bioRxivMicrobiologyPreprint
Bridging Viruses and Prokaryotic Host through Miniature Inverted-repeat Transposable Elements (MITEs)
F. Nadal-Molero, R. Rosselli, S. Garcia-Juan, A. Campos-Lopez, A. B. Martin-Cuadrado
Abstract
Transposable elements (TEs) have a pivotal role in the evolution of genomes across all life domains. "Miniature Inverted-repeat Transposable-Elements" (MITEs) are non-autonomous TEs mainly located in intergenic regions, relying on external transposases for mobilization. The boundaries of MITEs mobilome were explored across nearly 1700 prokaryotic genera, 183232 genomes, revealing a widespread distribution. MITEs were identified in 56.5% of genomes, totaling over 1.4 million cMITEs (cellular). Cluster analysis revealed that a significant 97.4% of cMITEs were conserved within genera boundaries, with up to 23% being species-specific. Subsequently, this genus-specificity was evaluated as a tool to link microbial host to their viruses. A total of 51655 cMITEs had counterparts in viral sequences, termed vMITE (viral), resulting in the identification of 2798 viral sequences with vMITEs. Among these, 1501 sequences were positively assigned to a previously known host (41.8% were isolated virus, and 12.3% were assigned through CRISPR data), while 379 new host-virus associations were predicted. Deeper analysis in Neisseria and Bacteroidetes groups allowed the association of 242 and 530 new additional viral sequences, respectively. Given the abundance of non-culturable virus sequences accumulated in databases lacking affiliations with their microbial targets, MITEs are proposed as a novel approach to establishing valid virus-host relationships. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/576219v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@f30826org.highwire.dtl.DTLVardef@19bff7borg.highwire.dtl.DTLVardef@a206eaorg.highwire.dtl.DTLVardef@17408ab_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: bacteria (other)
- assay: DNA methylation
- assay: whole-genome sequencing
- research focus: host-pathogen & immune response
- approach: statistical model
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