部分小檗科植物的RAPD 分析

利用随机扩增多态性DNA(RAPD)技术分析了部分小檗科(Berberidaceae)5 个属6 种植物:猫儿刺(Berberis julianae Schneid.), 日本绿叶小檗(Berberis thunbergii DC.), 阔叶十大功劳(Mahonia bealei (Fo rt.)Carr.), 南天竹(Nandina domestica Thunb.), 淫羊藿(Epimedium sagittatum(S.et Z.)Maxim.)和八角莲(Dysosma versipellis (Hance)M.Cheng.)。经筛选Sangon 公司的60 个引物, 其中29 个引物的谱带清晰并呈多态性。采用UPGMA 法对求出的遗传距离进行聚类分析, 结果显示:在小檗科内建立十大功劳属(Mahonia)和南天竹属(Nandina)是合理的。     

植物叶片蛋白质的双向电泳分析

本文介绍一种提取植物叶片蛋白质的方法及电泳分析条件,可以很好地用来分析绿色组织中的全蛋白质组分。     

植物叶片蛋白质的双向电泳分析

本文介绍一种提取植物叶片蛋白质的方法及电泳分析条件,可以很好地用来分析绿色组织中的全蛋白质组分。     

小檗科紫云小檗的名实订正

在野外考察和查阅模式标本的基础上,将紫云小檗Berberis ziyunensis P. K. Hsiao & Z. Y. Li与单花小檗B. uniflora F. N. Wei & Y. G. Wei归并。     

贵州小檗属植物(小檗科)叶脉序研究

采用制作叶脉标本和透明叶标本的方法,对贵州产28种2变种小檗属植物叶脉特征进行比较研究。结果表明:贵州小檗属植物的脉序类型有5种:半达缘羽状脉、花环状半达缘羽状脉、简单弓形羽状脉、花环状弓形羽状脉和混合型。叶脉分支一般有五级:1一级脉构架均为羽状脉,粗度有很粗、粗、中等粗细和纤细四种类型,分支方式包括单轴分支和合轴分支;2粗二级脉构架中有分支达缘或分支均不达缘,与中脉夹角变化各异,内二级脉存在或缺失,细二级脉半达缘、真曲行或简单弓形,间二级脉类型复杂多变但频度种间有差异;3三级脉贯串型、结网型或分支型;4四、五级脉网状或自由分支且常混合在一起。脉间区从发育差到良好,小脉从不分支到不均等分支等各种类型均有,叶缘末级脉缺失、不完整、钉状和环状。大部分种类叶缘具齿,每1cm齿数目和齿内腺点的特性等特征在不同种类间有区别,具有鉴定价值,但齿其它特征复杂多变或种间区别较小,同时齿内脉性状也不稳定。此外,齿的有无会对脉序类型产生影响。小檗属植物叶脉类型存在种间差异,具有重要的分类学价值,叶脉类型的变化和复杂程度显示了该属植物的进化特点;叶齿的有无和齿特征具有分类学和系统学意义。基于叶脉特征的研究结果并结合重要的外部形态学特征编制了贵州小檗属植物的分种检索表。研究结果可为小檗属植物分类寻找新的依据并探讨其系统学意义。     

小檗科魁臼亚科植物的核型研究

本文首次报道了中华山荷叶与川八角莲的核型,分别为Ｋ（２ｎ）＝１２＝８ｍ（４ＳＡＴ）＋２ｓｔ＋２ｔ及Ｋ（２ｎ）＝１２＝４ｍ（２ＳＡＴ）＋４ｓｍ＋２ｓｔ（２ＳＡＴ）＋２ｔ,核型类型均为２Ａ型。     

国产五味子科五种植物叶片脉序研究

首次报道了国产五味子科５种植物的叶脉特征,对科、属、种的特征作了描述,编排有分种检索表．通过与八角科叶脉的比较,支持建立五味子科与八角科的观点,认为五味子属的系统位置在南五味子属之后,并讨论了八角目的演化趋势     

红豆杉科、三尖杉科和罗汉松科植物叶片结构的比较观察

扫描电镜和光镜下的叶表皮特征以及叶片解剖结构的研究结果,支持在红豆杉科内建立白豆杉属的处理方式;赞同在三尖杉属内建立篦子三尖杉组,叶片解剖结构方面,三尖杉科和红豆杉科的穗花杉属的相似之处颇多。而叶表皮形态特征方面又表现为三尖杉科和罗汉松科更加接近。反映了出了红豆杉科、三尖杉科和罗汉松科之间的密切而又复杂的系统关系。     

30种植物叶蛋白中氨基酸组成及含量的测定与营养价值评价

评价植物叶蛋白的营养价值,既要考虑“量”,看植物叶蛋白含量的高低,也要考虑“质”,看必需氨基酸的含量及配比[1]。作者取叶蛋白含量50%以上的30种植物进行氨基酸含量测定[2],并进行营养价值评价。1　方　　法应用日立83550型氨基酸自动分析仪进行氨基酸含量的测定,并与?..     

Protein content and amino acid composition of cassava leaf

On the basis of leaf dry wt, the protein content of six varieties of cassava varied from 29.3 to 38.6% and the estimated leaf protein production ranged from 242 to 953 kg per ha. On the basis of fr. wt of leaf, the total amino acids ranged from 8.42 to 9.4% while the essential amino acids averaged 4.21% and the sulphur-containing amino acids only 0.25%. The amino acid composition profiles for the six varieties was similar.     

南天竹资源利用与开发研究

对小檗科南天竹属南天竹的形态结构特征、生长环境及分布、栽培要点及其生态价值、观赏价值、药用价值等开发利用价值各方面作了详细阐述,为更好地开发利用南天竹资源提供科学依据.     

基于氨基酸和二肽组成的蛋白质四级结构分类研究

基于最近邻居算法,从蛋白质一级序列出发,利用蛋白质序列氨基酸组成、二肤组成以及混合组成方法对蛋白质单聚体、二聚体、三聚体、四聚体、五聚体、六聚体和八聚体进行分类研究。结果表明:采用二肽组成编码方法的预洲效果最好,Jackknife检验和独立测试集检验的总体预测精度分别达到90.83%和95.48%,比相同数据集上基于伪氨基酸组成和组分耦合预测的方法提高了12和15个百分点;特别是对于五聚体蛋白,预测精度分别提高了90和50个百分点;说明二肽组成对于蛋白质四级结构分类研究是一种非常有效的特征提取方法。     

Prediction of membrane protein types based on the hydrophobic index of amino acids

A new algorithm to predict the types of membrane proteins is proposed. Besides the amino acid composition of the query protein, the information within the amino acid sequence is taken into account. A formulation of the autocorrelation functions based on the hydrophobicity index of the 20 amino acids is adopted. The overall predictive accuracy is remarkably increased for the database of 2054 membrane proteins studied here. An improvement of about 13% in the resubstitution test and 8% in the jackknife test is achieved compared with those of algorithms based merely on the amino acid composition. Consequently, overall predictive accuracy is as high as 94% and 82% for the resubstitution and jackknife tests, respectively, for the prediction of the five types. Since the proposed algorithm is based on more parameters than those in the amino acid composition approach, the predictive accuracy would be further increased for a larger and more class-balanced database. The present algorithm should be useful in the determination of the types and functions of new membrane proteins. The computer program is available on request.     

Monte Carlo simulation studies on the prediction of protein folding types from amino acid composition

A number of methods to predicting the folding type of a protein based on its amino acid composition have been developed during the past few years. In order to perform an objective and fair comparison of different prediction methods, a Monte Carlo simulation method was proposed to calculate the asymptotic limit of the prediction accuracy [Zhang and Chou (1992),Biophys. J. 63, 1523–1529, referred to as simulation method I]. However, simulation method I was based on an oversimplified assumption, i.e., there are no correlations between the compositions of different amino acids. By taking into account such correlations, a new method, referred to as simulation method II, has been proposed to recalculate the objective accuracy of prediction for the least Euclidean distance method [Nakashimaet al. (1986),J. Biochem. 99, 152–162] and the least Minkowski distance method [Chou (1989),Prediction in Protein Structure and the Principles of Protein Conformation, Plenum Press, New York, pp. 549–586], respectively. The results show that the prediction accuracy of the former is still better than that of the latter, as found by simulation method I; however, after incorporating the correlative effect, the objective prediction accuracies become lower for both methods. The reason for this phenomenon is discussed in detail. The simulation method and the idea developed in this paper can be applied to examine any other statistical prediction method, including the computersimulated neural network method.     

Amino acid composition and protein dimension

There is indirect evidence that the amino acid composition of proteins depends on their dimension. The amino acid composition of a nonredundant set of about 550,000 proteins was determined and it was observed that, in the range of 50-200 residues, the percentage of occurrence of most of the residue types significantly depends on protein dimension. This result should prove useful in analyzing protein sequences and genomics.     

Unique amino acid composition of proteins in halophilic bacteria

The amino acid compositions of proteins from halophilic archaea were compared with those from non-halophilic mesophiles and thermophiles, in terms of the protein surface and interior, on a genome-wide scale. As we previously reported for proteins from thermophiles, a biased amino acid composition also exists in halophiles, in which an abundance of acidic residues was found on the protein surface as compared to the interior. This general feature did not seem to depend on the individual protein structures, but was applicable to all proteins encoded within the entire genome. Unique protein surface compositions are common in both halophiles and thermophiles. Statistical tests have shown that significant surface compositional differences exist among halophiles, non-halophiles, and thermophiles, while the interior composition within each of the three types of organisms does not significantly differ. Although thermophilic proteins have an almost equal abundance of both acidic and basic residues, a large excess of acidic residues in halophilic proteins seems to be compensated by fewer basic residues. Aspartic acid, lysine, asparagine, alanine, and threonine significantly contributed to the compositional differences of halophiles from meso- and thermophiles. Among them, however, only aspartic acid deviated largely from the expected amount estimated from the dinucleotide composition of the genomic DNA sequence of the halophile, which has an extremely high G+C content (68%). Thus, the other residues with large deviations (Lys, Ala, etc.) from their non-halophilic frequencies could have arisen merely as "dragging effects" caused by the compositional shift of the DNA, which would have changed to increase principally the fraction of aspartic acid alone.     

A sulfur amino acid deficiency changes the amino acid composition of body protein in piglets

Experiments carried out to determine the amino acid requirement in growing animals are often based on the premise that the amino acid composition of body protein is constant. However, there are indications that this assumption may not be correct. The objective of this study was to test the effect of feeding piglets a diet deficient or not in total sulfur amino acids (TSAA; Met + Cys) on nitrogen retention and amino acid composition of proteins in different body compartments. Six blocks of three pigs each were used in a combined comparative slaughter and nitrogen balance study. One piglet in each block was slaughtered at 42 days of age, whereas the other piglets received a diet deficient or not in TSAA for 19 days and were slaughtered thereafter. Two diets were formulated to provide either 0.20% Met and 0.45% TSAA (on a standardized ileal digestible basis) or 0.46% Met and 0.70% TSAA. Diets were offered approximately 25% below ad libitum intake. At slaughter, the whole animal was divided into carcass, blood, intestines, liver, and the combined head, tail, feet and other organs (HFTO), which were analyzed for nitrogen and amino acid contents. Samples of the longissimus muscle (LM) were analyzed for myosin heavy chain (MyHC) and actin contents. Nitrogen retention was 20% lower in piglets receiving the TSAA-deficient diet (P < 0.01). In these piglets, the nitrogen content in tissue gain was lower in the empty body, carcass, LM and blood (P < 0.05) or tended to be lower in HFTO (P < 0.10), but was not different in the intestines and liver. The Met content in retained protein was lower in the empty body, LM and blood (P < 0.05), and tended to be lower in the carcass (P < 0.10). The Cys content was lower in LM, but higher in blood of piglets receiving the TSAA-deficient diet (P < 0.05). Skeletal muscle appeared to be affected most by the TSAA deficiency. In LM, the Met content in retained protein was reduced by 12% and total Met retention by more than 60%. The MyHC and actin contents in LM were not affected by the TSAA content of the diet. These results show that a deficient TSAA supply affects the amino acid composition of different body proteins. This questions the use of a constant ideal amino acid profile to express dietary amino acid requirements, but also illustrates the plasticity of the animal to cope with nutritional challenges.     

利用伪氨基酸组分和支持向量机预测抗冻蛋白

抗冻蛋白是一类具有提高生物抗冻能力的蛋白质。抗冻蛋白能够特异性的与冰晶相结合,进而阻止体液内冰核的形成与生长。因此,对抗冻蛋白的生物信息学研究对生物工程发展。提高作物抗冻性有重要的推动作用。本文采用由400条抗冻蛋白序列和400条非抗冻蛋白序列构成数据集,以伪氨基酸组分为特征,利用支持向量机分类算法预测抗冻蛋白,对训练集预测精度达到91．3％,对测试集预测精度达到78．8％。该结果证明伪氨基酸组分能够很好的反映抗冻蛋白特性,并能够用于预测抗冻蛋白。