Literature DB >> 31437556

Identification of lactic acid bacteria Enterococcus and Lactococcus by near-infrared spectroscopy and multivariate classification.

Sylvain Treguier1, Christel Couderc2, Helene Tormo3, Didier Kleiber4, Cecile Levasseur-Garcia5.   

Abstract

Lactic acid bacteria are important in numerous biological processes. The fabrication of cheese, for example, uses the lactic acid bacteria found in raw milk such as Lactococcus lactis as starters to improve the organoleptic properties of milk. Conventional methods to determine the genus and species of lactic acid bacteria isolated from raw milk involve genotyping and phenotyping, which require specific preparation and sample destruction. To improve on this situation, we present herein a simple and non-destructive screening method to discriminate between the Lactococcus and Enterococcus species most commonly found in raw milk (L. lactis, E. durans, E. faecalis, and E. faecium). The bacteria are grown on agar plates and assessed by using near-infrared spectroscopy in a spectral range from 800 to 2777 nm. Principle component analysis loading line plots highlight the inter-genus and inter-species differences at various wavelengths, which are mostly assigned to cell-wall compounds such as polysaccharides. The best artificial neural network identification models give 98.8% and 86.3% classification rates at the genus and species level, respectively, for an external validation set made of 80 samples. These results suggest that near-infrared spectroscopy may be used to identify lactic acid bacteria on agar medium.
Copyright © 2019 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Discrimination; Enterococcus; Identification; Lactic acid bacteria; Lactococcus; Near-infrared spectroscopy

Mesh:

Year:  2019        PMID: 31437556     DOI: 10.1016/j.mimet.2019.105693

Source DB:  PubMed          Journal:  J Microbiol Methods        ISSN: 0167-7012            Impact factor:   2.363


  3 in total

1.  Identification of bacteria by poly-aromatic hydrocarbon biosensors.

Authors:  Yaniv Shlosberg; Yair Farber; Salah Hasson; Valery Bulatov; Israel Schechter
Journal:  Anal Bioanal Chem       Date:  2022-02-07       Impact factor: 4.142

2.  Fast label-free identification of bacteria by synchronous fluorescence of amino acids.

Authors:  Yaniv Shlosberg; Yair Farber; Salah Hasson; Valery Bulatov; Israel Schechter
Journal:  Anal Bioanal Chem       Date:  2021-09-07       Impact factor: 4.142

3.  Real-Time Monitoring of Yogurt Fermentation Process by Aquaphotomics Near-Infrared Spectroscopy.

Authors:  Jelena Muncan; Kyoko Tei; Roumiana Tsenkova
Journal:  Sensors (Basel)       Date:  2020-12-29       Impact factor: 3.576

  3 in total

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