螺旋藻的培养及其分子生物学研究概况

本文评述了螺旋藻的培养及其分子生物学研究的新进展,认为：螺旋藻的生物学特性及其培养得到了广泛的研究,其工厂化生产日趋成熟,封闭式生物反应器的出现将加快螺旋藻产业的发展,螺旋藻的生物活性物质的功能越来越受到人们的重视,其结构与功能的关系进一步深入;分子生物学技术在螺旋藻上的应用将促进藻类学的研究和藻类资源的开发。     

富硒螺旋藻培养技术研究

采用富硒技术对印项螺旋藻培养进行强化,对硒（IV）浓度和亚硫酸盐的影响,以及硒的生物富集及其对藻细胞分子官能团结构的影响等进行了较为详细的研究,并对相关的可能机理进行了讨论。研究发现,硒对印顶螺旋藻生长具有刺激或抑制的双重作用。在0.02mg/L-411.00mg/L浓度范围内,硒不仅可以加快印顶螺旋藻的生长,而且还可以提高其生物量;同时,钝顶螺旋藻对硒的事集随着硒浓度的增加而增加,较为缓慢的生长利于钝顶螺旋藻对硒的富集。研究还证实,NaSO3会减轻高浓度Na2SeO3对印顶螺旋藻生长的毒性,富硒培养不会对藻细胞分子官能团结构产生损害。实验得出钝顶螺旋藻富硒培养较佳的硒处理浓度在10mg／L－40mg／L。     

螺旋藻耐盐相关基因启动子区功能分析

文章利用绿色荧光蛋白基因作为报告基因,研究2个螺旋藻耐盐相关基因启动子区域的功能。通过启动子预测软件预测螺旋藻耐盐相关基因5′端非翻译区的启动子结构,用Primer3.0程序在线设计引物,以pMD18-T载体和pUC18载体克隆螺旋藻启动子序列、gfp和卡那霉素抗性基因,将螺旋藻启动子-GFP基因-卡那霉素抗性基因(pro-gfp-kanr)三联DNA片段克隆至pKW1188载体,并将该重组质粒pKW1188::pro::gfp::kanr转化至受体菌集胞藻6803,激光共聚焦显微镜观察不同盐浓度培养条件下、不同时间段集胞藻表达GFP的情况。结果显示,通过不同盐浓度和不同时间的诱导,2个螺旋藻启动子在0.4~0.6 mol/L NaCl条件下,培养6~8 h表达的绿色荧光蛋白最多。文章成功构建了以绿色荧光蛋白为报告基因、卡那霉素抗性基因为选择标记、集胞藻6803作为外源基因表达受体,进行螺旋藻耐盐相关基因功能研究的平台;另外,从螺旋藻启动子能被盐诱导大量表达GFP的结果看,与启动子相关的螺旋藻基因很可能与螺旋藻的耐盐性相关。     

螺旋藻保健功能的研究(Ⅰ)——免疫调节保健功能的检验与评价

本研究对螺旋藻产品的免疫调节保健功能进行了检验和评价。小鼠实验结果显示 ,饲喂螺旋藻可以增强其体液免疫、细胞免疫、自然杀伤细胞和巨噬细胞等免疫系统的重要组成部分的活力。研究表明 ,螺旋藻能协调地改善免疫系统的功能 ,它不愧是优秀的保健食品。     

螺旋藻保健功能的研究（Ⅰ）：免疫调节保健的检验与评价

本研究对螺旋藻产品的免疫调节保健功能进行了检验和评价。小鼠实验结果显示,饲喂螺旋藻可以增强其体液免疫、细胞免疫、自然杀伤细胞和巨噬细胞等免疫系统的重要组成分部的活力。研究表明,螺旋藻能协调地改善免疫系统的功能,这不愧是优秀的保健食品。     

高浓度CO_2对极大螺旋藻生长和光合作用的影响

以极大螺旋藻作为实验材料 ,研究了高CO2 浓度对极大螺旋藻的生长和光合作用效应 ,结果表明在高光强下 (40 0 μmolm- 2 s- 1 ) ,高浓度CO2 对其生长和光合作用有明显的影响 ,高浓度CO2 培养下 ,螺旋藻的比生长速率是低浓度CO2 培养的 1 2倍 ;而在低光强下 ,高浓度CO2 对其生长和光合作用无明显影响。两种不同CO2 浓度和光强下培养的极大螺旋藻 ,在不同的生长时期 ,分别测定其P -I曲线 ,结果表明低光强下培养的极大螺旋藻 ,在 5d、8d、1 1d ,两者的Ik、α值均无显著差异 ,Pmax在第 5d、1 1d差异不显著 ,但在第 8d有显著差异。而在高光强培养条件下 ,第 8、1 1d通高浓度CO2 培养的极大螺旋藻 ,其Pmax、α值明显大于通低浓度CO2 培养的极大螺旋藻 ,但两者在第 5d无明显差异。     

高浓度CO2对极大螺旋藻生长和光合作用的影响

以极大螺旋藻作为实验材料,研究了高CO2浓度对极大螺旋藻的生长和光合作用效应,结果表明在高光强下（400μmolm^-2s^-1),高浓度CO2对其生长和光合作用有明显的影响。高浓度CO2培养下,辈放荡中的比生长速率是低浓度CO2培养的1.2倍;而在低光强下,高浓度CO2对其生长和光合作用无明显影响。两种不同CO2浓度和光强下培养的极大螺旋藻,在不同的生长时期,分别测定其P-I曲线,结果表明,低光强下培养的极大螺旋藻,在5d、8d、11d,两者的Ik、α值均无显著差异,Pmax在第5d、11d差异不显著,但在第8d有显著差异。而在高光强培养条件下,第8、11d通高浓度CO2培养的极大螺旋藻,其Pmax、α值明显大于通低浓度CO2培养的极大螺旋藻,但两者在第5d无明显差异。     

培养条件对螺旋藻生长和藻胆蛋白含量的影响

研究了不同质量浓度尿素代替硝酸钠作氮源和不同氯化钠质量浓度改变渗透压对螺旋藻的生长和藻胆蛋白含量的影响。结果发现适宜质量浓度尿素 ( 0 .1g·L-1)培养可加快螺旋藻生长 ,增加藻胆蛋白含量 ;质量浓度高于 0 .2g·L-1其生长受到抑制 ;而质量浓度过高 (≥ 0 .4g/L)时培养几天螺旋藻即断裂并逐渐死亡。培养基中不加氯化钠或质量浓度为 2 0g·L-1时培养 ,生长速度均与对照相当 ,但藻胆蛋白含量比对照要高 ;质量浓度为 40g·L-1～ 6 0g·L-1时培养 ,其生长明显变慢 ,且氯化钠浓度越高生长越慢 ;当质量浓度过高 (≥ 6 0g·L-1)时培养 3d ,螺旋藻细胞即破裂死亡。     

大螺旋藻的形态观察和培养试验

蓝藻—螺旋藻(Spirulina)作为大规模工业化培养的对象,以其高的蛋白质含量和合理的氨基酸组成,极大地吸引了国内外生物学工作者的注意,他们对原产于非洲的钝顶螺旋藻(S.platensis)或墨西哥的极大螺旋藻(S.maxima)进行了广泛的研究3-6。笔者在我国广州珠江河畔一个小池塘里发现采集了一种螺旋藻——大螺旋藻(Spirulina major)1,2,进行了分离和单种培养。       

高浓度CO2培养条件下极大螺旋藻光抑制研究

以极大螺旋藻作为实验材料,研究了不同CO2浓度培养对螺旋藻光抑制和恢复的影响,结果表明由光抑制导致的光合速率下降,高浓度CO2比低浓度CO2培养程度小,在高浓度CO2条件下培养的极大螺旋藻,虽然在强光下也表现出光抑制,但与低浓度CO2相比,光合速率下降得较慢。这种现象在强光与弱光培养均存在,但强光培养时更明显。光抑制后的恢复实验表明,不同CO2浓度培养的极大螺旋藻,光系统光化学活性(Fv/Fm)在弱光下恢复较好,高光强、高浓度CO2培养的藻,恢复速度稍快;而在黑暗中,几乎没有恢复;在弱光和含氯霉素的条件下Fv/Fm均下降。由此可见,高CO2浓度可减轻极大螺旋藻的光抑制,但对其光抑制后的恢复影响不大。       

几种绿藻对西草净的抗性与活性氧防御物质

４种绿藻对除莠剂西草净（Ｓｉｍｅｔｒｙｎ）的反应有很大差异,小球藻、羊角月芽藻、衣藻和四鞭藻的ＥＣ＿（５０）（影响浓度）值分别为７００、２５、２７和１１μｇ／Ｌ不同浓度西草净都能影响绿藻的光合作用,浓度为２００ｐｐｍ６时,羊角月牙藻和四鞭藻的光合抑制率分别为９５．３％和９４．０％,但对小球藻几乎无影响,当浓度增至２０００ｐｐｍ时,对小球藻的光合抑制率为８７％。小球藻中活性氧防御物（ＳＯＤ、ＡｓＡ－ＰＯＤ、ＧＲ等）的活性均比衣藻、羊角月牙藻等高几倍到几十倍,显示小球藻对西草净的抗性和忍耐性可能与它细胞内所含的活性氧防御物活性有关,它们的高活性使小球藻在西草净污染后,对体内生成的活性氧（Ｏ＿２、Ｈ＿２Ｏ＿２、Ｏ＿２等）伤害有解毒作用。     

海洋药物的抗病毒研究

海洋由于其特殊的生态环境,包含着极其丰富的生物来源的天然产物。自本世纪七十年代以来,已经从海藻类、海绵类、海鞘类、海星类、腹足动物、棘皮动物、腔肠动物、软体动物、珊瑚及海洋微生物等海洋生物中分离出一系列有抗病毒作用的天然化合物,其中有些结构类型已成为抗病毒药物研究的导向化合物。基于现代分离和分析技术的发展、新的实验模型的建立和在病毒学方面分子生物学研究的进展,从海洋生物中寻找新的抗病毒药物已步入一个新的时代。     

云南抚仙湖鱇(鱼良)白鱼若干生物学特性的形成和演化及其与湖泊环境演变的关系

根据1988年11月至1991年3月间野外收集的资料,本文记述了云南抚仙湖鱇(鱼良)白鱼的空间分布、食性和繁殖生物学特性。在此基础上,本文首次尝试从进化的观点出发,结合湖泊环境的演变历史深入一步分析了鱇(鱼良)白鱼生物学特性的形成和演化。研究结果表明,鱇(鱼良)白鱼喜在山泉水口等流水环境产卵及幼体喜居湖泊沿岸浅水区等生活习性属较原始的性状,提示了鱇(鱼良)白鱼的祖先是营溪流生活的鱼类。成体喜居湖泊敞水区中上层、营滤食为主、繁殖季节较长、各产卵群体的产卵时间间隔有明显规律性、繁殖力较低、性比较悬殊等特性则属较特化的性状,这些较特化性状的形成与湖泊环境的总体演变过程密切相关。在性状分析的基础上还进一步探讨了生物学特性的适应意义。     

Functional tissue engineering of tendon: Establishing biological success criteria for improving tendon repair

Improving tendon repair using Functional Tissue Engineering (FTE) principles has been the focus of our laboratory over the last decade. Although our primary goals were initially focused only on mechanical outcomes, we are now carefully assessing the biological properties of our tissue-engineered tendon repairs so as to link biological influences with mechanics. However, given the complexities of tendon development and healing, it remains challenging to determine which aspects of tendon biology are the most important to focus on in the context of tissue engineering. To address this problem, we have formalized a strategy to identify, prioritize, and evaluate potential biological success criteria for tendon repair. We have defined numerous biological properties of normal tendon relative to cellular phenotype, extracellular matrix and tissue ultra-structure that we would like to reproduce in our tissue-engineered repairs and prioritized these biological criteria by examining their relative importance during both normal development and natural tendon healing. Here, we propose three specific biological criteria which we believe are essential for normal tendon function: (1) scleraxis-expressing cells; (2) well-organized and axially-aligned collagen fibrils having bimodal diameter distribution; and (3) a specialized tendon-to-bone insertion site. Moving forward, these biological success criteria will be used in conjunction with our already established mechanical success criteria to evaluate the effectiveness of our tissue-engineered tendon repairs.     

Prospects for drug screening using the reverse two-hybrid system.

Rational drug-screening strategies have been limited by the number of available protein targets. The fields of genomics and functional genomics are now merging into 'chemical genomics' approaches, in which large numbers of potential target proteins can be used in standardized high-throughput drug-screening assays. Because protein-protein interactions are critical to most biological processes and can be tested in standardized assays, they may represent optimal targets in the chemical-genomics era. The reverse two-hybrid system appears to have several properties that would be critical for the success of this approach.     

Assessment of skin carbonyl content as a noninvasive measure of biological age.

The oxidative modification of proteins by reactive species, especially reactive oxygen species, is implicated in the etiology or progression of a panoply of disorders and diseases. For the most part, oxidatively modified proteins are not repaired and must be removed by proteolytic degradation. The level of these modified molecules can be quantitated by measurement of the protein carbonyl content, which has been shown to increase in a variety of diseases and processes, most notably during aging. However, these studies have required invasive techniques to obtain cells for analysis. We examined the possibility that desquamating skin cells (corneocytes) would also show an age-related increase in protein carbonyl content, thus providing a noninvasive method for assessing biological age. This was not the case, as we found no age-dependent relationship in the protein carbonyl content of skin cells from volunteers aged 20 to 79 years.     

Shotgun proteomic analysis of mulberry dwarf phytoplasma

Background  

Mulberry dwarf (MD), which is caused by phytoplasma, is one of the most serious infectious diseases of mulberry. Phytoplasmas have been associated with diseases in several hundred plant species. The inability to culture phytoplasmas in vitro has hindered their characterization at the molecular level. Though the complete genomes of two phytoplasmas have been published, little information has been obtained about the proteome of phytoplasma. Therefore, the proteomic information of phytoplasmas would be useful to elucidate the functional mechanisms of phytoplasma in many biological processes.     

Evolving views of viral evolution: towards an evolutionary biology of viruses.

Despite considerable interest in viral evolution, at least among virologists, viruses are rarely considered from the same evolutionary vantage point as other organisms. Early work of necessity emphasized phenotype and phenotypic variation (and therefore arguably was more oriented towards the broader biological and ecological perspectives). More recent work (essentially since the development of molecular evolution in the 1960's but beginning earlier) has concentrated on genotypic variation, with less clarity about the significance of such variations. Other aspects of evolutionary theory, especially considerations of natural selection and of evolutionary constraints, have not widely been applied to viruses, and an evolutionary framework for virology has long been lacking. This becomes apparent in considering 'emerging' viruses, which have often been treated on an ad hoc basis. It was often felt that, because previously unrecognized viruses are involved, mechanisms of viral emergence must mirror the unpredictability of mutations in the viral genome. However, most examples of viral emergence are independent of mutation, at least initially, and are often pre-existing viruses in changed circumstances ('viral traffic'). This conclusion also readily follows from ordinary Darwinian premises, which would require that, like other living species, 'new' organisms are descended only from existing species. In this respect, from a Darwinian perspective, viruses would appear to resemble other organisms.     

PNME – A gene-gene parallel network module extraction method

In the domain of gene-gene network analysis, construction of co-expression networks and extraction of network modules have opened up enormous possibilities for exploring the role of genes in biological processes. Through such analysis, one can extract interesting behaviour of genes and would help in the discovery of genes participating in a common biological process. However, such network analysis methods in sequential processing mode often have been found time-consuming even for a moderately sized dataset.It is observed that most existing network construction techniques are capable of handling only positive correlations in gene-expression data whereas biologically-significant genes exhibit both positive and negative correlations. To address these problems, we propose a faster method for construction and analysis of gene-gene network and extraction of modules using a similarity measure which can identify both negatively and positively correlated co-expressed patterns. Our method utilizes General-purpose computing on graphics processing units (GPGPU) to provide fast, efficient and parallel extraction of biologically relevant network modules to support biomarker identification for breast cancer. The modules extracted are validated using p-value and q-value for both metastasis and non-metastasis stages of breast cancer. PNME has been found capable of identifying interesting biomarkers for this critical disease. We identified six genes with the interesting behaviours which have been found to cause breast cancer in homo-sapiens.