R-loop-forming Sequences Analysis in Thousands of Viral Genomes Identify A New Common Element in Herpesviruses

R-loop and diseases: the cell cycle matters

The cell cycle is a crucial biological process that is involved in cell growth, development, and reproduction. It can be divided into G1, S, G2, and M phases, and each period is closely regulated to ensure the production of two similar daughter cells with the same genetic material. However, many obstacles influence the cell cycle, including the R-loop that is formed throughout this process. R-loop is a triple-stranded structure, composed of an RNA: DNA hybrid and a single DNA strand, which is ubiquitous in organisms from bacteria to mammals. The existence of the R-loop has important significance for the regulation of various physiological processes. However, aberrant accumulation of R-loop due to its limited resolving ability will be detrimental for cells. For example, DNA damage and genomic instability, caused by the R-loop, can activate checkpoints in the cell cycle, which in turn induce cell cycle arrest and cell death. At present, a growing number of factors have been proven to prevent or eliminate the accumulation of R-loop thereby avoiding DNA damage and mutations. Therefore, we need to gain detailed insight into the R-loop resolution factors at different stages of the cell cycle. In this review, we review the current knowledge of factors that play a role in resolving the R-loop at different stages of the cell cycle, as well as how mutations of these factors lead to the onset and progression of diseases.

Experimental and computational methods for studying the dynamics of RNA-RNA interactions in SARS-COV2 genomes

Long-range ribonucleic acid (RNA)-RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA-RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2's mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps and shed light on the impact of mutations on the RRI space in viral genomes. Investigating the evolution of long-range RNA interactions and that of virus-host interactions can contribute to the understanding of new and emerging variants as well as aid in developing improved RNA therapeutics critical for combating future outbreaks.

IFN-Induced PARPs—Sensors of Foreign Nucleic Acids?

Cells have developed different strategies to cope with viral infections. Key to initiating a defense response against viruses is the ability to distinguish foreign molecules from their own. One central mechanism is the perception of foreign nucleic acids by host proteins which, in turn, initiate an efficient immune response. Nucleic acid sensing pattern recognition receptors have evolved, each targeting specific features to discriminate viral from host RNA. These are complemented by several RNA-binding proteins that assist in sensing of foreign RNAs. There is increasing evidence that the interferon-inducible ADP-ribosyltransferases (ARTs; PARP9—PARP15) contribute to immune defense and attenuation of viruses. However, their activation, subsequent targets, and precise mechanisms of interference with viruses and their propagation are still largely unknown. Best known for its antiviral activities and its role as RNA sensor is PARP13. In addition, PARP9 has been recently described as sensor for viral RNA. Here we will discuss recent findings suggesting that some PARPs function in antiviral innate immunity. We expand on these findings and integrate this information into a concept that outlines how the different PARPs might function as sensors of foreign RNA. We speculate about possible consequences of RNA binding with regard to the catalytic activities of PARPs, substrate specificity and signaling, which together result in antiviral activities.

Epstein-Barr virus BNRF1 destabilizes SMC5/6 cohesin complexes to evade its restriction of replication compartments

Epstein-Barr virus (EBV) persistently infects people worldwide. Delivery of ∼170-kb EBV genomes to nuclei and use of nuclear membrane-less replication compartments (RCs) for their lytic cycle amplification necessitate evasion of intrinsic antiviral responses. Proteomics analysis indicates that, upon B cell infection or lytic reactivation, EBV depletes the cohesin SMC5/6, which has major roles in chromosome maintenance and DNA damage repair. The major tegument protein BNRF1 targets SMC5/6 complexes by a ubiquitin proteasome pathway dependent on calpain proteolysis and Cullin-7. In the absence of BNRF1, SMC5/6 associates with R-loop structures, including at the viral lytic origin of replication, and interferes with RC formation and encapsidation. CRISPR analysis identifies RC restriction roles of SMC5/6 components involved in DNA entrapment and SUMOylation. Our study highlights SMC5/6 as an intrinsic immune sensor and restriction factor for a human herpesvirus RC and has implications for the pathogenesis of EBV-associated cancers.

A panel of KSHV mutants in the polycistronic kaposin locus for precise analysis of individual protein products

Kaposi’s sarcoma-associated herpesvirus (KSHV) is the cause of several human cancers, including the endothelial cell (EC) malignancy, Kaposi’s sarcoma. Unique KSHV genes absent from other human herpesvirus genomes, the “K-genes,” are important for KSHV replication and pathogenesis. Among these, the kaposin transcript is highly expressed in all phases of infection, but its complex polycistronic nature has hindered functional analysis to date. At least three proteins are produced from the kaposin transcript: Kaposin A (KapA), B (KapB), and C (KapC). To determine the relative contributions of kaposin proteins during KSHV infection, we created a collection of mutant viruses unable to produce kaposin proteins individually or in combination. In previous work, we showed KapB alone recapitulated the elevated proinflammatory cytokine transcripts associated with KS via the disassembly of RNA granules called processing bodies (PBs). Using the new ΔKapB virus, we showed that KapB was necessary for this effect during latent KSHV infection. Moreover, we observed that despite the ability of all kaposin-deficient latent iSLK cell lines to produce virions, all displayed low viral episome copy number, a defect that became more pronounced after primary infection of naive ECs. For ΔKapB, provision of KapB in trans failed to complement the defect, suggesting a requirement for the kaposin locus in cis. These findings demonstrate that our panel of kaposin-deficient viruses enables precise analysis of the respective contributions of individual kaposin proteins to KSHV replication. Moreover, our mutagenesis approach serves as a guide for the functional analysis of other complex multicistronic viral loci.

IMPORTANCE Kaposi’s sarcoma-associated herpesvirus (KSHV) expresses high levels of the kaposin transcript during both latent and lytic phases of replication. Due to its repetitive, GC-rich nature and polycistronic coding capacity, until now no reagents existed to permit a methodical analysis of the role of individual kaposin proteins in KSHV replication. We report the creation of a panel of recombinant viruses and matched producer cell lines that delete kaposin proteins individually or in combination. We demonstrate the utility of this panel by confirming the requirement of one kaposin translation product to a key KSHV latency phenotype. This study describes a new panel of molecular tools for the KSHV field to enable precise analysis of the roles of individual kaposin proteins during KSHV infection.

KITSUNE: A Tool for Identifying Empirically Optimal K-mer Length for Alignment-Free Phylogenomic Analysis

Genomic DNA is the best “unique identifier” for organisms. Alignment-free phylogenomic analysis, simple, fast, and efficient method to compare genome sequences, relies on looking at the distribution of small DNA sequence of a particular length, referred to as k-mer. The k-mer approach has been explored as a basis for sequence analysis applications, including assembly, phylogenetic tree inference, and classification. Although this approach is not novel, selecting the appropriate k-mer length to obtain the optimal resolution is rather arbitrary. However, it is a very important parameter for achieving the appropriate resolution for genome/sequence distances to infer biologically meaningful phylogenetic relationships. Thus, there is a need for a systematic approach to identify the appropriate k-mer from whole-genome sequences. We present K-mer–length Iterative Selection for UNbiased Ecophylogenomics (KITSUNE), a tool for assessing the empirically optimal k-mer length of any given set of genomes of interest for phylogenomic analysis via a three-step approach based on (1) cumulative relative entropy (CRE), (2) average number of common features (ACF), and (3) observed common features (OCF). Using KITSUNE, we demonstrated the feasibility and reliability of these measurements to obtain empirically optimal k-mer lengths of 11, 17, and ∼34 from large genome datasets of viruses, bacteria, and fungi, respectively. Moreover, we demonstrated a feature of KITSUNE for accurate species identification for the two de novo assembled bacterial genomes derived from error-prone long-reads sequences, and for a published yeast genome. In addition, KITSUNE was used to identify the shortest species-specific k-mer accurately identifying viruses. KITSUNE is freely available at https://github.com/natapol/kitsune.