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Host–pathogen

Pathogenicity factors in Naegleria fowleri

Zysset-Burri DC, Müller N, Beuret C, et al. · BMC genomics · 2014

Open access · cc by · source: Europe PMC

Whole-genome analysis of N. fowleri highlights candidate pathogenicity factors for brain infection.

Study at a glance

Design
Computational / modelling — De novo genome sequencing plus proteomics to nominate N. fowleri pathogenicity factors
N
~29.6 Mb assembled nuclear genome (diploid estimate ~66 Mb); >500 million reads — genome resource study
Population
Naegleria fowleri (compared with non-pathogenic N. gruberi)
Outcome
Candidate pathogenicity gene sets from genome/proteome comparison

Structured fields used in claim comparison tables when every cited study has a complete layer.

Key findings

~30 Mb AT-rich genome assembled; candidate pathogenicity gene sets identified for follow-up.

Methodology

Sequenced and assembled the N. fowleri genome and compared features relevant to virulence.

Limitations

Genome candidates need functional validation in infection models.

How this study connects

Role on claims

Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.

  • Three papers are false-positive lexicon hits for proteomics. Naegleria fowleri work assembled an ~30 Mb AT-rich genome and listed candidate pathogenicity genes; Aspergillus comparative genomics reported ~29–36 Mb genomes with 9,113–13,553 genes (~20% Aspergillaceae-specific; section Nigri ~1,800 unique genes); Plasmodium falciparum IDC transcriptome was hourly expression across a ~48-hour blood-stage cycle. Those are DNA or RNA catalogues, not peptide spectra.

    Evidence for the claim as stated.

  • Naegleria and Aspergillus genomes and the Plasmodium IDC transcriptome should not be cited as mass-spectrometry evidence at all. Candidate pathogenicity gene lists and periodic RNA profiles are sequence resources that still need protein-level or infection-model tests.

    Evidence for the claim as stated.

  • SupportsFlow Cytometrymethod

    Two papers barely use flow cytometry as the core method. Spike glycosylation/palmitoylation trafficking used LYQD and cysteine-cluster mutants plus 2-bromopalmitate, scoring S2 mobility, packaging and ACE2 fusion — cell-based trafficking, not a leukocyte panel. Naegleria fowleri work assembled an ~30 Mb AT-rich genome and listed pathogenicity candidates that still need infection-model tests.

    Evidence for the claim as stated.

  • SupportsFlow Cytometrymethod

    Foxp3+ gating is a means to an epigenetic comparison (TSDR demethylation versus unstable induced Foxp3), whereas spike and Naegleria papers are trafficking genetics and a genome assembly. Treating every hit as a flow-cytometry methods paper hides those mismatches.

    Evidence for the claim as stated.

Open questions

Tensions this paper is part of

From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.

Related papers in this topic

Same topic cluster — not a recommendation engine.