Microbiological Testing & Analysis

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Unlike many other foodborne pathogens, Listeria can both survive and grow at refrigeration temperatures. This ability, along with the risk of cross-contamination to other foods and surfaces, contributes to its persistence in food processing environments and makes it a significant concern for food safety.

The Canadian Food Inspection Agency (CFIA) recently published the findings from several food sampling and testing assignments for microbiological and chemical contaminants across a range of food categories. In general, the results were satisfactory.

A JEMRA meeting was convened to help inform discussions about potential updates to Codex Alimentarius guidance, reflecting how scientific advances could strengthen microbiological risk assessments for food safety.

Researchers developed a quantitative microbiological risk assessment (QMRA) framework that evaluates the public health, environmental, and economic trade-offs of microbiological sampling plans. They suggested microbiological sampling may be most useful when risk-based or as a verification tool.

The low-cost approach enables simultaneous detection of multiple foodborne pathogens and spoilage microorganisms in a shorter timeframe than traditional detection methods, without requiring advanced technical training. 

The platform uses a DNAzyme-crosslinked hydrogel that produces a visible color change when E. coli is present, enabling equipment-free, point-of-use detection. It successfully detected E. coli in a range of foods, even when other pathogens were present.

The Infant Formula Safety Modernization Act includes provisions about expanded pathogen testing requirements and compulsory environmental monitoring for infant formula manufacturers, among other mandates.

Marking the country’s first use of whole genome sequencing (WGS) in an active foodborne illness outbreak investigation, advanced genomics enabled Moldovan authorities to rapidly solve and respond to a salmonellosis outbreak that sickened more than 140 people in 2025.

The researchers positioned the machine learning model as a low-cost complement to traditional testing workflows, helping dairy processors enhance food safety while targeting laboratory resources.

The scientists will isolate and identify pathogens like Salmonella enterica and Listeria monocytogenes from Pennsylvania wastewater using whole genome sequencing (WGS), then work with the State Department of Health to connect isolates to foodborne illness outbreaks.