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Updated: Jun 23, 2026

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Published on: October 25, 2018

Do microbial interactions and cultivation media decrease the accuracy of Salmonella surveillance systems and outbreak

Randall S Singer¹, Anne E Mayer, Timothy E Hanson

¹Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, 300A VSB, 1971 Commonwealth Avenue, University of Minnesota, St. Paul, Minnesota 55108, USA. singe024@umn.edu

Journal of Food Protection

|May 14, 2009

Summary

Cultivation methods can bias Salmonella surveillance and outbreak investigations. Different Salmonella strains show varied competitiveness in lab cultures, impacting detection accuracy and public health insights.

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Area of Science:

Microbiology
Food Safety
Veterinary Science

Background:

Cultivation methods are crucial for Salmonella surveillance and outbreak investigations.
Salmonella serotypes exhibit varying growth in enrichment and selective media, potentially biasing results.
This variability can lead to inaccurate conclusions about dominant strains and reduced detection sensitivity.

Purpose of the Study:

To investigate if cultivation media preferentially select specific Salmonella strains in mixed cultures.
To assess the impact of culture bias on Salmonella surveillance and outbreak investigations.

Main Methods:

Competed four Salmonella strains (S. Newport, S. Typhimurium, S. Enteritidis) in broth and bovine fecal experiments.
Varied combinations and concentrations of Salmonella strains were used.
Evaluated detection probability irrespective of initial concentration.

Main Results:

Salmonella Newport consistently demonstrated the highest competitiveness across all experiments.
One Salmonella Typhimurium strain was seldom detected, even when present alone in bovine feces.
Detection probability of a Salmonella strain was largely independent of its initial concentration.

Conclusions:

Culture-based methods introduce significant bias into Salmonella surveillance systems.
This bias can hinder accurate traceback investigations during Salmonella outbreaks.
Further research is needed to understand interstrain variability, minimize bias, and assess public health implications.