A table-top sensor for the detection of hydrophobins and yeasts in brewery applications

In this work, we present a biomimetic sensor for the sensitive and fast (< 15 min) detection of yeast cells (S. cerevisiae) and hydrophobins (e.g. HFB) in food and beverages. While unwanted yeast contaminations can cause off-flavors and stability issues, hydrophobin contaminations are a less-known but equally serious economic concern in beer production. Hydrophobins are small proteins, that are produced by pathogenic fungi that often infect barley. Due to their high temperature stability, HFBs survive all stages of brewing and, after bottling, they cause excessive foaming due to interactions between the HFBs, CO2, and glass surfaces. Tiny HFB concentrations are sufficient to cause this gushing and up to 10% of beer production is therefore discarded. Hence, an earlystage HFB detection, preferably even before malting, would reduce the loss of resources. However, existing tests are time-consuming and have sub-optimal accuracy. The novel sensor platform has a user-friendly design that combines impedimetric readout with wire-type electrodes, coated with poly-pyrrole layers that are imprinted with Trichoderma reesei hydrophobin I (HFBI) molecules or with yeast cells. In complex food samples, the sensor reaches detection limits of 50 yeast cells/mL (in yoghurt solution) and below 30 ng/mL HFBI in top-fermented beer samples. Cross-selectivity tests with proteins of similar size show a response to Hyd5 (another hydrophobin) and discrimination against insulin. As a final proof of application, we demonstrate hydrophobin detection directly in extracts of industrial malt samples with and without a natural hydrophobin contamination.

Automated summary

In this study, a biomimetic sensor was developed for the sensitive and fast detection of yeast cells and hydrophobins in food and beverages. Hydrophobin contamination is a significant concern in beer production, leading to excessive foaming and loss of resources. Existing tests are time-consuming and less accurate, while the novel sensor platform offers a user-friendly design and improved accuracy.