An algorithm for efficient identification of branched metabolic pathways

This article presents a new graph-based algorithm for identifying branched metabolic pathways in multi-genome scale metabolic data. The term branched is used to refer to metabolic pathways between compounds that consist of multiple pathways that interact biochemically. A branched pathway may produce a target compound through a combination of linear pathways that split compounds into smaller ones, work in parallel with many compounds, and join compounds into larger ones. While branched metabolic pathways predominate in metabolic networks, most previous work has focused on identifying linear metabolic pathways. The ability to automatically identify branched pathways is important in applications that require a deeper understanding of metabolism, such as metabolic engineering and drug target identification. The algorithm presented in this article utilizes explicit atom tracking to identify linear metabolic pathways and then merges them together into branched metabolic pathways. We provide results on several well-characterized metabolic pathways that demonstrate that the new merging approach can efficiently find biologically relevant branched metabolic pathways.     

Categorization of metabolome in bacterial systems

Analyses of biological databases such as those of genome, proteome, metabolome etc., have given insights in organization of biological systems. However, current efforts do not utilize the complete potential of available metabolome data. In this study, metabolome of bacterial systems with reliable annotations are analyzed and a simple method is developed to categorize pathways hierarchically, using rational approach. Ninety-four bacterial systems having for each ≥ 250 annotated metabolic pathways were used to identify a set of common pathways. 42 pathways were present in all bacteria which are termed as Core/Stage I pathways. This set of pathways was used along with interacting compounds to categorize pathways in the metabolome hierarchically. In each metabolome non-interacting pathways were identified including at each stage. The case study of Escherichia coli O157, having 433 annotated pathways, shows that 378 pathways interact directly or indirectly with 41 core pathways while 14 pathways are noninteracting. These 378 pathways are distributed in Stage II (289), Stage III (75), Stage IV (13) and Stage V (1) category. The approach discussed here allows understanding of the complexity of metabolic networks. It has pointed out that core pathways could be most ancient pathways and compounds that interact with maximum pathways may be compounds with high biosynthetic potential, which can be easily identified. Further, it was shown that interactions of pathways at various stages could be one to one, one to many, many to one or many to many mappings through interacting compounds. The granularity of the method discussed being high; the impact of perturbation in a pathway on the metabolome and particularly sub networks can be studied precisely. The categorizations of metabolic pathways help in identifying choke point enzymes that are useful to identify probable drug targets. The Metabolic categorizations for 94 bacteria are available at http://115.111.37.202/mpe/.     

Comparison of pathways associated with hepatitis B- and C-infected hepatocellular carcinoma using pathway-based class discrimination method

Molecular signatures causing hepatocellular carcinoma (HCC) from chronic infection of hepatitis B virus (HBV) or hepatitis C virus (HCV) are not clearly known. Using microarray datasets composed of HCV-positive HCC or HBV-positive HCC, pathways that could discriminate tumor tissue from adjacent non-tumor liver tissue were selected by implementing nearest shrunken centroid algorithm. Cancer-related signaling pathways and lipid metabolism-related pathways were predominantly enriched in HCV-positive HCC, whereas functionally diverse pathways including immune-related pathways, cell cycle pathways, and RNA metabolism pathways were mainly enriched in HBV-positive HCC. In addition to differentially involved pathways, signaling pathways such as TGF-β, MAPK, and p53 pathways were commonly significant in both HCCs, suggesting the presence of common hepatocarcinogenesis process. The pathway clustering also verified segregation of pathways into the functional subgroups in both HCCs. This study indicates the functional distinction and similarity on the pathways implicated in the development of HCV- and/or HBV-positive HCC.     

雌激素受体信号通路在乳腺癌发生和治疗中的作用

雌激素受体信号通路在调控乳腺细胞增殖和凋亡等生理机能中发挥重要功能,该通路出现调控异常时可导致乳腺癌发生。雌激素受体在乳腺癌发生中的作用机制包括核受体介导的基因组信号通路和膜受体介导的非基因组信号通路以及二者的相互作用。基于雌激素受体信号通路及其关键信号分子的靶向治疗是开展乳腺癌治疗的重要策略与有效途径。对雌激素受体结构以及雌激素受体信号通路在乳腺癌发生和治疗中的作用作一综述。     

Computer-aided synthesis of biochemical pathways

The synthesis of biochemical pathways satisfying stoichiometric constraints is discussed. Stoichiometric constraints arise primarily from designating compounds as required or allowed reactants, and required or allowed products of the pathways; they also arise from similar restrictions on intermediate metabolites and bioreactions participating in the pathways. An algorithm for the complete and correct solution of the problem is presented; the algorithm satisfies each constraint by recursively transforming a base-set of pathways. The algorithm is applied to the problem of lysine synthesis from glucose and ammonia. In addition to the established synthesis routes, the algorithm constructs several alternative pathways that bypass key enzymes, such as malate dehydrogenase and pyruvate dehydrogenase. Apart from the construction of pathways with desired characteristics, the systematic synthesis of pathways can also uncover fundamental constraints in a particular problem, by demonstrating that no pathways exist to meet certain sets of specifications. In the case of lysine, the algorithm shows that oxaloacetate is a necessary intermediate in all pathways leading to lysine from glucose, and that the yield of lysine over glucose cannot exceed 67% in the absence of enzymatic recovery of carbon dioxide.     

种子萌发过程中贮藏油脂的动员

对植物种子萌发过程中贮藏油脂动员的研究进展进行了综述。不同种子的贮藏油脂的降解途径不同。目前提出有3条途径:传统的脂酶直接水解途径;新近发现的酰基-CoA-二酯酰甘油酰基转移酶途径和脂氧合酶(LOX)途径。前两条途径不依赖于LOX。这3条途径可能在贮藏油脂动员过程中是并存的,但目前尚不知道在种子萌发过程中油脂降解是以那一条降解途径为主,以及不同的种之间是否存在差异。此外,3条降解途径目前都缺乏分子生物学的直接证据。     

A graph layout algorithm for drawing metabolic pathways

MOTIVATION: A large amount of data on metabolic pathways is available in databases. The ability to visualise the complex data dynamically would be useful for building more powerful research tools to access the databases. Metabolic pathways are typically modelled as graphs in which nodes represent chemical compounds, and edges represent chemical reactions between compounds. Thus, the problem of visualising pathways can be formulated as a graph layout problem. Currently available visual interfaces to biochemical databases either use static images or cannot cope well with more complex, non-standard pathways. RESULTS: This paper presents a new algorithm for drawing pathways which uses a combination of circular, hierarchic and force-directed graph layout algorithms to compute positions of the graph elements representing main compounds and reactions. The algorithm is particularly designed for cyclic or partially cyclic pathways or for combinations of complex pathways. It has been tested on five sample pathways with promising results.     

基于全局角度网络策略的复杂疾病风险通路识别

复杂疾病的发生发展与机体内生物学通路的功能紊乱有密切联系,从高通量数据出发,利用计算机辅助方法来研究疾病与通路间的关系具有重要意义.本文提出了一个新的基于网络的全局性通路识别方法.该方法利用蛋白质互作信息和通路的基因集组成信息构建复杂的蛋白质-通路网.然后,基于表达谱数据,通过随机游走算法从全局层面优化疾病风险通路.最终,通过扰动方式识别统计学显著的风险通路.将该网络运用于结肠直肠癌风险通路识别,识别出15个与结肠直肠癌发生与发展过程显著相关的通路.通过与其他通路识别方法(超几何检验,SPIA)相比较,该方法能够更有效识别出疾病相关的风险通路.     

Origins and Evolution of Pathways of Anaerobic Metabolism in the Animal Kingdom

Energetic characteristics and functional roles define two maintypes of anaerobicpathways in the animal kingdom: high efficiency/lowrates of energy production pathways geared to anoxia survival(aspartate-succinate and glucose-succinate pathways), and lowefficiency?/high rates of energy production pathways gearedto maintaining or increasing metabolic activity (multiple opinepathways and lactate pathway). The aspartate-succinate and opinepathways require both amino acids and carbohydrate as substrates,whereas the glucose-succinate and lactate pathways are dependenton carbohydrate only. Phylogenetic, functional and chemicalconsiderations indicate an evolutionary progression from aminoacid-linked to carbohydrate-based anaerobic pathways. The tauropineand strombine pathwaysare possibly the most ancient opine pathwaysso far discovered, and the octopine pathway the most advanced.The roles of the aspartate-succinate and opine pathways mayoriginally have been not too dissimilar. A hierarchy of "ratesof energy production pathways" of phosphagen > lactate >octopine > other opine pathways is proposed, which definesmuch of their phylogenetic selection and how they are used.The different properties of phosphocreatine compared to otherphosphagens is indicated to have been a key factor in the emergenceof vertebrates     

骨髓间充质干细胞向肝细胞分化的相关细胞因子及信号通路的研究进展

骨髓干细胞包括造血干细胞（HSCs）和间充质干细胞（MSCs）,骨髓间充质干细胞（BMSCs）是一类具有自我更新、增殖和多向分化能力的细胞,具有不对称分裂和无限增殖的特点。在肝细胞生长因子（HGF）的作用下,BMSCs可以分化为肝细胞,参与诱导这一分化过程的相关信号通路包括NF-kB信号通路、Notch信号通路、MAPK信号通路、Wnt信号通路和STAT3信号通路。文章主要就BMSCs分化为肝细胞的相关信号通路进行了综述。     

Exploring poly-beta-hydroxy-butyrate metabolism through network-based extreme pathway analysis

The objective of this article is to obtain a more detailed insight into poly-beta-hydroxybutyrate (PHB) metabolism through network-based metabolic pathway analysis. We employ extreme pathways to perform this study, because calculating and interpreting extreme pathways is a promising way for pathway analysis and metabolic engineering. After giving an in silico model of butanoate metabolism of Bacillus thuringiensis 97-27 (btk), extreme pathways were calculated and classified. Furthermore, the type I and II extreme pathways were further classified and analyzed in detail based on their structure and functional capabilities. Besides "historical" biochemical pathways, the results also suggest that there are some novel pathways.     

Protein trafficking to plastids: one theme, many variations

Plastids are a diverse group of essential organelles in plants that include chloroplasts. The biogenesis and maintenance of these organelles relies on the import of thousands of nucleus-encoded proteins. The complexity of plastid structure has resulted in the evolution of at least four general import pathways that target proteins into and across the double membrane of the plastid envelope. Several of these pathways can be further divided into specialty pathways that mediate and regulate the import of specific classes of proteins. The co-ordination of import by these specialized pathways with changes in gene expression is critical for plastid and plant development. Moreover, protein import is acutely regulated in response to physiological and metabolic changes within the cell. In the present review we summarize the current knowledge of the mechanism of import via these pathways and highlight the regulatory mechanisms that integrate the plastid protein-trafficking pathways with the developmental and metabolic state of the plant.     

Structural biology of the thioester-dependent degradation and synthesis of fatty acids

The fatty acid degradation and synthesis pathways consist of the same four chemical transformations. These transformations are facilitated by conjugating the fatty acid, via a thioester bond, to coenzyme A or acyl carrier protein in, respectively, the degradation and synthesis pathways. These pathways are compartmentalized in the peroxisomes, mitochondria and cytosol of eukaryotic cells. Current structural knowledge of the enzymes comprising these pathways shows that the approximately 130 entries in the RCSB Protein Data Bank can be grouped into seven superfamilies. Multifunctional enzymes are important in both pathways.     

Pathway Miner: extracting gene association networks from molecular pathways for predicting the biological significance of gene expression microarray data

We have developed a web-based system (Pathway Miner) for visualizing gene expression profiles in the context of biological pathways. Pathway Miner catalogs genes based on their role in metabolic, cellular and regulatory pathways. A Fisher exact test is provided as an option to rank pathways. The genes are mapped onto pathways and gene product association networks are extracted for genes that co-occur in pathways. The networks can be filtered for analysis based on user-selected options. AVAILABILITY: Pathway Miner is a freely available web accessible tool at http://www.biorag.org/pathway.html     

Generating stereochemically acceptable protein pathways

We describe a new method for rapidly generating stereochemically acceptable pathways in proteins. The method, called geometric targeting, is publicly available at the webserver http://pathways.asu.edu , and includes tools for visualization of the pathway and creating movie files for use in presentations. The user submits an initial structure and a target structure, and a pathway between the two input states is generated automatically. Besides visualization, the structural quality of the pathways makes them useful as input pathways into pathway refinement techniques and further computations. The approach in geometric targeting is to gradually change the system's RMSD relative to the target structure while enforcing a set of geometric constraints. The generated pathways are not minimum free energy pathways, but they are geometrically plausible pathways that maintain good covalent bond distances and angles, keep backbone dihedral angles in allowed Ramachandran regions, avoid eclipsed side‐chain torsion angles, avoid non‐bonded overlap, and maintain a set of hydrogen bonds and hydrophobic contacts. Resulting pathways for over 20 proteins featuring a wide variety of conformational changes are reported here, including the very large GroEL complex. Proteins 2010. © 2010 Wiley‐Liss, Inc.     

Average rank-based score to measure deregulation of molecular pathway gene sets

Background

Deregulation of biological pathways has been shown to be involved in the turmorigenesis of a variety of cancers. The co-regulation of pathways in tumor and normal tissues has not been studied in a systematic manner.

Results

In this study we propose a novel statistic named AR-score (average rank based score) to measure pathway activities based on microarray gene expression profiles. We calculate and compare the AR-scores of pathways in microarray datasets containing expression profiles for a wide range of cancer types as well as the corresponding normal tissues. We find that many pathways undergo significant activity changes in tumors with respect to normal tissues. AR-scores for a small subset of pathways are capable of distinguishing tumor from normal tissues or classifying tumor subtypes. In normal tissues many pathways are highly correlated in their activities, whereas their correlations reduce significantly in tumors and cancer cell lines. The co-expression of genes in the same pathways was also significantly perturbed in tumors.

Conclusions

The co-regulation of genes in the same pathways and co-regulation of different pathways are significantly perturbed in tumors versus normal tissues. Our method provides a useful tool for better understanding the mechanistic changes in tumors, which can also be used for exploring other biological problems.     

Prospects of yeast systems biology for human health: integrating lipid, protein and energy metabolism

The yeast Saccharomyces cerevisiae is a widely used model organism for studying cell biology, metabolism, cell cycle and signal transduction. Many regulatory pathways are conserved between this yeast and humans, and it is therefore possible to study pathways that are involved in disease development in a model organism that is easy to manipulate and that allows for detailed molecular studies. Here, we briefly review pathways involved in lipid metabolism and its regulation, the regulatory network of general metabolic regulator Snf1 (and its human homologue AMPK) and the proteostasis network with its link to stress and cell death. All the mentioned pathways can be used as model systems for the study of homologous pathways in human cells and a failure in these pathways is directly linked to several human diseases such as the metabolic syndrome and neurodegeneration. We demonstrate how different yeast pathways are conserved in humans, and we discuss the possibilities of using the systems biology approach to study and compare the pathways of relevance with the objective to generate hypotheses and gain new insights.     

An Effective Method to Identify Shared Pathways and Common Factors among Neurodegenerative Diseases

Groups of distinct but related diseases often share common symptoms, which suggest likely overlaps in underlying pathogenic mechanisms. Identifying the shared pathways and common factors among those disorders can be expected to deepen our understanding for them and help designing new treatment strategies effected on those diseases. Neurodegeneration diseases, including Alzheimer''s disease (AD), Parkinson''s disease (PD) and Huntington''s disease (HD), were taken as a case study in this research. Reported susceptibility genes for AD, PD and HD were collected and human protein-protein interaction network (hPPIN) was used to identify biological pathways related to neurodegeneration. 81 KEGG pathways were found to be correlated with neurodegenerative disorders. 36 out of the 81 are human disease pathways, and the remaining ones are involved in miscellaneous human functional pathways. Cancers and infectious diseases are two major subclasses within the disease group. Apoptosis is one of the most significant functional pathways. Most of those pathways found here are actually consistent with prior knowledge of neurodegenerative diseases except two cell communication pathways: adherens and tight junctions. Gene expression analysis showed a high probability that the two pathways were related to neurodegenerative diseases. A combination of common susceptibility genes and hPPIN is an effective method to study shared pathways involved in a group of closely related disorders. Common modules, which might play a bridging role in linking neurodegenerative disorders and the enriched pathways, were identified by clustering analysis. The identified shared pathways and common modules can be expected to yield clues for effective target discovery efforts on neurodegeneration.     

硝基苯污染物的生物降解途径

硝基苯是一种有毒化合物,目前,关于硝基苯污染物的生物降解已进行了大量的研究。综述了生物降解硝基苯的两种主要途径氧化途径和部分还原途径,介绍了两种途径降解硝基苯的具体机制及相关酶和编码基因的特点,并对两种降解途径进行了简要的对比分析,为硝基苯及其它有机污染物生物降解技术的开发应用提供依据。     

Pathways-Driven Sparse Regression Identifies Pathways and Genes Associated with High-Density Lipoprotein Cholesterol in Two Asian Cohorts

Standard approaches to data analysis in genome-wide association studies (GWAS) ignore any potential functional relationships between gene variants. In contrast gene pathways analysis uses prior information on functional structure within the genome to identify pathways associated with a trait of interest. In a second step, important single nucleotide polymorphisms (SNPs) or genes may be identified within associated pathways. The pathways approach is motivated by the fact that genes do not act alone, but instead have effects that are likely to be mediated through their interaction in gene pathways. Where this is the case, pathways approaches may reveal aspects of a trait''s genetic architecture that would otherwise be missed when considering SNPs in isolation. Most pathways methods begin by testing SNPs one at a time, and so fail to capitalise on the potential advantages inherent in a multi-SNP, joint modelling approach. Here, we describe a dual-level, sparse regression model for the simultaneous identification of pathways and genes associated with a quantitative trait. Our method takes account of various factors specific to the joint modelling of pathways with genome-wide data, including widespread correlation between genetic predictors, and the fact that variants may overlap multiple pathways. We use a resampling strategy that exploits finite sample variability to provide robust rankings for pathways and genes. We test our method through simulation, and use it to perform pathways-driven gene selection in a search for pathways and genes associated with variation in serum high-density lipoprotein cholesterol levels in two separate GWAS cohorts of Asian adults. By comparing results from both cohorts we identify a number of candidate pathways including those associated with cardiomyopathy, and T cell receptor and PPAR signalling. Highlighted genes include those associated with the L-type calcium channel, adenylate cyclase, integrin, laminin, MAPK signalling and immune function.