱数据的参考数据。对获得的近红外光谱进行多变量数据分析,建立不同的定性和定量模型,对不同益生菌强度的菌株进行分类,并确定其表型特征。益生菌和非益生菌菌株的体内评价结果,为基于细菌生长的光谱监测对益生菌菌株进行准确、快速、无创的鉴定提供了依据。结果还证明,利用近红外光谱和水光组学技术预测候选益生菌的主要表型特征也是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rapid bacteria selection using Aquaphotomics and near infrared spectroscopy
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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