铜绿微囊藻生物钟蛋白的表达纯化与抗体制备

为了获得融合表达的铜绿微囊藻(Microcystic aeruginosa)生物钟蛋白KaiA、KaiB、KaiC并制备其相应的多克隆抗体,将kaiA、kaiB、kaiC基因分别克隆到原核表达质粒pET-His中.重组质粒pET-His-KaiA,pET-His-KaiB和pET-His-KaiC经酶切和测序鉴定后,分别转化E.coli BL21(DE3)进行融合表达.经SDS-PAGE分析可知,融合表达的KaiA、KaiB和KaiC蛋白表达量可分别达到菌体总蛋白的25%、40%和20%.经亲和层析后融合蛋白KaiA和KaiB的纯度分别达95%和92%,而KaiC经胶回收纯化后纯度也可达93%.将纯化后的三种Kai蛋白作为抗原分别免疫小鼠制备多克隆抗体,经ELISA检测抗体滴度表明,制备的抗KaiA、抗KaiB和抗KaiC的多克隆抗体效价高,分别可达到1:50000、1:60000和1:100000.Western blotting结果表明:获得的多克隆抗体具有较高的效价,抗体能识别相应的Kai蛋白,具有较高的特异性,能用于铜绿微囊藻生物钟蛋白KaiA、KaiB和KaiC的表达节律检测.     

新型皱纹盘鲍防御素hd-def的cDNA序列分析、基因组克隆及表达研究

从构建的皱纹盘鲍肝肾cDNA文库中筛选到了鲍防御素基因EST.通过序列分析发现该基因的全长cDNA序列编码66个氨基酸残基,其前体由信号肽、前导肽和成熟肽组成.该前体的成熟肽含42个氨基酸(6个Cys),推测分子量为4323Da,等电点为8.02.氨基酸序列同源性分析表明,该多肽与昆虫防御素的相似性较高,最高可达70%.因成熟肽二级结构具有典型的昆虫防御素结构特征,该多肽应属于抗菌肽中的昆虫防御素亚家族,是一种新型抗菌肽,将其命名为鲍防御素hd-def.采用基因组步移法获得了全长4032bp的基因组序列.分析表明,该基因由3个内含子和4个外显子编码组成;3个内含子大小分别为497bp、2357bp和528bp,其中两个内含子存在于编码信号肽的序列中.用鳗弧菌和金黄色葡萄球菌刺激皱纹盘鲍,能诱导hd-def的表达.实验检测了5种组织,发现hd-def基因仅在肝胰腺中表达,具有明显的组织表达特异性;其表达属于诱导型表达,提示该基因可能参与皱纹盘鲍的抗细菌感染.     

斜带石斑鱼生长催乳素基因全长cDNA的克隆、表达及其免疫荧光分析

我们从斜带石斑鱼垂体的SMART cDNA质粒文库中筛选到生长催乳素基因(so-matolactin,SL)的全长cDNA片段,其编码区为1644bp,编码231个氨基酸,其中N-端的24个氨基酸肽段为信号肽。运用RT-PCR技术考察了其在石斑鱼不同组织中的mRNA的转录水平,结果表明,该基因在垂体中大量转录,在其他组织中几乎检测不到转录本的存在。选取基因开放阅读框的核苷酸序列插入pGEX-KG载体进行原核表达,在大肠杆菌中表达的融合蛋白的分子量约为50kDa,并以表达的产物为抗原免疫家兔制备了多克隆抗体。采用冰冻切片和FITC标记的荧光染色方法将SL基因初步定位于脑垂体中部,沿着神经组织边缘分布。本研究为深入研究石斑鱼的生长激素／催乳激素家族的进化关系及SL基因的功能奠定了基础。     

极大节旋藻(Arthrospira maxima)生物钟基因kaiC的克隆及分析

以kaiC基因簇部分已知序列为引物设计位点,采用PCR反应池法从节旋藻基因组fosmid文库中筛选到kaiC基因克隆,通过步移测序获得了kaiC基因全长序列。kaiC基因编码区长1554bo,基因GC碱基含量平均为41．76％,密码子第三位明显偏向于U。在基因上游385bp范围内发现一个可能的启动子序列和一些基因调控元件。KaiC蛋白分析发现了Walker A、DXXG、不完整的Walker B等重要模体和具有催化作用的功能位点。Southem杂交的结果证明kaiC基因在极大节旋藻中为单拷贝。极大节旋藻kaiC基因的特殊结构特征为研究kai基因簇的进化提供了重要的启示。     

从鳗弧菌M3 Fosmid文库筛选aroA基因

为克隆鳗弧菌aroA基因 (它在细菌中编码合成芳香族氨基酸的关键酶--5-烯醇氏丙酮酰莽草酸3-磷酸(EPSP)合成酶),在实验室中构建了鳗弧菌M3大分子量基因组Fosmid文库,并通过克隆测序获得了部分序列,以此为基础,通过延伸测序获得了ar oA基因序列全长. 该基因全长1281bp,编码427个氨基酸,包含一个11个氨基酸残基的信号肽;编码区GC平均含量为46.8%,推测分子量为46177 Da.相似性分析表明,鳗弧菌的aroA核苷酸和氨基酸序列与其他弧菌的相似性最高,分别在73%～75%和78%～82%;进化树结果也表明鳗弧菌ar oA与其他弧菌的亲缘关系最近.aroA基因的克隆为构建鳗弧菌弱毒疫苗奠定了基础.     

条斑紫菜锰超氧化物歧化酶基因克隆与序列分析

为研究紫菜抗逆抗病的分子机制,以本实验室建立的条斑紫菜表达序列标签(EST)和全长cDNA富集文库,结合PCR技术,克隆了条斑紫菜编码锰超氧化物歧化酶(Mn-SOD)的cDNA及基因组DNA全长序列,并进行了序列特性相关分析.研究结果表明:该基因cDNA序列全长为958个核苷酸,包含一个完整Mn-SOD基因的ORF,编码224个氨基酸和终止密码子;该基因在基因组中序列长度为1416bp,包含4个外显子和3个内含子,这既不同于高等植物的6个外显子和5个内含子,也不同于人的5个外显子和4个内含子;该基因编码区密码子的平均GC含量为60.9%,第三位密码子的GC含量高达84.9%;序列中包含4个与Mn2 的结合位点及一个保守的金属结合结构域,预测分子量为24469.09Da,等电点为5.99;条斑紫菜Mn-SOD与人的相关蛋白具有类似的空间结构,都有6个跨膜α螺旋结构域;由cDNA序列推导的氨基酸序列与莱茵衣藻相似性为57.7%,系统发生分析表明条斑紫菜Mn-SOD与绿藻莱茵衣藻和硅藻海链藻的亲缘关系较近.这是该基因在红藻门中的首次报道.     

具有5+12优质亚基节节麦的低分子量谷蛋白基因序列分析

根据低分子量谷蛋白亚基(LMW-GS)基因编码区保守序列设计引物,对具优质高分子量谷蛋白亚基(HMW-GS)5 12的节节麦材料AS63进行扩增,得到长度约为900bp和1000bp的DNA片段,克隆测序后获得3个LMW-GS基因序列LMWD-1(GenBank登录号AY841013)、LMWD-2(GenBank登录号AY841014)和LMWD-3(GenBank登录号AY841015)。它们具有小麦低分子量谷蛋白基因的典型结构特征。其中,LMWD-1和LMWD-2具有完整编码区,长度分别为1065bp和972bp,可分别编码333和302个氨基酸残基的成熟蛋白,且第一个半胱氨酸残基均出现在重复区第13位。在重复区,LMW-1的两个疏水单元为PIIIL和PVIIL,而LMWD-2的两个疏水单元为PIIIL和SVIIL。LMW-1的重复区中还存在一个连续13个Q组成的短肽。LMWD-3由于编码区内存在提前终止密码子,为不表达的假基因。氨基酸序列比较发现,LMW-GS基因的N-末端区序列具有位点特异性,且LMW-1和LMWD-2与普通小麦Gtu-D3位点的LMW-GS基因有很高的一致性。     

斑马鱼ILF2基因的电子克隆分析

利用电子克隆方法,成功获得了ILF2基因在斑马鱼中的同源基因,为进一步研究斑马鱼ILF2基因功能奠定了基础.斑马鱼ILF2基因cDNA全长为1560bp,含有一个编码387个氨基酸的完整开放阅读框架.比较斑马鱼ILF2基因和人ILF2基因,显示两者编码氨基酸序列相似性为87%,核苷酸序列有72%相同.     

牙鲆抗菌肽hepcidin基因的克隆及表达分析

采用同源克隆的方法设计简并引物从牙鲆(Paralichthys olivaceus)肝脏中克隆了牙鲆hepcidin抗菌肽基因.牙鲆抗菌肽hepcidin基因组DNA全长821bp,序列分析表明该基因具有3个外显子和2个内含子.cDNA全长588bp,包含一个270bp的开放阅读框,编码一个长89氨基酸的前体肽.RT-PCR分析表明:该抗菌肽基因在正常牙鲆的肝脏、头肾、鳃、脾脏中表达量较高,在心脏、小肠中表达量较低;受到病原鳗弧菌感染的牙鲆各组织该基因表达量明显上升.牙鲆抗菌肽基因的克隆为水产养殖等领域的抗耐病品种的选育提供了基因源,为开发新的生物工程药物提供了基础理论和实验数据.     

铜绿微囊藻Microcystis aeruginosa PCC7820 ATP含量和细胞分裂昼夜节律的研究

为了研究铜绿微囊藻Microcystis aeruginosa PCC7820中是否存在内源昼夜节律,检测了其细胞中的三磷酸腺苷(ATP)含量和细胞分裂的日变化规律.通过生物发光法检测的细胞内ATP含量变化结果表明,在12h光/12h暗(L/D)周期环境下该藻的ATP含量呈现明显的近似24h的昼夜周期性变化,且这种周期性变化在连续光照条件下能至少持续运行3个周期,周期长度具有温度补偿效应, 而光照和温度的改变能重置昼夜节律的时相,这说明铜绿微囊藻ATP含量的昼夜节律变化受到内源生物钟的控制.通过对细胞数、细胞大小和细胞分裂素含量的检测发现,传代时间为38.4h的铜绿微囊藻的细胞分裂也呈现受生物钟调控的昼夜节律性,这种昼夜节律变化可能是生物钟通过一种门控机制调控M. aeruginosa PCC7820的细胞分裂时相而产生的.     

Genetic redundancy strengthens the circadian clock leading to a narrow entrainment range

Circadian clocks are internal timekeepers present in almost all organisms. Driven by a genetic network of highly conserved structure, they generate self-sustained oscillations that entrain to periodic external signals such as the 24 h light–dark cycle. Vertebrates possess multiple, functionally overlapping homologues of the core clock genes. Furthermore, vertebrate clocks entrain to a range of periods three times as narrow as that of other organisms. We asked whether genetic redundancies play a role in governing entrainment properties and analysed locomotor activity rhythms of genetically modified mice lacking one set of clock homologues. Exposing them to non-24 h light–dark cycles, we found that the mutant mice have a wider entrainment range than the wild types. Spectral analysis furthermore revealed nonlinear phenomena of periodically forced self-sustained oscillators for which the entrainment range relates inversely to oscillator amplitude. Using the forced oscillator model to explain the observed differences in entrainment range between mutant and wild-type mice, we sought to quantify the overall oscillator amplitude of their clocks from the activity rhythms and found that mutant mice have weaker circadian clocks than wild types. Our results suggest that genetic redundancy strengthens the circadian clock leading to a narrow entrainment range in vertebrates.     

Digital clocks: simple Boolean models can quantitatively describe circadian systems

The gene networks that comprise the circadian clock modulate biological function across a range of scales, from gene expression to performance and adaptive behaviour. The clock functions by generating endogenous rhythms that can be entrained to the external 24-h day–night cycle, enabling organisms to optimally time biochemical processes relative to dawn and dusk. In recent years, computational models based on differential equations have become useful tools for dissecting and quantifying the complex regulatory relationships underlying the clock''s oscillatory dynamics. However, optimizing the large parameter sets characteristic of these models places intense demands on both computational and experimental resources, limiting the scope of in silico studies. Here, we develop an approach based on Boolean logic that dramatically reduces the parametrization, making the state and parameter spaces finite and tractable. We introduce efficient methods for fitting Boolean models to molecular data, successfully demonstrating their application to synthetic time courses generated by a number of established clock models, as well as experimental expression levels measured using luciferase imaging. Our results indicate that despite their relative simplicity, logic models can (i) simulate circadian oscillations with the correct, experimentally observed phase relationships among genes and (ii) flexibly entrain to light stimuli, reproducing the complex responses to variations in daylength generated by more detailed differential equation formulations. Our work also demonstrates that logic models have sufficient predictive power to identify optimal regulatory structures from experimental data. By presenting the first Boolean models of circadian circuits together with general techniques for their optimization, we hope to establish a new framework for the systematic modelling of more complex clocks, as well as other circuits with different qualitative dynamics. In particular, we anticipate that the ability of logic models to provide a computationally efficient representation of system behaviour could greatly facilitate the reverse-engineering of large-scale biochemical networks.     

Period?phase map: two-dimensional selection of circadian rhythm-related genes

Many genes related to the circadian rhythm, especially those involved in phase shifts induced by different environmental stimuli, still remain enigmatic. In this study, the authors monitored the expression of rat genes measured with multiple phase-resetting stimuli, and developed a technique to extract the candidate genes for the changes in circadian rhythm by the stimuli, from microarray data. First, the spectra for the time series of gene expression were estimated by fast Fourier transform, and then two fitting methods, the random period fitting method and the conditional curve fitting method, using the estimated periods as the initial values, were applied to the control and the stimulated expression data to estimate the periods and the phases. Finally, by comparing the two sets of periods and phases, the period change and the phase shift by stimuli were estimated to extract the candidate genes related to the master clock, by mapping the period change and the phase shift on a two-dimensional space, a period?phase map (PPM). As an indirect validation of the genes selected by our method, the significant enrichment of extracted gene clusters on the PPM was further evaluated, in terms of biological function. As a result, the gene clusters related to photoreceptors and neural regulation emerged on the PPM, thus implying the relationships in the stimulus response of the master clock that resides in the brain at the intersection of the optic nerves. Thus, the present approach is a feasible means to explore the oscillatory genes related to stimulus responses.     

Phase tracking and restoration of circadian rhythms by model-based optimal control

Periodic cellular processes and especially circadian rhythms governed by the oscillating expression of a set of genes based on feedback regulation by their products have become an important issue in biology and medicine. The central circadian clock is an autonomous biochemical oscillator with a period close to 24 h. Research in chronobiology demonstrated that light stimuli can be used to delay or advance the phase of the oscillator, allowing it to influence the underlying physiological processes. Phase shifting and restoration of altered rhythms can generally be viewed as open-loop control problems that may be used for therapeutic purposes in diseases. A circadian oscillator model of the central clock mechanism is studied for the fruit fly Drosophila and show how model-based mixed-integer optimal control allows for the design of chronomodulated pulse-stimuli schemes achieving circadian rhythm restoration in mutants and optimal phase synchronisation between the clock and its environment.     

Synchronisation mechanisms of circadian rhythms in the suprachiasmatic nucleus

In mammals, the suprachiasmatic nucleus (SCN) of the hypothalamus is considered as the master circadian pacemaker. Each cell in the SCN contains an autonomous molecular clock, and the SCN is composed of multiple single-cell circadian oscillators. The fundamental question is how the individual cellular oscillators, expressing a wide range of periods, interact and assemble to create an integrated pacemaker that can govern behavioural and physiological rhythmicity and be reset by environmental light. The key is that the heterogeneous network formed by the cellular clocks within the SCN must synchronise to maintain timekeeping activity. To study the synchronisation mechanisms and the circadian rhythm generation, we propose a model based on the structural and functional heterogeneity of the SCN. The model is a heterogeneous network of circadian oscillators in which individual oscillators are self-sustained. The authors show that the dorsomedial region can smooth the periodic light?dark (LD) signal curve and affect its wave form. The authors also study the rhythmic process of the circadian oscillators under the effect of the daily LD cycle, including three courses: information afferent inputs, oscillation and information efferent outputs. The numerical simulations are also given to demonstrate the theoretical results.     

Systems biology of the neurospora biological clock

A major challenge of systems biology is explaining complex traits, such as the biological clock, in terms of the kinetics of macromolecules. The clock poses at least four challenges for systems biology: (i) identifying the genetic network to explain the clock mechanism quantitatively; (ii) specifying the clock's functional connection to a thousand or more genes and their products in the genome; (iii) explaining the clock's response to light and other environmental cues; and (iv) explaining how the clock's genetic network evolves. Here, the authors illustrate an approach to these problems by fitting an ensemble of genetic networks to microarray data derived from oligonucleotide arrays with approximately all 11 000 Neurospora crassa genes represented. A promising genetic network for the clock mechanism is identified.