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Epineural optogenetic activation of nociceptors initiates and amplifies inflammation

Nature Biotechnology volume 39, pages 179–185 (2021)Cite this article

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Abstract

Activation of nociceptor sensory neurons by noxious stimuli both triggers pain and increases capillary permeability and blood flow to produce neurogenic inflammation1,2, but whether nociceptors also interact with the immune system remains poorly understood. Here we report a neurotechnology for selective epineural optogenetic neuromodulation of nociceptors and demonstrate that nociceptor activation drives both protective pain behavior and inflammation. The wireless optoelectronic system consists of sub-millimeter-scale light-emitting diodes embedded in a soft, circumneural sciatic nerve implant, powered and driven by a miniaturized head-mounted control unit. Photostimulation of axons in freely moving mice that express channelrhodopsin only in nociceptors resulted in behaviors characteristic of pain, reflecting orthodromic input to the spinal cord. It also led to immune reactions in the skin in the absence of inflammation and potentiation of established inflammation, a consequence of the antidromic activation of nociceptor peripheral terminals. These results reveal a link between nociceptors and immune cells, which might have implications for the treatment of inflammation.

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Fig. 1: A wireless optoelectronic system for epineural photostimulation of TRPV1-lineage neurons.
Fig. 2: Characterization of the soft micro-LED array and bio-integration.
Fig. 3: Remote, epineural optogenetic activation of TRPV1-lineage neurons in freely behaving mice.
Fig. 4: Recurrent optogenetic activation of TRPV1-Cre+ neurons produces immune changes.

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Raw data that support the findings of this study will be made available upon reasonable request to the corresponding authors. Source data are provided with this paper.

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Acknowledgements

The authors thank N. Andrews and L. Barrett for technical assistance, G. Courtine and his team (G-Lab, EPFL) for their advice on the surgical procedure and M. Stoeckel, A. Guillet and V. Ruhaut (Neuronal Microsystems Platform, Wyss Center) for help and advice on microfabrication. Further thanks go to T. Kleier for PCB assembly and device measurement support and M. Zahner for his help with antenna characterization. For funding, we would like to acknowledge a Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (109372/Z/15/Z, to L.E.B.), the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement (754354, to O.A.), the Bertarelli Foundation (to S.P.L. and C.J.W.), the Swiss National Science Foundation (BSCGI0_1578000, to S.P.L.) and the National Institutes of Health (R35NS105076, to C.J.W.).

Author information

Author notes

  1. These authors contributed equally: Frédéric Michoud, Corey Seehus, Philipp Schönle, Qiuting Huang, Clifford J. Woolf, Stéphanie P. Lacour.

Authors and Affiliations

  1. Laboratory for Soft Bioelectronics Interface, Institute of Microengineering, Institute of Bioengineering, Centre for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland

    Frédéric Michoud, Ivan Furfaro, Outman Akouissi, Katia Galan & Stéphanie P. Lacour

  2. Department of Neurobiology, Harvard Medical School, Boston, MA, USA

    Frédéric Michoud, Corey Seehus, Daniel Taub, Zihe Zhang, Aakanksha Jain, Rachel Moon, Benjamin Doyle, Michael Tetreault & Clifford J. Woolf

  3. F.M. Kirby Neurobiology Center, Boston Children’s Hospital, Boston, MA, USA

    Frédéric Michoud, Corey Seehus, Daniel Taub, Zihe Zhang, Aakanksha Jain, Rachel Moon, Benjamin Doyle, Michael Tetreault & Clifford J. Woolf

  4. Integrated Systems Laboratory, Department of Information Technology and Electrical Engineering, Swiss Institute of Technology Zurich (ETHZ), Zurich, Switzerland

    Philipp Schönle, Noé Brun, Pascale Meier & Qiuting Huang

  5. Département de Pharmacologie et Physiologie, Faculté de Médecine, Université de Montréal, Montreal, Quebec, Canada

    Sébastien Talbot

  6. Wolfson Institute for Biomedical Research, University College London, London, UK

    Liam E. Browne

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Contributions

F.M., C.S., P.S., Q.H., C.J.W. and S.P.L. contributed equally to this work. F.M., C.S., S.T., S.P.L. and C.J.W. designed the study and experiments. F.M. developed, fabricated and implanted the optoelectronic devices. C.S., F.M., D.T. and A.J. designed, performed and analyzed data from the neuroimmune experiments. P.S., N.B., P.M. and Q.H. developed the wireless LED-driving unit: P.S. designed the ASIC; N.B. and P.S. designed the PCB, manufactured the devices and performed the measurements; and the Android application and the BLE SoC were programmed by P.M. and N.B., respectively. F.M. and I.F. developed the mechanical and optical characterization setups. O.A. developed the thermal FEM. R.M., M.T. and B.D. assisted during surgery and collected and analyzed behavioral data. K.G. performed histology for biocompatibility. L.E.B. established the transgenic mouse line and advised on the control of the acquisition system. F.M., C.S., P.S., Q.H., C.J.W. and S.P.L. wrote and edited the manuscript.

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Correspondence to Qiuting Huang, Clifford J. Woolf or Stéphanie P. Lacour.

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Extended data

Extended Data Fig. 1 Wireless micro-LED-driving unit preparation.

a, Fully assembled PCB including additional ‘wings’ for access to various signals during device firmware development and for the initial flashing of the program code onto the device. After initial flashing and thorough testing, the ‘wings’ are cut and antenna and battery are attached and soldered. b, The final device measures 8.0 x 11.0 x 5.3 mm3 and weighs 0.85 g – 1.1g after encapsulation in silicone. c, The charging station is used for turning on/off the units – a design choice by which the wireless units can be fully encapsulated and be without any mechanical components (except the connector). Multiple stations can be interconnected to each other such that a single USB port can be used for the charging of many micro-LED driving units. d, Android application screen in experiment mode and overview on the configuration ranges. Each issued current pulse is monitored, that is, the wireless unit checks if the set current is actually reached and transmits this feedback to the tablet/smartphone. e, Android application screen in maximum-current test mode and overview on the configuration ranges. This operation mode enables the user to quickly determine the condition of a micro-LED implant: A sequence of short current pulses (too short to evoke an optogenetic stimulation) is emitted to determine the maximum current that can be achieved.

Extended Data Fig. 2 Antenna design and characterization.

a, Custom antenna layout with dimensions. The antenna is encapsulated within two layers of silicone prior to PCB soldering. b, Device dummy for return loss (S11) measurements. c, Measurement setup in the anechoic chamber. The device is mounted on a turntable. d, Radiation pattern characterization with a battery-operated device dummy constantly emitting a known-power carrier. Drawn lines represent measurements at center frequency (2440 MHz) while the shades cover the full BLE bandwidth (further measurements at 2402, 2430 and 2480 MHz).

Source data

Extended Data Fig. 3 Wireless micro-LED-driving unit performances.

a, Measurement of micro-LED array current during photostimulation pulse train (2 Hz, 10 mA, 10 ms pulse duration) as typically used in the in vivo experiments. b, Micro-LED current pulses emitted during a linear, ultra-low duty-cycle (100 ppm) maximum current search run. Short (20-100 µs) pulses at a low frequency (2 Hz) are used to avoid ChR2 activation during the test. The system delivers up to a 35 mA maximum current to the micro-LEDs. c, Measured overall power consumption of the wireless LED driving unit in various operation states. d, Battery lifetime measurement for a device in advertising state that is the device is turned on, however not connected to any tablet or smartphone and does not drive any micro-LED arrays. BLE connection will reduce lifetime by ca. 10%.

Source data

Extended Data Fig. 4 Microfabrication of the flexible micro-LED array to target activation of ChR2 in vivo.

a–c, Schematic illustration of the microfabrication process. Patterning of a Ti/Au film on a polyimide substrate (a). Polyimide superstrate covering of the film followed by patterning of the polyimide stack (b). Encapsulation in PDMS and subsequent patterning of the silicone layer (c). d, Schematic cross-sections of the interconnects and micro-LED site of integration. e–g, Illustrations of the micro-LED integration process. Printing of soldering paste on the interconnect pads followed by precise placement of the micro-LED (e). The reflow of the paste ensures mechanical and electrical interfacing. Printing of polyisobuthylene (PIB) on the micro-LED surface (f). PDMS encapsulation and release from the silicon carrier (g). h–j, Representative optical micrographs, such as solder paste printing (h), micro-LED deposition (i) and activation (j). Scale bar: 250 µm. k, Relative intensity associated with micro-LED emission spectrum, or spectral flux, and ChR2 normalized response spectrum. l, Relative changes in voltage for devices placed in 67 °C saline depending on micro-LED encapsulation material. Arrays only encapsulated with PDMS fail after day 7. n = 3 devices per group; mean ± s.d.

Source data

Extended Data Fig. 5 Illustration of surgical procedures for implanting the micro-LED array.

a, Under anesthesia and using aseptic technique, a craniotomy is performed and three micro-screws are fixed on the skull. b, Following a skin incision at the thigh level, implant wires are threaded subcutaneously. Suture threads are adjusted on the implant anchoring points. c, The micro-LED implant is placed transversally to the sciatic nerve and secured in position with the suture threads. d, Muscles are closed with sutures and the implant subcutaneous connector is secured at the vicinity. e, The implant is tested intraoperatively with a short activation of the micro-LEDs. f, Photograph of 3 mice carrying a wireless optoelectronic system.

Extended Data Fig. 6 Simulation of optoelectronic-induced temperature change in silico.

a, Elements and their relative 3D geometry used to model the appropriate heat transfer. The micro-LED array is placed epineurally, distributing equally 4 micro-LEDs or heat sources on the sciatic nerve. b, Thermodynamic parameters of the elements used in the thermal model. c, Temperature changes predicted by the 3D model, presented in cross and longitudinal sections. For visualization, the simulated photostimulation parameters (100 mW/mm2, 10% activation duty cycle) exceed the ones used in the in vivo experiments. d, Distribution of optoelectronic-induced temperature change across the different elements as a function of photostimulation irradiance. e, Maximum temperature increment at the interface between inner nerve and epineurium as a function of irradiance and micro-LED activation duty cycle.

Source data

Extended Data Fig. 7 Effects of micro-LED array implantation or sham surgery on animal behaviour.

a, Elements and their relative 3D geometry used to model the appropriate heat transfer. The micro-LED array is placed epineurally, distributing equally 4 micro-LEDs or heat sources on the sciatic nerve. b, Thermodynamic parameters of the elements used in the thermal model. c, Temperature changes predicted by the 3D model, presented in cross and longitudinal sections. For visualization, the simulated photostimulation parameters (100 mW/mm2, 10% activation duty cycle) exceed the ones used in the in vivo experiments. d, Distribution of optoelectronic-induced temperature change across the different elements as a function of photostimulation irradiance. e, Maximum temperature increment at the interface between inner nerve and epineurium as a function of irradiance and micro-LED activation duty cycle.

Source data

Extended Data Fig. 8 Flow cytometric data extracted from the ipsilateral hindpaw skin with respect to the micro-LED array location.

Pseudo-colorized dot plots showing myeloid (CD45+Thy1.2-) and lymphoid (CD45+Thy1.2+) cell populations depending on experimental protocol (± CFA and ± Stim). Population frequencies of the cells in the boxed regions are shown.

Extended Data Fig. 9 Optogenetic stimulation of TRPV1-Cre–/–::ChR2+/+ mice does not result in cell mobilization in innervated hind paw skin.

Major immune cell population numbers as assessed by flow cytometry. n = 5 animals per group; two-sided unpaired t-test. Symbols represent individual mice analyzed independently. The box plots display the median and interquartile range, ‘+’ denotes the mean, and the extending whiskers, the largest and lowest observations.

Source data

Extended Data Fig. 10 Injection of CFA in nociceptor ablated animal paw skin does not result in changes in immune cell numbers.

TRPV1-Cre+/+::DTA+/+ mice were injected with 3μl CFA in left hind paw, and immune cell population numbers were assessed by flow cytometry 3 days later. n = 3 animals per group; two-sided unpaired t-test. All data represented as mean ± s.e.m.

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Michoud, F., Seehus, C., Schönle, P. et al. Epineural optogenetic activation of nociceptors initiates and amplifies inflammation. Nat Biotechnol 39, 179–185 (2021). https://doi.org/10.1038/s41587-020-0673-2

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