Integrated Bioinformatics Analysis And Validation Of MiRNA In The Diagnosis Of Active Tuberculosis

BACKGROUND:Tuberculosis(TB)is one of the most prevalent pulmonary diseases caused by MycobacterLum tuberculosis(Mtb)infection.China is still one of the countries with the heaviest burden of tuberculosis in the world.Drug-resistant tuberculosis becomes a serious threat to global public health.At present,the diagnostic methods of tubercxulosis have many shortcomings,such as low specificity and sensitivity,long time consurming and so on-These have become the main obstacle to early diagnosis,early treatment,eradication of the source of infection and cutting off the route of transmission.Biomarkers,which can help diagnose early and have high sensitivity and specificity,are of great signiflcance in blocking the transmission of tuberculosis and even eliminating it.The regulation of gene expression by a highly conserved endogenous non-coding microRNA(miRNAs)has been widely used in the study of many infectious diseases.MiRNA has become a key regulator of gene expression at the post-transcriptional level by identifying and binding the complementary sequence of the target mRNA,miRNA can either block the translation of mRNA or promote its degradation.A single mRNA is regulated by multiple miRNAs,while a single miRNA regulates multiple mRNAs,and the interaction between different miRNAs determines the final biological effects,so it shows a complex gene regulatory network.When pathogens invade human cells,the expression of miRNAs changes rapidly.The expression of miRNA in peripheral blood monocyte(PBMC),serum and sputum in patients with active tuberculosis has been confirmed by several studies.It is suggested that miRNAs have the potential as diagnostic biomarkers of active tuberculosis.Further studies have confirmed that there is a significant difference in the expression of miRNAs between multidrug resistant(MDR)tuberculosis and antibiotic-sensitive tuberculosis,which provides a new era for the screening of drug-resistant tuberculosis.At the same time,the expression of miRNAs in CD4+T cells increases sig5ificantly in patients with active tuberceulosis after chemotherapy.These results suggest that miRNAs can be used not only as potential biomarkers for the diagnosis of tuberculosis,but also to help assess recovery after treatment.Reverse transcription quantitative real-time PCR(RT-qPCR)is a hybridization method to capture probes from DNA fixed on microarray platfonn.The expression of single miRNA can be quantitatively evaluated according to the intensity of fluorescence signal.Circulating serum or plasma miRNAs can be used to diagnose a variety of infectious diseases,and tuberculosis is one of the earliest diseases to use this method.MiRNA is involved in the process of tuberculosis infection by regulating the interaction between human body and mycobacterium tuberculosis.The biomformatic progress makes it possible to explore a new type of immunomodulatory miRNA and use it as a biomarker for the diagnosis of active pulmonary tuberculosis.At present,a variety of computer network technologies make it easy for researchers to analyze and compare experimental data with tuberculosis miRNA and mRNA transcript data groups.In the present study,differentially expressed mRNAs(DE-mRNAs)and miRNAs(DE-miRNAs)were screened from tuberculosis miRNA and mRNA datasets.Functional annotation,protein-protein interaction(PPI)network and miRNA-gene-immune process(MGIP)network were constructed to examine their connections with TB.Eight de-regulated miRNAs were selected from the screening results for quantitative real-time quantitative PCR(qRT.PCR)verification and compared with the healthy control group.At the same time,the diagnostic performance was evaluated by ROC curve.Methods:Clinical peripheral blood samples The serum samples were collected from 30 active TB patients and 30 healthy donors on an empty stomach in the mooning.The samples were placed at room temperature for 1-2h,centrifuged at 4,C for 10 min,and stored at-80? for 250 ?L each.GEO dataset download and raw data preprocessing The raw data of miRNA expression dataset GSE29190 and mRNA dataset GSE54992 were downloaded from the National Center of Biotechnology Infornation Gene Expression Omnibus.The downloaded data in CEL flies of GSE29190 were preprocessed using R limma package.Raw data in GSE54992 were preprocessed using Affy package.Background correction,log2 data transformation and quantile normalization were performed.Probes with a corresponding gene symbol were filtered.The expression of genes with multiple probes was calculated based on average expression.Screening differentially expressed miRNAs and mRNAs Student's t-test was used to identify deregulated miRNAs and mRNAs between ATB and healthy donors,respectively.Fold change were defined as the divided value of average gene expression of ATB groups by healthy donor groups.The raw p values were applied to Benjamini?Hochberg(BH)procedure and false discovery rate(FDR).The DE-miRNAs and DE-mRNAs were screened using cut-off criteria of p value<0.05,FDR<0.1 and llog2FC|>1.Functional annotation and enrichment of DE-mRNAs To gain insight into biological functions and pathways related to TB,Gene Ontology(GO)functional and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses were performed for the identified DE-mRNAs,using the online tool of Database for Annotation,Visualization and Integrated Discovery(DAVID)based on the method of Expression Analysis Systemic Explorer(EASE)test.The enrichment threshold was an EASE score of 0.1.Plots showing significantly enriched biological process,cellular components,molecular functions and pathways were drawn with R scripts.Protein-protein interaction(PPI)and gene-immune pathway network construction In order to explore the regulatory relationship of DE-mRNAs,corresponding protein names were uploaded into String database.With the minimum required interaction score>0.4,the protein-protein interaction data was exported and open with Cytoscape.The MCODE v.1.4.2 was used to identify clustered sub-networks densely connected based topology.CentiScape v2.2 pug-in was applied to calculate node centrality and find important modes.The ClueGO v2.3.5 application was used to annotate and enrich significant(p<0.05)connections between DE-mRNAs and pathways.DE-miRNAs targets prediction and miRNA-gene-immune process(MGIP)network construction MiRNA targets were first predicted with microT-CDS.Then,based on reverse fold change trend of DE-miRNAs and corresponding predicted DE-mRNAs,DE-miRNAs-DE-mRNA pairs were screened for network construction.At last,a three-layer network integrating miRNA-mRNA targeting,reverse expression trend and mRNA immune function were constructed with Cytoscape.QRT-PCR analysis of miRNAs Blood was collected in cell preparation tubes(CPTs)designed for one-step cell separation from TB patients(n=30)and healthy controls(n=30).Isolation of RNA from PBMC was carried out using the mirVanaTM miRNA Isolation Kit.RNA purity was measured using the NanoDrop Spectrophotometer.The purity of RNA was determined by the ratio A260/A280 with a ratio of 1.8-2 representing pure RNA.200 ng of each RNA sample were used for qRT-PCR.cDNA synthesis was performed by using TaqMan(?)MicroRNA Reverse Transcription Kit.miRNA qRT-PCR was performed using the miDETECT A Track 150 TM miRNA qRT-PCR Starter Kit in a 20ul reaction for 40 eycles.miRNA expression was analyzed using the difference in cycle threshold(ACt)method.The Ct values of the miRNAs were normalized to RNU6B using the equation:ACt=Ct reference-Ct target and expressed as ACt.Results:A total of 7463 DE-mRNAs and 38 DE-miRNAs were identified.Functional annotation found 42 identified MAPK signaling pathways and leukocyte migration top enriched processes.The PPI and MGIP network gave rise to CXCL1,CXCL2 chemokines and receptors CCR7 as important down-regulated genes.3 miRNAs(miR-892b,miR-199b-5p and miR-582-5p)showed significant differential expression between TB and healthy groups.MiR.892b showed the best overall performance of AUC 0.82,sensitivity 70%and specificity 90%.Conclusion:Most chemokines and receptors were down-regulated in TB,implicating suppressed chemotaxis.Patients with active TB have lower miR-892b levels,and miR.892b may be a diagnostic biomarker for TB.Further research is needed to elucidate the role of miR,892b as biomarker and in TB progression.