利用噬菌体展示技术构建Mhp168株Hsp70随机肽库

[目的]构建Mhp168株Hsp70 C端基因的噬菌体展示随机肽库。[方法]扩增猪肺炎支原体168株热休克蛋白Hsp70 C端1 803 bp的DNA序列。回收Hsp70 DNaseⅠ消化产物中80～150 bp的DNA片段与p C89载体连接。辅助噬菌体超感染转化重组噬粒的E.coli XL1-Blue细胞。检测肽库的多样性,测定库容。[结果]在噬菌体表面展示出Hsp70 C端基因的随机片段融合蛋白。随机肽库库容约为9.9×10~3,滴度约为1.5×10~(13)PFU/ml。[结论]所构建的随机肽库可以满足Hsp70构象型抗原表位筛选。     

人源天然ScFv噬菌体抗体库的构建及鉴定

噬菌体抗体库技术是获得治疗性抗体的一条重要途径。以20份健康人外周血为样本,通过提取淋巴细胞、逆转录－PCR（RT PCR）、抗体可变区基因的扩增、重叠PCR获得单链抗体（ScFv）基因,将ScFv克隆入噬粒载体,通过近300次的电转化获得了库容量为1.3×109的全人源天然ScFv噬菌体抗体库。通过随机挑克隆测序和用5种不同抗原筛选对抗体库进行了初步验证。随机测序表明抗体库具有较好的多样性,用5种不同抗原对其进行筛选,均获得了特异性噬菌体抗体的不同富集,表明成功构建了一个多样性良好的人源天然ScFv噬菌体抗体库。     

应用噬菌体展示随机肽库淘筛mAb5H5识别的抗原表位

本文利用噬菌体随机9肽库探索汉滩病毒(HTNV)核衣壳蛋白(NP)B细胞抗原表位.以抗HTNV NP单克隆抗体(mAb)5H5作为筛选分子,生物淘洗噬菌体递呈的随机9肽库.阳性克隆经夹心ELISA、竞争ELISA鉴定后,随机挑取10个克隆,DNA测序,与HTNV 76～118株S基因进行同源性分析.结果显示筛选到的噬菌体能特异地与5H5结合,这种结合可被天然抗原所抑制.10个克隆的氨基酸序列相同,均为VRDAEEQYE,与76～118株NP氨基端的aa25～33一致.证实了该线性表位是mAb 5H5识别的表位,噬菌体肽库有助于病毒抗原表位的确定.     

鼠疫耶尔森氏菌LcrV基因的克隆及序列分析

为了研究鼠疫耶尔森氏菌（Y.pestis）保护性抗原V蛋白,从基因库中查得Y.pestis LcrV基因DNA序列,针对序列设计合成了一对PCR扩增引物,以本所保存的Y.pestis菌种为模板进行基因扩增,结果获得长约980bp的DNA片段。将扩增产物回收纯化,克隆至pGEM-T载体,构建重组载体pGEN-T/ypV,经过PCR,酶切鉴定,并对pGEM-T/ypV中的V基因片段进行测序,分析测序结果与己知序列相同,表明获得了LcrV基因。     

东方田鼠感染血清免疫筛选日本血吸虫成虫cDNA文库

东方田鼠 (Microtusfortis ,Mf)对日本血吸虫 (Schistosomajaponicum ,Sj)感染具有抗性 .为探讨Mf感染Sj后是否产生针对虫体某些特异抗原分子的免疫应答 ,用Mf感染血清对Sj成虫cDNA文库进行免疫筛选 .经初筛和复筛 ,共筛选出 12个阳性克隆 .这些阳性克隆经辅助噬菌体自动剪切后PCR扩增显示 ,插入的SjcDNA片段大小在 3 0 0bp至 1 8kb之间 ,其中 1 8kb片段 5个 ,1kb片段 1个 ,3 0 0bp片段6个 .经DNA测序分析 ,鉴定出 3个未曾报道过的Sj新基因 ,分别命名为Sj Mf1、Sj Mf2和Sj胞质氨基肽酶 ,并在GenBank登记注册 .结果说明 ,Mf感染血清可识别Sj的特异性抗原分子 ,这些抗原分子的免疫保护作用值得进一步研究 .     

从噬菌体抗体库中淘选血纤维蛋白特异的单链抗体

为构建小鼠噬菌体抗体库 ,以获得对人血纤维蛋白特异的抗体 ,由小鼠脾脏提取 m RNA,经反转录 PCR扩增出抗体重链、轻链可变区基因片段 ,将二者和一段编码十五肽 (Gly4 Ser) 3的 DNA接头借助重组 PCR组装成为单链抗体 (single- chain antibody,Sc Ab)基因 .将单链抗体基因插入噬菌体展示载体 p CANTAB- 5E,通过电击法转化大肠杆菌 TG1细胞 ,用辅助噬菌体 M1 3K0 7超感染 ,构建了库容量在 1 0 8以上的噬菌体单链抗体库 .利用亲和选择方法 (淘选 ) ,从噬菌体抗体库中选得血纤维蛋白特异的单链抗体 .模拟抗体成熟过程 ,用 DNA改组 (DNA shuffling)技术使抗体基因重新组合 ,构建新的改组抗体库 ,并从中选择到提高了亲和力的噬菌体单链抗体 .抗体基因在大肠杆菌中表达 ,表达蛋白经 Sephadex G- 75柱层析分离 ,得到初步纯化的单链抗体蛋白 .     

应用噬菌体展示随机肽库淘筛mAb 5H5识别的抗原表位

本文利用噬菌体随机9肽库探索汉滩病毒（HTNV）核衣壳蛋白（NP）B细胞抗原表位。以抗HTNV NP单克隆抗体(mAb）5H5作为筛选分子,生物淘洗噬菌体递呈的随机9肽库。阳性克隆经夹心ELISA、竞争ELISA鉴定后,随机挑取10个克隆,DNA测序,与HTNV76－118株S基因进行同源性分析。结果显示筛选到的噬菌体能特异地与5H5结合,这种结合可被天然抗原所抑制。10个克隆的氨基酸序列相同,均为VRDAEEQYE,与76－118株NP氨基端的aa25-33一致。证实了该线性表位是mAb 5H5识别的表位,噬菌体肽库有助于病毒抗原表位的确定。     

SARS冠状病毒S蛋白噬菌体抗原库的构建及筛选

本研究旨在构建SARS冠状病毒S蛋白特异性噬菌体抗原库,并用于鉴定抗S蛋白单克隆抗体的抗原表位。首先采用PCR技术扩增出SARS冠状病毒S蛋白的全基因,以DNaseI将其随机酶切成50～500bp不同大小的DNA片段。然后将DNA片段平末端化并连接到经过改造的噬菌体表达载体pComb3XSS,经电转化大肠杆菌XL1-Blue和辅助噬菌体感染获得S蛋白的特异性噬菌体抗原库。利用两个抗S蛋白单克隆中和抗体(S-M1和S-M2)对S蛋白抗原库进行富集和筛选。结果表明,我们成功构建库容量为5.7×106的S蛋白噬菌体抗原库。通过对S-M1和S-M2的有效富集和筛选,分别得到14个和15个阳性克隆,序列分析初步揭示了抗体的抗原表位。因此,S蛋白噬菌体抗原库的构建为鉴定S蛋白的抗原表位提供了重要的技术平台,对研发SARS疫苗和诊断试剂具有重要的科学意义和应用价值。     

抗乙型肝炎病毒表面抗原T7噬菌体抗体库的构建

构建T7噬菌体单链抗体(scFv)库筛选抗乙型肝炎病毒表面抗原抗体.从抗-HBs阳性患者外周血淋巴细胞中提取总RNA,反转录合成cDNA第1条链,PCR分别扩增抗体重链可变区基因(VH)和轻链可变区基因(VL),经重叠延伸拼接(SOE)PCR组成scFv基因,并将其与T7噬菌体载体的2个臂相连接.体外包装后,在宿主菌BLT5403中,扩增重组噬菌体抗体库.以乙型肝炎病毒表面抗原进行4轮“吸附-洗脱-扩增”的筛选,酶免疫实验检测抗体活性.所建抗体库库容为1.53×107,扩增后初级库滴度为2.42×1010pfu/mL.以乙型肝炎病毒表面抗原筛选后抗体出现特异性富集,经酶免疫实验鉴定,得到2株与HBsAg抗原特异结合的噬菌体抗体,成功构建了抗HBsAg蛋白T7噬菌体抗体库.     

人源抗汉坦病毒核衣壳蛋白T7噬菌体抗体库的构建

构建人源T7噬菌体单链抗体(scFv)库筛选抗汉坦病毒核衣壳蛋白(NP)抗体。从肾综合征出血热恢复期患者外周血淋巴细胞中提取总RNA,反转录合成cDNA第一条链,PCR分别扩增抗体重链可变区基因(VH)和轻链可变区基因(VL),经重叠延伸拼接(SOE)PCR组成scFv基因,并将其与T7噬菌体载体的2个臂相连接。体外包装后,在宿主菌BLT5403中,扩增重组噬菌体抗体库。以基因工程表达NP进行4轮“吸附-洗脱-扩增”的筛选,酶免疫实验检测抗体活性。所建抗体库库容为1.35×107,扩增后初级库滴度为2.12×1010pfu/mL。以NP抗原筛选后抗体出现特异性富集,经酶免疫实验鉴定,得到2株与NP抗原特异结合的噬菌体抗体。结果表明,研究成功构建了人源抗NP蛋白T7噬菌体抗体库。     

Use of prior information in simple random sampling

Is is assumed that the population mean, to be estimated, is less than or equal to a known constant. An estimator is suggested which takes into account this information to advantage. It is also suggested that stratification coupled with the modified estimator can be best suited in such situations.     

Score test for missing at random or not under logistic missingness models

Missing data are frequently encountered in various disciplines and can be divided into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). Valid statistical approaches to missing data depend crucially on correct identification of the underlying missingness mechanism. Although the problem of testing whether this mechanism is MCAR or MAR has been extensively studied, there has been very little research on testing MAR versus MNAR. A critical challenge that is faced when dealing with this problem is the issue of model identification under MNAR. In this paper, under a logistic model for the missing probability, we develop two score tests for the problem of whether the missingness mechanism is MAR or MNAR under a parametric model and a semiparametric location model on the regression function. The implementation of the score tests circumvents the identification issue as it requires only parameter estimation under the null MAR assumption. Our simulations and analysis of human immunodeficiency virus data show that the score tests have well-controlled type I errors and desirable powers.     

Generalized prediction intervals for treatment effects in random‐effects models

This article derives generalized prediction intervals for random effects in linear random‐effects models. For balanced and unbalanced data in two‐way layouts, models are considered with and without interaction. Coverage of the proposed generalized prediction intervals was estimated in a simulation study based on an agricultural field experiment. Generalized prediction intervals were compared with prediction intervals based on the restricted maximum likelihood (REML) procedure and the approximate methods of Satterthwaite and Kenward and Roger. The simulation study showed that coverage of generalized prediction intervals was closer to the nominal level 0.95 than coverage of prediction intervals based on the REML procedure.     

NULL MODELS FOR THE NUMBER OF EVOLUTIONARY STEPS IN A CHARACTER ON A PHYLOGENETIC TREE

Random trees and random characters can be used in null models for testing phylogenetic hypothesis. We consider three interpretations of random trees: first, that trees are selected from the set of all possible trees with equal probability; second, that trees are formed by random speciation or coalescence (equivalent); and third, that trees are formed by a series of random partitions of the taxa. We consider two interpretations of random characters: first, that the number of taxa with each state is held constant, but the states are randomly reshuffled among the taxa; and second, that the probability each taxon is assigned a particular state is constant from one taxon to the next. Under null models representing various combinations of randomizations of trees and characters, exact recursion equations are given to calculate the probability distribution of the number of character state changes required by a phylogenetic tree. Possible applications of these probability distributions are discussed. They can be used, for example, to test for a panmictic population structure within a species or to test phylogenetic inertia in a character's evolution. Whether and how a null model incorporates tree randomness makes little difference to the probability distribution in many but not all circumstances. The null model's sense of character randomness appears more critical. The difficult issue of choosing a null model is discussed.     

Inhibition of expression of virulence genes of Yersinia pestis in Escherichia coli by external guide sequences and RNase P

External guide sequences (EGSs) targeting virulence genes from Yersinia pestis were designed and tested in vitro and in vivo in Escherichia coli. Linear EGSs and M1 RNA-linked EGSs were designed for the yscN and yscS genes that are involved in type III secretion in Y. pestis. RNase P from E. coli cleaves the messages of yscN and yscS in vitro with the cognate EGSs, and the expression of the EGSs resulted in the reduction of the levels of these messages of the virulence genes when those genes were expressed in E. coli.     

Properties of behavior under different random ratio and random interval schedules: A parametric study

Four pigeons were trained to peck a key under different values of a temporally defined independent variable (T) and different probabilities of reinforcement (p). Parameter T is a fixed repeating time cycle and p the probability of reinforcement for the first response of each cycle T. Two dependent variables were used: mean response rate and mean postreinforcement pause. For all values of p a critical value for the independent variable T was found (T=1 sec) in which marked changes took place in response rate and postreinforcement pauses. Behavior typical of random ratio schedules was obtained at T

1 sec and behavior typical of random interval schedules at T

1 sec.     

Micropropagation of Tectona grandis: Assessment of Genetic Fidelity

Random amplified polymorphic DNA (RAPD) markers were used to analyze genetic fidelity of micropropagated teak (Tectona grandis L.) clones with respect to subcultural passage. Of the twenty primers screened, no variation in RAPD profiles was noticed in the in vitro clones of fifth, tenth, fifteenth and twentieth passage in comparison to the in vivo mother plants. Only one micropropagated plant of twenty-fifth subcultural passage, however, differed from the in vivo ones. It revealed the appearance of a new polymorphic DNA fragment (molecular mass 379 kb) in case of primer OPB-08. This primer, manifesting detectable variation, may be utilized as a diagnostic marker for assessing genetic fidelity of micropropagted teak plants. This revised version was published online in July 2006 with corrections to the Cover Date.     

Quantifying individual variation in reaction norms: Mind the residual

Phenotypic plasticity is a central topic in ecology and evolution. Individuals may differ in the degree of plasticity (individual‐by‐environment interaction (I × E)), which has implications for the capacity of populations to respond to selection. Random regression models (RRMs) are a popular tool to study I × E in behavioural or life‐history traits, yet evidence for I × E is mixed, differing between species, populations, and even between studies on the same population. One important source of discrepancies between studies is the treatment of heterogeneity in residual variance (heteroscedasticity). To date, there seems to be no collective awareness among ecologists of its influence on the estimation of I × E or a consensus on how to best model it. We performed RRMs with differing residual variance structures on simulated data with varying degrees of heteroscedasticity and plasticity, sample size and environmental variability to test how RRMs would perform under each scenario. The residual structure in the RRMs affected the precision of estimates of simulated I × E as well as statistical power, with substantial lack of precision and high false‐positive rates when sample size, environmental variability and plasticity were small. We show that model comparison using information criteria can be used to choose among residual structures and reinforce this point by analysis of real data of two study populations of great tits (Parus major). We provide guidelines that can be used by biologists studying I × E that, ultimately, should lead to a reduction in bias in the literature concerning the statistical evidence and the reported magnitude of variation in plasticity.     

Edge-count probabilities for the identification of local protein communities and their organization

We present a computational approach based on a local search strategy that discovers sets of proteins that preferentially interact with each other. Such sets are referred to as protein communities and are likely to represent functional modules. Preferential interaction between module members is quantified via an analytical framework based on a network null model known as the random graph with given expected degrees. Based on this framework, the concept of local protein community is generalized to that of community of communities. Protein communities and higher-level structures are extracted from two yeast protein interaction data sets and a network of published interactions between human proteins. The high level structures obtained with the human network correspond to broad biological concepts such as signal transduction, regulation of gene expression, and intercellular communication. Many of the obtained human communities are enriched, in a statistically significant way, for proteins having no clear orthologs in lower organisms. This indicates that the extracted modules are quite coherent in terms of function.