Improved Detection Techniques for Foodborne Pathogens: FT-IR Applications

Investigator: Lisa Mauer (Department of Food Science)

Project Report 2010 - 2011

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Project Rationale

Foodborne illness in the U.S. is an important public health concern causing over 48 million illnesses, 128,000 hospitalizations, and 3,000 deaths each year. The economic burden is estimated at $152 billion annually (CDC). To keep the food supply safe, food production, processing, and retail establishments must be able to identify microbial foodborne contaminants, such as pathogenic Salmonella and E. coli O157:H7, before products reach consumers.

Viability assessment of bacteria is important in a wide variety of applications in the food industry, including evaluation of the effectiveness of inactivation treatments and microbial quality assessment of foods. The suitability of pathogen detection methods for food analysis depends on sensitivity, total time to detection, and cost of consumables. Even though the detection limit for conventional plating methods is low, the detection procedures are labor-intensive, often requiring extensive sample preparation and long incubation times. Conventional detection methods take at least 24 to 48 hours to differentiate and identify microorganisms; therefore, measures taken to counteract food contamination are delayed at least that long. Additionally, conventional methods do not provide information about dead bacteria and may underestimate sub-lethally damaged cells present in a food sample. To facilitate timely intervention measures, the food industry needs rapid detection methods that are able to accurately and rapidly identify low levels of microbial foodborne contaminants within complex food products.

Mid-infrared, Fourier-transform infrared spectroscopy (FT-IR) methods are based on studying the interaction of infrared light (wavenumbers 4000-400cm-1) with samples. In FT-IR spectra, the wavenumber positions of absorbance peaks, peak intensities, and peak widths are useful for functional group, cell component, and sample identification. The advantage of quickly screening a sample for contamination using FT-IR is balanced with the ability to specifically identify the contaminating substance from its spectra. Therefore, a reference library of spectra must be collected for each bacteria of interest, ideally spanning a range of concentrations, growth conditions, spectral collection parameters, and food matrices.

Project Objectives

  • Improve FT-IR detection techniques for pathogen detection.
  • Identify detection limits for methods developed and opportunities for improving sensitivity and specificity of FT-IR detection techniques.
  • Determine how spectroscopic differentiation relates to known cell surface characteristics from laboratory and foodborne outbreak pathogens.
  • Determine how cell surface characteristics vary with conditions and treatments (live/dead, processing treatments, phase variation) and resulting differences in FT-IR spectra.
  • Improve commercially available mid-IR sensor for pathogen detection applications.
  • Generate searchable database of foodborne pathogen spectral fingerprints.

Project Highlights

This year, we improved Fourier-transform infrared spectroscopy (FT-IR) pathogen detection techniques for determining (1) how spectroscopic differentiation relates to cell surface characteristics, (2) how these structures vary with conditions and treatments (including differentiation of live and dead cells), (3) how the techniques could be applied to detect pathogens in food systems (fruit juice, ground beef, chicken breast), and (4) how L. monocytogenes, E. coli O157:H7, and Salmonella can be classified at the serotype, haplotype, and/or strain level. For example, starting from a pure culture, this method enabled classification of L. monocytogenes at the serotype, haplotype, and/or strain level within 18 hours, which is faster and potentially less expensive than the molecular methods and previous FT-IR methods. This is the first report of the identification of L. monocytogenes at the haplotype level using FT-IR. Additionally, a searchable database of spectra of L. monocytogenes, E. coli O157:H7, and Salmonella was compiled.

""Starting from a pure culture, our FT-IR method enabled classification of L. monocytogenes at the serotype, haplotype, and/or strain level within 18 hours, which is faster and potentially less expensive than molecular methods.""

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