BBReader: A computer program for the combined use of the BioMagResBank and PDB databases

A computer program (BBReader) was developed which performs an inverse search in theBioMagResBank database. Given (cross) peak positions of a protein, the program searchesfor atoms with matching chemical shifts and suggests possible assignments for user-specifiedhomo- and heteronuclear one- to three-dimensional COSY- and NOESY-type experiments.It can handle 1H, 13C and 15N spectra. Distance information from PDB files can be utilizedfor filtering possible NOESY cross peak assignments.     

The SEA module: a new extracellular domain associated with O-glycosylation.

Using a variety of homology search methods and multiple alignments, a new extracellular module was identified in (1) agrin, (2) enterokinase, (3) a 63-kDa sea urchin sperm protein, (4) perlecan, (5) the breast cancer marker MUCI (episialin), (6) the cell surface antigen 114/A10, and (7/8) two functionally uncharacterized, probably extracellular, Caenorhabditis elegans proteins. Despite the functional diversity of these adhesive proteins, a common denominator seems to be their existence in heavily glycosylated environments. In addition, the better characterized proteins mentioned above contain all O-glycosidic-linked carbohydrates such as heparan sulfate that contribute considerably to their molecular masses. The common module might regulate or assist binding to neighboring carbohydrate moieties.     

Planning an adaptive numerical classification

Summary While numerical methods of classification seek to strictly formalise one part of the classificatory process, a human classifier uses a variety of different approaches to obtain a satisfactory organisation of data. In this paper some means of increasing the flexibility of numerical methods are discussed, in particular the possible uses of the taxonomic hierarchy. It is first necessary to show that higher taxonomic units contain ecologically interesting information. Then, using a two parameter classification method a means of progressing from higher to lower taxonomic units, during analysis and in a data dependent manner, is outlined. A similar procedure is possible with nested samples. However, since the value of a classification resides in its ecological interpretation, an automatic classification requires some means of ascribing meanings to classes. While such a semantic analysis seems theoretically possible, its practical attainment presents considerable difficulties.Contribution to the Symposium on Plant species and plant communities, held at Nijmegen, 11–12 November 1976, on the occasion of the 60th birthday of Professor Victor Westhoff.     

Quantitative Metaproteomics and Activity-based Protein Profiling of Patient Fecal Microbiome Identifies Host and Microbial Serine-type Endopeptidase Activity Associated With Ulcerative Colitis

The gut microbiota plays an important yet incompletely understood role in the induction and propagation of ulcerative colitis (UC). Organism-level efforts to identify UC-associated microbes have revealed the importance of community structure, but less is known about the molecular effectors of disease. We performed 16S rRNA gene sequencing in parallel with label-free data-dependent LC-MS/MS proteomics to characterize the stool microbiomes of healthy (n = 8) and UC (n = 10) patients. Comparisons of taxonomic composition between techniques revealed major differences in community structure partially attributable to the additional detection of host, fungal, viral, and food peptides by metaproteomics. Differential expression analysis of metaproteomic data identified 176 significantly enriched protein groups between healthy and UC patients. Gene ontology analysis revealed several enriched functions with serine-type endopeptidase activity overrepresented in UC patients. Using a biotinylated fluorophosphonate probe and streptavidin-based enrichment, we show that serine endopeptidases are active in patient fecal samples and that additional putative serine hydrolases are detectable by this approach compared with unenriched profiling. Finally, as metaproteomic databases expand, they are expected to asymptotically approach completeness. Using ComPIL and de novo peptide sequencing, we estimate the size of the probable peptide space unidentified (“dark peptidome”) by our large database approach to establish a rough benchmark for database sufficiency. Despite high variability inherent in patient samples, our analysis yielded a catalog of differentially enriched proteins between healthy and UC fecal proteomes. This catalog provides a clinically relevant jumping-off point for further molecular-level studies aimed at identifying the microbial underpinnings of UC.     

参数序列比对算法研究

序列比对是生物信息学中的一项重要任务,通过序列比对可以发现生物序列中的功能、结构和进化的信息。序列比对结果的生物学意义与所选择的匹配、不匹配、插入和删除以及空隙的罚分函数密切相关。现介绍一种参数序列比对方法,该方法把最佳比对作为权值和罚分的函数,可以系统地得到参数的选择对最佳比对结果的影响。然后将其应用于RNA序列比对,分析不同的参数选择对序列比对结果的影响。最后指出参数序列比对算法的应用以及未来的发展方向。     

Strategic mining of cyanobacterial patents from the USPTO patent database and analysis of their scope and implications

Patent analysis with the help of the strategic mining of patents from databases is important and useful within the framework of application-oriented research and its commercialization. In the analysis reported here, we have mined cyanobacterial patents from the patent database of the United States Patent and Trademark Office (USPTO). In order to make an assessment of the commercial potentials of cyanobacteria, we conducted the patent search (from 1976 to April 2006) using certain generic terms and the 84 genera of cyanobacteria as keywords. The search was performed in two major ways – searching the abstracts and claims of the patents cumulatively and searching the entire patent documents by the mode of ‘all fields’ in USPTO. In the abstract- and claims-based search, 234 patents were obtained after the removal of overlapping patents among the keywords. An additional 31 patents were added following the ‘all fields’ search; these patents were not covered in the search that was based on abstracts and claims. The entire package of 265 patents, of which 244 were related to cyanobacteria, was then analyzed. Information derived from these patents identified five major areas of cyanobacterial utilization. Cyanobacteria have been patented as a source of a wide spectrum of products, for medical, agriculture and environmental applications, for gene-based products, for methods of cultivation and for methods of control. The chronological development in granting cyanobacterial patents was also traced. This study demonstrates that such strategic mining and analysis of patent data can be used as an index for future development.     

dbEST‐derived microsatellite markers in celery (Apium graveolens L. var. dulce)

We report on the development of 11 (from database expressed sequence tags) dbEST‐derived microsatellite markers in celery (Apium graveolens L. var. dulce). The sequences were obtained from DNA accessions available from GenBank and contained di‐, tri‐ and pentanucleotidic motifs. All the microsatellites were found in expressed sequence tags and they are expected to become useful tools for ecological, genetic and evolutionary studies, as well as for celery breeding. Polymorphism was explored in 16 celery commercial varieties, and marker transferability was tested on three accessions of celeriac (A. graveolens var. rapaceum). Primers and PCR conditions for microsatellite amplification are reported.     

基于空间生态集合覆盖模型的自学习禁忌搜索算法在保护区空间选址中的应用——以戴云山为例

自然保护区规划是保护生物多样性的有效方式.传统保护区规划方法只能识别物种保护的重点区域,无法科学确定保护区的适宜面积.地块选择方法基于数学模型,从规划区域中选择部分地块组成自然保护区,保护特定物种或生态系统,是缓解生态保护与开发利用矛盾的重要手段.现有地块选择法未考虑各单元生态差异,且最优化算法存在计算效率的瓶颈.本文首先构建适用于森林生态系统的生态值赋分评价体系,据此计算戴云山生态值并绘制其分布图;然后,结合生态值建立生态集合覆盖模型(ESCP),并基于ESCP嵌入空间紧凑性提出空间生态集合覆盖模型(SSCP);最后,利用寻优性能良好的自学习禁忌搜索算法(STS)搜索各保护目标下的近似最优选址方案,给出福建省戴云山现有建成区优化方案.结果表明: 戴云山生态值计算结果在空间分布上存在明显差异;ESCP比原集合覆盖模型(SCP)能产生生态值更高的选址方案;SSCP在ESCP基础上对生态值较高区域有聚集作用,且周长权重越大,聚集效果越明显;建议现保护区可向外拓展136 km²,并将西北向分布长苞铁杉的地块纳入保护区范围.研究结果为实现戴云山保护区可持续发展及土地资源优化配置提供了优化方案,也可为我国森林生态系统类型的自然保护区设计提供新思路.     

Telomere Recognition and Assembly Mechanism of Mammalian Shelterin

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褐飞虱EST资源的微卫星信息分析

表达序列标签（expressed sequence tags,ESTs）是开发微卫星标记的一个重要的资源。褐飞虱Nilaparvata lugens （Stål） EST序列的公布为开发EST-SSRs提供了宝贵的数据资源,本研究利用生物信息学对NCBI公共数据库中的37 398条褐飞虱ESTs序列进行EST-SSRs特征分析,得到全长为7 619 324 kb的无冗余EST 9 852条。按照3个不同的查找标准在这些序列中搜索SSR。查找结果显示：褐飞虱EST-SSRs主要重复基元以1～3碱基为主,占总EST-SSR的95％以上。在单碱基重复基元中,A/T是占优势的重复基元,在二相重复类型中,AG/CT重复基元出现的频率最多,而AAG/CTT是三相重复中占绝对优势的重复基元。在褐飞虱EST-SSRs中未查找到GC重复基元。以100 bp为参照,在3种查找标准下含有SSR的EST序列中两端侧翼序列均≥100 bp的序列分别为738,89和42个。通过分析褐飞虱EST-SSRs标记可以为褐飞虱和近缘种的SSR标记的开发提供信息,同时通过分析褐飞虱EST-SSRs的分布频率和分布特征可以为昆虫EST-SSRs的研究提供借鉴和参考。