mstasie@illinois.edu | Stasiewicz Food Safety Laboratory | Vision: A world where everyone, everywhere is food secure

Advancing Food Recovery in K-12 School Cafeterias by Removing Food Safety and Operational Barriers of Share Tables

Our group is a co-PI (Lead PI is Dr. Prescott) on this three year research and Extension project funded by:

Objectives:

Conduct qualitative interviews with health inspectors to identify the perceived food safety risks that are informing restrictive share table policies: Research
Conduct a Quantitative Microbial Risk Assessment (QMRA) of foodborne disease risk due to the consumption of share table food items to address stakeholder food safety concerns and identify best food-safety practices: Research *Our group’s main contribution*
Develop share table resources in collaboration with key stakeholders and use a train-the-trainer model to pilot them across approximately 60 schools in the FNS Midwest Region: Extension.
Launch and evaluate a national dissemination of our research findings and share table resources to key stakeholders via social media marketing and online professional development dissemination: Extension

More information can be found in the funder’s database.

Aggregative Sampling for Powerful Preharvest Leafy Green Food Safety Testing

A three year project funded by:

The overall objective of this project is to demonstrate and validate that aggregative swab sampling can be used for powerful preharvest leafy green food safety testing that will ultimately allow producers to better protect public health by identifying adulterating pathogens before they enter the food supply.

Develop aggregative sampling for preharvest food safety testing and determine its power to detect bacterial hazards using inoculated field trials.
Validate the power of aggregative sampling to detect bacterial foodborne pathogens by comparing to composite grab sampling in commercial fields with previous pathogen positive test results

More information can be found in the funder’s database.

Digital farm-to-facility food safety testing optimization

A two-year project funded by the:

With the following three objectives:

Build a Field-to-Facility generic supply chain model of produce safety testing.
Adapt the supply chain and collect parameters to represent a variety of commodities with distinct risk profiles and risk-management options.
Optimize testing across the supply chain of each commodity incorporating representative testing programs at primary production, harvesting, receiving, processing, and packing and assessing their impact to manage safety.

More information on the project can be found in the funder’s database.

Improving Microbial Food Safety Through Simulation Analysis of Food Systems

A 5-year project from USDA NIFA Hatch funds to support the following project objectives:

Simulating Milk Powder Testing to Improve Capabilities to Detect Rare Pathogens
Simulating K-12 Share Tables to Assess Food Safety

More information can be found in the funder’s database.

When to use one-dimensional, two-dimensional, and Shifted Transversal Design pooling in mycotoxin screening

Abstract

While complex sample pooling strategies have been developed for large-scale experiments with robotic liquid handling, many medium-scale experiments like mycotoxin screening by Enzyme-Linked Immunosorbent Assay (ELISA) are still conducted manually in 48- and 96-well plates. At this scale, the opportunity to save on reagent costs is offset by the increased costs of labor, materials, and risk-of-error caused by increasingly complex pooling strategies. This paper compares one-dimensional (1D), two-dimensional (2D), and Shifted Transversal Design (STD) pooling to study whether pooling affects assay accuracy and experimental cost and to provide guidance for when a human experimentalist might benefit from pooling. We approximated mycotoxin contamination in single corn kernels by fitting statistical distributions to experimental data (432 kernels for aflatoxin and 528 kernels for fumonisin) and used experimentally-validated Monte-Carlo simulation (10,000 iterations) to evaluate assay sensitivity, specificity, reagent cost, and pipetting cost. Based on the validated simulation results, assay sensitivity remains 100% for all four pooling strategies while specificity decreases as prevalence level rises. Reagent cost could be reduced by 70% and 80% in 48- and 96-well plates, with 1D and STD pooling being most reagent-saving respectively. Such a reagent-saving effect is only valid when prevalence level is < 21% for 48-well plates and < 13%-21% for 96-well plates. Pipetting cost will rise by 1.3–3.3 fold for 48-well plates and 1.2–4.3 fold for 96-well plates, with 1D pooling by row requiring the least pipetting. Thus, it is advisable to employ pooling when the expected prevalence level is below 21% and when the likely savings of up to 80% on reagent cost outweighs the increased materials and labor costs of up to 4 fold increases in pipetting.

DOI

https://doi.org/10.1371/journal.pone.0236668

Improving Microbial Food Safety Through Engineering and Statistical Approaches in Food Microbiology

A five-year project funded by USDA NIFA Hatch funds which represented a significant portion of my group’s startup funds.

To support the long-term goal of developing a flexible applied food safety laboratory, Hatch funds will be used to support the following initial, discrete projects:

Genomics and Engineering Tools for Persistent Pathogen Identification and Control.
Single-Kernel Sorting to Remove Mycotoxins from Cereals.
Systems Approaches to Valuing Reductions in Foodborne Pathogen Contamination of Foods.

More information can be found on the funder’s database.

Simulation Analysis of In-Field Produce Sampling for Risk-Based Sampling Plan Development

A two year project funded by the:

With the following four objectives:

Simulate contamination of produce fields that are representative of commercial fields in four produce-growing regions of the United States.
Evaluate convenience, improved generic, and risk-based sampling plans.
Validate simulations against data from industry partners and academic literature.
Validate simulations against field-trials of controlled contamination events.

More information on the project can be found in the funder’s database.

Here is a 1-minute update from 2019.

Simulating Large-Number Bulk-Product Sampling to Improve Food Safety Sampling Plans

A two-year externally funded project by:

This project will build a simulation model to solve the problem of how to best take many samples of bulk products for food safety testing. That way, industries can use that knowledge to create sampling plans, and sampling devices, for their products that achieve important food safety goals. The general objective of this project is to build a validated and ready-to-use simulation model of bulk product sampling to improving sampling plans. The specific aims are:

Build a bulk product sampling simulation model for food safety testing.
Validate the simulation model against reported bulk product sampling.
Validate corn-aflatoxin simulation against experimental Texas corn sampling.
Build a user interface to parameterize the simulation model by answering a series of web-based questions.

ILSI, and my group, is committed to open, honest science particularly when industry stakeholder come together to aggregate support for important projects such as this. Therefore, you can find a complete pre-registration of this project under the Open Science Framework: Project Public Registration.

And additional information on the funder’s website of projects.

There is a video update of a poster presentation at IAFP 2019 here.

A Review of the Methodology of Analyzing Aflatoxin and Fumonisin in Single Corn Kernels and the Potential Impacts of These Methods on Food Security

Abstract

Current detection methods for contamination of aflatoxin and fumonisin used in the corn industry are based on bulk level. However, literature demonstrates that contamination of these mycotoxins is highly skewed and bulk samples do not always represent accurately the overall contamination in a batch of corn. Single kernel analysis can provide an insightful level of analysis of the contamination of aflatoxin and fumonisin, as well as suggest a possible remediation to the skewness present in bulk detection. Current literature describes analytical methods capable of detecting aflatoxin and fumonisin at a single kernel level, such as liquid chromatography, fluorescence imaging, and reflectance imaging. These methods could provide tools to classify mycotoxin contaminated kernels and study potential co-occurrence of aflatoxin and fumonisin. Analysis at a single kernel level could provide a solution to the skewness present in mycotoxin contamination detection and offer improved remediation methods through sorting that could impact food security and management of food waste.

DOI

https://doi.org/10.3390/foods9030297

(This article belongs to the Special Issue Safeguarding the Global Food Supply: Advances in Mycotoxin Prevention, Surveillance and Mitigation)

Persistent and sporadic Listeria monocytogenes strains do not differ when growing at 37°C, in planktonic state, under different food associated stresses or energy sources

Abstract

The foodborne pathogen Listeria monocytogenes causes the potentially lethal disease listeriosis. Within food-associated environments, L. monocytogenes can persist for long periods and increase the risk of contamination by continued presence in processing facilities or other food-associated environments. Most research on phenotyping of persistent L. monocytogenes’ has explored biofilm formation and sanitizer resistance, with less data examining persistent L. monocytogenes’ phenotypic responses to extrinsic factors, such as variations in osmotic pressure, pH, and energy source availability. It was hypothesized that isolates of persistent strains are able to grow, and grow faster, under a broader range of intrinsic and extrinsic factors compared to closely related isolates of sporadic strains.

DOI

https://doi.org/10.1186/s12866-019-1631-3