Characterization of a Planctomycetal Organelle: a Novel Bacterial Microcompartment for the Aerobic Degradation of Plant Saccharides

Bacterial microcompartments (BMCs) are organelles that encapsulate functionally linked enzymes within a proteinaceous shell. The prototypical example is the carboxysome, which functions in carbon fixation in cyanobacteria and some chemoautotrophs. It is increasingly apparent that diverse heterotrophic bacteria contain BMCs that are involved in catabolic reactions, and many of the BMCs are predicted to have novel functions. However, most of these putative organelles have not been experimentally characterized. In this study, we sought to discover the function of a conserved BMC gene cluster encoded in the majority of the sequenced planctomycete genomes. This BMC is especially notable for its relatively simple genetic composition, its remote phylogenetic position relative to characterized BMCs, and its apparent exclusivity to the enigmatic Verrucomicrobia and Planctomycetes. Members of the phylum Planctomycetes are known for their morphological dissimilarity to the rest of the bacterial domain: internal membranes, reproduction by budding, and lack of peptidoglycan. As a result, they are ripe for many discoveries, but currently the tools for genetic studies are very limited. We expanded the genetic toolbox for the planctomycetes and generated directed gene knockouts of BMC-related genes in Planctomyces limnophilus. A metabolic activity screen revealed that BMC gene products are involved in the degradation of a number of plant and algal cell wall sugars. Among these sugars, we confirmed that BMCs are formed and required for growth on l-fucose and l-rhamnose. Our results shed light on the functional diversity of BMCs as well as their ecological role in the planctomycetes, which are commonly associated with algae.     

Assembly of Robust Bacterial Microcompartment Shells Using Building Blocks from an Organelle of Unknown Function

Bacterial microcompartments (BMCs) sequester enzymes from the cytoplasmic environment by encapsulation inside a selectively permeable protein shell. Bioinformatic analyses indicate that many bacteria encode BMC clusters of unknown function and with diverse combinations of shell proteins. The genome of the halophilic myxobacterium Haliangium ochraceum encodes one of the most atypical sets of shell proteins in terms of composition and primary structure. We found that microcompartment shells could be purified in high yield when all seven H. ochraceum BMC shell genes were expressed from a synthetic operon in Escherichia coli. These shells differ substantially from previously isolated shell systems in that they are considerably smaller and more homogeneous, with measured diameters of 39 ± 2 nm. The size and nearly uniform geometry allowed the development of a structural model for the shells composed of 260 hexagonal units and 13 hexagons per icosahedral face. We found that new proteins could be recruited to the shells by fusion to a predicted targeting peptide sequence, setting the stage for the use of these remarkably homogeneous shells for applications such as three-dimensional scaffolding and the construction of synthetic BMCs. Our results demonstrate the value of selecting from the diversity of BMC shell building blocks found in genomic sequence data for the construction of novel compartments.     

Structural Insight into the Mechanisms of Transport across the Salmonella enterica Pdu Microcompartment Shell

Bacterial microcompartments are a functionally diverse group of proteinaceous organelles that confine specific reaction pathways in the cell within a thin protein-based shell. The propanediol utilizing (Pdu) microcompartment contains the reactions for metabolizing 1,2-propanediol in certain enteric bacteria, including Salmonella. The Pdu shell is assembled from a few thousand protein subunits of several different types. Here we report the crystal structures of two key shell proteins, PduA and PduT. The crystal structures offer insights into the mechanisms of Pdu microcompartment assembly and molecular transport across the shell. PduA forms a symmetric homohexamer whose central pore appears tailored for facilitating transport of the 1,2-propanediol substrate. PduT is a novel, tandem domain shell protein that assembles as a pseudohexameric homotrimer. Its structure reveals an unexpected site for binding an [Fe-S] cluster at the center of the PduT pore. The location of a metal redox cofactor in the pore of a shell protein suggests a novel mechanism for either transferring redox equivalents across the shell or for regenerating luminal [Fe-S] clusters.     

Characterization of the PduS Cobalamin Reductase of Salmonella enterica and Its Role in the Pdu Microcompartment

Salmonella enterica degrades 1,2-propanediol (1,2-PD) in a coenzyme B₁₂ (adenosylcobalamin, AdoCbl)-dependent fashion. Salmonella obtains AdoCbl by assimilation of complex precursors, such as vitamin B₁₂ and hydroxocobalamin. Assimilation of these compounds requires reduction of their central cobalt atom from Co³⁺ to Co²⁺ to Co⁺, followed by adenosylation to AdoCbl. In this work, the His₆-tagged PduS cobalamin reductase from S. enterica was produced at high levels in Escherichia coli, purified, and characterized. The anaerobically purified enzyme reduced cob(III)alamin to cob(II)alamin at a rate of 42.3 ± 3.2 μmol min⁻¹ mg⁻¹, and it reduced cob(II)alamin to cob(I)alamin at a rate of 54.5 ± 4.2 nmol min⁻¹ mg⁻¹ protein. The apparent K_m values of PduS-His₆ were 10.1 ± 0.7 μM for NADH and 67.5 ± 8.2 μM for hydroxocobalamin in cob(III)alamin reduction. The apparent K_m values for cob(II)alamin reduction were 27.5 ± 2.4 μM with NADH as the substrate and 72.4 ± 9.5 μM with cob(II)alamin as the substrate. High-performance liquid chromatography (HPLC) and mass spectrometry (MS) indicated that each monomer of PduS contained one molecule of noncovalently bound flavin mononucleotide (FMN). Genetic studies showed that a pduS deletion decreased the growth rate of Salmonella on 1,2-PD, supporting a role in cobalamin reduction in vivo. Further studies demonstrated that the PduS protein is a component of the Pdu microcompartments (MCPs) used for 1,2-PD degradation and that it interacts with the PduO adenosyltransferase, which catalyzes the terminal step of AdoCbl synthesis. These studies further characterize PduS, an unusual MCP-associated cobalamin reductase, and, in conjunction with prior results, indicate that the Pdu MCP encapsulates a complete cobalamin assimilation system.Coenzyme B₁₂ (adenosylcobalamin, AdoCbl) is an indispensable cofactor for a variety of enzymes that are widely distributed among microbes and higher animals (2, 55). Organisms obtain AdoCbl by de novo synthesis or by assimilation of complex precursors, such as vitamin B₁₂ (cyanocobalamin, CN-Cbl) and hydroxocobalamin (OH-Cbl), which can be enzymatically converted to AdoCbl. De novo synthesis occurs only in prokaryotes, but the assimilation of complex precursors is more widespread, taking place in many microbes and in higher animals (56). A model for the assimilation of CN-Cbl and OH-Cbl to AdoCbl, based on work done in a number of laboratories, is shown in Fig. ​Fig.1.1. CN-Cbl is first reductively decyanated to cob(II)alamin (22, 30, 68). Next, cob(II)alamin is reduced to cob(I)alamin, and ATP:cob(I)alamin adenosyltransferase (ATR) transfers a 5′ deoxyadenosyl group from ATP to cob(I)alamin to form AdoCbl (10, 11, 28, 29, 35, 63, 64, 72). Studies indicate that prior to reduction cob(II)alamin binds the ATR and undergoes a transition to the 4-coordinate base-off conformer (41, 48, 59, 61, 62). Transition to the 4-coordinate state raises the midpoint potential of the cob(II)alamin/cob(I)alamin couple by about 250 mV, facilitating reduction (60). OH-Cbl assimilation occurs by a similar pathway except that the first step is reduction of OH-Cbl to cob(II)alamin by cobalamin reductase or by the reducing environment of the cell (19, 69).Open in a separate windowFIG. 1.Cobalamin assimilation and recycling pathway. Many organisms are able to take up CN-Cbl and OH-Cbl and convert them to the active coenzyme form, AdoCbl. This process involves reduction of the central cobalt atom of the corrin ring followed by addition of a 5′ deoxyadenosyl (Ado) group via a carbon-cobalt bond. The Ado group is unstable in vivo, and AdoCbl breaks down to form OH-Cbl. Consequently, cobalamin recycling is required for AdoCbl-dependent processes, and recycling uses the same pathway that functions in the assimilation of cobalamin from the environment. PPPi, triphosphate.The pathway used for the assimilation of OH-Cbl and CN-Cbl is also used for intracellular cobalamin recycling. During catalysis the adenosyl group of AdoCbl is periodically lost due to by-reactions and is usually replaced by a hydroxyl group, resulting in the formation of an inactive OH-Cbl enzyme complex (66). Cobalamin recycling begins with a reactivase that converts the inactive OH-Cbl-enzyme complex to OH-Cbl and apoenzyme (43, 44). Next, the process described in Fig. ​Fig.11 converts OH-Cbl to AdoCbl, which spontaneously associates with apoenzyme to form active holoenzyme (43, 44, 66). In the organisms that have been studied, cobalamin recycling is essential, and genetic defects in this process block AdoCbl-dependent metabolism (3, 16, 29).Salmonella enterica degrades 1,2-propanediol (1,2-PD) via an AdoCbl-dependent pathway (27). 1,2-PD is a major product of the anaerobic degradation of common plant sugars rhamnose and fucose and is thought to be an important carbon and energy source in natural environments (38, 46). Twenty-four genes for 1,2-PD utilization (pdu) are found in a contiguous cluster (pocR, pduF, and pduABB′CDEGHJKLMNOPQSTUVWX) (7, 27). This locus encodes enzymes for the degradation of 1,2-PD and cobalamin recycling, as well as proteins for the formation of a bacterial microcompartment (MCP) (7). Bacterial MCPs are simple proteinaceous organelles used by diverse bacteria to optimize metabolic pathways that have toxic or volatile intermediates (6, 13, 14, 71). They are polyhedral in shape, 100 to 150 nm in cross section (about the size of a large virus), and consist of a protein shell that encapsulates sequentially acting metabolic enzymes. Sequence analyses indicate that MCPs are produced by 20 to 25% of all bacteria and function in seven or more different metabolic processes (14). The function of the Pdu MCP is to confine the propionaldehyde formed in the first step of 1,2-PD degradation in order to mitigate its toxicity and prevent DNA damage (7, 23, 24, 51). Prior studies indicate that 1,2-PD traverses the protein shell and enters the lumen of the Pdu MCP, where it is converted to propionaldehyde and then to propionyl-coenzyme A (CoA) by AdoCbl-dependent diol dehydratase (DDH; PduCDE) and propionaldehyde dehydrogenase (PduP) (8, 33). Propionyl-CoA then exits the MCP into the cytoplasm, where it is converted to 1-propanol or propionate or enters central metabolism via the methylcitrate pathway (25, 47). The shell of the Pdu MCP is thought to limit the diffusion of propionaldehyde in order to protect cytoplasmic components from toxicity. The Pdu MCP was purified, and 14 major polypeptide components were identified (PduABB′CDEGHJKOPTU), all of which are encoded by the pdu locus (23). PduABB′JKTU are confirmed or putative shell proteins (23, 24, 51). PduCDE and PduP catalyze the first 2 steps of 1,2-PD degradation as described above (7, 8, 23, 33). The PduO and PduGH enzymes are used for cobalamin recycling. PduO is an adenosyltransferase (29), and PduGH is a homolog of the Klebsiella DDH reactivase, which mediates the removal of OH-Cbl from an inactive OH-Cbl-DDH complex (43, 44). However, a reductase which is also required for cobalamin recycling was not previously identified as a component of the Pdu MCP (23). This raises the question of how cobalamin is recycled for the AdoCbl-dependent DDH that resides within the Pdu MCP.Prior studies indicated that the PduS enzyme (which is encoded by the pdu locus) is a cobalamin reductase (52). Very recently PduS was purified from S. enterica and shown to be a flavoprotein that can mediate the reduction of 4-coordinate cob(II)alamin bound to ATR but was not further characterized (40). In this study, PduS from S. enterica is purified and more extensively characterized, including identification of its cofactor requirements and kinetic properties. In addition, we show that PduS is a component of the Pdu MCP. This finding in conjunction with prior work indicates that, in addition to 1,2-PD degradative enzymes, the Pdu MCP encapsulates a complete cobalamin recycling system.     

PPIM: A Protein-Protein Interaction Database for Maize

Maize (Zea mays) is one of the most important crops worldwide. To understand the biological processes underlying various traits of the crop (e.g. yield and response to stress), a detailed protein-protein interaction (PPI) network is highly demanded. Unfortunately, there are very few such PPIs available in the literature. Therefore, in this work, we present the Protein-Protein Interaction Database for Maize (PPIM), which covers 2,762,560 interactions among 14,000 proteins. The PPIM contains not only accurately predicted PPIs but also those molecular interactions collected from the literature. The database is freely available at http://comp-sysbio.org/ppim with a user-friendly powerful interface. We believe that the PPIM resource can help biologists better understand the maize crop.Maize (Zea mays) is one of the most important crops in the world. Understanding the molecular mechanisms underlying various traits of maize (e.g. response to drought and salt) is important to improve the quality and yield of the crop. Although the maize genome sequence has unraveled the gene components of the crop, most traits involve complex interactions among molecules. Some protein-protein interactions (PPIs) have been experimentally determined in maize. For example, the CENTRORADIALIS8 protein was found to interact with the floral activator DLF1 protein with yeast two-hybrid assays (Danilevskaya et al., 2008), and barren stalk1 was found to interact with barren inflorescence2 with pull-down assays (Skirpan et al., 2008). Unfortunately, unlike other model organisms, there are very few molecular interactions available for maize. Therefore, a comprehensive maize interactome map is highly demanded.Recently, with more information about maize available, it has become practical to investigate the interactions between maize molecules. For example, with accumulating gene expression data, a gene coexpression network has been built to identify gene modules that play important roles in conditions of interest. With this idea, Downs et al. (2013) constructed a gene coexpression network based on gene expression data from 50 maize tissues and identified some gene modules that are important for development. By comparing the maize and rice (Oryza sativa) coexpression networks, Ficklin and Feltus (2011) identified some conserved gene modules between the two species, indicating their essential roles in crops. With protein abundance and phosphorylation data in different maize tissues across seven developmental stages, Walley et al. (2013) built a protein coexpression network to present kinase-substrate relationships. The metabolic network MaizeCyc (Monaco et al., 2013), containing enzyme catalysts, proteins, and other metabolites, has also been constructed. Focusing on maize kernel development, the expression quantitative trait loci have been investigated with RNA sequencing data (Fu et al., 2013), and the gene regulations underlying endosperm cell differentiation have been identified (Zhan et al., 2015).Despite the above efforts to identify possible interactions between molecules, no comprehensive interactome is available for maize. Most current approaches construct gene coexpression networks; however, these only describe the associations between genes and cannot tell which genes have real interactions. Under these circumstances, we present a comprehensive Protein-Protein Interaction Database for Maize (PPIM), which provides both our predicted physical and functional interactions as well as molecular interactions collected from the literature and public databases. To our knowledge, the PPIM is the most comprehensive database for maize to date. The user-friendly powerful interface accompanying the database can help biologists better explore the database.     

A Taxonomy of Bacterial Microcompartment Loci Constructed by a Novel Scoring Method

Bacterial microcompartments (BMCs) are proteinaceous organelles involved in both autotrophic and heterotrophic metabolism. All BMCs share homologous shell proteins but differ in their complement of enzymes; these are typically encoded adjacent to shell protein genes in genetic loci, or operons. To enable the identification and prediction of functional (sub)types of BMCs, we developed LoClass, an algorithm that finds putative BMC loci and inventories, weights, and compares their constituent pfam domains to construct a locus similarity network and predict locus (sub)types. In addition to using LoClass to analyze sequences in the Non-redundant Protein Database, we compared predicted BMC loci found in seven candidate bacterial phyla (six from single-cell genomic studies) to the LoClass taxonomy. Together, these analyses resulted in the identification of 23 different types of BMCs encoded in 30 distinct locus (sub)types found in 23 bacterial phyla. These include the two carboxysome types and a divergent set of metabolosomes, BMCs that share a common catalytic core and process distinct substrates via specific signature enzymes. Furthermore, many Candidate BMCs were found that lack one or more core metabolosome components, including one that is predicted to represent an entirely new paradigm for BMC-associated metabolism, joining the carboxysome and metabolosome. By placing these results in a phylogenetic context, we provide a framework for understanding the horizontal transfer of these loci, a starting point for studies aimed at understanding the evolution of BMCs. This comprehensive taxonomy of BMC loci, based on their constituent protein domains, foregrounds the functional diversity of BMCs and provides a reference for interpreting the role of BMC gene clusters encoded in isolate, single cell, and metagenomic data. Many loci encode ancillary functions such as transporters or genes for cofactor assembly; this expanded vocabulary of BMC-related functions should be useful for design of genetic modules for introducing BMCs in bioengineering applications.     

Interaction between Intrinsically Disordered Proteins Frequently Occurs in a Human Protein-Protein Interaction Network

Intrinsic protein disorder is a widespread phenomenon characterised by a lack of stable three-dimensional structures and is considered to play an important role in protein-protein interactions (PPIs). This study examined the genome-wide preference of disorder in PPIs by using exhaustive disorder prediction in human PPIs. We categorised the PPIs into three types (interaction between disordered proteins, interaction between structured proteins, and interaction between a disordered protein and a structured protein) with regard to the flexibility of molecular recognition and compared these three interaction types in an existing human PPI network with those in a randomised network. Although the structured regions were expected to become the identifiers for binding recognition, this comparative analysis revealed unexpected results. The occurrence of interactions between disordered proteins was significantly frequent, and that between a disordered protein and a structured protein was significantly infrequent. We found that this propensity was much stronger in interactions between nonhub proteins. We also analysed the interaction types from a functional standpoint by using GO, which revealed that the interaction between disordered proteins frequently occurred in cellular processes, regulation, and metabolic processes. The number of interactions, especially in metabolic processes between disordered proteins, was 1.8 times as large as that in the randomised network. Another analysis conducted by using KEGG pathways provided results where several signaling pathways and disease-related pathways included many interactions between disordered proteins. All of these analyses suggest that human PPIs preferably occur between disordered proteins and that the flexibility of the interacting protein pairs may play an important role in human PPI networks.     

Predicting Disease-Related Proteins Based on Clique Backbone in Protein-Protein Interaction Network

Network biology integrates different kinds of data, including physical or functional networks and disease gene sets, to interpret human disease. A clique (maximal complete subgraph) in a protein-protein interaction network is a topological module and possesses inherently biological significance. A disease-related clique possibly associates with complex diseases. Fully identifying disease components in a clique is conductive to uncovering disease mechanisms. This paper proposes an approach of predicting disease proteins based on cliques in a protein-protein interaction network. To tolerate false positive and negative interactions in protein networks, extending cliques and scoring predicted disease proteins with gene ontology terms are introduced to the clique-based method. Precisions of predicted disease proteins are verified by disease phenotypes and steadily keep to more than 95%. The predicted disease proteins associated with cliques can partly complement mapping between genotype and phenotype, and provide clues for understanding the pathogenesis of serious diseases.     

生物信息学方法预测蛋白质相互作用网络中的功能模块

蛋白质相互作用是大多数生命过程的基础。随着高通量实验技术和计算机预测方法的发展,在各种生物中已获得了数目十分庞大的蛋白质相互作用数据,如何从中提取出具有生物学意义的数据是一项艰巨的挑战。从蛋白质相互作用数据出发获得相互作用网络进而预测出其中的功能模块,对于蛋白质功能预测、揭示各种生化反应过程的分子机理都有着极大的帮助。我们分类概括了用生物信息学预测蛋白质相互作用功能模块的方法,以及对这些方法的评价,并介绍了蛋白质相互作用网络比较的一些方法。     

A Protein-Protein Interaction Map of the Trypanosoma brucei Paraflagellar Rod

We have conducted a protein interaction study of components within a specific sub-compartment of a eukaryotic flagellum. The trypanosome flagellum contains a para-crystalline extra-axonemal structure termed the paraflagellar rod (PFR) with around forty identified components. We have used a Gateway cloning approach coupled with yeast two-hybrid, RNAi and 2D DiGE to define a protein-protein interaction network taking place in this structure. We define two clusters of interactions; the first being characterised by two proteins with a shared domain which is not sufficient for maintaining the interaction. The other cohort is populated by eight proteins, a number of which possess a PFR domain and sub-populations of this network exhibit dependency relationships. Finally, we provide clues as to the structural organisation of the PFR at the molecular level. This multi-strand approach shows that protein interactome data can be generated for insoluble protein complexes.     

The Structural Basis of Coenzyme A Recycling in a Bacterial Organelle

Bacterial Microcompartments (BMCs) are proteinaceous organelles that encapsulate critical segments of autotrophic and heterotrophic metabolic pathways; they are functionally diverse and are found across 23 different phyla. The majority of catabolic BMCs (metabolosomes) compartmentalize a common core of enzymes to metabolize compounds via a toxic and/or volatile aldehyde intermediate. The core enzyme phosphotransacylase (PTAC) recycles Coenzyme A and generates an acyl phosphate that can serve as an energy source. The PTAC predominantly associated with metabolosomes (PduL) has no sequence homology to the PTAC ubiquitous among fermentative bacteria (Pta). Here, we report two high-resolution PduL crystal structures with bound substrates. The PduL fold is unrelated to that of Pta; it contains a dimetal active site involved in a catalytic mechanism distinct from that of the housekeeping PTAC. Accordingly, PduL and Pta exemplify functional, but not structural, convergent evolution. The PduL structure, in the context of the catalytic core, completes our understanding of the structural basis of cofactor recycling in the metabolosome lumen.     

Adding Protein Context to the Human Protein-Protein Interaction Network to Reveal Meaningful Interactions

Interactions of proteins regulate signaling, catalysis, gene expression and many other cellular functions. Therefore, characterizing the entire human interactome is a key effort in current proteomics research. This challenge is complicated by the dynamic nature of protein-protein interactions (PPIs), which are conditional on the cellular context: both interacting proteins must be expressed in the same cell and localized in the same organelle to meet. Additionally, interactions underlie a delicate control of signaling pathways, e.g. by post-translational modifications of the protein partners - hence, many diseases are caused by the perturbation of these mechanisms. Despite the high degree of cell-state specificity of PPIs, many interactions are measured under artificial conditions (e.g. yeast cells are transfected with human genes in yeast two-hybrid assays) or even if detected in a physiological context, this information is missing from the common PPI databases. To overcome these problems, we developed a method that assigns context information to PPIs inferred from various attributes of the interacting proteins: gene expression, functional and disease annotations, and inferred pathways. We demonstrate that context consistency correlates with the experimental reliability of PPIs, which allows us to generate high-confidence tissue- and function-specific subnetworks. We illustrate how these context-filtered networks are enriched in bona fide pathways and disease proteins to prove the ability of context-filters to highlight meaningful interactions with respect to various biological questions. We use this approach to study the lung-specific pathways used by the influenza virus, pointing to IRAK1, BHLHE40 and TOLLIP as potential regulators of influenza virus pathogenicity, and to study the signalling pathways that play a role in Alzheimer''s disease, identifying a pathway involving the altered phosphorylation of the Tau protein. Finally, we provide the annotated human PPI network via a web frontend that allows the construction of context-specific networks in several ways.     

荧光素酶在蛋白相互作用研究中的应用

蛋白质相互作用参与细胞的多项生理活动,是生命科学研究的一个重要领域。化学发光,特别是基于生物酶的化学发光即生物发光,提供了极灵敏的检测信号,因而在实际应用中具有诸多优势。荧光素酶如萤火虫荧光素酶、细菌荧光素酶、海肾荧光素酶,以及近年来出现的几种低分子量荧光素酶,具有不同的酶催化特性及理化特征。它们应用于蛋白质片段互补与共振能量转移技术等各种生化检测方法,为观察蛋白质相互作用提供了更安全便捷的手段,拓宽了蛋白质相互作用检测技术的适用范围。本文综述了常用荧光素酶的特征和它们在各种蛋白质相互作用检测方法中使用的原理、策略及其适用性。     

t-LSE: A Novel Robust Geometric Approach for Modeling Protein-Protein Interaction Networks

Protein-protein interaction (PPI) networks provide insights into understanding of biological processes, function and the underlying complex evolutionary mechanisms of the cell. Modeling PPI network is an important and fundamental problem in system biology, where it is still of major concern to find a better fitting model that requires less structural assumptions and is more robust against the large fraction of noisy PPIs. In this paper, we propose a new approach called t-logistic semantic embedding (t-LSE) to model PPI networks. t-LSE tries to adaptively learn a metric embedding under the simple geometric assumption of PPI networks, and a non-convex cost function was adopted to deal with the noise in PPI networks. The experimental results show the superiority of the fit of t-LSE over other network models to PPI data. Furthermore, the robust loss function adopted here leads to big improvements for dealing with the noise in PPI network. The proposed model could thus facilitate further graph-based studies of PPIs and may help infer the hidden underlying biological knowledge. The Matlab code implementing the proposed method is freely available from the web site: http://home.ustc.edu.cn/~yzh33108/PPIModel.htm.     

基于MADS-box诱饵与蛋白质相互作用的拟南芥花瓣发育分子网络拓展

阐明花器官发育调控机理具重要的进化、发育和生态学意义。该文以拟南芥(Arabidopsis thaliana)花瓣发育为例, 整合蛋白质互作、亚细胞定位、基因芯片和基因功能注释等数据库, 通过组建蛋白质互作可信预测模型, 获得拟南芥花瓣蛋白质互作网络, 以含有MADS-box结构域蛋白为诱饵在网络中进行一级拓展, 得到含38个蛋白质和67对互作的拓展网络。基于拓展网络, DAVID基因功能注释表明, 多数蛋白质涉及的生物学过程与花发育调控相关; 提取到19个候选四元互作, 涉及ABCDE模型基因之外的8个基因, 其中含MADS-box结构域的AGL16可能是B类基因新成员或其冗余; SEU、LUH、CHR4、CHR11、CHR17和AT3G04960为拟南芥花瓣AP1-AP3-PI-SEP四聚体的候选靶标基因。研究结果为深入解析拟南芥花瓣发育分子调控网络奠定了基础。