Dataset Information

Reprogramming of Small Noncoding RNA Populations in Peripheral Blood Reveals Host Biomarkers for Latent and Active Mycobacterium tuberculosis Infection.

ABSTRACT: In tuberculosis (TB), as in other infectious diseases, studies of small noncoding RNAs (sncRNA) in peripheral blood have focused on microRNAs (miRNAs) but have neglected the other major sncRNA classes in spite of their potential functions in host gene regulation. Using RNA sequencing of whole blood, we have therefore determined expression of miRNA, PIWI-interacting RNA (piRNA), small nucleolar RNA (snoRNA), and small nuclear RNA (snRNA) in patients with TB (n?=?8), latent TB infection (LTBI; n?=?21), and treated LTBI (LTBItt; n?=?6) and in uninfected exposed controls (ExC; n?=?14). As expected, sncRNA reprogramming was greater in TB than in LTBI, with the greatest changes seen in miRNA populations. However, substantial dynamics were also evident in piRNA and snoRNA populations. One miRNA and 2 piRNAs were identified as moderately accurate (area under the curve [AUC]?=?0.70 to 0.74) biomarkers for LTBI, as were 1 miRNA, 1 piRNA, and 2 snoRNAs (AUC?=?0.79 to 0.91) for accomplished LTBI treatment. Logistic regression identified the combination of 4 sncRNA (let-7a-5p, miR-589-5p, miR-196b-5p, and SNORD104) as a highly sensitive (100%) classifier to discriminate TB from all non-TB groups. Notably, it reclassified 8 presumed LTBI cases as TB cases, 5 of which turned out to have features of Mycobacterium tuberculosis infection on chest radiographs. SNORD104 expression decreased during M. tuberculosis infection of primary human peripheral blood mononuclear cells (PBMC) and M2-like (P?=?0.03) but not M1-like (P?=?0.31) macrophages, suggesting that its downregulation in peripheral blood in TB is biologically relevant. Taken together, the results demonstrate that snoRNA and piRNA should be considered in addition to miRNA as biomarkers and pathogenesis factors in the various stages of TB.IMPORTANCE Tuberculosis is the infectious disease with the worldwide largest disease burden and there remains a great need for better diagnostic biomarkers to detect latent and active M. tuberculosis infection. RNA molecules hold great promise in this regard, as their levels of expression may differ considerably between infected and uninfected subjects. We have measured expression changes in the four major classes of small noncoding RNAs in blood samples from patients with different stages of TB infection. We found that, in addition to miRNAs (which are known to be highly regulated in blood cells from TB patients), expression of piRNA and snoRNA is greatly altered in both latent and active TB, yielding promising biomarkers. Even though the functions of many sncRNA other than miRNA are still poorly understood, our results strongly suggest that at least piRNA and snoRNA populations may represent hitherto underappreciated players in the different stages of TB infection.

SUBMITTER: de Araujo LS

PROVIDER: S-EPMC6890987 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Reprogramming of Small Noncoding RNA Populations in Peripheral Blood Reveals Host Biomarkers for Latent and Active Mycobacterium tuberculosis Infection.

de Araujo Leonardo Silva LS Ribeiro-Alves Marcelo M Leal-Calvo Thyago T Leung Janaína J Durán Verónica V Samir Mohamed M Talbot Steven S Tallam Aravind A Mello Fernanda Carvalho de Queiroz FCQ Geffers Robert R Saad Maria Helena Féres MHF Pessler Frank F

mBio 20191203 6

In tuberculosis (TB), as in other infectious diseases, studies of small noncoding RNAs (sncRNA) in peripheral blood have focused on microRNAs (miRNAs) but have neglected the other major sncRNA classes in spite of their potential functions in host gene regulation. Using RNA sequencing of whole blood, we have therefore determined expression of miRNA, PIWI-interacting RNA (piRNA), small nucleolar RNA (snoRNA), and small nuclear RNA (snRNA) in patients with TB (<i>n</i> = 8), latent TB infection (LT ...[more]

PMID: 31796535

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Project description:Despite a century of research into tuberculosis (TB), there is a dearth of reproducible, easily quantifiable, biomarkers that can predict disease onset and differentiate between host disease states. Due to the challenges associated with human sampling, nonhuman primates (NHPs) are utilized for recapitulating the closest possible modelling of human TB. To establish a predictive peripheral biomarker profile based on a larger cohort of rhesus macaques (RM), we analyzed results pertaining to peripheral blood serum chemistry and cell counts from RMs that were experimentally exposed to Mtb in our prior studies and characterized as having either developed active TB (ATB) disease or latent TB infection (LTBI). We compared lung CFU burdens and quantitative pathologies with a number of measurables in the peripheral blood. Based on our results, the investigations were then extended to the study of specific molecules and cells in the lung compartments of a subset of these animals and their immune responses. In addition to the elevated serum C-reactive protein (CRP) levels, frequently used to discern the level of Mtb infection in model systems, reduced serum albumin-to-globulin (A/G) ratios were also predictive of active TB disease. Furthermore, higher peripheral myeloid cell levels, particularly those of neutrophils, kynurenine-to-tryptophan ratio, an indicator of induced expression of the immunosuppressive molecule indoleamine dioxygenase, and an influx of myeloid cell populations could also efficiently discriminate between ATB and LTBI in experimentally infected macaques. These quantifiable correlates of disease were then used in conjunction with a regression-based analysis to predict bacterial load. Our results suggest a potential biomarker profile of TB disease in rhesus macaques, that could inform future NHP-TB research. Our results thus suggest that specific biomarkers may be developed from the myeloid subset of peripheral blood or plasma with the ability to discriminate between active and latent Mtb infection.

Project description:Tuberculosis (TB) is a serious infectious disease in that 90% of those latently infected with Mycobacterium tuberculosis present no symptoms, but possess a 10% lifetime chance of developing active TB. To prevent the spread of the disease, early diagnosis is crucial. However, current methods of detection require improvement in sensitivity, efficiency or specificity. In the present study, we conducted a microarray experiment, comparing the gene expression profiles in the peripheral blood mononuclear cells among individuals with active TB, latent infection, and healthy conditions in a Taiwanese population.Bioinformatics analysis revealed that most of the differentially expressed genes belonged to immune responses, inflammation pathways, and cell cycle control. Subsequent RT-PCR validation identified four differentially expressed genes, NEMF, ASUN, DHX29, and PTPRC, as potential biomarkers for the detection of active and latent TB infections. Receiver operating characteristic analysis showed that the expression level of PTPRC may discriminate active TB patients from healthy individuals, while ASUN could differentiate between the latent state of TB infection and healthy condidtion. In contrast, DHX29 may be used to identify latently infected individuals among active TB patients or healthy individuals. To test the concept of using these biomarkers as diagnostic support, we constructed classification models using these candidate biomarkers and found the Naïve Bayes-based model built with ASUN, DHX29, and PTPRC to yield the best performance.Our study demonstrated that gene expression profiles in the blood can be used to identify not only active TB patients, but also to differentiate latently infected patients from their healthy counterparts. Validation of the constructed computational model in a larger sample size would confirm the reliability of the biomarkers and facilitate the development of a cost-effective and sensitive molecular diagnostic platform for TB.

Dataset Information

Reprogramming of Small Noncoding RNA Populations in Peripheral Blood Reveals Host Biomarkers for Latent and Active Mycobacterium tuberculosis Infection.

Publications

Reprogramming of Small Noncoding RNA Populations in Peripheral Blood Reveals Host Biomarkers for Latent and Active Mycobacterium tuberculosis Infection.

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