Evidence map›Paper›PMID 27071037›Full record

ArticleAutophagy2016

hfAIM: A reliable bioinformatics approach for in silico genome-wide identification of autophagy-associated Atg8-interacting motifs in various organisms.

Qingjun Xie, Oren Tzfadia, Matan Levy, Efrat Weithorn, Hadas Peled-Zehavi, Thomas Van Parys, Yves Van de Peer, Gad Galili

Open access · bronzeAbstract read
In one paragraph

Article in Autophagy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed, 1 pooled it
6.9field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

  1. Guideline
  2. Building peroxisomes: perspectives on plant peroxins.Biochemical Society transactions · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
  16. Review
  17. Article
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 3 countries.

Qingjun Xiea Department of Plant and Environmental Science , Weizmann Institute of Science , Rehovotx , Israel.
Oren Tzfadiaa Department of Plant and Environmental Science , Weizmann Institute of Science , Rehovotx , Israel.
Matan Levya Department of Plant and Environmental Science , Weizmann Institute of Science , Rehovotx , Israel.
Efrat Weithorna Department of Plant and Environmental Science , Weizmann Institute of Science , Rehovotx , Israel.
Hadas Peled-Zehavia Department of Plant and Environmental Science , Weizmann Institute of Science , Rehovotx , Israel.
Thomas Van Parysb Department of Plant Systems Biology , VIB , Ghent , Belgium.
Yves Van de Peerb Department of Plant Systems Biology , VIB , Ghent , Belgium.
Gad Galilia Department of Plant and Environmental Science , Weizmann Institute of Science , Rehovotx , Israel.
Weizmann Institute of Science · ILVIB-UGent Center for Plant Systems Biology · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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/.

Indexed as

Adaptor Proteins, Signal TransducingArabidopsisAutophagyAutophagy-Related Protein 8 FamilyComputational BiologyGenome, FungalGenome, PlantProtein DomainsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsAdaptor Proteins, Signal TransducingAutophagy-Related Protein 8 FamilySaccharomyces cerevisiae ProteinsAIMArabidopsisAtg8autophagybioinformaticsPEXpexophagy

Identifiers

PMID27071037
PMCPMC4854547
OpenAlexW2338774928

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.