RESUMEN
OBJECTIVE: The transcription factor networks that drive parotid salivary gland progenitor cells to terminally differentiate, remain largely unknown and are vital to understanding the regeneration process. METHODOLOGY: A systems biology approach was taken to measure mRNA and microRNA expression in vivo across acinar cell terminal differentiation in the rat parotid salivary gland. Laser capture microdissection (LCM) was used to specifically isolate acinar cell RNA at times spanning the month-long period of parotid differentiation. RESULTS: Clustering of microarray measurements suggests that expression occurs in four stages. mRNA expression patterns suggest a novel role for Pparg which is transiently increased during mid postnatal differentiation in concert with several target gene mRNAs. 79 microRNAs are significantly differentially expressed across time. Profiles of statistically significant changes of mRNA expression, combined with reciprocal correlations of microRNAs and their target mRNAs, suggest a putative network involving Klf4, a differentiation inhibiting transcription factor, which decreases as several targeting microRNAs increase late in differentiation. The network suggests a molecular switch (involving Prdm1, Sox11, Pax5, miR-200a, and miR-30a) progressively decreases repression of Xbp1 gene transcription, in concert with decreased translational repression by miR-214. The transcription factor Xbp1 mRNA is initially low, increases progressively, and may be maintained by a positive feedback loop with Atf6. Transfection studies show that Xbp1 activates the Mist1 promoter [corrected]. In addition, Xbp1 and Mist1 each activate the parotid secretory protein (Psp) gene, which encodes an abundant salivary protein, and is a marker of terminal differentiation. CONCLUSION: This study identifies novel expression patterns of Pparg, Klf4, and Sox11 during parotid acinar cell differentiation, as well as numerous differentially expressed microRNAs. Network analysis identifies a novel stemness arm, a genetic switch involving transcription factors and microRNAs, and transition to an Xbp1 driven differentiation network. This proposed network suggests key regulatory interactions in parotid gland terminal differentiation.
Asunto(s)
Células Acinares/citología , Glándula Parótida/citología , Biología de Sistemas/métodos , Animales , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genética , Diferenciación Celular/genética , Diferenciación Celular/fisiología , Proteínas de Unión al ADN/genética , Femenino , Redes Reguladoras de Genes/genética , Factor 4 Similar a Kruppel , Embarazo , ARN Mensajero/genética , Ratas , Factores de Transcripción del Factor Regulador X , Factores de Transcripción/genética , Proteína 1 de Unión a la X-BoxRESUMEN
In modern systems biology the modeling of longitudinal data, such as changes in mRNA concentrations, is often of interest. Fully parametric, ordinary differential equations (ODE)-based models are typically developed for the purpose, but their lack of fit in some examples indicates that more flexible Bayesian models may be beneficial, particularly when there are relatively few data points available. However, under such sparse data scenarios it is often difficult to identify the most suitable model. The process of falsifying inappropriate candidate models is called model discrimination. We propose here a formal method of discrimination between competing Bayesian mixture-type longitudinal models that is both sensitive and sufficiently flexible to account for the complex variability of the longitudinal molecular data. The ideas from the field of Bayesian analysis of computer model validation are applied, along with modern Markov Chain Monte Carlo (MCMC) algorithms, in order to derive an appropriate Bayes discriminant rule. We restrict attention to the two-model comparison problem and present the application of the proposed rule to the mRNA data in the de-differentiation network of three mRNA concentrations in mammalian salivary glands as well as to a large synthetic dataset derived from the model used in the recent DREAM6 competition.
Asunto(s)
Algoritmos , Amilasas/genética , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genética , Modelos Estadísticos , Glándula Parótida/citología , ARN Mensajero/genética , Proteínas y Péptidos Salivales/genética , Amilasas/metabolismo , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismo , Teorema de Bayes , Humanos , Cadenas de Markov , Simulación de Dinámica Molecular , Método de Montecarlo , Glándula Parótida/metabolismo , ARN Mensajero/metabolismo , Reacción en Cadena en Tiempo Real de la Polimerasa , Reacción en Cadena de la Polimerasa de Transcriptasa Inversa , Proteínas y Péptidos Salivales/metabolismo , Factores de TiempoRESUMEN
Exocrine cells have an essential function of sorting secreted proteins into the correct secretory pathway. A clear understanding of sorting in salivary glands would contribute to the correct targeting of therapeutic transgenes. The present work investigated whether there is a change in the relative proportions of basic proline-rich protein (PRP) and acidic PRPs in secretory granules in response to chronic isoproterenol treatment, and whether this alters the sorting of endogenous cargo proteins. Immunoblot analysis of secretory granules from rat parotids found a large increase of basic PRP over acidic PRPs in response to chronic isoproterenol treatment. Pulse chase experiments demonstrated that isoproterenol also decreased regulated secretion of newly synthesized secretory proteins, including PRPs, amylase and parotid secretory protein. This decreased efficiency of the apical regulated pathway may be mediated by alkalization of the secretory granules since it was reversed by treatment with mild acid. We also investigated changes in secretion through the basolateral (endocrine) pathways. A significant increase in parotid secretory protein and salivary amylase was detected in sera of isoproterenol-treated animals, suggesting increased routing of the regulated secretory proteins to the basolateral pathway. These studies demonstrate that shifts of endogenous proteins can modulate regulated secretion and sorting of cargo proteins.