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Two Small Extracellular Vesicle sRNAs Derived From Mycobacterium tuberculosis Serve as Diagnostic Biomarkers for Active Pulmonary Tuberculosis.

ABSTRACT: The rapid diagnosis of tuberculosis (TB) is of great significance for the control and treatment of TB. However, TB remains a major healthy, social, and economic burden worldwide because of the lack of ideal diagnostic biomarkers. Mycobacterium tuberculosis (M. tuberculosis)-encoded small RNA (sRNA) is a class of regulation small RNA. Several studies have identified M. tuberculosis encoded-sRNAs in the serum/plasm of M. tuberculosis-infected patients. Small extracellular vesicles are small membrane vesicles secreted by many cell types during physiological and pathological conditions. Recent evidence has indicated that most of the nucleic acids in the serum/plasma are packaged in the small extracellular vesicles and could serve as ideal diagnostic biomarkers. In this study, we attempted a novel approach for TB diagnosis: targeting small extracellular vesicles M. tuberculosis encoded sRNA (sRNA) by qRT-PCR. The results showed that M. tuberculosis-encoded ASdes and MTB-miR5 only existed in tuberculosis patients and have the potential to serve as a sensitive and accurate methodology for TB diagnosis.

SUBMITTER: Lu G

PROVIDER: S-EPMC8082067 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Two Small Extracellular Vesicle sRNAs Derived From Mycobacterium tuberculosis Serve as Diagnostic Biomarkers for Active Pulmonary Tuberculosis.

Lu Geng G Jiang XinRui X Wu Anni A Zhou Jiawei J Liu Hengjun H He Fei F Zhang Qiuling Q Zen Ke K Gu Shuangshuang S Wang Jun J

Frontiers in microbiology 20210415

The rapid diagnosis of tuberculosis (TB) is of great significance for the control and treatment of TB. However, TB remains a major healthy, social, and economic burden worldwide because of the lack of ideal diagnostic biomarkers. Mycobacterium tuberculosis (M. tuberculosis)-encoded small RNA (sRNA) is a class of regulation small RNA. Several studies have identified M. tuberculosis encoded-sRNAs in the serum/plasm of M. tuberculosis-infected patients. Small extracellular vesi ...[more]

PMID: 33936000

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Project description:BackgroundThe identification of indeterminate pulmonary nodules (IPNs) following a low-dose computed tomography (LDCT) is a major challenge for early diagnosis of lung cancer. The inadequate assessment of IPNs' malignancy risk results in a large number of unnecessary surgeries or an increased risk of cancer metastases. However, limited studies on non-invasive diagnosis of IPNs have been reported.MethodsIn this study, we identified and evaluated the diagnostic value of circulating small extracellular vesicle (sEV) microRNAs (miRNAs) in patients with IPNs that had been newly detected using LDCT scanning and were scheduled for surgery. Out of 459 recruited patients, 109 eligible patients with IPNs were enrolled in the training cohort (n = 47) and the test cohort (n = 62). An external cohort (n = 99) was used for validation. MiRNAs were extracted from plasma sEVs, and assessed using Small RNA sequencing. 490 lung adenocarcinoma samples and follow-up data were used to investigate the role of miRNAs in overall survival.ResultsA circulating sEV miRNA (CirsEV-miR) model was constructed from five differentially expressed miRNAs (DEMs), showing 0.920 AUC in the training cohort (n = 47), and further identified in the test cohort (n = 62) and in an external validation cohort (n = 99). Among five DEMs of the CirsEV-miR model, miR-101-3p and miR-150-5p were significantly associated with better overall survival (p = 0.0001 and p = 0.0069). The CirsEV-miR scores were calculated, which significantly correlated with IPNs diameters (p < 0.05), and were able to discriminate between benign and malignant PNs (diameter ≤ 1 cm). The expression patterns of sEV miRNAs in the benign, adenocarcinoma in situ/minimally invasive adenocarcinoma, and invasive adenocarcinoma subgroups were found to gradually change with the increase in aggressiveness for the first time. Among all DEMs of the three subgroups, five miRNAs (miR-30c-5p, miR-30e-5p, miR-500a-3p, miR-125a-5p, and miR-99a-5p) were also significantly associated with overall survival of lung adenocarcinoma patients.ConclusionsOur results indicate that the CirsEV-miR model could help distinguish between benign and malignant PNs, providing insights into the feasibility of circulating sEV miRNAs in diagnostic biomarker development.Trial registrationChinese Clinical Trials: ChiCTR1800019877. Registered 05 December 2018, https://www.chictr.org.cn/showproj.aspx?proj=31346 .

Project description:BackgroundNew diagnosis tests are urgently needed to address the global tuberculosis (TB) burden and to improve control programs especially in resource-limited settings. An effective in vitro diagnostic of TB based on serological methods would be regarded as an attractive progress because immunoassays are simple, rapid, inexpensive, and may offer the possibility to detect cases missed by standard sputum smear microscopy. However, currently available serology tests for TB are highly variable in sensitivity and specificity. Lipolytic enzymes have recently emerged as key factors in lipid metabolization during dormancy and/or exit of the non-replicating growth phase, a prerequisite step of TB reactivation. The focus of this study was to analyze and compare the potential of four Mycobacterium tuberculosis lipolytic enzymes (LipY, Rv0183, Rv1984c and Rv3452) as new markers in the serodiagnosis of active TB.MethodsRecombinant proteins were produced and used in optimized ELISA aimed to detect IgG and IgM serum antibodies against the four lipolytic enzymes. The capacity of the assays to identify infection was evaluated in patients with either active TB or latent TB and compared with two distinct control groups consisting of BCG-vaccinated blood donors and hospitalized non-TB individuals.ResultsA robust humoral response was detected in patients with active TB whereas antibodies against lipolytic enzymes were infrequently detected in either uninfected groups or in subjects with latent infection. High specifity levels, ranging from 93.9% to 97.5%, were obtained for all four antigens with sensitivity values ranging from 73.4% to 90.5%, with Rv3452 displaying the highest performances. Patients with active TB usually exhibited strong IgG responses but poor IgM responses.ConclusionThese results clearly indicate that the lipolytic enzymes tested are strongly immunogenic allowing to distinguish active from latent TB infections. They appear as potent biomarkers providing high sensitivity and specificity levels for the immunodiagnosis of active TB.

Project description:BackgroundBlood transcriptional signatures are candidates for non-sputum triage or confirmatory tests of tuberculosis. Prospective head-to-head comparisons of their diagnostic accuracy in real-world settings are necessary to assess their clinical use. We aimed to compare the diagnostic accuracy of candidate transcriptional signatures identified by systematic review, in a setting with a high burden of tuberculosis and HIV.MethodsWe did a prospective observational study nested within a diagnostic accuracy study of sputum Xpert MTB/RIF (Xpert) and Xpert MTB/RIF Ultra (Ultra) tests for pulmonary tuberculosis. We recruited consecutive symptomatic adults aged 18 years or older self-presenting to a tuberculosis clinic in Cape Town, South Africa. Participants provided blood for RNA sequencing, and sputum samples for liquid culture and molecular testing using Xpert and Ultra. We assessed the diagnostic accuracy of candidate blood transcriptional signatures for active tuberculosis (including those intended to distinguish active tuberculosis from other diseases) identified by systematic review, compared with culture or Xpert MTB/RIF positivity as the standard reference. In our primary analysis, patients with tuberculosis were defined as those with either a positive liquid culture or Xpert result. Patients with missing blood RNA or sputum results were excluded. Our primary objective was to benchmark the diagnostic accuracy of candidate transcriptional signatures against the WHO target product profile (TPP) for a tuberculosis triage test.FindingsBetween Feb 12, 2016, and July 18, 2017, we obtained paired sputum and RNA sequencing data from 181 participants, 54 (30%) of whom had confirmed pulmonary tuberculosis. Of 27 eligible signatures identified by systematic review, four achieved the highest diagnostic accuracy with similar area under the receiver operating characteristic curves (Sweeney3: 90·6% [95% CI 85·6-95·6]; Kaforou25: 86·9% [80·9-92·9]; Roe3: 86·9% [80·3-93·5]; and BATF2: 86·8% [80·6-93·1]), independent of age, sex, HIV status, previous tuberculosis, or sputum smear result. At test thresholds that gave 70% specificity (the minimum WHO TPP specificity for a triage test), these four signatures achieved sensitivities between 83·3% (95% CI 71·3-91·0) and 90·7% (80·1-96·0). No signature met the optimum criteria, of 95% sensitivity and 80% specificity proposed by WHO for a triage test, or the minimum criteria (of 65% sensitivity and 98% specificity) for a confirmatory test, but all four correctly identified Ultra-positive, culture-negative patients.InterpretationSelected blood transcriptional signatures met the minimum WHO benchmarks for a tuberculosis triage test but not for a confirmatory test. Further development of the signatures is warranted to investigate their possible effects on clinical and health economic outcomes as part of a triage strategy, or when used as add-on confirmatory test in conjunction with the highly sensitive Ultra test for Mycobacterium tuberculosis DNA.FundingRoyal Society Newton Advanced Fellowship, Wellcome Trust, National Institute of Health Research, and UK Medical Research Council.

Project description:Despite more than a century fighting against tuberculosis, the World Health Organisation has estimated that around 1.7 million people died of tuberculosis in 2016 and over a quarter of the world’s population is infected. One of the critical hurdles for stopping tuberculosis transmission is early and effective diagnosis of patients with the active pulmonary disease. Although important innovations in molecular diagnosis have been recently developed (e.g. Xpert MTB/RIF, Cepheid Inc., USA), there are no suitable tests for population screening at point-of-care. The current tuberculosis diagnosis pipeline presents a highly variable performance and requires access to reference laboratory facilities. A non-sputum based rapid test with high specificity and sensitivity could save ~400,000 lives per year. Therefore, new biomarkers for diagnosis are urgently required for identifying patients with early symptoms and to expedite treatment. Variable sensitivity and specificity can be overcome using a combination of multiple biomarkers (5). Proteins, as ultimate biological effectors, are ideal candidates for diagnostic biomarkers; consequently, proteomic studies are a crucial platform for biomarker discovery in tuberculosis. This work aims to develop a multi-marker panel for tuberculosis diagnosis with high performance capable of differentiating tuberculosis patients from relevant controls. Quantitative Multidimensional Protein Identification Technology (qMudPIT) is applied for biomarker discovery identifying candidates for early diagnosis of tuberculosis. The multidimensional method optimised in this work led to the identification of 5022 plasma proteins and 3577 quantified proteins using iTRAQ labelling. Known and completely novel markers for active tuberculosis in plasma were identified including a peptide derived from Mycobacterium tuberculosis. Complementary statistical and bioinformatic analysis were applied to prioritise candidates for validation in one or two independent cohorts. The plasma proteomic profile here described represents a power strategy for biomarker discovery and the panel proposed has the potential to be translated to a rapid test and which might contribute to tuberculosis control.

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Two Small Extracellular Vesicle sRNAs Derived From Mycobacterium tuberculosis Serve as Diagnostic Biomarkers for Active Pulmonary Tuberculosis.

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Two Small Extracellular Vesicle sRNAs Derived From <i>Mycobacterium tuberculosis</i> Serve as Diagnostic Biomarkers for Active Pulmonary Tuberculosis.

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