Bayram Helen L, Claydon Amy J, Brownridge Philip J, Hurst Jane L, Mileham Alan, Stockley Paula, Beynon Robert J, Hammond Dean E
Mammalian Behaviour and Evolution Group, Institute of Integrative Biology, University of Liverpool, Leahurst Campus, Neston CH64 7TE, UK.
Centre for Proteome Research, Institute of Integrative Biology, University of Liverpool, Liverpool L69 7ZB, UK.
J Proteomics. 2016 Mar 1;135:38-50. doi: 10.1016/j.jprot.2015.12.027. Epub 2016 Jan 6.
Many proteomics studies are conducted in model organisms for which fully annotated, detailed, high quality proteomes are available. By contrast, many studies in ecology and evolution are conducted in species which lack high quality proteome data, limiting the perceived value of a proteomic approach for protein discovery and quantification. This is particularly true of rapidly evolving proteins in the reproductive system, such as those that have an immune function or are under sexual selection, and can compromise the potential for cross-species proteomics to yield confident identification. In this investigation we analysed the sperm proteome, from a range of ungulates and rodents, and explored the potential of routine proteomic workflows to yield characterisation and quantification in non-model organisms. We report that database searching is robust to cross-species matching for a mammalian core sperm proteome, comprising 623 proteins that were common to most of the 19 species studied here, suggesting that these proteins are likely to be present and identifiable across many mammalian sperm. Further, label-free quantification reveals a consistent pattern of expression level. Functional analysis of this core proteome suggests consistency with previous studies limited to model organisms and has value as a quantitative reference for analysis of species-specific protein characterisation.
From analysis of the sperm proteome for diverse species (rodents and ungulates) using LC-MS/MS workflows and standard data processing, we show that it is feasible to obtain cross-species matches for a large number of proteins that can be filtered stringently to yield a highly expressed mammalian sperm core proteome, for which label-free quantitative data are also used to inform protein function and abundance.
许多蛋白质组学研究是在具有完全注释、详细且高质量蛋白质组的模式生物中进行的。相比之下,许多生态学和进化领域的研究是在缺乏高质量蛋白质组数据的物种中开展的,这限制了蛋白质组学方法在蛋白质发现和定量方面的可感知价值。对于生殖系统中快速进化的蛋白质来说尤其如此,比如那些具有免疫功能或处于性选择之下的蛋白质,这可能会影响跨物种蛋白质组学进行可靠鉴定的潜力。在本研究中,我们分析了一系列有蹄类动物和啮齿动物的精子蛋白质组,并探讨了常规蛋白质组学工作流程在非模式生物中进行表征和定量的潜力。我们报告称,对于一个包含623种蛋白质的哺乳动物核心精子蛋白质组,数据库搜索在跨物种匹配方面表现稳健,这623种蛋白质在我们研究的19个物种中的大多数中都很常见,这表明这些蛋白质很可能存在于许多哺乳动物的精子中并且能够被鉴定出来。此外,无标记定量揭示了一致的表达水平模式。对这个核心蛋白质组的功能分析表明,它与之前仅限于模式生物的研究结果一致,并且作为分析物种特异性蛋白质特征的定量参考具有价值。
通过使用液相色谱 - 串联质谱工作流程和标准数据处理对不同物种(啮齿动物和有蹄类动物)的精子蛋白质组进行分析,我们表明对于大量蛋白质获得跨物种匹配是可行的,这些蛋白质可以经过严格筛选以产生一个高表达的哺乳动物精子核心蛋白质组,对于该蛋白质组,无标记定量数据还可用于了解蛋白质功能和丰度。