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Detection of microRNAs expression signatures in vitreous humor of intraocular tuberculosis

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Abstract

Background

MicroRNA (miRNA) expression analysis has been shown to provide them as biomarkers in several eye diseases and has a regulatory role in pathogenesis. However, miRNA expression analysis in the vitreous humor (VH) of intraocular tuberculosis (IOTB) is not studied. Thus, we aim to find miRNA expression signatures in the VH of IOTB patients to identify their regulatory role in disease pathogenesis and to find them as potential biomarkers for IOTB.

Methods and results

First, we profiled miRNAs in VH of three IOTB and three Macular hole (MH) samples as controls through small-RNA deep sequencing using Illumina Platform. In-house bioinformatics analysis identified 81 dysregulated miRNAs in IOTB. Further validation in VH of IOTB (n = 15) compared to MH (n = 15) using Real-Time quantitative PCR (RT-qPCR) identified three significantly upregulated miRNAs, hsa-miR-150-5p, hsa-miR-26b-5p, and hsa-miR-21-5p. Based on the miRNA target prediction, functional network analysis, and RT-qPCR analysis of target genes, the three miRNAs downregulating WNT5A, PRKCA, MAP3K7, IL7, TGFB2, IL1A, PRKCB, TNFA, and TP53 genes involving MAPK signaling pathway, PI3K-AKT signaling pathway, WNT signaling pathway, Cell cycle, TGF-beta signaling pathway, Long-term potentiation, and Sphingolipid signaling pathways, have a potential role in disease pathogenesis. The ROC analysis of RT-qPCR data showed that hsa-miR-150-5p with AUC = 0.715, hsa-miR-21-5p with AUC = 0.789, and hsa-miR-26b-5p with AUC = 0.738; however, the combination of hsa-miR-21-5p and hsa-miR-26b-5p with AUC = 0.796 could serve as a potential biomarker for IOTB.

Conclusions

This study provides the first report on miRNA expression signatures detected in VH for IOTB pathogenesis and also provides a potential biomarker for IOTB.

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Data Availability

The data is available upon request from authors.

Abbreviations

OTB:

Ocular Tuberculosis

Mtb :

Mycobacterium tuberculosis

ETB:

Extrapulmonary tuberculosis

TB:

Tuberculosis

ATT:

Anti-tuberculosis therapy

PPD:

Purified protein derivative

IGRA:

Interferon-gamma release assay

NAAT:

Nucleic acid amplification test

AH:

Aqueous humor

VH:

Vitreous humor

IL:

6-Interleukin-6

CXCL8:

C-X-C Motif Chemokine Ligand 8

IL:

8- Interleukin-8

CXCL9:

C-X-C Motif Chemokine Ligand 9

CXCL10:

C-X-C Motif Chemokine Ligand 10

ESAT:

6- Early secretory antigenic 6 kDa

CFP:

10-Culture filtrate protein 10

CXCL13:

C-X-C Motif Chemokine Ligand 13

CCL17:

CC motif chemokine ligand 17

IL:

17- Interleukin-17

IOTB:

Intraocular tuberculosis

PCR:

Polymerase chain reaction

BD:

Becton Dickinson

MH:

Macular hole

RT:

Room temperature

FTMH:

Full-thickness macular hole

RNA:

Ribonucleic acid

DNA:

Deoxy ribonucleic acid

cDNA:

complementary DNA

STAR:

Spliced transcripts alignment to a reference

GRCh38:

Genome reference consortium human build 38

DE:

Differential expression

TMM:

Trimmed mean of M-values

FC:

Fold change

CPM:

Counts per million

ROC curve:

Receiver operating characteristic curve

RT:

qPCR-Real time quantitative PCR

ACTB:

β-Actin

DAVID:

Database for Annotation, Visualization, and Integrated Discovery

KEGG:

Kyoto Encyclopedia of Genes and Genomes

FDR:

False Discovery Rate

MPB64:

Mannose binding protein 64

miRNA:

MicroRNA

MAPK:

Mitogen-activated protein kinase

TGFB:

Transforming growth factor beta

WNT:

Wingless-related integration site

PI3K:

Akt- phosphoinositide-3-kinase-protein kinase B

TP53:

Tumor protein 53

IL:

1A-Interleukin-1A

PRKCB:

Protein Kinase C beta

PRKCA:

Protein Kinase C Alpha

MAP3K7:

Mitogen-activated protein kinase kinase kinase 7

IL:

7-Interleukin-7

TNFα or TNFA:

Tumor necrosis factor alpha

WNT5A:

WNT family member 5A

AUC:

Area under the ROC curve

CI:

Confidence interval

MPT53:

Mycobacterium protein tuberculosis 53

IFNɣ:

Interferon ɣ

References

  1. Neuhouser AJ, Sallam A (2023) Ocular tuberculosis. StatPearls Treasure Island (FL) ineligible companies. Ahmed Sallam declares no relevant financial relationships with ineligible companies, Disclosure

    Google Scholar 

  2. Moule MG, Cirillo JD (2020) Mycobacterium tuberculosis Dissemination plays a critical role in Pathogenesis. Front Cell Infect Microbiol 10:65. https://doi.org/10.3389/fcimb.2020.00065

    Article  PubMed  PubMed Central  Google Scholar 

  3. Lin CJ, Hsia NY, Hwang DK, Hwang YS, Chang YC, Lee YC, Hsu YR, Yeh PT, Lin CP, Chen HF et al (2022) Clinical Manifestations and Outcomes of Tubercular Uveitis in Taiwan-A ten-year Multicenter Retrospective Study. Med (Kaunas) 58(3):376. https://doi.org/10.3390/medicina58030376

    Article  Google Scholar 

  4. 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 

  5. Chawla R, Singh MK, Singh L, Shah P, Kashyap S, Azad S, Venkatesh P, Sen S (2022) Tubercular DNA PCR of ocular fluids and blood in cases of presumed ocular tuberculosis: a pilot study. Ther Adv Ophthalmol 14:25158414221123522. https://doi.org/10.1177/25158414221123522

    Article  PubMed  PubMed Central  Google Scholar 

  6. Ang M, Cheung G, Vania M, Chen J, Yang H, Li J, Chee SP (2012) Aqueous cytokine and chemokine analysis in uveitis associated with tuberculosis. Mol Vis 18:565–573

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Alam A, Imam N, Ahmed MM, Tazyeen S, Tamkeen N, Farooqui A, Malik M, Ishrat R (2019) Identification and classification of differentially expressed genes and Network Meta-Analysis reveals potential Molecular Signatures Associated with Tuberculosis. Front Genet 10:932. https://doi.org/10.3389/fgene.2019.00932

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Alam K, Sharma G, Forrester JV, Basu S (2023) Antigen-Specific intraocular cytokine responses distinguish ocular tuberculosis from undifferentiated uveitis in tuberculosis-immunoreactive patients. Am J Ophthalmol 246:31–41. https://doi.org/10.1016/j.ajo.2022.08.029

    Article  CAS  PubMed  Google Scholar 

  9. Bansal R, Khan MM, Dasari S, Verma I, Goodlett DR, Manes NP, Nita-Lazar A, Sharma SP, Kumar A, Singh N (2021) Proteomic profile of vitreous in patients with tubercular uveitis. Tuberculosis (Edinb) 126:102036. https://doi.org/10.1016/j.tube.2020.102036

    Article  CAS  PubMed  Google Scholar 

  10. Hutchinson PE, Kee AR, Agrawal R, Yawata N, Tumulak MJ, Connolly JE, Chee SP, Siak J (2021) Singapore Ocular Tuberculosis Immunity Study (SPOTIS): role of T-lymphocyte profiling in patients with presumed ocular tuberculosis. Ocul Immunol Inflamm 29(7–8):1489–1495. https://doi.org/10.1080/09273948.2020.1767791

    Article  CAS  PubMed  Google Scholar 

  11. Chadalawada S, Kathirvel K, Lalitha P, Rathinam S, Devarajan B (2022) Dysregulated expression of microRNAs in aqueous humor from intraocular tuberculosis patients. Mol Biol Rep 49:1–11. https://doi.org/10.1007/s11033-021-06846-4

    Article  CAS  Google Scholar 

  12. Mammadzada P, Bayle J, Gudmundsson J, Kvanta A, Andre H (2019) Identification of Diagnostic and Prognostic microRNAs for recurrent vitreous hemorrhage in patients with proliferative Diabetic Retinopathy. J Clin Med 8(12):2217. https://doi.org/10.3390/jcm8122217

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Toro M, Reibaldi M, Avitabile T, Bucolo C, Salomone S, Rejdak R, Nowomiejska K, Tripodi S, Posarelli C, Ragusa M et al (2020) MicroRNAs in the vitreous humor of patients with retinal detachment and a different grading of proliferative vitreoretinopathy: a pilot study MicroRNAs and proliferative vitreoretinopathy. Transl Vis Sci Technol 9(6):23. https://doi.org/10.1167/tvst.9.6.23

    Article  PubMed  PubMed Central  Google Scholar 

  14. Kot A, Kaczmarek R (2022) Exosomal miRNA profiling in vitreous humor in proliferative Diabetic Retinopathy. Cells 12(1):123. https://doi.org/10.3390/cells12010123

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Bansal R, Dogra M, Chawla R, Kumar A (2020) Pars plana vitrectomy in uveitis in the era of microincision vitreous surgery. Indian J Ophthalmol 68(9):1844–1851. https://doi.org/10.4103/ijo.IJO_1625_20

    Article  PubMed  PubMed Central  Google Scholar 

  16. Gupta A, Bansal R, Gupta V, Sharma A, Bambery P (2010) Ocular signs predictive of tubercular uveitis. Am J Ophthalmol 149(4):562–570. https://doi.org/10.1016/j.ajo.2009.11.020

    Article  PubMed  Google Scholar 

  17. Brandine G, Smith A (2019) Falco: high-speed FastQC emulation for quality control of sequencing data. F1000Res 8:1874. https://doi.org/10.12688/f1000research.21142.2

    Article  Google Scholar 

  18. Marconcini M, Pischedda E, Houe V, Palatini U, Lozada-Chavez N, Sogliani D, Failloux AB, Bonizzoni M (2021) Profile of small RNAs, vDNA forms and viral integrations in late Chikungunya Virus infection of Aedes albopictus Mosquitoes. Viruses 13(4):553. https://doi.org/10.3390/v13040553

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. 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. Bioinf (Oxford England) 29(1):15–21. https://doi.org/10.1093/bioinformatics/bts635

    Article  CAS  Google Scholar 

  20. Chisanga D, Liao Y, Shi W (2022) Impact of gene annotation choice on the quantification of RNA-seq data. BMC Bioinformatics 23(1):107. https://doi.org/10.1186/s12859-022-04644-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kozomara A, Birgaoanu M, Griffiths-Jones S (2019) miRBase: from microRNA sequences to function. Nucleic Acids Res 47(D1):D155–D162. https://doi.org/10.1093/nar/gky1141

    Article  CAS  PubMed  Google Scholar 

  22. 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 

  23. Abbas-Aghababazadeh F, Li Q, Fridley BL (2018) Comparison of normalization approaches for gene expression studies completed with high-throughput sequencing. PLoS ONE 13(10):e0206312. https://doi.org/10.1371/journal.pone.0206312

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Goedhart J, Luijsterburg MS (2020) VolcaNoseR is a web app for creating, exploring, labeling and sharing volcano plots. Sci Rep 10(1):20560. https://doi.org/10.1038/s41598-020-76603-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. McDermaid A, Monier B, Zhao J, Liu B, Ma Q (2019) Interpretation of differential gene expression results of RNA-seq data: review and integration. Brief Bioinform 20(6):2044–2054. https://doi.org/10.1093/bib/bby067

    Article  CAS  PubMed  Google Scholar 

  26. 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 

  27. Otasek D, Morris JH, Boucas J, Pico AR, Demchak B (2019) Cytoscape automation: empowering workflow-based network analysis. Genome Biol 20(1):185. https://doi.org/10.1186/s13059-019-1758-4

    Article  PubMed  PubMed Central  Google Scholar 

  28. Abhishek S, Ryndak MB, Choudhary A, Sharma S, Gupta A, Gupta V, Singh N, Laal S, Verma I (2019) Transcriptional signatures of Mycobacterium tuberculosis in mouse model of intraocular tuberculosis. Pathog Dis 77(5):ftz045. https://doi.org/10.1093/femspd/ftz045

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Russo A, Ragusa M, Barbagallo C, Longo A, Avitabile T, Uva M, Bonfiglio V, Toro M, Caltabiano R, Mariotti C et al (2017) MiRNAs in the vitreous humor of patients affected by idiopathic epiretinal membrane and macular hole. PLoS ONE 12:e0174297. https://doi.org/10.1371/journal.pone.0174297

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Loporchio DF, Tam EK, Cho J, Chung J, Jun GR, Xia W, Fiorello MG, Siegel NH, Ness S, Stein TD et al (2021) Cytokine levels in human vitreous in proliferative Diabetic Retinopathy. Cells 10(5):1069. https://doi.org/10.3390/cells10051069

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. El Faouri M, Ally N, Lippera M, Subramani S, Moussa G, Ivanova T, Patton N, Dhawahir-Scala F, Rocha-de-Lossada C, Ferrara M et al (2023) Long-term safety and efficacy of Pars Plana Vitrectomy for Uveitis: experience of a Tertiary Referral Centre in the United Kingdom. J Clin Med 12(9):3252. https://doi.org/10.3390/jcm12093252

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  33. Chaurasiya SK, Srivastava K (2009) Downregulation of protein kinase C- αenhances intracellular survival of Mycobacteria: role of PknG. BMC Microbiol 9:271. https://doi.org/10.1186/1471-2180-9-271

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Shariq M, Quadir N, Sheikh JA, Singh AK, Bishai WR, Ehtesham NZ, Hasnain SE (2021) Post translational modifications in tuberculosis: ubiquitination paradox. Autophagy 17(3):814–817. https://doi.org/10.1080/15548627.2020.1850009

    Article  CAS  PubMed  Google Scholar 

  35. Olsen A, Chen Y, Ji Q, Zhu G, De Silva AD, Vilcheze C, Weisbrod T, Li W, Xu J, Larsen M et al (2016) Targeting Mycobacterium tuberculosis Tumor necrosis factor alpha-downregulating genes for the development of Antituberculous Vaccines. mBio 7(3):e01023–e01015. https://doi.org/10.1128/mBio.01023-15

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Lim YJ, Lee J, Choi JA, Cho SN, Son SH, Kwon SJ, Son JW, Song CH (2020) M1 macrophage dependent-p53 regulates the intracellular survival of mycobacteria. Apoptosis 25(1–2):42–55. https://doi.org/10.1007/s10495-019-01578-0

    Article  PubMed  Google Scholar 

  37. Adankwah E, Harelimana JDD, Minadzi D, Aniagyei W, Abass K, Debrah L, Owusu O, Mayatepek D, Phillips E, Jacobsen R M (2020) Lower monocyte Interleukin-7 receptor expression impairs Anti-Mycobacterial Effector Functions in Tuberculosis Patients. J Immunol 206(10):2430–2440. https://doi.org/10.4049/jimmunol.2001256

    Article  CAS  Google Scholar 

  38. Gern BH, Adams KN, Plumlee CR, Stoltzfus CR, Shehata L, Moguche AO, Busman-Sahay K, Hansen SG, Axthelm MK, Picker LJ et al (2021) TGFbeta restricts expansion, survival, and function of T cells within the tuberculous granuloma. Cell Host Microbe 29(4):594–606e596. https://doi.org/10.1016/j.chom.2021.02.005

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Trinath J, Holla S, Mahadik K, Prakhar P, Singh V, Balaji KN (2014) The WNT signaling pathway contributes to dectin-1-dependent inhibition of toll-like receptor-induced inflammatory signature. Mol Cell Biol 34(23):4301–4314. https://doi.org/10.1128/MCB.00641-14

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Takaki K, Ramakrishnan L, Basu S (2018) A zebrafish model for ocular tuberculosis. PLoS ONE 13(3):e0194982. https://doi.org/10.1371/journal.pone.0194982

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Sharma RKM, Gupta VM, Bansal RM, Sharma KM, Gupta AM, Sachdeva NP (2018) Immune profiling of T cells infiltrating vitreous humor in Tubercular Uveitis. Immunol Invest 47(6):615–631. https://doi.org/10.1080/08820139.2018.1470640

    Article  CAS  PubMed  Google Scholar 

  42. Zheng L, Leung E, Lee N, Lui G, To KF, Chan RC, Ip M (2015) Differential MicroRNA expression in human macrophages with Mycobacterium tuberculosis infection of Beijing/W and Non-Beijing/W strain types. PLoS ONE 10(6):e0126018. https://doi.org/10.1371/journal.pone.0126018

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Duroux-Richard I, Robin M, Peillex C, Apparailly F (2019) MicroRNAs: fine tuners of Monocyte Heterogeneity. Front Immunol 10:2145. https://doi.org/10.3389/fimmu.2019.02145

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Koenig AL, Shchukina I, Amrute J, Andhey PS, Zaitsev K, Lai L, Bajpai G, Bredemeyer A, Smith G, Jones C et al (2022) Single-cell transcriptomics reveals cell-type-specific diversification in human heart failure. Nat Cardiovasc Res 1(3):263–280

    Article  PubMed  PubMed Central  Google Scholar 

  45. Richter E, Ventz K, Harms M, Mostertz J, Hochgrafe F (2016) Induction of macrophage function in human THP-1 cells is Associated with rewiring of MAPK signaling and activation of MAP3K7 (TAK1) protein kinase. Front Cell Dev Biol 4:21. https://doi.org/10.3389/fcell.2016.00021

    Article  PubMed  PubMed Central  Google Scholar 

  46. Bergenfelz C, Janols H, Wullt M, Jirstrom K, Bredberg A, Leandersson K (2013) Wnt5a inhibits human monocyte-derived myeloid dendritic cell generation. Scand J Immunol 78(2):194–204. https://doi.org/10.1111/sji.12075

    Article  CAS  PubMed  Google Scholar 

  47. Saarela J, Kallio SP, Chen D, Montpetit A, Jokiaho A, Choi E, Asselta R, Bronnikov D, Lincoln MR, Sadovnick AD et al (2006) PRKCA and multiple sclerosis: association in two independent populations. PLoS Genet 2(3):e42. https://doi.org/10.1371/journal.pgen.0020042

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Ondee T, Jaroonwitchawan T, Pisitkun T, Gillen J, Nita-Lazar A, Leelahavanichkul A, Somparn P (2019) Decreased protein kinase C-β type II Associated with the prominent endotoxin exhaustion in the macrophage of FcGRIIb–/– Lupus Prone mice is revealed by phosphoproteomic analysis. Int J Mol Sci 20:1354. https://doi.org/10.3390/ijms20061354

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. 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  PubMed Central  Google Scholar 

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Acknowledgements

The authors thank Dr. Radhika Thundikandy, Dr. Vedhanayaki Rajesh, Dr. Anjana Somanath, Mrs. Kokila, and the Uvea Clinic, Aravind Eye Hospital, Madurai, India, for the sample collection and clinical assessment. Balagiri Sundar, biostatistician for ROC curve preparation. Dr. Shanthi R, pathologist for histopathological examinations.

Funding

Project supported by the Department of Biotechnology (DBT), India (No: BT/PR20733/MED/29/1075/2016), Swathi Chadalawada is funded by a Senior Research Fellowship provided by the Indian Council of Medical Research (ICMR), India (Sanction letter No. 2019–4013/Gen-BMS dt.30.09.2019).

Author information

Authors and Affiliations

  1. Department of Microbiology and Bioinformatics, Aravind Medical Research Foundation, 1, Anna Nagar, Madurai, India

    Swathi Chadalawada & Bharanidharan Devarajan

  2. Biomedical Sciences, Madurai Kamaraj University, Madurai, 625021, Tamil Nadu, India

    Swathi Chadalawada

  3. Uveitis Service, Aravind Eye Hospital and PG Institute of Ophthalmology, Madurai, Tamil Nadu, India

    SR Rathinam

  4. Department of Microbiology, Aravind Eye Hospital, Madurai, Tamil Nadu, India

    Prajna Lalitha

  5. Chief, Retina Vitreous Services, Aravind Eye Hospital, Madurai, Tamil Nadu, India

    Naresh Babu Kannan

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Contributions

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

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Correspondence to Bharanidharan Devarajan.

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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).

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Supplementary Material: Table S1

. Clinical features of patients with IOTB, Macular hole, and Noninfectious Uveitis samples. Table S2. NGS data statistics. Table S3. List of primers used for the RT-qPCR analysis. Table S4. ROC analysis of VH miRNAs. Table S5. Serum miRNAs validated using RT-qPCR. Table S6. Differential expression analysis of miRNAs using NOISeq

Supplementary Fig. S1

. Log2 FC values of miRNAs in serum of intraocular tuberculosis. Real-time qPCR validation of differentially expressed miRNAs in serum of intraocular tuberculosis (n = 12) and Noninfectious Uveitis samples (n = 8)

Supplementary Fig. S2

. Selected target genes functional network for RT-qPCR validation

Supplementary Fig. S3

. Low power view of haematoxylin and eosin stained section of a enucleated eye with necrotic granuloma within the vitreous cavity and degenerated retina

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Chadalawada, S., Rathinam, S., Lalitha, P. et al. Detection of microRNAs expression signatures in vitreous humor of intraocular tuberculosis. Mol Biol Rep 50, 10061–10072 (2023). https://doi.org/10.1007/s11033-023-08819-1

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