KEGG数据库在生物合成研究中的应用

KEGG(Kyoto Encyclopedia of Genes and Genomes)提供了一个操作平台,即以基因组信息(GENES)和化学物质信息(LIGAND)为构建模块,通过代谢网络(PATHWAY)将基因组和生物系统联系起来,然后根据功能等级进行归纳分类(BRITE)。KEGG还为各种组学研究提供相关软件,用于代谢途径重建、遗传分析和化合物比对。作为一个综合数据库,KEGG不仅指导生物燃料、药物和新材料等生物基化学品的合成,而且致力于研究日趋严重的环境问题。系统介绍了KEGG数据库的结构、功能及其相关工具的最新进展,并展望在生物合成中的应用前景。     

Relocation of genes generates non-conserved chromosomal segments in Fusarium graminearum that show distinct and co-regulated gene expression patterns

Background

Genome comparisons between closely related species often show non-conserved regions across chromosomes. Some of them are located in specific regions of chromosomes and some are even confined to one or more entire chromosomes. The origin and biological relevance of these non-conserved regions are still largely unknown. Here we used the genome of Fusarium graminearum to elucidate the significance of non-conserved regions.

Results

The genome of F. graminearum harbours thirteen non-conserved regions dispersed over all of the four chromosomes. Using RNA-Seq data from the mycelium of F. graminearum, we found weakly expressed regions on all of the four chromosomes that exactly matched with non-conserved regions. Comparison of gene expression between two different developmental stages (conidia and mycelium) showed that the expression of genes in conserved regions is stable, while gene expression in non-conserved regions is much more influenced by developmental stage. In addition, genes involved in the production of secondary metabolites and secreted proteins are enriched in non-conserved regions, suggesting that these regions could also be important for adaptations to new environments, including adaptation to new hosts. Finally, we found evidence that non-conserved regions are generated by sequestration of genes from multiple locations. Gene relocations may lead to clustering of genes with similar expression patterns or similar biological functions, which was clearly exemplified by the PKS2 gene cluster.

Conclusions

Our results showed that chromosomes can be functionally divided into conserved and non-conserved regions, and both could have specific and distinct roles in genome evolution and regulation of gene expression.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-191) contains supplementary material, which is available to authorized users.     

Shared KEGG pathways of icariin-targeted genes and osteoarthritis

The beneficial effects of icariin in the management of many diseases, such as chronic renal failure and heart failure, are well known. Icariin has also been shown to ameliorate osteoarthritis (OA) symptoms; however, the underlying mechanisms remain unclear. In this study, a bioinformatics analysis was performed to investigate the KEGG pathways of icariin-targeted genes involved in OA. Our study suggests that icariin plays a role in OA by regulating inflammatory cytokine production, insulin resistance, and cell survival through modulation of the NF-κB, MAPK, and Akt signaling pathways. Importantly, IKBKB, NFKBIA, MAPK8, MAPK9, and MAPK10 may be the hub genes affected by icariin when providing its beneficial effects on OA. In addition, we found that icariin decreases proinflammatory factors and inhibits chondrocyte apoptosis through suppression of the NF-κB pathway. Our study highlights a set of KEGG pathways that could explain the molecular mechanism of icariin's action on OA, suggesting that icariin could be considered as a promising therapeutic option for OA.     

Gene expression patterns define pathways correlated with loss of differentiation in lung adenocarcinomas

An analysis of microarray data from 86 lung adenocarcinomas reveals hundreds of genes significantly correlated with tumor cell differentiation. A bioinformatics approach of linking these genes to public information from the Locuslink and KEGG databases yields evidence for a loss of tumor cell differentiation being associated with biological processes of cell division, protein degradation, pyrimidine and purine metabolism, oxidative phosphorylation, glyoxylate and dicarboxylate metabolism, folate biosynthesis, and glutamate metabolism. The increased expression of genes involved in these processes is consistent with increased proliferation and metabolism characteristics of poorly differentiated tumors. The complete results of this analysis are available at http://dot.ped.med.umich.edu:2000/pub/diff/index.htm.     

Computational identification of altered metabolism using gene expression and metabolic pathways

Understanding altered metabolism is an important issue because altered metabolism is often revealed as a cause or an effect in pathogenesis. It has also been shown to be an important factor in the manipulation of an organism's metabolism in metabolic engineering. Unfortunately, it is not yet possible to measure the concentration levels of all metabolites in the genome‐wide scale of a metabolic network; consequently, a method that infers the alteration of metabolism is beneficial. The present study proposes a computational method that identifies genome‐wide altered metabolism by analyzing functional units of KEGG pathways. As control of a metabolic pathway is accomplished by altering the activity of at least one rate‐determining step enzyme, not all gene expressions of enzymes in the pathway demonstrate significant changes even if the pathway is altered. Therefore, we measure the alteration levels of a metabolic pathway by selectively observing expression levels of significantly changed genes in a pathway. The proposed method was applied to two strains of Saccharomyces cerevisiae gene expression profiles measured in very high‐gravity (VHG) fermentation. The method identified altered metabolic pathways whose properties are related to ethanol and osmotic stress responses which had been known to be observed in VHG fermentation because of the high sugar concentration in growth media and high ethanol concentration in fermentation products. With the identified altered pathways, the proposed method achieved best accuracy and sensitivity rates for the Red Star (RS) strain compared to other three related studies (gene‐set enrichment analysis (GSEA), significance analysis of microarray to gene set (SAM‐GS), reporter metabolite), and for the CEN.PK 113‐7D (CEN) strain, the proposed method and the GSEA method showed comparably similar performances. Biotechnol. Bioeng. 2009;103: 835–843. © 2009 Wiley Periodicals, Inc.     

基因表达差异显示分析技术在创伤研究中的应用

基因是细胞增殖,分化,成熟等各项生命活动的调控中心,也是许多痢疾发生,发展和转归的决定性因素。基因表达的变化必然导致细胞,组织,器官乃至整个机体的各种异常。包括创伤在内的各种内外刺激,都可不同程度地引起基因表达的变化,最终妨碍机体健康。随着生物信息学的逐渐兴起和分子生物学的不断发展并向其他学科的逐渐渗透,业已建立起一系列研究基因表达变化的切实可行的技术手段（即“基因表达差异分析技术”,如DNA微阵列）,对捕获基因表达的种种变化具有重要价值。这些技术已经在肿瘤及其他疾病的研究中得到广泛应用,近几年也逐渐进入创伤研究领域,在一定程度上推动了创伤研究的发展。     

Assignment and expression patterns of porcine muscle-specific isoform of phosphoglycerate mutase gene

It has been reported that the muscle-specific isoform (type M, PGAM2) of phosphoglycerate mutase (PGAM) is a housekeeping en-zyme; it catalyzes the conversion of 3-phospboglycerate into 2-phosphoglycerate in the glyeolysis process to release energy. It is encoded by the Pgam2 gene. In this study, the eDNA of the porcine Pgam2 was cloned. This gene contains an open reading frame of 765 bp en-coding a protein of 253 residues, and the predicted protein sequences share high similarity with other mammalians, 96% identity with humans, and 94% identity with mouse and rats. Pgam2 was mapped to SSC18q13-q21 by the RH panel. In this region, there are several QTLs, such as fat ratio, lean percentage, and diameter of muslce fiber, which affect meat production and quality. The reverse transcrip-tase-polymerase chain reaction revealed that the porcine Pgam2 gene was mainly expressed in the muscle tissue (skeletal muscle and cardiac muscle), and was expressed highly at skeletal muscle development stages (embryonic periods: 33, 65, and 90 days post-conception(dpe); postnatal pigs: 4 days and adult). This indicates that the Pgam2 gene plays an important role in muscle growth and development. In addition, it was demonstrated that PGAM2 locates both in cytoplasm and nuclei, and takes part in the glycometabolism process of cyto-plasm and nuclei.     

特征代谢通路上的基因表达相关性及共调控表达模式

利用随机森林-通路分析法,通过袋外样本OOB的分类错误率筛选特征代谢通路,在特征通路上作基因表达相关性研究并对通路上的基因采用MAP(Mining attribute profile)算法挖掘不同实验条件下基因的共调控表达模式,对共调控表达模式进行聚类.分析结果显示同一特征代谢通路上的基因表达倾向相似,有2条特征代谢通路存在共表达模式.其中一条通路含108个表达模式,对这些模式进行聚类,其最低聚类的相似系数仍高达0.623.说明同一特征代谢通路上的基因共表达模式在不同实验条件下仍具有高度的相似性.对以通路作为基因模块进行复杂疾病的研究具有借鉴意义.     

心肌细胞肥大的信号转导通路

心肌肥厚是肥大刺激诱导核内基因异常表达的结果,细胞内信号转导通路是肥大刺激与核内基因转录活化的偶联环节。然而,淡同刺激诱导的心肌肥大可能具有不同的“分子表型”,这主要取决于它们启动的信号转导通路。对心肌肥大信号转导通路的深入认识,不仅胡助于阐明心肌肥厚的细胞分子机制,而且可为药物干预防治心肌肥厚提供新思路。     

CpG island methylation pattern in different human tissues and its correlation with gene expression

The study on DNA methylation pattern in different human tissues attracts increasing interest nowadays, but a systematic analysis of CpG island methylation pattern between both somatic tissues and gametocyte is still lacking. In this work, we analyzed the CpG island methylation data of sperm and other 11 somatic tissues from Human Epigenome Project, and found that the CpG island methylation profiles are highly correlated between somatic tissues, while the methylation profile in sperm is quite distinct. Furthermore, we observed that in the six tissues investigated, there is no obvious correlation between the methylation level of promoter CpG islands and corresponding gene expression across different tissues.     

Culture temperature affects gene expression and metabolic pathways in the 2-methylisoborneol-producing cyanobacterium Pseudanabaena galeata

A volatile metabolite, 2-methylisoborneol (2-MIB), causes an unpleasant taste and odor in tap water. Some filamentous cyanobacteria produce 2-MIB via a two-step biosynthetic pathway: methylation of geranyl diphosphate (GPP) by methyl transferase (GPPMT), followed by the cyclization of methyl-GPP by monoterpene cyclase (MIBS). We isolated the genes encoding GPPMT and MIBS from Pseudanabaena galeata, a filamentous cyanobacterium known to be a major causal organism of 2-MIB production in Japanese lakes. The predicted amino acid sequence showed high similarity with that of Pseudanabaena limnetica (96% identity in GPPMT and 97% identity in MIBS). P. galeata was cultured at different temperatures to examine the effect of growth conditions on the production of 2-MIB and major metabolites. Gas chromatograph–mass spectrometry (GC–MS) measurements showed higher accumulation of 2-MIB at 30 °C than at 4 °C or 20 °C after 24 h of culture. Real-time-RT PCR analysis showed that the expression levels of the genes encoding GPPMT and MIBS decreased at 4 °C and increased at 30 °C, compared with at 20 °C. Furthermore, metabolite analysis showed dramatic changes in primary metabolite concentrations in cyanobacteria grown at different temperatures. The data indicate that changes in carbon flow in the TCA cycle affect 2-MIB biosynthesis at higher temperatures.     

哺乳动物中基因持续表达的策略

人类遗传病的治疗越来越依赖于基因水平上的治疗,但外源基因不能在哺乳动物中持续表达的缺陷严重阻碍了这一手段的快速发展。含有转座子载体的染色体基因组整合,裸露质粒DNA转化到肝脏的压力输送,或是在质粒载体中插入真核基因的顺式作用元件如内含子、3’端非翻译区、EBV序列等,都可以在一定程度上赋于外源基因以长期持续的表达,这些策略对于基因治疗的发展具有重要的意义。 Abstract: Gene therapy holds great promises to a variety of inherited diseases. However, the limitations on extended and consistent foreign gene expression has severely hampered the development of applicable gene therapy approaches. Technologies are reviewed here including transponson integration, biolistic measures that pulse the naked plasmid into living organs, or the integration of eukaryotic cis elements into introns, 3′ untranslated regions, or the integration of the EBV sequences, which could assist in the prolonged gene expression of the introduced foreign genes. These strategies may significantly promote the progresses of gene therapy.     

Nitric oxide-modulated marker gene expression of signal transduction pathways in lung endothelial cells

Nitric oxide (NO) is a signal molecule involved in regulation of physiological and pathophysiological functions of the vascular endothelium such as apoptosis. We examined whether NO-modulates marker gene expression of signal transduction pathways in cultured pulmonary artery endothelial cell (PAEC). Cells were exposed to a NO donor, 1 mM NOC-18, for 0.5, 5, and 24 h, thereafter, expression levels of 96 marker genes associated with 18 signal transduction pathways were assessed using a signal transduction pathway-finder microarray analysis system. NO modulation of apoptotic pathways and nuclear factor (NF) microarray were further analyzed. Gene array analyses revealed that 17 genes in 13 signal pathways were up- or down-regulated in cells exposed to NO, four of which were significantly altered by NO and are associated with apoptotic pathways. Apoptotic pathways resulted in identification of 11 genes in this group. Nuclear factor microarray studies demonstrated that NO-modulated expression of these signal transduction genes was associated with regulation of NF-binding activities. Gel shift analysis verified the effects of NO on DNA-binding activity of NF. These results demonstrated that NO signaling modulates at least 13 signal transduction pathways including apoptosis-related families in PAEC.     

Gene expression patterns in glucose-stimulated podocytes

To explore the mechanisms of podocyte injury under diabetic conditions, we performed an expression profile in glucose-stimulated podocytes. Differential gene expression profiles between conditionally immortalized mouse podocytes cultured in medium containing 5.6 and 30 mM glucose were measured with oligonucleotide microarrays. Of the genes identified, heme oxygenase-1, vascular endothelial growth factor-A, and thrombospondin-1 showed a consistently increased pattern, whereas angiotensin-converting enzyme-2 and peroxisomal proliferator activator receptor-γ were down-regulated. These results were validated using real-time PCR and western blotting in podocytes, and with immunohistochemistry on renal tissues from streptozotocin-induced diabetic rats. Not only is this the first report of gene expression profiling of podocyte injury under diabetic conditions, but the identified genes are promising targets for future diabetes research.     

金针菇单、双核菌丝差异表达基因分析

对金针菇Flammulina velutipes单核菌丝W23的菌丝体以及与L11质配后的双核菌丝H1123菌丝体进行了转录组测序,以本实验室已获得的W23基因组为参考基因组研究两样本间差异基因,并对这些差异基因进行了GO功能和Pathway显著性富集分析。差异基因分析显示,两个样本中共有显著性差异表达的基因3 504个,其中在双核菌丝中上调、下调的基因数分别为2 151和1 353个。研究发现差异表达基因含有很多的转录因子基因、蛋白激酶以及WD40 repeat-like蛋白。Gene Ontology（GO）功能分析结果表明,extracellular region和membrane-enclosed lumen条目下的差异基因全部为上调表达,而envelope下的差异基因全部为下调表达,以利于双核菌丝分裂时锁状联合的形成而便于核的迁移。Pathway 功能富集分析结果表明,脂肪酸、氨基酸以及大部分糖类合成相关基因具有比较活跃的上调表达。说明双核菌丝主要进行营养物质的富集,为下一步在合适条件下分化成原基,进入生殖生长阶段储备物质基础。     

Dynamic models of gene expression and classification

Powerful new methods, like expression profiles using cDNA arrays, have been used to monitor changes in gene expression levels as a result of a variety of metabolic, xenobiotic or pathogenic challenges. This potentially vast quantity of data enables, in principle, the dissection of the complex genetic networks that control the patterns and rhythms of gene expression in the cell. Here we present a general approach to developing dynamic models for analyzing time series of whole genome expression. In this approach, a self-consistent calculation is performed that involves both linear and non-linear response terms for interrelating gene expression levels. This calculation uses singular value decomposition (SVD) not as a statistical tool but as a means of inverting noisy and near-singular matrices. The linear transition matrix that is determined from this calculation can be used to calculate the underlying network reflected in the data. This suggests a direct method of classifying genes according to their place in the resulting network. In addition to providing a means to model such a large multivariate system this approach can be used to reduce the dimensionality of the problem in a rational and consistent way, and suppress the strong noise amplification effects often encountered with expression profile data. Non-linear and higher-order Markov behavior of the network are also determined in this self-consistent method. In data sets from yeast, we calculate the Markov matrix and the gene classes based on the linear-Markov network. These results compare favorably with previously used methods like cluster analysis. Our dynamic method appears to give a broad and general framework for data analysis and modeling of gene expression arrays. Electronic Publication