Tannu Nilesh S, Hemby Scott E
Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
BMC Genomics. 2007 Aug 8;8:270. doi: 10.1186/1471-2164-8-270.
Macaca mulatta is one of the most utilized non-human primate species in biomedical research offering unique behavioral, neuroanatomical, and neurobiochemcial similarities to humans. This makes it a unique organism to model various diseases such as psychiatric and neurodegenerative illnesses while also providing insight into the complexities of the primate brain. A major obstacle in utilizing rhesus monkey models for human disease is the paucity of protein annotations for this species (~42,000 protein annotations) compared to 330,210 protein annotations for humans. The lack of available information limits the use of rhesus monkey for proteomic scale studies which rely heavily on database searches for protein identification. While characterization of proteins of interest from Macaca mulatta using the standard database search engines (e.g., MASCOT) can be accomplished, searches must be performed using a 'broad species database' which does not provide optimal confidence in protein annotation. Therefore, it becomes necessary to determine partial or complete amino acid sequences using either manual or automated de novo peptide sequence analysis methods.
The recently popularized MALDI-TOF-TOF mass spectrometer yields a complex MS/MS fragmentation pattern difficult to characterize by manual de novo sequencing method on a proteomics scale. Therefore, PEAKS assisted de novo sequencing was performed on nucleus accumbens cytosolic proteins from Macaca mulatta. The most abundant peptide fragments 'b-ions and y-ions', the less abundant peptide fragments 'a-ions' as well as the immonium ions were utilized to develop confident and complete peptide sequences de novo from MS/MS spectra. The generated sequences were used to perform homology searches to characterize the protein identification.
The current study validates a robust method to confidently characterize the proteins from an incomplete sequence database of Macaca mulatta, using the PEAKS de novo sequencing software, facilitating the use of this animal model in various neuroproteomics studies.
猕猴是生物医学研究中使用最广泛的非人类灵长类动物之一,在行为、神经解剖学和神经生物化学方面与人类具有独特的相似性。这使其成为模拟各种疾病(如精神疾病和神经退行性疾病)的独特生物体,同时也有助于深入了解灵长类大脑的复杂性。与人类的330,210个蛋白质注释相比,利用恒河猴模型研究人类疾病的一个主要障碍是该物种的蛋白质注释较少(约42,000个蛋白质注释)。可用信息的缺乏限制了恒河猴在蛋白质组学规模研究中的应用,这类研究严重依赖数据库搜索来识别蛋白质。虽然使用标准数据库搜索引擎(如MASCOT)可以完成对猕猴中感兴趣蛋白质的表征,但搜索必须使用“广泛物种数据库”进行,而该数据库在蛋白质注释方面并不能提供最佳的可信度。因此,有必要使用手动或自动从头肽序列分析方法来确定部分或完整的氨基酸序列。
最近普及的基质辅助激光解吸电离飞行时间串联质谱仪产生了复杂的二级质谱碎裂模式,在蛋白质组学规模上难以通过手动从头测序方法进行表征。因此,对猕猴伏隔核胞质蛋白进行了PEAKS辅助从头测序。利用最丰富的肽片段“b离子和y离子”、较不丰富的肽片段“a离子”以及亚氨离子,从二级质谱谱图中从头开发出可靠且完整的肽序列。所生成的序列用于进行同源性搜索以表征蛋白质鉴定。
本研究验证了一种可靠的方法,即使用PEAKS从头测序软件,从猕猴不完整的序列数据库中可靠地表征蛋白质,这有助于在各种神经蛋白质组学研究中使用这种动物模型。