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Characterization of serum small extracellular vesicles and their small RNA contents across humans, rats, and mice.

Zhao, Fengbo, Cheng, Li, Shao, Qian, Chen, Zixing, Lv, Xiufang, Li, Jing, He, Li, Sun, Yufeng, Ji, Qiuhong, Lu, Peng, Ji, Yuhua, Ji, Juling·2020·Scientific Reports
DOI 10.1038/s41598-020-61098-9PMC PMC7060188
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Abstract

Serum small extracellular vesicles (sEVs) have recently drawn considerable interest because of the diagnostic and therapeutic potential of their miRNAs content. However, the characteristics of human, mouse and rat serum sEVs and their differences in small RNA contents are still unknown. In this study, through nanoparticle tracking analysis and small RNA sequencing, we found that human, rat, and mouse serum sEVs exhibited distinct sizes and particle numbers as well as small RNA contents. Serum sEVs contained not only abundant miRNAs but also a large number of tRNA fragments. Most serum miRNAs existed both inside and outside of sEVs but were enriched in sEVs. Common serum sEV miRNAs (188 miRNAs) and species-specific serum sEV miRNAs (265, 58, and 159 miRNAs, respectively) were identified in humans, rats, or mice. The serum sEVs contained miRNAs from tissues and organs throughout the body, with blood cells as the main contributors. In conclusion, our findings confirmed the rationality of exploring serum sEV miRNAs as noninvasive diagnostic markers and revealed great differences in serum sEV small RNAs between humans, rats, and mice. Inadequate attention to these differences and the contribution of blood cells to serum sEV miRNAs could hinder the clinical translation of basic studies.

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Figures

Figure 1 Characterization of sEV isolated from human, rat and mouse serum by Exoquick precipitation. (A) Transmission electron microscopy image of the isolated particles, bar = 200 nm, representative image of sEVs from rat. (B) Representative NTA size distribution profiles of isolated particles and their concentrations. (C) The expression of CD63, CD81 and CD9, as well as calnexin and albumin in the isolated particles was determined by western blotting. Lanes from left to right are serum sEV, de-sEV serum and whole serum, respectively. The images are the representatives of three or more independent experiments. Full-length blots/gels are presented in Supplementary Fig S2. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.
Figure 1 Characterization of sEV isolated from human, rat and mouse serum by Exoquick precipitation. (A) Transmission electron microscopy image of the isolated particles, bar = 200 nm, representative image of sEVs from rat. (B) Representative NTA size distribution profiles of isolated particles and their concentrations. (C) The expression of CD63, CD81 and CD9, as well as calnexin and albumin in the isolated particles was determined by western blotting. Lanes from left to right are serum sEV, de-sEV serum and whole serum, respectively. The images are the representatives of three or more independent experiments. Full-length blots/gels are presented in Supplementary Fig S2. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.CC BY · PubMed Central
Figure 2 The length distribution and concentration of small RNAs in serum sEV and de-sEV serum samples from human, rats and mice as detected by Agilent 2100 Bioanalyzer using small RNA chips. (A) Gel-like image of all the samples with biological replicates. (B) For each group, electropherograms for one of the two biological replicates was provided. (C) The concentrations of small RNA (0–296nt) in serum sEV from human, rat and mouse, human vs. rat, ***P = 0.0003; human vs. mouse, **P = 0.0053; rat vs. mouse, *P = 0.0159; de-sEV serum, human vs. rat, P > 0.05, ns; human vs. mouse, **P = 0.0052; rat vs. mouse, *P = 0.0397; the concentrations of small RNA in serum sEV vs. de-sEV serum, human, P > 0.05, ns; rat, P > 0.05, ns; mouse, *P = 0.0134. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.
Figure 2 The length distribution and concentration of small RNAs in serum sEV and de-sEV serum samples from human, rats and mice as detected by Agilent 2100 Bioanalyzer using small RNA chips. (A) Gel-like image of all the samples with biological replicates. (B) For each group, electropherograms for one of the two biological replicates was provided. (C) The concentrations of small RNA (0–296nt) in serum sEV from human, rat and mouse, human vs. rat, ***P = 0.0003; human vs. mouse, **P = 0.0053; rat vs. mouse, *P = 0.0159; de-sEV serum, human vs. rat, P > 0.05, ns; human vs. mouse, **P = 0.0052; rat vs. mouse, *P = 0.0397; the concentrations of small RNA in serum sEV vs. de-sEV serum, human, P > 0.05, ns; rat, P > 0.05, ns; mouse, *P = 0.0134. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.CC BY · PubMed Central
Figure 3 The length distribution and frequency of annotated reads of small RNAs in serum sEV samples and de-sEV serum samples from human, rats and mice. (A) Length distribution of the clean reads. (B) Pie charts of annotated small RNA species and their percentages in total clean reads, others including: rRNA, snRNA, Cis-reg and other_Rfam_RNA. For each group, one representative chart of the two replicates was provided. Detailed annotation data for all the samples were provided in Supplementary Table S3. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.
Figure 3 The length distribution and frequency of annotated reads of small RNAs in serum sEV samples and de-sEV serum samples from human, rats and mice. (A) Length distribution of the clean reads. (B) Pie charts of annotated small RNA species and their percentages in total clean reads, others including: rRNA, snRNA, Cis-reg and other_Rfam_RNA. For each group, one representative chart of the two replicates was provided. Detailed annotation data for all the samples were provided in Supplementary Table S3. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.CC BY · PubMed Central
Figure 4 Profiling of human, rat, and mouse serum sEV miRNAs. (A) Correlation between normalized miRNAs read counts (Log2TPM) between the biological replications from each group. (B) Correlation between normalized read counts (Log2TPM) obtained by small RNA-seq and adjusted q-RT-PCR CT values for 6 miRNAs (miR-125a-5p, miR-125b-5p, miR-191-5p, miR-27b-3p, miR-486-5p and miR-99a-5p). q-RT-PCR for miRNAs were performed with the same batch of RNAs that prepared for sequencing. The relative expression of the selected miRNAs as determined by qPCR were expressed as (40-Ct) miRNA. TPM, transcripts per million reads; h, human; r, rat; m, mouse; e, serum small extracellular vesicle; d, small extracellular vesicle depleted serum.
Figure 4 Profiling of human, rat, and mouse serum sEV miRNAs. (A) Correlation between normalized miRNAs read counts (Log2TPM) between the biological replications from each group. (B) Correlation between normalized read counts (Log2TPM) obtained by small RNA-seq and adjusted q-RT-PCR CT values for 6 miRNAs (miR-125a-5p, miR-125b-5p, miR-191-5p, miR-27b-3p, miR-486-5p and miR-99a-5p). q-RT-PCR for miRNAs were performed with the same batch of RNAs that prepared for sequencing. The relative expression of the selected miRNAs as determined by qPCR were expressed as (40-Ct) miRNA. TPM, transcripts per million reads; h, human; r, rat; m, mouse; e, serum small extracellular vesicle; d, small extracellular vesicle depleted serum.CC BY · PubMed Central
Figure 5 The frequency of known miRNAs among total clean reads of small RNAs. (A) The frequency of known miRNAs in serum sEVs from human, rat and mouse, human vs. rat, **P = 0.0035; human vs. mouse, ***P = 0.0002; rat vs. mouse, *P = 0.0458; de-sEV serum, human vs. rat, **P = 0.0019; human vs. mouse, **P = 0.0039; rat vs. mouse, ns, P = 0.2693. (B) The frequency of known miRNAs in serum sEVs vs. de-sEV serum, human, *P = 0.014; rat, *P = 0.0103; mouse, *P = 0.0399. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.
Figure 5 The frequency of known miRNAs among total clean reads of small RNAs. (A) The frequency of known miRNAs in serum sEVs from human, rat and mouse, human vs. rat, **P = 0.0035; human vs. mouse, ***P = 0.0002; rat vs. mouse, *P = 0.0458; de-sEV serum, human vs. rat, **P = 0.0019; human vs. mouse, **P = 0.0039; rat vs. mouse, ns, P = 0.2693. (B) The frequency of known miRNAs in serum sEVs vs. de-sEV serum, human, *P = 0.014; rat, *P = 0.0103; mouse, *P = 0.0399. sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted.CC BY · PubMed Central
Figure 6 The expression of miRNAs in serum sEV vs. de-sEV serum, and the expression of miRNAs in serum sEV between species. (A) The venny diagram depicts the common and unique miRNAs identified in serum sEV miRNAs and de-sEV serum miRNAs from human, rat and mouse, respectively. (B) The composition of miRNAs based on the relative expression of serum sEVs vs. sEV-depleted serum, only those miRNAs existed both inside and outside of serum sEV were included. (C) The venny diagram depicts the common and unique miRNAs identified in serum sEV miRNAs from human, rat and mouse. (D) Heat map of hierarchical clustering of the 188 common serum sEV miRNAs between species based on log2 transformed TMP (transcripts per million reads). Each column represents an individual sample, each row represents an individual miRNA. miRNAs were ordered by Pearson correlation and complete linkage. TPM, transcripts per million reads; sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted; e, serum small extracellular vesicle; d, small extracellular vesicle depleted serum.
Figure 6 The expression of miRNAs in serum sEV vs. de-sEV serum, and the expression of miRNAs in serum sEV between species. (A) The venny diagram depicts the common and unique miRNAs identified in serum sEV miRNAs and de-sEV serum miRNAs from human, rat and mouse, respectively. (B) The composition of miRNAs based on the relative expression of serum sEVs vs. sEV-depleted serum, only those miRNAs existed both inside and outside of serum sEV were included. (C) The venny diagram depicts the common and unique miRNAs identified in serum sEV miRNAs from human, rat and mouse. (D) Heat map of hierarchical clustering of the 188 common serum sEV miRNAs between species based on log2 transformed TMP (transcripts per million reads). Each column represents an individual sample, each row represents an individual miRNA. miRNAs were ordered by Pearson correlation and complete linkage. TPM, transcripts per million reads; sEV, small extracellular vesicle; de-sEV, small extracellular vesicle depleted; e, serum small extracellular vesicle; d, small extracellular vesicle depleted serum.CC BY · PubMed Central
Figure 7 Pie charts of the top ten most abundant serum sEV miRNAs in human, rat and mice, and venny diagram depicts the common and unique miRNAs identified in the top ten most abundant serum sEV miRNAs from human, rat and mouse.
Figure 7 Pie charts of the top ten most abundant serum sEV miRNAs in human, rat and mice, and venny diagram depicts the common and unique miRNAs identified in the top ten most abundant serum sEV miRNAs from human, rat and mouse.CC BY · PubMed Central

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Research works printed but not linked: 36

  1. Chen, X. et al. Characterization of microRNAs in serum: a novel class of biomarkers for diagnosis of cancer and other diseases. Cell research 18, 997–1006, https://doi.org/10.1038/cr.2008.282 (2008). · DOI · Paper page
  2. Valadi, H. et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nature cell biology 9, 654–659, https://doi.org/10.1038/ncb1596 (2007). · DOI · Paper page
  3. Cheng, L., Sharples, R. A., Scicluna, B. J. & Hill, A. F. Exosomes provide a protective and enriched source of miRNA for biomarker profiling compared to intracellular and cell-free blood. Journal of extracellular vesicles 3, https://doi.org/10.3402/jev.v3.23743 (2014). · DOI · Paper page
  4. Chen, F. et al. Effects of Focal Cerebral Ischemia on Exosomal Versus Serum miR126. Translational stroke research 6, 478–484, https://doi.org/10.1007/s12975-015-0429-3 (2015). · DOI
  5. Bala, S. et al. Circulating microRNAs in exosomes indicate hepatocyte injury and inflammation in alcoholic, drug-induced, and inflammatory liver diseases. Hepatology 56, 1946–1957, https://doi.org/10.1002/hep.25873 (2012). · DOI
  6. Saha, B. et al. Extracellular vesicles from mice with alcoholic liver disease carry a distinct protein cargo and induce macrophage activation through heat shock protein 90. Hepatology 67, 1986–2000, https://doi.org/10.1002/hep.29732 (2018). · DOI
  7. Mitchell, P. S. et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proceedings of the National Academy of Sciences of the United States of America 105, 10513–10518, https://doi.org/10.1073/pnas.0804549105 (2008). · DOI · Paper page
  8. Thery, C. et al. Minimal information for studies of extracellular vesicles 2018 (MISEV2018): a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines. Journal of extracellular vesicles 7, 1535750, https://doi.org/10.1080/20013078.2018.1535750 (2018). · DOI · Paper page
  9. Vickers, K. C., Palmisano, B. T., Shoucri, B. M., Shamburek, R. D. & Remaley, A. T. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nature cell biology 13, 423–433, https://doi.org/10.1038/ncb2210 (2011). · DOI · Paper page
  10. Arroyo, J. D. et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proceedings of the National Academy of Sciences of the United States of America 108, 5003–5008, https://doi.org/10.1073/pnas.1019055108 (2011). · DOI · Paper page
  11. Kuksa, P. P. et al. DASHR 2.0: integrated database of human small non-coding RNA genes and mature products. Bioinformatics 35, 1033–1039, https://doi.org/10.1093/bioinformatics/bty709 (2019). · DOI
  12. Minami, K. et al. miRNA expression atlas in male rat. Scientific data 1, 140005, https://doi.org/10.1038/sdata.2014.5 (2014). · DOI · Paper page
  13. Ji, Q. et al. Increased Brain-Specific MiR-9 and MiR-124 in the Serum Exosomes of Acute Ischemic Stroke Patients. PloS one 11, e0163645, https://doi.org/10.1371/journal.pone.0163645 (2016). · DOI
  14. Zhou, X. et al. Characterization of mouse serum exosomal small RNA content: The origins and their roles in modulating inflammatory response. Oncotarget 8, 42712–42727, https://doi.org/10.18632/oncotarget.17448 (2017). · DOI
  15. Buschmann, D. et al. Evaluation of serum extracellular vesicle isolation methods for profiling miRNAs by next-generation sequencing. Journal of extracellular vesicles 7, 1481321, https://doi.org/10.1080/20013078.2018.1481321 (2018). · DOI
  16. Raposo, G. & Stoorvogel, W. Extracellular vesicles: exosomes, microvesicles, and friends. The Journal of cell biology 200, 373–383, https://doi.org/10.1083/jcb.201211138 (2013). · DOI · Paper page
  17. Szabo, G. & Momen-Heravi, F. Extracellular vesicles in liver disease and potential as biomarkers and therapeutic targets. Nature reviews. Gastroenterology & hepatology 14, 455–466, https://doi.org/10.1038/nrgastro.2017.71 (2017). · DOI
  18. Vallabhajosyula, P. et al. Tissue-specific exosome biomarkers for noninvasively monitoring immunologic rejection of transplanted tissue. J. Clin. Invest. 127, 1375–1391, 87993 [pii]10.1172/JCI87993 (2017). · DOI
  19. Tian, F. et al. Aberrant miR-181b-5p and miR-486-5p expression in serum and tissue of non-small cell lung cancer. Gene 591, 338–343, https://doi.org/10.1016/j.gene.2016.06.014 (2016). · DOI
  20. Ji, X. et al. The Anti-fibrotic Effects and Mechanisms of MicroRNA-486-5p in Pulmonary Fibrosis. Scientific reports 5, 14131, https://doi.org/10.1038/srep14131 (2015). · DOI
  21. Regev, K. et al. Association Between Serum MicroRNAs and Magnetic Resonance Imaging Measures of Multiple Sclerosis Severity. JAMA neurology 74, 275–285, https://doi.org/10.1001/jamaneurol.2016.5197 (2017). · DOI · Paper page
  22. Cun, J. & Yang, Q. Bioinformatics-based interaction analysis of miR-92a-3p and key genes in tamoxifen-resistant breast cancer cells. Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie 107, 117–128, https://doi.org/10.1016/j.biopha.2018.07.158 (2018). · DOI
  23. Kong, R., Gao, J., Si, Y. & Zhao, D. Combination of circulating miR-19b-3p, miR-122-5p and miR-486-5p expressions correlates with risk and disease severity of knee osteoarthritis. American journal of translational research 9, 2852–2864 (2017).
  24. Li, C. et al. Serum miR-486-5p as a diagnostic marker in cervical cancer: with investigation of potential mechanisms. BMC cancer 18, 61, https://doi.org/10.1186/s12885-017-3753-z (2018). · DOI
  25. Anderson, P. & Ivanov, P. tRNA fragments in human health and disease. FEBS letters 588, 4297–4304, https://doi.org/10.1016/j.febslet.2014.09.001 (2014). · DOI · Paper page
  26. Garcia-Silva, M. R., Cabrera-Cabrera, F., Guida, M. C. & Cayota, A. Hints of tRNA-Derived Small RNAs Role in RNA Silencing Mechanisms. Genes 3, 603–614, https://doi.org/10.3390/genes3040603 (2012). · DOI
  27. Sobala, A. & Hutvagner, G. Small RNAs derived from the 5′ end of tRNA can inhibit protein translation in human cells. RNA biology 10, 553–563, https://doi.org/10.4161/rna.24285 (2013). · DOI · Paper page
  28. Maute, R. L. et al. tRNA-derived microRNA modulates proliferation and the DNA damage response and is down-regulated in B cell lymphoma. Proceedings of the National Academy of Sciences of the United States of America 110, 1404–1409, https://doi.org/10.1073/pnas.1206761110 (2013). · DOI
  29. Goodarzi, H. et al. Endogenous tRNA-Derived Fragments Suppress Breast Cancer Progression via YBX1 Displacement. Cell 161, 790–802, https://doi.org/10.1016/j.cell.2015.02.053 (2015). · DOI · Paper page
  30. Hanada, T. et al. CLP1 links tRNA metabolism to progressive motor-neuron loss. Nature 495, 474–480, https://doi.org/10.1038/nature11923 (2013). · DOI
  31. Selitsky, S. R. et al. Small tRNA-derived RNAs are increased and more abundant than microRNAs in chronic hepatitis B and C. Scientific reports 5, 7675, https://doi.org/10.1038/srep07675 (2015). · DOI
  32. Dhahbi, J. M. et al. 5′ tRNA halves are present as abundant complexes in serum, concentrated in blood cells, and modulated by aging and calorie restriction. BMC genomics 14, 298, https://doi.org/10.1186/1471-2164-14-298 (2013). · DOI
  33. Telonis, A. G. et al. Dissecting tRNA-derived fragment complexities using personalized transcriptomes reveals novel fragment classes and unexpected dependencies. Oncotarget 6, 24797–24822, https://doi.org/10.18632/oncotarget.4695 (2015). · DOI · Paper page
  34. Witwer, K. W. et al. Standardization of sample collection, isolation and analysis methods in extracellular vesicle research. Journal of extracellular vesicles 2, https://doi.org/10.3402/jev.v2i0.20360 [pii] (2013). · DOI
  35. Thery, C., Amigorena, S., Raposo, G. & Clayton, A. Isolation and characterization of exosomes from cell culture supernatants and biological fluids. Current protocols in cell biology / editorial board, Juan S. Bonifacino… [et al.] Chapter 3, Unit 3, 22, https://doi.org/10.1002/0471143030.cb0322s30 (2006). · DOI · Paper page
  36. Kumar, P., Mudunuri, S. B., Anaya, J. & Dutta, A. tRFdb: a database for transfer RNA fragments. Nucleic acids research 43, D141–145, https://doi.org/10.1093/nar/gku1138 (2015). · DOI

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Metadata

Authors
Zhao, F., Cheng, L., Shao, Q., Chen, Z., Lv, X., Li, J., He, L., Sun, Y., Ji, Q., Lu, P., Ji, Y., & Ji, J.
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2020-03-06
Volume
10
Issue
1
ISSN
2045-2322
DOI
10.1038/s41598-020-61098-9
PMC
PMC7060188
Cited by
45
References
4
Language
en
Licence
Funders
  • National Natural Science Foundation of China (81201016, 81272027, 81761128018)
  • Six Talents Peak Project of Jiangsu Province (2017-WSN-094)
  • Natural Science Foundation of Jiangsu Province (BK20151277)

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