Characterization of RNA in exosomes secreted by human breast cancer cell lines using next-generation sequencing

Abstract

Exosomes are nanosized (30-100 nm) membrane vesicles secreted by most cell types. Exosomes have been found to contain various RNA species including miRNA, mRNA and long non-protein coding RNAs. A number of cancer cells produce elevated levels of exosomes. Because exosomes have been isolated from most body fluids they may provide a source for non-invasive cancer diagnostics. Transcriptome profiling that uses deep-sequencing technologies (RNA-Seq) offers enormous amount of data that can be used for biomarkers discovery, however, in case of exosomes this approach was applied only for the analysis of small RNAs. In this study, we utilized RNA-Seq technology to analyze RNAs present in microvesicles secreted by human breast cancer cell lines. Exosomes were isolated from the media conditioned by two human breast cancer cell lines, MDA-MB-231 and MDA-MB-436. Exosomal RNA was profiled using the Ion Torrent semiconductor chip-based technology. Exosomes were found to contain various classes of RNA with the major class represented by fragmented ribosomal RNA (rRNA), in particular 28S and 18S rRNA subunits. Analysis of exosomal RNA content revealed that it reflects RNA content of the donor cells. Although exosomes produced by the two cancer cell lines shared most of the RNA species, there was a number of non-coding transcripts unique to MDA-MB-231 and MDA-MB-436 cells. This suggests that RNA analysis might distinguish exosomes produced by low metastatic breast cancer cell line (MDA-MB-436) from that produced by highly metastatic breast cancer cell line (MDA-MB-231). The analysis of gene ontologies (GOs) associated with the most abundant transcripts present in exosomes revealed significant enrichment in genes encoding proteins involved in translation and rRNA and ncRNA processing. These GO terms indicate most expressed genes for both, cellular and exosomal RNA. For the first time, using RNA-seq, we examined the transcriptomes of exosomes secreted by human breast cancer cells. We found that most abundant exosomal RNA species are the fragments of 28S and 18S rRNA subunits. This limits the number of reads from other RNAs. To increase the number of detectable transcripts and improve the accuracy of their expression level the protocols allowing depletion of fragmented rRNA should be utilized in the future RNA-seq analyses on exosomes. Present data revealed that exosomal transcripts are representative of their cells of origin and thus could form basis for detection of tumor specific markers.

Keywords: Biomarkers; Breast cancer; Exosomes; Microvesicles; Next generation sequencing.

Figure 1. Analysis of exosomes produced by breast cancer cell lines, MDA-MB-436 and MDA-MB-231, with Nanosight LM10-HS instrument.

Figure 2. TEM image of the exosomes produces by MDA-MB-436 cell line.

Electron microscopy allowed visualizing membrane-bound nanovesicles sized ∼100 nm. White arrowheads pointing to the exosomes. Scale bar = 100 nm.

Figure 3. Analysis of RNA from cells and exosomes by Bioanalyzer.

Exosomal and total cell RNA was analyzed with PicoChip and NanoChip, respectively.

Figure 4. Flowchart of RNA-seq data analysis.

The raw reads are exposed to pre-alignment quality checks including the removal of adaptor sequences and low quality reads. The high quality reads are then mapped to rRNA sequences using Bowtie2 version 2.1.0. The non-mapped rRNA reads were mapped to human genome hg19 build of the human genome using TopHat version 2.0.6 with the aligner Bowtie 2.0.5. After mapping, low mapping quality reads less than 10; short reads with length less than 20 base pairs and multi- reads were removed. Estimation of read counts and read coverage on mapped reads where over 90% of exon (non-coding) and CDs (for coding) in transcript isoforms of RefGene and/ or GENCODE v14 gene models. The EM algorithm along with GENCODE v14 annotations was used to estimate the read count and reads per kilo base per million mapped reads (RPKM) on mapped transcripts.

Figure 5. Distribution of uniquely mapped RNA-seq reads among transcriptome.

Reads which overlapped with annotated gene models (RefSeq and/or GENCODE) are termed as “known genes”. Reads that placed outside of annotated gene models are termed as “unknown”. Reads which are mapped to rRNA sequences including 5S, 5.8S, 18S, and 28S rRNA are named as “rRNA”.

Figure 6. Example of low coverage transcript but very high RPKM in AURKAIP1 and ATPIF1 genes.

(A) AURKAIP1 gene from chromosome position chr1:1,309,009–1,310,847 is shown using Integrative Genomic Viewer. Among the three variants, the maximum value of protein-coding sequence (CDS) coverage, read count and RPKM is shown in the right panel of read mapping. Both the exosomes shows very low coverage (7–22%) with read counts of 4, whereas the RPKM value is 65.44 and 80.78 RPKM for exosomes of MDA-MB-231 and MDA-MB-436, respectively. (B) ATPIF1 gene from chromosome position chr1:28,562,494–28,564,655 is visualized. The MDA-MB-231 exosomes exhibit high CDS coverage (91%) with an exon count of 4.

Figure 7. Venn diagram presents overlap among protein-coding and non-coding gene symbols in exosomes and cells.

Almost all the genes in both exosomal RNA are the subset of cellular genes.

Figure 8. Gene Ontology (GO) enrichment analysis of genes detected in cellular and exosomal RNA from breast cancer cell lines.

The significant GO terms was defined as described in Materials and Methods. (A) Top 20 significant GO terms found in MDA-MB-231 cellular genes (3115 genes). (B) Significant GO terms found in exosomal genes from both cell-lines (MDA-MB-231 and MDA-MB-436). (C) Top 20 significant GO terms found in the most expressed 115 genes from MDA-MB-231 cellular genes. The asterisks (*) indicate GO terms that present in exosomal genes.

Figure 9. Expressed genes in exosomes found to be highly expressed in the host cells.

The box plot indicates expression level of all genes in cellular samples as compared to that of genes which were found to be express in exosomes. Wilcoxon rank sum test represents significant difference in expression level of the two sets.

Figure 10. Validation of RNA-seq data by qRT-PCR.

(A) Ct values for six mRNA transcripts which were detected in exosomal samples by RNA-seq are shown. (B) Comparison of different expression values (RPKM; MDA-MB-436/RPKM; MDA-MB-231) detected by RNA-Seq (dark-grey columns) and qRT-PCR (light-grey columns) for six differently expressed genes.