Noninvasive detection of bacterial biofilms using an insect olfactory brain-based gas sensor

Bacteria emit volatile organic compounds (VOCs) that can be targeted for disease detection. Biological olfactory systems have keen senses of smell, can detect VOCs at low concentrations, and are naturally adapted to classifying mixtures of VOCs as odors. Here, we employed locust (Schistocerca americana) olfactory neural circuitry to differentiate biofilm and planktonic cultures of Pseudomonas aeruginosa and Staphylococcus aureus using their odors.

In vivo extracellular neural recordings were taken from the second-order olfactory processing center (antennal lobe) of locusts. The VOCs from biofilm cultures evoked distinct spiking responses compared to the planktonic cultures for both bacterial species. By analyzing the population neuronal responses, we classified individual bacterial biofilm vs. planktonic odors with up to 96% accuracy.

The neural responses were highly discriminatory within the first couple of seconds of odor presentation and our analysis was conducted on less than five seconds of data, highlighting the potential of our biological sensor for real-time biofilm detection. Funding for this work was provided by the NSF CAREER [2238686] grant to D.S., NSF Graduate Research Fellowship to A.M.S. and S.M.S. Department of Biomedical Engineering, Michigan State University, East Lansing, MI, USA Michael Parnas, Autumn K.

McLane-Svoboda, Summer B. McLane-Svoboda & Debajit Saha The Institute for Quantitative Health Science and Engineering (IQ), Michigan State University, East Lansing, MI, USA Michael Parnas, Autumn K. McLane-Svoboda, Mariam Shahab, Camron Stout, Summer B.

McLane-Svoboda, Elyssa Cox, Mitchell Vaske, Jonathan Hardy & Debajit Saha Department of Microbiology, Genetics, Immunology, Michigan State University, East Lansing, MI, USA Correspondence to Jonathan Hardy or Debajit Saha. The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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