人博卡病毒2基因组扩增及序列分析

为获得人博卡病毒2(Human bocavirus 2,HBoV2)基因组序列,以2010年HBoV2单阳粪便标本为材料,PCR方法扩增HBoV2基因组不同区域,经序列拼接后得到5444bp的全基因组序列(HBoV2-NC)。系统进化分析显示,HBoV2-NC与兰州株HBoV2亲缘关系最近;DINAMelt末端回文结构预测证实,HBoV2-NC 5′末端存在反向互补序列,具有典型的细小病毒末端的茎环样结构;接头法PCR扩增得到HBoV2-NC部分末端侧翼序列。     

BOX-PCR技术在微生物多样性研究中的应用

近年来在微生物多样性研究中,利用微生物基因组中广泛分布的短重复序列设计引物,选择性地扩增重复序列之间的不同基因区域,以得到大小不等的DNA扩增片段的方法日渐增多.以BOX插入因子(细菌基因组重复序列)为基础的PCR技术,具有操作简单快捷,可重复性强,容易获得较为丰富的扩增条带等特点,最初主要应用于细菌的多样性研究.目前研究发现用BoxA1R引物对微生物中的真菌、放线菌进行选择性的扩增,也能够达到很好的遗传及多样性分析的目的.本文综述了BOX-PCR指纹图谱分析技术的特点和一般步骤;结合作者对植物内生细菌的BOX-PCR指纹图谱分析体系的优化,对BOX-PCR技术的改进进行了总结:并对该技术在微生物菌株多样性研究领域的应用现状和前景进行了阐述.     

正反向测序信息在全基因组序列拼接及分析中的应用

插入片段双末端正反向测序信息(double-barreled data, DB信息)已广泛应用于大基因组测序组装项目. 根据绘制籼稻全基因组工作框架图的经验, 总结了DB信息在序列组装流程中的应用, 同时, 在原有基础上提出了改进的DB信息使用方法, 包括基因组序列拼接、质量检验和重叠群的连接. 此外, 进一步提出了DB信息在下游数据分析过程中新的应用, 包括利用DB信息获得基因组文库中每个克隆所包含的基因组片段的精确信息, 以及在此基础上设计低成本全基因组基因芯片的一种基因芯片设计新方法. 随着待测序物种的逐年增多, 相信正反向测序信息在基因组测序组装工作, 以及后续的基因组研究中将发挥越来越重要的作用.     

基因组结构信息在动物系统发育研究中的应用

随着人类基因组和一些模式生物、重要经济生物以及大量微生物基因组测序的完成,生物学整体研究业已进入基因组时代.最近5～10年以来,利用基因组结构信息进行系统发育推断的研究形成了分类学和进化生物学中的前沿领域之一.相对于核苷酸或氨基酸序列中的突变而言,基因组的结构变化--内含子的插入/缺失、反转录子的整合、签名序列、基因重复以及基因排序等--是更大空间(或者时间空间)尺度上的相对稀缺的系统发育信息,一般用于科和科以上阶元间的亲缘关系研究.基因组全序列的获得和其中各基因位置的确定有利于将基因组中不同层次的系统发育信息综合起来,利用全面分子证据(total molecular evidence;包括基因组信息,DNA、RNA、蛋白质的序列信息,RNA和蛋白质的高级结构等)进行分子系统学研究.     

研发动态

中国烟草基因组数据库(1.0版)开放运行中国烟草基因组数据库(1.0版)近日面向行业开放运行。数据库设在国家烟草基因研究中心,储存了去年底绘制的绒毛状烟草和林烟草全基因组序列图谱的所有原始数据以及基因注释结果,总数据量将近7T。这两张序列图谱是目前已知植物基因组序列图谱中基因组最大、组装精度最高、组装     

鹅源腺病毒基因组DNA物理图谱的构建

将鹅源腺病毒Y81G4株全基因组DNA的HindⅢ酶切片段分别插入质粒pUC18, 成功构建了全基因组DNA文库.在此基础上,将重组质粒携带的插入片段切出、回收并分别用地高辛标记后作为探针,与经限制酶BamHI、EcoRI、PstI、Eco RV消化的病毒基因组DNA进行Southern Blotting,杂交结果经比较综合后获得了该病毒基因组DNA的HindⅢ、Ba mH I、EcoR I、PstI、EcoR V限制性内切酶的物理图谱.利用已发表的含有鸡EDS76病毒AA-2 株基因组DNA右末端的重组质粒pBE42作为探针,与本病毒两末端重组质粒进行Southern Blo tting,根据同源性杂交结果确定了本病毒基因组DNA物理图谱与EDSVAA-2株相应的方向. 本病毒基础因组DNA物理图谱的精确构建,为进行基因组结构分析,筛选复制非必需区,构建禽腺病毒载体打下了基础.     

美国能源部资助的微生物基因组研究概况

自 1 995年 1 2月完成第一个微生物 (流感嗜血杆菌 )全基因组测序以来[1] ,微生物基因组学策略和技术提高很快 ,促进了其他生命形式 (包括人类 )的基因组学发展 ,开创了生物基因组计划新时代[2 ] 。短短几年内 ,互联网数据库中各种生物基因组数据迅速增长。 1 998年 2月 2 0日美国Ｓｃｉｅｎｃｅ杂志评选的当年世界十大科技进展 ,将微生物基因组图谱的构建列为其中第六项 ,同年 3月 2 7日Ｓｃｉｅｎｃｅ杂志编者指出 :生物基因组革命可以同工业革命和计算机革命所带来的变化相比 ,是“第三次技术革命”[3 ] 。微生物全基因组测序 ,不仅是人…     

非模式细菌功能基因组获取策略比较

高通量测序技术的发展以及成本的降低使得细菌基因组测序成为研究细菌的标准流程。但细菌基因组变异度大,近缘基因组修正以及基因组从头拼接各有利弊,如何准确获得更多的有效功能基因尚无系统性的研究。本研究对真实环境中分离的一株短小芽孢杆菌(Bacillus pumilus)进行基因组测序,使用近缘基因组修正、基因组从头拼接、修正完剩下的reads再拼接(修正+拼接)这3种策略进行对比拼接,评价各策略的效能:近缘基因组修正获得原有标准基因组中已有的基因更准确;基因组从头拼接能获得大部分有效基因,但会引入大量的假阳性;修正+拼接策略可兼顾二者,但引入的假阳性也是最多的。分析还发现,注释到门以下的拼接结果可靠性高,有效减少拼接引入的假阳性。本研究为环境微生物研究提供策略指导,将促进环境微生物功能基因组的研究。     

用ERIC-PCR结合分子杂交监测焦化废水处理系统(A2/O)中微生物群落结构的变化

建立一种不依赖纯培养 ,可以在废水处理工业现场使用的监测微生物群落结构变化的分子技术。以处理焦化工业废水(A2 /O生物膜工艺 )不同构筑物中的悬浮污泥的微生物群落为研究对象 ,每周采样 1次 ,连续 4周。获得悬浮污泥总 DNA的ERIC- PCR指纹图谱 ,结合分子杂交进一步区分相同条带间的不同序列信息。结果表明 ,在缺氧池 (A2池 )和好氧池 (O池 )之间 ,各个采样点的 ERIC- PCR图谱差异不大 ,悬浮污泥在各构筑物之间交流充分 ;同一采样点的图谱在不同采样时期具有明显差异 ,显示了在此期间微生物群落的连续动态变化过程。通过对生物膜系统中悬浮污泥的微生物群落结构的指纹图谱分析 ,可开发出对该系统微生物群落结构动态变化进行检测的技术     

医学遗传学2.0:导致人类慢病的主因可能首先是人体共生微生物基因异常,其次才是人类基因异常

当前慢病高发的现实对"健康中国2030"战略目标的实现提出了巨大挑战。虽然众多医疗机构和政府管理部门付出巨大努力,然而如果仍然沿袭现有慢病防控模式和医疗改革理念,恐怕很难在近期内实现慢病防控的突破,迫切需要引入新思路,才有可能破解慢病高发这个难题。根据近年来国内外大量报道人体共生微生物尤其是肠道菌群与人体多种慢病之间存在密切相关性甚至因果性的研究进展,以及在此启发下我们实验室通过大量研究发现"饥饿源于菌群",结合诸多文献报道证明通过调控肠道菌群微生态可改善多种慢病,为"慢病源于菌群"提供了重要依据,从而提出"医学遗传学2.0"(Medical genetics 2.0, MG2.0)的概念,其核心思想是将复杂性疾病(主要指慢病)的致病因素优先归因于人体共生微生物尤其是肠道菌群基因组异常,而人类基因组异常则是跟随前者发生顺应性改变的结果,即人体共生微生物基因组异常是慢病的主要矛盾,人类自身的基因组异常是慢病的次要矛盾,两套基因组通过联立交互作用,最终导致人体慢病持续发展。如果只是通过纠正人类基因组异常,而忽视了纠正菌群基因组异常,则难以从根本上治疗慢病,因为异常的菌群基因组仍然会持续影响人体健康。因此,在慢病防控方面,建议医学遗传学领域的研究重点可向肠道菌群等人体共生微生物领域进行深化,广泛开展以人体共生微生物尤其是肠道菌群基因组为主、人类基因组为辅的人菌双基因组关联分析研究,建立不同慢病的菌群图谱(含基因组学、转录组学、蛋白质组学、代谢组学以及生命组学等相关研究),并研究纠正异常菌群图谱的方法(含靶向肠道菌群的新药研发),为慢病防控找到新出路。     

MGView: an alignment and visualization tool to enhance gap closure of microbial genomes

Gap closure is a challenging phase in microbial random shotgun genome sequencing projects, particularly since genome assemblies are often complicated by the presence of repeat elements, insertion sequences and other similar factors that contribute to sequence misassemblies. While it is well recognized that the conservation of genetic information between microbial genomes, combined with the exponential increase in available microbial sequences, can be exploited to increase the efficiency of gap closure, we lack the computational tools to aid in this process. We describe here a new tool, MGView, which was developed to create a graphical depiction of the alignment of a set of microbial contigs against a completed microbial genome. The results of our assembly of the Staphylococcus aureus RF122 genome show that MGView enables a considerable reduction in time and economic cost associated with closure. Together, the results also show that the application of MGView not only enables a reduction in fold-coverage requirements of the random shotgun sequence phase, but also provides interesting insights into differences in gene content and organization between finished and unfinished microbial genomes.     

微生物单细胞基因组技术及其在环境微生物研究中的应用

单细胞及单细胞基因组学研究是近年生命科学研究的热点之一,微生物单细胞基因组学研究是继微生物元基因组学(又称宏基因组学,Metagenomics)之后新发展起来的,可有效获取环境中大量无法培养的微生物遗传信息的技术。微生物单细胞基因组技术包括单细胞获取、全基因组扩增、全基因组测序以及数据分析等步骤,目前该技术在环境微生物研究中的应用主要集中于探索未被元基因组技术或其它常规技术探测到的新型功能基因,或是对环境中物种丰度极小的未培养微生物的发现,以及对微生物细胞生命进化过程的研究等。本文对微生物单细胞基因组技术中单细胞获取和全基因组扩增所涉及到的不同方法以及应用此技术对环境微生物取得的主要研究进展进行综述。     

Use of genome-scale metabolic models for understanding microbial physiology

The exploitation of microorganisms in industrial, medical, food and environmental biotechnology requires a comprehensive understanding of their physiology. The availability of genome sequences and accumulation of high-throughput data allows gaining understanding of microbial physiology at the systems level, and genome-scale metabolic models represent a valuable framework for integrative analysis of metabolism of microorganisms. Genome-scale metabolic models are reconstructed based on a combination of genome sequence information and detailed biochemical information, and these reconstructed models can be used for analyzing and simulating the operation of metabolism in response to different stimuli. Here we discuss the requirement for having detailed physiological insight in order to exploit microorganisms for production of fuels, chemicals and pharmaceuticals. We further describe the reconstruction process of genome-scale metabolic models and different algorithms that can be used to apply these models to gain improved insight into microbial physiology.     

Whole gene amplification and protein separation from a few cells

Despite the growing interest to explore untapped microbial gene and protein diversity, no single platform has been able to acquire both gene and protein information from just a few cells. We present a microfluidic system that simultaneously performs on-chip capillary electrophoresis for protein analysis and whole genome amplification (WGA), and we demonstrate this by doing both for the same cohort of cyanobacterial cells. This technology opens avenues for studying protein profiles of precious environmental microbial samples and simultaneously accessing genomic information based on WGA.     

Genetic comparison of Bacillus anthracis and its close relatives using amplified fragment length polymorphism and polymerase chain reaction analysis

Amplified fragment length polymorphism (AFLP) analysis allows a rapid, relatively simple analysis of a large portion of a microbial genome, providing information about the species and its phylogenetic relationship to other microbes (Vos et al. 1995). The method simply surveys the genome for length and sequence polymorphisms. The AFLP pattern identified can be used for comparison to the genomes of other species. Unlike other methods, it does not rely on analysis of a single genetic locus that may bias the interpretation of results and does not require any prior knowledge of the targeted organism. Moreover, a standard set of reagents can be applied to any species without using species-specific information or molecular probes. We are using AFLP analysis to rapidly identify different bacterial species. A comparison of AFLP profiles generated from a large battery of Bacillus anthracis strains shows very little variability among different isolates (Keim et al. 1997). By contrast, there is a significant difference between AFLP profiles generated for any B. anthracis strain and even the most closely related Bacillus species. Sufficient variability is apparent among all known microbial species to allow phylogenetic analysis based on large numbers of genetically unlinked loci. These striking differences among AFLP profiles allow unambiguous identification of previously identified species and phylogenetic placement of newly characterized isolates relative to known species based on a large number of independent genetic loci. Data generated thus far show that the method provides phylogenetic analyses that are consistent with other widely accepted phylogenetic methods. However, AFLP analysis provides a more detailed analysis of the targets and samples a much larger portion of the genome. Consequently, it provides an inexpensive, rapid means of characterizing microbial isolates to further differentiate among strains and closely related microbial species. Such information cannot be rapidly generated by other means. AFLP sample analysis quickly generates a very large amount of molecular information about microbial genomes. However, this information cannot be analysed rapidly using manual methods. We are developing a large archive of electronic AFLP signatures that is being used to identify isolates collected from medical, veterinary, forensic and environmental samples. We are also developing the computational packages necessary to rapidly and unambiguously analyse the AFLP profiles and conduct a phylogenetic comparison of these data relative to information already in our database. We will use this archive and the associated algorithms to determine the species identity of previously uncharacterized isolates and place them phylogenetically relative to other microbes based on their AFLP signatures. This study provides significant new information about microbes with environmental, veterinary and medical significance. This information can be used in further studies to understand the relationships among these species and the factors that distinguish them from one another. It should also allow the identification of unique factors that contribute to important microbial traits, including pathogenicity and virulence. We are also using AFLP data to identify, isolate and sequence DNA fragments that are unique to particular microbial species and strains. The fragment patterns and sequence information provide insights into the complexity and organization of bacterial genomes relative to one another. They also provide the information necessary for the development of species-specific polymerase chain reaction primers that can be used to interrogate complex samples for the presence of B. anthracis, other microbial pathogens or their remnants.     

Integrated Artificial Intelligence Approaches for Disease Diagnostics

Mechanocomputational techniques in conjunction with artificial intelligence (AI) are revolutionizing the interpretations of the crucial information from the medical data and converting it into optimized and organized information for diagnostics. It is possible due to valuable perfection in artificial intelligence, computer aided diagnostics, virtual assistant, robotic surgery, augmented reality and genome editing (based on AI) technologies. Such techniques are serving as the products for diagnosing emerging microbial or non microbial diseases. This article represents a combinatory approach of using such approaches and providing therapeutic solutions towards utilizing these techniques in disease diagnostics.     

Structural genomics of microbes: an objective

A comparison of the genome sequences of more than 20 microorganisms reveals that a large fraction of the genes have unknown functions. Determining the structures of the proteins coded by these genes may provide additional key information in an effort to uncover the molecular functions of such proteins and new protein fold patterns. Using existing technology, it is possible to obtain a complete sequence complement and a near complete structural complement for a small microbial genome. Such information may provide a comprehensive view of a small organism, which, in turn, can serve as a platform for understanding more complex organisms.     

Microbial genomics: rhetoric or reality?

The availability of complete genome sequences of many bacterial species is facilitating numerous computational approaches for understanding bacterial genomes. One of the major incentives behind the genome sequencing of many pathogenic bacteria is the desire to better understand their diversity and to develop new approaches for controlling human diseases caused by these microorganisms. This task has become even more urgent with the rapid evolution of antibiotic resistance among many bacterial pathogens. Novel drug targets are required in order to design new antimicrobials against antibiotic-resistant pathogens. The complete genome sequences of an ever increasing number of pathogenic microbes constitute an invaluable resource and provide lead information on potential drug targets. This review focuses on in silico analyses of microbial genomes, their host-specific adaptations, with specific reference to genome architecture, design, evolution, and trends in computational identification of microbial drug targets. These trends underscore the utility of genomic data for systematic in silico drug target identification in the post-genomic era.     

Construction and analysis of bacterial artificial chromosome libraries from a marine microbial assemblage

Cultivation-independent surveys of ribosomal RNA genes have revealed the existence of novel microbial lineages, many with no known cultivated representatives. Ribosomal RNA-based analyses, however, often do not provide significant information beyond phylogenetic affiliation. Analysis of large genome fragments recovered directly from microbial communities represents one promising approach for characterizing uncultivated microbial species better. To assess further the utility of this approach, we constructed large-insert bacterial artificial chromosome (BAC) libraries from the genomic DNA of planktonic marine microbial assemblages. The BAC libraries we prepared had average insert sizes of 80 kb, with maximal insert sizes > 150 kb. A rapid screening method assessing the phylogenetic diversity and representation in the library was developed and applied. In general, representation in the libraries agreed well with previous culture-independent surveys based on polymerase chain reaction (PCR)amplified rRNA fragments. A significant fraction of the genome fragments in the BAC libraries originated from as yet uncultivated microbial species, thought to be abundant and widely distributed in the marine environment. One entire BAC insert, derived from an uncultivated, surface-dwelling euryarchaeote, was sequenced completely. The planktonic euryarchaeal genome fragment contained some typical archaeal genes, as well as unique open reading frames (ORFs) suggesting novel function. In total, our results verify the utility of BAC libraries for providing access to the genomes of as yet uncultivated microbial species. Further analysis of these BAC libraries has the potential to provide significant insight into the genomic potential and ecological roles of many indigenous microbial species, cultivated or not.