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Quantification of background expression of interferon beta in cell culture of Siberian bat (Myotis sibiricus)

https://doi.org/10.29413/ABS.2025-10.5.25

Abstract

Background. The study of the immune response of these mammals to viral infections is necessary to reveal the fundamental mechanisms of the circulation of zoonotic infections in nature. There is a hypothesis about the constantly “on” activity of the interferon pathway proteins, developed evolutionarily in bats to counteract viral infections. We assessed the expression of interferon beta as a marker of the innate immune system in kidney cells of the Siberian bat (Myotis sibiricus, Kastschenko, 1905) MdbK3-14.

The aim. Evaluation of the background level of interferon beta (IFN-β) gene expression in bat cells as a marker of the activity of the mammalian innate immune system.

Materials and methods. MdbK3-14 cells were grown in 24-well plates. Cell monolayers were detached with trypsin solution and total RNA was isolated. The concentration of mRNA of IFN-β gene transcripts and reference genes beta actin (ACTB) and succinate dehydrogenase subunit A (SDHA) was determined by one-step multiplex RT-qPCR and confirmed by RT-dPCR.

Results. Specific primers with a probe for detecting mRNA of the IFN-β gene in bat cells were designed. The detection of SDHA and IFN-β gene transcripts was stable both in RT-qPCR (CV = 0.5 % and CV = 0.2 %, respectively) and in RT-dPCR (CV = 0.8 % and CV = 1.4 %, respectively). In addition, stable detection of ACTB mRNA was achieved using RT-dPCR (CV = 0.8 %), but the average variability value for actin using RT-qPCR exceeded the permissible value (CV = 3.6 % with an acceptable CV ≤ 2 %). The results of quantitative determination in RT-qPCR and RT-dPCR correlated with each other. The expression levels of IFN-β in MdbK3-14 cells averaged 0.97 ± 0.15 relative units in RT-qPCR and 0.13 ± 0.05 relative units in RT-dPCR.

Conclusions. In the absence of immune stimulation, background expression of IFN-β occurs in the M. sibiricus kidney cell line.

About the Authors

N. A. Liapunova
Scientific Centre for Family Health and Human Reproduction Problems
Russian Federation

Natalia A. Liapunovа – Cand. Sc. (Biol.), Research Officer at the Laboratory of Arthropod-Borne Infections, Institute of Epidemiology and Microbiology, 

Timiryazeva st., 16, Irkutsk 664003



M. A. Khasnatinov
Scientific Centre for Family Health and Human Reproduction Problems
Russian Federation

Maxim A. Khasnatinov – Dr. Sc. (Biol.), Chief Researcher, Head of the Laboratory of Arthropod-Borne Infections, Institute of Epidemiology and Microbiology, 

Timiryazeva st., 16, Irkutsk 664003



G. A. Danchinova
Scientific Centre for Family Health and Human Reproduction Problems
Russian Federation

Galina A. Danchinova – Dr. Sc. (Biol.), Chief Researcher at the Laboratory of Arthropod-Borne Infections, Institute of Epidemiology and Microbiology, 

Timiryazeva st., 16, Irkutsk 664003



I. S. Solovarov
Scientific Centre for Family Health and Human Reproduction Problems
Russian Federation

Innokentii S. Solovarov – Cand. Sc. (Biol.), Junior Research Officer at the Laboratory of Arthropod-Borne Infections, Institute of Epidemiology and Microbiology, 

Timiryazeva st., 16, Irkutsk 664003



References

1. Botvinkin AD. Viruses and bats: interdisciplinary problems. Voprosy virusologii. 2021; 66(4): 259-268. (In Russ.). doi: 10.36233/0507-4088-79

2. Baker ML, Schountz T, Wang LF. Antiviral immune responses of bats: a review. Zoonoses Public Health. 2013; 60(1): 104-16. doi: 10.1111/j.1863-2378.2012.01528.x

3. Liang YZ, Wu LJ, Zhang Q, et al. Cloning, expression, and antiviral activity of interferon β from the Chinese microbat, Myotis davidii. Virol Sin. 2015; 30(6): 425-32. doi: 10.1007/s12250-015-3668-2

4. Li J, Zhang G, Cheng D, Ren H, et al. Molecular characterization of RIG-I, STAT-1 and IFN-beta in the horseshoe bat. Gene. 2015; 561(1): 115-23. doi: 10.1016/j.gene.2015.02.013

5. Hölzer M, Schoen A, Wulle J, et al. Virus- and Interferon Alpha-Induced Transcriptomes of Cells from the Microbat Myotis daubentonii. iScience. 2019; 19: 647-661. doi: 10.1016/j.isci.2019.08.016

6. Schountz T, Baker ML, Butler J, Munster V. Immunological Control of Viral Infections in Bats and the Emergence of Viruses Highly Pathogenic to Humans. Front Immunol. 2017; 8: 1098. doi: 10.3389/fimmu.2017.01098

7. Zhou P, Tachedjian M, Wynne JW, et al. Contraction of the type I IFN locus and unusual constitutive expression of IFN-α in bats. Proc Natl Acad Sci USA. 2016; 113(10): 2696- 701. doi: 10.1073/pnas.1518240113

8. Liapunovа NA, Khasnatinov MA, Danchinova GA. Optimization of a Quantitative Real-Time RT-PCR Technique for Evaluation of Concentration of Genomic +RNA of Tick-Borne Encephalitis Virus. Acta Biomedica Scientifica. 2019; 4(5): 116-121. (In Russ.). doi: 10.29413/ABS.2019-4.5.18

9. Liapunovа NA, Khasnatinov MA, Danchinova GA. Features of Reproduction of Tick-Borne Encephalitis Virus in a New Cell Line of the Siberian Bat Myotis sibiricus (Kastschenko, 1905). Acta Biomedica Scientifica. 2020; 5(6): 271-275. (In Russ.). doi: 10.29413/ABS.2020-5.6.36

10. Liapunova NA. Features of reproduction of tick-borne encephalitis virus in transplantable cell lines of wild mammals – reservoir and accidental hosts of the virus. Avtoref. dis. kand. biol. nauk. Kol’tsovo: FBUN GNTS VB «Vektor»; 2021. (In Russ.).

11. Gu Y, Tang S, Wang Z, et al. A pan-cancer analysis of the prognostic and immunological role of β-actin (ACTB) in human cancers. Bioengineered. 2021; 12(1): 6166- 6185. doi: 10.1080/21655979.2021.1973220

12. Higuera A, Muñoz M, López MC, et al. Succinate dehydrogenase gene as a marker for studying Blastocystis genetic diversity. Heliyon. 2020; 6(11): e05387. doi: 10.1016/j.heliyon.2020.e05387

13. Liapunova NA, Khasnatinov MA, Danchinova GA, Solovarov IS. Development of RT-qPCR assay for assessing the expression of ACTB and SDHA housekeeping genes in the cell cultures of mammalian hosts of zoonotic infections. Acta Biomedica Scientifica. 2024; 9(5): 84-95. (In Russ.). doi: 10.29413/ABS.2024-9.5.9

14. Taylor SC, Laperriere G, Germain H. Droplet digital PCR versus qPCR for gene expression analysis with low abundant targets: from variable nonsense to publication quality data. Sci. Rep. 2017; 7(1): 2409. doi: 10.1038/s41598-017-02217-x

15. Walpole RE, Myers RH, Myers SL, et al. Probability and statistics for engineers and scientists, 8th ed. Upper Saddle River: Pearson Education. 2007: 791.

16. Rogers-Broadway KR, Karteris E. Amplification efficiency and thermal stability of qPCR instrumentation: Current landscape and future perspectives. Exp Ther Med. 2015; 10(4): 1261-1264. doi: 10.3892/etm.2015.2712

17. Hays A, Islam R, Matys K, et al. Best Practices in qPCR and dPCR Validation in Regulated Bioanalytical Laboratories. AAPS J. 2022; 24(2): 36. doi: 10.1208/s12248-022-00686-1

18. Limothai U, Chuaypen N, Poovorawan K, et al. Reverse transcriptase droplet digital PCR vs reverse transcriptase quantitative real-time PCR for serum HBV RNA quantification. J. Med. Virol. 2020; 92(12): 3365-3372. doi: 10.1002/jmv.25792

19. Whale AS, von der Heide EK, Kohlenberg M, et al. Digital PCR can augment the interpretation of RT-qPCR Cq values for SARS-CoV-2 diagnostics. Methods. 2022; 201: 5-14. doi: 10.1016/j.ymeth.2021.08.006


Review

For citations:


Liapunova N.A., Khasnatinov M.A., Danchinova G.A., Solovarov I.S. Quantification of background expression of interferon beta in cell culture of Siberian bat (Myotis sibiricus). Acta Biomedica Scientifica. 2025;10(5):233-243. (In Russ.) https://doi.org/10.29413/ABS.2025-10.5.25

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