A billion years arms-race between viruses, virophages, and eukaryotes

Bamfordviruses are arguably the most diverse group of viruses infecting eukaryotes. They include the Nucleocytoplasmic Large DNA viruses (NCLDVs), virophages, adenoviruses, Mavericks and Polinton-like viruses. Two main hypotheses for their origins have been proposed: the ‘nuclear-escape’ and ‘virophage-first’ hypotheses. The nuclear-escape hypothesis proposes an endogenous, Maverick-like ancestor which escaped from the nucleus and gave rise to adenoviruses and NCLDVs. In contrast, the virophage-first hypothesis proposes that NCLDVs coevolved with protovirophages; Mavericks then evolved from virophages that became endogenous, with adenoviruses escaping from the nucleus at a later stage. Here, we test the predictions made by both models and consider alternative evolutionary scenarios. We use a data set of the four core virion proteins sampled across the diversity of the lineage, together with Bayesian and maximum-likelihood hypothesis-testing methods, and estimate rooted phylogenies. We find strong evidence that adenoviruses and NCLDVs are not sister groups, and that Mavericks and Mavirus acquired the rve-integrase independently. We also found strong support for a monophyletic group of virophages (family Lavidaviridae) and a most likely root placed between virophages and the other lineages. Our observations support alternatives to the nuclear-escape scenario and a billion years evolutionary arms-race between virophages and NCLDVs

Ecological and evolutionary dynamics of cell-virus-virophage systems

Microbial eukaryotes, giant viruses and virophages form a unique hyperparasitic system. Virophages are parasites of the virus transcription machinery and can interfere with virus replication, resulting in a benefit to the eukaryotic host population. Surprisingly, virophages can integrate into the genomes of their cell or virus hosts, and have been shown to reactivate during coinfection. This raises questions about the role of integration in the dynamics of cell-virus-virophage systems. We use mathematical models and computational simulations to understand the effect of virophage integration on populations of cells and viruses. We also investigate multicellularity and programmed cell-death (PCD) as potential antiviral defence strategies used by cells. We found that virophages which enter the cell independently of the host virus, such as Mavirus, are expected to integrate commonly into the genomes of their cell hosts. Our models suggest that integrations from virophages without an independent mode of entry like Sputnik, are less likely to become fixed in the cell host population. Alternatively, we found that Sputnik virophages can stably persist integrated in the virus population, as long as they do not completely inhibit virus replication. We also show that increasing virophage inhibition can stabilise oscillatory dynamics, which may explain the long-term persistence of viruses and virophages in the environment. Our results demonstrate that inhibition by virophages and multicellularity are effective antiviral strategies that may act in synergy against viral infection in microbial species

Limitations of current high-throughput sequencing technologies lead to biased expression estimates of endogenous retroviral elements

Human endogenous retroviruses (HERVs), the remnants of ancient germline retroviral integrations, comprise almost 8% of the human genome. The elucidation of their biological roles is hampered by our inability to link HERV mRNA and protein production with specific HERV loci. To solve the riddle of the integration-specific RNA expression of HERVs, several bioinformatics approaches have been proposed; however, no single process seems to yield optimal results due to the repetitiveness of HERV integrations. The performance of existing data-bioinformatics pipelines has been evaluated against real world datasets whose true expression profile is unknown, thus the accuracy of widely-used approaches remains unclear. Here, we simulated mRNA production from specific HERV integrations to evaluate second and third generation sequencing technologies along with widely used bioinformatic approaches to estimate the accuracy in describing integration-specific expression. We demonstrate that, while a HERV-family approach offers accurate results, per-integration analyses of HERV expression suffer from substantial expression bias, which is only partially mitigated by algorithms developed for calculating the per-integration HERV expression, and is more pronounced in recent integrations. Hence, this bias could erroneously result into biologically meaningful inferences. Finally, we demonstrate the merits of accurate long-read high-throughput sequencing technologies in the resolution of per-locus HERV expression

Larger mammalian body size leads to lower retroviral activity

Retroviruses have been infecting mammals for at least 100 million years, leaving descendants in host genomes known as endogenous retroviruses (ERVs). The abundance of ERVs is partly determined by their mode of replication, but it has also been suggested that host life history traits could enhance or suppress their activity. We show that larger bodied species have lower levels of ERV activity by reconstructing the rate of ERV integration across 38 mammalian species. Body size explains 37% of the variance in ERV integration rate over the last 10 million years, controlling for the effect of confounding due to other life history traits. Furthermore, 68% of the variance in the mean age of ERVs per genome can also be explained by body size. These results indicate that body size limits the number of recently replicating ERVs due to their detrimental effects on their host. To comprehend the possible mechanistic links between body size and ERV integration we built a mathematical model, which shows that ERV abundance is favored by lower body size and higher horizontal transmission rates. We argue that because retroviral integration is tumorigenic, the negative correlation between body size and ERV numbers results from the necessity to reduce the risk of cancer, under the assumption that this risk scales positively with body size. Our model also fits the empirical observation that the lifetime risk of cancer is relatively invariant among mammals regardless of their body size, known as Peto's paradox, and indicates that larger bodied mammals may have evolved mechanisms to limit ERV activity

Discovery of novel papillomaviruses in the critically endangered Malayan and Chinese pangolins

Pangolins are scaly and toothless mammals which are distributed across Africa and Asia. Currently, the Malayan, Chinese and Philippine pangolins are designated as critically endangered species. Although few pangolin viruses have been described, their viromes have received more attention following the discovery that they harbour sarbecoviruses related to SARS-CoV-2. Using large-scale genome mining, we discovered novel lineages of papillomaviruses infecting the Malayan and Chinese pangolins. We were able to assemble three complete circular papillomavirus genomes with an intact coding capacity and five additional L1 genes encoding the major capsid protein. Phylogenetic analysis revealed that seven out of eight L1 sequences formed a monophyletic group which is the sister lineage to the Tupaia belangeri papillomavirus 1, isolated from Yunnan province in China. Additionally, a single L1 sequence assembled from a Chinese pangolin was placed in a clade closer to Alphapapillomavirus and Omegapapillomavirus. Examination of the SRA data from 95 re-sequenced genomes revealed that 49.3% of Malayan pangolins and 50% of Chinese pangolins were positive for papillomavirus reads. Our results indicate that pangolins in South-East Asia are the hosts of diverse and highly prevalent papillomaviruses, and highlight the value of in silico mining of host sequencing data for the discovery of novel viruses

HIV-1 p24Gag adaptation to modern and archaic HLA-allele frequency differences in ethnic groups contributes to viral subtype diversification

Pathogen-driven selection and past interbreeding with archaic human lineages have resulted in differences in HLA-allele frequencies between modern human populations. Whether or not this variation affects pathogen subtype diversification is unknown. Here we show a strong positive correlation between ethnic diversity in African countries and both HIV-1 p24gag and subtype diversity. We demonstrate that ethnic HLA-allele differences between populations has influenced HIV-1 subtype diversification as the virus adapted to escape common antiviral immune responses. The evolution of HIV subtype B (HIV-B), which does not appear to be indigenous to Africa, is strongly affected by immune responses associated with Eurasian HLA variants acquired through adaptive introgression from Neanderthals and Denisovans. Furthermore, we show that the increasing and disproportionate number of HIV-infections among African Americans in the United States drive HIV-B evolution towards an Africa-centric HIV-1 state. Similar adaptation of other pathogens to HLA variants common in affected populations is likely