Evidence map›Paper›PMID 41556308›Full record

ArticleMicrobial biotechnology2026

Exploiting the Endogenous Type II-A CRISPR-Cas System for Functional Engineering of Probiotic Lacticaseibacillus rhamnosus GG.

Zifan Xie, Yong-Su Jin, Michael J Miller

Abstract read
In one paragraph

Article in Microbial biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Nutrient control enables metabolic reconstruction ofbioRxiv : the preprint server for biology · 2026
    Article
  4. Review
  5. Article
  6. Article
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

3 authors.

Zifan XieDepartment of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.
Yong-Su JinDepartment of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.
Michael J MillerDepartment of Food Science and Human Nutrition, University of Illinois Urbana-Champaign, Urbana, Illinois, USA.

Funding

University of Illinois at Urbana-Champaign
6 · The paper itself

Abstract

Lacticaseibacillus rhamnosus GG (LGG) is one of the most extensively studied probiotic strains, widely used in food and health applications. However, the absence of efficient, precise genome editing methods has limited its broader potential and functional versatility. Here, we present an endogenous type II-A CRISPR-Cas genome editing workflow for LGG designed for functional strain construction. Using a plasmid interference assay together with single-nucleotide substitutions, we confirm the precise PAM requirement as 5'-NGAAA-3'. We pair a synthetic sgRNA cassette with homology-directed repair donors to enable targeted deletions and insertions across multiple loci, achieving modest but practically relevant editing efficiencies (11.1-25.0% of recovered transformants) that support routine strain construction. Using this optimised and precise genome engineering method, we generated a β-glucuronidase (GUS)-expressing LGG strain for robust strain tracking within complex microbial communities. This work removes barriers to LGG engineering, expands the probiotic CRISPR toolkit, and provides broadly applicable strategies for designing next-generation probiotics with applications in food biotechnology and microbial therapeutics.

Indexed as

CRISPR-Cas SystemsGene EditingLacticaseibacillus rhamnosusProbioticsGenetic EngineeringGlucuronidasePlasmidsGlucuronidaseCRISPR‐Caslactic acid bacteriaLacticaseibacillus rhamnosusprobioticsynthetic biology

Identifiers

PMID41556308
PMCPMC12817194

What OpenQuestion holds

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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.