Manchester Metropolitan University's Research Repository

Label-Free Detection of Escherichia coli Based on Thermal Transport through Surface Imprinted Polymers

van Grinsven, B and Eersels, K and Akkermans, O and Ellermann, S and Kordek, A and Peeters, M and Deschaume, O and Bartic, C and Diliën, H and Steen Redeker, E and Wagner, P and Cleij, TJ (2016) Label-Free Detection of Escherichia coli Based on Thermal Transport through Surface Imprinted Polymers. ACS Sensors, 1 (9). pp. 1140-1147. ISSN 2379-3694


Download (1MB) | Preview


This work focuses on the development of a label-free biomimetic sensor for the specific and selective detection of bacteria. The platform relies on the rebinding of bacteria to synthetic cell receptors, made by surface imprinting of polyurethane-coated aluminum chips. The heat-transfer resistance (Rth) of these so-called surface imprinted polymers (SIPs) was analyzed in time using the heat-transfer method (HTM). Rebinding of target bacteria to the synthetic receptor led to a measurable increase in thermal resistance at the solid–liquid interface. Escherichia coli and Staphylococcus aureus were used as model organisms for several proof-of-principle experiments, demonstrating the potential of the proposed platform for point-of-care bacterial testing. The results of these experiments indicate that the sensor is able to selectively detect bacterial rebinding to the SIP surface, distinguishing between dead and living E. coli cells on one hand and between Gram-positive and Gram-negative bacteria on the other hand (E. coli and S. aureus). In addition, the sensor was capable of quantifying the number of bacteria in a given sample, enabling detection at relatively low concentrations (104 CFU mL–1 range). As a first proof-of-application, the sensor was exposed to a mixed bacterial solution containing only a small amount (1%) of the target bacteria. The sample was able to detect this trace amount by using a simple gradual enrichment strategy.

Impact and Reach


Activity Overview

Additional statistics for this dataset are available via IRStats2.


Actions (login required)

View Item View Item