pBV220载体中外源基因表达水平定量分析

运用基于螺旋区随机堆积的ＲＮＡ二级结构预测与密码子偏性计算等序列分析技术,分析了ｐＢＶ２２０载体中携带的人白细胞介素２、人白细胞介素４等２２个外源基因的表达水平,结果表明：５‘－３０－３９区域和３’端３０－－３９区域的二级结构有与表达水平具有显的统计学意义;其次是３端９ｂｐ的局部密码子偏性,ＳＤ序列与起始密友子ＡＴＧ之间碱基数在８±３范围内与表达水平无显关系。另外,运用判别分析方法构建了判别函     

RNA二级结构预测系统构建

运用下列RNA二级结构预测算法:碱基最大配对方法、Zuker极小化自由能方法、螺旋区最优堆积、螺旋区随机堆积和所有可能组合方法与基于一级螺旋区的RNA二级结构绘图技术, 构建了RNA二级结构预测系统Rnafold. 另外, 通过随机选取20个tRNA序列, 从自由能和三叶草结构两个方面比较了前4种二级结构预测算法, 并运用t检验方法分析了自由能的统计学差别. 从三叶草结构来看, 以随机堆积方法最好, 其次是螺旋区最优堆积方法和Zuker算法, 以碱基最大配对方法最差. 最后, 分析了两种极小化自由能方法之间的差别.     

银胶中三螺旋RNA poly（rU）．poly（rA）．poly（rU）的付立叶表面增强拉曼光谱研究

采用近红外付上叶拉曼光谱研究了三螺旋ＲＮＡ（ｒＵ）．ｐｏｌｙ（ｒＡ）．ｐｏｌｙ（ｒＵ）在溶液中的构象和在银胶中的表面增强拉曼散射行为。结果表明在溶液中,该三螺旋ＲＮＡ分子中以Ｗａｔｓｏｎ—Ｃｒｉｃｋ碱基配对的两条链处于Ａ－构型,而第二条嘧啶链处于Ｃ２＇－ｅｎｄｏ／ａｎｔｉ构象。在银胶中,该三螺旋ＲＮＡ的表面增强拉曼效应明显。与溶液状态下相比,８３５和８１９ｃｍ－１谱带的出现暗示该三螺旋ＲＮＡ吸附到银胶表面后,该三螺旋ＲＮＡ分子的螺旋结构仍得到保留,且其构象与溶液中的相近。同时该三螺旋ＲＮＡ主要是通过核酸骨架上带负电荷的磷酸基团定位于银胶表面而吸附的。     

固定化枯草杆菌色氨酰tRNA合成酶(英文)

为研究ｔＲＮＡＴｒｐ 与色氨酰ｔＲＮＡ合成酶（ＴｒｐＲＳ） 的相互识别及其结构、功能关系, 纯化了枯草杆菌ＴｒｐＲＳ并用溴化氰活化的Ｓｅｐｈａｒｏｓｅ ４Ｂ 将ＴｒｐＲＳ固定化, 固定化ＴｒｐＲＳ的蛋白质回收率为９５ ．５ ％ , 活力回收率为３１．３％ 。研究了固定化ＴｒｐＲＳ的酶学性质, 其热稳定性和贮存稳定性方面均比液相ＴｒｐＲＳ有了较大的提高, 最适温度、最适ｐＨ 均有一定程度的增大, 工作稳定性良好。以固定化ＴｒｐＲＳ为亲和层析介质, 对含有２０ 个核苷酸随机序列、长度为５６ 个核苷酸的单链ＲＮＡ 随机库进行了３ 轮筛选,ＲＮＡ 群体亲和固定化ＴｒｐＲＳ的比例从４ ．３ ％ 上升至１４ ．７ ％ 。筛选得到了与ｔＲＮＡＴｒｐ 氨基酸接受茎类似的ＲＮＡ二级结构。实验结果表明固定化ＴｒｐＲＳ可以作为ＳＥＬＥＸ 亲和层析介质, 进行模拟ｔＲＮＡＴｒｐ 分子的ＲＮＡ 随机库的ＳＥＬＥＸ 筛选。     

蓖麻蚕核糖体大亚基RNA基因3‘—端序列分析及进化研究

测定了蓖麻蚕核糖体大亚基ＲＮＡ编码区３’－端ＤＮＡ序列,分析了其二级结构,并与昆虫伊蚊、果蝇;线虫;脊椎动物人、小鼠、爪蟾;低等脊索动物海鞘以及真菌酵母、毛霉相应的保守区段进行了同源比较。邻接法分析表明,昆虫核糖体大亚基ＲＮＡ在进化上与５ＳｒＲＮＡ相似,有加快的趋势。     

酿酒酵母中的RNA解旋酶

ＲＮＡ解旋酶是一类能解开双链ＲＮＡ的酶 ,存在于所有生物体中 ,其家族成员在进化上具有保守序列。ＲＮＡ解旋酶属于分子伴侣 ,对于确保ＲＮＡ分子的正确折叠以及保持和修饰其特定的二级、三级结构必不可少。在核转录、前体ｍＲＮＡ剪接、核糖体生物发生、核质转运、翻译、ＲＮＡ降解以及结构基因表达等过程中ＲＮＡ解旋酶都发挥了一定的作用。1 .解旋酶的结构ＲＮＡ解旋酶大部分属于蛋白质超家族Ⅱ (ＳＦⅡ ) ,包含七个保守序列 (图 1 ) [1] 。除核心区域外 ,多数ＲＮＡ解旋酶具有不同的Ｎ末端和Ｃ末端部分 ,可能与底物专一性有关。目前 ,…     

银胶中三螺旋RNA poly（rU）．poly（rA）．poly（rU）的付立叶表面增强拉曼光谱研究

采用近红外付立叶拉曼光谱研究了三螺旋ＲＮＡ（ｒＵ）．ｐｏｌｙ（ｒＡ）．ｐｏｌｙ（ｒＵ）在溶液中的构象和在银胶中的表面增强拉曼散行为。结果表明在溶液中,该三螺旋ＲＮＡ分子中以Ｗａｔｓｏｎ－Ｃｒｉｃｋ碱基酸对的两条链处于Ａ－构型,而第二条嘧啶链处于Ｃ２’－ｅｎｄｏ／ａｎｔｉ构象。在银胶中,该三螺旋ＲＮＡ的表面增强拦曼效应明显。与溶液状态下相比,８３５和８１９ｃｍ＾－１谱带的出现暗示该三螺旋ＲＮＡ吸附到     

tPA K_2编码区mRNA二级结构对其在大肠杆菌中表达的影响研究

序列分析中发现ｔＰＡＫ２编码区结构基因中存在一段反转重复序列,富含Ｇ、Ｃ。利用计算机预测ｔＰＡｍＲＮＡ二级结构证明ｔＰＡｍＲＮＡ在此处可以形成△Ｇｍ＝－２５．５ＫＣａｌ／ｍｏｌ的发夹结构。本研究利用定点突变技术消除了这段反转重复序列,在大肠杆菌中进行了消除前后ｔＰＡ转录和翻译水平的比较。结果表明消除之后,细菌总ＲＮＡ中ｔＰＡ特异ｍＲＮＡ含量减少,细菌表达产物中ｔＰＡ蛋白占破菌沉淀物的百分比却基本不变。提示大肠杆菌中基因编码区ｍＲＮＡ二级结构一般不构成转录的终止,但有利于ｍＲＮＡ的稳定性,对翻译表达无影响。     

优化外源基因在大肠杆菌中表达的翻译起始率的策略和方法(英文)

ｍＲＮＡ的翻译起始区（ＴＩＲ）的二级结构对翻译起始率有很大的影响。本文建立了一种改进外源基因在大肠杆菌中翻译起始率的系统。以人分裂细胞核抗原（ＰＣＮＡ）基因为模型,将ＰＣＮＡ基因５′端编码区的１１４ｂｐ的顺序插入质粒ｐＴＺ１９Ｒ中ＬａｃＺ′的５′端构成融合基因。用定点突变法在ＰＣＮＡ的ＡＵＧ的８位插入一个Ｓｈｉｎｅ／Ｄａｌｇａｒｎｏ（ＳＤ）顺序ＧＡＧＧＴ,再以合成的带部分随机序列寡核苷酸作引物,用ＰＣＲ法在ＳＤ顺序两侧,即ＳＤ上游６个碱基和ＳＤ与ＡＵＧ之间７个碱基,进行随机突变,它们与结构基因５′端序列形成各种可能的翻译起始区（ＴＩＲ）二级结构。重组质粒转化大肠杆菌株ＪＭ１０９（ＤＥ３）,５′ＰＣＮＡ－ｌａｃＺ′ｍＲＮＡ可通过诱导表达Ｔ７ＲＮＡ聚合酶而得到专一而有效的转录。通过在Ｘ－ｇａｌ板上蓝色筛选以及随后的杂交鉴定,共得到２６９个５′ＰＣＮＡ－ｌａｃＺ′融合质粒。从中选择８个不同蓝色的重组子进行β－ｇａｌ活性测定,结果表明它们的酶活性相差在２０倍以上。而ＲＮＡ点杂交表明它们在转录水平无明显的差异。由此提示,通过此策略和方法能得到一个在大肠杆菌中能高效表达的翻译起始区。     

cDNA克隆p14－6肿瘤抑制功能的分子机制

本文探讨了具有肿瘤抑制功能的ｃＤＮＡ克隆Ｐ１４－６（即人白细胞介素６核转录因子ＮＦ－ＩＬ６的３’非翻译区）的ＲＮＡ转录物与回复相关蛋白ＢＮＦ的相互作用,发现该ＲＮＡ与ＢＮＦ的相互作用位点为其３’侧的富Ｕ序列内的１个２４核苷酸片段;并发现ＢＮＦ系一群蛋白质,它们可能先相互结合成１个蛋白质复合物,然后再与ＲＮＡ位点作用．其中可能只有１个蛋白质（Ｒ６２）直接与该ＲＮＡ结合。     

Analysis of Four-Way Junctions in RNA Structures

RNA secondary structures can be divided into helical regions composed of canonical Watson-Crick and related base pairs, as well as single-stranded regions such as hairpin loops, internal loops, and junctions. These elements function as building blocks in the design of diverse RNA molecules with various fundamental functions in the cell. To better understand the intricate architecture of three-dimensional (3D) RNAs, we analyze existing RNA four-way junctions in terms of base-pair interactions and 3D configurations. Specifically, we identify nine broad junction families according to coaxial stacking patterns and helical configurations. We find that helices within junctions tend to arrange in roughly parallel and perpendicular patterns and stabilize their conformations using common tertiary motifs such as coaxial stacking, loop-helix interaction, and helix packing interaction. Our analysis also reveals a number of highly conserved base-pair interaction patterns and novel tertiary motifs such as A-minor-coaxial stacking combinations and sarcin/ricin motif variants. Such analyses of RNA building blocks can ultimately help in the difficult task of RNA 3D structure prediction.     

Prediction of RNA secondary structure based on helical regions distribution

MOTIVATION: RNAs play an important role in many biological processes and knowing their structure is important in understanding their function. Due to difficulties in the experimental determination of RNA secondary structure, the methods of theoretical prediction for known sequences are often used. Although many different algorithms for such predictions have been developed, this problem has not yet been solved. It is thus necessary to develop new methods for predicting RNA secondary structure. The most-used at present is Zuker's algorithm which can be used to determine the minimum free energy secondary structure. However many RNA secondary structures verified by experiments are not consistent with the minimum free energy secondary structures. In order to solve this problem, a method used to search a group of secondary structures whose free energy is close to the global minimum free energy was developed by Zuker in 1989. When considering a group of secondary structures, if there is no experimental data, we cannot tell which one is better than the others. This case also occurs in combinatorial and heuristic methods. These two kinds of methods have several weaknesses. Here we show how the central limit theorem can be used to solve these problems. RESULTS: An algorithm for predicting RNA secondary structure based on helical regions distribution is presented, which can be used to find the most probable secondary structure for a given RNA sequence. It consists of three steps. First, list all possible helical regions. Second, according to central limit theorem, estimate the occurrence probability of every helical region based on the Monte Carlo simulation. Third, add the helical region with the biggest probability to the current structure and eliminate the helical regions incompatible with the current structure. The above processes can be repeated until no more helical regions can be added. Take the current structure as the final RNA secondary structure. In order to demonstrate the confidence of the program, a test on three RNA sequences: tRNAPhe, Pre-tRNATyr, and Tetrahymena ribosomal RNA intervening sequence, is performed. AVAILABILITY: The program is written in Turbo Pascal 7.0. The source code is available upon request. CONTACT: Wujj@nic.bmi.ac.cn or Liwj@mail.bmi.ac.cn      

Refined secondary structure models for the 16S and 23S ribosomal RNA of Escherichia coli

The complete range of published sequences for ribosomal RNA (or rDNA), totalling well over 50,000 bases, has been used to derive refined models for the secondary structures of both 16S and 23S RNA from E. coli. Particular attention has been paid to resolving the differences between the various published secondary structures for these molecules. The structures are described in terms of 133 helical regions (45 for 16S RNA and 88 for 23S RNA). Of these, approximately 20 are still tentative or unconfirmed. A further 20 represent helical regions which definitely exist, but where the detailed base-pairing is still open to discussion. Over 90 of the helical regions are however now precisely established, at least to within one or two base pairs.     

A unique secondary folding pattern for 5S RNA corresponds to the lowest energy homologous secondary structure in 17 different prokaryotes.

A general secondary structure is proposed for the 5S RNA of prokaryotic ribosomes, based on helical energy filtering calculations. We have considered all secondary structures that are common to 17 different prokaryotic 5S RNAs and for each 5S sequence calculated the (global) minimum energy secondary structure (300,000 common structures are possible for each sequence). The 17 different minimum energy secondary structures all correspond, with minor differences, to a single, secondary structure model. This is strong evidence that this general 5S folding pattern corresponds to the secondary structure of the functional 5S rRNA. The general 5S secondary structure is forked and in analogy with the cloverleaf of tRNA is named the "wishbone" model. It constant 8 double helical regions; one in the stem, four in the first, or constant arm, and three in the second arm. Four of these double helical regions are present in a model earlier proposed (1) and four additional regions not proposed by them are presented here. In the minimum energy general structure, the four helices in the constant arm are exactly 15 nucleotide pairs long. These helices are stacked in the sequences from gram-positive bacteria and probably stacked in gram-negative sequences as well. In sequences from gram-positive bacteria the length of the constant arm is maintained at 15 stacked pairs by an unusual minimum energy interaction involving a C26-G57 base pair intercalated between two adjacent helical regions.     

G.U base pairing motifs in ribosomal RNA.

An increasing number of recognition mechanisms in RNA are found to involve G.U base pairs. In order to detect new functional sites of this type, we exhaustively analyzed the sequence alignments and secondary structures of eubacterial and chloroplast 16S and 23S rRNA, seeking positions with high levels of G.U pairs. Approximately 120 such sites were identified and classified according to their secondary structure and sequence environment. Overall biases in the distribution of G.U pairs are consistent with previously proposed structural rules: the side of the wobble pair that is subject to a loss of stacking is preferentially exposed to a secondary structure loop, where stacking is not as essential as in helical regions. However, multiple sites violate these rules and display highly conserved G.U pairs in orientations that could cause severe stacking problems. In addition, three motifs displaying a conserved G.U pair in a specific sequence/structure environment occur at an unusually high frequency. These motifs, of which two had not been reported before, involve sequences 5''UG3'' 3''GA5'' and 5''UG3'' 3''GU5'', as well as G.U pairs flanked by a bulge loop 3'' of U. The possible structures and functions of these recurrent motifs are discussed.     

No evidence that mRNAs have lower folding free energies than random sequences with the same dinucleotide distribution

This work investigates whether mRNA has a lower estimated folding free energy than random sequences. The free energy estimates are calculated by the mfold program for prediction of RNA secondary structures. For a set of 46 mRNAs it is shown that the predicted free energy is not significantly different from random sequences with the same dinucleotide distribution. For random sequences with the same mononucleotide distribution it has previously been shown that the native mRNA sequences have a lower predicted free energy, which indicates a more stable structure than random sequences. However, dinucleotide content is important when assessing the significance of predicted free energy as the physical stability of RNA secondary structure is known to depend on dinucleotide base stacking energies. Even known RNA secondary structures, like tRNAs, can be shown to have predicted free energies indistinguishable from randomized sequences. This suggests that the predicted free energy is not always a good determinant for RNA folding.     

Predicting coaxial helical stacking in RNA junctions

RNA junctions are important structural elements that form when three or more helices come together in space in the tertiary structures of RNA molecules. Determining their structural configuration is important for predicting RNA 3D structure. We introduce a computational method to predict, at the secondary structure level, the coaxial helical stacking arrangement in junctions, as well as classify the junction topology. Our approach uses a data mining approach known as random forests, which relies on a set of decision trees trained using length, sequence and other variables specified for any given junction. The resulting protocol predicts coaxial stacking within three- and four-way junctions with an accuracy of 81% and 77%, respectively; the accuracy increases to 83% and 87%, respectively, when knowledge from the junction family type is included. Coaxial stacking predictions for the five to ten-way junctions are less accurate (60%) due to sparse data available for training. Additionally, our application predicts the junction family with an accuracy of 85% for three-way junctions and 74% for four-way junctions. Comparisons with other methods, as well applications to unsolved RNAs, are also presented. The web server Junction-Explorer to predict junction topologies is freely available at: http://bioinformatics.njit.edu/junction.     

Circular dichroism of double-helical oligoribonucleotides

The ultraviolet circular dichroism and absorption of 15 double-stranded helical oligoribonucleotides have been measured. These molecules of chain-length 6 to 12 contain all 10 possible nearest neighbors of Watson-Crick base pairs. They are thus good models for short double-stranded regions in RNA molecules. The contribution to the circular dichroism of each of the nearest neighbor base pairs has been obtained. The circular dichroism is found to be very sequence-dependent and may be useful in distinguishing possible secondary structures. However, the nearest neighbor approximation for circular dichroism fails to give a quantitative measure of the circular dichroism of double-strand regions.