作物节木代料香菇与纯木屑代料香菇蛋白质营养比较研究

采用国际通用的蛋白质营养评价方法,对2种作物节木代料和纯木屑代料(CK)香菇子实体蛋白质的营养价值进行了比较研究。结果表明,2种作物节木代料香菇子实体蛋白质的NI指标低于纯木屑代料香菇,而CS、AAS、EAAI、BV、SRCAA等指标均高于纯木屑代料香菇。结论:作物节木代料香菇子实体和纯木屑代料香菇子实体蛋白质均具有较高营养价值,且二者之间无显著差异。     

香菇dsRNA病毒LeV的RT-PCR检测

香菇病毒HKB(Lentinula edodes mycovirus HKB,LeV)是一种具有潜隐性特点的真菌病毒,广泛存在于香菇菌株中。为了快速、准确地检测出LeV,根据LeV病毒基因组序列(AB.429556.2)的信息,设计合成一对引物,对25个香菇菌株进行RTPCR检测,在20个香菇菌株中分别扩增出LeV病毒基因组特有的条带,在5个香菇菌株中未能扩增出条带。通过对25个香菇菌株进行dsRNA提取检测,结果也表明不存在扩增片段的菌株提取不到dsRNA,存在扩增片段的菌株能够提取得到dsRNA。因此建立的RT-PCR方法可以快速检测到香菇dsRNA病毒LeV,能够对香菇的质量检测提供技术支持。     

核酸类物质脱嘌呤的反应特性、机制及影响因素

核酸的脱嘌呤反应是指核酸链上核糖与嘌呤之间的糖苷键断裂,从而产生游离嘌呤和无嘌呤位点的过程。脱嘌呤过程与基因突变和细胞老化等过程都有着密切的关系。文章主要叙述了酸性和生理条件下核酸脱嘌呤的反应特点及影响因素,并对脱嘌呤的机理进行了描述。同时,总结了致癌物对于脱嘌呤的促进作用并揭示了脱嘌呤与癌症等疾病的密切关系。此外,糖苷酶对于核酸脱嘌呤的催化作用也在文中进行了探讨。对于核酸脱嘌呤的系统研究可以为基因变异、核酸代谢等研究提供一定的理论基础,并且有助于癌症和痛风等疾病的研究。     

正交实验法优选香菇多糖的提取工艺及其硫酸酯化研究

目的:考察香菇多糖的提取工艺,制备香菇多糖硫酸酯。方法:采用正交试验法考察加水量、提取时间、提取温度和粒度4个因素对香菇多糖硫酸酯提取率及其中总糖含量的影响,应用硫酸法制备香菇多糖硫酸酯并对得到的成分进行鉴别。结果:通过对正交实验结果的极差分析。得出提取温度和加水量对多糖提取率影响比较著性,提取温度和提取时间对多糖含量的影响比较著性。确定香菇多糖提取的最佳工艺为:应用40倍量的水,每次提取4 h,提取温度90℃,香菇粒度为80目。制备的多糖硫酸酯中硫酸基含量为22.80%,显示了相对较强的生物活性。结论:本实验成功的确定了提取香菇多糖的最佳工艺,制备了硫酸基含量较高的硫酸酯化香菇多糖。     

SCAR分子标记技术在香菇菌株鉴定上的应用研究

为了建立一套基于DNA分子标记技术快速鉴定香菇菌株的有效方法,本研究首先通过对生产上常用的14个香菇菌株进行RAPD多态性分析,从香菇菌株162中扩增获得了一个片段长为1166bp的特异RAPD标记XG1166,随之利用分子克隆技术将该特异RAPD标记成功转化为稳定的SCAR标记。用同样的方法,本研究又从另一香菇菌株申香10号中获得了一段长度为347bp的特异SCAR标记SX347。试验结果表明,利用本研究获得的香菇菌株162和申香10号的特异SCAR标记,能在一天时间内准确鉴定出香菇菌株162或申香10号菌株的真伪。由此可见,SCAR分子标记是一种快速、稳定、准确鉴定香菇菌株的新方法, 可应用于食用菌种质资源保护利用、品种分类与鉴定和假种辨别。     

介绍一种脱嘌呤干扰足纹法

报道了一种鉴定蛋白质与DNA的相互作用位点的新方法——脱嘌呤干扰足纹法,并用该方法鉴定大鼠脂酰-CoA氧化酶基因的表达调控部位。此方法基于用甲酸使DNA脱嘌呤后,再与核蛋白相互作用,然后通过凝胶电泳迁移率的改变,将游离DNA和与蛋白质结合的DNA片段分开,再经六氢吡啶降解DNA中无嘌呤部位的磷酸酯键和进行电泳分析。此方法具有分辨率高、重复性好、干扰少等优点,适用于对结合位点中缺乏鸟苷酸的基因进行分析。     

耐高温香菇新品种的选育

正香菇(Lentinula edodes)是产于北半球温带与亚热带地区的一种腐生真菌,不仅营养丰富,而且具有较高的保健价值,自古以来深受人们的喜爱[1]。但香菇属中低温型变温结实性菇类,在福建、浙江等香菇主产区,因夏季温度较高,能够高温出菇的香菇品种少,导致夏季鲜香菇供应不足。目前可用于夏季香菇栽培的方法主要有两种:一是在海拔500 m以上的高山上栽培;二是利用林下或山沟出菇、覆土栽培出菇等。但这两种栽培方法也有其局限性。因此,要从根本上解决香菇高温栽培的问     

香菇复配氨基酸培养基优化及其对香菇菌丝生长生理的影响

[背景]L-氨基酸能够提供香菇生长发育的部分养分需求,利用外源添加氨基酸的方式对香菇生长基质进行优化,对于香菇产业的增产提质具有积极的发展意义.[目的]利用外源添加丙氨酸(Ala)、丝氨酸(Ser)和天冬酰胺(Asn)的方式改善培养基成分,并探究复配氨基酸促进香菇生长的可能代谢途径.[方法]在三因素三水平上,通过响应面...     

利用SSR标记鉴定香菇单核体及杂交后代

【目的】研究简单重复序列(Simple sequence repeat,SSR)分子标记方法用于香菇原生质体单核体、孢子单核体及其杂交后代的分离和鉴定。【方法】利用基于香菇全基因组序列信息开发的SSR标记,分析由香菇品种"L808"双核菌丝制备的原生质体单核体、孢子单核体及其杂交后代的SSR指纹。【结果】对制备的原生质体单核体的鉴定中,在不经过杂交配对的情况下,鉴定出"L808"的两种不同极性的原生质体单核体,其分离比例为191:1,该鉴定结果得到SSR标记、随机扩增多态性DNA(Random amplified polymorphismic DNA,RAPD)标记及传统方法的验证。另外,开发的香菇SSR标记还能以多位点组合的方式,用于对孢子单核体及其杂交后代的鉴定。【结论】应用SSR标记可加快香菇单核体的制备进程,并提高鉴定单核体及相关杂交菌株的准确性,促进香菇遗传育种研究。     

香菇C91-3菌丝发酵蛋白对S180小鼠细胞免疫功能和IFN-γ及TNF-α的作用

目的观察香菇C91-3菌丝发酵蛋白对荷瘤小鼠免疫系统的作用。方法昆明小鼠24只,S180瘤细胞荷瘤建立动物模型,随机平均分为3组：香菇C91-3菌丝发酵蛋白治疗组、环磷酰胺治疗组、生理盐水对照组。观察香菇C91-3菌丝发酵蛋白对荷瘤小鼠NK细胞活性、淋巴细胞转化率、IFN-γ和TNF-α等免疫指标的影响。结果香菇C91-3菌丝发酵蛋白能够显著提高治疗组小鼠的NK细胞活性、淋巴细胞转化率和血清中IFN-γ和TNF-α的含量。结论香菇C91-3菌丝发酵蛋白能够显著提高荷瘤小鼠免疫系统的活性。     

Effects of dietary eritadenine on the liver microsomal Delta6-desaturase activity and its mRNA in rats

Eritadenine, a hypocholesterolemic factor of Lentinus edodes mushroom, has a wide range of effects on lipid metabolism such as an increase in the liver microsomal phosphatidylethanolamine (PE) concentration, a decrease in the liver microsomal Delta6-desaturase activity, and an alteration of the fatty acid and molecular species profile of liver and plasma lipids. In this study, the time-dependent effects of dietary eritadenine on several variables concerning lipid metabolism were investigated in rats to clarify the sequence of metabolic changes caused by eritadenine, with special interest in the association of the liver microsomal phospholipid profile and the activity of Delta6-desaturase. The effect of dietary eritadenine on the abundance of mRNA for Delta6-desaturase was also investigated. When the time required for a half-change of variables was estimated during the first 5 days after the change from the control diet to the eritadenine-supplemented (50 mg/kg) diet, the change rates of the variables were fastest in the following order: alteration of the liver microsomal phospholipid profile>decrease in liver microsomal Delta6-desaturase activity>alteration of the fatty acid and molecular species profiles of microsomal and plasma phosphatidylcholine (PC)>decrease in the plasma cholesterol concentration. There was a significant correlation between the Delta6-desaturase activity and liver microsomal PE concentration, but not PC concentration, or the proportion of PC and PE or the PC/PE ratio. The suppression of Delta6-desaturase activity by dietary eritadenine was accompanied by a significant reduction in the abundance of mRNA for the enzyme. These results suggest that dietary eritadenine might suppress the activity of liver microsomal Delta6-desaturase by altering the microsomal phospholipid profile, as represented by an increase in PE concentration, and that the effect of eritadenine is mediated by the regulation of gene expression.     

Effects of dietary eritadenine on delta6-desaturase activity and fatty acid profiles of several lipids in rats fed different fats

Effects of dietary eritadenine on liver microsomal delta6-desaturase activity and the fatty acid profile of phosphatidylcholine, cholesteryl esters, and triglycerides of liver microsomes or plasma were investigated in rats fed different fats (palm oil, olive oil, and safflower oil). The activity of delta6-desaturase was influenced by both dietary fat types and eritadenine. In rats fed control diets, delta6-desaturase activity was higher in the order of the palm oil, olive oil, and safflower oil groups. In rats fed eritadenine-supplemented diets, the enzyme activity was markedly decreased to a constant level irrespective of dietary fat type. The 20:4n-6/18:2n-6 ratio of phosphatidylcholine and cholesteryl esters, as compared with triglycerides, was highly sensitive to eritadenine. The results suggest that the activity of delta6-desaturase is regulated by dietary fats and eritadenine independently, and that the effect of eritadenine is stronger than that of dietary fats.     

Eritadenine-induced alterations of plasma lipoprotein lipid concentrations and phosphatidylcholine molecular species profile in rats fed cholesterol-free and cholesterol-enriched diets

The effects of dietary eritadenine on the concentration of plasma lipoprotein lipids and the molecular species profile of plasma lipoprotein phosphatidylcholine (PC) were investigated in rats fed cholesterol-free and cholesterol-enriched diets to obtain insights into the relationship between the changes in PC molecular species profile and the hypocholesterolemic action of eritadenine. The effect of eritadenine on the secretion rate of very low density lipoprotein (VLDL) from the liver was also estimated. Rats were fed the control or eritadenine-supplemented (50 mg/kg) diets with or without exogenous cholesterol for 14 d. Eritadenine supplementation significantly decreased the cholesterol of major plasma lipoproteins, high density lipoprotein and VLDL, in rats fed cholesterol-free and cholesterol-enriched diets, respectively. The ratio of PC to phosphatidylethanolamine, delta6-desaturase activity, and the ratio of arachidonic acid to linoleic acid in liver microsomes were markedly decreased by eritadenine irrespective of the presence or absence of exogenous cholesterol. Dietary eritadenine increased the proportion of 16:0-18:2 molecular species with a decrease in 18:0-20:4 in plasma lipoprotein PC in both rats fed cholesterol-free and cholesterol-enriched diets. Eritadenine did not depress the secretion rate of VLDL in rats fed a cholesterol-free diet containing a high level of choline. The results indicate that dietary eritadenine elicits its hypocholesterolemic action with modulations of the fatty acid and molecular species profiles of PC irrespective of the presence or absence of exogenous cholesterol. The eritadenine-induced alteration of PC molecular species profile is discussed in relation to the hypocholesterolemic action of eritadenine.     

Suppression of methionine-induced hyperhomocysteinemia by dietary eritadenine in rats

The effect of dietary eritadenine on the plasma homocysteine concentration was investigated in methionine-induced hyperhomocysteinemic rats. The rats were fed on the control or eritadenine-supplemented (50 mg/kg) diet for 10 d. The animals were then injected with saline or methionine at a level of 100 or 300 mg/kg of body weight, and sacrificed 2 h or a more appropriate time after injection. The methionine injection increased the post-2 h concentration of plasma homocysteine in a dose-dependent manner in the control rats, this increase being significantly suppressed in the eritadenine-fed rats. This effect persisted up to 8 h after the methionine injection. The hepatic concentrations of S-adenosylmethionine and S-adenosylhomocysteine were increased by eritadenine, whereas the hepatic homocysteine concentration was inversely decreased. The cystathionine beta-synthase activity in the liver was increased by eritadenine. It is suggested from these results that eritadenine might suppress the methionine-induced increase in plasma homocysteine concentration by dual mechanisms: slowing the homocysteine production from S-adenosylhomocysteine and increasing the removal of homocysteine due to the enhanced activity of cystathionine beta-synthase.     

去细胞方法及其在组织工程中的应用

去细胞基质在组织工程及再生医学的大量应用为解决组织器官的修复和重建等难题带来了希望。去细胞方法大致可以分为三类:化学处理法、物理处理法及酶学处理法,且已经应用于组织工程及再生医学的各个方面。本文总结并分类目前常用的去细胞方法及其在组织工程各方面的应用,对目前国内外常用的去细胞方法及其在组织工程及再生医学中的应用进行回顾总结与分析。     

Spatial analysis of two-species interactions

Summary In this paper, I present and discuss some methods for the analysis of univariate and bivariate spatial point pattern data. Examples of such data in ecology include x-y coordinates of organisms in mapped field plots. I illustrate the methods with analyses of data from mapped field plots on Mount St. Helens, Washington state, USA. The statistical methods I emphasize are graphical methods that rely on analysis of distances between organisms. Hypothesis testing for methods like these is easily done using Monte Carlo methods, which I also discuss. For both univariate and bivariate analyses, I find that second-order methods such as K-function plots are often preferable to first-order methods (i.e., QQ-plots). However, for multivariate analyses, these second-order methods are more sensitive to small sample sizes than first-order analyses.     

Ensemble Methods for MiRNA Target Prediction from Expression Data

Background

microRNAs (miRNAs) are short regulatory RNAs that are involved in several diseases, including cancers. Identifying miRNA functions is very important in understanding disease mechanisms and determining the efficacy of drugs. An increasing number of computational methods have been developed to explore miRNA functions by inferring the miRNA-mRNA regulatory relationships from data. Each of the methods is developed based on some assumptions and constraints, for instance, assuming linear relationships between variables. For such reasons, computational methods are often subject to the problem of inconsistent performance across different datasets. On the other hand, ensemble methods integrate the results from individual methods and have been proved to outperform each of their individual component methods in theory.

Results

In this paper, we investigate the performance of some ensemble methods over the commonly used miRNA target prediction methods. We apply eight different popular miRNA target prediction methods to three cancer datasets, and compare their performance with the ensemble methods which integrate the results from each combination of the individual methods. The validation results using experimentally confirmed databases show that the results of the ensemble methods complement those obtained by the individual methods and the ensemble methods perform better than the individual methods across different datasets. The ensemble method, Pearson+IDA+Lasso, which combines methods in different approaches, including a correlation method, a causal inference method, and a regression method, is the best performed ensemble method in this study. Further analysis of the results of this ensemble method shows that the ensemble method can obtain more targets which could not be found by any of the single methods, and the discovered targets are more statistically significant and functionally enriched. The source codes, datasets, miRNA target predictions by all methods, and the ground truth for validation are available in the Supplementary materials.     

A simulation-based evaluation of methods for inferring linear barriers to gene flow

Different analytical techniques used on the same data set may lead to different conclusions about the existence and strength of genetic structure. Therefore, reliable interpretation of the results from different methods depends on the efficacy and reliability of different statistical methods. In this paper, we evaluated the performance of multiple analytical methods to detect the presence of a linear barrier dividing populations. We were specifically interested in determining if simulation conditions, such as dispersal ability and genetic equilibrium, affect the power of different analytical methods for detecting barriers. We evaluated two boundary detection methods (Monmonier's algorithm and WOMBLING), two spatial Bayesian clustering methods (TESS and GENELAND), an aspatial clustering approach (STRUCTURE), and two recently developed, non-Bayesian clustering methods [PSMIX and discriminant analysis of principal components (DAPC)]. We found that clustering methods had higher success rates than boundary detection methods and also detected the barrier more quickly. All methods detected the barrier more quickly when dispersal was long distance in comparison to short-distance dispersal scenarios. Bayesian clustering methods performed best overall, both in terms of highest success rates and lowest time to barrier detection, with GENELAND showing the highest power. None of the methods suggested a continuous linear barrier when the data were generated under an isolation-by-distance (IBD) model. However, the clustering methods had higher potential for leading to incorrect barrier inferences under IBD unless strict criteria for successful barrier detection were implemented. Based on our findings and those of previous simulation studies, we discuss the utility of different methods for detecting linear barriers to gene flow.     

Estimating counterfactuals for evaluation of ecological and conservation impact: an introduction to matching methods

Matching methods encompass non-parametric approaches to estimating counterfactual states through a rigorous selection of control units with similar characteristics to units submitted to an intervention. These methods enable comparisons between treated and control units in a way that facilitates understanding of causal relationships between interventions and outcomes. Matching methods have been used only recently in ecology and conservation biology, where such applications changed the way the field investigates causal questions, for example, in impact-evaluation studies. However, the strengths and limitations of matching methods are not well understood by most ecologists and environmental scientists. Herein, we review state-of-the-art matching methods aiming to help fill this gap in understanding. First, we present relevant theoretical concepts related to matching methods and related subjects such as counterfactual states and causation. Next, we propose guidelines and strategies for the application of matching methods in ecology and conservation biology. Finally, we discuss the possibilities for future applications of matching methods in the environmental sciences.     

A Benchmark of Parametric Methods for Horizontal Transfers Detection

Horizontal gene transfer (HGT) has appeared to be of importance for prokaryotic species evolution. As a consequence numerous parametric methods, using only the information embedded in the genomes, have been designed to detect HGTs. Numerous reports of incongruencies in results of the different methods applied to the same genomes were published. The use of artificial genomes in which all HGT parameters are controlled allows testing different methods in the same conditions. The results of this benchmark concerning 16 representative parametric methods showed a great variety of efficiencies. Some methods work very poorly whatever the type of HGTs and some depend on the conditions or on the metrics used. The best methods in terms of total errors were those using tetranucleotides as criterion for the window methods or those using codon usage for gene based methods and the Kullback-Leibler divergence metric. Window methods are very sensitive but less specific and detect badly lone isolated gene. On the other hand gene based methods are often very specific but lack of sensitivity. We propose using two methods in combination to get the best of each category, a gene based one for specificity and a window based one for sensitivity.