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Small RNA sequencing and bioinformatics analysis of RAW264.7-derived exosomes after Mycobacterium Bovis Bacillus Calmette-Guérin infection

Zhan, Xuehua, Yuan, Wenqi, Zhou, Yueyong, Ma, Rong, Ge, Zhaohui·2022·BMC Genomics
DOI 10.1186/s12864-022-08590-wPMC PMC9080156
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Abstract

Background: The mechanisms through which Mycobacterium tuberculosis evades immune surveillance during tuberculosis (TB) infection remain complex. Previous studies have found that Mycobacteria can manipulate the miRNAs of host cells to promote their survival during host-pathogen interactions, and most of these effects occur at the cellular miRNA level. We attempted to investigate the possible related mechanisms at the exosomal miRNA level. Results: High-throughput sequencing revealed that Bacillus Calmette-Guérin (BCG) infection could alter the composition of the macrophage exosome content, and the expression levels of miRNAs in exosomes derived from the cell culture media of macrophages showed significant differences between the BCG-infected and non-infected groups. Compared with the non-infected group, 20 exosomal miRNAs were up-regulated and 7 exosomal miRNAs were down-regulated in the infection group (p < 0.05), of which mmu-miR-27b-3p, mmu-miR-93-5p, mmu-miR-25-3p, mmu-miR-1198-5p, mmu-let-7c-5p and let-7a-5p were significantly up-regulated. A bioinformatic analysis indicated that these differentially expressed exosomal miRNAs were involved in multiple biological processes and pathways. The target genes of top six miRNAs in up-regulated groups were positively correlated with the regulation of apoptosis. Conclusions: The expression profile of miRNA in exosomes derived from macrophage were altered after Mycobacterium Bovis Bacillus Calmette-Guérin infection, and the differentially expressed miRNAs were involved in multiple biological processes and signalling pathways. The top six up-regulated miRNAs and their targeted genes were predominantly correlated with the regulation of apoptosis.

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Fig. 1 Characterization of exosomes by transmission electron microscopy (TEM). The exosome morphology was scanned by TEM. The scale bars represent 1 μm (A), 500 nm (B), 200 nm (C), and 100 nm (D)
Fig. 1 Characterization of exosomes by transmission electron microscopy (TEM). The exosome morphology was scanned by TEM. The scale bars represent 1 μm (A), 500 nm (B), 200 nm (C), and 100 nm (D)CC BY · PubMed Central
Fig. 2 Characterization of exosomes by NanoFCM. The exosome transmembrane proteins CD9 and CD81 and isotype control FITC-IgG were detected and quantified by NanoFCM (A-C). The particle concentration was analysed by NanoFCM (D, E). The size distribution was analysed by NanoFCM (F)
Fig. 2 Characterization of exosomes by NanoFCM. The exosome transmembrane proteins CD9 and CD81 and isotype control FITC-IgG were detected and quantified by NanoFCM (A-C). The particle concentration was analysed by NanoFCM (D, E). The size distribution was analysed by NanoFCM (F)CC BY · PubMed Central
Fig. 3 MiRNAs showing differential expression between the following two groups: Group A (noninfection group) and Group B (infection group)
Fig. 3 MiRNAs showing differential expression between the following two groups: Group A (noninfection group) and Group B (infection group)CC BY · PubMed Central
Fig. 4 Heatmap of differently expressed miRNAs. The miRNA expression levels are presented as the log10-transformed normalized values. The different colours represent different miRNA expression levels. The colour range from blue to orange represents an expression level range from low to high; specifically, the dark blue colour indicates high expression, and the orange colour indicates low expression
Fig. 4 Heatmap of differently expressed miRNAs. The miRNA expression levels are presented as the log10-transformed normalized values. The different colours represent different miRNA expression levels. The colour range from blue to orange represents an expression level range from low to high; specifically, the dark blue colour indicates high expression, and the orange colour indicates low expressionCC BY · PubMed Central
Fig. 5 Volcano plot of differently expressed miRNAs. Log2(FC) represents the change in the differential expression of miRNAs in different samples; −log10(p value) represents the statistical significance of the difference in miRNA expression; the red colour indicates significantly differentially upregulated genes, the blue colour indicates significantly differentially downregulated genes, and the grey points represent genes showing nonsignificant differential expression
Fig. 5 Volcano plot of differently expressed miRNAs. Log2(FC) represents the change in the differential expression of miRNAs in different samples; −log10(p value) represents the statistical significance of the difference in miRNA expression; the red colour indicates significantly differentially upregulated genes, the blue colour indicates significantly differentially downregulated genes, and the grey points represent genes showing nonsignificant differential expressionCC BY · PubMed Central
Fig. 6 GO enrichment of the target genes. A Bar plot. B Scatterplot. The rich factor indicates the ratio of the number of differentially expressed genes divided by the total number of genes annotated with a specific term. For a term, a smaller p-value indicates a higher degree of enrichment. The diameter of the point represents the number of genes enriched with the item
Fig. 6 GO enrichment of the target genes. A Bar plot. B Scatterplot. The rich factor indicates the ratio of the number of differentially expressed genes divided by the total number of genes annotated with a specific term. For a term, a smaller p-value indicates a higher degree of enrichment. The diameter of the point represents the number of genes enriched with the itemCC BY · PubMed Central
Fig. 7 KEGG enrichment of the target genes. A Bar plot. B Scatterplot. The percentage of genes refers to the percentage of significantly enriched genes in the corresponding secondary categories
Fig. 7 KEGG enrichment of the target genes. A Bar plot. B Scatterplot. The percentage of genes refers to the percentage of significantly enriched genes in the corresponding secondary categoriesCC BY · PubMed Central
Fig. 8 Bar graph of enriched terms across input gene lists (coloured by p-values). A. Top 20 enriched terms across input gene lists. B. Top Gene Ontology biological process terms
Fig. 8 Bar graph of enriched terms across input gene lists (coloured by p-values). A. Top 20 enriched terms across input gene lists. B. Top Gene Ontology biological process termsCC BY · PubMed Central
Fig. 9 Network of enriched terms. A Coloured by cluster ID. Nodes that share the same cluster ID are typically close to each other. Terms with similarity scores > 0.3 are linked by edges (the thickness of the edges represents the similarity score). B Coloured by the p-values. Terms containing more genes tended to have more significant p-values. A darker colour indicates that the node is more statistically significant
Fig. 9 Network of enriched terms. A Coloured by cluster ID. Nodes that share the same cluster ID are typically close to each other. Terms with similarity scores > 0.3 are linked by edges (the thickness of the edges represents the similarity score). B Coloured by the p-values. Terms containing more genes tended to have more significant p-values. A darker colour indicates that the node is more statistically significantCC BY · PubMed Central
Fig. 10 Protein–protein interaction enrichment analysis. Protein–protein interaction network and MCODE components identified in the gene lists. The MCODE algorithm was applied to the network to identify the neighbourhoods of protein-intensive connections. Each MCODE network is assigned a unique colour. MCODE: Molecular Complex Detection
Fig. 10 Protein–protein interaction enrichment analysis. Protein–protein interaction network and MCODE components identified in the gene lists. The MCODE algorithm was applied to the network to identify the neighbourhoods of protein-intensive connections. Each MCODE network is assigned a unique colour. MCODE: Molecular Complex DetectionCC BY · PubMed Central
Fig. 11 Validation of relative miRNA expression in exosomes by qRT–PCR. A1-A3: Non-infection group. B1-B3: Infection group
Fig. 11 Validation of relative miRNA expression in exosomes by qRT–PCR. A1-A3: Non-infection group. B1-B3: Infection groupCC BY · PubMed Central

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Metadata

Authors
Zhan, X., Yuan, W., Zhou, Y., Ma, R., & Ge, Z.
Venue
BMC Genomics
Publisher
Springer Science and Business Media LLC
Published
2022-05-07
Volume
23
Issue
1
ISSN
1471-2164
DOI
10.1186/s12864-022-08590-w
PMC
PMC9080156
Cited by
23
References
1
Language
en
Licence
Funders
National Natural Science Foundation of China (8196090244)

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CoChat. (2026). Citation check: Small RNA sequencing and bioinformatics analysis of RAW264.7-derived exosomes after Mycobacterium Bovis Bacillus Calmette-Guérin infection. https://app.cochat.ai/papers/10.1186/s12864-022-08590-w
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Zhan, X., Yuan, W., Zhou, Y., Ma, R., & Ge, Z. (2022). Small RNA sequencing and bioinformatics analysis of RAW264.7-derived exosomes after Mycobacterium Bovis Bacillus Calmette-Guérin infection. BMC Genomics. https://doi.org/10.1186/s12864-022-08590-w