Closed-loop in situ isolation of deep-sea extremophiles through sensor-driven microenvironment preservation

Deep sea microorganisms remain largely inaccessible because existing sampling and cultivation methods fail to preserve native high-pressure microenvironments from seafloor to laboratory. Here we show a closed-loop cyber physical platform that maintains in situ deep-sea conditions through real-time sensing, digital twin control and robotic high-pressure manipulation to enable targeted isolation of extremophiles. The system integrates intelligent site selection, active pressure retention and multimodal vision–tactile feedback to automate colony recognition with 94.6% accuracy and perform compliant streaking and picking, enabling the recovery of deep-sea-adapted strains from cold seep environments. These results establish a sensor-driven framework for standardized exploration of the deep biosphere and provide a generalizable approach for isolating microorganisms from environments inaccessible to conventional methods. A closed-loop cyber physical platform that preserves native deep-sea microenvironments enables fully automated in situ cultivation and isolation of extremophiles through sensor-driven sampling, pressure retentive handling and robotic high-pressure manipulation.

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Publication Details

Journal
Nature Sensors
Published
2026-09-09
DOI
https://doi.org/10.1038/s44460-026-00128-x
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
0.00
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Closed-loop in situ isolation of deep-sea extremophiles through sensor-driven microenvironment preservation

Dapeng Zou, Nishi Yu, Chunlei Chen, Canrong Li et al.
Nature Sensors
Micro and Nano Robotics
article

Closed-loop in situ isolation of deep-sea extremophiles through sensor-driven microenvironment preservation

Dapeng Zou, Nishi Yu, Chunlei Chen, Canrong Li, Zhengguang Liu, Bingxu Hu, Minghui Shi, Liangyun Qin, Xuanyu Tao, Guang Yang, Jianzhen Liang, Jing‐Chun Feng, Kelei Zhu, Si Zhang, Nan Zhao, Zhen Zhang, Cun Li, Yajing Li, Zhifeng Yang, Xin Lin, Qixuan Wu, Renzeng Shi, Rui Lu, Yihan Shao, Chaoqi Li, Weiyu Yuan, Mengzhuo Zhu, Xi Yang, Junrong Zhai, Mingxin Wu, Li Tang, Weicong Liang, Qian Zhang, Jingnan Tian, Xiaokang Wang, Zhifeng Yang, Wentao Wang, Yi Wang, Yuhang Zhang, Hongyi Liu, Jinhua Li, Junjie Chen, Yue Zhu
article en

Abstract

Deep sea microorganisms remain largely inaccessible because existing sampling and cultivation methods fail to preserve native high-pressure microenvironments from seafloor to laboratory. Here we show a closed-loop cyber physical platform that maintains in situ deep-sea conditions through real-time sensing, digital twin control and robotic high-pressure manipulation to enable targeted isolation of extremophiles. The system integrates intelligent site selection, active pressure retention and multimodal vision–tactile feedback to automate colony recognition with 94.6% accuracy and perform compliant streaking and picking, enabling the recovery of deep-sea-adapted strains from cold seep environments. These results establish a sensor-driven framework for standardized exploration of the deep biosphere and provide a generalizable approach for isolating microorganisms from environments inaccessible to conventional methods. A closed-loop cyber physical platform that preserves native deep-sea microenvironments enables fully automated in situ cultivation and isolation of extremophiles through sensor-driven sampling, pressure retentive handling and robotic high-pressure manipulation.

Nature Sensors
Guangdong University of Technology (CN), Harbin Engineering University (CN), Northwestern Polytechnical University (CN), Chinese Academy of Sciences (CN), Hong Kong University of Science and Technology (HK), University of Manchester (GB), Guangdong Polytechnic of Science and Technology (CN), Institute of Oceanology (CN), South China Sea Institute Of Oceanology (CN), Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou) (CN), Institute of Geology and Geophysics (CN), Guangzhou Institute of Energy Conversion (CN), Guangdong Ocean University (CN)
Life below water
Openalex Percentile: Top 16%
Micro and Nano Robotics
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