Bradshaw Patrick C, Samuels David C
Virginia Bioinformatics Institute, Virginia Polytechnic and State Univ., Bioinformatics Facility I (0477 Blacksburg, VA 24061, USA.
Am J Physiol Cell Physiol. 2005 May;288(5):C989-1002. doi: 10.1152/ajpcell.00530.2004. Epub 2005 Jan 5.
We present a computational model of mitochondrial deoxynucleotide metabolism and mitochondrial DNA (mtDNA) synthesis. The model includes the transport of deoxynucleosides and deoxynucleotides into the mitochondrial matrix space, as well as their phosphorylation and polymerization into mtDNA. Different simulated cell types (cancer, rapidly dividing, slowly dividing, and postmitotic cells) are represented in this model by different cytoplasmic deoxynucleotide concentrations. We calculated the changes in deoxynucleotide concentrations within the mitochondrion during the course of a mtDNA replication event and the time required for mtDNA replication in the different cell types. On the basis of the model, we define three steady states of mitochondrial deoxynucleotide metabolism: the phosphorylating state (the net import of deoxynucleosides and export of phosphorylated deoxynucleotides), the desphosphorylating state (the reverse of the phosphorylating state), and the efficient state (the net import of both deoxynucleosides and deoxynucleotides). We present five testable hypotheses based on this simulation. First, the deoxynucleotide pools within a mitochondrion are sufficient to support only a small fraction of even a single mtDNA replication event. Second, the mtDNA replication time in postmitotic cells is much longer than that in rapidly dividing cells. Third, mitochondria in dividing cells are net sinks of cytoplasmic deoxynucleotides, while mitochondria in postmitotic cells are net sources. Fourth, the deoxynucleotide carrier exerts the most control over the mtDNA replication rate in rapidly dividing cells, but in postmitotic cells, the NDPK and TK2 enzymes have the most control. Fifth, following from the previous hypothesis, rapidly dividing cells derive almost all of their mtDNA precursors from the cytoplasmic deoxynucleotides, not from phosphorylation within the mitochondrion.
我们提出了一种线粒体脱氧核苷酸代谢和线粒体DNA(mtDNA)合成的计算模型。该模型包括脱氧核苷和脱氧核苷酸向线粒体基质空间的转运,以及它们磷酸化并聚合成mtDNA的过程。在这个模型中,不同的模拟细胞类型(癌症细胞、快速分裂细胞、缓慢分裂细胞和有丝分裂后细胞)由不同的细胞质脱氧核苷酸浓度来表示。我们计算了线粒体DNA复制过程中线粒体内脱氧核苷酸浓度的变化,以及不同细胞类型中线粒体DNA复制所需的时间。基于该模型,我们定义了线粒体脱氧核苷酸代谢的三种稳态:磷酸化状态(脱氧核苷的净输入和磷酸化脱氧核苷酸的输出)、去磷酸化状态(磷酸化状态的反向)和高效状态(脱氧核苷和脱氧核苷酸的净输入)。基于此模拟,我们提出了五个可检验的假设。第一,线粒体内的脱氧核苷酸库甚至仅足以支持单个线粒体DNA复制事件的一小部分。第二,有丝分裂后细胞中的线粒体DNA复制时间比快速分裂细胞中的长得多。第三,分裂细胞中的线粒体是细胞质脱氧核苷酸的净汇,而有丝分裂后细胞中的线粒体是净源。第四,脱氧核苷酸载体对快速分裂细胞中线粒体DNA复制速率的控制作用最大,但在有丝分裂后细胞中,核苷二磷酸激酶(NDPK)和胸苷激酶2(TK2)酶的控制作用最大。第五,根据前一个假设,快速分裂细胞几乎所有的线粒体DNA前体都来自细胞质脱氧核苷酸,而不是线粒体内的磷酸化过程。