Isolation and identification of chlorate-reducing Hafnia sp. from milk

Abstract

Chlorate has become a concern in the food and beverage sector, related to chlorine sanitizers in industrial food production and water treatment. It is of particular concern to regulatory bodies due to the negative health effects of chlorate exposure. This study investigated the fate of chlorate in raw milk and isolated bacterial strains of interest responsible for chlorate breakdown. Unpasteurized milk was demonstrated to have a chlorate-reducing capacity, breaking down enriched chlorate to undetectable levels in 11 days. Further enrichment and isolation using conditions specific to chlorate-reducing bacteria successfully isolated three distinct strains of Hafnia paralvei . Chlorate-reducing bacteria were observed to grow in a chlorate-enriched medium with lactate as an electron donor. All isolated strains were demonstrated to reduce chlorate in liquid medium; however, the exact mechanism of chlorate degradation was not definitively identified in this study.

Revealing the genetic traits of the foodborne microbial genus Hafnia: Implications for the human gut microbiome

“…After thoroughly assessing the completeness of the downloaded genomes of Hafnia , contamination, and nucleotide identity scores, we used the retained high‐quality genomes to perform a comprehensive tracking analysis within the main environmental sources of Hafnia strains providing an ecological overview of the distribution of this bacterial species (Data Set S2). Among the environmental sources available, honeybee gut and raw milk cheese were chosen for this study due to recent literature identifying Hafnia as a common pathogen in bees and a prevalent bacterial species in fermented foods and related food spoilage processes (McCarthy et al, 2023). Therefore, we selected 128 deep‐shotgun metagenomics datasets from food‐dairy samples (Fontana et al, 2023) and 158 metagenomics datasets from honeybee gut samples (additional details in material & methods) to track Hafnia strains with an in silico approach.…”