IP Library › Granted Patent US 12,474,270
Granted Patent B2
US 12,474,270 · App. 17/480,654 · Granted Nov 18, 2025

Biological sensing and communication using optogenetics and electronics

Inventors: Bhuvana Krishnaswamy (Madison, WI); Megan N. Mcclean (Madison, WI)
Assignee: WISCONSIN ALUMNI RESEARCH FOUNDATION
G01N21/6458B01L3/502715C12M21/02C12M23/22C12N1/16C12N15/81G01N33/533H04B10/80H04B13/00B01L2300/0663C12R2001/865
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Quick Facts
Patent No.
US 12,474,270
App. No.
17/480,654
Granted
Nov 18, 2025
Kind
B2
Abstract

Devices, systems and methods for biological sensing and communication using optogenetics and electronics are described. One example method includes generating a light beam incident on multiple regions in a device, wherein each region comprises an optogenetic system to generate, upon interacting with the light beam, biosensors, wherein an interaction between the biosensors and stimulus molecules in each region is associated with a threshold for a production of an output molecule or an alteration of an output property of the output molecule, the biosensors, or the stimulus molecules, wherein the production or the alteration is based on a value associated with an information source, detecting an output received from one or more of the multiple regions corresponding to the output molecule or the output property in that region, and generating an electric signal associated therewith, and processing the electrical signal to determine the value associated with the information source.

Claims (86)

1 . An optogenetic communication system, comprising:

a biosensor subsystem comprising a plurality of biosensors;

a biotransmitter subsystem configured to produce an output molecule or alter an output property in response to the plurality of biosensors interacting with a plurality of stimulus molecules, the output property being associated with the output molecule, the plurality of biosensors, or the plurality of stimulus molecules; and

an electronic receiver subsystem comprising:

an output detector,

a processor, and

a memory including instructions executable by the processor stored thereon, wherein the instructions, upon execution by the processor, configure the processor to:

receive information from the output detector representative of sensing information conveyed by the biotransmitter subsystem, and process the information in digital form to detect one or more of the following:

the output property associated with the output molecule,

a concentration associated with the output molecule,

the output property associated with the plurality of biosensors,

the output property associated with the plurality of stimulus molecules,

a concentration of the plurality of biosensors, or

a concentration of the plurality of stimulus molecules.

2 . The system of claim 1 , wherein the output molecule comprises a light-emitting molecule.

3 . The system of claim 2 , wherein processing the received information in digital form comprises:

performing a demodulation operation on an electrical signal corresponding to an intensity of the light produced by the light-emitting molecules.

4 . The system of claim 2 , wherein the biosensor subsystem further comprises an optogenetic system configured to produce the plurality of biosensors upon being optically triggered by a light beam with a predetermined wavelength.

5 . The system of claim 4 , wherein the plurality of biosensors comprises a chimeric transcriptional activator Gal4dbd.ER.VP16 (GEV),

the plurality of stimulus molecules comprises beta-estradiol molecules,

wherein the light-emitting molecules comprise green fluorescent protein (GFP) molecules, and

wherein the optogenetic system comprises a ZCRY2/CIB1AD optogenetic system.

6 . The system of claim 1 , wherein the biosensor and biotransmitter subsystems are implemented using a microfluidic device comprising a plurality of regions,

wherein each of the plurality of regions produces a different granularity of biosensing detection in response to an incident light.

7 . The system of claim 1 , wherein the biosensor and biotransmitter subsystems are implemented using a microfluidic device comprising a plurality of regions,

wherein each of the plurality of regions is configured with a different type of biosensor and a different type of stimulus molecule.

8 . The system of claim 1 , wherein the output property comprises a pH level, or an electrical impedance.

9 . The system of claim 1 , wherein the output property comprises a level of molecular interaction between any combination of at least two of the following: the output molecule, the plurality of biosensors, or the plurality of stimulus molecules.

10 . The system of claim 5 , wherein each of the plurality of biosensors is expressed by yeast.

11 . The system of claim 6 , wherein each of the plurality of biosensors is associated with a respective region of the plurality of regions, and

wherein the biotransmitter subsystem is configured to implement, for each respective region of the plurality of regions, a distinct threshold of a plurality of distinct thresholds, such that, for each of the plurality of regions, and

wherein the biotransmitter subsystem is further configured to produce the output molecule or alter the output property, for each region, in response to a value of a signal measured by the biosensor subsystem satisfying the distinct threshold associated with the region, thereby indicating that the region has been activated.

12 . The system of claim 11 , wherein the information from the output detector representative of sensing information conveyed by the biotransmitter subsystem comprises:

an indication, for each region of the plurality of regions, of whether the region was activated, and

wherein processing the received information in digital form comprises:

determining the value of the signal based on which of the plurality of regions was activated and which of the plurality of regions was not activated.

13 . The system of claim 1 , wherein the biosensor subsystem further comprises a second plurality of biosensors,

the biotransmitter subsystem is configured to produce a second output molecule or alter a second output property in response to the second plurality of biosensors interacting with a second plurality of stimulus molecules, the second output property being associated with the second output molecule, the second plurality of biosensors, or the second plurality of stimulus molecules; and

wherein the instructions, upon execution by the processor, further configure the processor to:

receive information from the output detector representative of sensing information conveyed by the biotransmitter subsystem, and process the information in digital form to detect one or more of the following:

the second output property associated with the output molecule,

a concentration associated with the second output molecule,

the second output property associated with the second plurality of biosensors,

the second output property associated with the second plurality of stimulus molecules,

a concentration of the second plurality of biosensors, or

a concentration of the second plurality of stimulus molecules.

14 . The system of claim 13 , wherein activity of the plurality of biosensors is modulated using a first trigger, and activity of the second plurality of biosensors is modulated using a second trigger that is different from the first trigger, and

wherein the second output molecule or second output property is the same as the output molecule or second output property, and the second plurality of biosensors or plurality of biosensors is addressed based on a timing of when the first trigger or second trigger was applied to activate the plurality of biosensors or the second plurality of biosensors.

15 . An optogenetic communication method, comprising:

generating, using an output detector of an electronic receiver subsystem of an optogenetic communication system, information representative of sensing information conveyed by a biotransmitter subsystem of the optogenetic communication system,

wherein the optogenetic communication system comprises:

a biosensor subsystem comprising a plurality of biosensors;

the biotransmitter subsystem configured to produce an output molecule or alter an output property in response to the plurality of biosensors interacting with a plurality of stimulus molecules, the output property being associated with the output molecule, the plurality of biosensors, or the plurality of stimulus molecules; and

an electronic receiver subsystem comprising:

 an output detector,

 a memory, and

 a processor configured to execute instructions included on the memory;

receiving, using the processor, the information representative of sensing information conveyed by the biotransmitter subsystem; and

processing the information in digital form to detect one or more of the following:

the output property associated with the output molecule,

a concentration associated with the output molecule,

the output property associated with the plurality of biosensors,

the output property associated with the plurality of stimulus molecules,

a concentration of the plurality of biosensors, or

a concentration of the plurality of stimulus molecules.

16 . The method of claim 15 , wherein the output molecule comprises a light-emitting molecule.

17 . The method of claim 16 , wherein processing the information in digital form comprises:

performing, using the processor, a demodulation operation on an electrical signal corresponding to an intensity of the light produced by the light-emitting molecules.

18 . The method of claim 15 , wherein the output property comprises a pH level, or an electrical impedance.

19 . A non-transitory computer-readable medium containing computer executable instructions that, when executed by a processor, configure the processor to perform an optogenetic communication method, the method comprising:

generating, using an output detector of an electronic receiver subsystem of an optogenetic communication system, information representative of sensing information conveyed by a biotransmitter subsystem of the optogenetic communication system,

wherein the optogenetic communication system comprises:

a biosensor subsystem comprising a plurality of biosensors;

the biotransmitter subsystem configured to produce an output molecule or alter an output property in response to the plurality of biosensors interacting with a plurality of stimulus molecules, the output property being associated with the output molecule, the plurality of biosensors, or the plurality of stimulus molecules; and

an electronic receiver subsystem comprising:

 an output detector,

 a memory, and

 a processor configured to execute instructions included on the memory;

receiving, using the processor, the information representative of sensing information conveyed by the biotransmitter subsystem; and

processing the information in digital form to detect one or more of the following:

the output property associated with the output molecule,

a concentration associated with the output molecule,

the output property associated with the plurality of biosensors,

the output property associated with the plurality of stimulus molecules,

a concentration of the plurality of biosensors, or

a concentration of the plurality of stimulus molecules.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 29, 2021
From: KRISHNASWAMY, BHUVANA; MCCLEAN, MEGAN
To: WISCONSIN ALUMNI RESEARCH FOUNDATION
Reel/Frame 057957/0063 →
Continuity (2)
Provisional Application 63081853 · Sep 22, 2020
Related Publication 20220091040A1 · Mar 24, 2022
References Cited (79)
US 20100167263A1 · Groll · 2010 [cited by examiner]
US 20100291703A1 · Meng · 2010 [cited by examiner]
US 20210181146A1 · Stowell · 2021 [cited by examiner]
Adeniran, A., et al., “Yeast-based biosensors: design and applications,” FEMS Yeast Research (2015) 15:1-15. [cited by applicant]
Akyildiz, I. F., et al., “Moving forward with molecular communication: From theory to human health applications,” Proceedings of the IEEE (2019) 107(5):858-865. [cited by applicant]
An-Adirekkun, J. M., et al., “A yeast optogenetic toolkit (yOTK) for gene expression control in [cited by applicant]
Anderson, J. C., et al., “Environmentally controlled invasion of cancer cells by engineered bacteria,” J. Mol. Biol. (2006) 355:619-627. [cited by applicant]
Atakan, B., et al., “Single and multiple-access channel capacity in molecular nanonetworks,” Nano-Net (2009) 20:14-23. [cited by applicant]
Austin, C. M., “Dynamics of molecular communication in bacteria within microfluidic environments,” A Dissertation, Woodruff School of Mechanical Engineering, Georgia Institute of Technology (2016), 163 pages. [cited by applicant]
Benzinger, D., et al., “Pulsatile inputs achieve tunable attenuation of gene expression variability and graded multi-gene regulation,” Nat. Commun. (2018) 9:3521. [cited by applicant]
Boyden, E. S., et al., “A history of optogenetics: the development of tools for controlling brain circuits with light,” F1000 Biology Reports (2011) 3:1. [cited by applicant]
Bradley, R. W., et al., “Recognizing and engineering digital-like logic gates and switches in gene regulatory networks,” Curr. Opin. Microbiol. (2016) 33:74-82. [cited by applicant]
Bugaj, L. J., et al., “High-throughput multicolor optogenetics in microwell plates,” Nat. Protocols (2019) 14:2205-2228. [cited by applicant]
Chien, T., et al., “Advances in bacterial cancer therapies using synthetic biology,” Curr. Opin. Syst. Biol. (2017) 5:1-8. [cited by applicant]
Dai, B., et al., “Colour compound lenses for a portable fluorescence microscope,” Light: Science & Applications (2019) 8:75. [cited by applicant]
Darlington, A. P.S., et al., “Dynamic allocation of orthogonal ribosomes facilitates uncoupling of co-expressed genes,” Nat. Commun. (2018) 9:695. [cited by applicant]
Einolghozati, A., et al., “Decode and forward relaying in diffusion-based molecular communication between two populations of biological agents,” 2014 IEEE International Conference on Communications (2014), pp. 3975-3980. [cited by applicant]
Fang, Y., et al., “Symbol-by-symbol maximum likelihood detection for cooperative molecular communication,” IEEE Transactions on Communications (2019) 67(7):4885-4899. [cited by applicant]
Farsad, N., et al., “A comprehensive survey of recent advancements in molecular communication,” IEEE Commun. Surveys & Tutorials (2016) 18(3):1887-1919. [cited by applicant]
Farsad, N., et al., “Capacity limits of diffusion-based molecular timing channels with finite particle lifetime,” IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (2018) 4(2):88-106. [cited by applicant]
Ford, T. J., et al., “Synthetic biology expands chemical control of microorganisms,” Curr. Opin. Chem. Biol. (2015) 28:20-28. [cited by applicant]
Gerhardt, K. P., et al., “An open-hardware platform for optogenetics and photobiology,” Sci. Rep. (2016) 6:35363. [cited by applicant]
Gore, A. C., et al., “EDC-2: The endocrine society's second scientific statement on endocrine-disrupting chemicals,” Endocrine Reviews (2015) 36:E1-E150. [cited by applicant]
Grebenstein, L., et al., “Biological optical-to-chemical signal conversion interface: A small-scale modulator for molecular communications,” IEEE Transactions on NanoBioscience (2019) 18(1):31-42. [cited by applicant]
Guo, W., et al., “Molecular communications:Channel model and physical layer techniques,” IEEE Wireless Communications (2016) 23(4):120-127. [cited by applicant]
He, P., et al., “Improving reliability performance of diffusion-based molecular communication with adaptive threshold variation algorithm,” Int. J. Commun. Syst. (2016) 29:2669-2680. [cited by applicant]
Hiyama, S., et al., “Molecular communication: Harnessing biochemical materials to engineer biomimetic communication systems,” Nano Communication Networks (2010) 1:20-30. [cited by applicant]
Jones, K. A., et al., “Recent advances in developing and applying biosensors for synthetic biology,” Nano Futures (2019) 3:042002. [cited by applicant]
Kennedy, M. J., et al., “Rapid blue-light-mediated induction of protein interactions in living cells,” Nat. Methods (2010) 7(12):973-977. [cited by applicant]
Khalil, A. S., et al., “Synthetic biology:Applications come of age,” Nat. Rev. Genet. (2010) 11:367-379. [cited by applicant]
Kim, N.R., et al., “An experimentally validated channel model for molecular communication systems,” IEEE Access (2019) 7:81849-81858. [cited by applicant]
Kolar, K., et al., “OptoBase: A web platform for molecular optogenetics,” ACS Synth. Biol. (2018) 7:1825-1828. [cited by applicant]
Krishnaswamy, B., et al., “Time-elapse communication: Bacterial communication on a microfluidic chip,” IEEE Transactions on Communications (2013) 61(12):5139-5151. [cited by applicant]
Krishnaswamy, B., et al., “ADMA: Amplitude-division multiple access for bacterial communication networks,” IEEE Transactions on Molecular, Biological, and Multi-scale Communications (2017) 3(3):134-149. [cited by applicant]
Kuran, M. S., et al., “Modulation techniques for communication via diffusion in nanonetworks,” IEEE International Conference on Communications (2011), pp. 1-5. [cited by applicant]
Kuros, J. F., et al., Computer Networking, Pearson Education Inc. (1991) 6th Ed., 889 pages. [cited by applicant]
Lavan, D. A., et al., “Small-scale systems for in vivo drug delivery,” Nat. Biotechnol. (2003) 21(10):1184-1191. [cited by applicant]
Lin, X., et al., “Multiple advanced logic gates made of DNA-Ag nanocluster and the application for intelligent detection of pathogenic bacterial genes,” Chem. Sci. (2018) 9:1774. [cited by applicant]
Lio, P., et al., “Opportunistic routing through conjugation in bacteria communication nanonetwork,” Nano Communication Networks (2012) 3:36-45. [cited by applicant]
Liu, Z., et al., “Programming bacteria with light-sensors and applications in synthetic biology,” Front. Microbiol. (2018) 9:2692. [cited by applicant]
Loessner, M. J., et al., “Construction of luciferase reporter bacteriophage A511 ::luxAB for rapid and sensitive detection of viable listeria cells,” Applied and Environmental Microbiology (1996) 62(4):1133-1140. [cited by applicant]
Luo, X., et al., “Biofabrication of stratified biofilm mimics for observation and control of bacterial signaling,” Biomaterials (2012) 33:5136-5143. [cited by applicant]
Luo, X., et al., “Distal modulation of bacterial cell-cell signalling in a synthetic ecosystem using partitioned microfluidics,” Lab Chip (2015) 15:1842. [cited by applicant]
Mai, T. C., et al., “Event detection in molecular communication networks with anomalous diffusion,” IEEE Commun. Lett. (2017) 21(6):1249-1252. [cited by applicant]
Mansouri, M., et al., “Light-controlled mammalian cells and their therapeutic applications in synthetic biology,” Adv. Sci. (2019) 6:1800952. [cited by applicant]
Marchisio, M. A., et al., “Automatic design of digital synthetic gene circuits,” PLoS Comput. Biol. 7(2):e1001083. [cited by applicant]
Mcisaac, R. S., et al., “Fast-acting and nearly gratuitous induction of gene expression and protein depletion in [cited by applicant]
Melendez, J., et al., “Real-time optogenetic control of intracellular protein concentration in microbial cell cultures,” Integr. Biol. (2014) 6:366. [cited by applicant]
Metzger, D., et al., “The human oestrogen receptor functions in yeast,” Nature (1988) 334:31-36. [cited by applicant]
Miyamoto, T., et al., “Synthesizing biomolecule-based boolean logic gates,” ACS Synth. Biol. (2013) 2:72-82. [cited by applicant]
Molinari, S., et al., “A synthetic system for asymmetric cell division in [cited by applicant]
Moore, M. J., et al., “Addressing by beacon distances using molecular communication,” Nano Communication Networks (2011) 2:161-173. [cited by applicant]
Moser, F., et al., “Genetic sensor for strong methylating compounds,” ACS Synth. Biol. (2013) 2:614-624. [cited by applicant]
Mushnikov, N. V., et al., “Inducible asymmetric cell division and cell differentiation in a bacterium,” Nat. Chem. Biol. (2019) 15:925-931. [cited by applicant]
Nguyen, C., et al., “Detection of bacillus anthracis spores from environmental water using bioluminescent reporter phage,” J. Applied Microbiol. (2017) 123:1184-1193. [cited by applicant]
Pierobon, M., et al., “A physical end-to-end model for molecular communication in nanonetworks,” IEEE JJournal on Selected Areas in Communications (2010) 28(4):602-611. [cited by applicant]
Pierobon, M., et al., “Information capacity of diffusion-based molecular communication in nanonetworks,” Proceedings IEEE Infocom (2011) 506-510. [cited by applicant]
Pierobon, M., et al., “A systems-theoretic model of a biological circuit for molecular communication in nanonetworks,” Nano Commun. Networks (2014) 5:25-34. [cited by applicant]
Prindle, A., et al., “A sensing array of radically coupled genetic ‘biopixels’,” Nature (2012) 481:39-44. [cited by applicant]
Rajasarkka, J., et al., “Developing a compound-specific receptor for bisphenol A by directed evolution of human estrogen receptor α,” Biotechnol. Bioeng. (2011) 108:2526-2534. [cited by applicant]
Repina, N. A., et al., “At light speed: Advances in optogenetic systems for regulating cell signaling and behavior,” Annu. Rev. Chem. Biomol. Eng. (2017) 8:13-39. [cited by applicant]
Russell, J. J., et al., “Non-model model organisms,” BMC Biology (2017) 15:55. [cited by applicant]
Salinas, F., et al., “Optogenetic switches for light-controlled gene expression in yeast,” Appl. Microbiol. Biotechnol. (2017) 101:2629-2640. [cited by applicant]
Sanseverino, J., et al., “Screening of potentially hormonally active chemicals using bioluminescent yeast bioreporters,” Toxicological Sciences (2009) 107(1):122-134. [cited by applicant]
Shih, P.J., et al., “Channel codes for mitigating intersymbol interference in diffusion-based molecular communications,” IEEE Global Communications Conference (GLOBECOM) (2012) 4228-4232. [cited by applicant]
Shiizaki, K., et al., “Establishment of yeast reporter assay systems to detect ligands of thyroid hormone receptors α and β,” Toxicology in Vitro (2010) 24:638-644. [cited by applicant]
Siuti, P., et al., “Synthetic circuits integrating logic and memory in living cells,” Nat. Biotechnol. (2013) 31(5):448-453. [cited by applicant]
Slomovica, S., et al., “Synthetic biology devices for in vitro and in vivo diagnostics,” PNAS (2015) 112(47):14429-14435. [cited by applicant]
Snoek, T., et al., “Evolution-guided engineering of small-molecule biosensors,” Nucl. Acids Res. (2020) 48(1):e3, 14 pages. [cited by applicant]
Stewart, C. J., et al., “Design and implementation of an automated illuminating, culturing, and sampling system for microbial optogenetic applications,” J. Vis. Exp. (2017) 120:e54894. [cited by applicant]
Sweeney, K., et al., “Easy calibration of the light plate apparatus for optogenetic experiments,” MethodsX (2019) 6:1480-1488. [cited by applicant]
Tamsir, A., et al., “Robust multicellular computing using genetically encoded NOR gates and chemical ‘wires’,” Nature (2011) 469:212-215. [cited by applicant]
Trang, P. T. K., et al., “Bacterial bioassay for rapid and accurate analysis of arsenic in highly variable groundwater samples,” Environ. Sci. Technol. (2005) 39:7625-7630. [cited by applicant]
Van Der Meer, J. R., et al., “Where microbiology meets microengineering: design and applications of reporter bacteria,” Nat. Rev. Microbiol. (2010) 8:511-522. [cited by applicant]
Vasconcelos, M. M., et al., “A continuous-time decision-making model for bacterial growth via quorum sensing: theory and evidence,” NANOCOM '19: Proceedings of the Sixth Annual ACM International Conference on Nanoscale … [cited by applicant]
Xiang, Y., et al., “Scaling up genetic circuit design for cellular computing: advances and prospects,” Natural Computing (2018) 17:833-853. [cited by applicant]
Xu, T., et al., “High-throughput analysis of endocrine-disrupting compounds using BLYES and BLYAS bioluminescent yeast bioassays,” Meth. Mol. Biol. (2020) 2081:29-41. [cited by applicant]
Yan, Q., et al., “Challenges and advances for genetic engineering of non-model bacteria and uses in consolidated bioprocessing,” Front. Microbiol. (2017) 8:2060. [cited by applicant]
Zhang, K., et al., “Light-mediated kinetic control reveals the temporal effect of the Raf/MEK/ERK pathway in PC12 cell neurite outgrowth,” PLoS One (2014) 9(3): e92917. [cited by applicant]