RESUMEN
Aging-related salivary gland degeneration usually causes poor oral health. Periductal fibrosis frequently occurs in the submandibular gland of the elderly. Transforming growth factor ß1 (TGF-ß1) is the primary driving factor for fibrosis, which exhibits an increase in the fibrotic submandibular gland tissue. This study aimed to investigate the effects of TGF-ß1 on the human submandibular gland (HSG) cell secretory function and its influences on aquaporin 5 (AQP5) expressions and distribution. We found that TGF-ß1 reduces the protein secretion amount of HSG and leads to the abundance alteration of 151 secretory proteins. Data are available via ProteomeXchange with the identifier PXD043185. The majority of HSG secretory proteins (84.11%) could be matched to the human saliva proteome. Meanwhile, TGF-ß1 enhances the expression of COL4A2, COL5A1, COL7A1, COL1A1, COL2A1, and α-SMA, hinting that TGF-ß1 possesses the potential to drive HSG fibrosis-related events. Besides, TGF-ß1 also attenuates the AQP5 expression and its membrane distribution in HSGs. The percentage for TGF-ß1-induced AQP5 reduction (52.28%) is much greater than that of the TGF-ß1-induced secretory protein concentration reduction (16.53%). Taken together, we concluded that TGF-ß1 triggers salivary hypofunction via attenuating protein secretion and AQP5 expression in HSGs, which may be associated with TGF-ß1-driven fibrosis events in HSGs.
Asunto(s)
Acuaporina 5 , Glándula Submandibular , Factor de Crecimiento Transformador beta1 , Humanos , Acuaporina 5/genética , Acuaporina 5/metabolismo , Colágeno Tipo VII/metabolismo , Saliva/metabolismo , Glándula Submandibular/citología , Glándula Submandibular/metabolismo , Factor de Crecimiento Transformador beta1/farmacologíaRESUMEN
Transforming growth factor-beta (TGF-ß) superfamily members orchestrate a wide breadth of biological processes. Through Sma and Mad (Smad)-related dependent or noncanonical pathways, TGF-ß members involve in the occurrence and development of many diseases such as cancers, fibrosis, autoimmune diseases, cardiovascular diseases and brain diseases. Glycosylation is one kind of the most common posttranslational modifications on proteins or lipids. Abnormal protein glycosylation can lead to protein malfunction and biological process disorder, thereby causing serious diseases. Previously, researchers commonly make comprehensive systematic overviews on the roles of TGF-ß signaling in a specific disease or biological process. In recent years, more and more evidences associate glycosylation modification with TGF-ß signaling pathway, and we can no longer disengage and ignore the roles of glycosylation from TGF-ß signaling to make investigation. In this review, we provide an overview of current findings involved in glycosylation within TGF-ßs and theirs receptors, and the interaction effects between glycosylation and TGF-ß subfamily signaling, concluding that there is an intricate mutual regulation between glycosylation and TGF-ß signaling, hoping to present the glycosylation regulatory patterns that concealed in TGF-ßs signaling pathways.
Asunto(s)
Receptores de Factores de Crecimiento Transformadores beta , Transducción de Señal , Glicosilación , Receptores de Factores de Crecimiento Transformadores beta/metabolismo , Transducción de Señal/fisiología , Factor de Crecimiento Transformador beta/metabolismo , Isoformas de Proteínas/metabolismo , Factores de Crecimiento Transformadores/metabolismo , Factor de Crecimiento Transformador beta1/metabolismoRESUMEN
BACKGROUND: Fibroblasts are the most predominant cell subpopulation in the dermal layer of human skin, they play an important role in maintaining skin architecture and function. The senescence of fibroblasts is one of major causes of skin aging and chronic wound in the elderly, which is accompanied with a reduction of α2,6-sialylation on the cell surface. AIMS: In this study, we investigated the effects of the bovine sialoglycoproteins on normal human dermal fibroblasts (NHDF). RESULTS: The results showed that bovine sialoglycoproteins could promote the proliferation and migration of NHDF cells, and accelerate the contraction of fibroblast-populated collagen lattice (FPCL). The average doubling time of NHDF cells treated with bovine sialoglycoproteins (0.5 mg/mL) was 31.1 ± 1.0 h whereas that was 37.9 ± 2.7 h for the control (p Ë 0.05). Moreover, the expression of basic fibroblast growth factor (FGF-2) was upregulated, while that of transforming growth factor-beta 1 (TGF-ß1) and human type I collagen (COL-I) were downregulated in treated NHDF cells. Furthermore, bovine sialoglycoproteins treatment significantly enhanced the α2,6-sialylation on the cell surfaces, which was consistent with the upregulation of α2,6-sialyltransferase I (ST6GAL1) expression. CONCLUSIONS: These results indicated that the bovine sialoglycoproteins might be developed as a reagent against skin aging in the cosmetic industry, or as a new candidate for accelerating skin wound healing and inhibiting scar formation.
Asunto(s)
Envejecimiento de la Piel , Cicatrización de Heridas , Humanos , Animales , Bovinos , Anciano , Piel , Cicatriz/patología , Colágeno/metabolismo , Factor de Crecimiento Transformador beta1/metabolismo , Fibroblastos/metabolismoRESUMEN
With the advantages of convenient, painless and non-invasive collection, saliva holds great promise as a valuable biomarker source for cancer detection, pathological assessment and therapeutic monitoring. Salivary glycopatterns have shown significant potential for cancer screening in recent years. However, the understanding of benign lesions at non-cancerous sites in cancer diagnosis has been overlooked. Clarifying the influence of benign lesions on salivary glycopatterns and cancer screening is crucial for advancing the development of salivary glycopattern-based diagnostics. In this study, 2885 samples were analyzed using lectin microarrays to identify variations in salivary glycopatterns according to the number, location, and type of lesions. By utilizing our previously published data of tumor-associated salivary glycopatterns, the performance of machine learning algorithm for cancer screening was investigated to evaluate the effect of adding benign disease cases to the control group. The results demonstrated that both the location and number of lesions had discernible effects on salivary glycopatterns. And it was also revealed that incorporating a broad range of benign diseases into the controls improved the classifier's performance in distinguishing cancer cases from controls. This finding holds guiding significance for enhancing salivary glycopattern-based cancer screening and facilitates their practical implementation in clinical settings.