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

Abstract

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.

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.