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J Clin Microbiol. Dec 2011; 49(12): 4246–4251.
PMCID: PMC3232949

Circulating MicroRNAs in Patients with Active Pulmonary Tuberculosis[down-pointing small open triangle]

Abstract

Emerging evidence shows that microRNAs (miRNAs) play an important role in pathogen-host interactions. Circulating miRNAs have been repeatedly and stably detected in blood and hold promise to serve as molecular markers for diverse physiological and pathological conditions. To date, the relationship between circulating miRNAs and active pulmonary tuberculosis (TB) has not been reported. Using microarray-based expression profiling followed by real-time quantitative PCR validation, the levels of circulating miRNAs were compared between patients with active pulmonary tuberculosis and matched healthy controls. The receiver operating characteristic curve was used to evaluate the diagnostic effect of selected miRNA. Bioinformatic analysis was used to explore the potential roles of these circulating miRNAs in active pulmonary tuberculosis infection. Among 92 miRNAs significantly detected, 59 miRNAs were downregulated and 33 miRNAs were upregulated in the TB serum compared to their levels in the control serum. Interestingly, only two differentially expressed miRNAs were increased not only in the serum but also in the sputum of patients with active pulmonary tuberculosis compared to the levels for the healthy controls. Upregulated miR-29a could discriminate TB patients from healthy controls with reasonable sensitivity and specificity. A number of significantly enriched pathways regulated by these circulating miRNAs were predicted, and most of them were involved in acute-phase response, inflammatory response, and the regulation of the cytoskeleton. In all, for the first time our results revealed that a number of miRNAs were differentially expressed during active pulmonary tuberculosis infection, and circulating miR-29a has great potential to serve as a marker for the detection of active pulmonary tuberculosis infection.

INTRODUCTION

MicroRNAs (miRNAs) are small, noncoding, highly conserved, single-stranded RNAs which can specifically regulate gene expression by targeting messenger RNAs (mRNAs). miRNA transcription occurs in the nucleus, leading to primary miRNAs (pri-miRNAs) produced by RNA polymerase II or III. They are subsequently processed into shorter (60- to 70-nucleotide), hairpin-shaped, double-stranded precursor miRNAs (pre-miRNAs) by the RNase III enzyme Drosha and protein Pasha/DGCR8, which are transported into the cytoplasm and further processed into mature miRNAs, single-stranded RNAs of approximately 22 nucleotides in length. Upon guiding multiprotein RNA-induced silencing complex (miRISC) to the target sequences through the mature miRNA binding of the 3′-untranslated regions (UTRs) of the mRNA, this binding of miRISC leads to the inhibition of mRNA translation or mRNA cleavage and subsequent degradation (1).

Studies have revealed that miRNAs play important roles in diverse processes such as cell differentiation, cell proliferation, and organ development (2, 26). More importantly, beyond their roles in physiological processes, extensive research has explored miRNA involvement in various pathologies, including infectious diseases. For instance, the let-7 family was iden-tified as the common denominator of Salmonella-regulated microRNAs in macrophages and epithelial cells, and the repression of let-7 relieves cytokine IL-6 and IL-10 mRNAs (23). miRNA-155 is essential for the T cell-mediated control of Helicobacter pylori infection and for the induction of chronic gastritis and colitis (20). These data suggested that some miRNA species play important roles in infectious disease.

Tuberculosis (TB) remains a major challenge to global public health in the 21st century, and one-third of the world's population is estimated to be infected with Mycobacterium tuberculosis (5). In developing countries, TB is still a common and often deadly infectious disease. China has the world's second largest tuberculosis epidemic, which has resulted in increased health care costs and other socioeconomic burdens. Recent studies showed that the mycobacterial infection of human macrophages causes a specific miRNA response (24), and the infection of mice with Mycobacterium bovis bacillus Calmette-Guérin (BCG) downregulates miR-29 expression in gamma interferon (IFN-γ)-producing natural killer cells, CD4+ T cells, and CD8+ T cells (16). These findings should open a new and interesting field in elucidating the relationship between miRNAs and TB infection.

Considering the central role of miRNAs in development and disease, we proposed that certain circulating miRNAs influence the outcome of TB infection, and this may be measured by the levels of miRNA in the blood. Endogenous miRNAs exist in serum and are resistant to RNase activity. There is emerging evidence that the amounts of circulating miRNAs promise to serve as useful clinical biomarkers (8, 17). Nonetheless, cell-free miRNAs in serum have not been studied in pulmonary TB infection. Therefore, the goal of this study was to identify a panel of serum miRNAs which are differentially expressed in patients with active pulmonary TB compared to expression in matched healthy controls and to explore the potential biological function of identified candidate miRNAs.

MATERIALS AND METHODS

Human subjects.

Seventy-five patients with active pulmonary TB from the Affiliated Hospital of Weifang Medical University and the Chest Specialty Hospital of Weifang, China, were enrolled. Eligibility for entry into the study included typical symptoms of pulmonary TB: fibrocavitary lung infiltrate on chest radiograph, at least one sputum specimen staining positive with Ziehl-Neelsen for acid-fast bacilli, and/or a positive sputum culture. For sputum culture, specimens were inoculated onto Lowenstein-Jensen (LJ) culture medium after treatment with 4% NaOH. All culture tubes were incubated at 37°C and observed daily for the first week of incubation and weekly thereafter until 8 weeks. Biochemical tests, specifically niacin production and nitrate tests, were used to identify M. tuberculosis in LJ culture medium. Patients who had another coexisting disease were excluded. Also, 52 healthy age- and sex-matched subjects were recruited as controls (Table 1). Healthy controls involved in the study were free of TB infection, including active and latent TB infection, and free of any clinical symptoms of any infectious disease.

Table 1.
Characteristics of participantsa

The study was performed with the approval of the Weifang Medical University local ethics committee and carried out in compliance with the Helsinki Declaration. Informed consent was obtained from all of the subjects before the commencement of the study.

Sample preparation, RNA isolation, and RNA quality control. Five milliliters of venous blood was collected from each participant. To harvest cell-free serum, the blood was drawn into a sterile polyolefin resin tube without anticoagulant. After leaving the tube in a standing position for 20 min at room temperature, samples were centrifuged at 3,000 rpm for 10 min, and the supernatant serum was quickly removed, aliquoted, and stored immediately in liquid nitrogen until analysis.

Total RNA was harvested using TRIzol (Invitrogen) and further purified using an RNeasy minikit (Qiagen, Denmark) from serum samples according to the manufacturer's instructions. The concentration and quality of RNA from each serum sample were measured by a Nanodrop spectrophotometer (ND-1000; Nanodrop Technologies) and checked by gel electrophoresis. Equal amounts of RNA from each patient and control sample were pooled in two groups (designated the active TB group and control group, respectively).

Sputum was collected into a sterile plastic dish, placed on ice, and processed within 1 h. Aliquots of sputum were taken for cell counting from all samples before processing with dithioerythritol (0.1%) and RNase inhibitor (20 U/ml) for homogenization. The homogenized sputum samples were centrifuged and the supernatant was collected, aliquoted, and stored immediately in liquid nitrogen until analysis. Total RNA was extracted from sputum supernatant using TRIzol reagent as described above.

miRNA labeling and array hybridization.

After RNA isolation from the samples, the miRCURY Hy3 power labeling kit (Exiqon, Vedbaek, Denmark) was used for the miRNA labeling of the two pooled total RNA groups according to the manufacturer's guidelines. Briefly, 1 μg of each sample was labeled using T4 RNA ligase in calf intestinal alkaline phosphatase (CIP) buffer and CIP (Exiqon). After stopping the labeling procedure, the Hy3-labeled samples were hybridized at 56°C overnight on the miRCURY LNA array (v.16.0) (Exiqon), containing probes for 1,223 human miRNAs, in a 12-bay hybridization system (NimbleGen Inc., Madison, WI). Following hybridization, the slides were washed several times using a wash buffer kit (Exiqon) and finally dried. Each miRNA spot was replicated four times on the same slide, and two microarray chips were used for each group.

Microarray data analysis.

The slides were scanned using an Axon GenePix 4000B microarray scanner (Axon Instruments, Foster City, CA). Scanned images then were imported into GenePix Pro 6.0 software (Axon) for grid alignment and data extraction. Signal intensities for each spot were scanned and calculated by subtracting background levels. miRNAs with intensities of >50 were chosen for calculating the median normalization factor. Expressed miRNA data were normalized using median normalization. After normalization, obtained average values for each miRNA spot were used for statistics. Finally, hierarchical clustering was performed to show distinguishable miRNAs using MEV software (v4.6; TIGR [The institute for Genomic Research]).

Real-time RT-PCR.

Stem-loop reverse transcription-PCR (RT-PCR) was performed to confirm the array results. Reverse transcriptase reaction mixtures contained 200 ng of purified total RNA, 20 nM stem-loop RT primer (primer sequence is available upon request), 1× RT buffer, 0.125 mM (each) dATP, dGTP, dCTP, and dTTP, 1 U/μl reverse transcriptase, and 0.6 U/μl RNase inhibitor. Using the Gene Amp PCR system 9700 (Applied Biosystems), 20-μl reaction mixtures were subjected to thermal cycling parameters of 30 min at 16°C, 40 min at 42°C, and 5 min at 85°C, and then they were held at 4°C. Each reaction mixture for real-time quantitative PCR contained 1× PCR buffer, 1.5 mM MgCl2, 0.25 mM (each) dATP, dGTP, dCTP, and dTTP, 1 U DNA polymerase, 0.4 μM each primer, 0.25× SYBR green I, 1 μl cDNA, and deionized water to a total volume of 25 μl. Reactions were run with the following thermal cycling parameters: 95°C for 5 min, followed by 45 cycles of 95°C for 10 s, 60°C for 20 s, and 72°C for 20 s. The threshold cycle (CT) was defined as the fractional cycle number at which the fluorescence passes the fixed threshold, and each sample was normalized on the basis of its endogenous U6 RNA content. The experiment was conducted in triplicate.

Pathway enrichment analysis.

Using TargetScan (http://www.targetscan.org), we obtained the list of genes predicted to be targeted by the identified miRNAs. The predicted miRNA target genes were analyzed for enriched KEGG pathways by using the NCBI DAVID server (http://david.abcc.ncifcrf.gov) with default settings (10).

ROC curve analysis.

To confirm that the pattern of specific differentially expressed miRNA is reproducible in independent participants, we performed a validation study using independent samples. Stem-loop RT-quantitative PCR was used to quantify the level of serum miR-29a. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic effect of miR-29a with the ROCR package (7). ROC curves were displayed as the true-positive rate (TPR) versus the false-positive rate (FPR). The area under the ROC curve (AUC), a measure of discrimination accuracy, was reported.

Statistical analysis.

Data are presented as means ± standard deviations (SD). Analysis of variance (ANOVA) tests or Student's t tests were used for statistical analysis. The data were regarded as significantly different at P < 0.05.

RESULTS

Differential expression of miRNAs between active TB and control groups.

By employing a highly sensitive, high-throughput, and specific miRCURY LNA microarray platform, miRNA expression profiles for the two groups were determined. After normalization, obtained average values for each miRNA spot were used for statistics. The ratio of active TB signal to control signal was calculated. A total of 1,223 miRNAs were detected, and 92 miRNAs with significantly altered expression were identified, of which 59 were overexpressed and 33 were underexpressed in the TB serum. miRNA expression in the TB serum compared to that in the control serum was increased on average by 3.06- to 258-fold but decreased by 2.56- to 50.0-fold (Tables 2 and and3).3). The P values for these 92 miRNAs were less than 0.05 in the TB sample compared to results for the control sample. Based on these differentially expressed miRNAs, a tree with a clear distinction between the active TB sample and the control sample was generated by cluster analysis (Fig. 1).

Table 2.
Upregulated miRNAs in TB serum
Table 3.
Downregulated miRNAs in TB serum
Fig. 1.
Hierarchical clustering of miRNA in serum. Samples were clustered according to the expression profile of 92 differentially expressed miRNAs. Data from each miRNA were median centered. Samples are in columns and miRNAs are in rows. Red indicates high relative ...

Validation of microarray results using real-time PCR. Because microarray results were derived from the pooled serum samples, to validate our microarray results, quantitative real-time RT-PCR analysis was further performed for the detection of miR-3125, miR-93*, and miR-29a using individual serum sample from the same 30 controls and 30 active TB cases.

The real-time PCR analysis was consistent with microarray data (Fig. 2): the expression of miR-3125 was present in lower abundance while miR-93* and miR-29a were present in higher abundance in the TB serum than in that of the healthy controls. At the same time, to validate whether there was consistency between serum and sputum, we also detected the expression of miR-93* and miR-29a in sputum. In particular, miR-29a also was present in higher abundance in TB sputum than in that of the healthy controls. There was, however, no significant difference for the sputum levels of miR-93* between TB patients and controls (Fig. 2).

Fig. 2.
Confirmation miRNA expression by quantitative real-time PCR. Quantitative real-time PCR analysis confirmed microarray data. After normalization to U6 RNA in each group, data were represented as the means ± SD (n = 30), and obtained average values ...

Bioinformatic exploratory analysis.

As the number of experimentally validated miRNA targets is limited, we used the widely used TargetScan algorithm to obtain the list of Entrez genes predicted to be targeted by the obtained miRNAs. We then used the NCBI DAVID server to identify the significantly enriched pathways in these conserved targets. As shown in Table 4, the acute-phase response pathway was one of the most enriched pathways. Pathways involved in inflammatory response, the regulation of cytoskeleton, and the homeostatic process also were significantly enriched in patient-control comparisons. This reassured the correctness of our approach and indicated the potentially important functional role of circulating miRNAs in active pulmonary tuberculosis infection.

Table 4.
Enriched pathways in the genes predicted to be targeted by differentially expressed microRNAs from comparisons of TB serum to control serum

Receiver operating characteristic analysis.

ROC analysis was performed to examine if circulating miR-29a could be used as a diagnostic biomarker for active pulmonary TB. Expression data for miR-29a in patient and control groups was used to build an ROC plot. Figure 3 shows that the AUC of miR-29a was 0.831, which reflected reasonable separation between the two groups.

Fig. 3.
Increased serum level of miR-29a for patients with active pulmonary TB versus healthy controls, with sensitivity of 83% and specificity of 80%, respectively.

DISCUSSION

The spectra and levels of some miRNAs could reflect altered physiological and pathological conditions. Mature miRNAs, single-stranded RNAs of about 22 nucleotides in length, originate from endogenous hairpin-shaped transcripts and have well-established roles in eukaryotic host responses to viruses and bacterial pathogens (11, 19, 20). For example, a recent study reported cell type-dependent miRNA regulation upon the infection of mammalian cells with the enteroinvasive pathogen Salmonella enterica serovar Typhimurium and suggested that miRNAs belonged to the first line of antibacterial defense (23).

It is estimated that one-third of the world population is latently infected with M. tuberculosis, and 5 to 10% of infected people will develop active pulmonary TB in their life time. miRNAs are stably present in human serum and offer unique opportunities for the early diagnosis of clinical conditions, such as lung diseases (18). The relationship between circulating miRNAs and TB infection has not been reported previously. Considering the biological relevance of miRNAs to bacterial infection and recent studies of circulating miRNAs in serum, we hypothesized that the serum miRNAs are novel biomarkers for the diagnosis and evaluation of active pulmonary TB infection.

The results of our present study clearly showed that 59 miRNAs were overexpressed and 33 were underexpressed in the active TB serum compared to their expression in the controls. miRNAs that have been proven to participate in the regulation of adaptive immune response, such as miR-150 and miR-155 (27, 30), were not found to be differentially expressed in the TB serum, and this suggested that other miRNAs are involved in the regulation of anti-TB immune responses. Only several differentially expressed miRNAs, such as miR-552, were determined to be involved in many different signaling pathways; however, functions of most differentially expressed miRNAs, such as miR-1470, miR-1280, miR-3125, and miR-380*, and their predicted target genes are largely unknown.

We chose miR-93* for further validation using real-time PCR, given that it was the most upregulated miRNA in active TB infection. miR-93* was found to be involved in promoting tumor growth by targeting the tumor suppressor gene Fus1 and integrin-β8 (4, 6). Previous study also demonstrated that host miR-93 could inhibit vesicular stomatitis virus replication by targeting large protein and phosphoprotein genes (21). Our results showed that miR-93* was the most upregulated miRNA in the active TB serum. These findings suggested that miR-93* also was involved in pathogen infections. miR-518d-5p, miR-520c-5p, and miR-526a were the most decreased miRNAs in the active TB serum compared to the levels of the controls. Until now, the functions of miR-518d-5p and miR-520c-5p were largely unknown. miR-526a was identified as being associated with pregnancy (14). Our results suggested that the miRNAs mentioned above also play important roles in TB infection, and the association between these miRNAs and active TB infection may need further research.

Many differentially expressed miRNAs, such as miR-194*, miR-143, miR-146b–5p, miR-769-5p, and miR-765, have been shown to be associated with the carcinogenesis of different organs and tissues (13, 14, 32). Besides being involved in carcinogenesis, miR-221* also was involved in infection and was decreased in epithelial cells in response to Cryptosporidium parvum infection (9). miR-511 was identified as a novel potent modulator of human immune response and as a positive regulator of Toll-like receptor 4 (28). Our results showed that levels of miR-221* and miR-511 were decreased 0.20- and 0.22-fold in the TB serum, respectively. However, functions of the other miRNAs with the most decreased levels in the TB serum still are unknown, such as miR-582-3p, miR-518c*, and miR-618. IL-6 is a pleiotropic cytokine that plays a central role in host defense. miR-365 is a direct negative regulator of IL-6 by binding the 3′UTR of IL-6 mRNA (31). Our results showed that miR-365 was increased 24.7-fold in the TB serum compared to its expression in the control serum. miR-375 has well-established roles in many tumors (29). Recently, circulating miR-375 was significantly upregulated in HBV infection (15). Our data showed that miR-375 increased 21.4-fold in the TB serum. These results suggested that miR-375 plays an important role in pathogen-host interactions. The miR-let-7 family is well known to regulate the apoptosis of cancer cells by targeting BCL2L1 (25). Recent studies also have shown that miR-let-7i can regulate immune responses against Cryptosporidium parvum infection (3). Our data showed that miR-let-7i and miR-let-7g were upregulated in the TB serum, which suggested that the let-7 family also was involved in the regulation of anti-TB immune response. Our results suggested that these miRNAs play important roles in TB infection, and further investigations are required to substantiate their functions in TB infection.

miR-29a was shown to directly target negative regulators of Wnt signaling, and Wnt was known to trigger macrophage inflammatory responses (12, 22). A recent study showed that miR-29a was specifically upregulated after the mycobacterial infection of human macrophages (24). The infection of mice with Listeria monocytogenes or Mycobacterium bovis bacillus Calmette-Guérin (BCG) downregulated miR-29 expression in IFN-γ-producing natural killer cells, CD4+ T cells, and CD8+ T cells. Moreover, miR-29 suppressed IFN-γ production by directly targeting IFN-γ mRNA (16). This was consistent with our data showing increased miR-29a (11.9- and 5.2-fold) in the TB serum and in the TB sputum, respectively, compared to the expression of the controls. These findings suggested that miR-29a plays an important role in anti-TB infections. To further evaluate the diagnostic value of miR-29a, we performed a more detailed analysis by ROC curve analysis. Data showed that miR-29a has great potential to serve as a marker for the detection of active pulmonary tuberculosis infection.

In addition, bioinformatic exploratory analysis predicted that these differentially expressed circulating miRNAs affect critical pathways conducive to active pulmonary tuberculosis infection, a potentially important mechanism warranting further investigation. As the miRNA target prediction algorithm is known to contain both false positives and false negatives and our pathway enrichment analysis is based on miRNA genes predicted to be targeted by circulating miRNAs, a full understanding of the potential functional role of circulating miRNAs can be established only by using functional experiments.

Taken together, we provided evidence, for the first time, that a significant change in the levels of serum miRNAs occurred in patients with active tuberculosis infection compared to the levels for healthy controls. The miRNA expression profiling may provide a useful clue for the pathophysiology research of active pulmonary TB and lead to finding their potential for improving diagnosis and prognosis and their effect on future therapeutic strategies. However, the molecular roles that these serum miRNAs play in TB infection are not completely understood at this time. Future studies and advanced technologies are needed to confirm our findings and further explore the existing potential of circulating miRNAs to be utilized clinically as novel biomarkers for active pulmonary TB as well as their mechanism in TB infection.

ACKNOWLEDGMENTS

This work was supported by grants from the National Science Foundation of China (30972639) and the Project of Shandong Province, Higher Educational Science and Technology Program of China (J09LF20).

The microarray experiments were performed by KangChen Bio-Tech, Shanghai, China.

Footnotes

[down-pointing small open triangle]Published ahead of print on 12 October 2011.

REFERENCES

1. Aigner A. 2011. MicroRNAs (miRNAs) in cancer invasion and metastasis: therapeutic approaches based on metastasis-related miRNAs. J. Mol. Med. (Berlin) 89: 445–457 [PubMed]
2. Ambros V. 2004. The functions of animal microRNAs. Nature 431: 350–355 [PubMed]
3. Chen X. M., Splinter P. L., O'Hara S. P., LaRusso N. F. 2007. A cellular micro-RNA, let-7i, regulates Toll-like receptor 4 expression and contributes to cholangiocyte immune responses against Cryptosporidium parvum infection. J. Biol. Chem. 282: 28929–28938 [PMC free article] [PubMed]
4. Du L., et al. 2009. miR-93, miR-98, and miR-197 regulate expression of tumor suppressor gene FUS1. Mol. Cancer Res. 7: 1234–1243 [PMC free article] [PubMed]
5. Dye C., Williams B. G. 2010. The population dynamics and control of tuberculosis. Science 328: 856–861 [PubMed]
6. Fang L., et al. 2011. MicroRNA miR-93 promotes tumor growth and angiogenesis by targeting integrin-β8. Oncogene 30: 806–821 [PubMed]
7. Filipowicz W., Bhattacharyya S. N., Sonenberg N. 2008. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat. Rev. 9: 102–114 [PubMed]
8. Gilad S., et al. 2008. Serum microRNAs are promising novel biomarkers. PLoS One 3: e3148. [PMC free article] [PubMed]
9. Gong A. Y., et al. 2011. MicroRNA-221 controls expression of intercellular adhesion molecule-1 in epithelial cells in response to Cryptosporidium parvum infection. Int. J. Parasitol. 41: 397–403 [PMC free article] [PubMed]
10. Huang D. W., et al. 2007. DAVID bioinformatics resources: expanded annotation database and novel algorithms to better extract biology from large gene lists. Nucleic Acids Res. 35: W169–W175 [PMC free article] [PubMed]
11. Ji F., et al. 2011. Circulating microRNAs in hepatitis B virus-infected patients. J. Viral Hepat. 18: e242–251 [PubMed]
12. Kapinas K., Kessler C., Ricks T., Gronowicz G., Delany A. M. 2010. miR-29 modulates Wnt signaling in human osteoblasts through a positive feedback loop. J. Biol. Chem. 285: 25221–25231 [PMC free article] [PubMed]
13. Katakowski M., et al. 2010. MiR-146b-5p suppresses EGFR expression and reduces in vitro migration and invasion of glioma. Cancer Investig. 28: 1024–1030 [PMC free article] [PubMed]
14. Kotlabova K., Doucha J., Hromadnikova I. 2011. Placental-specific microRNA in maternal circulation-identification of appropriate pregnancy-associated microRNAs with diagnostic potential. J. Reprod. Immunol. 89: 185–191 [PubMed]
15. Li L. M., et al. 2010. Serum microRNA profiles serve as novel biomarkers for HBV infection and diagnosis of HBV-positive hepatocarcinoma. Cancer Res. 70: 9798–9807 [PubMed]
16. Ma F., et al. 2011. The microRNA miR-29 controls innate and adaptive immune responses to intracellular bacterial infection by targeting interferon-γ. Nat. Immunol. 12: 861–869 [PubMed]
17. Mitchell P. S., et al. 2008. Circulating microRNAs as stable blood-based markers for cancer detection. Proc. Natl. Acad. Sci. U. S. A. 105: 10513–10518 [PMC free article] [PubMed]
18. Nana-Sinkam S. P., et al. 2009. Integrating the MicroRNome into the study of lung disease. Am. J. Respir. Crit. Care Med. 179: 4–10 [PMC free article] [PubMed]
19. Navarro L., et al. 2006. A plant miRNA contributes to antibacterial resistance by repressing auxin signaling. Science 312: 436–439 [PubMed]
20. Oertli M., et al. 2011. MicroRNA-155 is essential for the T cell-mediated control of helicobacter pylori infection and for the induction of chronic gastritis and colitis. J. Immunol. 187: 3578–3586 [PubMed]
21. Otsuka M., et al. 2007. Hypersusceptibility to vesicular stomatitis virus infection in Dicer1-deficient mice is due to impaired miR24 and miR93 expression. Immunity 27: 123–134 [PubMed]
22. Pereira C. P., Bachli E. B., Schoedon G. 2009. The wnt pathway: a macrophage effector molecule that triggers inflammation. Curr. Atheroscler. Rep. 11: 236–242 [PubMed]
23. Schulte L. N., Eulalio A., Mollenkopf H. J., Reinhardt R., Vogel J. 2011. Analysis of the host microRNA response to Salmonella uncovers the control of major cytokines by the let-7 family. EMBO J. 30: 1977–1989 [PMC free article] [PubMed]
24. Sharbati J., et al. 2011. Integrated microRNA-mRNA-analysis of human monocyte derived macrophages upon Mycobacterium avium subsp. hominissuis infection. PLoS One 6: e20258. [PMC free article] [PubMed]
25. Shimizu S., et al. 2010. The let-7 family of microRNAs inhibits Bcl-xL expression and potentiates sorafenib-induced apoptosis in human hepatocellular carcinoma. J. Hepatol. 52: 698–704 [PubMed]
26. Stefani G., Slack F. J. 2008. Small non-coding RNAs in animal development. Nat. Rev. Mol. Cell Biol. 9: 219–230 [PubMed]
27. Thai T. H., et al. 2007. Regulation of the germinal center response by microRNA-155. Science 316: 604–608 [PubMed]
28. Tserel L., et al. 2011. MicroRNA expression profiles of human blood monocyte-derived dendritic cells and macrophages reveal miR-511 as putative positive regulator of Toll-like receptor 4. J. Biol. Chem. 286: 26487–26495 [PMC free article] [PubMed]
29. Tsukamoto Y., et al. 2010. MicroRNA-375 is downregulated in gastric carcinomas and regulates cell survival by targeting PDK1 and 14-3-3zeta. Cancer Res. 70: 2339–2349 [PubMed]
30. Xiao C., et al. 2007. MiR-150 controls B cell differentiation by targeting the transcription factor c-Myb. Cell 131: 146–159 [PubMed]
31. Xu Z., et al. 2011. miR-365, a novel negative regulator of interleukin-6 gene expression, is cooperatively regulated by Sp1 and NF-κB. J. Biol. Chem. 286: 21401–21412 [PMC free article] [PubMed]
32. Xu B., et al. 2011. miR-143 decreases prostate cancer cells proliferation and migration and enhances their sensitivity to docetaxel through suppression of KRAS. Mol. Cell. Biochem. 350: 207–213 [PubMed]

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