Combination of histological and transcriptomic approaches for cell types annotation in non-model organisms by example of spiny mice Acomys cahirinus

Cover Page

Cite item

Full Text

Open Access Open Access
Restricted Access Access granted
Restricted Access Subscription Access

Abstract

In mammals, cartilage tissue has a low potential for regeneration. Typically, the defect site is replaced by connective tissue. The Acomys cahirinus mouse is a relatively new model for studying tissue regeneration processes, specifically the elastic cartilage of the auricle. To investigate the molecular genetic mechanisms responsible for these processes and gain insight into the cellular and tissue composition of the intact auricle, we utilized the method of single-cell RNA sequencing (scRNA-seq). This method enables quantification of gene expression in the sample and modeling of cell clustering based on expression profiles. This allows for assessment of sample heterogeneity in terms of specific cell populations. Annotation of cell types, particularly in non-model organisms, should be supported by classical morphological studies to allow for more detailed identification of cell populations. This is necessary to separate clusters of cells that are grouped statistically based on similar expression profiles of a group of genes into smaller subpopulations. The objective of this study was to annotate all cell types present in the intact Acomys cahirinus auricle using a combination of transcriptomic approaches and classical histology methods. The study resulted in the annotation of 24 cell clusters based on known marker genes and by comparing genetic and morphological data.

Full Text

Restricted Access

About the authors

N. S. Filatov

Kazan (Volgaregion) Federal University

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008

A. I. Bilyalov

Kazan (Volgaregion) Federal University; Loginov Moscow Clinical Scientific Center

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008; Moscow, 111123

G. R. Gazizova

Kazan (Volgaregion) Federal University

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008

A. A. Bilyalova

Kazan (Volgaregion) Federal University

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008

E. I. Shagimardanova

Kazan (Volgaregion) Federal University, Russia 2Loginov Moscow Clinical Scientific Center,

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008; Moscow, 111123

M. V. Vorontsova

Lomonosov Moscow State University

Email: olga-sphinx@yandex.ru
Russian Federation, Moscow, 119991

A. P. Kiyasov

Kazan (Volgaregion) Federal University

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008

O. A. Gusev

Kazan (Volgaregion) Federal University; Juntendo University School of Medicine; LIFT Center LLC

Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008; Tokyo, 113-8421 Japan; Moscow, Skolkovo, 121205

O. S. Kozlova

Kazan (Volgaregion) Federal University

Author for correspondence.
Email: olga-sphinx@yandex.ru
Russian Federation, Kazan, 420008

References

  1. Maden M., Varholick J.A. Model systems for regeneration: The spiny mouse, Acomys cahirinus// Development. 2020. V. 147. № 4. https://doi.org/10.1242/dev.167718
  2. Билялов А.И., Филимошина Д.Д., Филатов Н.С. и др. У мышей рода Acomys после травмы восстанавливается эластический хрящ ушной раковины // Гены и клетки. 2022. Т. 17. № 1. С. 42–47. (Bilyalov A.I., Filimoshina D.D., Filatov N.S. et al. In mice of the genus Acomys, the elastic cartilage of the auricle is restored after injury // Genes and cells. 2022. V. 17. № 1. P. 42–47.) https://doi.org/10.23868/202205003
  3. Kuksin M., Morel D., Aglave M. et al. Applications of single-cell and bulk RNA sequencing in onco-immunology // Eur. J. Cancer. 2021. V. 149. P. 193–210. https://doi.org/10.1016/j.ejca.2021.03.005
  4. Nguyen E.D., Fard V.N., Kim B.Y. et al. Genome report: Chromosome-scale genome assembly of the African spiny mouse (Acomys cahirinus) // bioRxiv 2023.04.03.535372. https://doi.org/10.1101/2023.04.03.535372
  5. Lun A.T.L., Riesenfeld S., Andrews T. et al. EmptyDrops: Distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data // Genome Biol. 2019. V. 20. № 1. P. 63. https://doi.org/10.1186/s13059-019-1662-y
  6. Wolock S.L., Lopez R., Klein A.M. Scrublet: Computational identification of cell doublets in single-cell transcriptomic data // Cell Syst. 2019. V. 8. № 4. P. 281–291.e9. https://doi.org/10.1016/j.cels.2018.11.005
  7. Hao Y., Hao S., Andersen-Nissen E. et al. Integrated analysis of multimodal single-cell data // Cell. 2021. V. 184. № 13. P. 3573–3587. e29. https://doi.org/doi: 10.1016/j.cell.2021.04.048
  8. Bairati A., Comazzi M., Gioria M. A comparative study of perichondrial tissue in mammalian cartilages // Tissue Cell. 1996. V. 28. № 4. P. 455–468. https://doi.org/10.1016/s0040-8166(96)80031-0
  9. Treuting P.M., Dintzis S.M. 22 – Special senses: Ear // Comparative Anatomy and Histology, Acad. Press, 2012. P. 419–432. https://doi.org/10.1016/B978-0-12-381361-9.00022-6
  10. Lefebvre V., Angelozzi M., Haseeb A. SOX9 in cartilage development and disease // Curr. Opin. Cell Biol. 2019. V. 61. P. 39–47. https://doi.org/10.1016/j.ceb.2019.07.008
  11. Dateki S. ACAN mutations as a cause of familial short stature // Clin. Pediatr. Endocrinol. 2017. V. 26. № 3. P. 119–125. https://doi.org/10.1297/cpe.26.119
  12. Batista M.A., Nia H.T., Önnerfjord P. et al. Nanomechanical phenotype of chondroadherin-null murine articular cartilage // Matrix Biol. 2014. V. 38. P. 84–90. https://doi.org/10.1016/j.matbio.2014.05.008
  13. Taylor S.E., Lee J., Smeriglio P. et al. Identification of human juvenile chondrocyte-specific factors that stimulate stem cell growth // Tissue Eng. Part A. 2016. V. 22. № 7–8. P. 645–653. https://doi.org/10.1089/ten.TEA.2015.0366
  14. Boot-Handford R.P., Tuckwell D.S. Fibrillar collagen: The key to vertebrate evolution? A tale of molecular incest // Bioessays. 2003. V. 25. № 2. P. 142–151. https://doi.org/10.1002/bies.10230
  15. Reed C.C., Iozzo R.V. The role of decorin in collagen fibrillogenesis and skin homeostasis // Glycoconj. J. 2002. V. 19. № 4–5. P. 249–255. https://doi.org/10.1023/A:1025383913444
  16. Billi A.C., Ma F., Plazyo O. et al. Nonlesional lupus skin contributes to inflammatory education of myeloid cells and primes for cutaneous inflammation // Sci. Transl. Med. 2022. V. 27. № 14. P. 642. https://doi.org/10.1126/scitranslmed.abn2263
  17. Wang S., Drummond M.L., Guerrero-Juarez C.F. et al. Single cell transcriptomics of human epidermis identifies basal stem cell transition states // Nat. Commun. 2020. V. 11. № 1. P. 4239. https://doi.org/10.1038/s41467-020-18075-7
  18. Alderson N.L., Maldonado E.N., Kern M.J. et al. FA2H-dependent fatty acid 2-hydroxylation in postnatal mouse brain // J. Lipid Res. 2006. V. 47. № 12. P. 2772–2780. https://doi.org/10.1194/jlr.M600362-JLR200
  19. Xu Y., Du X., Turner N. et al. Enhanced acyl-CoA: Cholesterol acyltransferase activity increases cholesterol levels on the lipid droplet surface and impairs adipocyte function // J. Biol. Chem. 2019. V. 294. № 50. P. 19306–19321. https://doi.org/10.1074/jbc.RA119.011160
  20. Shih B.B., Nirmal A.J., Headon D.J. et al. Derivation of marker gene signatures from human skin and their use in the interpretation of the transcriptional changes associated with dermatological disorders // J. Pathol. 2017. V. 241. № 5. P. 600–613. https://doi.org/10.1002/path.4864
  21. Polkoff K.M., Gupta N.K., Green A.J. et al. LGR5 is a conserved marker of hair follicle stem cells in multiple species and is present early and throughout follicle morphogenesis // Sci. Rep. 2022. V. 12. № 1. P. 9104. https://doi.org/10.1038/s41598-022-13056-w
  22. Park S., DiMaio T.A., Scheef E.A. et al. PECAM-1 regulates proangiogenic properties of endothelial cells through modulation of cell-cell and cell-matrix interactions // Am. J. Physiol. Cell Physiol. 2010. V. 299. № 6. P. 1468–1484. https://doi.org/10.1152/ajpcell.00246.2010
  23. Rossi E., Bernabeu C., Smadja D.M. Endoglin as an adhesion molecule in mature and progenitor endothelial cells: A function beyond TGF-β // Front. Med. 2019. V. 6. https://doi.org/10.3389/fmed.2019.00010
  24. Inoue M., Ishida T., Yasuda T. et al. Endothelial cell-selective adhesion molecule modulates atherosclerosis through plaque angiogenesis and monocyte-endothelial interaction // Microvasc. Res. 2010. V. 80. № 2. P. 179–187. https://doi.org/10.1016/j.mvr.2010.04.005
  25. Ma S.C., Li Q., Peng J.Y et al. Claudin-5 regulates blood-brain barrier permeability by modifying brain microvascular endothelial cell proliferation, migration, and adhesion to prevent lung cancer metastasis // CNS Neurosci. Theor. 2017. V. 23. № 12. P. 947–960. https://doi.org/10.1111/cns.12764
  26. Fajardo L.F. The complexity of endothelial cells. A review // Am. J. Clin. Pathol. 1989. V. 92. № 2. P. 241–250. https://doi.org/10.1093/ajcp/92.2.241
  27. Su H., Na N., Zhang X., Zhao Y. The biological function and significance of CD74 in immune diseases // Inflamm. Res. 2017. V. 66. № 3. P. 209–216. https://doi.org/10.1007/s00011-016-0995-1
  28. Stephens W.Z., Kubinak J.L., Ghazaryan A. et al. Epithelial-myeloid exchange of MHC class II constrains immunity and microbiota composition // Cell Rep. 2021. V. 37. № 5. https://doi.org/10.1016/j.celrep.2021.109916
  29. Hou W., Kong L., Hou Z., Ji H. CD44 is a prognostic biomarker and correlated with immune infiltrates in gastric cancer // BMC Med. Genomics. 2022. V. 15. № 1. P. 225. https://doi.org/10.1186/s12920-022-01383-w
  30. Muruganandam M., Ariza-Hutchinson A., Patel R.A., Sibbitt W.L. Jr. Biomarkers in the pathogenesis, diagnosis, and treatment of systemic sclerosis // J. Inflamm. Res. 2023. V. 16. P. 4633–4660. https://doi.org/10.2147/JIR.S379815
  31. Kendirli A., de la Rosa C., Lämmle K.F. et al. A genome-wide in vivo CRISPR screen identifies essential regulators of T cell migration to the CNS in a multiple sclerosis model // Nat. Neurosci. 2023. V. 26. № 10. P. 1713–1725. https://doi.org/10.1038/s41593-023-01432-2
  32. Kozina A.A., Baryshnikova N.V., Ilinskaya A.Y. et al. Novel mutation in the MPZ gene causes early-onset but slow-progressive Charcot-Marie-Tooth disease in a Russian family: A case report // J. Int. Med. Res. 2022. V. 50. № 12. https://doi.org/doi: 10.1177/03000605221139718
  33. Smirnova E.V., Rakitina T.V., Ziganshin R.H. et al. Comprehensive atlas of the myelin basic protein interaction landscape // Biomolecules. 2021. V. 11. № 11. https://doi.org/10.3390/biom11111628
  34. Kim D., An H., Fan C., Park Y. Identifying oligodendrocyte enhancers governing Plp1 expression // Hum. Mol. Genet. 2021. V. 30. № 23. P. 2225–2239. https://doi.org/10.1093/hmg/ddab184
  35. Ruan J., Zhang L., Hu D. et al. Novel Myh11 dual reporter mouse model provides definitive labeling and identification of smooth muscle cells-brief report // Arterioscler. Thromb. Vasc. Biol. 2021. V. 41. № 2. P. 815–821. https://doi.org/10.1161/ATVBAHA.120.315107
  36. Goding C.R., Arnheiter H. MITF-the first 25 years // Genes Dev. 2019. V. 33. № 15–16. P. 983–1007. https://doi.org/10.1101/gad.324657.119
  37. Кичигина Т.Н., Грушин В.Н., Беликова И.С., Мяделец О.Д. Меланоциты: строение, функции, методы выявления, роль в кожной патологии // Вестн. Витебского гос. мед. ун-та. 2007. Т. 6. № 4. С. 5–16. https://elib.vsmu.by/handle/123/8528
  38. Jeong J., Han W., Hong E. et al. Regulation of NLGN3 and the synaptic Rho-GEF signaling pathway by CDK5 // J. Neurosci. 2023. V. 43. № 44. P. 7264–7275. https://doi.org/10.1523/JNEUROSCI.2309-22.2023
  39. Sato S., Suzuki Y., Kikuchi M. et al. Sputum neurturin levels in adult asthmatic subjects // J. Asthma Allergy. 2023. V. 16. P. 889–901. https://doi.org/10.2147/JAA.S421742

Supplementary files

Supplementary Files
Action
1. JATS XML
2. Fig. 1. Auricle of Acomys. 1 – epidermis, 2 – dermis, 3 – hair follicle, 4 – sebaceous glands, 5 – white adipocytes, 6 – striated skeletal myocytes, 7 – elastic cartilage, 8 – blood vessel, 9 – fibrous layer of perichondrium, 10 – chondrogenic layer of perichondrium. Stained according to Mallory. Magnification x200 (a), x500 (b).

Download (403KB)
3. Fig. 2. Clustering and annotation of cell types based on scRNA-Seq data. a – clusterogram (clusters 1–24) of Acomys cahirinus auricle cells constructed using the UMAP (Uniform Manifold Approximation and Projection) method; b – visualization of the average expression of a number of marker genes characteristic of different cell types.

Download (243KB)
4. Fig. 3. Expression of marker genes and final cell type annotation. (a) Heat map showing the most specifically expressed genes in each cell cluster (1–15); (b) Acomys cahirinus ear cell clusterogram with cell type annotation constructed by the UMAP method.

Download (919KB)

Copyright (c) 2024 Russian Academy of Sciences