Freitag Johannes, Stehlik Thorsten, Stiebler Alina C, Bölker Michael
Department of Biology, Philipps-Universität Marburg, Marburg, Germany.
Subcell Biochem. 2018;89:139-155. doi: 10.1007/978-981-13-2233-4_6.
Fungal peroxisomes are characterized by a number of specific biological functions. To understand the physiology and biochemistry of these organelles knowledge of the proteome content is crucial. Here, we address different strategies to predict peroxisomal proteins by bioinformatics approaches. These tools range from simple text searches to network based learning strategies. A complication of this analysis is the existence of cryptic peroxisomal proteins, which are overlooked in conventional bioinformatics queries. These include proteins where targeting information results from transcriptional and posttranscriptional alterations. But also proteins with low efficiency targeting motifs that are predominantly localized in the cytosol, and proteins lacking any canonical targeting information, can play important roles within peroxisomes. Many of these proteins are so far unpredictable. Detection and characterization of these cryptic peroxisomal proteins revealed the presence of novel peroxisomal enzymatic reaction networks in fungi.
真菌过氧化物酶体具有许多特定的生物学功能。要了解这些细胞器的生理学和生物化学,蛋白质组内容的知识至关重要。在此,我们探讨通过生物信息学方法预测过氧化物酶体蛋白的不同策略。这些工具从简单的文本搜索到基于网络的学习策略不等。该分析的一个复杂之处在于存在隐匿性过氧化物酶体蛋白,它们在传统的生物信息学查询中被忽视。这些包括其靶向信息源于转录和转录后改变的蛋白质。而且,具有低效率靶向基序且主要定位于细胞质中的蛋白质,以及缺乏任何典型靶向信息的蛋白质,也可在过氧化物酶体中发挥重要作用。到目前为止,许多这类蛋白质是无法预测的。对这些隐匿性过氧化物酶体蛋白的检测和表征揭示了真菌中存在新的过氧化物酶体酶促反应网络。