Abstract:
Most of the proteins that are specifically turned over by selective autophagy are recognized by
the presence of short Atg8 interacting motifs (AIMs) that facilitate their association with the
autophagy apparatus. Such AIMs can be identified by bioinformatics methods based on their
defined degenerate consensus F/W/Y-X-X-L/I/V sequences in which X represents any amino
acid. Achieving reliability and/or fidelity of the prediction of such AIMs on a genome-wide
scale represents a major challenge. Here, we present a bioinformatics approach, high fidelity
AIM (hfAIM), which uses additional sequence requirements—the presence of acidic amino
acids and the absence of positively charged amino acids in certain positions—to reliably
identify AIMs in proteins. We demonstrate that the use of the hfAIM method allows for in
silico high fidelity prediction of AIMs in AIM-containing proteins (ACPs) on a genome-wide
scale in various organisms. Furthermore, by using hfAIM to identify putative AIMs in the
Arabidopsis proteome, we illustrate a potential contribution of selective autophagy to various
biological processes. More specifically, we identified 9 peroxisomal PEX proteins that contain
hfAIM motifs, among which AtPEX1, AtPEX6 and AtPEX10 possess evolutionary-conserved
AIMs. Bimolecular fluorescence complementation (BiFC) results verified that AtPEX6 and
AtPEX10 indeed interact with Atg8 in planta. In addition, we show that mutations occurring
within or nearby hfAIMs in PEX1, PEX6 and PEX10 caused defects in the growth and
development of various organisms. Taken together, the above results suggest that the hfAIM
tool can be used to effectively perform genome-wide in silico screens of proteins that are
potentially regulated by selective autophagy. The hfAIM system is a web tool that can be
accessed at link: http://bioinformatics.psb.ugent.be/hfAIM/.
