Applying Fourier-transform infrared spectroscopy and chemometrics to the characterization and identification of lactic acid bacteria

Mouwen, D.J.M.; Hörman, Ari; Korkeala, Hannu; Álvarez‐Ordóñez, Avelino; Prieto, Miguel

doi:10.1016/j.vibspec.2011.02.008

Cited by 42 publications

(22 citation statements)

References 40 publications

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“…One strain (C-600) remained unclustered. FT-IR spectroscopy has high discriminatory power at the subspecies level (Mouwen et al, 2005;Mouwen et al, 2011), including for E. coli (Davis et al, 2012;Sousa et al, 2013;Dawson et al, 2014;Prieto-Calvo et al, 2014). The current study also showed a significant level of agreement between certain groupings (strains MF2494, MF2522 and MF3578; strains EDL933 and MF3582) when using FT-IR spectra and ribotyping or ITS rRNA gene sequencing (Figure 2).…”

Section: Carbon Source Utilisation Resultssupporting

confidence: 63%

Comparison of methods for the identification and sub-typing of O157 and non-O157 Escherichia coli serotypes and their integration into a polyphasic taxonomy approach

Prieto-Calvo¹,

Omer²,

Alvseike³

et al. 2016

Irish Journal of Agricultural and Food Research

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Phenotypic, chemotaxonomic and genotypic data from 12 strains of Escherichia coli were collected, including carbon source utilisation profiles, ribotypes, sequencing data of the 16S-23S rRNA internal transcribed region (ITS) and Fourier transform-infrared (FT-IR) spectroscopic profiles. The objectives were to compare several identification systems for E. coli and to develop and test a polyphasic taxonomic approach using the four methodologies combined for the subtyping of O157 and non-O157 E. coli. The nucleotide sequences of the 16S-23S rRNA ITS regions were amplified by polymerase chain reaction (PCR), sequenced and compared with reference data available at the GenBank database using the Basic Local Alignment Search Tool (BLAST) . Additional information comprising the utilisation of carbon sources, riboprint profiles and FT-IR spectra was also collected. The capacity of the methods for the identification and typing of E. coli to species and subspecies levels was evaluated. Data were transformed and integrated to present polyphasic hierarchical clusters and relationships. The study reports the use of an integrated scheme comprising phenotypic, chemotaxonomic and genotypic information (carbon source profile, sequencing of the 16S-23S rRNA ITS, ribotyping and FT-IR spectroscopy) for a more precise characterisation and identification of E. coli. The results showed that identification of E. coli strains by each individual method was limited mainly by the extension and quality of reference databases. On the contrary, the polyphasic approach, whereby heterogeneous taxonomic data were combined and weighted, improved the identification results, gave more consistency to the final clustering and provided additional information on the taxonomic structure and phenotypic behaviour of strains, as shown by the close clustering of strains with similar stress resistance patterns.

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Section: Carbon Source Utilisation Resultssupporting

confidence: 63%

Comparison of methods for the identification and sub-typing of O157 and non-O157 Escherichia coli serotypes and their integration into a polyphasic taxonomy approach

Prieto-Calvo¹,

Omer²,

Alvseike³

et al. 2016

Irish Journal of Agricultural and Food Research

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show abstract

“…Rapid and non-invasive methods based on analytical instrumental techniques, such as Fourier transform infrared spectroscopy (FTIR) [2] and Raman spectroscopy [3] have been considered for their potential in meat quality assessment. The "mechanism" of these approaches is based on the assumption that the metabolic activity of microorganisms on meat results in biochemical changes, with the simultaneous formation of metabolic by-products, which may contribute to the spoilage phenomenon.…”

Section: Introductionmentioning

confidence: 99%

A fuzzy-wavelet neural network model for the detection of meat spoilage using an electronic nose

Kodogiannis

Alshejari

2016

2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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“…Rapid and non-invasive methods based on analytical instrumental techniques, such as Fourier transform infrared spectroscopy (FTIR) [2] and Raman spectroscopy [3] have been considered for their potential in meat quality assessment. In the past two decades, awareness about the food safety from the point of specific pathogenic bacteria has considered the need for a rapid and accurate detection system for microbial spoilage by checking the volatile organic compounds (VOCs) generated by these microorganisms [4].…”

Section: Introductionmentioning

confidence: 99%

Neuro-fuzzy based identification of meat spoilage using an electronic nose

Kodogiannis

Alshejari

2016

2016 IEEE 8th International Conference on Intelligent Systems (IS)

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Applying Fourier-transform infrared spectroscopy and chemometrics to the characterization and identification of lactic acid bacteria

Cited by 42 publications

References 40 publications

Comparison of methods for the identification and sub-typing of O157 and non-O157 Escherichia coli serotypes and their integration into a polyphasic taxonomy approach

Comparison of methods for the identification and sub-typing of O157 and non-O157 Escherichia coli serotypes and their integration into a polyphasic taxonomy approach

A fuzzy-wavelet neural network model for the detection of meat spoilage using an electronic nose

Neuro-fuzzy based identification of meat spoilage using an electronic nose

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