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Green Targeting Predictor and Ambiguous Targeting Predictor 2: the pitfalls of plant protein targeting prediction and of transient protein expression in heterologous systems
Author(s) -
Fuss Janina,
Liegmann Oliver,
Krause Kirsten,
Rensing Stefan A.
Publication year - 2013
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.12433
Subject(s) - physcomitrella patens , in silico , biology , heterologous , computational biology , arabidopsis thaliana , arabidopsis , heterologous expression , systems biology , genetics , gene , recombinant dna , mutant
Summary The challenges of plant protein targeting prediction are the existence of dual subcellular targets and the bias of experimentally confirmed data towards few and mostly nonplant model species. To assess whether training with proteins from evolutionarily distant species has a negative impact on prediction accuracy, we developed the Green Targeting Predictor tool, which was trained with a species‐specific data set for Physcomitrella patens . Its performance was compared with that of the same tool trained with a mixed data set. In addition, we updated the Ambiguous Targeting Predictor. We found that predictions deviated from in vivo observations predominantly for proteins diverging within the green lineage, as well as for dual targeted proteins. To evaluate the usefulness of heterologous expression systems, selected proteins were subjected to localization studies in P. patens , Arabidopsis thaliana and Nicotiana tabacum . Four out of six proteins that show dual targeting in the original plant system were located only in a single compartment in one or both heterologous systems. We conclude that targeting signals of divergent plant species exhibit differences, calling for custom in silico and in vivo approaches when aiming to unravel the actual distribution patterns of proteins within a plant cell.

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