Molecular Structure of Animal Viruses and Cells

动物病毒和细胞的分子结构

• 批准号: 7048218
• 负责人: james carl barrett
• 金额: --
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7048218
• 关键词: Internet; RNA interference; computational biology; computer assisted sequence analysis; computer human interaction; computer program /software; computer simulation; computer system design /evaluation; messenger RNA; molecular dynamics; nucleic acid sequence; nucleic acid structure; parathyroid hormones; protein structure; protooncogene; statistics /biometry; structural biology; three dimensional imaging /topography; virus RNA

Our research goal emphasizes developing novel, sophisticated algorithms that integrate statistical and computational tools for RNA folding, pattern search, sequence and structure comparison. These tools find non-coding (ncRNAs) and functional RNA elements, and enable analyses of complete genome sequences. Our scientific accomplishments during the past year are summarized as follows:A. Development of computer algorithms for analyses of RNA structures and the discovery of ncRNAs, RNA motifs and RNA functional elements.Functional RNAs have characteristic RNA structural motifs represented by specific combinations of base pairings and conserved nucleotides in loop regions. Discovery of distinct well-ordered structures and their homologues in genome-wide searches will enhance our ability to discover RNA structural motifs and help us to highlight their association with functional ncRNAs and regulatory RNA elements. In collaboration with Prof. Zhang's Lab. (Dept. of Computer Science, Univ. of Western Ontario, London, Ontario, Canada), we developed a novel computer algorithm , HomoStRscan, that takes a single RNA sequence along with its secondary structure to search for homologous RNAs in complete genomes. This novel algorithm differs completely from other currently used search algorithms for homologous structures or structural motifs in two important aspects: first, it takes detailed account of information of both the primary sequence and the secondary structural constraints of the query RNA including each base-pair in duplexes and each nucleotide in the single strands; second, the homologous RNA structures are strictly inferred from a robust statistical distribution of a quantitative measure, maximal similarity score. The method provides a flexible, robust and fine search tool for any homologous structural RNAs. To test this novel program we searched for 5S rRNA and tRNA in bacterial genome databases. Our results from more than 20 bacterial genomes indicate that HomoStRscan discovers these ncRNAs with high sensitivity/specificity ratios. Our computational experiments for these complete genomic sequences indicate that HomoStRscan detects 100% of the true 5S rRNAs with no false positives. Moreover, HomoStRscan finds new 5S rRNA genes in several bacterial genomes that are not currently annotated in the database.HomoStRscan can also discover tRNAs in the genomic sequences with very high sensitivity/specificity ratios, even if those tRNAs have introns. Our test for tRNA genes in K.lactis yeast genome of 10.6 Mb correctly predicts all tRNA genes listed in published databases, and also predicts an additional 31 tRNAs, most of which have intron sequences of various sizes within the anticodon loop.In general, our method can be used to search for any RNA segments that have established secondary structure. The search for ncRNAs is being conducted on a large scale using HomoStRscan and rna_match for known ncRNAs.B. Development of computer programs StemEd and SigStem for the statistical inference of local well-ordered structures in genomic sequences.Discovery of microRNAs (miRNAs)suggests that there are a large class of small non-coding RNAs in eukaryotic genomes. These miRNAs have the potential to form distinct, fold-back, stem-loop structures. The prediction of these well-ordered, folding sequences (WFS) in genomic sequences is very helpful for our understanding of RNA-based gene regulation and the determination of local RNA elements with structure-dependent functions. Previously, we developed EDscan and SigED that have the power to discover such distinct WFS by scanning successive segments along a sequence and evaluating the difference between E_diff of the natural sequence and those computed from randomly shuffled sequences. The measure E_diff of a given RNA segment here is same as was defined in the previous EDscan method, where E_diff is the difference of free energies between the folded global, minimal energy structure in the segment and its corresponding optimal, restrained structure (ORS) where all the previous base pairings in the lowest free energy structure are forbidden. Using a standard z-score, SigZscr, we can estimate the behavior of E_diff in the real biological segment and make a robust statistical inference based on the general behavior of E_diff in the tested random sample. However, the computational complexity of EDscan and SigED is directly proportional to the cube of the scanning window length. Thus it is very compute intensive in searching the whole human genome. Since for miRNAs we are interested in relatively simple, distinct fold-back, stem-loop structures only in the search of those miRNA precursors in the genomic sequence we improved our algorithm to consider only stem-loop structures. Consequently, the new algorithms StemEd and SigStem contain all the power of EDscan and SigED, but the computational complexity was reduced to be directly proportional to the square of the window length. In addition, the predicting ability of the new method is less sensitive to the selection of the scanning window. This is especially advantageous in discovering unknown structural motifs and ncRNAs in genomic sequences.Our results and statistical test from all known miRNA precursors indicate that the statistically significant WFS detected by StemEd and SigStem in genomic sequences are coincident with known fold-back stem-loops found in the miRNA precursors. In statistical tests, we include 207 miRNA precursors of human, 208 of mouse, 187 of rat,121 of G. gallus, 78 of Drosophila melanogaster, 116 of Caenorhabditis elegans, 50 of Caenorhabditis briggsae, 92 of Arabidopsis thaliana and122 miRNA precursors of Oryza sativa.We are continuing the detailed analysis and intend to find distinct well-ordered folding patterns in other species and expect them to be potential miRNAs.C. Data mining of large dsRNA segments and RNA functional elements in sequence databases.Recent developments in the study of RNA silencing indicate that double-stranded RNA (dsRNA) can be used in eukaryotes to block expression of a corresponding cellular gene. In the RNAi pathway, dsRNAs serve as the initial triggers that are chopped by an ribonuclease termed "Dicer" and may result in aberrant mRNA. We search for the stalk-like dsRNAs in the 3'UTR database. The occurrence rate of the dsRNA structures in 3'UTRs ranges from 0.01% in plant to 0.30% in vertebrate mRNAs. These stalk-like dsRNAs are predicted to be very significant in Monte Carlo simulations and are well-determined' in RNA structure predictions. The distinct dsRNA structures in the database can be used to test the hypothesis for the nature of endogenous dsRNAs in the 3'UTR and the possibility that they can induce RNAi. We collaborated on studies of induction and suppression of RNA interference by HIV-1 with Dr. Jeang's Lab. (Mol. Virol. Section, Lab of Mol. Microbio., NIAID, NIH). Our results indicate that although short interfering RNAs have been used artificially to silence viral infections, no direct evidence exists that natural viral sequences provoke such immunity in mammalian cells. Our computation discovers a series of dsRNAs of 19 base-pair sin about 500 HIV and related sequences. The conserved, naturally occurring 19 base-pair dsRNA elicits antiviral RNA interference in human cells. Interestingly, HIV has evolved a suppressor of RNA silencing embodied in its Tat protein to combat this induced RNA interference. And Tat suppresses RNA silencing through a functional abrogation of Dicer activity. Our results suggest it is the pre-processed, short, interfering siRNA, but not processing-requiring long interfering liRNA nor short hairpin shRNA, that should be the preferred consideration for inhibiting HIV-1 infections.

我们的研究目标强调开发新颖、复杂的算法，集成用于 RNA 折叠、模式搜索、序列和结构比较的统计和计算工具。这些工具可查找非编码 (ncRNA) 和功能性 RNA 元件，并能够分析完整的基因组序列。一年来我们的科学成就总结如下： A．开发用于分析 RNA 结构和发现 ncRNA、RNA 基序和 RNA 功能元件的计算机算法。功能性 RNA 具有特征性 RNA 结构基序，由碱基配对和环区域保守核苷酸的特定组合表示。在全基因组搜索中发现独特的有序结构及其同源物将增强我们发现 RNA 结构基序的能力，并帮助我们强调它们与功能性 ncRNA 和调控 RNA 元件的关联。与张教授实验室合作。 （加拿大安大略省伦敦西安大略大学计算机科学系），我们开发了一种新颖的计算机算法 HomoStRscan，它采用单个 RNA 序列及其二级结构来搜索完整基因组中的同源 RNA。这种新颖的算法在两个重要方面与目前使用的其他同源结构或结构基序搜索算法完全不同：首先，它详细考虑了查询RNA的一级序列和二级结构约束信息，包括双链体中的每个碱基对和单链中的每个核苷酸；其次，同源 RNA 结构是从定量测量（最大相似性得分）的稳健统计分布中严格推断出来的。该方法为任何同源结构RNA提供了灵活、稳健和精细的搜索工具。为了测试这个新程序，我们在细菌基因组数据库中搜索了 5S rRNA 和 tRNA。我们对 20 多个细菌基因组的结果表明，HomoStRscan 发现这些 ncRNA 具有高灵敏度/特异性比。我们对这些完整基因组序列的计算实验表明，HomoStRscan 可以检测到 100% 的真实 5S rRNA，没有误报。此外，HomoStRscan 在多个细菌基因组中发现了目前数据库中尚未注释的新 5S rRNA 基因。HomoStRscan 还可以以非常高的灵敏度/特异性比在基因组序列中发现 tRNA，即使这些 tRNA 具有内含子。我们对 10.6 Mb 乳酸克鲁维酵母基因组中 tRNA 基因的测试正确预测了已发表数据库中列出的所有 tRNA 基因，还预测了额外的 31 个 tRNA，其中大多数在反密码子环内具有不同大小的内含子序列。 一般来说，我们的方法可用于搜索任何已建立二级结构的 RNA 片段。使用 HomoStRscan 和 rna_match 对已知的 ncRNA 进行大规模的 ncRNA 搜索。开发计算机程序 StemEd 和 SigStem，用于对基因组序列中局部有序结构进行统计推断。microRNA (miRNA) 的发现表明真核基因组中存在一大类小型非编码 RNA。这些 miRNA 有可能形成独特的、折叠的、茎环结构。预测基因组序列中这些有序的折叠序列（WFS）对于我们理解基于RNA的基因调控以及确定具有结构依赖性功能的局部RNA元件非常有帮助。之前，我们开发了 EDscan 和 SigED，它们能够通过扫描序列上的连续片段并评估自然序列的 E_diff 与根据随机打乱的序列计算出的 E_diff 之间的差异来发现这种不同的 WFS。这里给定 RNA 片段的测量 E_diff 与之前的 EDscan 方法中定义的相同，其中 E_diff 是片段中折叠的全局最小能量结构与其相应的最佳约束结构 (ORS) 之间的自由能差，其中最低自由能结构中的所有先前碱基配对都被禁止。使用标准 z 分数 SigZscr，我们可以估计 E_diff 在真实生物片段中的行为，并根据 E_diff 在测试的随机样本中的一般行为做出稳健的统计推断。然而，EDscan和SigED的计算复杂度与扫描窗口长度的立方成正比。因此，搜索整个人类基因组的计算量非常大。由于对于 miRNA，我们只对相对简单、独特的折返、茎环结构感兴趣，仅在基因组序列中搜索这些 miRNA 前体时，我们改进了算法以仅考虑茎环结构。因此，新算法 StemEd 和 SigStem 包含 EDscan 和 SigED 的所有功能，但计算复杂度降低到与窗口长度的平方成正比。此外，新方法的预测能力对扫描窗口的选择不太敏感。这对于发现基因组序列中未知的结构基序和 ncRNA 特别有利。我们的结果和所有已知 miRNA 前体的统计测试表明，StemEd 和 SigStem 在基因组序列中检测到的统计显着性 WFS 与 miRNA 前体中发现的已知折叠茎环一致。在统计测试中，我们包括207个人类的miRNA前体，208个小鼠的miRNA前体，187个大鼠的miRNA前体，121个G. gallus，78个果蝇的miRNA前体，116个秀丽隐杆线虫的miRNA前体，50个Caenorhabditis briggsae，92个拟南芥的miRNA前体和122个水稻的miRNA前体。我们正在继续详细分析并打算找到不同的 其他物种中有序的折叠模式并期望它们成为潜在的 miRNA。C.序列数据库中大 dsRNA 片段和 RNA 功能元件的数据挖掘。RNA 沉默研究的最新进展表明，双链 RNA (dsRNA) 可用于真核生物中，以阻断相应细胞基因的表达。在 RNAi 途径中，dsRNA 作为初始触发因素，被称为“Dicer”的核糖核酸酶切割，并可能导致异常 mRNA。我们在 3'UTR 数据库中搜索茎状 dsRNA。 3'UTR 中 dsRNA 结构的出现率范围为植物 mRNA 中的 0.01% 到脊椎动物 mRNA 中的 0.30%。这些茎状 dsRNA 预计在蒙特卡罗模拟中非常重要，并且在 RNA 结构预测中具有明确的意义。数据库中不同的 dsRNA 结构可用于检验 3'UTR 中内源 dsRNA 性质的假设以及它们诱导 RNAi 的可能性。我们与Jeang 博士的实验室合作研究了HIV-1 对RNA 干扰的诱导和抑制。 （分子病毒科，分子微生物实验室，NIAID，NIH）。我们的结果表明，尽管短干扰RNA已被人为地用于沉默病毒感染，但没有直接证据表明天然病毒序列在哺乳动物细胞中激发了这种免疫力。我们的计算发现了一系列 19 个碱基对的 dsRNA，涉及约 500 个 HIV 和相关序列。这种保守的、天然存在的 19 个碱基对 dsRNA 可在人体细胞中引发抗病毒 RNA 干扰。有趣的是，HIV 已经进化出一种 RNA 沉默抑制因子，包含在其 Tat 蛋白中，以对抗这种诱导的 RNA 干扰。 Tat 通过功能性消除 Dicer 活性来抑制 RNA 沉默。我们的结果表明，预处理的短干扰 siRNA，而不是需要加工的长干扰 liRNA 或短发夹 shRNA，应该是抑制 HIV-1 感染的首选考虑因素。