RESUMO
mTOR, a serine/threonine protein kinase that is involved in a series of critical cellular processes, can be found in two functionally distinct complexes, mTORC1 and mTORC2. In contrast to mTORC1, little is known about the mechanisms that regulate mTORC2. Here we show that mTORC2 activity is reduced in mice with a hypomorphic mutation of the Ric-8B gene. Ric-8B is a highly conserved protein that acts as a non-canonical guanine nucleotide exchange factor (GEF) for heterotrimeric Gαs/olf type subunits. We found that Ric-8B hypomorph embryos are smaller than their wild type littermates, fail to close the neural tube in the cephalic region and die during mid-embryogenesis. Comparative transcriptome analysis revealed that signaling pathways involving GPCRs and G proteins are dysregulated in the Ric-8B mutant embryos. Interestingly, this analysis also revealed an unexpected impairment of the mTOR signaling pathway. Phosphorylation of Akt at Ser473 is downregulated in the Ric-8B mutant embryos, indicating a decreased activity of mTORC2. Knockdown of the endogenous Ric-8B gene in cultured cell lines leads to reduced phosphorylation levels of Akt (Ser473), further supporting the involvement of Ric-8B in mTORC2 activity. Our results reveal a crucial role for Ric-8B in development and provide novel insights into the signals that regulate mTORC2.
Assuntos
Fatores de Troca do Nucleotídeo Guanina/genética , Alvo Mecanístico do Complexo 2 de Rapamicina/metabolismo , Animais , Células Cultivadas , Regulação para Baixo/genética , Embrião de Mamíferos , Desenvolvimento Embrionário/genética , Feminino , Deleção de Genes , Perfilação da Expressão Gênica , Regulação da Expressão Gênica no Desenvolvimento , Masculino , Camundongos , Camundongos da Linhagem 129 , Camundongos Endogâmicos C57BL , Camundongos Knockout , Transdução de Sinais/genéticaRESUMO
Very little is known about long non-coding RNAs (lncRNAs) in the mammalian olfactory sensory epithelia. Deciphering the non-coding transcriptome in olfaction is relevant because these RNAs have been shown to play a role in chromatin modification and nuclear architecture reorganization, processes that accompany olfactory differentiation and olfactory receptor gene choice, one of the most poorly understood gene regulatory processes in mammals. In this study, we used a combination of in silico and ex vivo approaches to uncover a comprehensive catalogue of olfactory lncRNAs and to investigate their expression in the mouse olfactory organs. Initially, we used a novel machine-learning lncRNA classifier to discover hundreds of annotated and unannotated lncRNAs, some of which were predicted to be preferentially expressed in the main olfactory epithelium and the vomeronasal organ, the most important olfactory structures in the mouse. Moreover, we used whole-tissue and single-cell RNA sequencing data to discover lncRNAs expressed in mature sensory neurons of the main epithelium. Candidate lncRNAs were further validated by in situ hybridization and RT-PCR, leading to the identification of lncRNAs found throughout the olfactory epithelia, as well as others exquisitely expressed in subsets of mature olfactory neurons or progenitor cells.
Assuntos
Aprendizado de Máquina , Neurônios Receptores Olfatórios/metabolismo , RNA Longo não Codificante/genética , Transcriptoma , Órgão Vomeronasal/metabolismo , Animais , Feminino , Masculino , Camundongos , RNA Longo não Codificante/metabolismoRESUMO
Somatically acquired chromosomal rearrangements occur at early stages during tumorigenesis and can be used to indirectly detect tumor cells, serving as highly sensitive and tumor-specific biomarkers. Advances in high-throughput sequencing have allowed the genome-wide identification of patient-specific chromosomal rearrangements to be used as personalized biomarkers to efficiently assess response to treatment, detect residual disease and monitor disease recurrence. However, sequencing and data processing costs still represent major obstacles for the widespread application of personalized biomarkers in oncology. We developed a computational pipeline (ICRmax) for the cost-effective identification of a minimal set of tumor-specific interchromosomal rearrangements (ICRs). We examined ICRmax performance on sequencing data from rectal tumors and simulated data achieving an average accuracy of 68% for ICR identification. ICRmax identifies ICRs from low-coverage sequenced tumors, eliminates the need to sequence a matched normal tissue and significantly reduces the costs that limit the utilization of personalized biomarkers in the clinical setting.