RESUMO
The rates of mRNA synthesis and degradation determine cellular mRNA levels and can be monitored by comparative dynamic transcriptome analysis (cDTA) that uses nonperturbing metabolic RNA labeling. Here we present cDTA data for 46 yeast strains lacking genes involved in mRNA degradation and metabolism. In these strains, changes in mRNA degradation rates are generally compensated by changes in mRNA synthesis rates, resulting in a buffering of mRNA levels. We show that buffering of mRNA levels requires the RNA exonuclease Xrn1. The buffering is rapidly established when mRNA synthesis is impaired, but is delayed when mRNA degradation is impaired, apparently due to Xrn1-dependent transcription repressor induction. Cluster analysis of the data defines the general mRNA degradation machinery, reveals different substrate preferences for the two mRNA deadenylase complexes Ccr4-Not and Pan2-Pan3, and unveils an interwoven cellular mRNA surveillance network.
Assuntos
Exorribonucleases/metabolismo , Estabilidade de RNA , RNA Fúngico/metabolismo , RNA Mensageiro/metabolismo , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/enzimologia , Proteínas Adaptadoras de Transdução de Sinal/metabolismo , Análise por Conglomerados , Exorribonucleases/genética , Regulação Fúngica da Expressão Gênica , Cinética , Modelos Genéticos , Mutação , N-Glicosil Hidrolases/metabolismo , RNA Fúngico/biossíntese , RNA Mensageiro/biossíntese , Proteínas Repressoras/metabolismo , Saccharomyces cerevisiae/genética , Proteínas de Saccharomyces cerevisiae/genética , Especificidade por SubstratoRESUMO
Cancer chromosomal instability (CIN) results in an increased rate of change of chromosome number and structure and generates intratumour heterogeneity. CIN is observed in most solid tumours and is associated with both poor prognosis and drug resistance. Understanding a mechanistic basis for CIN is therefore paramount. Here we find evidence for impaired replication fork progression and increased DNA replication stress in CIN(+) colorectal cancer (CRC) cells relative to CIN(-) CRC cells, with structural chromosome abnormalities precipitating chromosome missegregation in mitosis. We identify three new CIN-suppressor genes (PIGN (also known as MCD4), MEX3C (RKHD2) and ZNF516 (KIAA0222)) encoded on chromosome 18q that are subject to frequent copy number loss in CIN(+) CRC. Chromosome 18q loss was temporally associated with aneuploidy onset at the adenoma-carcinoma transition. CIN-suppressor gene silencing leads to DNA replication stress, structural chromosome abnormalities and chromosome missegregation. Supplementing cells with nucleosides, to alleviate replication-associated damage, reduces the frequency of chromosome segregation errors after CIN-suppressor gene silencing, and attenuates segregation errors and DNA damage in CIN(+) cells. These data implicate a central role for replication stress in the generation of structural and numerical CIN, which may inform new therapeutic approaches to limit intratumour heterogeneity.
Assuntos
Instabilidade Cromossômica/genética , Neoplasias Colorretais/genética , Replicação do DNA/genética , Aneuploidia , Linhagem Celular Tumoral , Instabilidade Cromossômica/efeitos dos fármacos , Segregação de Cromossomos/efeitos dos fármacos , Segregação de Cromossomos/genética , Cromossomos Humanos Par 18/efeitos dos fármacos , Cromossomos Humanos Par 18/genética , Neoplasias Colorretais/patologia , Variações do Número de Cópias de DNA/genética , Dano ao DNA/efeitos dos fármacos , Dano ao DNA/genética , Replicação do DNA/efeitos dos fármacos , Deleção de Genes , Inativação Gênica , Genes Supressores de Tumor , Humanos , Mitose/efeitos dos fármacos , Nucleosídeos/farmacologia , Fosfotransferases/genética , Proteínas de Ligação a RNA/genéticaRESUMO
Diseases and toxins may lead to death of active liver tissue, resulting in a loss of total clearance capacity at the whole-body level. However, it remains difficult to study, whether the loss of metabolizing tissue is sufficient to explain loss of metabolic capacity of the liver or whether the surviving tissue undergoes an adaptive response to compensate the loss. To understand the cellular impact of toxic liver damage in an in vivo situation, we here used physiologically-based pharmacokinetic modelling to investigate pharmacokinetics of a specifically designed drug cocktail at three different sampling sites of the body in healthy mice and mice treated with carbon tetrachloride (CCl4). Liver zonation was explicitly quantified in the models through immunostaining of cytochrome P450s enzymes. Comparative analyses between the simulated decrease in clearance capacity and the experimentally measured loss in tissue volume indicated that CCl4-induced impairment of metabolic functions goes beyond the mere loss of metabolically active tissue. The here established integrative modelling strategy hence provides mechanistic insights into functional consequences of toxic liver damage in an in vivo situation, which would not have been accessible by conventional methods.
Assuntos
Tetracloreto de Carbono/toxicidade , Doença Hepática Induzida por Substâncias e Drogas/patologia , Fígado/patologia , Preparações Farmacêuticas/metabolismo , Animais , Doença Hepática Induzida por Substâncias e Drogas/etiologia , Doença Hepática Induzida por Substâncias e Drogas/metabolismo , Desenho de Fármacos , Fígado/efeitos dos fármacos , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Distribuição TecidualRESUMO
Many physiological processes and pathological conditions in livers are spatially heterogeneous, forming patterns at the lobular length scale or varying across the organ. Steatosis, a common liver disease characterized by lipids accumulating in hepatocytes, exhibits heterogeneity at both these spatial scales. The main goal of the present study was to provide a method for zonated quantification of the steatosis patterns found in an entire mouse liver. As an example application, the results were employed in a pharmacokinetics simulation. For the analysis, an automatic detection of the lipid vacuoles was used in multiple slides of histological serial sections covering an entire mouse liver. Lobuli were determined semi-automatically and zones were defined within the lobuli. Subsequently, the lipid content of each zone was computed. The steatosis patterns were found to be predominantly periportal, with a notable organ-scale heterogeneity. The analysis provides a quantitative description of the extent of steatosis in unprecedented detail. The resulting steatosis patterns were successfully used as a perturbation to the liver as part of an exemplary whole-body pharmacokinetics simulation for the antitussive drug dextromethorphan. The zonated quantification is also applicable to other pathological conditions that can be detected in histological images. Besides being a descriptive research tool, this quantification could perspectively complement diagnosis based on visual assessment of histological images.
Assuntos
Simulação por Computador , Fígado Gorduroso , Hepatócitos , Processamento de Imagem Assistida por Computador , Fígado , Modelos Biológicos , Animais , Fígado Gorduroso/metabolismo , Fígado Gorduroso/patologia , Hepatócitos/metabolismo , Hepatócitos/patologia , Metabolismo dos Lipídeos , Fígado/metabolismo , Fígado/patologia , Masculino , Camundongos , Vacúolos/metabolismo , Vacúolos/patologiaRESUMO
Quality control of human induced pluripotent stem cells (iPSCs) can be performed by several methods. These methods are usually relatively labor-intensive, difficult to standardize, or they do not facilitate reliable quantification. Here, we describe a biomarker to distinguish between pluripotent and non-pluripotent cells based on DNA methylation (DNAm) levels at only three specific CpG sites. Two of these CpG sites were selected by their discriminatory power in 258 DNAm profiles - they were either methylated in pluripotent or non-pluripotent cells. The difference between these two ß-values provides an Epi-Pluri-Score that was validated on independent DNAm-datasets (264 pluripotent and 1,951 non-pluripotent samples) with 99.9% specificity and 98.9% sensitivity. This score was complemented by a third CpG within the gene POU5F1 (OCT4), which better demarcates early differentiation events. We established pyrosequencing assays for the three relevant CpG sites and thereby correctly classified DNA of 12 pluripotent cell lines and 31 non-pluripotent cell lines. Furthermore, DNAm changes at these three CpGs were tracked in the course of differentiation of iPSCs towards mesenchymal stromal cells. The Epi-Pluri-Score does not give information on lineage-specific differentiation potential, but it provides a simple, reliable, and robust biomarker to support high-throughput classification into either pluripotent or non-pluripotent cells.
Assuntos
Biomarcadores , Metilação de DNA/genética , Epigênese Genética , Células-Tronco Pluripotentes Induzidas/metabolismo , Diferenciação Celular/genética , Linhagem Celular , Células Cultivadas , Ilhas de CpG/genética , Humanos , Células-Tronco Mesenquimais/metabolismo , Fator 3 de Transcrição de Octâmero/genéticaRESUMO
The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.