ReviewMicroorganisms2025
Alternatives Integrating Omics Approaches for the Advancement of Human Skin Models: A Focus on Metagenomics, Metatranscriptomics, and Metaproteomics.
Review in Microorganisms, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- The human breast milk microbiome: a landscape review of its composition, origins, and impact on infant health.Archives of microbiology · 2026Review
- Emerging Therapeutic Approaches for Modulating the Intestinal Microbiota.Pharmaceutics · 2026Review
- Decoding host-microbiome interactions through integrative multi-omics and artificial intelligence: from biological mechanisms to predictive modelling.Frontiers in microbiomes · 2026Review
- Skin microbiome and cutaneous aging mechanisms and clinical implications.Frontiers in microbiology · 2026Review
- Metagenomics and its impact on environmental and therapeutic microbiology.Archives of microbiology · 2025Review
- The Human Archaeome: Commensals, Opportunists, or Emerging Pathogens?Pathogens (Basel, Switzerland) · 2025Review
- The skin microbiome: from historical ecology to therapeutic frontiers.Anais brasileiros de dermatologiaReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The human skin microbiota, a complex community of bacterial, fungal, and viral organisms, plays a crucial role in maintaining skin homeostasis and regulating host-pathogen interactions. Dysbiosis within this microbial ecosystem has been implicated in various dermatological conditions, including acne vulgaris, psoriasis, seborrheic dermatitis, and atopic dermatitis. This review, for the first time, provides recent advancements in all four layers of omic technologies-metagenomics, metatranscriptomics, metaproteomics, and metabolomics-offering comprehensive insights into microbial diversity, in the context of functional skin modeling. Thus, this review explores the application of these omic tools to in vitro skin models, providing an integrated framework for understanding the molecular mechanisms underlying skin-microbiota interactions in both healthy and pathological contexts. We highlight the importance of developing advanced in vitro skin models, including the integration of immune components and endothelial cells, to accurately replicate the cutaneous microenvironment. Moreover, we discuss the potential of these models to identify novel therapeutic targets, enabling the design of personalized treatments aimed at restoring microbial balance, reinforcing the skin barrier, and modulating inflammation. As the field progresses, the incorporation of multi-omic approaches into skin-microbiome research will be pivotal in unraveling the complex interactions between host and microbiota, ultimately advancing therapeutic strategies for skin-related diseases.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.