Regulation of Cellular Proliferation by Novel Mitochondrial-Encoded Tumor Suppressors

摘要 细胞区室通过各种细胞之间的动态双向通信网络进行协调。 细胞器在这里，我们专注于线粒体和细胞核之间的通信，细胞器，每个 拥有自己的基因组。线粒体和核基因组已经共同进化了十亿多年， 可能需要密切沟通和交叉监管。然而，尽管线粒体被认为是 由1,000多种核编码蛋白调控，但目前还没有已知的核编码因子 主动与细胞核沟通并调节细胞核。我们最近发现了一种新的基因编码， 将其命名为MOTS-c（Mitochondrial ORF within the Twelve S rRNA type-c）。MOTS-C是一个 一种由16个氨基酸组成的小肽，部分通过主营养传感器AMPK调节代谢稳态 （腺苷一磷酸活化蛋白激酶）。我们最近报道MOTS-c可以易位到 细胞核响应代谢应激而结合染色质并调节核基因表达。此外，我们的 初步研究使用多管齐下的方法，包括单细胞RNA-seq，生物信息学（包括机器 学习），染色质免疫沉淀（ChIP）结合定量PCR（qPCR）和细胞分选，显示 MOTS-c可以调节细胞增殖; MOTS-c靶向p53/p21通路和核糖体过程。 考虑到线粒体在细胞增殖过程中的重要代谢作用（29），一个关键问题 仍然很大程度上是个谜的是，神经元编码的因子如何与细胞核沟通，以协调细胞内的神经元活动。 在增殖过程中随着基因表达的代谢变化。值得注意的是，快速分裂的癌细胞中 MOTS-c或核转位缺陷，表明MOTS-c的线粒体-核通讯丢失。 总之，癌症可能是一种遗传性疾病，其中我们的两个基因组以双向干扰的状态存在。 MOTS-c在细胞内的表达和调节，并可能作为一个独特的模型，开始了解MOTS-c在细胞内的作用。 增殖由于MOTS-c表达/功能失调，并且MOTS-c可以负调节 细胞周期/增殖，我们假设MOTS-c是一种细胞编码的肿瘤抑制因子， 直接调节细胞核以协调细胞代谢和增殖。我们提出了三 旨在验证这一假设。首先，我们将MOTS-c描述为一种肿瘤抑制因子，它调节细胞增殖， 分子、细胞、基因水平。第二，我们将全面绘制MOTS-c依赖的功能核 使用多种互补基因组学方法的基因组景观，包括单细胞RNA-seq，ATAC-seq （染色质可及性）和使用ChIP-seq的基因组足迹。每种基因组方法的数据将 集成使用尖端的计算方法，包括机器学习，以破译消息MOTS- c递送到核基因组以调节癌细胞增殖和存活。最后，我们将确定MOTS- c-介导的细胞核通讯可以差异调节细胞增殖和应激抗性， 和恶性细胞。 如果成功，我们预计我们的研究将对（i）基础研究产生广泛而持久的影响， 细胞编码的肿瘤抑制因子的范式转变概念， 增殖和（ii）通过揭示mtDNA作为新药物靶点的来源（目前有 没有FDA批准的基于线粒体基因组的药物）。

ABSTRACT Cellular compartments are coordinated through a dynamic bidirectional communication network amongst various organelles. Here, we focus on the communication between mitochondria and the nucleus, organelles that each possess their own genomes. The mitochondrial and nuclear genomes have co-evolved for over a billion years and have likely required close communication and cross-regulation. However, whereas mitochondria are known to be regulated by over 1,000 nuclear-encoded proteins, but there is currently no known mitochondrial-encoded factor that actively communicates to and regulates the nucleus. We have recently identified a novel gene encoded within the mitochondrial DNA and named it MOTS-c (Mitochondrial ORF within the Twelve S rRNA type-c). MOTS-c is a small 16 amino acid peptide that regulates metabolic homeostasis, in part, via the master nutrient sensor AMPK (adenosine monophosphate-activated protein kinase). We recently reported that MOTS-c can translocate into the nucleus in response to metabolic stress to bind to chromatin and regulate nuclear gene expression. Further, our preliminary study using a multi-pronged approach, including single cell RNA-seq, bioinformatics (including machine learning), chromatin immunoprecipitation (ChIP) coupled with quantitative PCR (qPCR), and cell sorting, showed that MOTS-c can regulate cellular proliferation; MOTS-c targeted the p53/p21 pathway and ribosomal processes. Considering the important metabolic role of mitochondria in cellular proliferation processes (29), a critical question that remains largely enigmatic is how mitochondrial-encoded factors communicate to the nucleus to coordinate the metabolic shift with gene expression during proliferation. Notably, rapidly dividing cancer cells had undetectable levels of MOTS-c or nuclear-translocation deficiency, suggesting loss of mito-nuclear communication by MOTS-c. Together, cancer may be a genetic disease in which our two genomes exist in a state of disrupted bi-directional communication/regulation, and may serve as a unique model to start understanding the role of MOTS-c in cellular proliferation. Because MOTS-c expression/function was dysregulated and that MOTS-c can negatively regulate cell cycle/proliferation, we hypothesize that MOTS-c is a mitochondrial-encoded tumor suppressor, the first of its kind to be identified, that directly regulates the nucleus to coordinate cellular metabolism with proliferation. We propose three aims to test this hypothesis. First, we will characterize MOTS-c as a tumor suppressor that regulates cell proliferation at the molecular, cellular, genetic level. Second, we will comprehensively map the MOTS-c-dependent functional nuclear genomic landscape using multiple complimentary genomics approach, including single cell RNA-seq, ATAC-seq (chromatin accessibility), and genomic footprinting using ChIP-seq. The data from each genomic approach will be integrated using cutting-edge computational methods, including machine learning, to decipher the message(s) MOTS- c delivers to the nuclear genome to regulate cancer cell proliferation and survival. Lastly, we will determine how MOTS- c-mediated communication to the nucleus can differentially regulate cellular proliferation and stress resistance in normal and malignant cells using mouse models of cancer. If successful, we predict that our study will have broad and lasting impact on (i) basic research by introducing the paradigm-shifting concept of mitochondrial-encoded tumor suppressors that coordinate cellular metabolism and proliferation and (ii) therapeutic development by revealing mtDNA as a source of novel drug targets (currently there are no FDA-approved drugs based on the mitochondrial genome).