Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor.

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers.

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

New Vision for Visual Prostheses.

Developments of new strategies to restore vision and improving on current strategies by harnessing new advancements in material and electrical sciences, and biological and genetic-based technologies are of upmost health priorities around the world. Federal and private entities are spending billions of dollars on visual prosthetics technologies. This review describes the most current and state-of-the-art bioengineering technologies to restore vision. This includes a thorough description of traditional electrode-based visual prosthetics that have improved substantially since early prototypes. Recent advances in molecular and synthetic biology have transformed vision-assisted technologies; For example, optogenetic technologies that introduce light-responsive proteins offer excellent resolution but cortical applications are restricted by fiber implantation and tissue damage. Other stimulation modalities, such as magnetic fields, have been explored to achieve non-invasive neuromodulation. Miniature magnetic coils are currently being developed to activate select groups of neurons. Magnetically-responsive nanoparticles or exogenous proteins can significantly enhance the coupling between external electromagnetic devices and any neurons affiliated with these modifications. The need to minimize cytotoxic effects for nanoparticle-based therapies will likely restrict the number of usable materials. Nevertheless, advances in identifying and utilizing proteins that respond to magnetic fields may lead to non-invasive, cell-specific stimulation and may overcome many of the limitations that currently exist with other methods. Finally, sensory substitution systems also serve as viable visual prostheses by converting visual input to auditory and somatosensory stimuli. This review also discusses major challenges in the field and offers bioengineering strategies to overcome those.