Cordwell S J, Humphery-Smith I
Centre for Proteome Research and Gene-Product Mapping, National Innovation Centre, Eveleigh, Australia.
Electrophoresis. 1997 Aug;18(8):1410-7. doi: 10.1002/elps.1150180816.
The ability to effectively search databases for the identification of protein spots from two-dimensional electrophoresis gels has become an essential step in the study of microbial proteomes. A variety of analytical techniques are currently being employed during protein characterisation. A number of algorithms used to search databases, accessible via the World Wide Web, depend upon information concerning N- and C-terminal microsequence, amino acid composition, and peptide-mass fingerprinting. The effectiveness of nine such algorithms, as well as COMBINED (software developed in this laboratory for identifying proteins across species boundaries) was examined. Fifty-four ribosomal proteins from the Mycoplasma genitalium genome, and 72 amino acyl tRNA synthetases from the Haemophilus influenzae, M. genitalium and Methanococcus jannaschii genomes were chosen for study. These proteins were selected because they represent a wide range of sequence identities across species boundaries (22.7-100% identity), as detected by standard sequence alignment tools. Such sequence variation allowed for a statistical comparison of algorithm success measured against published sequence identity. The ability of analytical techniques used in protein characterisation and associated database query programs to detect identity at the functional group level was examined for proteins with low levels of homology at the gene/protein sequence level. The significance of these theoretical data manipulations provided the means to predict the utility of data acquired experimentally for non-sequence-dependent software in proteome analysis. The data obtained also predicted that 'sequence tagging' of peptide fingerprints would need to be accompanied by at least 11-20 residues of amino acid sequence for it to be widely used for protein characterisation across species boundaries.
能够有效地在数据库中搜索以从二维电泳凝胶中鉴定蛋白质斑点，已成为微生物蛋白质组研究中的关键步骤。目前在蛋白质表征过程中采用了多种分析技术。许多用于搜索可通过万维网访问的数据库的算法，依赖于有关N端和C端微序列、氨基酸组成以及肽质量指纹图谱的信息。研究了九种此类算法以及COMBINED（本实验室开发的用于跨物种鉴定蛋白质的软件）的有效性。选择了来自生殖支原体基因组的54种核糖体蛋白，以及来自流感嗜血杆菌、生殖支原体和詹氏甲烷球菌基因组的72种氨酰tRNA合成酶进行研究。选择这些蛋白质是因为通过标准序列比对工具检测到，它们代表了跨物种的广泛序列同一性（同一性为22.7%-100%）。这种序列变异允许对根据已发表的序列同一性衡量的算法成功率进行统计比较。对于在基因/蛋白质序列水平上具有低同源性的蛋白质，研究了蛋白质表征中使用的分析技术和相关数据库查询程序在功能基团水平上检测同一性的能力。这些理论数据操作的意义提供了预测实验获得的数据在蛋白质组分析中对非序列依赖性软件的效用手段。获得的数据还预测，肽指纹图谱的“序列标签”需要伴随至少11-20个氨基酸序列残基，才能广泛用于跨物种的蛋白质表征。
