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Real-time, cross-modal genotype mapping of free-moving <i>Drosophila</i> larvae via simultaneous mechano-electrophysiological recording.

Overview

Authors: Kairu Dong1,2,3, Hao Song2, Qianhui Zhao4,5,6, Zhiying Song1,7,8, Fu Lv9, Siouwen Wan2, Tianyu Zheng1,3, Yunlong Fan2, Wen-Che Liu2, Shaomin Zhang1, Yongjun Wu9, Yuhui Huang9, Jizhou Song10, Zhefeng Gong4,5,6, Nenggan Zheng1,7,8, Kewang Nan2
ORCID iDs: Kairu Dong, Hao Song, Qianhui Zhao, Zhiying Song, Fu Lv, Yunlong Fan, Shaomin Zhang, Yongjun Wu, Yuhui Huang, Jizhou Song, Zhefeng Gong, Nenggan Zheng, Kewang Nan
  1. Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou 310027, China
  2. State Key Laboratory of Advanced Drug Delivery and Release Systems, School of Pharmacy, Zhejiang University, Hangzhou 310058, China
  3. College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China
  4. NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
  5. Department of Neurology of the Fourth Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China
  6. Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China
  7. State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou 310058, China
  8. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
  9. School of Materials Science and Engineering, Zhejiang University, Hangzhou 310058, China
  10. Department of Engineering Mechanics, Zhejiang University, Hangzhou 310027, China
Institutions: Zhejiang University (China)
Journal: Science advances, volume 12, issue 38, article eaef7492
Dates: received 2 February 2026; accepted 12 August 2026; published online 18 September 2026; in print September 2026
Type: Research article · Language: English
License: CC BY
Identifiers: DOI 10.1126/sciadv.aef7492 · PMID 42758840 · PMCID PMC13588200 · OpenAlex W7213532110
Open access: gold, a free copy (OpenAlex)
Status: data only (how the code is found and verified)
Categories: genetics / omics (modality), drosophila (organism)
Methods: Spectral & time-frequency, Machine learning, Single-unit activity, calcium imaging
MeSH: Drosophila*, Drosophila melanogaster*, Electrophysiological Phenomena*, Larva*, Animals, Genotype, Locomotion, Phenotype (* major topic)
Journal subjects: Physical and Materials Sciences, Life Sciences, Physical Sciences
Topic: Advanced Sensor and Energy Harvesting Materials (Biomedical Engineering, Engineering), according to OpenAlex
Funding: National Natural Science Foundation of China (62504200, 12225209, T2293723); Natural Science Foundation of Zhejiang Province (LZ25F040002, LZ24F020003)
Citations: not cited yet (Europe PMC); 75 references in the paper

Abstract

Drosophila larvae provide a powerful model for interrogating genes associated with human muscle and neurological disorders; however, existing genotyping and phenotyping approaches remain low-throughput and often rely on destructive, invasive, or toxic procedures. Here, we present a scalable bioelectronic platform that enables real-time, simultaneous mechano-electrophysiological recording from freely moving Drosophila larvae in an open three-dimensional (3D) space, allowing high-throughput cross-modal genotype mapping (CMGM). The system integrates conductive and piezoelectric microneedle electrodes into a flexible sensory array that achieves stable, long-term signal acquisition during unrestricted and complex 3D locomotion. By coupling dual-modal signal acquisition with machine-learning-assisted classification, we directly identify muscle defects in unlabeled RNAi-knockdown larvae within 30 minutes, without invasive manipulation or time-consuming sample preparation. Incorporation of both electrophysiological and mechanical waveform features improves overall classification accuracy to 96%, outperforming single-modality approaches. This non-destructive, high-throughput CMGM strategy establishes a generalizable framework for bridging genotype and phenotype in intact, freely behaving organisms, with broad implications for functional genetics and disease modeling.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

The paper links to its data and to no code of its authors: see the Data section.

The paper's code and data availability statement is in the Data section.

Tracing map

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Data

Datasets cited

Data, code, and materials availability

The raw data is available at https://doi.org/10.5061/dryad.s1rn8pkpr. All data and code needed to evaluate and reproduce the results in the paper are present in the paper and/or the Supplementary Materials. This study did not generate new materials.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 27 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 16 authors, 8 MeSH terms, 2 funders, 63 references.

Cite

This paper

Dong, K., Song, H., Zhao, Q., Song, Z., Lv, F., Wan, S., Zheng, T., Fan, Y., Liu, W.-C., Zhang, S., Wu, Y., Huang, Y., Song, J., Gong, Z., Zheng, N., & Nan, K. (2026). Real-time, cross-modal genotype mapping of free-moving <i>Drosophila</i> larvae via simultaneous mechano-electrophysiological recording. Science advances, 12(38), eaef7492. https://doi.org/10.1126/sciadv.aef7492

BibTeX

@article{dong2026real,
author = {Dong, Kairu and Song, Hao and Zhao, Qianhui and Song, Zhiying and Lv, Fu and Wan, Siouwen and Zheng, Tianyu and Fan, Yunlong and Liu, Wen-Che and Zhang, Shaomin and Wu, Yongjun and Huang, Yuhui and Song, Jizhou and Gong, Zhefeng and Zheng, Nenggan and Nan, Kewang},
title = {{Real-time, cross-modal genotype mapping of free-moving \<i\>Drosophila\</i\> larvae via simultaneous mechano-electrophysiological recording}},
journal = {Science advances},
year = {2026},
month = sep,
volume = {12},
number = {38},
pages = {eaef7492},
publisher = {American Association for the Advancement of Science},
issn = {2375-2548},
doi = {10.1126/sciadv.aef7492},
url = {https://doi.org/10.1126/sciadv.aef7492},
pmid = {42758840},
pmcid = {PMC13588200}
}

RIS

TY - JOUR
AU - Dong, Kairu
AU - Song, Hao
AU - Zhao, Qianhui
AU - Song, Zhiying
AU - Lv, Fu
AU - Wan, Siouwen
AU - Zheng, Tianyu
AU - Fan, Yunlong
AU - Liu, Wen-Che
AU - Zhang, Shaomin
AU - Wu, Yongjun
AU - Huang, Yuhui
AU - Song, Jizhou
AU - Gong, Zhefeng
AU - Zheng, Nenggan
AU - Nan, Kewang
TI - Real-time, cross-modal genotype mapping of free-moving <i>Drosophila</i> larvae via simultaneous mechano-electrophysiological recording
T2 - Science advances
J2 - Sci Adv
PY - 2026
DA - 2026/09/18
VL - 12
IS - 38
SP - eaef7492
SN - 2375-2548
PB - American Association for the Advancement of Science
DO - 10.1126/sciadv.aef7492
UR - https://doi.org/10.1126/sciadv.aef7492
LA - en
ER -

CSL-JSON

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