The V(D)J recombination signal sequence and kappa B binding protein Rc binds DNA as dimers and forms multimeric structures with its DNA ligands.

The murine DNA binding protein Rc binds to the heptamer motif of the V(D)J recombination signal sequences and to the kappa B motif of the immunoglobulin enhancer. Bacterial fusion proteins for Rc and DNA ligands of Rc form multiple protein-DNA complexes in electrophoretic mobility shift assays (EMSA). Large complexes formation is favored by an increased Rc concentration. In order to determine the architecture of these complexes, the apparent molecular weights of the protein-DNA complexes were first determined by their gel mobilities. The data suggest that Rc binds to its DNA ligands as dimers, tetramers, and multiples of tetramers. The inference that Rc binds DNA as dimers was substantiated by the formation of chimeric complexes when two electrophoretically distinguishable Rc proteins were employed in EMSA. Methylation interference experiments show that there are no contiguous protein binding sites evident in the DNA of the larger complexes. Apparently, multimerization occurs via protein-protein interactions. Such interaction was demonstrated by the formation of Rc dimers and tetramers in a chemical crosslinking experiment. Significantly, the multimerization of DNA-bound Rc could be involved in bringing the variable region gene segments together for the somatic V(D)J recombination.     

一种结合SELEX与二代测序技术筛选RNA结合蛋白特异识别序列新方法的建立

RNA结合蛋白通过特异识别RNA底物发挥重要的生物学作用。指数富集的配体系统进化(Systematic evolution of ligands by exponential enrichment,SELEX)技术是一种体外筛选核酸底物的基本方法,SELEX技术通过重复多轮筛选从随机核酸序列库中筛选出特异性与靶物质高度亲和的核酸底物,本研究将利用该技术与二代高通量测序(NGS)相结合,体外合成含有20个随机碱基的RNA文库,将所要研究的蛋白构建到带有可被链亲和酶素磁珠捕获的SBP标记的载体上去,显著提高筛选效率,仅需1轮筛选即可获得所需RNA底物motif。通过该方法获得了人的hn RNP A1的UP1结构域特异识别AGG和AG二种RNA序列,并通过EMSA实验证实其可以与获得的RNA motif结合。这一方法的建立对于研究RNA结合蛋白识别底物的序列特异性,并进一步了解其在生物体内的调控机制有重要意义。     

Cyclophilin A binds to linear peptide motifs containing a consensus that is present in many human proteins

Cyclophilin A (CypA) is a peptidyl-prolyl cis/trans-isomerase that is involved in multiple signaling events of eukaryotic cells. It might either act as a catalyst for prolyl bond isomerization, or it can form stoichiometric complexes with target proteins. We have investigated the linear sequence recognition code for CypA by phage display and found the consensus motif FGPXLp to be selected after five rounds of panning. The peptide FGPDLPAGD showed inhibition of the isomerase reaction and NMR chemical shift mapping experiments highlight the CypA interaction epitope. Ligand docking suggests that the peptide was able to bind to CypA in the cis- and trans-conformation. Protein Data Bank searches reveal that many human proteins contain the consensus motif, and several of these protein motifs are shown to interact with CypA in vitro. These sequences represent putative target sites for binding of CypA to intracellular proteins.     

酵母核糖体蛋白基因组合转录调控位点统计分析

真核基因的转录调控是后基因组时代研究的主要问题之一,其基础是认识DNA上转录因子结合位点(模体)及分布状况。基于马尔可夫链模型对酵母核糖体蛋白基因上游启动子序列中模体出现次数进行统计,利用Z-score统计量抽提出过表达和低表达的模体,其中95%的模体与实验得到的转录因子结合位点相符合。然后将抽提出的模体两两配对,通过与背景序列比较,找出酵母核糖体蛋白基因中出现概率及距离分布均具有统计显著性的模体对,这些非随机出现的模体对具有潜在的组合转录调控功能,其中一些模体对的组合调控作用已有实验支持。对提取出的模体对在序列中的位置分布进行分析,发现近94%的模体对位于转录起始位点上游,超过半数的模体对两模体之间的最短距离在0～100bp之间,距离小于30bp的模体对接近30%,这样的短距离间隔有利于两模体的相同作用。这些结果将有助于对酵母核糖体蛋白基因转录调控机制的深入认识。     

Structure-based prediction of DNA target sites by regulatory proteins

Regulatory proteins play a critical role in controlling complex spatial and temporal patterns of gene expression in higher organism, by recognizing multiple DNA sequences and regulating multiple target genes. Increasing amounts of structural data on the protein-DNA complex provides clues for the mechanism of target recognition by regulatory proteins. The analyses of the propensities of base-amino acid interactions observed in those structural data show that there is no one-to-one correspondence in the interaction, but clear preferences exist. On the other hand, the analysis of spatial distribution of amino acids around bases shows that even those amino acids with strong base preference such as Arg with G are distributed in a wide space around bases. Thus, amino acids with many different geometries can form a similar type of interaction with bases. The redundancy and structural flexibility in the interaction suggest that there are no simple rules in the sequence recognition, and its prediction is not straightforward. However, the spatial distributions of amino acids around bases indicate a possibility that the structural data can be used to derive empirical interaction potentials between amino acids and bases. Such information extracted from structural databases has been successfully used to predict amino acid sequences that fold into particular protein structures. We surmised that the structures of protein-DNA complexes could be used to predict DNA target sites for regulatory proteins, because determining DNA sequences that bind to a particular protein structure should be similar to finding amino acid sequences that fold into a particular structure. Here we demonstrate that the structural data can be used to predict DNA target sequences for regulatory proteins. Pairwise potentials that determine the interaction between bases and amino acids were empirically derived from the structural data. These potentials were then used to examine the compatibility between DNA sequences and the protein-DNA complex structure in a combinatorial "threading" procedure. We applied this strategy to the structures of protein-DNA complexes to predict DNA binding sites recognized by regulatory proteins. To test the applicability of this method in target-site prediction, we examined the effects of cognate and noncognate binding, cooperative binding, and DNA deformation on the binding specificity, and predicted binding sites in real promoters and compared with experimental data. These results show that target binding sites for several regulatory proteins are successfully predicted, and our data suggest that this method can serve as a powerful tool for predicting multiple target sites and target genes for regulatory proteins.