Single-cell transcriptome characterization of oral mucosal fibroblasts

doi:10.19439/j.sjos.2024.01.001

Abstract

Abstract: PURPOSE: To elucidate the disparities and similarities in the composition and function of fibroblast subtypes between normal oral mucosa and cutaneous tissue, to establish a unified classification of fibroblast subtypes between these two tissue types, comprehend the differences and similarities in their functionalities, and provide a foundational basis for future applications in the fields of tissue repair and regeneration. METHODS: Four single-cell databases from both oral mucosa and cutaneous tissue were integrated and fibroblast subpopulations were extracted. Batch effects were eliminated using Harmony, and fibroblast subpopulations were subsequently classified via UMAP (Uniform Manifold Approximation and Projection) clustering. The functional analysis of these subpopulations was conducted through gene set enrichment results. Statistical analysis was performed with R 4.2.0 software package. RESULTS: Eight distinct functional fibroblast subpopulations were defined, and their functions were found to be associated with the composition of the extracellular matrix, immunity, and contraction. Statistical analysis revealed differences in the composition ratios of these subpopulations between oral mucosa and skin tissue. CONCLUSIONS: To evaluate the role of fibroblasts in tissue homeostasis and wound healing accomplished by integrating and analyzing fibroblasts from normal skin and oral mucosal tissue from various sites, this study identifies the differences in fibroblast subpopulation composition and function between these two tissue types in healthy conditions, and provides an understanding of oral mucosa and skin homeostasis and cellular function at the transcriptomic level. The findings of this study may serve as a basis for future research in this area.

Key words: Oral mucosa, Fibroblasts, Single-cell gene expression analysis

CLC Number:

R782.1

ZHAO Jiong, BAI Guo, YANG Chi. Single-cell transcriptome characterization of oral mucosal fibroblasts[J]. Shanghai Journal of Stomatology, 2024, 33(1): 1-5.

References

[1] Waasdorp M, Krom BP, Bikker FJ, et al.The bigger picture: why oral mucosa heals better than skin[J]. Biomolecules, 2021, 11(8): 1165-1187.
[2] Griffin MF, Fahy EJ, King M, et al.Understanding scarring in the oral mucosa[J]. Adv Wound Care (New Rochelle), 2022, 11(10): 537-547.
[3] Torres P, Castro M, Reyes M, et al.Histatins, wound healing, and cell migration[J]. Oral Dis, 2018, 24(7): 1150-1160.
[4] Sim SL, Kumari S, Kaur S, et al.Macrophages in skin wounds: functions and therapeutic potential[J]. Biomolecules, 2022, 12(11): 1659-1659.
[5] Guan Y, Yang YJ, Nagarajan P, et al.Transcriptional and signalling regulation of skin epithelial stem cells in homeostasis, wounds and cancer[J]. Exp Dermatol, 2021, 30(4): 529-545.
[6] Zhou Y.Beyond fibroblast heterogeneity: what single-cell RNA sequencing tells us[J]. Am J Respir Cell Mol Biol, 2019, 61(1): 7-8.
[7] Ascensión AM, Fuertes-álvarez S, Ibañez-Solé O, et al. Human dermal fibroblast subpopulations are conserved across single-cell RNA sequencing studies[J]. J Invest Dermatol, 2021, 141(7): 1735-1744.
[8] Williams DW, Greenwell-Wild T, Brenchley L, et al.Human oral mucosa cell atlas reveals a stromal-neutrophil axis regulating tissue immunity[J]. Cell, 2021, 184(15): 4090-4104.
[9] Magnano M, Bussi M, de Stefani A, et al. Prognostic factors for head and neck tumor recurrence[J]. Acta Otolaryngol, 1995, 115(6): 833-838.
[10] Takizawa H, Karakawa A, Suzawa T, et al.Neural crest-derived cells possess differentiation potential to keratinocytes in the process of wound healing[J]. Biomed Pharmacother, 2022, 146: 112593.
[11] Korsunsky I, Millard N, Fan J, et al.Fast, sensitive and accurate integration of single-cell data with Harmony[J]. Nat Methods, 2019, 16(12): 1289-1296.
[12] Hao Y, Hao S, Andersen-Nissen E, et al.Integrated analysis of multimodal single-cell data[J]. Cell, 2021, 184(13): 3573-3587.
[13] Hänzelmann S, Castelo R, Guinney J.GSVA: gene set variation analysis for microarray and RNA-Seq data[J]. BMC Bioinformatics, 2013, 14(1): 7-15.
[14] Attwell D, Mishra A, Hall CN, et al.What is a pericyte?[J]. J Cereb Blood Flow Metab, 2016, 36(2): 451-455.
[15] Hosaka K, Yang Y, Seki T, et al.Pericyte-fibroblast transition promotes tumor growth and metastasis[J]. Proc Natl Acad Sci USA, 2016, 113(38): e5618-e5627.
[16] Humphreys BD.Targeting pericyte differentiation as a strategy to modulate kidney fibrosis in diabetic nephropathy[J]. Semin Nephrol, 2012, 32(5): 463-470.
[17] Chen Y, Wang H, Yang Q, et al.Single-cell RNA landscape of the osteoimmunology microenvironment in periodontitis[J]. Theranostics, 2022, 12(3): 1074-1096.
[18] Pagani F, Tratta E, DellEra P, et al. EBF1 is expressed in pericytes and contributes to pericyte cell commitment[J]. Histochem Cell Biol, 2021, 156(4): 333-347.
[19] Sinha S, Sparks HD, Labit E, et al.Fibroblast inflammatory priming determines regenerative versus fibrotic skin repair in reindeer[J]. Cell, 2022, 185(25): 4717-4736.
[20] Petrou IG, Nikou S, Madduri S, et al.The role of hippo signaling pathway and ILK in the pathophysiology of human hypertrophic scars and keloids: an immunohistochemical investigation[J]. Cells, 2022, 11(21): 3426-3426.
[21] Tabib T, Huang M, Morse N, et al.Myofibroblast transcriptome indicates SFRP2^hi fibroblast progenitors in systemic sclerosis skin[J]. Nat Commun, 2021, 12(1): 4384-4396.
[22] Mascharak S, des Jardins-Park HE, Davitt MF, et al. Preventing engrailed-1 activation in fibroblasts yields wound regeneration without scarring [J]. Science (1979), 2021, 372(6540): eaba2374.