High-throughput approaches for the analysis of extrinsic regulators of stem cell fate

The complexity of stem cell niches poses a tremendous challenge to understanding mechanisms of extrinsic regulation of stem cell fate. In order to better understand niche signaling and its effect on stem cell fate choices, in vitro systems are being engineered which recapitulate, in a simplistic but increasingly sophisticated manner, native stem cell niches. New technologies or new combinations of existing technologies allow more systematic ways to probe niche signaling in high-throughput. Systems biology approaches in experimental design, data acquisition and analysis will be necessary to tackle the challenges that lie ahead.     

The protein architecture of human secretory vesicles reveals differential regulation of signaling molecule secretion by protein kinases

Secretory vesicles are required for release of chemical messengers to mediate intercellular signaling among human biological systems. It is necessary to define the organization of the protein architecture of the 'human' dense core secretory vesicles (DCSV) to understand mechanisms for secretion of signaling molecules essential for cellular regulatory processes. This study, therefore, conducted extensive quantitative proteomics and systems biology analyses of human DCSV purified from human pheochromocytoma. Over 600 human DCSV proteins were identified with quantitative evaluation of over 300 proteins, revealing that most proteins participate in producing peptide hormones and neurotransmitters, enzymes, and the secretory machinery. Systems biology analyses provided a model of interacting DCSV proteins, generating hypotheses for differential intracellular protein kinases A and C signaling pathways. Activation of cellular PKA and PKC pathways resulted in differential secretion of neuropeptides, catecholamines, and β-amyloid of Alzheimer's disease for mediating cell-cell communication. This is the first study to define a model of the protein architecture of human DCSV for human disease and health.     

Scaffold蛋白介导细胞信号转导专一性的定量分析

细胞使用相对有限的蛋白质组分传递大量的信号,因此不同的信号通常由相同的蛋白质组分传递。这些蛋白质组分是如何选择性地参与不同的信号通路,“高保真”地传递不同的刺激,从而产生特定的细胞应答,是目前细胞生物学领域中的研究热点和难点之一。鉴于Scaffold蛋白在确保信号转导专一性和保真性中的关键作用,作者基于酵母S.cerevisiae的生物学实验数据,建立了由Scaffold介导的丝裂原活化蛋白激酶(mitogenactivatedproteinkinase,MAPK)级联信号转导网络的数学模型。并对已报道的工作进行扩展,给出了多条信号级联网络的“专一性(specificity)”和“保真性(fidelity)”的精确数学定义,计算了MAPK信号网络的专一性和保真性的解析解。用这些解定量分析细胞信号转导的专一性和保真性与信号通路各种动力学参数(输入信号的强度和时间、反应率、磷酸化和去磷酸化系数、降解系数等)之间的关系,从理论上阐述Scaffold蛋白通过隔离(sequestration)和选择性激活(selectiveactivation)等机制增强信号转导网络的专一性和保真性。从而有助于加深对细胞信号转导及其调控过程的系统理解,为揭示某些因细胞信号转导异常所致疾病的发生机理,寻找治疗药物提供新的思路。     

Emerging technologies: systems biology

The field of systems biology is based on the paradigm that the whole is greater than the sum of the parts. Through a combination of high-throughput experiments analyzing "-omic" scale phenomenon and the development of new computational techniques and algorithms, it is now feasible to study biological systems in a way that was previously not possible. During the 232nd National Meeting of the American Chemical Society, a session devoted to the emerging technology of Systems Biology was held. A number of talks on a wide variety of subjects covering cell signaling, network regulation and analysis, novel experimental procedures, synthetic biology, and metabolic flux analysis were presented. All of these approaches shared the common theme of using a systems biology approach to aid in the understanding of fundamental biology, with an eye toward applications for the benefit of society.     

Systems biology as a foundation for genome-scale synthetic biology

As the ambitions of synthetic biology approach genome-scale engineering, comprehensive characterization of cellular systems is required, as well as a means to accurately model cell-scale molecular interactions. These requirements are coincident with the goals of systems biology and, thus, systems biology will become the foundation for genome-scale synthetic biology. Systems biology will form this foundation through its efforts to reconstruct and integrate cellular systems, develop the mathematics, theory and software tools for the accurate modeling of these integrated systems, and through evolutionary mechanisms. As genome-scale synthetic biology is so enabled, it will prove to be a positive feedback driver of systems biology by exposing and forcing researchers to confront those aspects of systems biology which are inadequately understood.     

Shining light on signaling and metabolic networks by genetically encoded biosensors

Fluorescent labels have revolutionized cell biology. Signaling intermediates and metabolites can be measured in real time with subcellular spatial resolution. Most of these sensors are based on fluorescent proteins, and many report fluorescence resonance energy transfer. Because the biosensors are genetically encoded, a toolbox for addressing cell biological questions at the systems level is now available. Fluorescent biosensors are able to determine the localization of proteins and their dynamics, to reveal the cellular and subcellular localization of the respective interactions and activities, and to provide complementary data on the steady state levels of ions, metabolites, and signaling intermediates with high temporal and spatial resolution. They represent the basis for cell-based high-throughput assays that are necessary for a systems perspective on plant cell function.     

Restricting restriction

Systems biology is a new, fashionable and well-funded discipline, which to quote from a recent review aims to 'examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism em leader ' (Kitano, H. (2002) Science 295:1662-1664). Systems biology will do this by profiting from the vast amounts of biological information that are available in the genomics era and make extensive use of computer modelling. But: 'many breakthroughs in experimental devices, advanced software and analytical methods are required before the achievements of system biology can live up to their much-touted potential'. This edition of Molecular Microbiology contains a paper that is the product of traditional experimental biology but which could serve as a test case for systems biology. The paper shows how bacteria integrate such disparate subsystems as DNA restriction, homologous recombination and regulated proteolysis to protect their chromosomes from degradation. When systems biology can predict this level of choreography, it will be a mature discipline.     

Structure-based systems biology: a zoom lens for the cell

Systems biology seeks to explain complex biological systems, such as the cell, through the integration of many different types of information. Here, we discuss how the incorporation of high-resolution structural data can provide key molecular details often necessary to understand the complex connection between individual molecules and cell behavior. We suggest a process of zooming on the cell, from global networks through pathways to the precise atomic contacts at the interfaces of interacting proteins.     

Regulatory modules: Coupling protein stability to phopshoregulation during cell division

Multiple post-translational regulation systems regulate cell biology. Two key mechanisms that coordinate the myriad processes of cell replication are phosphorylation and ubiquitin-mediated degradation of proteins. Regulatory modules have evolved to integrate these two control systems at key decision points in the cell division cycle. These modules enable information to be processed with high fidelity by filtering noise, improving specificity, generating feedback loops, and optimizing spatiotemporal coordination of cellular processes. This review provides examples of these modules and considers the advantages of this signaling nexus.     

碱蓬属植物耐盐机理研究进展

碱蓬属(Suaeda)植物是一类典型的真盐生植物,属于重要的盐生植物资源,全球广泛分布.人们已经对20种碱蓬属植物进行了观察和盐胁迫实验,研究了不同器官或组织的生理生化特征及其对盐胁迫的反应,并基于这些研究分析了盐胁迫的应答机制.叶片肉质化、细胞内离子区域化、渗透调节物质增加和抗氧化系统能力增强是碱蓬属植物响应和适应盐胁迫的重要方式和途径.但迄今为止的研究工作尚有一定的局限性,主要包括:研究工作主要集中在植物地上部分,而对植物地下部分的研究较少;多是少数生物学指标或生理学现象的单独观察,而缺乏对生理代谢过程的整体和综合分析;针对某种碱蓬的独立分析较多,而与近缘种的比较研究较少;植物对中性盐胁迫的反应研究较多,而对碱性盐的研究较少.为进一步系统阐明碱蓬属植物的耐盐机制,今后的工作应注重碱蓬属植物响应和适应盐胁迫的信号网络和调控机制研究,基于系统生物学研究思路,采用现代组学技术探索该属植物响应盐胁迫的由复杂信号网络调控的特殊生理特征和特异代谢途径.     

Contact spotting of protein microarrays coupled with spike-in of normalizer protein permits time-resolved analysis of ERBB receptor signaling

Protein microarrays allow highly accurate comparison and quantification of numerous biological samples in parallel while requiring only little material. This qualifies protein arrays for systems biology and clinical research where only limited sample material is available, but a precise readout is required. With the introduction of signal normalization steps to monitor the drop size of manually contact-spotted RP protein arrays, the usefulness of normalizer proteins to ensure a high-throughput but inexpensive protein analysis was demonstrated. This approach was applied for the analysis of signaling through ERBB receptor activated kinases in the breast cancer cell line MCF-7. Activation of ERK1/2 and AKT by ERBB1 (EGFR), ERRB2 (HER2/neu), and ERBB3-4 was monitored in a time-resolved manner. Analysis of pathway activation by stimulation with epidermal growth factor and heregulin, or inhibition by blocking with gefitinib or herceptin allowed a characterization of the distinct signaling properties of the different ERBB receptor subtypes.     

Systems biology of virus-host signaling network interactions

Viruses have evolved to manipulate the host cell machinery for virus propagation, in part by interfering with the host cellular signaling network. Molecular studies of individual pathways have uncovered many viral host-protein targets; however, it is difficult to predict how viral perturbations will affect the signaling network as a whole. Systems biology approaches rely on multivariate, context-dependent measurements and computational analysis to elucidate how viral infection alters host cell signaling at a network level. Here we describe recent advances in systems analyses of signaling networks in both viral and non-viral biological contexts. These approaches have the potential to uncover virus- mediated changes to host signaling networks, suggest new therapeutic strategies, and assess how cell-to-cell variability affects host responses to infection. We argue that systems approaches will both improve understanding of how individual virus-host protein interactions fit into the progression of viral pathogenesis and help to identify novel therapeutic targets.     

Ensemble modeling for analysis of cell signaling dynamics

Systems biology iteratively combines experimentation with mathematical modeling. However, limited mechanistic knowledge, conflicting hypotheses and scarce experimental data severely hamper the development of predictive mechanistic models in many areas of biology. Even under such high uncertainty, we show here that ensemble modeling, when combined with targeted experimental analysis, can unravel key operating principles in complex cellular pathways. For proof of concept, we develop a library of mechanistically alternative dynamic models for the highly conserved target-of-rapamycin (TOR) pathway of Saccharomyces cerevisiae. In contrast to the prevailing view of a de novo assembly of type 2A phosphatases (PP2As), our integrated computational and experimental analysis proposes a specificity factor, based on Tap42p-Tip41p, for PP2As as the key signaling mechanism that is quantitatively consistent with all available experimental data. Beyond revising our picture of TOR signaling, we expect ensemble modeling to help elucidate other insufficiently characterized cellular circuits.     

Exploiting biological complexity for strain improvement through systems biology

Cellular complexity makes it difficult to build a complete understanding of cellular function but also offers innumerable possibilities for modifying the cellular machinery to achieve a specific purpose. The exploitation of cellular complexity for strain improvement has been a challenging goal for applied biological research because it requires the coordinated understanding of multiple cellular processes. It is therefore pursued most efficiently in the framework of systems biology. Progress in strain improvement will depend not only on advances in technologies for high-throughput measurements but, more importantly, on the development of theoretical methods that increase the information content of these measurements and, as such, facilitate the elucidation of mechanisms and the identification of genetic targets for modification.     

Interactome Mapping: Using Protein Microarray Technology to Reconstruct Diverse Protein Networks

A major focus of systems biology is to characterize interactions between cellular components, in order to develop an accurate picture of the intricate networks within biological systems. Over the past decade, protein microarrays have greatly contributed to advances in proteomics and are becoming an important platform for systems biology. Protein microarrays are highly flexible, ranging from large-scale proteome microarrays to smaller customizable microarrays, making the technology amenable for detection of a broad spectrum of biochemical properties of proteins. In this article, we will focus on the numerous studies that have utilized protein microarrays to reconstruct biological networks including protein-DNA interactions, posttranslational protein modifications (PTMs), lectin-glycan recognition, pathogen-host interactions and hierarchical signaling cascades. The diversity in applications allows for integration of interaction data from numerous molecular classes and cellular states, providing insight into the structure of complex biological systems. We will also discuss emerging applications and future directions of protein microarray technology in the global frontier.     

一种基于基因表达模型识别酵母细胞周期条件特异调控子网的方法

由高通量微阵列技术产生的数据集可以用于解释生物系统基因调控的未知机制.生物过程是动态的,所以很有必要关注某些条件下特异的基因调控子网络.细胞周期是一个基本的细胞过程,识别酵母的细胞周期特异调控子网是理解细胞周期过程的基础,并且有助于揭示其他细胞条件的基因调控机理.使用一个基因表达微分方程模型(GEDEM),从静态网络中识别了动态的细胞周期相关调控关系.与已经报道的细胞周期相关调控相互作用相比,该方法识别了更多的真实存在的条件特异调控关系,取得了比当前的方法更好的性能.在大数据集上,GEDEM 识别了具有高敏感性和特异性的调控子网.组合调控的深入分析显示,条件特异调控子网的转录因子之间的相关性呈现出比静态网络中转录因子相关性更强,这说明条件特异网络比静态网络更加接近真实情况.另外,GEDEM 方法还识别更多潜在的共调控转录因子.     

Dupuytren's: a systems biology disease

Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder of the palm of the hands leading to digital contracture. DD commonly occurs in individuals of northern European extraction. Cellular components and processes associated with DD pathogenesis include altered gene and protein expression of cytokines, growth factors, adhesion molecules, and extracellular matrix components. Histology has shown increased but varying levels of particular types of collagen, myofibroblasts and myoglobin proteins in DD tissue. Free radicals and localised ischaemia have been suggested to trigger the proliferation of DD tissue. Although the existing available biological information on DD may contain potentially valuable (though largely uninterpreted) information, the precise aetiology of DD remains unknown. Systems biology combines mechanistic modelling with quantitative experimentation in studies of networks and better understanding of the interaction of multiple components in disease processes. Adopting systems biology may be the ideal approach for future research in order to improve understanding of complex diseases of multifactorial origin. In this review, we propose that DD is a disease of several networks rather than of a single gene, and show that this accounts for the experimental observations obtained to date from a variety of sources. We outline how DD may be investigated more effectively by employing a systems biology approach that considers the disease network as a whole rather than focusing on any specific single molecule.