不同地理种群鳄蜥tlr4基因遗传多样性及SNPs分布特点分析

Toll样受体(TLRs)是一类识别病原体中高度保守的病原相关分子模式(PAMPs)的蛋白家族,在启动先天性免疫中具有重要作用。人类toll样受体4基因(toll4)的点突变与许多疾病有关,如呼吸道合胞病毒感染、动脉粥样硬化、疟疾等,并且这种点突变往往具有种族分布特异性。鳄蜥(Shinisaurus crocodilurus)是一种古老的爬行动物,属于国家Ⅰ级保护野生动物,由于其遭受非法捕杀、栖息地破坏等人为干扰,目前数量极其稀少。近年来,鳄蜥因疾病造成大量的死亡,且这种疾病的分布具有种群差异性,不同种群往往疾病症状也不同,可能是因不同的病原体感染引起的。我们设想toll4基因的点突变在鳄蜥种群之间可能具有分布的差异性,以适应不同的当地病原体。因此,本文利用PCR产物直接测序和生物信息学分析法初步探索鳄蜥toll4基因的遗传多样性以及单核苷酸多态性(SNPs)的分布特点,验证该基因的点突变是否具有种群特异性分布特点,以及预测其氨基酸替换是否对蛋白质结构和功能产生影响。结果获得的扩增片段长为1 694 bp,在5个种群52条序列中(登录号MN380726～MN380777),共发现27个突变位点,导致9个氨基酸替换,其中3个氨基酸替换被预测为影响蛋白质的结构和功能。27个点突变中有12个只分布在单个种群,4个分布无种群特异性,即每个种群中均有野生型和突变型,其余11个点突变的突变型分布在2或3个种群不等。研究表明,鳄蜥toll4基因遗传多态性在各种群间不一致,且点突变具有种群特异性分布特征,反映不同地理种群遭受不同的病原压力。     

乙型肝炎病毒X蛋白的优势氨基酸序列与热点突变位点的生物信息学分析

乙型肝炎病毒X蛋白(hepatitis B virus X protein,HBx)全长154个氨基酸,与肝癌发生密切相关.为确定HBx的优势氨基酸序列和热点突变位点,在GenBank中下载所有HBx的氨基酸序列13950条,剔除插入突变、缺失突变和起始密码子非甲硫氨酸的序列,最后保留7126条.通过分析这7126条序列,计算出HBx每个位点的氨基酸分布情况,出现频率最高的氨基酸为该位点的优势氨基酸,其他氨基酸为突变氨基酸.154个位点的优势氨基酸组成HBx优势氨基酸序列.突变率>10.0%的热点突变位点有32个.其中第36、42、44、87、88和127位氨基酸有4种(突变率>1.0%)以上突变形式,具有较高的多态性.与肝癌密切相关的K130M/V131I双突变率为34.7%.通过7126条HBx序列与优势序列的同源性比较,随机选出其中50条序列(2条与优势序列同源性<75%,48条同源性为76%~99%),与23条参考序列及优势序列共同构建系统发生树.结果显示,HBx优势氨基酸序列属于基因型C,这与基因型C为全球主要流行型一致.本研究首次系统性分析了GenBank中HBx的优势序列,确定了32个HBx热点突变位点和6个多态性较高的位点,为基于HBx突变的基础和应用研究奠定了基础.     

南宁市HIV-1/AIDS人群治疗前pol区遗传特性及蛋白结构分析

为探讨南宁市某县艾滋病病毒1型(HIV-1)感染人群中治疗前pol区遗传特性及蛋白结构变化情况,本研究通过RT-PCR扩增pol区部分序列并进行测序,将序列同源比对构建系统进化树;分型确定毒株亚型和斯坦福大学HIV耐药性数据库比对,分析耐药相关位点;SWISS-MODEL蛋白质同源数据库进行建模分析氨基酸的突变对蛋白质结构和功能的影响。本研究在90份HIV-1标本中获得46个pol区有效序列,共发现4种亚型,其中CRF01_AE占76.08%(35/46)、CRF08_BC占15.22%(7/46)、CRF07_BC占(3/46)6.52%、CRF59_01B1占2.17%(1/46);46个序列中有4例(8.69%)出现耐药突变位点,没有针对核苷酸反转录酶抑制剂(NRTI)的耐药突变;针对蛋白酶类抑制剂(PIs)1例,PR蛋白酶的柔性部位I47V位点发生突变,β折叠结构的I84V位点发生突变,都是异亮氨酸突变为缬氨酸;针对非核苷酸反转录酶抑制剂(NNRTI)有3例,2例位于活性中心的Y181C位点由酪氨酸突变为半胱氨酸,1例位于转角处的E138G位点由谷氨酸突变为甘氨酸。研究表明,南宁市某县HIV-1病毒CRF01_AE重组亚型比例最大,未经抗病毒治疗HIV1感染者中已经出现pol区耐药突变株,突变位点主要位于活性中心及柔性部位,传播水平已经处于中等流行状态。深入分析蛋白质与抑制剂相互作用机制,有助于为艾滋病抗病毒及耐药性监测方案提供科学依据。     

禽流感病毒血凝素HA的可变性解析

以重组的蒙古鸭H5N2禽流感病毒A/Duck/Mongolia/54/01的血凝素HA蛋白的cDNA为模板,进行PCR随机突变,表达只有单个氨基酸突变的H5HA基因共计38个.根据红细胞吸附反应,分析这些突变HA的功能,仍然具有红细胞吸附活性的单个氨基酸突变的HA约占89%,说明H5HA单个氨基酸突变的容许率是相当高的.HA1区突变数目大约是HA2区的两倍.对失去红细胞吸附功能和某些仍然拥有红细胞吸附功能的HA及单个氨基酸突变的位置与结构的关系进行探讨.有两个位点氨基酸突变了两次,但都不影响红细胞吸附功能,对红细胞吸附功能的影响,似乎主要由位置决定,而不是取决于取代的氨基酸的种类.位点179位和122位的突变是不允许的;位点179位于H5N1的受体结合区域RBD内,122位位于A抗原决定簇区附近,推测在H5HA三维结构上,这两个位点位于HA分子的内部,维持着H5HA的结构.HA1Cys位点4和HA2Cys位点148的突变是不允许的.这两个Cys正好形成HA1和HA2连接的桥梁,对维持H5HA结构也是相当重要的.本实验中HA先后失去了三个糖基化位点,但并不影响吸附红细胞的功能.总之,通过实验分析以研究某些氨基酸改变的效果,寻找关键位点是否突变,可以作为评估H5N1野毒株大流行潜力的分子标志.     

重组人淋巴毒素随机点突变组合文库的构建

构建重组人淋巴毒素（rhLT）随机点突变组合文库以进行体外分子进化及结构和功能的研究。应用含随机核苷酸序列的引物,通过Overlap PCR的方法分别对rhLT 的46、106和130位氨基酸进行定点随机突变,获得各单点随机突变体库。通过基因操作将这三个单点随机突变体库拼接并克隆于Pmd_18T载体建立三点组合突变体文库,DNA测序鉴定突变位点的随机性和多样性,原核表达该变异体库,体外测定生物学活性。成功获得rhLT三点随机点突变组合文库,其转化克隆数达到1.5×10⁵,是多样性理论值的4.5倍。50个样品的序列分析显示各个位点的核苷酸和氨基酸序列的突变都呈随机性分布。对原核表达的30个样品进行生物学活性测定,结果70%(21个)的样品无活性、23.3%(7个)的样品活性低于rhLT、6.7%(2个)的样品活性高于rhLT。成功构建了rhLT随机点突变组合文库,该库不仅在一级结构上具有良好的随机性和多样性,而且具有生物学活性的多样性,为应用噬菌体展示等高通量筛选策略对淋巴毒素进行体外分子进化和结构与功能的深入研究打下了基础。     

一种快速构建基因多个点突变体方法的建立

蛋白质内部多个位点的翻译后修饰在基因的功能调节过程中发挥重要作用,基因的点突变体在其结构和功能研究中发挥非常关键的作用,因此,高效、快速构建基因的多个点突变体在基因的功能研究中意义重大．本研究在建立了对目的基因进行高效准确的单点突变方法的基础上,以SRrp53点突变体的构建为例,设计了新型的以反向PCR为基础的多个点突变的实验流程,获得的多位点突变体质粒经测序后均与预期相符,将测序正确的多位点突变体质粒转染293T细胞后,均表达了分子质量正确的蛋白质．以上结果表明,该实验设计方案能够高效、方便地用于基因多个点突变体的构建,为进一步研究它们的分子功能打下了基础．     

PSS定点突变及酶活研究

磷脂酰丝氨酸可在磷脂酰丝氨酸合成酶(PSS)催化下由磷脂酰胆碱和L-丝氨酸生成。通过生物信息学手段对磷脂酰丝氨酸合成酶蛋白质结构进行解析和研究分析,获得2个可突变位点F139和P272,通过Overlap PCR法进行定点突变,测定突变序列,并进行酶活测定。结果显示,PSS位点F139突变为L139、M139,位点P272突变为A272,能提高酶活力,说明蛋白质结构解析结合氨基酸定点突变技术,可以改善重组酶的活力。     

用DREAM技术进行全长质粒快速定点突变

利用“设计限制酶辅助突变”(Designed Restriction Enzyme Assisted Mutagenesis, DREAM)进行全长质粒快速定点突变。根据突变位点附近氨基酸靶序列, 以简并密码子进行逆向推导, 这样在不改变氨基酸序列的前提下可以得到数目巨大的隐性突变体(Silent mutants), 这些突变体中包含大量的限制性酶切位点, 选择合适的酶切位点设计引物, 用Phusion超保真DNA聚合酶扩增全长质粒的DNA序列, 得到的PCR产物用T4多聚核苷酸激酶添加5￠磷酸基团后进行平末端连接, 转化大肠杆菌受体菌后用设计的酶切位点进行快速筛选。本研究用该方法成功地纠正了长约8 kb的质粒pcDNA3.1-pIgR中的突变碱基, 从而获得了多聚免疫球蛋白受体(pIgR)的野生型氨基酸序列。以上结果表明: 利用DREAM技术将限制性酶切位点引入目的基因而不改变目的蛋白质的氨基酸序列, 使突变体的筛选简单化; 配合使用高保真和高效率的Phusion DNA聚合酶可以进行长达8 kb的全长质粒的快速突变; 该方法无需使用定点突变试剂盒和特殊的受体菌, 同时避免了核酸杂交以及同位素的使用。     

乙型肝炎病毒Ⅹ蛋白的优势氨基酸序列与热点突变位点的生物信息学分析

乙型肝炎病毒X蛋白(hepatitis B virus X protein,HBx)全长154个氨基酸,与肝癌发生密切相关。为确定HBx的优势氨基酸序列和热点突变位点,在GenBank中下载所有HBx的氨基酸序列13 950条,剔除插入突变、缺失突变和起始密码子非甲硫氨酸的序列,最后保留7 126条。通过分析这7 126条序列,计算出HBx每个位点的氨基酸分布情况,出现频率最高的氨基酸为该位点的优势氨基酸,其他氨基酸为突变氨基酸。154个位点的优势氨基酸组成HBx优势氨基酸序列。突变率10.0%的热点突变位点有32个。其中第36、42、44、87、88和127位氨基酸有4种(突变率1.0%)以上突变形式,具有较高的多态性。与肝癌密切相关的K130M/V131I双突变率为34.7%。通过7 126条HBx序列与优势序列的同源性比较,随机选出其中50条序列(2条与优势序列同源性75%,48条同源性为76%~99%),与23条参考序列及优势序列共同构建系统发生树。结果显示,HBx优势氨基酸序列属于基因型C,这与基因型C为全球主要流行型一致。本研究首次系统性分析了GenBank中HBx的优势序列,确定了32个HBx热点突变位点和6个多态性较高的位点,为基于HBx突变的基础和应用研究奠定了基础。     

红纹黄单胞菌a-氨基酸酯水解酶的克隆、序列分析及热稳定性提高

【目的】克隆红纹黄单胞菌α-氨基酸酯水解酶基因全序列,对序列进行生物信息学分析,并提高酶的热稳定性。【方法】利用多聚酶链式反应(PCR)克隆α-氨基酸酯水解酶基因全序列;应用生物信息学软件对获得的基因序列及编码的蛋白序列进行分析;通过同源建模,预测红纹黄单胞菌α-氨基酸酯水解酶的三维结构;通过定点突变替换氨基酸序列中高度柔性的位点,提高该酶的热稳定性。【结果】从红纹黄单胞菌(Xanthomonas rubrillineans)中扩增得到α-氨基酸酯水解酶基因aeh(GenBank登录号JF744990),核苷酸序列长度1 917 bp,编码638个氨基酸。序列比对和同源性分析显示,该酶与白纹黄单胞菌Xanthomonas albilineans str.GPE PC73的肽酶及地毯草黄单胞菌Xanthomonas axono-podis pv. citri str. 306的戊二酰-7-氨基头孢烷酸酰化酶氨基酸序列相似性最高,分别为91%和83%,系统进化分析表明,该酶与白纹黄单胞菌Xanthomonas albilineans str. GPEPC73的肽酶亲缘性最高。基于预测的三维模型,对高度柔性的位点进行饱和突变,从282株突变体中筛选得到3株T50较野生型高5°C以上的突变体。【结论】对红纹黄单胞菌AEH的氨基酸序列分析有助于探索同源蛋白的进化过程。对高度柔性位点进行饱和突变的策略可以用于提高热稳定性。     

The Protein Mutant Database.

Currently the protein mutant database (PMD) contains over 81 000 mutants, including artificial as well as natural mutants of various proteins extracted from about 10 000 articles. We recently developed a powerful viewing and retrieving system (http://pmd.ddbj.nig.ac.jp), which is integrated with the sequence and tertiary structure databases. The system has the following features: (i) mutated sequences are displayed after being automatically generated from the information described in the entry together with the sequence data of wild-type proteins integrated. This is a convenient feature because it allows one to see the position of altered amino acids (shown in a different color) in the entire sequence of a wild-type protein; (ii) for those proteins whose 3D structures have been experimentally determined, a 3D structure is displayed to show mutation sites in a different color; (iii) a sequence homology search against PMD can be carried out with any query sequence; (iv) a summary of mutations of homologous sequences can be displayed, which shows all the mutations at a certain site of a protein, recorded throughout the PMD.     

Transferrin trojan horses as a rational approach for the biological delivery of therapeutic peptide domains.

One novel approach for the biological delivery of peptide drugs is to incorporate the sequence of the peptide into the structure of a natural transport protein, such as human serum transferrin. To examine whether this is feasible, a peptide sequence cleavable by the human immunodeficiency virus type 1 protease (VSQNYPIVL) was inserted into various regions of human serum transferrin, and the resultant proteins were tested for function. Experimentally, molecular modeling was used to identify five candidate insertion sites in surface exposed loops of human serum transferrin that were distant from biologically active domains. These insertions were cloned using polymerase chain reaction mutagenesis, and the proteins were expressed using a baculovirus expression vector system. Analysis of the mutant proteins provided a number of important findings: (a) they retained native human serum transferrin function, (b) the inserted peptide sequence was surface exposed, and most importantly, (c) two of these mutants could be cleaved by human immunodeficiency virus-1 protease. In conclusion, this investigation has validated the use of human serum transferrin as a carrier protein for functional peptide domains introduced into its structure using protein engineering. These findings will be useful for developing a novel class of therapeutic agents for a broad spectrum of diseases.     

The prediction of virus mutation using neural networks and rough set techniques

Viral evolution remains to be a main obstacle in the effectiveness of antiviral treatments. The ability to predict this evolution will help in the early detection of drug-resistant strains and will potentially facilitate the design of more efficient antiviral treatments. Various tools has been utilized in genome studies to achieve this goal. One of these tools is machine learning, which facilitates the study of structure-activity relationships, secondary and tertiary structure evolution prediction, and sequence error correction. This work proposes a novel machine learning technique for the prediction of the possible point mutations that appear on alignments of primary RNA sequence structure. It predicts the genotype of each nucleotide in the RNA sequence, and proves that a nucleotide in an RNA sequence changes based on the other nucleotides in the sequence. Neural networks technique is utilized in order to predict new strains, then a rough set theory based algorithm is introduced to extract these point mutation patterns. This algorithm is applied on a number of aligned RNA isolates time-series species of the Newcastle virus. Two different data sets from two sources are used in the validation of these techniques. The results show that the accuracy of this technique in predicting the nucleotides in the new generation is as high as 75 %. The mutation rules are visualized for the analysis of the correlation between different nucleotides in the same RNA sequence.     

Evolution and similarity evaluation of protein structures in contact map space

Prediction of fold from amino acid sequence of a protein has been an active area of research in the past few years, but the limited accuracy of existing techniques emphasizes the need to develop newer approaches to tackle this task. In this study, we use contact map prediction as an intermediate step in fold prediction from sequence. Contact map is a reduced graph-theoretic representation of proteins that models the local and global inter-residue contacts in the structure. We start with a population of random contact maps for the protein sequence and "evolve" the population to a "high-feasibility" configuration using a genetic algorithm. A neural network is employed to assess the feasibility of contact maps based on their 4 physically relevant properties. We also introduce 5 parameters, based on algebraic graph theory and physical considerations, that can be used to judge the structural similarity between proteins through contact maps. To predict the fold of a given amino acid sequence, we predict a contact map that will sufficiently approximate the structure of the corresponding protein. Then we assess the similarity of this contact map with the representative contact map of each fold; the fold that corresponds to the closest match is our predicted fold for the input sequence. We have found that our feasibility measure is able to differentiate between feasible and infeasible contact maps. Further, this novel approach is able to predict the folds from sequences significantly better than a random predictor.     

Wiggle—Predicting Functionally Flexible Regions from Primary Sequence

The Wiggle series are support vector machine–based predictors that identify regions of functional flexibility using only protein sequence information. Functionally flexible regions are defined as regions that can adopt different conformational states and are assumed to be necessary for bioactivity. Many advances have been made in understanding the relationship between protein sequence and structure. This work contributes to those efforts by making strides to understand the relationship between protein sequence and flexibility. A coarse-grained protein dynamic modeling approach was used to generate the dataset required for support vector machine training. We define our regions of interest based on the participation of residues in correlated large-scale fluctuations. Even with this structure-based approach to computationally define regions of functional flexibility, predictors successfully extract sequence-flexibility relationships that have been experimentally confirmed to be functionally important. Thus, a sequence-based tool to identify flexible regions important for protein function has been created. The ability to identify functional flexibility using a sequence based approach complements structure-based definitions and will be especially useful for the large majority of proteins with unknown structures. The methodology offers promise to identify structural genomics targets amenable to crystallization and the possibility to engineer more flexible or rigid regions within proteins to modify their bioactivity.     

Computer-aided design in protein engineering

The amino acid sequence of a protein can be engineered genetically to yield a molecule with modified or novel properties of clinical or industrial importance, through knowledge of the relationships between sequence, three-dimensional structure and function. Interactive computer graphics can display and model the structural information revealed by protein cyrstallography. In the absence of a suitable crystal structure, computer methods must predict protein conformation from sequence. The most powerful approaches for structure prediction are based on sequence homology or a more general analogy with known crystal structures. Improvements in these methods will require access to data bases containing the basic motifs of protein architecture.     

Beta-turn propensities as paradigms for the analysis of structural motifs to engineer protein stability.

The thermodynamic stability of a protein provides an experimental metric for the relationship of protein sequence and native structure. We have investigated an approach based on an analysis of the structural database for stability engineering of an immunoglobulin variable domain. The most frequently occurring residues in specific positions of beta-turn motifs were predicted to increase the folding stability of mutants that were constructed by site-directed mutagenesis. Even in positions in which different residues are conserved in immunoglobulin sequences, the predictions were confirmed. Frequently, mutants with increased beta-turn propensities display increased folding cooperativities, suggesting pronounced effects on the unfolded state independent of the expected effect on conformational entropy. We conclude that structural motifs with predominantly local interactions can serve as templates with which patterns of sequence preferences can be extracted from the database of protein structures. Such preferences can predict the stability effects of mutations for protein engineering and design.     

Annotating nucleic acid-binding function based on protein structure

Many of the targets of structural genomics will be proteins with little or no structural similarity to those currently in the database. Therefore, novel function prediction methods that do not rely on sequence or fold similarity to other known proteins are needed. We present an automated approach to predict nucleic-acid-binding (NA-binding) proteins, specifically DNA-binding proteins. The method is based on characterizing the structural and sequence properties of large, positively charged electrostatic patches on DNA-binding protein surfaces, which typically coincide with the DNA-binding-sites. Using an ensemble of features extracted from these electrostatic patches, we predict DNA-binding proteins with high accuracy. We show that our method does not rely on sequence or structure homology and is capable of predicting proteins of novel-binding motifs and protein structures solved in an unbound state. Our method can also distinguish NA-binding proteins from other proteins that have similar, large positive electrostatic patches on their surfaces, but that do not bind nucleic acids.