Sensor Technologies and Biological Sensing Lecture 2024 PDF

BIOINSPIRED SENSORS: BALANCE, OLFACTION AND GUSTATION Lecture 7 2024. 11. 13. Dr. Sándor Földi Sensor technologies and biological sensing  CONTENTS 1. Physiology of balance 2. Biomimetic bal...

BIOINSPIRED SENSORS: BALANCE, OLFACTION AND GUSTATION Lecture 7 2024. 11. 13. Dr. Sándor Földi Sensor technologies and biological sensing  CONTENTS 1. Physiology of balance 2. Biomimetic balance sensors 3. Physiology of olfaction 4. Bioinspired olfaction sensor technologies 5. Gustation physiology 6. Biomimetic gustation sensors 3  RECAP – BALANCE 4 Reference: Hall, John E., and Guyton AC. "Guyton and Hall textbook of medical physiology." (2006).  ARTIFICIAL VESTIBULAR SYSTEM Based on MEMS technology and 3D printing MEMS technology-based flow/pressure sensor 3D structure mimiced from the biological semicircular canal Similar dimensions and mechanisms as in a human semicircular canal Prototype of the biomimiced lateral semicircular canal Reference: Raoufi, M. A., Moshizi, S. A., Razmjou, A., Wu, S., Warkiani, M. E., & Asadnia, M. (2019). Development of a biomimetic semicircular canal with MEMS sensors to restore balance. IEEE Sensors 5 Journal, 19(23), 11675-11686.  ARTIFICIAL VESTIBULAR SYSTEM Testing of the biomimiced lateral semicircular canal Reference: Raoufi, M. A., Moshizi, S. A., Razmjou, A., Wu, S., Warkiani, M. E., & Asadnia, M. (2019). Development of a biomimetic semicircular canal with MEMS sensors to restore balance. IEEE Sensors 6 Journal, 19(23), 11675-11686.  ARTIFICIAL VESTIBULAR SYSTEM Testing of the biomimiced lateral semicircular canal Reference: Raoufi, M. A., Moshizi, S. A., Razmjou, A., Wu, S., Warkiani, M. E., & Asadnia, M. (2019). Development of a biomimetic semicircular canal with MEMS sensors to restore balance. IEEE Sensors 7 Journal, 19(23), 11675-11686.  RECAP – OLFACTION MECHANISM Reference: Auffarth, Benjamin, Bernhard Kaplan, and Anders Lansner. "Map formation in the olfactory bulb by axon guidance of olfactory neurons." Frontiers in systems 8 neuroscience 5 (2011): 84.  OLFACTION – BIOLOGY VS. ARTIFICIAL Reference: Cuypers, Wim, and Peter A. Lieberzeit. "Combining two selection principles: Sensor arrays based on both biomimetic recognition and chemometrics." Frontiers in 9 chemistry 6 (2018): 268.  OLFACTION The olfactory system has high complexity Human olfactory nose: 300 receptors Thousands of different molecules in the environment, millions of possible combinations To discriminate between millions of odors with only a few hundred sensors → combinatorial code: each receptor is sensitive at different levels to a variety of chemicals, while each odorant can stimulate to different extents several receptors Comparison with vision and hearing 10 Reference: Lakhtakia, Akhlesh, and Raúl José Martín-Palma, eds. Engineered biomimicry. Newnes, 2013.  OLFACTION Complexity at the processing level: The responses of the 300 olfactory receptors generate in the olfactory bulbs unique odor pictures that can be visualized using fluorescence dyes and imaging systems Such pictures, however, are further processed in the brain and integrated with inputs from other sensory modalities, as well as compared with memories of past experience. Finally, the smell produces a sensation that becomes expressed through verbal description, behavioral responses and emotions. In analogy with the color code, we can define the olfactory code as the list of elementary odors that can be combined to produce the innumerable different sensations we experience every day 11  OLFACTION Odors could be represented by chemical structures, each one being the best ligand or each olfactory receptor 50 human olfactory receptors have been deorphanized Redundancy observed for several of them → Ensure that in spite of random mutations that might switch off some receptors, some important odors can still be detected Specific anosmia: is the inability of some subjects of the human population to detect one or more odors. related to the absence or the malfunctioning of one or more olfactory receptors. 12  OLFACTION Phylogenetic tree of the 50 human receptors deorphanized 13 Reference: Pelosi, Paolo, Jiao Zhu, and Wolfgang Knoll. "From gas sensors to biomimetic artificial noses." Chemosensors 6.3 (2018): 32.  OLFACTION One of the great challenges in reproducing the functioning of biological noses is to match their exceptional sensitivity Olfactory threshold: the minimum concentration that an average individual is able to detect Much lower for most animals Still, electronic instruments requires at least 3–5 orders of magnitude sensitivity improvement compared to humans for real time analysis of odors. 14  ARTIFICIAL NOSE 3 steps to translate chemical information encoded in volatile molecules into measurable parameters describing odor quality and concentration: 1. An array of gas sensors, able to interact with volatile molecules and produce some sort of signal (electrical, optical, etc.) suitable to be amplified and processed. 2. An amplifier to cope with the very low concentrations associated with odors. 3. A pattern recognition software for recognizing specific response profiles associated with different odors. 15 Reference: Lakhtakia, Akhlesh, and Raúl José Martín-Palma, eds. Engineered biomimicry. Newnes, 2013.  ARTIFICIAL NOSE – SIGNAL DETECTION Type of sensing elements: Aim: discrimination between different molecules Stereochemical parameters are more important than functional groups → Sensors should discriminate on the basis of size and shape Number of sensing elements: Mammals: several hundreds of receptors Human: ~300 receptors Comparison with vision and hearing Coding the information: Physiological noses detect and discriminate between a very large number of odorants using a combinatorial approach, similar to the letters of the alphabet that can form thousands of different words Question: use the physiological coding or not Analogy: color vision – can be made by 3 sensors, but not necessarily tuned to the same wavelength of our 3 rhodopsins. 16  ARTIFICIAL NOSE – FEATURES OF BIOLOGICAL AND ARTIFICIAL NOSE 17 Reference: Pelosi, Paolo, Jiao Zhu, and Wolfgang Knoll. "From gas sensors to biomimetic artificial noses." Chemosensors 6.3 (2018): 32.  TYPES OF GAS SENSORS Metal oxides: Most frequently used platforms in gas sensing devices Measures electrical resistance in response to odors Zinc, tin, nickel or transition metals (their electric resistance changes when in contact organic compounds in the gas phase) More recently graphene-based materials Cheap and robust Two major problems: Very limited selectivity and respond with similar intensities to most volatiles Very slow regeneration, they have to be heated at 300 °C to bring the response back to base line Used as smoke alarms or to detect leaking cooking gas in homes 18  TYPES OF GAS SENSORS Conducting polymers: Measures electrical resistance in response to odors Improved selectivity Highest selectivity by using polypyrrole and ammonia Advantage: possibility of changing the materials’ spectra of response by modifying their chemical structure Olfactory receptors: Ideal choice for mimicking the human nose Difficulties: Transmembrane proteins → a membrane is required to sit across Very delicate as far as their 3D structure is concerned Only stable in laboratory environment Almost impossible to regenerate the receptor after signal production 19  TYPES OF GAS SENSORS Soluble binding proteins: Odorant Binding Proteins (OBPs): have simple structure and high stability OBPs present a binding cavity, where molecules of odorants and pheromones can be accommodated with relatively good affinity (dissociation constants in the micromolar order) Their selectivity to hydrophobic ligands is not as high as known for olfactory receptors Advantages: Can be produced in bacteria in relatively large quantities Their compact structure grants them an exceptional stability to temperature, to proteolity digestiona and organic solvents 20  ARTIFICIAL NOSE – TRANSDUCING STRATEGIES Metal oxides or semiconducting polymers: signal is directly produced as a change in electric resistance upon interactions with odors Soluble binding proteins: only conformational changes in the protein → it has to be converted into a signal, amplified and processed Three conversion categories: Changes of mass Optical signals Electric properties 21 Reference: Persaud, Krishna C. "Biomimetic olfactory sensors." IEEE Sensors Journal 12.11 (2012): 3108-3112.  ARTIFICIAL NOSE – TRANSDUCING STRATEGIES Changes of mass: Measured using piezoelectric quartz crystals by monitoring the proteins oscillations Surface Acoustic Wave (SAW): Immobilization of the protein on the crystal and monitoring the change of frequency occuring when a ligand binds to the protein, thus increasing the mass of the sensor Optical sensors: Record the changes in refractive index consequent to binding of a ligand to a protein or a DNA fragment Surface Plasmon Resonance (SPR): Olfactory receptors immobilised on a prism Detection limits in the micromolar range Bulky and expensive instrument Not very accurate in the case of small organic compounds (e.g.: odorants) 22  ARTIFICIAL NOSE – TRANSDUCING STRATEGIES Electric sensors: Voltage, current and impedance detectors Modified field effect transistors: OBPs attached to the gate electrode Measuring the variations in current produced in the presence of various ligands Development of a biosensor using interdigitated electrodes coated with OBPs embedded in nitrocellulose. Such devices respond to the presence of ligands with changes in impedance. 23  ARTIFICIAL NOSE – EXAMPLES In vivo biosensing approach Reference: Wu, C., Du, Y. W., Huang, L., Ben-Shoshan Galeczki, Y., Dagan-Wiener, A., Naim, M.,... & Wang, P. (2017). Biomimetic sensors for the senses: towards better understanding of 24 taste and odor sensation. Sensors, 17(12), 2881.  ARTIFICIAL NOSE – EXAMPLES In vivo biosensing approach Reference: Gao, K., Gao, F., Li, J., He, C., Liu, M., Zhu, Q.,... & Wang, P. (2021). Biomimetic integrated olfactory sensory and olfactory bulb systems in vitro based on a chip. Biosensors and 25 Bioelectronics, 171, 112739.  ARTIFICIAL NOSE – EXAMPLES Vibration-based biomimetic odor classification Inspired by the vibration theory of biological olfaction Eigen-value vibrational pseudo spectra Unsupervised Machine Learning (spectral clustering) Shape and vibration theory 26 Reference: Pandey, N., Pal, D., Saha, D., & Ganguly, S. (2021). Vibration-based biomimetic odor classification. Scientific reports, 11(1), 1-8.  ARTIFICIAL NOSE – EXAMPLES Quantum biomimetic Electronic Nose Sensor Inspired by the vibration theory of biological olfaction Photon-assisted inelastic electron tunneling spectroscopy 27 Reference: Patil, Ashlesha, Dipankar Saha, and Swaroop Ganguly. "A quantum biomimetic electronic nose sensor." Scientific reports 8.1 (2018): 1-8.  RECAP – GUSTATION 28 Reference: Lu, Lin, Xianqiao Hu, and Zhiwei Zhu. "Biomimetic sensors and biosensors for qualitative and quantitative analyses of five basic tastes." TRAC Trends in Analytical Chemistry 87 (2017): 58-70.  GUSTATION – PHYSIOLOGY Tongue contains tens of thousands of taste buds Each taste bud has 50–100 taste receptor cells Taste sensation: Specific signals are generated on the buds stimulated by various substances and tastants. Brain recognizes the patterns to differentiate, classify and analyse the concerned substances or tastants. Taste cells and taste tissues can recieve multiple taste signals evoked by different substances or tastants. 29  GUSTATION – PHYSIOLOGY Transduction: Reception of chemical substances by taste cells A nerve fiber connected to the taste cell shows excitation One nerve fiber does not necessarily have the information of only one taste quality Nerve fiber shows nonselective, nonspecific response to each taste quality The taste quality is distinguished using the overall excitation pattern of nerve fibers Reference: Toko, Kiyoshi. Biomimetic sensor technology. Cambridge University Press, 2000. 30  GUSTATION – BASIC TASTES 31 Reference: Toko, Kiyoshi. Biomimetic sensor technology. Cambridge University Press, 2000.  GUSTATION– BASIC TASTES Reference: Lu, Lin, Xianqiao Hu, and Zhiwei Zhu. "Biomimetic sensors and biosensors for qualitative and quantitative analyses of five basic tastes." TRAC Trends in 32 Analytical Chemistry 87 (2017): 58-70.  BIOMIMETIC GUSTATION SENSORS Measurement of taste: Required sensor characteristics: high sensitivity, stability and high selectivity High complexity: e.g. tea and coffee are included over 1000 chemical substances Taste sensors can be realized by the use of lipid membranes as transducers Discrimination of each chemical substance is not important here The taste sensor using lipid/polymer membranes is based on a concept of global selectivity, which implies the ability to classify enormous numbers of chemical substances into several groups, as really found in the taste reception in biological systems. 33  BIOMIMETIC GUSTATION SENSORS– MAIN TYPES Reference: Lu, Lin, Xianqiao Hu, and Zhiwei Zhu. "Biomimetic sensors and biosensors for qualitative and quantitative analyses of five basic tastes." TRAC Trends in 34 Analytical Chemistry 87 (2017): 58-70.  BIOMIMETIC GUSTATION SENSORS Multichannel taste sensor Measurement system for laboratory use 35 Reference: Toko, Kiyoshi. Biomimetic sensor technology. Cambridge University Press, 2000.  GUSTATION– VOLTAMMETRIC SENSOR Reference: Ivarsson, P., Kikkawa, Y., Winquist, F., Krantz-Rülcker, C., Höjer, N. E., Hayashi, K.,... & Lundström, I. (2001). Comparison of a voltammetric electronic tongue and a lipid 36 membrane taste sensor. Analytica Chimica Acta, 449(1-2), 59-68.  GUSTATION– POTENTIOMETRIC SENSOR Reference: Ivarsson, P., Kikkawa, Y., Winquist, F., Krantz-Rülcker, C., Höjer, N. E., Hayashi, K.,... & Lundström, I. (2001). Comparison of a voltammetric electronic tongue and a lipid 37 membrane taste sensor. Analytica Chimica Acta, 449(1-2), 59-68.  GUSTATION – TISSUE-BASED GUSTATION BIOSENSOR Multielectrode array Taste epithelium isolated from rats Reference: Wu, C., Du, Y. W., Huang, L., Ben-Shoshan Galeczki, Y., Dagan-Wiener, A., Naim, M.,... & Wang, P. (2017). Biomimetic sensors for the senses: towards better 38 understanding of taste and odor sensation. Sensors, 17(12), 2881.  GUSTATION – CELL-BASED GUSTATION BIOSENSOR Taste receptor cells Light-addressable potentiometric sensor (LAPS) Reference: Wu, C., Du, Y. W., Huang, L., Ben-Shoshan Galeczki, Y., Dagan-Wiener, A., Naim, M.,... & Wang, P. (2017). Biomimetic sensors for the senses: towards better understanding of 39 taste and odor sensation. Sensors, 17(12), 2881.  GUSTATION – POTENTIOMETRIC SENSOR Reference: Zhang, W., Li, Y., Liu, Q., Xu, Y., Cai, H., & Wang, P. (2008). A novel experimental research based on taste cell chips for taste transduction mechanism. Sensors and Actuators B: 40 Chemical, 131(1), 24-28.  SUMMARY – QUESTIONS How can a biomimetic sensor be designed and validated? What is the difficulty with chemical senses? How does a biomimetic smell sensor work? (Introduce one smell sensor in details.) Introduce two taste sensors briefly. 41  REFERENCES 1. Raoufi, M. A., Moshizi, S. A., Razmjou, A., Wu, S., Warkiani, M. E., & Asadnia, M. (2019). Development of a biomimetic semicircular canal with MEMS sensors to restore balance. IEEE Sensors Journal, 19(23), 11675-11686. 2. Cuypers, Wim, and Peter A. Lieberzeit. "Combining two selection principles: Sensor arrays based on both biomimetic recognition and chemometrics." Frontiers in chemistry 6 (2018): 268. 3. Pelosi, Paolo, Jiao Zhu, and Wolfgang Knoll. "From gas sensors to biomimetic artificial noses." Chemosensors 6.3 (2018): 32. 4. Persaud, Krishna C. "Biomimetic olfactory sensors." IEEE Sensors Journal 12.11 (2012): 3108- 3112. 5. Pandey, N., Pal, D., Saha, D., & Ganguly, S. (2021). Vibration-based biomimetic odor classification. Scientific reports, 11(1), 1-8. 6. Wu, C., Du, Y. W., Huang, L., Ben-Shoshan Galeczki, Y., Dagan-Wiener, A., Naim, M.,... & Wang, P. (2017). Biomimetic sensors for the senses: towards better understanding of taste and odor sensation. Sensors, 17(12), 2881. 7. Gao, K., Gao, F., Li, J., He, C., Liu, M., Zhu, Q.,... & Wang, P. (2021). Biomimetic integrated olfactory sensory and olfactory bulb systems in vitro based on a chip. Biosensors and Bioelectronics, 171, 112739. 42  REFERENCES 8. Patil, Ashlesha, Dipankar Saha, and Swaroop Ganguly. "A quantum biomimetic electronic nose sensor." Scientific reports 8.1 (2018): 1-8. 9. Lu, Lin, Xianqiao Hu, and Zhiwei Zhu. "Biomimetic sensors and biosensors for qualitative and quantitative analyses of five basic tastes." TRAC Trends in Analytical Chemistry 87 (2017): 58-70. 10. Toko, Kiyoshi. Biomimetic sensor technology. Cambridge University Press, 2000. 11. Wu, C., Du, Y. W., Huang, L., Ben-Shoshan Galeczki, Y., Dagan-Wiener, A., Naim, M.,... & Wang, P. (2017). Biomimetic sensors for the senses: towards better understanding of taste and odor sensation. Sensors, 17(12), 2881. 12. Zhang, W., Li, Y., Liu, Q., Xu, Y., Cai, H., & Wang, P. (2008). A novel experimental research based on taste cell chips for taste transduction mechanism. Sensors and Actuators B: Chemical, 131(1), 24-28. 13. Ivarsson, P., Kikkawa, Y., Winquist, F., Krantz-Rülcker, C., Höjer, N. E., Hayashi, K.,... & Lundström, I. (2001). Comparison of a voltammetric electronic tongue and a lipid membrane taste sensor. Analytica Chimica Acta, 449(1-2), 59-68. 43