Differentiation of probiotic and environmental Saccharomyces cerevisiae strains in animal feed

N. R. Büchl, M. Hutzler, H. Mietke-Hofmann, M. Wenning, S. Scherer

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

Aims: To establish an identification system for probiotic Saccharomyces cerevisiae strains based on artificial neural network (ANN)-assisted Fourier-transform infrared (FTIR) spectroscopy to improve quality control of animal feed. Methods and Results: The ANN-based system for differentiating environmental from probiotic S. cerevisiae strains comprises five authorized feed additive strains plus environmental strains isolated from different habitats. A total of 108 isolates were used as reference strains to create the ANN. DHPLC analysis and -PCR were used as reference methods to type probiotic yeast isolates. The performance of the FTIR-ANN was tested in an internal validation using unknown spectra of each reference strain. This validation step yielded a classification rate of 99·1 %. For an external validation, a test data set comprising 965 spectra of 63 probiotic and environmental S. cerevisiae isolates unknown to the ANN was used, resulting in a classification rate of 98·2 %. Conclusions: Our results demonstrate that probiotic S. cerevisiae strains in feed can be differentiated successfully from environmental isolates using both genotypic approaches and ANN-based FTIR spectroscopy. Significance and Impact of the Study: FTIR-based artificial neural network analysis provides a rapid and inexpensive technique for yeast identification both at the species and at the strain level in routine diagnostic laboratories, using a single sample preparation.

Original languageEnglish
Pages (from-to)783-791
Number of pages9
JournalJournal of Applied Microbiology
Volume109
Issue number3
DOIs
StatePublished - Sep 2010

Keywords

  • -PCR
  • DHPLC
  • FTIR spectroscopy
  • Saccharomyces cerevisiae
  • artificial neural network
  • microbial feed additives
  • probiotics
  • strain typing

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