从酵母表达时间序列估计基因调控网络

基因调控网络是生命功能在基因表达层面上的展现。用组合线性调控模型、调控元件识别和基因聚类等方法 ,从基因组表达谱解读酵母在细胞周期与环境胁迫中的基因调控网络。结果表明 ,细胞在不同环境条件下会调整基因调控网络。在适应的环境下 ,起主要作用的是细胞生长和增殖有关的基因调控网络 ;而在响应环境胁迫时 ,细胞会再规划调控网络 ,抑制细胞生长和增殖相关的基因 ,诱导跟适应性糖类代谢与结构修复相关的基因 ,还可能启动减数分裂产生孢子。分别从细胞周期和环境胁迫响应相关基因中 ,搜索到转录因子Mcm1结合位点TT CC T GGAAA ,和Dal82在尿囊素代谢途径相关基因上的结合位点TGAAAAWTTT。从而 ,从酵母表达时间序列估计基因调控网络是可行的 ,与至今已知的实验观察相当吻合     

时间延迟基因调控网络重构的决策树方法研究

基因调控网络的重构是功能基因组中最具挑战性的课题之一. 针对基因间转录调控的时间延迟性, 提出了一种寻找时间延迟调控关系的方法: 多点延迟调控网络算法, 简称TdGRN (time-delayed gene regulatory networking). 该方法根据时间序列基因表达谱数据, 构建时间延迟基因表达矩阵, 利用有监督决策树分类器方法和随机重排技术挖掘基因之间的时间延迟调控关系, 从而构建时间延迟的基因调控网络. 该方法是一种不依赖模型的基因网络重建方法, 相对于目前采用的基于模型的网络重建方法有显著优势, 可直接利用连续的基因表达谱数据发现延迟任一时间单位差的基因表达调控关系, 并避免了目前一些研究方法中需要人为设定基因的最大调控子数目(k)的问题. 将该方法应用于酿酒酵母细胞周期的基因表达谱数据, 并构建时间延迟的基因调控网络, 结果发现多数时间延迟调控关系获得了已有知识的支持.     

竞争内源性RNA在肿瘤中的研究进展

竞争内源性RNA (competing endogenous RNA, ceRNA)理论是解释基因表达调控和生物功能的关键线索之一。这种机制联合了不同的RNA分子,为RNA之间相互作用和RNA调控网络提供了新的见解。最近的研究证实了ceRNA调控在肿瘤发生发展中的作用,其中大多以lncRNA-miRNA-mRNA和circRNA-miRNA-mRNA调控网络为主。研究表明,多种ceRNA调控网络参与肿瘤细胞增殖、侵袭和迁移、药物抗性、血管生成以及肿瘤免疫等,影响肿瘤发展进程。该文搜集了最新的ceRNA调控肿瘤发生发展过程的研究进展,讨论在此过程中发挥关键作用的ceRNA调控网络。     

浅谈染色质高级结构与基因转录的远程调控

精确的基因表达调控是细胞分化、个体发育和细胞维持正常生命活动的必要条件,转录调控是真核细胞基因表达调控最关键的环节,其神秘和精深吸引着无数科学家为之奋斗不已。染色质构象捕获及其衍生技术的建立和2003年启动的"DNA元件百科全书"计划,将人们对基因转录调控的认识从二维层面推向三维空间。基因组中分布着众多调控元件,它们与所调控的靶基因间可相距几万甚至几十万个核苷酸,可以与靶基因位于相同或不同的染色体上。依据染色质环模型,调控元件可通过染色质环高级结构,与靶基因在空间上充分接近并相互作用,发挥其调控功能。同一个调控元件可以调控不同的靶基因,而相同的基因亦可能受不同调控元件的调节,由此细胞在染色质高级结构层面形成了一个复杂的调节基因转录活性的三维网络。该文分别从基因远程调控现象的发现、研究方法、相关机制及面临的挑战等方面作一简要综述。     

基因转录后调控在DNA损伤反应中的重要功能

DNA损伤发生时,细胞会激活一系列复杂的信号网络来调控细胞周期检查,完成DNA损伤修复或当损伤超过修复能力时诱导凋亡,这一信号网络被称为DNA损伤反应(DNA damage response,DDR)。以往DDR信号网络的研究主要集中于基因转录调控和蛋白共价修饰对功能分子的稳定性和活性调控。近年来,mRNA稳定性调控和mRNA翻译调控等基因转录后调控机制在DDR中的重要作用引起研究者越来越多的关注。研究证明:多种microRNAs和RNA结合蛋白(RNA-binding proteins,RBPs)在转录后水平调控诸多重要功能蛋白的表达,在DDR信号网络中起着不可或缺的作用。文章针对DDR反应中转录后调控的研究进展以及参与其中的microRNAs和RBPs进行阐述和讨论。     

鼻咽癌转录组学研究的现状与进展

转录组学是一门在整体水平上研究某一时刻某一细胞中基因全部转录本种类、结构和功能及转录调控规律的学科,它为研究鼻咽癌不同发病阶段的分子机理和调控网络提供全新的手段.现简要介绍鼻咽癌不同发病阶段相关易感/抑瘤基因的分离鉴定及其功能研究,各阶段基因转录谱和转录调控网络的构建等方面的研究现状和进展.     

乳腺癌致病microRNA调控网络的识别与生物信息学分析

目的:构建并解析乳腺癌致病microRNA(miRNA)调控网络,探究其在乳腺癌发生发展中的调控机制。方法:整合TCGA、ENCODE、Fantom等公共数据库资源,得到miRNA、转录因子和基因候选调控关系数据,结合差异表达、变异系数与PCA,构建乳腺癌miRNA调控网络,解析调控网络的度中心性与聚类系数,使用DAVID进行功能富集分析,构建Cox回归模型作生存曲线。结果:共识别miRNA调控网络262个,其中包含5个显著差异表达miRNA,8个转录因子和130个基因。通过功能富集分析发现这些miRNA靶基因显著参与细胞周期、细胞分化、细胞生长、转移等转录后调控的肿瘤生物进程,并与FoxO信号通路、p53信号通路、基因监测通路等信号通路高度相关。通过分析生存曲线发现hsa-mir-144与hsa-mir-133a-2显著与乳腺癌患者生存相关。结论:识别的乳腺癌致病miRNA调控网络中miRNA之间有相互作用,且网络整体功能不仅受hub网络影响,也受元件自身特性影响,这些miRNA靶基因显著富集于肿瘤相关生物学进程与信号通路中。     

工业微生物中NADH的代谢调控

NADH是微生物代谢网络中的一种关键辅因子。调节微生物胞内NADH的形式与浓度是定向改变和优化微生物细胞代谢功能, 实现代谢流最大化、快速化地导向目标代谢产物的重要手段之一。以下在详尽总结了NADH生理功能的基础上, 从生化工程(添加外源电子受体、不同氧化还原态底物及NAD合成前体物, 调节培养环境和氧化还原电势)和代谢工程(过量表达NADH代谢相关酶、缺失NADH竞争途径及引入NADH外源代谢途径)两方面分析、归纳了NADH代谢调控策略, 进而凝练出调控NADH/NAD+比率调节微生物细胞代谢功能研究方面亟待解决的3个科学问题及可能的解决途径。     

植物种子特异基因调控网络研究

通过比较种子植物与蕨类植物的基因及其调控网络,为研究种子性状出现的分子机制提供更多的信息.下载拟南芥(Arabidopsis thaliana)种子特异基因和基因网络数据,构建拟南芥种子特异基因调控网络,并与江南卷柏(Selaginella moellendorffii)基因组数据比较,发现其中重要的调控节点.分析得到构成调控网络的1053个拟南芥种子特异基因,其中的969个基因形成一个复杂的调控网络.该网络的核心模块包括39个基因,形成哑铃状的子网络,其中重要节点基因AT1G54860只存在于种子植物基因组中.AT1G54860基因编码GPI锚定蛋白,参与细胞壁的形成、细胞间信号传导及生长分化等过程,推测其在种子形成中具有重要地位,可能起了"开关"的作用.     

谷氨酸棒状杆菌集成细胞网络的构建与结构分析

谷氨酸棒状杆菌是一种重要的传统工业微生物,其基因组学和分子遗传操作工具的快速发展使得谷氨酸棒状杆菌具备了作为新型细胞工厂的潜力。但是,相对于大肠杆菌等模式生物,对于棒杆菌的代谢调控研究较少,特别是目前还缺乏谷氨酸棒状杆菌集成细胞网络的研究,这一现状阻碍了谷氨酸棒状杆菌的系统生物学研究和大规模菌种理性设计优化。文中综合应用公共数据库、文献数据库资源,首次构建了谷氨酸棒状杆菌的集成细胞网络,包含1 384个反应,1 276个代谢物,88个调节子,999对转录调控关系。其转录调控可分为5层,代谢网络呈现出清晰的bow-tie结构。文中还以赖氨酸的生物合成为例,提出了一种提取代谢调控子网络的新方法,这对氨基酸等产品高产生物机制的研究和工程菌株的重新设计具有指导意义。     

Maps, books and other metaphors for systems biology

We briefly review the use of metaphors in science and progressively focus on fields from biology and molecular biology to genomics and bioinformatics. We discuss how metaphors are both a tool for scientific exploration and a medium for public communication of complex subjects, by various short examples. Finally, we propose a metaphor for systems biology that provides an illuminating perspective for the ambitious goals of this field and delimits its current agenda.     

How to be an anti-reductionist about developmental biology: Response to Laubichler and Wagner

Alexander Rosenberg recently claimed (1997) that developmental biology is currently being reduced to molecular biology. cite several concrete biological examples that are intended to impugn Rosenberg's claim. I first argue that although Laubichler and Wagner's examples would refute a very strong reductionism, a more moderate reductionism would escape their attacks. Next, taking my cue from the antireductionist's perennial stress on the importance of spatial organization, I describe one form an empirical finding that refutes this moderate reductionism would take. Finally, I point out an actual example, anterior-posterior axis determination in the chick, that challenges the reductionist's belief that all developmental regularities can be explained by molecular biology. In short, I argue that Rosenberg's position can be saved from Laubichler and Wagner's criticisms and putative counter-examples, but it would not survive a different kind of counter-example.     

Building momentum for systems and synthetic biology in India

Biological systems are inherently noisy. Predicting the outcome of a perturbation is extremely challenging. Traditional reductionist approach of describing properties of parts, vis-a-vis higher level behaviour has led to enormous understanding of fundamental molecular level biology. This approach typically consists of converting genes into junk (knock-down) and garbage (knock-out) and observe how a system responds. To enable broader understanding of biological dynamics, an integrated computational and experimental strategy was formally proposed in mid 1990s leading to the re-emergence of Systems Biology. However, soon it became clear that natural systems were far more complex than expected. A new strategy to address biological complexity was proposed at MIT (Massachusetts Institute of Technology) in June 2004, when the first meeting of synthetic biology was held. Though the term ‘synthetic biology’ was proposed during 1970s (Szybalski in Control of gene expression, Plenum Press, New York, 1974), the usage of the original concept found an experimental proof in 2000 with the demonstration of a three-gene circuit called repressilator (Elowitz and Leibler in Nature, 403:335–338, 2000). This encouraged people to think of forward engineering biology from a set of well described parts.     

Reproductive biology of Trichocentrum pumilum: an orchid pollinated by oil-collecting bees

The reproductive biology, reward production and pollination mechanism of Trichocentrum pumilum were studied in a gallery forest in the interior of the State of São Paulo, southeast Brazil. The floral visitors and pollination mechanism were recorded, and experimental pollinations were carried out in order to determine the breeding system of this species. Trichocentrum pumilum blooms in spring. Each paniculate inflorescence bears an average of 85 flowers that present a central yellow callus and finger‐like trichomes on the lateral lobes of the lip. A lipoidal substance is produced and stored among these trichomes. In the studied population, T. pumilum is exclusively visited and pollinated by two bee species (Tetrapedia diversipes and Lophopedia nigrispinis). Pollinaria are deposited on mouthparts of bees during collection of the lipoidal substance from the lateral lobes of the labellum. Trichocentrum pumilum is self‐incompatible and pollinator‐limited. Natural fruit set was low (9%, compared to 45% in experimentally cross‐pollinated flowers). Potentially viable seed exceed 97% in fruits obtained through cross‐pollination and in natural conditions (open pollination).     

Improved understanding of gene expression regulation using systems biology

This article reviews the current state of systems biology approaches, including the experimental tools used to generate ‘omic’ data and computational frameworks to interpret this data. Through illustrative examples, systems biology approaches to understand gene expression and gene expression regulation are discussed. Some of the challenges facing this field and the future opportunities in the systems biology era are highlighted.     

冷冻电子显微学在结构生物学研究中的现状与展望

冷冻电子显微学近年来在电子显微镜的硬件设备及结构解析的软件算法等方面取得了多个重要的技术突破,正在成为结构生物学研究的重要技术手段,为越来越多的生物学研究者所重视.冷冻电子显微学的技术特点决定了它所具备的一些独特优势和发展方向,同时作为一个正在迅速发展的科学技术领域,需要多学科的交叉促进.本文主要介绍冷冻电子显微学的研究现状及面临的技术挑战,并提出未来可能实现结构生物学与细胞生物学不同尺度的研究在冷冻电子显微学技术上融合的新方法.     

进化细胞生物学的提出及其任务

作者提出应创建一门源于进化生物学与细胞生物学两者的交叉学科一进化细胞生物学(细胞的进化生物学)。其根本任务在于用进化的观点考察真核细胞的一切方面,从它们的起源和演化来认识它们的现在。文中列举了其具体的研究内容,并分析了其研究方法上的特点,指出在这里需要把进化生物学的综合性分析与细胞生物学的实验研究最紧密地结合起来。文中还论述了真核细胞的细胞器的“不进化”现象,指出其根本原因在于进化焦点的转移。     

Application of an integrated physical and functional screening approach to identify inhibitors of the Wnt pathway

Large‐scale proteomic approaches have been used to study signaling pathways. However, identification of biologically relevant hits from a single screen remains challenging due to limitations inherent in each individual approach. To overcome these limitations, we implemented an integrated, multi‐dimensional approach and used it to identify Wnt pathway modulators. The LUMIER protein–protein interaction mapping method was used in conjunction with two functional screens that examined the effect of overexpression and siRNA‐mediated gene knockdown on Wnt signaling. Meta‐analysis of the three data sets yielded a combined pathway score (CPS) for each tested component, a value reflecting the likelihood that an individual protein is a Wnt pathway regulator. We characterized the role of two proteins with high CPSs, Ube2m and Nkd1. We show that Ube2m interacts with and modulates β‐catenin stability, and that the antagonistic effect of Nkd1 on Wnt signaling requires interaction with Axin, itself a negative pathway regulator. Thus, integrated physical and functional mapping in mammalian cells can identify signaling components with high confidence and provides unanticipated insights into pathway regulators.     

Multi-scale modeling in biology: how to bridge the gaps between scales?

Human physiological functions are regulated across many orders of magnitude in space and time. Integrating the information and dynamics from one scale to another is critical for the understanding of human physiology and the treatment of diseases. Multi-scale modeling, as a computational approach, has been widely adopted by researchers in computational and systems biology. A key unsolved issue is how to represent appropriately the dynamical behaviors of a high-dimensional model of a lower scale by a low-dimensional model of a higher scale, so that it can be used to investigate complex dynamical behaviors at even higher scales of integration. In the article, we first review the widely-used different modeling methodologies and their applications at different scales. We then discuss the gaps between different modeling methodologies and between scales, and discuss potential methods for bridging the gaps between scales.     

A computational framework for the design of optimal protein synthesis

Despite the establishment of design principles to optimize codon choice for heterologous expression vector design, the relationship between codon sequence and final protein yield remains poorly understood. In this work, we present a computational framework for the identification of a set of mutant codon sequences for optimized heterologous protein production, which uses a codon-sequence mechanistic model of protein synthesis. Through a sensitivity analysis on the optimal steady state configuration of protein synthesis we are able to identify the set of codons, that are the most rate limiting with respect to steady state protein synthesis rate, and we replace them with synonymous codons recognized by charged tRNAs more efficient for translation, so that the resulting codon-elongation rate is higher. Repeating this procedure, we iteratively optimize the codon sequence for higher protein synthesis rate taking into account multiple constraints of various types. We determine a small set of optimized synonymous codon sequences that are very close to each other in sequence space, but they have an impact on properties such as ribosomal utilization or secondary structure. This limited number of sequences can then be offered for further experimental study. Overall, the proposed method is very valuable in understanding the effects of the different properties of mRNA sequences on the final protein yield in heterologous protein production and it can find applications in synthetic biology and biotechnology.