Evidence map›Paper›PMID 39760805›Full record

ArticleGenome biology and evolution2025

Novel High-Quality Amoeba Genomes Reveal Widespread Codon Usage Mismatch Between Giant Viruses and Their Hosts.

Anouk Willemsen, Alejandro Manzano-Marín, Matthias Horn

Abstract read
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Article in Genome biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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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

3 authors.

Anouk WillemsenCentre for Microbiology and Environmental Systems Science, Division of Microbial Ecology, University of Vienna, Vienna 1030, Austria.ORCID 0000-0002-8511-3244
Alejandro Manzano-MarínCentre for Microbiology and Environmental Systems Science, Division of Microbial Ecology, University of Vienna, Vienna 1030, Austria.ORCID 0000-0002-0707-9052
Matthias HornCentre for Microbiology and Environmental Systems Science, Division of Microbial Ecology, University of Vienna, Vienna 1030, Austria.ORCID 0000-0002-8309-5855

Funding

Austrian Science FundEuropean Research Council Executive AgencyEuropean Union 101039843European Union's Horizon 2020 research and innovation programmeMarie Sklodowska-Curie 891572
6 · The paper itself

Abstract

The need for high-quality protist genomes has prevented in-depth computational and experimental studies of giant virus-host interactions. In addition, our current knowledge of host range is highly biased due to the few hosts used to isolate novel giant viruses. This study presents 6 high-quality amoeba genomes from known and potential giant virus hosts belonging to 2 distinct eukaryotic clades: Amoebozoa and Discoba. We employ their genomic data to investigate the predictability of giant virus host range. Using a combination of long- and short-read sequencing, we obtained highly contiguous and complete genomes of Acanthamoeba castellanii, Acanthamoeba griffini, Acanthamoeba terricola, Naegleria clarki, Vermamoeba vermiformis, and Willaertia magna, contributing to the collection of sequences for the eukaryotic tree of life. We found that the 6 amoebae have distinct codon usage patterns and that, contrary to other virus groups, giant viruses often have different and even opposite codon usage with their known hosts. Conversely, giant viruses with matching codon usage are frequently not known to infect or replicate in these hosts. Interestingly, analyses of integrated viral sequences in the amoeba host genomes reveal potential novel virus-host associations. Matching of codon usage preferences is often used to predict virus-host pairs. However, with the broad-scale analyses performed in this study, we demonstrate that codon usage alone appears to be a poor predictor of host range for giant viruses infecting amoeba. We discuss the potential strategies that giant viruses employ to ensure high viral fitness in nonmatching hosts. Moreover, this study emphasizes the need for more high-quality protist genomes. Finally, the amoeba genomes presented in this study set the stage for future experimental studies to better understand how giant viruses interact with different host species.

Indexed as

AmoebaCodon UsageGiant VirusesAcanthamoebaGenome, ProtozoanHost SpecificityPhylogenyamoeba genomescodon usagegiant virusesvirus–host interactions

Identifiers

PMID39760805
PMCPMC11702301

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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.