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SCENT: Hybrid Gels for Rapid Microbial Detection

Periodic Reporting for period 3 - SCENT (SCENT: Hybrid Gels for Rapid Microbial Detection)

Reporting period: 2018-12-01 to 2020-05-31

Antimicrobial resistant bacteria are a global threat spreading at an alarming pace. They cause over 25,000 annual deaths in the EU, and represent an economic burden exceeding €1.5 billion a year. Current methods for microbial detection in clinical settings take about 24-36 h, but for slow-growing bacteria, as those causing tuberculosis, it can take more than a week. Early-detection and confinement of the infected individuals are the only ways to provide adequate therapy and control infection spread. Thus, tools for rapid identification of bacterial infections are greatly needed.
The analysis of microbial volatile metabolites is an area of increasing interest in diagnostics. Recent works demonstrate that fast microbial identification is possible with chemical nose sensors. These sensors usually present limited stability and selectivity, and require aggressive conditions during processing and operation. Bioinspired nose sensors employing biological olfactory receptors are an alternative. Unfortunately, their complexity and low stability are a limitation. The SCENT team is working with an innovative class of stimulus-responsive gels, which tackle these key challenges. Our gels are customisable and have a low environmental footprint associated. The SCENT project is exploring the potential of these new materials to advance the field of odour detection, while providing new tools for the scientific community. To accomplish this, the SCENT team is: 1) building libraries of gels with semi-selective and selective properties, 2) generating odorant specific peptides mimicking olfactory receptors, 3) assembling artificial noses for analysis of microbial volatiles, 4) creating databases with organism-specific signal signatures, 5) identifying pathogenic bacteria, including those with acquired antimicrobial-resistances. This project is a timely approach, which will place Europe in the forefront of infectious disease control.
Gels that smell?
Can you imagine a gel that can distinguish different samples by smelling them? Roque and co-workers made this vision come true. The SCENT team is developing gas-sensitive materials with a unique combination of biological and chemical components, which self-assemble to form gels. These new materials mimic the biological olfactory system but are much simpler in composition and robust in their design. The gas sensing-gels are then used in a tailor-made electronic-nose device, and tested to distinguish different volatile organic compounds, showing the potential for discrimination of distinct odors. Potential applications for the technology have been shown towards the quantification of ethanol in automotive fuel (Hussain et al, Adv. Funct. Mater. 2017, 27, 1700803; DOI: 10.1002/adfm.201700803) and monitoring of fish deterioration due to microbial action (Semeano et al, Food Control. 2018 Jul;89:72-76; DOI: 10.1016/j.foodcont.2018.01.025).
The final goal of this artificial olfaction device is to detect in a non-invasive and timely manner infected individuals. To meet this goal, SCENT researchers designed a machine learning algorithm to make predictions of human microbial pathogens based on the volatile compounds released (Palma et al, Scientific Reports. 2018. volume 8, Article number: 3360; DOI:10.1038/s41598-018-21544-1). Such information will help us designing more selective electroni noses towards the diagnostic of human infections.
Detection of smells, or gas sensing, is becoming increasingly relevant in such diverse areas as medical diagnostics, manufacturing industry, security, environment, agricultural and food sciences. Electronic noses (e-noses) are devices used for gas sensing. These devices are able to distinguish gases by “smelling”, conceptually mimicking the biological olfactory system in humans and other animals. E-noses are comprised of an array of gas-sensitive materials that all have different and complementary selectivity thus, when considering the entire array, the e-nose gives rise to a pattern that is unique to the gaseous sample. These devices thereby mimic the set of biological receptors, which recognize odors in a combinatorial manner and are coupled to pattern recognition systems – mimicking signal processing analogous to that made by the brain – and are therefore capable of recognizing simple or complex odors.
The new materials developed within the SCENT project are sensitive to both chemical and physical stimuli, and as such several future applications can be envisaged compatible with miniaturized, wireless and wearable devices, from bioplastic electronics to electrochemical and medical devices.
Monitoring fish deterioration due to microbial action using a single optical sensor operating at amb
The proof-of-concept: Gels that can smell! (VOC – volatile organic compound) (DOI: 10.1002/adfm.2017
Can we find sets of “smells” to distinguish between human microbial pathogens? (DOI:10.1038/s41598-0