＜正＞Background:The small nematode Caenorhabditis elegans（C.elegans）is an excellent model organism for studying ...
Hai-ning Zhang1,Zheng-xing Wu 1,An-lian Qu 1,Tao Xu 2 1 Huazhong University of Science and Technology,Wuhan 430074,P.R.China 2 Institute of Biophysics,Chinese Academy of Sciences,Beijing 100101,P.R.China
What is the relationship between the topological connections among enzymes and their functions during metabolic network evolution? Does this relationship show similarity among closely related or-ganisms? Here we investigated the relationship between enzyme connectivity and functions in meta-bolic networks of chloroplast and its endosymbiotic ancestor, cyanobacteria (Synechococcus sp. WH8102). Also several other species, including E. coli, Arabidopsis thaliana and Cyanidioschyzon merolae, were used for the comparison. We found that the average connectivity among different func-tional pathways and enzyme classifications (EC) was different in all the species examined. However, the average connectivity of enzymes in the same functional classification was quite similar between chloroplast and one representative of cyanobacteria, syw. In addition, the enzymes in the highly con-served modules between chloroplast and syw, such as amino acid metabolism, were highly connected compared with other modules. We also discovered that the isozymes of chloroplast and syw often had higher connectivity, corresponded to primary metabolism and also existed in conserved module. In conclusion, despite the drastic re-organization of metabolism in chloroplast during endosymbiosis, the relationship between network topology and functions is very similar between chloroplast and its pre-cursor cyanobacteria, which demonstrates that the relationship may be used as an indicator of the closeness in evolution.
Organism development is a systems level process. It has benefited greatly from the recent technological advances in the field of systems biology. DNA microarray, phenome, interactome and transcriptome mapping, the new generation of deep sequencing technologies, and faster and better computational and modeling approaches have opened new frontiers for both systems biologists and developmental biologists to reexamine the old developmental biology questions, such as pattern formation, and to tackle new problems, such as stem cell reprogramming. As showcased in the International Developmental Systems Biology Symposium organized by Chinese Academy of Sciences, developmental systems biology is flourishing in many perspectives, from the evolution of developmental systems, to the underlying genetic and molecular pathways and networks, to the genomic, epigenomic and noncoding levels, to the computational analysis and modeling. We believe that the field will continue to reap rewards into the future with these new approaches.
Jing-Dong J. HanYi LiuHuiling XueKai XiaHong YuShanshan ZhuZhang ChenWei ZhangZheng HuangChunyu JinBo XianJing LiLei HouYixing HanChaoqun NiuTimothy C. Alcon
Dear Editor, Eukaryotic transcriptional regulation networks are extremely complex. Usually, multiple transcription factors (TFs) bind to the promoter region of a gene and cooperate to control gene expression precisely. Identifying cooperative TFs remains a major challenge in modem biological research. Various types of data, including genomic sequences, expression profiles, ChiP-chip data and protein-protein interactions, have been used to identify mechanisms of cooperative transcriptional regulation.
