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Viruses are the intracellular pathogens that reproduce only in the living cell and manipulate the cellular machinery to produce more viruses. Viral replications can affect cellular genes of the host in multiple cancerous ways. Approximately, 20% of all human oncogenesis is caused by cancer-causing viruses known as oncoviruses. Viral infection causes chronic inflammation leading to cell death, uncontrollable proliferation, and modulated expression of some of the regulatory proteins. Oncogenesis is a multistep phenomenon in which normal host cells are transformed into cancerous cells on the basis of host genetic variability. Oncogenic viruses encode genes that cause viral replication and transformation of the host cells to produce viral proteins and protein complexes. The phenomenon from basic viral infection to tumorigenesis is lengthy due to the involvement of factors like immunity complications, cellular mutations, and exposure to other cancerous agents. The viruses that are involved in human cancer development are Hepatitis B virus (HBV), Hepatitis C virus (HCV), Epstein-Barr virus (EBV), Human papilloma virus (HPV), Kaposi's sarcoma herpes virus (KSHV), and Human T lymphotrophic virus 1 (HTLV-1). This review article summarizes advanced knowledge related to human oncogenic viruses and the molecular mechanisms that lead to tumorigenesis in humans. [ABSTRACT FROM AUTHOR]

Eco-evolutionary dynamics have been shown to be important for understanding population and community stability and their adaptive potential. However, coevolution in the framework of eco-evolutionary theory has not been addressed directly. Combining experiments with an algal host and its viral parasite, and mathematical model analyses we show eco-evolutionary dynamics in antagonistic coevolving populations. The interaction between antagonists initially resulted in arms race dynamics (ARD) with selective sweeps, causing oscillating host-virus population dynamics. However, ARD ended and populations stabilised after the evolution of a general resistant host, whereas a trade-off between host resistance and growth then maintained host diversity over time (trade-off driven dynamics). Most importantly, our study shows that the interaction between ecology and evolution had important consequences for the predictability of the mode and tempo of adaptive change and for the stability and adaptive potential of populations. [ABSTRACT FROM AUTHOR]

Background: When biomolecules physically interact, natural selection operates on them jointly. Contacting positions in protein and RNA structures exhibit correlated patterns of sequence evolution due to constraints imposed by the interaction, and molecular arms races can develop between interacting proteins in pathogens and their hosts. To evaluate how well methods developed to detect coevolving residues within proteins can be adapted for cross-species, inter-protein analysis, we used statistical criteria to quantify the performance of these methods in detecting inter-protein residues within 8 angstroms of each other in the co-crystal structures of 33 bacterial protein interactions. We also evaluated their performance for detecting known residues at the interface of a host-virus protein complex with a partially solved structure. Results: Our quantitative benchmarking showed that all coevolutionary methods clearly benefit from alignments with many sequences. Methods that aim to detect direct correlations generally outperform other approaches. However, faster mutual information based methods are occasionally competitive in small alignments and with relaxed false positive rates. Two commonly used null distributions are anti-conservative and have high false positive rates in some scenarios, although the empirical distribution of scores performs reasonably well with deep alignments. Conclusions: We conclude that coevolutionary analysis of cross-species protein interactions holds great promise but requires sequencing many more species pairs. [ABSTRACT FROM AUTHOR]

Viral infection depends on a complex interplay between host and viral factors. Here, we link host susceptibility to viral infection to a network encompassing sulfur metabolism, tRNA modification, competitive binding, and programmed ribosomal frameshifting (PRF).We first demonstrate that the iron-sulfur cluster biosynthesis pathway in Escherichia coli exerts a protective effect during lambda phage infection, while a tRNA thiolation pathway enhances viral infection. We show that tRNALys uridine 34 modification inhibits PRF to influence the ratio of lambda phage proteins gpG and gpGT. Computational modeling and experiments suggest that the role of the iron-sulfur cluster biosynthesis pathway in infection is indirect, via competitive binding of the shared sulfur donor IscS. Based on the universality of many key components of this network, in both the host and the virus, we anticipate that these findings may have broad relevance to understanding other infections, including viral infection of humans. [ABSTRACT FROM AUTHOR]

The Coronaviridae is a family of positive-strand RNA viruses that includes SARS-CoV-2, the etiologic agent of the COVID-19 pandemic. Bearing the largest single-stranded RNA genomes in nature, coronaviruses are critically dependent on long-distance RNA-RNA interactions to regulate the viral transcription and replication pathways. Here we experimentally mapped the in vivo RNA-RNA interactome of the full-length SARS-CoV-2 genome and subgenomic mRNAs. We uncovered a network of RNA-RNA interactions spanning tens of thousands of nucleotides. These interactions reveal that the viral genome and subgenomes adopt alternative topologies inside cells and engage in different interactions with host RNAs. Notably, we discovered a long-range RNA-RNA interaction, the FSE-arch, that encircles the programmed ribosomal frameshifting element. The FSE-arch is conserved in the related MERS-CoV and is under purifying selection. Our findings illuminate RNA structure-based mechanisms governing replication, discontinuous transcription, and translation of coronaviruses and will aid future efforts to develop antiviral strategies. • Comprehensive RNA-RNA networks of the SARS-CoV-2 genome and subgenomes inside cells • Long-range structures spanning thousands of bases resulting in dynamic topologies • Multiple site-specific interactions between host and virus RNAs • An arch around the ribosomal frameshifting element is under purifying selection Coronaviruses use RNA structure to regulate their function. Ziv et al. identified maps of RNA-RNA interactions along the SARS-CoV-2 genome and subgenomes inside cells, revealing long-range base-pairing between distal elements, alternative co-existing RNA topologies, and interactions between virus and host RNA and providing insights into the coronavirus modes of action. [ABSTRACT FROM AUTHOR]