The AI-RACS system, developed by Chinese Academy of Sciences researchers, automates the isolation of aluminum-tolerant microorganisms, advancing microbial research through high-throughput workflows.
Researchers from the Single-Cell Center at the Qingdao Institute of Bioenergy and Bioprocess Technology, part of the Chinese Academy of Sciences (CAS), in collaboration with their partners, have developed an artificial intelligence-assisted Raman-activated cell sorting (AI-RACS) system. This cutting-edge system automates the isolation and functional analysis of aluminum-tolerant microorganisms (ATMs) from acidic soil, representing a significant leap from manual, labor-intensive methods to high-throughput automated workflows.
This study was published in Analytical Chemistry.
Microbiomes—dynamic communities of microorganisms—offer untapped potential for advancing biotechnology and environmental sustainability. However, their complexity poses challenges for the isolation and detailed study of specific functional microbes.
To address this issue, the AI-RACS system integrates optical tweezers, single-cell Raman spectroscopy (SCRS), and artificial intelligence. This integration enables the precise identification, sorting, and collection of single cells, transforming microbial single-cell research from low-throughput manual operations to high-throughput automated workflows.
Breakthrough in ATM Isolation
The researchers utilized the RACS-Seq/Culture instrument to identify and sort ATMs from acidic soil samples. By employing SCRS to assess cellular metabolic activity under aluminum stress, the researchers successfully identified and isolated 13 aluminum-tolerant strains, including Burkholderia spp., Rhodanobacter spp., and Staphylococcus aureus. These strains exhibited higher metabolic activity compared to those identified through traditional cultivation methods. The use of SCRS as a quantitative biomarker allowed the researchers to pinpoint and categorize metabolically active microbes with unmatched precision.
“AI-RACS allows us to uncover how ATMs thrive in toxic red soils, providing new perspectives on microbial survival and soil health restoration,” said Prof. Yuting Liang, corresponding author of the study, from the Institute of Soil Science of the CAS.
“Our goal is to develop a system that automates single-cell analysis while improving precision and throughput needed for studying complex microbial communities,” said Dr. Zhidian Diao, first author of the study, from the Single-Cell Center. “This system enables researchers to explore microbiomes under near in situ conditions with high efficiency.”
The AI-RACS system opens up new possibilities in fields such as resource recovery, environmental management, and industrial biotechnology.
Reference: “Artificial Intelligence-Assisted Automatic Raman-Activated Cell Sorting (AI-RACS) System for Mining Specific Functional Microorganisms in the Microbiome” by Zhidian Diao, Xiaoyan Jing, Xibao Hou, Yu Meng, Jiaping Zhang, Yongshun Wang, Yuetong Ji, Anle Ge, Xixian Wang, Yuting Liang, Jian Xu and Bo Ma, 11 November 2024, Analytical Chemistry.
DOI: 10.1021/acs.analchem.4c03213
The study was funded by the National Natural Science Foundation of China and the Chinese Academy of Sciences.
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