Evidence map›Paper›PMID 42555388›Full record

ReviewFrontiers in cellular and infection microbiology2026

Harnessing the gut microbiome to combat tuberculosis: a technological and clinical review.

Weiguo Sun, Meng Xiao, Syed Luqman Ali, Chanyuan Jin, Asifullah Khan, Shakirullah, Ruizi Ni, Yajing An, Mingming Zhang, Yuan Tian and 3 more

Abstract readReview
In one paragraph

Review in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Weiguo Sun *Beijing Key Laboratory of Emergency Vaccine Development and Process Translation, Senior Department of Tuberculosis, Chinese PLA General Hospital, Beijing, China.
Meng Xiao *Computer Network Information Center, Chinese Academy of Sciences, Beijing, China.
Syed Luqman Ali *Department of Biochemistry, Abdul Wali Khan University Mardan, Mardan, KPK, Pakistan.
Chanyuan Jin *2nd Dental Center, Peking University School and Hospital of Stomatology, Beijing, China.
Asifullah KhanDepartment of Biochemistry, Abdul Wali Khan University Mardan, Mardan, KPK, Pakistan.
ShakirullahDepartment of Zoology, Abdul Wali Khan University Mardan, Mardan, KPK, Pakistan.
Ruizi NiBeijing Key Laboratory of Emergency Vaccine Development and Process Translation, Senior Department of Tuberculosis, Chinese PLA General Hospital, Beijing, China.
Yajing AnBeijing Key Laboratory of Emergency Vaccine Development and Process Translation, Senior Department of Tuberculosis, Chinese PLA General Hospital, Beijing, China.
Mingming ZhangBeijing Key Laboratory of Emergency Vaccine Development and Process Translation, Senior Department of Tuberculosis, Chinese PLA General Hospital, Beijing, China.
Yuan TianBeijing Key Laboratory of Emergency Vaccine Development and Process Translation, Senior Department of Tuberculosis, Chinese PLA General Hospital, Beijing, China.
Shradha KaushikDepartment of Biomedical Sciences, University of Windsor, Windsor, ON, Canada.
Yuhang ZhangInstitute of Clinical Pharmacology, Peking University First Hospital, Beijing, China.
Wenping GongBeijing Key Laboratory of Emergency Vaccine Development and Process Translation, Senior Department of Tuberculosis, Chinese PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tuberculosis (TB), especially multidrug-resistant and extensively drug-resistant strains, remains a severe global health threat. Advances in high-throughput sequencing, omics technologies and artificial intelligence have revealed the critical involvement of the gut microbiome (GM) in TB pathogenesis, diagnosis and treatment via the gut-lung axis. The GM modulates host immunity and metabolism; TB patients typically show reduced microbial diversity and enriched pro-inflammatory taxa closely linked to disease severity and treatment responses. Omics research has identified promising biomarkers and pathways for early diagnosis and personalized management, while artificial intelligence improves diagnostic accuracy and treatment outcome prediction. GM-targeted interventions, including probiotics, dietary adjustment and fecal microbiota transplantation, can enhance therapeutic efficacy and relieve adverse drug reactions. Current limitations include insufficient validation of the gut-lung axis' causal mechanisms, lagged clinical translation of biomarkers, biases and errors in diagnosis and prediction, data privacy and security concerns, gaps in intervention research, and poor accessibility of related technologies in resource-scarce medical regions. Future studies need rigorous causal analyses, real-time monitoring tools and large-scale multicenter trials to validate microbiome-based strategies. This review highlights the translational potential of GM interventions to optimize personalized TB prevention, diagnosis and treatment and improve clinical outcomes.

Indexed as

Gastrointestinal MicrobiomeTuberculosisArtificial IntelligenceBiomarkersFecal Microbiota TransplantationHumansMultiomicsProbioticsBiomarkersartificial intelligence (AI)gut microbiome (GM)metabolomicsnext-generation sequencing (NGS)proteomicstuberculosis (TB)

Identifiers

PMID42555388
PMCPMC13328407

What Socratic 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 Socratic graph.