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Huang, Y.;  Li, Y.;  Lin, W.;  Fan, S.;  Chen, H.;  Xia, J.;  Pi, J.;  Xu, J. Role of Circular RNAs in Therapy of Tuberculosis. Encyclopedia. Available online: https://encyclopedia.pub/entry/27471 (accessed on 07 February 2026).
Huang Y,  Li Y,  Lin W,  Fan S,  Chen H,  Xia J, et al. Role of Circular RNAs in Therapy of Tuberculosis. Encyclopedia. Available at: https://encyclopedia.pub/entry/27471. Accessed February 07, 2026.
Huang, Yifan, Ying Li, Wensen Lin, Shuhao Fan, Haorong Chen, Jiaojiao Xia, Jiang Pi, Jun-Fa Xu. "Role of Circular RNAs in Therapy of Tuberculosis" Encyclopedia, https://encyclopedia.pub/entry/27471 (accessed February 07, 2026).
Huang, Y.,  Li, Y.,  Lin, W.,  Fan, S.,  Chen, H.,  Xia, J.,  Pi, J., & Xu, J. (2022, September 22). Role of Circular RNAs in Therapy of Tuberculosis. In Encyclopedia. https://encyclopedia.pub/entry/27471
Huang, Yifan, et al. "Role of Circular RNAs in Therapy of Tuberculosis." Encyclopedia. Web. 22 September, 2022.
Role of Circular RNAs in Therapy of Tuberculosis
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This entry is adapted from the peer-reviewed paper 10.3390/biom12091235

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb) infection, remains one of the most threatening infectious diseases worldwide. A series of challenges still exist for TB prevention, diagnosis and treatment, which therefore require more attempts to clarify the pathological and immunological mechanisms in the development and progression of TB. Circular RNAs (circRNAs) are a large class of non-coding RNA, mostly expressed in eukaryotic cells, which are generated by the spliceosome through the back-splicing of linear RNAs.

circular RNAs tuberculosis biomarkers

1. Introduction

Tuberculosis (TB) is one of the most common infectious diseases in the world, predominantly caused by one of the most tricky pathogens, Mycobacterium tuberculosis (Mtb), which lies dormant in the host cells by escaping the host immune clearance [1][2]. Among people infected with Mtb, totaling a quarter of the population worldwide, 5–10% of the infected patients will develop active TB disease (ATB) [1]. To the present time, the increasing emergence of multidrug resistant TB has been a major barrier to public health security, reported to be responsible for over ten thousand deaths related to antimicrobial resistance [2]. The co-infection conditions, such as human immunodeficiency virus (HIV) co-infected TB, and other disease coexisted conditions, such as diabetes coexisted TB, make the pathogenesis of TB more a more complicated question as to cure and control of the disease [3][4]. Other factors, such as the widespread prevalence of the tuberculosis bacterium of high virulence [5] and uncontrollable relapse TB cases [6][7], also present challenges to TB disease control. Currently, the only licensed tuberculosis vaccine, Bacillus Calmette-Guérin (BCG) is recommended at birth to protect children against tubercular meningitis, but its protective effects against TB are very poor in adults [8][9]. Moreover, Mtb can remain dormant in the host cells for a long time [10], which introduces an asymptomatic latent TB infection condition, likely detectable by an interferon-γ release assay, but without other combined methods for accurate and rapid diagnosis. Therefore, it is urgent to clarify the pathological and immunological mechanisms in the development and progression of TB, an effort which might benefit the developments of more effective strategies for TB prevention, diagnosis and treatment.
Circular RNAs (circRNAs) are a kind of non-coding protein RNA expressed in most eukaryotic cells. Compared with linear RNAs, the absence of five-prime caps and three-prime tails allow circRNAs to loop into a single-stranded, covalently closed structure for more stable and highly conserved characteristics, which helps to avoid or escape from RNAse digestion [11][12]. In the 1970s, viroids in plants, exhibiting high thermal stability and single-stranded covalently closed structure, were found to be the first circular RNA by Sanger et al. [13], which further confirmed by sequence analysis two years later [14]. Researchers thus opened up a new field of biology and medicine for the functional and mechanistic study of circRNAs in different species.
In the 1990s, researchers serendipitously discovered that the products of splicing transcripts with an inverted order of exons, called mis-splicing, which occurred specifically at consensus splice sites, could lead to the formation of circular RNA molecules, such as the tumor suppressor gene deleted in colorectal carcinomas (DCC) [15] and human proto-oncogene ets-1 [16]. These non-polyadenylated scrambled transcripts were found at much lower levels than in the normal transcripts [17]. However, the prevalence and the significance of circRNAs were not discovered over the ensuing decades, until high-throughput sequencing could be applied. With the assistance of deep sequencing, substantial circRNAs were discovered and were no longer simply considered to be accidental byproducts of splicing [18]. Salzman et al. identified numerous RNA isoforms with scrambled exons in normal and malignant human cells, and then confirmed that these scrambled-exon transcripts were circRNAs enriched in cytoplasm. These results proved that circRNAs were ubiquitous, and that most of them were highly expressed in human cells [11]. After this discovery, circRNAs in human cells began to receive extensive attention, and the emerging functions of circRNAs were subsequently identified.

2. Potentials of circRNAs as Biomarkers in TB

At present, laboratory diagnosis of TB is mainly based on sputum specimen smear microscopy and sputum culture. However, the sputum specimen smear microscopy is limited by the low sensitivity and specificity values and the sputum culture is restricted by its long detection time, which may miss the proper treatment in time [19]. Therefore, it is of great significance to develop novel strategies for early diagnosis and timely treatments, thus curbing the spread of TB disease. Discovering molecular markers with significant distinguishing efficiency to discriminate between TB cases and healthy individuals are of vital importance to develop novel strategy for rapid diagnosis of TB.
It has been established that circRNAs are widely involved in a variety of physiological and pathological processes. The aberrantly expressed circRNAs found in patients might hint at the potential role of circRNAs in the diagnosis of diverse diseases [20]. As for the wide distribution and stability characteristics, circRNAs are able to be easily detected in body fluids, such as blood, urine, exosomes and so on [21][22]. Recently, more and more studies are suggesting that circRNAs can act as diagnostic biomarkers for TB [23][24][25][26][27][28][29][30][31]. Researchers have summarized of all the circular RNAs that are currently reported to be involved in regulating Tuberculosis in Table 1. However, there are still many aspects of the question that have yet to be sufficiently explored to learn about the essential roles of circRNAs after tuberculosis infection, which might enhance the understanding of TB pathogenesis and benefit the development of TB diagnostic or therapeutic strategies.
Table 1. Summary of all the circular RNAs that are currently reported to be involved in regulating Tuberculosis.
Circular RNA Function Expression Derived From Targets/Signaling
Pathways		 AUC Number of TB
Patients/Controls		 Ref.
hsa_circ_0001204 biomarker down plasma   0.871 145/120 [28]
hsa_circ_0001747 biomarker down plasma   0.830 145/120 [28]
hsa_circ_0001204;
hsa_circ_0001747		 biomarker down plasma   0.928 * 145/120 [28]
hsa_circ_0001953 biomarker up plasma   0.826 120/100 [27]
hsa_circ_0009024 biomarker up plasma   0.777 120/100 [27]
hsa_circ_0001953; hsa_circ_0009024 biomarker up plasma   0.915 * 120/100 [27]
hsa_circ_001937 biomarker up PBMCs   0.873 115/90 [29]
hsa_circ_0043497 biomarker up Mtb-infected MDMs   0.860 96/85 [25]
hsa_circ_0001204 biomarker down Mtb-infected MDMs   0.848 96/85 [25]
hsa_circ_103017 biomarker up PBMCs   0.870 31/30 [30]
hsa_circ_059914 biomarker up PBMCs   0.821 31/30 [30]
hsa_circ_0028883 biomarker up PBMCs miR-409-5p 0.773 20/20 [31]
hsa_circ_0005836 biomarker down PBMCs   no mention 49/45 [23]
hsa_circ_0001380 biomarker down PBMCs   0.9502 32/31 [32]
hsa_circ_103571 biomarker down plasma   0.838 32/29 [24]
circ_051239 biomarker up serum   0.9738 72/30 [26]
circ_029965 biomarker up serum   0.9443 72/30 [26]
circ_404022 biomarker up serum   0.9682 72/30 [26]
SAMD8_
hsa_circRNA994		 no mention no mention whole blood   no mention 45/61 [33]
TWF1_
hsa_circRNA9897		 no mention no mention whole blood   no mention 45/61 [33]
circTRAPPC6B miRNA sponge down PBMCs miR-874-3p
ATG16L1
autophagy		 0.8609 32/31 [34]
hsa_circ_0003528 miRNA sponge up plasma miR-224-5p
miR-324-5p
miR-488-5p
CTLA4
polarization		 no mention 50/50 [35]
hsa_circ_101128 biomarker; miRNA sponge up PBMCs let-7a
MAPK/P13K-Akt
pathway		 0.817 31/30 [30]
hsa_circ_0045474 miRNA sponge down PBMCs miR-582-5p
TNKS2
autophagy		 no mention 15/15 [36]
circAGFG1 miRNA sponge up alveolar macrophages in ATB patients Notch
miR-1257
apoptosis
autophagy		 no mention no mention [37]
circ_0001490 miRNA sponge down Mtb-infected THP-1 macrophages;
serum		 miR-579-3p
FSTL1
inflammatory
response		 no mention 40/23 [38]
cPWWP2A miRNA sponge down primary human MDMs miR-579 no mention no mention [39]
* The AUC for distinguishing TB patients when several circRNAs are used in combination.
Regarding the feasibility application of circRNAs as potential biomarkers for TB diagnosis, the method of identifying TB-related functional circRNAs is a critical issue. The circRNAs microarrays can be used to screen the circRNAs expression profiles between Mtb-infected group and control group. Then differentially expressed circRNAs can be verified by quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, receiver operating characteristic curve (ROC) or the area under the ROC curve (AUC) can be applied to evaluate the diagnostic value of circRNAs for TB with the sensitivity and specificity values determined based on the respective cut-off values [24].
In term of circulating circRNAs as potential biomarkers, there are three perspectives related to the diagnosis and progression of TB. Firstly, emerging studies have identified that various kinds of samples in TB patients, including plasma, serum, PBMCs, MDMs, whole blood and exosomes, contain diverse levels of dysregulated circRNAs for potential TB diagnosis. The alterations of circRNAs are involved in human immunological responses against TB infection. Plasma level of hsa_circ_103571, human MDMs level of hsa_circ_0043497 and hsa_circ_0001204, and serum levels of circRNA_051239, circRNA_029965, and circRNA_404022 in active TB samples were found to be served as potential biomarkers for TB diagnosis [24][25][26]. Another study first analyzed the expression profile of circRNAs in PBMCs from three active pulmonary tuberculosis (APTB) patients and three healthy controls by microarray screening. Six circRNAs were then chosen for validation using qRT-PCR in 40 TB patients and 40 control subjects. The AUC of six candidate circRNAs were all larger than 0.750, suggesting their potential diagnostic value in TB diagnosis. In order to further verify the specificity of selected circRNAs and their abilities to effectively distinguish TB from other lung diseases according to the circRNAs expression levels, further evaluation was performed in an independent cohort consisting of 115 TB patients, 40 pneumonia patients, 40 COPD patients, 40 lung cancer patients and 90 control subjects. It was established that the expression of hsa_circRNA_001937 is significantly higher in TB patients compared with that in patients with other pulmonary diseases such as pneumonia, COPD and lung cancer, revealing that hsa_circRNA_001937 may serve as a TB-specific signature circRNA and could be used as a candidate biomarker of TB [29].
The previous work also focused on six differentially expressed circRNAs in the PBMCs of APTB through high-throughput sequencing validated in 10 APTB patients and ten health volunteers. Furthermore, the verification of hsa_circ_0005836 and hsa_circ_0009128 was also conducted between 34 APTB and 30 health controls. It has been demonstrated that hsa_circ_0005836 and hsa_circ_0009128 expression levels were significantly down-regulated in the PBMCs of APTB, which indicated their potentials as new diagnostic biomarkers and therapeutic target of active TB [23]. By comparing the peripheral blood of 31 healthy controls and 32 active TB patients, hsa_circ_0001380 was found to be down-regulated in TB patients with a diagnostic value evaluated by AUC of 0.9502. These results indicated high sensitivity and specificity of 93.75% and 87.50%, respectively, suggesting the high diagnostic value of hsa_circ_0001380 in APTB [32].
Moreover, the combination of several circRNAs as biomarkers can increase the diagnostic value. For instance, hsa_circRNA_001937 showed 85% of sensitivity and 77.5% of specificity as candidate biomarkers for TB diagnosis, while hsa_circRNA_009024 showed 75.0% of sensitivity and 80.0% of specificity. Importantly, the sensitivity and specificity for the combination of hsa_circRNA_001937 and hsa_circRNA_009024 are found to reach 95.0% and 80.0%, respectively, which are higher than that of single circRNA and can provide better diagnostic accuracy with the AUC of 0.926 [29]. In addition, in a completely different sample comprising 120 TB and 100 healthy control subjects, the diagnostic potential of combining hsa_circ_0001953 and hsa_circ_0009024 in the clinical setting was determined. The AUC, sensitivity and specificity for hsa_circ_0001953 were 0.826, 69.17% and 89.00%, respectively. For hsa_circ_0009024, an AUC of 0.777 was obtained, and sensitivity and specificity were 60.00 and 86.00%, respectively. Notably, when the plasma levels of hsa_circ_0001953 and hsa_circ_0009024 were used in combination, the AUC of 0.915 was obtained for detecting TB, with sensitivity and specificity of 72.50% and 96.00%, respectively [27]. Also, plasma levels of hsa_circ_0001204 and hsa_circ_0001747 were selected for further analysis in 145 TB patients and 120 control individuals, which then showed AUC of 0.871 and 0.830, respectively. However, the AUC for distinguishing TB patients was increased to 0.928 (sensitivity = 86.21%, specificity = 89.17%) when hsa_circ_0001204 and hsa_circ_0001747 were used in combination. Recently, a study determined the ncRNAs expression profiles in exosomes derived from H37Ra and BCG infected macrophages. A total number of 2332 circRNAs were recognized associated with TB infection and some circRNAs such as hsa_circ_0129477, hsa_circ_0082641, hsa_circ_0072892, hsa_circ_0104568 and hsa_circ_0036372 were predicted to interact with known miRNAs, which revealed the potential functional circRNAs markers in the pathogenesis and diagnosis of TB [40].
Secondly, circRNAs are able to evaluate the clinical curative effect in TB. It has been identified that the abnormal plasma level of circRNAs can be markedly altered to the normal level in TB patients upon successful therapy. For instance, hsa_circRNA_001937 expression is elevated in active TB patients, which is significantly reduced to the normal level after successful anti-TB therapy through eight-month following up in 20 newly diagnosed TB patients [29]. Additionally, the expression of hsa_circ_0001204 in plasma and MDMs both decreased in TB patients, and hsa_circ_0001204 expression can be significantly up-regulated after anti-TB treatment [25][28]. Hsa_circ_0001953 and hsa_circ_0009024 expression levels are markedly decreased in TB patients upon successful therapy; this was assessed in 25 TB cases pre- and post-treatment, with no significant difference between the control and TB treated group [27]. Additionally, as well as distinguishing TB patients and health controls, circRNAs also showed strong potential for diagnosis of drug-resistant TB. In a recent study, the plasma levels of circRNAs were analyzed in 20 drug-resistant TB patients and 31 pan-susceptible TB patients, and found that circRNA_051239 was significantly increased in the drug-resistant group, revealing a marker that could be used to distinguish drug-resistant TB patients from pan-susceptible TB patients [26]. Additionally, in a study related to the anti-TB drug-induced liver injury (ADLI) in TB patients, peripheral blood from sixteen ADLI patients and 16 non-ADLI patients were collected and isolated to obtain total RNAs for human circRNAs microarray expression profiling. Among the ADLI-specific circRNAs, the expression of circMARS was found to be elevated in the serum of TB patients, which was validated by qRT-PCR in a cohort consisting of 150 ADLI patients and 150 non-ADLI patients. Also, cytology experiments and a self-controlled cohort of 35 participants before and during ADLI were used to verify the function of circMARS after anti-TB treatment. In this way, circMARS could act as a miR-6808-5p/-6874-3p/-3157-5p sponge to participate in the compensatory repair of ADLI, which might hamper the achievement of the treatment goals of TB [41].
Thirdly, circRNAs harbor the potential to distinguish the degree of TB disease or TB disease progress. Some circRNAs are reported to be positively correlated with TB severity. For instance, in clinical settings, according to pulmonary radiographic images, APTB patients can be classified into three severity levels: minimal, moderate and advanced disease. By using a double-blind test to classify 40 APTB patients regarding the severity of disease, each one gained radiological severity scores (RSS), and the number of minimal, moderate and advanced disease were 18, 12 and 10, respectively. Then the correlation between circRNAs levels and RSS were analyzed by using Spearman’s rank correlation test, and three of the six differentially expressed circRNAs were found to be correlated with the RSS, including hsa_circRNA_001937, hsa_circRNA_009024 and hsa_circRNA_102101 [29]. Similarly, hsa_circ_0001204 and hsa_circ_0001747 were found to be markedly down-regulated, while hsa_circ_0001953 and hsa_circ_0009024 were up-regulated in the plasma levels of active pulmonary TB patients [27][28]. Both of their plasma levels are correlated with the radiological severity scores, which are assessed according to pulmonary radiographic images, implying that these circRNAs might be involved in the disease progress of TB and associated with TB pathology.
Also, Lyu et al. have summarized and validated the TB-related circRNAs diagnostic panels to reveal their performance and biological function in datasets. They indicated that the parental genes of circRNAs mostly participated in the biological processes including GTPase activity and protein autophosphorylation, while circRNAs in related panels were involved in Wnt and JAK-STAT signaling pathways through GO and KEGG analysis [42]. Researchers provides a potential basis for clinical choice of TB-related circRNAs diagnostic panels. There is no doubt that the circRNAs chosen as TB-markers can be somehow involved in different pathways, which might present a puzzle in diagnosing a healthy patient with false positive signals. It is still necessary to combine other clinical detection for TB diagnosis such as Ziehl-Neelsen acid fast staining analysis of the sputum smears and lung images to eliminate the interference signals from other diseases [23][29].

3. CircRNAs Regulate Anti-TB Defense as Potential Therapeutic Targets

Upon Mtb infection, host macrophages are activated as the first line of defense to fight against the bacteria. Intriguingly, Mtb can successfully evolve into several mechanisms to escape from bactericidal activities of macrophages, thus safely surviving inside the cell host, and leading to a life-long latent infection or even active TB [43]. An increasing number of studies have indicated that circRNAs can act as the key molecules involved in the immune defense response during TB infection through modulating macrophages’ functions, with the aim of controlling and eliminating of Mtb invaded in macrophages [36][37][38]. Therefore, it is of great significance to identify the relevance of aberrantly expressed circRNAs in TB and to clarify their potential mechanisms involved in the pathogenesis of TB infection.
Previous studies have identified the potential interactions for circRNA-miRNA-mRNA in TB, which might provide some detailed mechanisms for TB development in genetic scale. By circRNA/miRNA interaction prediction, Fu et al. found that circRNA_101128 expression in TB samples was negatively correlated with the level of its possible target let-7a and circRNA_101128 was potentially involved in MAPK and P13K-Akt pathway possibly via modulation of let-7a [30]. Luo et al. indicated that hsa_circ_0001380 in blood sample could be a biomarker for active pulmonary TB and the potential target miRNAs might be hsa-miR-622 and hsa-miR-136-5p [32]. Hsa_circRNA_103571 expression was significantly decreased in the plasma of active TB patients and showed potential interaction with active TB related miRNAs, such as miR-29a and miR-16 [24]. Additionally, circRNA_051239 might act as a ceRNA for miR-320a, and play a vital role in the TB drug-resistant progress [26]. Circ_0001490 expression was down-regulated both in the serum samples of TB patients and Mtb-infected THP-1 macrophages. Additionally, circ_0001490 could interact with miR-579-3p as miRNA sponge, and miR-579-3p could interact with the 3′ untranslated region (3′UTR) of follistatin-like protein 1 (FSTL1). Thus, overexpression of circ_0001490 suppressed Mtb survival and promoted the viability and inflammatory response of Mtb-infected THP-1 macrophages partly by regulating miR-579-3p/FSTL1 axis based on its miRNA sponge roles [38]. The expression of cPWWP2A was down-regulated in Mtb-infected macrophages and was identified to function as an endogenous miR-579 sponge, inhibiting miR-579 activity and expression. Conversely, ectopic cPWWP2A over-expression largely attenuated the cytotoxicity and apoptosis of macrophage induced by Mtb infection, suggesting that targeting this cPWWP2A/miR-579 axis might be a novel strategy to protect human macrophages from Mtb infection and provide new directions for possible clinical TB control [39]. These results indicate that circRNAs can function as miRNAs sponges or decoys to regulate different progress of TB.
Among the immune escape mechanisms exploited by Mtb, cellular apoptosis and autophagy exert essential roles in the control of bacterial infection [44]. As a part of innate immune response, apoptosis is regarded as an efficient strategy for intracellular pathogens removal, via potently eliminating their replicative niche, thus restricting the transmission of the infection [45]. It has been identified that Mtb can inhibit macrophage apoptosis, reversing the manipulation of host immunity. Unlike apoptosis, autophagy is shown to maintain the homeostasis in host cells without inducing cell death, which therefore can be developed to inhibit intracellular Mtb growth by inducing autophagy in macrophages [46].
Given these two major roles, the immunity status of macrophages is manipulated by Mtb in order to circumvent host immune response and promote its intracellular survival. For example, circAGFG1 was of the type of circRNAs to balance the physiological and pathological activation of macrophages caused by autophagy and apoptosis. CircAGFG1 was highly expressed in active TB and was sufficiently plastic to the modulation of Mtb by enhancing autophagy but reducing apoptosis via the miRNA-1257/Notch axis, which would benefit of the host defense against Mtb [37].
Moreover, many circRNAs induce autophagy in the progression of TB, suppressing the intracellular survival of Mtb. For example, hsa_circ_0045474 was down-regulated in monocytes from TB patients and induced macrophage autophagy, via modulation of miR-582-5p/ TNKS2 axis, implying a potential strategy to treat the occurrence of active pulmonary TB by targeting hsa_circ_0045474 [36]. According to the principle that the physiological activation of autophagy in macrophages could facilitate mycobacterial clearance, circTRAPPC6B-enhanced autophagy aggregation or sequestration have been observed for intracellular Mtb inhibition by the group [34]. The overexpression of circTRAPPC6B could enhance the colocalization of LC3B puncta and GFP expressing BCG in THP-1 macrophages, exhibiting elimination of invading pathogens. In detail, circTRAPPC6B could antagonize the ability of miR-874-3p to suppress ATG16L1 and enhance autophagy sequestration to restrict Mtb growth in macrophages.
Additionally, macrophages can differentiate into several specific phenotypes in response to various stimuli in diverse physiological and pathological contexts, thereby exhibiting various functionalities [47]. It is widely accepted that macrophages can be classified into two subtypes: classically activated M1 macrophages and alternately activated M2 macrophages. M1 macrophages can lead to pro-inflammatory responses with increased microbicidal capacity, while M2 macrophages can lead to anti-inflammatory responses with lower microbicidal capacity [48]. Previous studies have also identified that Mtb infection can induce the polarization of monocyte-derived macrophages [49]. Similarly, M1 macrophages could promote granuloma formation and macrophage bactericidal activity in vitro, while M2 macrophages inhibit these effects.
For example, hsa_circ_0003528 was found to be elevated in the plasma of active pulmonary TB patients in comparison with that of healthy controls. Additionally, has_circ_0003528 can function as ceRNAs (including sponging miR-224-5p, miR-324-5p and miR-488-5p), targeting the co-share gene CTLA4. It is demonstrated that up-regulation hashsa_circ_0003528 could promote TB associated macrophage polarization by up-regulating the expression of CTLA4, reminding researchers of the critical roles of circRNAs in macrophage polarization regulations against Mtb infection [35].
Relying on the high-throughput studies and bioinformatic analysis, an increasing number of circRNAs related to Mtb infection can be emergingly predicted and recognized. Based on circRNA-miRNA-mRNA and protein-protein interaction networks, three hub genes associated with the development of pulmonary TB were identified, including hsa_circ_0007919, hsa_circ_0002419, and hsa_circ_0005521. Such a prediction might provide references to find candidate biomarkers for the early diagnosis of pulmonary TB and for possible therapeutic strategy development [50]. By using prediction databases online, circRNAs such as SAMD8_hsa_circRNA994 and TWF1_hsa_circRNA9897 were found be significantly correlated with the interferon signaling pathway, as potential molecules to act as a defense against TB infection in host cells [33].

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Subjects: Biology
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Yifan Huang
, Ying Li ,
Wensen Lin
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Shuhao Fan
,
Haorong Chen
,
Jiaojiao Xia
, Jiang Pi , Jun-Fa Xu
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Update Date: 23 Sep 2022
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