Sample preparation and sequencing efficiency of microRNA libraries from pituitary adenoma tissue and blood plasma of patients with acromegaly for Illumina platform

Мұқаба

Дәйексөз келтіру

Толық мәтін

Ашық рұқсат Ашық рұқсат
Рұқсат жабық Рұқсат берілді
Рұқсат жабық Тек жазылушылар үшін

Аннотация

MicroRNAs in tissues and biological fluids represent a promising class of biomarkers for the molecular diagnostics and therapy of numerous diseases, including oncological diseases. Biomarkers based on easily accessible biological fluids, primarily blood-based biomarkers, are of particular value for diagnostic and prognostic purposes. To explore the potential of microRNAs as prognostic cancer markers and targets for molecular therapy, global microRNA profiling is required, which is provided by next-generation sequencing (NGS). NGS offers high sensitivity, single nucleotide resolution, and the possibility of profiling a large number of samples in parallel. Despite the promising potential of microRNAs as biomarkers and the growing number of works in this area, the literature does not sufficiently address in detail the problems associated with sample preparation methods, the specifics of library preparation for microRNA sequencing, and the difficulties of quantitative analysis. Protocols for creating libraries for microRNA sequencing present specific challenges and require selecting conditions for each type of biological sample. Here, we present in detail the preparation of libraries for microRNA sequencing from pituitary adenoma tumor tissue and blood plasma of patients with acromegaly on the Illumina platform. We discuss the difficulties and limitations of the methods and evaluate the effectiveness of sequencing plasma and brain samples. The work can serve as a guide for researchers studying the mechanisms of microRNA regulation in endocrine diseases of the pituitary gland and will also allow for the adaptation of technical procedures for various biological samples in relation to other pathologies.

Толық мәтін

Рұқсат жабық

Авторлар туралы

Е. Ignatieva

Almazov National Medical Research Centre

Хат алмасуға жауапты Автор.
Email: lefutr@mail.ru
Ресей, Saint-Petersburg

E. Nerubenko

Almazov National Medical Research Centre

Email: lefutr@mail.ru
Ресей, Saint-Petersburg

O. Ivanova

Almazov National Medical Research Centre

Email: lefutr@mail.ru
Ресей, Saint-Petersburg

U. Tsoy

Almazov National Medical Research Centre

Email: lefutr@mail.ru
Ресей, Saint-Petersburg

R. Dmitrieva

Almazov National Medical Research Centre

Email: lefutr@mail.ru
Ресей, Saint-Petersburg

Әдебиет тізімі

  1. Iacomino G. (2023) miRNAs: the road from bench to bedside. Genes. 14, 314.
  2. O’Brien J., Hayder H., Zayed Y., Peng C. (2018) Overview of microRNA biogenesis, mechanisms of actions, and circulation. Front. Endocrinol. 9, 402.
  3. Svoronos A.A., Engelman D.M., Slack F.J. (2016) OncomiR or tumor suppressor? The duplicity of microRNAs in cancer. Cancer Res.76, 3666–3670.
  4. Chakrabortty A., Patton D.J., Smith B.F., Agarwal P. (2023) miRNAs: potential as biomarkers and therapeutic targets for cancer. Genes. 14, 1375.
  5. Lagos-Quintana M., Rauhut R., Yalcin A., Meyer J., Lendeckel W., Tuschl T. (2002) Identification of tissue-specific microRNAs from mouse. Curr. Biol. 12, 735–739.
  6. Si W., Shen J., Zheng H., Fan W. (2019) The role and mechanisms of action of microRNAs in cancer drug resistance. Clin. Epigenetics. 11, 25.
  7. Dai S., Li F., Xu S., Hu J., Gao L. (2023) The important role of miR-1-3p in cancers. J. Transl. Med. 21, 769.
  8. Jurj A., Zanoaga O., Braicu C., Lazar V., Tomuleasa C., Irimie A., Berindan-Neagoe I.A Comprehensive picture of extracellular vesicles and their contents. Molecular transfer to cancer cells. (2020) Cancers. 12, 298.
  9. Li M., Zeringer E., Barta T., Schageman J., Cheng A., Vlassov A.V. (2014) Analysis of the RNA content of the exosomes derived from blood serum and urine and its potential as biomarkers. Philosoph. Transact. Royal Soc. B: Biol. Sci. 369, 1652.
  10. Potla P., Ali S.A., Kapoor M. (2020) A bioinformatics approach to microRNA-sequencing analysis. Osteoarthr. Cartil. Open. 3, 100131.
  11. Andrews S. (2010) FastQC – a quality control tool for high throughput sequence data. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
  12. Martin M. (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10.
  13. Langmead B., Trapnell C., Pop M., Salzberg S.L. (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25.
  14. Kozomara A., Birgaoanu M., Griffiths-Jones S. (2019) miRBase: from microRNA sequences to function. Nucl. Acids Res. 47(D1), D155–D162.
  15. Liao Y., Smyth G.K., Shi W. (2014) FeatureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics. 30, 923–930.
  16. Ewels P., Magnusson M., Lundin S., Käller M. (2016) MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 32, 3047.
  17. Brown R.A.M., Epis M.R., Horsham J.L., Kabir T.D., Richardson K.L., Leedman P.J. (2018) Total RNA extraction from tissues for microRNA and target gene expression analysis: not all kits are created equal. BMC Biotechnol. 18, 16.
  18. Aryani A., Denecke B. (2015) In vitro application of ribonucleases: comparison of the effects on mRNA and miRNA stability. BMC Res. Notes. 8, 164.
  19. Li Z., Chen D., Wang Q., Tian H., Tan M., Peng D., Tan Y., Zhu J., Liang W., Zhang L. (2021) mRNA and microRNA stability validation of blood samples under different environmental conditions. Forensic Sci. Int. Genet. 55, 102567.
  20. Kondratov K., Kurapeev D., Popov M., Sidorova M., Minasian S., Galagudza M., Kostareva A., Fedorov A. (2016) Heparinase treatment of heparin-contaminated plasma from coronary artery bypass grafting patients enables reliable quantification of microRNAs. Biomol. Detect. Quantif. 8, 9.
  21. Coenen-Stass A.M.L, Magen I., Brooks T., Ben-Dov I.Z., Greensmith L., Hornstein E., Fratta P. (2018) Evaluation of methodologies for microRNA biomarker detection by next generation sequencing. RNA Biol. 15, 1133.
  22. Yeri A., Courtright A., Danielson K., Hutchins E., Alsop E., Carlson E., Hsieh M., Ziegler O., Das A., Shah R.V., Rozowsky J., Das S., Van Keuren-Jensen K. (2018) Evaluation of commercially available small RNASeq library preparation kits using low input RNA. BMC Genomics. 19, 331.
  23. Androvic P., Benesova S., Rohlova E., Kubista M., Valihrach L. (2022) Small RNA-sequencing for analysis of circulating miRNAs: benchmark study. J. Mol. Diagnostics. 24, 386–394.
  24. Heinicke F., Zhong X., Zucknick M., Breidenbach J., Sundaram A.Y.M., T. Flåm S., Leithaug M., Dalland M., Farmer A., Henderson J.M., Hussong M.A., Moll P., Nguyen L., McNulty A., Shaffer J.M., Shore S., Yip H.K., Vitkovska J., Rayner S., Lie B.A., Gilfillan G.D. (2020) Systematic assessment of commercially available low-input miRNA library preparation kits. RNA Biol. 17, 75–86.
  25. Alotaibi F. (2023) Exosomal microRNAs in cancer: potential biomarkers and immunotherapeutic targets for immune checkpoint molecules. Front. Genet. 14, 1052731.
  26. Kalinina O.V., Khudiakov A.А., Panshin D.D., Nikitin Yu. V., Ivanov A.M., Kostareva A.A., Golovkin A.S. (2022) Small non-coding RNA profiles of sorted plasma extracellular vesicles: technical approach. J. Evol. Biochem. Physiol. 58, 1847–1864.
  27. Petrova T., Kalinina O., Aquino A., Grigoryev E., Dubashynskaya N.V., Zubkova K., Kostareva A., Golovkin A. (2024) Topographic distribution of miRNAs (miR-30a, miR-223, miR-let-7a, miR-let-7f, miR-451, and miR-486) in the plasma extracellular vesicles. Non-Coding RNA. 10(1), 15.

Қосымша файлдар

Қосымша файлдар
Әрекет
1. JATS XML
Жүктеу
2. Fig. 1. Association of hsa-mir-1-3p microRNA with human diseases (according to data from the miRNet 2.0 visual analytical platform).

Жүктеу (346KB)
Метадеректер
3. Fig. 2. Scheme of RNA isolation from pituitary adenoma tissue and blood plasma of patients with acromegaly by the phenol extraction method using TRIzol®/TRIzol® LS reagents.

Жүктеу (547KB)
Метадеректер
4. Fig. 3. Analysis of total RNA from pituitary adenoma tissue and blood plasma samples of patients with acromegaly. a, b – Analysis of the quality of RNA isolated from pituitary tumor tissue of patients with acromegaly on the 2100 Bioanalyzer (Agilent RNA 6000 Nano Kit, “Agilent Technologies”). High-quality RNA from tissues is characterized by two distinct peaks of 18S and 28S rRNA (RIN = 7.8–10). c, d – Analysis of the quality of RNA isolated from blood plasma of patients with acromegaly on the 2100 Bioanalyzer. RNA is fragmented and concentrated in the low-molecular region (˂ 200 nucleotides, RIN about 2).

Жүктеу (212KB)
Метадеректер
5. Fig. 4. Scheme of preparation of small RNA library.

Жүктеу (307KB)
Метадеректер
6. Fig. 5. Analysis of small RNA libraries from pituitary adenoma tissue and blood plasma samples of patients with acromegaly. a, b – Electropherograms of small RNA library samples from pituitary tumor tissue of patients with acromegaly, obtained on the 2100 Bioanalyzer. The libraries are characterized by multiple peaks. The 142 bp peak is the target set of fragments containing sequences corresponding to microRNAs. Peaks of 65–85 bp correspond to residual primers. c, d – Electropherograms obtained on the 2100 Bioanalyzer, of small RNA library samples from blood plasma of patients with acromegaly. Peak 146/147 bp is the target set of fragments containing sequences corresponding to microRNAs and ready for high-throughput sequencing on the Illumina platform. The magnitudes of the target peak and the 124/125 bp peak containing adapter sequences are inversely proportional to each other.

Жүктеу (432KB)
Метадеректер
7. Fig. 6. Separation of a small RNA library pool in polyacrylamide gel (PAGE) and extraction of a set of target DNA fragments containing sequences corresponding to microRNAs from the gel. a – Scheme of electrophoretic separation in PAGE of a pool of small RNA libraries obtained from the blood plasma of patients with acromegaly. As a rule, during electrophoresis in the prepared pool of libraries, the target band (about 140 bp, containing fragments with inserts corresponding to microRNAs) and the band of adapter dimers (about 120 bp) are distinguished. b, c – Pool of microRNA libraries on an electropherogram (2100 Bioanalyzer), obtained by purification in PAGE according to the Small RNA-Seq Library Preparation Kit protocol (“Lexogen”). Peak 145/147 bp. represents a target set of fragments containing sequences corresponding to microRNAs, ready for high-throughput sequencing on the Illumina platform. Peaks 123/125 bp are formed by adapter dimers. With a high content (more than 50%) of adapter dimers in the pool, effective separation of fragments in PAGE is not ensured, as a result of which the final library extracted from the gel contains a large number of linker-linker type constructs (c).

Жүктеу (292KB)
Метадеректер
8. Fig. 7. Overall sequencing efficiency of pituitary adenoma tissue and plasma samples from patients with acromegaly. To assess the sequencing efficiency, the percentage of reads that passed adapter removal and alignment filtering was calculated. The distribution of reads obtained during sequencing is shown as the average percentage of reads: excluded after adapter removal; aligned to known human microRNAs (according to miRBase v22); uniquely aligned to the genome at miRNA-coding sites, relative to the total number of reads for microRNA libraries from brain tissue and plasma. n = 34 for brain tumor samples, n = 23 for plasma samples (seven blood samples from healthy donors and 16 from patients with acromegaly).

Жүктеу (285KB)
Метадеректер

© Russian Academy of Sciences, 2025