The m6A landscape of polyadenylated nuclear (PAN) RNA and its related methylome in the context of KSHV replication

METTL16 controls Kaposi's sarcoma-associated herpesvirus replication by regulating S-adenosylmethionine cycle

Oncogenic Kaposi's sarcoma-associated herpesvirus (KSHV) consists of latent and lytic replication phases, both of which are important for the development of KSHV-related cancers. As one of the most abundant RNA modifications, N6-methyladenosine (m6A) and its related complexes regulate KSHV life cycle. However, the role of METTL16, a newly discovered RNA methyltransferase, in KSHV life cycle remains unknown. In this study, we have identified a suppressive role of METTL16 in KSHV lytic replication. METTL16 knockdown increased while METTL16 overexpression reduced KSHV lytic replication. METTL16 binding to and writing of m6A on MAT2A transcript are essential for its splicing, maturation and expression. As a rate-limiting enzyme in the methionine-S-adenosylmethionine (SAM) cycle, MAT2A catalyzes the conversion of L-methionine to SAM required for the transmethylation of protein, DNA and RNA, transamination of polyamines, and transsulfuration of cystathionine. Consequently, knockdown or chemical inhibition of MAT2A reduced intracellular SAM level and enhanced KSHV lytic replication. In contrast, SAM treatment was sufficient to inhibit KSHV lytic replication and reverse the effect of the enhanced KSHV lytic program caused by METTL16 or MAT2A knockdown. Mechanistically, METTL16 or MAT2A knockdown increased while SAM treatment decreased the intracellular reactive oxygen species level by altering glutathione level, which is essential for efficient KSHV lytic replication. These findings demonstrate that METTL16 suppresses KSHV lytic replication by modulating the SAM cycle to maintain intracellular SAM level and redox homeostasis, thus illustrating the linkage of KSHV life cycle with specific m6A modifications, and cellular metabolic and oxidative conditions.

N6-methyladenosine and Its Implications in Viruses

N6-methyladenine (m6A) is the most abundant RNA modification in mammalian messenger RNAs (mRNAs), which participates in and regulates many important biological activities, such as tissue development and stem cell differentiation. Due to an improved understanding of m6A, researchers have discovered that the biological function of m6A can be linked to many stages of mRNA metabolism and that m6A can regulate a variety of complex biological processes. In addition to its location on mammalian mRNAs, m6A has been identified on viral transcripts. m6A also plays important roles in the life cycle of many viruses and in viral replication in host cells. In this review, we briefly introduce the detection methods of m6A, the m6A-related proteins, and the functions of m6A. We also summarize the effects of m6A-related proteins on viral replication and infection. We hope that this review provides researchers with some insights for elucidating the complex mechanisms of the epitranscriptome related to viruses, and provides information for further study of the mechanisms of other modified nucleobases acting on processes such as viral replication. We also anticipate that this review can stimulate collaborative research from different fields, such as chemistry, biology, and medicine, and promote the development of antiviral drugs and vaccines.

Functional and molecular dissection of HCMV long non-coding RNAs

Small, compact genomes confer a selective advantage to viruses, yet human cytomegalovirus (HCMV) expresses the long non-coding RNAs (lncRNAs); RNA1.2, RNA2.7, RNA4.9, and RNA5.0. Little is known about the function of these lncRNAs in the virus life cycle. Here, we dissected the functional and molecular landscape of HCMV lncRNAs. We found that HCMV lncRNAs occupy ~ 30% and 50-60% of total and poly(A)+viral transcriptome, respectively, throughout virus life cycle. RNA1.2, RNA2.7, and RNA4.9, the three abundantly expressed lncRNAs, appear to be essential in all infection states. Among these three lncRNAs, depletion of RNA2.7 and RNA4.9 results in the greatest defect in maintaining latent reservoir and promoting lytic replication, respectively. Moreover, we delineated the global post-transcriptional nature of HCMV lncRNAs by nanopore direct RNA sequencing and interactome analysis. We revealed that the lncRNAs are modified with N⁶-methyladenosine (m⁶A) and interact with m⁶A readers in all infection states. In-depth analysis demonstrated that m⁶A machineries stabilize HCMV lncRNAs, which could account for the overwhelming abundance of viral lncRNAs. Our study lays the groundwork for understanding the viral lncRNA-mediated regulation of host-virus interaction throughout the HCMV life cycle.

Multilevel regulation of N6-methyladenosine RNA modifications: Implications in tumorigenesis and therapeutic opportunities

N⁶-methyladenosine (m⁶A) RNA modification is widely perceived as the most abundant and common modification in transcripts. This modification is dynamically regulated by specific m⁶A "writers", "erasers" and "readers" and is reportedly involved in the occurrence and development of many diseases. Since m⁶A RNA modification was discovered in the 1970s, with the progress of relevant research technologies, an increasing number of functions of m⁶A have been reported, and a preliminary understanding of m⁶A has been obtained. In this review, we summarize the mechanisms through which m⁶A RNA modification is regulated from the perspectives of expression, posttranslational modification and protein interaction. In addition, we also summarize how external and internal environmental factors affect m⁶A RNA modification and its functions in tumors. The mechanisms through which m⁶A methylases, m⁶A demethylases and m⁶A-binding proteins are regulated are complicated and have not been fully elucidated. Therefore, we hope to promote further research in this field by summarizing these mechanisms and look forward to the future application of m⁶A in tumors.

Inhibition of RNA Binding in SND1 Increases the Levels of miR-1-3p and Sensitizes Cancer Cells to Navitoclax

Simple Summary

Despite of decades of intensive research, several cancer types, for example aggressive colon cancers, are still difficult to treat, and life expectancy is low. Since cancer cells are often resilient and tolerate chemical stresses such as cancer drugs efficiently, they have been difficult to treat. Therefore, combined treatment methods that target cancer cells’ stress tolerance may enhance the treatment outcome. Here we have shown that certain cancer drugs are more effective in colon cancer cells when the expression of a protein called SND1, implicated in regulation of stress responses, is prevented in those cells. We also found that a drug compound called suramin binds to a certain “pocket” of an SND1 protein, and this prevents the interaction of SND1 and certain small RNA molecules, called microRNAs. This block of SND1-microRNA interaction reduces the resilience of colon cancer cells and thus sensitizes them to cancer treatment.

Abstract

SND1 is an RNA-binding protein overexpressed in large variety of cancers. SND1 has been proposed to enhance stress tolerance in cancer cells, but the molecular mechanisms are still poorly understood. We analyzed the expression of 372 miRNAs in the colon carcinoma cell line and show that SND1 silencing increases the expression levels of several tumor suppressor miRNAs. Furthermore, SND1 knockdown showed synergetic effects with cancer drugs through MEK-ERK and Bcl-2 family-related apoptotic pathways. To explore whether the SND1-mediated RNA binding/degradation is responsible for the observed effect, we developed a screening assay to identify small molecules that inhibit the RNA-binding function of SND1. The screen identified P2X purinoreceptor antagonists as the most potent inhibitors. Validation confirmed that the best hit, suramin, inhibits the RNA binding ability of SND1. The binding characteristics and mode of suramin to SND1 were characterized biophysically and by molecular docking that identified positively charged binding cavities in Staphylococcus nuclease domains. Importantly, suramin-mediated inhibition of RNA binding increased the expression of miR-1-3p, and enhanced sensitivity of cancer cells to Bcl-2 inhibitor navitoclax treatment. Taken together, we demonstrate as proof-of-concept a mechanism and an inhibitor compound for SND1 regulation of the survival of cancer cells through tumor suppressor miRNAs.

The m6A reader YTHDC2 is essential for escape from KSHV SOX-induced RNA decay

The role of N6-methyladenosine (m6A) modifications has increasingly been associated with a diverse set of roles in modulating viruses and influencing the outcomes of viral infection. Here, we report that the landscape of m6A deposition is drastically shifted during Kaposi's sarcoma-associated herpesvirus (KSHV) lytic infection for both viral and host transcripts. In line with previous reports, we also saw an overall decrease in host methylation in favor of viral messenger RNA (mRNA), along with 5' hypomethylation and 3' hypermethylation. During KSHV lytic infection, a major shift in overall mRNA abundance is driven by the viral endoribonuclease SOX, which induces the decay of greater than 70% of transcripts. Here, we reveal that interlukin-6 (IL-6) mRNA, a well-characterized, SOX-resistant transcript, is m6A modified during lytic infection. Furthermore, we show that this modification falls within the IL-6 SOX resistance element, an RNA element in the IL-6 3' untranslated region (UTR) that was previously shown to be sufficient for protection from SOX cleavage. We show that the presence of this m6A modification is essential to confer SOX resistance to the IL-6 mRNA. We next show that this modification recruits the m6A reader YTHDC2 and found that YTHDC2 is necessary for the escape of the IL-6 transcript. These results shed light on how the host cell has evolved to use RNA modifications to circumvent viral manipulation of RNA fate during KSHV infection.

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN): The Present and Future of the Burgeoning Field

The International Society of RNA Nanotechnology and Nanomedicine (ISRNN) hosts an annual meeting series focused on presenting the latest research achievements involving RNA-based therapeutics and strategies, aiming to expand their current biomedical applications while overcoming the remaining challenges of the burgeoning field of RNA nanotechnology. The most recent online meeting hosted a series of engaging talks and discussions from an international cohort of leading nanotechnologists that focused on RNA modifications and modulation, dynamic RNA structures, overcoming delivery limitations using a variety of innovative platforms and approaches, and addressing the newly explored potential for immunomodulation with programmable nucleic acid nanoparticles. In this Nano Focus, we summarize the main discussion points, conclusions, and future directions identified during this two-day webinar as well as more recent advances to highlight and to accelerate this exciting field.

Beyond sequencing: machine learning algorithms extract biology hidden in Nanopore signal data

Nanopore sequencing provides signal data corresponding to the nucleotide motifs sequenced. Through machine learning-based methods, these signals are translated into long-read sequences that overcome the read size limit of short-read sequencing. However, analyzing the raw nanopore signal data provides many more opportunities beyond just sequencing genomes and transcriptomes: algorithms that use machine learning approaches to extract biological information from these signals allow the detection of DNA and RNA modifications, the estimation of poly(A) tail length, and the prediction of RNA secondary structures. In this review, we discuss how developments in machine learning methodologies contributed to more accurate basecalling and lower error rates, and how these methods enable new biological discoveries. We argue that direct nanopore sequencing of DNA and RNA provides a new dimensionality for genomics experiments and highlight challenges and future directions for computational approaches to extract the additional information provided by nanopore signal data.