Skip to main content

Advertisement

Log in

Dysregulated expression of microRNAs in aqueous humor from intraocular tuberculosis patients

Molecular Biology Reports Aims and scope Submit manuscript

Abstract

Background

Systemic Mycobacterium tuberculosis (Mtb) infection alters microRNA’s expression that controls cellular processes and modulates host defense mechanisms. However, the role of miRNAs in intraocular tuberculosis (IOTB) remains unknown. Therefore, this study aims to identify dysregulated miRNAs in the aqueous humor (AH) of patients with IOTB.

Methods

AH from intraocular tuberculosis patients (n = 2) and cataract controls (n = 2) were used for small RNA deep sequencing using HiSeq Illumina sequencing platform. Differentially expressed miRNAs and their targets were identified by the bioinformatics approach, and their regulatory functions were predicted by pathway enrichment analysis. The expression of selected miRNAs and their binding targets were further validated by real-time quantitative PCR (RT-qPCR).

Results

In total, we identified 56 differentially expressed miRNAs in the AH of intraocular tuberculosis (IOTB) patients compared to controls. We selected four significantly dysregulated miRNAs (miR-423-5p, miR-328-3p, miR-21-5p, and miR-16-5p) based on the RT-qPCR validation and predicted their gene targets. We developed a miRNA-targets regulatory network by combining pathways of interest and genes associated with TB. We identified that these four miRNAs might play an important role in IOTB pathogenesis via tuberculosis-associated pathways; PI3K-Akt signaling, autophagy and MAPK pathway.

Conclusions

For the first time, this study identifies the dysregulation of four miRNAs in the AH of IOTB patients using the ultra-low input small-RNA sequencing approach. Further target prediction and validation identify the role of these miRNAs in tuberculosis pathogenesis via tuberculosis-related pathways. This study identifies miRNAs as potentially ideal biomarkers in the aqueous humor of IOTB patients.

Graphic abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (France)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Data availability

All data generated during this study are included in this article and its additional files.

Abbreviations

AH:

Aqueous humor

Mtb :

Mycobacterium tuberculosis

IOTB:

Intraocular tuberculosis

PCR:

Polymerase chain reaction

miRNA:

MicroRNA

TB:

Tuberculosis

HIV:

Human immunodeficiency virus

LTB:

Latent tuberculosis

NGS:

Next generation sequencing

OTB:

Ocular tuberculosis

PTB:

Pulmonary tuberculosis

DNA:

Deoxyribonucleic acid

CAT:

Cataract

RNA:

Ribonucleic acid

STAR:

Spliced transcripts alignment to a reference

DAVID:

Database for annotation, visualization, and integrated discovery

FDR:

False discovery rate

P-value:

Calculated probability

KEGG:

Kyoto encyclopedia of genes and genomes

cDNA:

Complementary DNA

SRA:

Sequence read archive

ATT:

Anti-tuberculosis therapy

DE:

Differential expression

TST:

Tuberculin skin test

CT:

Computerized tomography

MAPK9:

Mitogen-activated protein kinase 9

VPS33A:

Vacuolar protein sorting-associated protein 33A

IL-1B:

Interleukin 1 beta

CREB1:

Cyclic AMP-responsive element-binding protein 1

CTSD:

Catepsin D

CEBPB:

CCAAT/enhancer-binding protein beta

RAB5B:

Ras-related protein Rab-5B

SRC:

Proto-oncogene tyrosine-protein kinase Src

APAF1:

Apoptotic protease- activating factor 1

IRAK2:

Interleukin-1 receptor-associated kinase-like 2

MRC2:

Mannose receptor, C type 2

CD209:

DC-SIGN

ATP6VOD1:

V-ATPase

References

  1. Carranza C, Pedraza-Sanchez S, de Oyarzabal-Mendez E, Torres M (2020) Diagnosis for latent tuberculosis infection: new alternatives. Front Immunol 10(11):2006. https://doi.org/10.3389/fimmu.2020.02006

    Article  CAS  Google Scholar 

  2. Gopalaswamy R, Dusthackeer VNA, Kannayan S, Subbian S (2021) Extrapulmonary tuberculosis: an update on the diagnosis treatment and drug resistance. J Respir 1(2):141–164. https://doi.org/10.3390/jor1020015

    Article  Google Scholar 

  3. Mahdavi Fard A, Sorkhabi R, Tajlil A (2015) Extrapulmonary tuberculosis presenting with isolated Uveitis. Iran J Public Health 44(12):1720–1722

    PubMed  PubMed Central  Google Scholar 

  4. Shakarchi FI (2015) Ocular tuberculosis: current perspectives. Clin Ophthalmol 9:2223–2227. https://doi.org/10.2147/OPTH.S65254

    Article  PubMed  PubMed Central  Google Scholar 

  5. Testi I, Agrawal R, Mehta S, Basu S, Nguyen Q, Pavesio C, Gupta V (2020) Ocular tuberculosis: where are we today? Indian J Ophthalmol 68(9):1808–1817. https://doi.org/10.4103/ijo.IJO_1451_20

    Article  PubMed  PubMed Central  Google Scholar 

  6. Dalvin LA, Smith WM (2017) Intraocular manifestations of mycobacterium tuberculosis: a review of the literature. J Clin Tuberc Other Mycobact Dis 7:13–21. https://doi.org/10.1016/j.jctube.2017.01.003

    Article  PubMed  PubMed Central  Google Scholar 

  7. Papaliodis G (2017) Uveitis: a practical guide to the diagnosis and treatment of intraocular inflammation. Springer, Cham

    Book  Google Scholar 

  8. Muralidharan B, Lalitha P, Arya LK, Rathinam S (2017) Polymerase chain reaction and its correlation with clinical features and treatment response in tubercular Uveitis. Ocul Immunol Inflamm 26:1–8. https://doi.org/10.1080/09273948.2017.1287925

    Article  CAS  Google Scholar 

  9. Nouailles G, Dorhoi A, Koch M, Zerrahn J, Weiner J 3rd, Faé KC, Arrey F, Kuhlmann S, Bandermann S, Loewe D, Mollenkopf HJ, Vogelzang A, Meyer-Schwesinger C, Mittrücker HW, McEwen G, Kaufmann SH (2014) CXCL5-secreting pulmonary epithelial cells drive destructive neutrophilic inflammation in tuberculosis. J Clin Invest 124(3):1268–1282. https://doi.org/10.1172/JCI72030

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Mehrotra P, Jamwal SV, Saquib N, Sinha N, Siddiqui Z, Manivel V, Chatterjee S, Rao KV (2014) Pathogenicity of Mycobacterium tuberculosis is expressed by regulating metabolic thresholds of the host macrophage. PLoS Pathog 10(7):e1004265. https://doi.org/10.1371/journal.ppat.1004265

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. de Martino M, Lodi L, Galli L, Chiappini E (2019) Immune response to Mycobacterium tuberculosis: a narrative review. Front Pediatr 7:350. https://doi.org/10.3389/fped.2019.00350

    Article  PubMed  PubMed Central  Google Scholar 

  12. Han S, Jhun B, Kim S-Y, Moon S, Yang B, Kwon OJ, Daley C, Shin S, Koh W-J (2020) miRNA expression profiles and potential as biomarkers in nontuberculous mycobacterial pulmonary disease. Sci Rep. https://doi.org/10.1038/s41598-020-60132-0

    Article  PubMed  PubMed Central  Google Scholar 

  13. Behrouzi A, Alimohammadi M, Nafari A, Yousefi MH, Rad F, Vaziri F, Siadat SD (2019) The role of host miRNAs on Mycobacterium tuberculosis. ExRNA. https://doi.org/10.1186/s41544-019-0040-y

    Article  Google Scholar 

  14. Philips J, Ernst J (2011) Tuberculosis pathogenesis and immunity. Annu Rev Pathol 7:353–384. https://doi.org/10.1146/annurev-pathol-011811-132458

    Article  CAS  PubMed  Google Scholar 

  15. Furci L, Schena E, Miotto P, Cirillo D (2013) Alteration of human macrophages microRNA expression profile upon infection with Mycobacterium tuberculosis. Int J Mycobacteriol 2:128–134. https://doi.org/10.1016/j.ijmyco.2013.04.006

    Article  PubMed  Google Scholar 

  16. Ahmad S (2011) Pathogenesis, immunology, and diagnosis of latent Mycobacterium tuberculosis infection. Clin Dev Immunol 2011:814943. https://doi.org/10.1155/2011/814943

    Article  CAS  PubMed  Google Scholar 

  17. Zhang X, Zhu M, Hu X (2018) Integrated miRNA and mRNA expression profiling to identify mRNA targets of dysregulated miRNAs in pulmonary tuberculosis. Epigenomics 10(8):1051–1069. https://doi.org/10.2217/epi-2018-0028

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Zhang X, Huang T, Wu Y, Peng W, Xie H, Pan M, Zhou H, Cai B, Wu Y (2017) Inhibition of the PI3K-Akt-mTOR signaling pathway in T lymphocytes in patients with active tuberculosis. Int J Infect Dis 59:110–117. https://doi.org/10.1016/j.ijid.2017.04.004

    Article  CAS  PubMed  Google Scholar 

  19. Sinigaglia A, Peta E, Riccetti S, Venkateswaran S, Manganelli R, Barzon L (2020) Tuberculosis-associated MicroRNAs: from pathogenesis to disease biomarkers. Cells 9(10):2160. https://doi.org/10.3390/cells9102160

    Article  CAS  PubMed Central  Google Scholar 

  20. Wang C, Yang S, Sun G, Tang X, Lu S, Neyrolles O, Gao Q (2011) Comparative miRNA expression profiles in individuals with latent and active tuberculosis. PLoS ONE 6(10):e25832–e25832. https://doi.org/10.1371/journal.pone.0025832

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ollar R (2018) Application of microRNA markers for early detection of latent tuberculosis transitioning to active tuberculosis. J Mahatma Gandhi Inst Med Sci 23:5–6. https://doi.org/10.4103/jmgims.jmgims_4_18

    Article  Google Scholar 

  22. Liu C-H, Huang S, Britton WR, Chen J (2020) MicroRNAs in vascular eye diseases. Int J Mol Sci 21(2):649. https://doi.org/10.3390/ijms21020649

    Article  CAS  PubMed Central  Google Scholar 

  23. Azhwar R, Perumal E (2015) Micro-RNAs and their roles in eye disorders. Ophthalmic Res 53:169–186. https://doi.org/10.1159/000371853

    Article  CAS  Google Scholar 

  24. Drewry M, Helwa I, Allingham RR, Hauser M, Liu Y (2016) miRNA profile in three different normal human ocular tissues by miRNA-seq. Investig Opthalmol Vis Sci 57:3731. https://doi.org/10.1167/iovs.16-19155

    Article  CAS  Google Scholar 

  25. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR (2013) STAR: ultrafast universal RNA-seq aligner. Bioinformatics (Oxford, England) 29(1):15–21. https://doi.org/10.1093/bioinformatics/bts635

    Article  CAS  Google Scholar 

  26. Li X, Cooper NG, O’Toole TE, Rouchka EC (2020) Choice of library size normalization and statistical methods for differential gene expression analysis in balanced two-group comparisons for RNA-seq studies. BMC Genomics 21(1):1–7

    Article  Google Scholar 

  27. Tarazona S, Furió-Tarí P, Turrà D, Pietro AD, Nueda MJ, Ferrer A, Conesa A (2015) Data quality aware analysis of differential expression in RNA-seq with NOISeq R/Bioc package. Nucleic Acids Res 43(21):e140–e140. https://doi.org/10.1093/nar/gkv711

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Sticht C, De La Torre C, Parveen A, Gretz N (2018) miRWalk: an online resource for prediction of microRNA binding sites. PLoS ONE 13(10):e0206239–e0206239. https://doi.org/10.1371/journal.pone.0206239

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Jiao X, Sherman BT, Huang DW, Stephens R, Baseler MW, Lane HC, Lempicki RA (2012) DAVID-WS: a stateful web service to facilitate gene/protein list analysis. Bioinformatics (Oxford, England) 28(13):1805–1806. https://doi.org/10.1093/bioinformatics/bts251

    Article  CAS  Google Scholar 

  30. Raudvere U, Kolberg L, Kuzmin I, Arak T, Adler P, Peterson H, Vilo J (2019) g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update). Nucleic Acids Res 47(W1):W191–W198. https://doi.org/10.1093/nar/gkz369

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Wu L, Lee S-W, Huang K-Y, Lee T-Y, Hsu P, Weng J (2014) Systematic expression profiling analysis identifies specific MicroRNA-gene interactions that may differentiate between active and latent tuberculosis infection. BioMed Res Int 2014:895179. https://doi.org/10.1155/2014/895179

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Tu H, Yang S, Jiang T, Wei L, Shi L, Liu C, Wang C, Huang H, Hu Y, Chen Z et al (2019) Elevated pulmonary tuberculosis biomarker miR-423-5p plays critical role in the occurrence of active TB by inhibiting autophagosome-lysosome fusion. Emerg Microbes Infect 8(1):448–460. https://doi.org/10.1080/22221751.2019.1590129

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Kumar R, Halder Dey P, Sahu S, Kumar M, Kumari M, Jana K, Ghosh Z, Sharma P, Kundu M, Basu J (2012) Identification of a novel role of ESAT-6-dependent miR-155 induction during infection of macrophages with Mycobacterium tuberculosis. Cell Microbiol 14:1620–1631. https://doi.org/10.1111/j.1462-5822.2012.01827.x

    Article  CAS  PubMed  Google Scholar 

  34. Delgobo M, Mendes DA, Kozlova E, Rocha EL, Rodrigues-Luiz GF, Mascarin L, Dias G, Patrício DO, Dierckx T, Bicca MA et al (2019) An evolutionary recent IFN/IL-6/CEBP axis is linked to monocyte expansion and tuberculosis severity in humans. Elife 8:e47013. https://doi.org/10.7554/eLife.47013

    Article  PubMed  PubMed Central  Google Scholar 

  35. Killick K, Cheallaigh C, O’Farrelly C, Hokamp K, Machugh D, Harris J (2013) Receptor-mediated recognition of mycobacterial pathogens. Cell Microbiol 15(9):1484–1495. https://doi.org/10.1111/cmi.12161

    Article  CAS  PubMed  Google Scholar 

  36. Goyal S, Klassert T, Slevogt H (2016) C-type lectin receptors in tuberculosis: what we know. Med Microbiol Immunol 205(6):513–535. https://doi.org/10.1007/s00430-016-0470-1

    Article  CAS  PubMed  Google Scholar 

  37. Lu N, Zhou Z (2012) Membrane trafficking and phagosome maturation during the clearance of apoptotic cells. Int Rev Cell Mol Biol 293:269–309. https://doi.org/10.1016/b978-0-12-394304-0.00013-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Wen A, Sakamoto K, Miller L (2010) The role of the transcription factor CREB in immune function. J Immunol (Baltimore, MD: 1950) 185:6413–6419. https://doi.org/10.4049/jimmunol.1001829

    Article  CAS  Google Scholar 

  39. Liu Y, Guo Y-L, Zhou S-J, Liu F, Du F-J, Zheng X-J, Jia H-Y, Zhang Z-D (2010) CREB is a positive transcriptional regulator of gamma interferon in latent but not active tuberculosis infections. Clin Vaccine immunol 17(9):1377–1380. https://doi.org/10.1128/cvi.00242-10

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Gottipati S, Rao N, Fung-Leung W-P (2008) IRAK1: A critical signaling mediator of innate immunity. Cell Signal 20:269–276. https://doi.org/10.1016/j.cellsig.2007.08.009

    Article  CAS  PubMed  Google Scholar 

  41. Karim A, Chandra P, Chopra A, Siddiqui Z, Bhaskar A, Singh A, Kumar D (2011) Express path analysis identifies a tyrosine kinase src-centric network regulating divergent host responses to Mycobacterium tuberculosis infection. J Biol Chem 286:40307–40319. https://doi.org/10.1074/jbc.M111.266239

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Cardona P, Cardona PJ (2019) Regulatory T cells in Mycobacterium tuberculosis infection. Front Immunol 10:2139. https://doi.org/10.3389/fimmu.2019.02139

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Liu CH, Liu H, Ge B (2017) Innate immunity in tuberculosis: host defense vs pathogen evasion. Cell Mol Immunol 14(12):963–975. https://doi.org/10.1038/cmi.2017.88

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Srinivasan L, Ahlbrand S, Briken V (2014) Interaction of Mycobacterium tuberculosis with host cell death pathways. Cold Spring Harb Perspect Med 4(8):a022459. https://doi.org/10.1101/cshperspect.a022459

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Rapanoel H, Mazandu G, Mulder N (2013) Predicting and analyzing interactions between Mycobacterium tuberculosis and its human host. PLoS ONE 8:e67472. https://doi.org/10.1371/journal.pone.0067472

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Lachmandas E, Thiem K, Heuvel C, Hijmans A, Galan B, Tack C, Netea M, Van Crevel R, van Diepen J (2018) Patients with type 1 diabetes mellitus have impaired IL-1β production in response to Mycobacterium tuberculosis. Eur J Clin Microbiol Infect Dis 37(2):371–380. https://doi.org/10.1007/s10096-017-3145-y

    Article  CAS  PubMed  Google Scholar 

  47. Lou SM, Montgomery PA, Larkin KL, Winthrop K, Zierhut M, Rosenbaum JT, Group USS (2015) Diagnosis and treatment for ocular tuberculosis among uveitis specialists: the international perspective. Ocul Immunol Inflamm 23(1):32–39. https://doi.org/10.3109/09273948.2014.994784

    Article  PubMed  Google Scholar 

  48. Khan F (2020) Role of fiberoptic bronchoscopy in the rapid diagnosis of sputum smear-negative disseminated tuberculosis with pulmonary miliary infiltrates. Oman Med J 35:514–518. https://doi.org/10.5001/omj.2020.05

    Article  Google Scholar 

  49. Hashimoto S, Zhao H, Hayakawa M, Nakajima K, Taguchi Y, Murakami Y (2020) Developing a diagnostic method for latent tuberculosis infection using circulating miRNA. Transl Med Commun 5(1):1–7. https://doi.org/10.1186/s41231-020-00078-7

    Article  Google Scholar 

  50. Wagh V, Urhekar A, Modi D (2016) Levels of microRNA miR-16 and miR-155 are altered in serum of patients with tuberculosis and associate with responses to therapy. Tuberculosis 102:24–30. https://doi.org/10.1016/j.tube.2016.10.007

    Article  CAS  PubMed  Google Scholar 

  51. Zhao Z, Hao J, Li X, Chen Y, Qi X (2019) MiR-21-5p regulates mycobacterial survival and inflammatory responses by targeting Bcl-2 and TLR4 in Mycobacterium tuberculosis-infected macrophages. FEBS Lett 593(12):1326–1335. https://doi.org/10.1002/1873-3468.13438

    Article  CAS  PubMed  Google Scholar 

  52. Bonilla-Muro M, Cruz O, Gonzalez-Barrios J, Alcaraz L, Castañón-Arreola M (2019) EsxA mainly contributes to the miR-155 overexpression in human monocyte-derived macrophages and potentially affect the immune mechanism of macrophages through miRNA dysregulation. J Microbiol Immunol Infect 54(2):185–192. https://doi.org/10.1016/j.jmii.2019.07.007

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The authors thank the Uvea Clinic, Aravind Eye Hospital, Madurai, India, for the IOTB samples, and Dr. Madhu Shekar, Aravind Eye Hospital, for cataract control samples. We also thank Department of Biotechnology (DBT), India for funding support and Indian Council of Medical Research (ICMR), India for Senior Research Fellowship.

Funding

Department of Biotechnology, India (No: BT/PR20733/MED/29/1075/2016), Senior Research Fellow -Indian Council of Medical Research (ICMR), India (Sanction letter No. 2019-4013/Gen-BMS dt.30.09.2019).

Author information

Authors and Affiliations

Authors

Contributions

SC: Data curation, Formal analysis, Writing- Original draft preparation KK: NGS data analysis, Reviewing PL: Reviewing and Editing RS: Resources, Investigation, Reviewing and Editing BD: Conceptualization, Methodology, Writing- Reviewing and Editing.

Corresponding author

Correspondence to Bharanidharan Devarajan.

Ethics declarations

Conflict of interest

All the authors declared that they have no conflict of interest.

Ethical approval

This study was approved by the Institutional Ethics Committee of Aravind Eye Hospital, Madurai, Tamil Nadu, India (IRB2017007BAS).

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

11033_2021_6846_MOESM1_ESM.tif

Supplementary file1 (TIF 204 kb). Additional file 1: Supplementary Figure S1. The expression analysis of selected thirteen miRNAs in aqueous humor of IOTB patients (N=7) and Cataract controls (N=7) using RT-qPCR. Median values are showed in horizontal lines using a Mann-Whitney test. *P<0.05, ** P<0.01, *** P<0.001

11033_2021_6846_MOESM2_ESM.tif

Supplementary file2 (TIF 372 kb). Additional file 2: Supplementary Figure S2. The expression analysis of selected miRNA’s targets genes in aqueous humor of IOTB patients (N=5) and Cataract controls (N=6) using RT-qPCR. Median values are shown by horizontal lines using a Mann-Whitney test. *P<0.05, ** P<0.01

11033_2021_6846_MOESM3_ESM.docx

Supplementary file3 (DOCX 16 kb). Additional file 3: Supplementary Table S1. Patient details of Intraocular tuberculosis and Cataract controls

Supplementary file4 (DOCX 43 kb). Additional file 4: Supplementary Table S2. List of primers used for RT-qPCR analysis

11033_2021_6846_MOESM5_ESM.docx

Supplementary file5 (DOCX 13 kb). Additional file 5: Supplementary Table S3. Summary statistics of small-RNA deep sequencing of two IOTB and cataract controls

Supplementary file6 (XLSX 28 kb). Additional file 6: Supplementary Table S4: List of MiRNAs detected in NGS data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chadalawada, S., Kathirvel, K., Lalitha, P. et al. Dysregulated expression of microRNAs in aqueous humor from intraocular tuberculosis patients. Mol Biol Rep 49, 97–107 (2022). https://doi.org/10.1007/s11033-021-06846-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11033-021-06846-4

Keywords

Navigation