Time-course investigation of Phytophthora infestans infection of potato leaf from three cultivars by quantitative proteomics

Abstract

Potato late blight is one the most important crop diseases worldwide. Even though potato has been studied for many years, the potato disease late blight still has a vast negative effect on the potato production [1–3]. Late blight is caused by the pathogen Phytophthora infestans (P. infestans), which initiates infection through leaves. However, the biological activities during different stages of infection are poorly described, and could enable novel or improved ways of defeating late blight infection [4]. Therefore, we investigated the interactions between P. infestans (mixed strain culture) and potato (Solanum tuberosum). Three commercially available field potato cultivars of different resistance to late blight infection; Kuras (moderate), Sarpo Mira (highly resistant) and Bintje (very susceptable) were grown under controlled green house conditions and inoculated with a diversity of P. infestans populations.We used label-free quantitative proteomics to investigate the infection with P. infestans in a time-course study over 258 h. Several key issues limits proteome analysis of potato leaf tissue [5–7]. Firstly, the immense complexity of the plant proteome, which is further complicated by the presence of highly abundant proteins, such as ribulose bisphosphate carboxylase/oxygenase (RuBisCO). Secondly, plant leaf and potato, in particular, contain abundant levels amounts of phenols and polyphenols, which hinder or completely prevent a successful protein extraction. Hitherto, protein profiling of potato leaf tissues have been limited to few proteome studies and only 1484 proteins have been extracted and comprehensively described [5,8,9]. We here present the detailed methods and raw data by optimized gel-enhanced label free quantitative approach. The methodology enabled us to detect and quantify between 3248 and 3529 unique proteins from each cultivar, and up to 758 P. infestans derived proteins. The complete dataset is available via ProteomeXchange, with the identifier http://www.ebi.ac.uk/pride/archive/projects/PXD002767.