Abstract

Foodborne pathogens are a major concern for public health. We demonstrate for the first time a partially automated sensing system for rapid (~17 min), label-free impedimetric detection of Escherichia coli spp. in food samples (vegetable broth) and hydroponic media (aeroponic lettuce system) based on temperature-responsive poly(N-isopropylacrylamide) (PNIPAAm) nanobrushes. This proof of concept (PoC) for the Sense-Analyze-Respond-Actuate (SARA) paradigm uses a biomimetic nanostructure that is analyzed and actuated with a smartphone. The bio-inspired soft material and sensing mechanism is inspired by binary symbiotic systems found in nature, where low concentrations of bacteria are captured from complex matrices by brush actuation driven by concentration gradients at the tissue surface. To mimic this natural actuation system, carbon-metal nanohybrid sensors were fabricated as the transducer layer, and coated with PNIPAAm nanobrushes. The most effective coating and actuation protocol for E. coli detection at various temperatures above/below the critical solution temperature of PNIPAAm was determined using a series of electrochemical experiments. After analyzing nanobrush actuation in stagnant media, we developed a flow through system using a series of pumps that are triggered by electrochemical events at the surface of the biosensor. SARA PoC may be viewed as a cyber-physical system that actuates nanomaterials using smartphone-based electroanalytical testing of samples. This study demonstrates thermal actuation of polymer nanobrushes to detect (sense) bacteria using a cyber-physical systems (CPS) approach. This PoC may catalyze the development of smart sensors capable of actuation at the nanoscale (stimulus-response polymer) and macroscale (non-microfluidic pumping).

Highlights

  • Foodborne pathogens in the global food supply chain increase the risk of mortality and morbidity

  • We show that actuation of PNIPAAm nanobrushes leads to enhanced bacteria capture and controllable electrochemical transduction based on an external stimulus in laboratory studies

  • As foodborne pathogens are a persistent concern in the food industry, there is a demand for a rapid, reliable, and cost-effective detection method

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Summary

Introduction

Foodborne pathogens in the global food supply chain increase the risk of mortality and morbidity. Outbreak Reporting System (NORS), an annual average of 15,332 illnesses, 879 hospitalizations, and 22 deaths caused by foodborne diseases were reported from 2008 to 2017 [5]. The U.S Centers of Disease Control and Prevention (CDC) [6] estimates that around 48 million people get sick, 128,000 are hospitalized, and 3000 deaths occur in the. Such discrepancy emphasizes the limitations of data collection correlated with misinformation, misreport, and lack of accessible diagnostic tools. Among the food products commonly associated with outbreaks, fresh produce is one of the leading causes of foodborne illnesses [7], with 377 outbreaks reported by the CDC from 2004 to 2012 [8]. The bacteria commonly associated with foodborne outbreaks include Salmonella spp., Listeria monocytogenes, and pathogenic Escherichia coli

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