Peripheral blood microbiome signature and Mycobacterium tuberculosis-derived rsRNA as diagnostic biomarkers for tuberculosis in human
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI Uniform resource identifier for web resources.
Authors
Gu W, Huang Z, Fan Y, Li T, Yu X, Chen Z, Hu Y, Li A, Zhang F, Fu Y
Journal
Journal of translational medicine
Year
2025
Keywords:
Biomarker, Blood, Diagnosis, Microbiome, Tuberculosis, rsRNA
BACKGROUND: Tuberculosis (TB) is a major global health issue. Early diagnosis of TB is still a challenge. Studies are seeking non-sputum biomarker-based TB test. Emerging evidence indicates potential significance of blood microbiome signatures for diseases. However, blood microbiome RNA profiles are unknown in TB. We aimed to characterize the blood microbiome of TB patients and identify Mycobacterium tuberculosis (Mtb) genome-derived small RNA molecules to serve as diagnostic biomarkers for TB. METHODS: RNA sequencing data of the blood from TB patients and healthy controls were retrieved from the NCBI-SRA database for analyzing the blood microbiome and identifying rRNA-derived small RNA (rsRNA) of Mtb. Small RNA-seq was performed on plasma exosomes from TB patients and healthy controls. The levels of the candidate Mtb rsRNAs were determined by real-time quantitative reverse transcription PCR (RT-qPCR) on plasma from a separate cohort of 73 TB patients and 62 healthy controls. RESULTS: The blood microbiome of TB patients consisted of RNA signals from bacteria, fungi, archaea, and viruses, with bacteria accounting for more than 97% of the total. Reduced blood microbial diversity and abundance of 6 Mycobacterium-associated bacterial genera, including Mycobacterium, Priestia, Nocardioides, Agrobacterium, Bradyrhizobium, and Escherichia, were significantly altered in the blood of TB patients. A diagnostic model for TB based on the 6 genera achieved an area under the curve (AUC) of 0.8945. rsRNAs mapped to the Mtb genome were identified from blood and plasma exosomes of TB patients. RT-qPCR results showed that 2 Mtb-derived rsRNAs, 16 S-L1 and 16 S-L2, could be used as diagnostic biomarkers to differentiate TB patients from healthy controls, with a high co-diagnostic efficacy (AUC = 0.7197). CONCLUSIONS: A panel of blood microbiome signatures and Mtb-derived rsRNAs can serve as blood biomarkers for TB diagnosis.
Experiment 1
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Blood Portion of blood,Vertebrate blood,Whole blood,Blood,blood
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Pulmonary tuberculosis lung TB,lung tuberculosis,pulmonary TB,pulmonary tuberculosis,Tuberculosis, Pulmonary,Pulmonary tuberculosis
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy controls
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Active pulmonary tuberculosis
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Culture-confirmed pulmonary tuberculosis (PTB)
- Group 0 sample size Number of subjects in the control (unexposed) group
- 62
- Group 1 sample size Number of subjects in the case (exposed) group
- 73
- Antibiotics exclusion Number of days without antibiotics usage (if applicable) and other antibiotics-related criteria used to exclude participants (if any)
- No prebiotics, or antibiotics one month before the enrollment.
Lab analysis
- Sequencing type
- PCR
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- RT-qPCR
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- LEfSe
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
- Matched on Factors on which subjects have been matched on in a case-control study
- age, sex
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- decreased
Signature 1
Source: Figure 1A and B
Description: (A) Significantly differential taxa in terms of relative abundance (LDA score of ≥ 2) between TB and healthy control groups. (B) Significantly different taxa in the cladogram according to a LDA score of ≥ 2 (each circle represents phylogenetic levels from phylum to genus [inside to outside], and each diameter is proportional to the taxon’s abundance).
Abundance in Group 1: increased abundance in Active pulmonary tuberculosis
Revision editor(s): Nuerteye
Signature 2
Source: Figure 1A and B
Description: (A) Significantly differential taxa in terms of relative abundance (LDA score of ≥ 2) between TB and healthy control groups. (B) Significantly different taxa in the cladogram according to a LDA score of ≥ 2 (each circle represents phylogenetic levels from phylum to genus [inside to outside], and each diameter is proportional to the taxon’s abundance).
Abundance in Group 1: decreased abundance in Active pulmonary tuberculosis
Revision editor(s): Nuerteye
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