Evidence map›Paper›PMID 41675162›Full record

ReviewiMetaOmics2025

Skin microbiome engineering: Challenges and opportunities in skin diseases treatment.

Yiang Lyu, Juntao Shen, You Che, Lei Dai

Abstract readReview
In one paragraph

Review in iMetaOmics, 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. Review
  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

4 authors.

Yiang LyuCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China.ORCID 0009-0005-7412-7543
Juntao ShenCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China.ORCID 0009-0009-7505-789X
You CheHKU-Pasteur Research Pole, School of Public Health, Li Ka Shing Faculty of Medicine The University of Hong Kong China.
Lei DaiCAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The skin microbiome, consisting of a vast array of microorganisms, is essential for human skin health, aiding in barrier protection, immune regulation, wound repair, and defense against pathogens. Disruptions in this microbial balance are closely linked to the onset and worsening of various skin disorders. This review evaluates the potential of skin microbiome engineering as a therapeutic strategy for treating skin diseases. We discuss nontargeted approaches like probiotics and fecal microbiota transplantation that aim to reshape the microbial community, as well as targeted methods such as phage therapy, phage lysins, and engineered bacteria, which specifically modulate microbial populations or influence the skin environment. These approaches open new avenues for personalized dermatological treatments. Despite significant progress, challenges remain in the clinical translation of microbiome-based therapies. Safety, standardization, regulatory approval, and long-term ecological stability must be addressed to ensure efficacy and reproducibility in clinical settings, underscoring the critical need for further research in their dermatological applications.

Indexed as

immune modulationmicrobiome engineeringskin barriertargeted therapies

Identifiers

PMID41675162
PMCPMC12806513

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.