Evidence map›Paper›PMID 41073418›Full record

ArticleNature communications2025

AI-powered high-throughput digital colony picker platform for sorting microbial strains by multi-modal phenotypes.

Zhidian Diao, Qiqun Peng, Sijun Luo, Lingyan Kan, Anle Ge, Wei Gao, Runxia Li, Weiwei Bao, Xixian Wang, Yuetong Ji and 3 more

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Zhidian Diao *Key Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Qiqun Peng *State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan, Hubei, China.ORCID http://orcid.org/0009-0004-3721-2311
Sijun LuoQingdao Single-Cell Biotech., Co., Ltd., Qingdao, China.
Lingyan KanKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Anle GeKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Wei GaoKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.
Runxia LiState Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan, Hubei, China.
Weiwei BaoState Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan, Hubei, China.ORCID http://orcid.org/0009-0001-0582-4952
Xixian WangKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China.ORCID http://orcid.org/0000-0003-4856-6516
Yuetong JiQingdao Single-Cell Biotech., Co., Ltd., Qingdao, China.
Jian XuKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China. xujian@qibebt.ac.cn.ORCID http://orcid.org/0000-0002-0548-8477
Shihui YangState Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan, Hubei, China. Shihui.Yang@hubu.edu.cn.ORCID http://orcid.org/0000-0002-9394-9148
Bo MaKey Laboratory of Photoelectric Conversion and Utilization of Solar Energy, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, Shandong, China. mabo@qibebt.ac.cn.ORCID http://orcid.org/0000-0002-8501-772X

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32030003National Natural Science Foundation of China (National Science Foundation of China) 32170103National Natural Science Foundation of China (National Science Foundation of China) 32370098National Natural Science Foundation of China (National Science Foundation of China) 32470087
6 · The paper itself

Abstract

Phenotype-based screening remains a major bottleneck in the development of microbial cell factories. Here, we present a Digital Colony Picker (DCP), an AI-powered platform for automated, high-throughput screening and export of microbial clones based on growth and metabolic phenotypes at single-cell resolution, without agar or physical contact. Using a microfluidic chip comprising 16,000 addressable picoliter-scale microchambers, individual cells are compartmentalized, dynamically monitored by AI-driven image analysis, and selectively exported via laser-induced bubble technique. Applied to Zymomonas mobilis, DCP enabled en masse screening and identified a mutant with 19.7% increased lactate production and 77.0% enhanced growth under 30 g/L lactate stress. This phenotype was linked to overexpression of ZMOp39x027, a canonical outer membrane autotransporter that promotes lactate transport and cell proliferation under stress. DCP provides a multi-modal phenotyping solution with spatiotemporal precision and scalable throughput, offering a generalizable strategy for accelerated strain engineering and functional gene discovery.

Indexed as

High-Throughput Screening AssaysZymomonasBacterial ProteinsLab-On-A-Chip DevicesLactic AcidPhenotypeBacterial ProteinsLactic Acid

Identifiers

PMID41073418
PMCPMC12514280

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.