A comparison of marker gene conservation between these groups and established viral taxa suggested that the former Inoviridae family should be reclassified as an order, provisionally divided into 6 candidate families and candidate subfamilies, with few shared genes across candidate families Fig. Beyond gene content, these proposed families also displayed clearly distinct host ranges as well as specific genome features, particularly in terms of genome size and coding density Supplementary Fig.
If confirmed, and compared with currently recognized inoviruses, the genomes reported here would increase diversity by 3 families and subfamilies.
Conversely, no structuring by biome was observed and all proposed families were broadly detected across multiple types of ecosystems. Hence, we propose here a classification of inovirus diversity into six families based on gene content with coherent host ranges and specific genomic features, which strongly suggests that they represent ecologically and evolutionarily meaningful units.
The extended catalogue of inovirus genomes offers an unprecedented window into the diversity of their genes and predicted functions. Overall, 68, proteins were predicted and clustered into 3, protein families and 13, singletons. This is on par with the functional diversity observed in known Caudovirales genomes, the largest order of dsDNA viruses, for which the same number of proteins clustered into 12, protein families but only 8, singletons see Methods.
A putative function was predicted for 1, of the 3, inovirus protein families iPFs. A total of 51 and 47 distinct iPFs could be annotated as major and minor coat proteins, respectively, with an additional iPFs identified as potentially structural based on their size and presence of a TMD see Methods. Notably, each candidate inovirus family seemed to be associated with a specific set of structural proteins, including distinct major coat iPFs Supplementary Fig. Conversely, genome replication and integration-associated iPFs were broadly shared across candidate families Fig.
This confirms that replication-associated and integration-associated genes are among the most frequently exchanged among viral genomes and with other mobile genetic elements, especially in small single-stranded DNA viruses In addition, 15 distinct sets of iPFs representing potential toxin—antitoxin pairs were identified across inovirus genomes, including 10 unaffiliated iPFs that were predicted as putative antitoxins through co-occurrence with a toxin iPF Fig.
These genes typically stabilize plasmids or prophages in host cell populations, although alternative roles in stress response and transcription regulation have been reported In addition, toxin—antitoxin systems often affect host cell phenotypes, such as motility or biofilm formation 1. Here, similar toxin proteins could be associated with distinct and seemingly unrelated antitoxins and vice versa, suggesting that gene shuffling and lateral transfer occur even within these tightly linked gene pairs Supplementary Fig.
All but one toxin—antitoxin pairs were detected in proteobacteria-associated inoviruses, most likely because of a database bias. Thus, numerous uncharacterized iPFs across other candidate families of inoviruses may also encode previously undescribed toxin—antitoxin systems and, more generally, host manipulation mechanisms.
Finally, we investigated potential interactions between persistently infecting inoviruses, other co-infecting viruses, and the host clustered regularly interspaced short palindromic repeats CRISPR —CRISPR-associated Cas immunity systems. These spacers were associated with three types and eight subtypes of CRISPR—Cas systems, indicating that inoviruses are broadly targeted by antiviral defences Fig.
Several host groups, most notably Neisseria meningitidis , were clear outliers, that is, they displayed a particularly high ratio of inovirus-derived spacers suggesting a uniquely high level of spacer acquisition and inovirus infection Fig.
This is particularly notable because inoviruses were recently suggested to increase N. The proportions are calculated only on hosts with at least one spacer matching an inovirus sequence, with hosts grouped at the family rank hosts unclassified at this rank were not included. Outliers identified as values larger than the third quartile plus three times the interquartile range from the complete distribution are highlighted in red.
The number of observations is indicated next to each family. From top to bottom: cells were transformed with an empty vector, one expressing gene or one expressing gene The formation of plaques dark circles indicates successful infection, whereas the absence of plaques indicates superinfection exclusion. Interpretation of infection outcome is indicated to the right of each lane, with successful infection represented by a phage symbol and superinfection exclusion represented by a phage symbol barred by a red cross.
Results from additional superinfection exclusion experiments are presented in Supplementary Figs. All superinfection experiments were conducted twice and produced similar results. Antagonistic interactions primarily involve superinfection exclusion, in which a chronic inovirus infection prevents a secondary infection by an unrelated virus.
Among the 1, genomes that included both a CRISPR—Cas system and an inovirus prophage, only 45 displayed a spacer match es to a resident prophage Supplementary Table 6 , suggesting that self-targeting of these integrated elements is lethal and strongly counter-selected This was confirmed experimentally using the Pseudomonas aeruginosa strain PA14 harbouring an integrated inovirus prophage Pf1 , for which the introduction of a plasmid carrying Pf1-targeting CRISPR spacers was lethal Supplementary Fig.
We first evaluated ten hypothetical proteins, and hence candidate Acr proteins, from self-targeted inoviruses infecting P. Alternatively, inoviruses could leverage the Acr activity of a co-integrated virus. This hypothesis was further reinforced by the fact that 43 of the 45 self-targeted inoviruses were detected alongside co-infecting dsDNA phages, with 5 of these encoding known acr genes Supplementary Table 6.
We confirmed experimentally cross-protection by trans -acting Acr in the P. While this represents an instance of beneficial co-infection for inoviruses, we also uncovered evidence of antagonistic interactions between inoviruses and dsDNA bacteriophages. Specifically, 2 of the 10 inovirus-encoded hypothetical proteins tested strongly limited infection of Pseudomonas cells by different bacteriophages Fig.
This superinfection exclusion effect was found to be host and virus strain dependent, which could drive intricate tripartite coevolution dynamics. Thus, these preliminary observations indicate that inoviruses may not only evade CRISPR—Cas immunity by leveraging the Acr activity of co-integrated phages, but also significantly influence the infection dynamics of unrelated co-infecting viruses through superinfection exclusion Fig.
Given their broad host range Fig. Taken together, the results presented here call for a complete re-evaluation of the diversity and role of inoviruses in nature. Collectively, inoviruses are distributed across all biomes and display an extremely broad host range spanning both prokaryotic domains of life. Comparative genomics revealed evidence of longstanding virus—host codiversification, leading to strong partitioning of inovirus diversity by host taxonomy, high inovirus prevalence in several microbial groups, including major pathogens, and potential interdomain transfer.
In contrast, a preference for distal pA selection was reported for higher Clp1 levels in a mouse myoblast cell line based on siRNA Clp1 loss-of-function experiments Li et al. The Aire-sensitive genes are expressed at much lower levels than the Aire-neutral genes.
Genes between the dashed lines have a change in expression less than twofold Aire-neutral. Duplicate reads were discarded to allow more accurate dataset comparison. We observed a preference for the smaller ratios Figure 1E , Figure 1—figure supplement 1B and Figure 1—source data 3 and 4 in Aire-sensitive versus neutral genes in the Aire -KO cells. To this end, we collected RNA-seq datasets corresponding to a variety of tissues Shen et al.
To circumvent this issue, we used the HEK cell line for these experiments. For each candidate gene, we measured the knockdown efficiency of, typically, five different shRNAs and selected the three most effective Supplementary file 1. A Individual probe-level analysis of microarray data from knockdown and control HEK cells. Ctr LacZ knockdown samples. Significance and direction of the enrichment is shown for each hit shRNA, as well as P value thresholds of 0.
For each candidate factor, we computed the rank of differential expression of all genes in Ctr versus HEK cells knockdown for the tested candidate, and found that CLP1 was the only gene whose knockdown by two distinct shRNAs led to a significant reduction of the expression of Aire-sensitive genes Figure 3B , focusing our subsequent study on CLP1.
Furthermore, we observed that the extent of the effect of CLP1 knockdown on the levels of Aire-sensitive gene expression in Aire -transfected HEK cells Figure 3—figure supplement 4 was similar, although slightly stronger than the one we described above in AIRE-negative HEK cells.
Three shRNAs targeting the murine Clp1 with the highest knockdown efficiency Supplementary file 1 were cloned as a multi-miR construct into a lentiviral vector, downstream of a doxycycline inducible promoter and upstream of the GFP as a marker of activity.
Purified concentrated lentiviruses containing this construct and the lentiviral vector expressing the TetOn3G protein were used to microinfect fertilized oocytes, which were reimplanted into pseudopregnant females Figure 4A.
A Schematic of the lentigenic knockdown strategy. The resulting pups were screened for integration of the constructs and, after treatment by doxycycline, for GFP expression in mTEChi.
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