Evidence map›Paper›PMID 40212379›Full record

ArticleFrontiers in microbiology2025

High throughput construction of species characterized bacterial biobank for functional bacteria screening: demonstration with GABA-producing bacteria.

Yanci Qiu, Dingding Fan, Jianxin Wang, Xiaoxue Zhou, Xin Teng, Chitong Rao

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. 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

6 authors.

Yanci Qiu *Bluepha Co., Ltd., Shanghai, China.
Dingding Fan *Bluepha Co., Ltd., Shanghai, China.
Jianxin WangBluepha Co., Ltd., Shanghai, China.
Xiaoxue ZhouBluepha Co., Ltd., Shanghai, China.
Xin TengBluepha Co., Ltd., Shanghai, China.
Chitong RaoBluepha Co., Ltd., Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacteria and their metabolites exhibit remarkable diversity, offering substantial potential for industrial biotechnology. However, the low throughput for constructing and screening bacterial biobanks limits the exploration and utilization of this diversity. In this study, we developed a cost-effective, high-throughput platform for bacterial biobank construction and functional screening. We employed a double-ended barcoding strategy, enabling thousands of bacterial isolates to be pooled for simultaneous Nanopore sequencing of full-length 16S rDNA for species identification. This approach demonstrated 99% accuracy compared to Sanger sequencing while reducing per-sample costs to under 10%. Using this platform, we established a bacterial biobank comprising 15,337 bacterial isolates derived from fermented foods and infant feces collected across China. To identify functional bacteria within the biobank, we designed a versatile fluorescence-based biosensor system employing dual plasmids to decouple metabolite sensing from signal reporting. This modular biosensor framework can be readily adapted for detecting diverse metabolites. As a proof-of-concept, we screened 1,740 isolates and identified 46 with high γ-aminobutyric acid (GABA)-producing capacity, demonstrating potential for probiotic development. Together, our integrated bacterial identification and functional screening platform provides an efficient pipeline for the discovery of functional bacteria, advancing industrial biotechnology through synthetic biology.

Indexed as

barcodingbiosensorfunctional bacteriaGABAhigh-throughput screeningNanoporespecies-characterized bacterial biobank

Identifiers

PMID40212379
PMCPMC11984947

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Registered trials

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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.