Back

The mechanosensitive ion channel Piezo1 contributes to ultrasound neuromodulation

Zhu, J.; Xian, Q.; Hou, X.; Wong, K. F.; Zhu, T.; Chen, Z.; He, D.; Kala, S.; Jing, J.; Wu, Y.; Zhao, X.; Li, D.; Guo, J.; Qiu, Z.; Sun, L.

2023-01-08 neuroscience
10.1101/2023.01.07.523089 bioRxiv
Show abstract

Transcranial low-intensity ultrasound is a promising neuromodulation modality, with the advantages of non-invasiveness, deep penetration, and high spatiotemporal accuracy. However, the underlying biological mechanism of ultrasonic neuromodulation remains unclear, hindering the development of efficacious treatments. Here, the well-known Piezo1, was studied through a conditional knockout mouse model as a major molecule for ultrasound neuromodulation ex vivo and in vivo. We showed that Piezo1 knockout in the right motor cortex of mice significantly reduced ultrasound-induced neuronal calcium responses, limb movement and muscle EMG responses. We also detected higher Piezo1 in the central amygdala (CEA) which were found more sensitive to ultrasound stimulation than that of cortex. Knocking out the Piezo1 in CEA neurons showed a significant reduction of response under ultrasound stimulation while knocking out astrocytic Piezo1 showed no obvious changes in neuronal responses. Additionally, we excluded an auditory confound by monitoring auditory cortical activation and using smooth waveform ultrasound with randomized parameters to stimulate P1KO ipsilateral and contralateral regions of the same brain and recording evoked movement in the corresponding limb. Thus, we demonstrate that Piezo1 is functionally expressed in different brain regions, and that it is an important mediator of ultrasound neuromodulation in the brain, laying the ground for further mechanistic studies of ultrasound.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.