Toward a Noninvasive, Label-Free Screening Method for Determining Spore Inoculum Quality of Penicillium chrysogenum Using Raman Spectroscopy

Fecha de publicación:

Autores de IIS La Fe

Participantes ajenos a IIS La Fe

  • Wieland, K
  • Ehgartner, D
  • Ramer, G
  • Koch, C
  • Ofner, J
  • Herwig, C
  • Lendl, B

Grupos

Abstract

We report on a label-free, noninvasive method for determination of spore inoculum quality of Penicillium chrysogenum prior to cultivation/germination. Raman microspectroscopy providing direct, molecule-specific information was used to extract information on the viability state of spores sampled directly from the spore inoculum. Based on the recorded Raman spectra, a supervised classification method was established for classification between living and dead spores and thus determining spore inoculum quality for optimized process control. A fast and simple sample preparation method consisting of one single dilution step was employed to eliminate interfering signals from the matrix and to achieve isolation of single spores on the sample carrier (CaF2). Aiming to avoid any influence of the killing procedure in the Raman spectrum of the spore, spores were considered naturally dead after more than one year of storage time. Fluorescence staining was used as reference method. A partial least squares discriminant analysis classifier was trained with Raman spectra of 258 living and dead spores (178 spectra for calibration, 80 spectra for validation). The classifier showed good performance when being applied to a 1 mu L droplet taken from a 1:1 mixture of living and dead spores. Of 135 recorded spectra, 51% were assigned to living spores while 49% were identified as dead spores by the classifier. The results obtained in this work are a fundamental step towards developing an automated, label-free, and noninvasive screening method for assessing spore inoculum quality.

Datos de la publicación

ISSN/ISSNe:
0003-7028, 1943-3530

APPLIED SPECTROSCOPY  SAGE PUBLICATIONS INC

Tipo:
Article
Páginas:
2661-2669
PubMed:
28776414
Factor de Impacto:
0,489 SCImago
Cuartil:
Q2 SCImago

Citas Recibidas en Web of Science: 4

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Keywords

  • Raman microspectroscopy; classification; spore inoculum quality; Penicillium chrysogenum; partial least squares discriminant analysis; PLS-DA; process optimization

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