Detection of A-to-I RNA Editing in SARS-COV-2

Identification of key gene expression associated with quality of life after recovery from COVID-19

Post-acute sequelae of COVID-19 (PASC) is a persistent complication of severe acute respiratory syndrome coronavirus 2 infection that includes symptoms, such as fatigue, cognitive impairment, and respiratory distress. These symptoms severely affect the quality of life of patients after their recovery from COVID-19. In this study, a group of machine learning algorithms analyzed the whole blood RNA-seq data from patients with different PASC levels. The purpose of this analysis was to identify the gene markers associated with PASC and the special expression patterns for different PASC levels. By comparing the quality of life of patients after the acute phase of COVID-19 and before the disease, samples in the dataset were divided into three groups, namely, "Better," "The Same," and "Worse." Each patient was represented by the expression levels of 58,929 genes. The machine learning-based workflow included six feature-ranking algorithms, incremental feature selection (IFS), and four classification algorithms. The feature ranking algorithms were in charge of assessing feature importance, whereas IFS with classification algorithms were used to extract essential genes and to construct efficient classifiers and classification rules. The expression of top genes in the results was associated with the immune response to viral infection, which is supported by the published literature. For example, patients with low CCDC18 expression and high CPED1 expression had good quality of life, whereas those with low CDC16 expression had poor quality of life.

Mutational signature dynamics indicate SARS-CoV-2's evolutionary capacity is driven by host antiviral molecules

The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to more efficient human infection since the emergence of this new human coronavirus in late 2019. Here, we use machine learning models to identify shared signatures, i.e., common underlying mutational processes and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and virus properties were associated with the waves of regional SARS-CoV-2 reported infection numbers and this impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity and the effectiveness of government stringency. To assess underlying evolutionary change, we used non-negative matrix factorisation and observed three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 1, 2 and 3 were biased to C→T, T→C/A→G and G→T point mutations. We hypothesise assignments of these mutational signatures to the host antiviral molecules APOBEC, ADAR and ROS respectively. We observe a shift amidst the pandemic in relative mutational signature activity from predominantly Signature 1 changes to an increasingly high proportion of changes consistent with Signature 2. This could represent changes in how the virus and the host immune response interact and indicates how SARS-CoV-2 may continue to generate variation in the future. Linkage of the detected mutational signatures to the VOC-defining amino acids substitutions indicates the majority of SARS-CoV-2's evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.

Differential RNA editing landscapes in host cell versus the SARS-CoV-2 genome

The SARS-CoV-2 pandemic was defined by the emergence of new variants formed through virus mutation originating from random errors not corrected by viral proofreading and/or the host antiviral response introducing mutations into the viral genome. While sequencing information hints at cellular RNA editing pathways playing a role in viral evolution, here, we use an in vitro human cell infection model to assess RNA mutation types in two SARS-CoV-2 strains representing the original and the alpha variants. The variants showed both different cellular responses and mutation patterns with alpha showing higher mutation frequency with most substitutions observed being C-U, indicating an important role for apolipoprotein B mRNA editing catalytic polypeptide-like editing. Knockdown of select APOBEC3s through RNAi increased virus production in the original virus, but not in alpha. Overall, these data suggest a deaminase-independent anti-viral function of APOBECs in SARS-CoV-2 while the C-U editing itself might function to enhance genetic diversity enabling evolutionary adaptation.

A-to-I RNA editing by ADAR and its therapeutic applications: From viral infections to cancer immunotherapy

ADAR deaminases catalyze adenosine-to-inosine (A-to-I) editing on double-stranded RNA (dsRNA) substrates that regulate an umbrella of biological processes. One of the two catalytically active ADAR enzymes, ADAR1, plays a major role in innate immune responses by suppression of RNA sensing pathways which are orchestrated through the ADAR1-dsRNA-MDA5 axis. Unedited immunogenic dsRNA substrates are potent ligands for the cellular sensor MDA5. Upon activation, MDA5 leads to the induction of interferons and expression of hundreds of interferon-stimulated genes with potent antiviral activity. In this way, ADAR1 acts as a gatekeeper of the RNA sensing pathway by striking a fine balance between innate antiviral responses and prevention of autoimmunity. Reduced editing of immunogenic dsRNA by ADAR1 is strongly linked to the development of common autoimmune and inflammatory diseases. In viral infections, ADAR1 exhibits both antiviral and proviral effects. This is modulated by both editing-dependent and editing-independent functions, such as PKR antagonism. Several A-to-I RNA editing events have been identified in viruses, including in the insidious viral pathogen, SARS-CoV-2 which regulates viral fitness and infectivity, and could play a role in shaping viral evolution. Furthermore, ADAR1 is an attractive target for immuno-oncology therapy. Overexpression of ADAR1 and increased dsRNA editing have been observed in several human cancers. Silencing ADAR1, especially in cancers that are refractory to immune checkpoint inhibitors, is a promising therapeutic strategy for cancer immunotherapy in conjunction with epigenetic therapy. The mechanistic understanding of dsRNA editing by ADAR1 and dsRNA sensing by MDA5 and PKR holds great potential for therapeutic applications. This article is categorized under: RNA Processing > RNA Editing and Modification RNA in Disease and Development > RNA in Disease.

No evidence for epitranscriptomic m5C modification of SARS-CoV-2, HIV and MLV viral RNA

The addition of chemical groups to cellular RNA to modulate RNA fate and/or function is summarized under the term epitranscriptomic modification. More than 170 different modifications have been identified on cellular RNA, such as tRNA, rRNA and, to a lesser extent, on other RNA types. Recently, epitranscriptomic modification of viral RNA has received considerable attention as a possible additional mechanism regulating virus infection and replication. N6-methyladenosine (m6A) and C5-methylcytosine (m5C) have been most broadly studied in different RNA viruses. Various studies, however, reported varying results with regard to number and extent of the modification. Here we investigated the m5C methylome of SARS-CoV-2, and we reexamined reported m5C sites in HIV and MLV. Using a rigorous bisulfite-sequencing protocol and stringent data analysis, we found no evidence for the presence of m5C in these viruses. The data emphasize the necessity for optimizing experimental conditions and bioinformatic data analysis.

Retrospect of the Two-Year Debate: What Fuels the Evolution of SARS-CoV-2: RNA Editing or Replication Error?

Mutation is one of the mechanisms of the evolutionary divergence of an organism. Under this global COVID-19 pandemic, the fast evolution of SARS-CoV-2 became one of the most worrying issues. Some researchers believed that the hosts' RNA deamination systems (APOBECs and ADARs) are the major source of mutations and have driven the evolution of SARS-CoV-2. However, apart from RNA editing, the RDRP (RNA-dependent RNA polymerase)-mediated replication errors may also contribute to the mutation of SARS-CoV-2 (just like the single-nucleotide polymorphisms/variations in eukaryotes caused by DNA replication errors). Unfortunately, it is technically unable to distinguish RNA editing and replication errors (SNPs) in this RNA virus. Here comes a fundamental question: we indeed observed the fast evolution of SARS-CoV-2, but what exactly fuels its evolution: RNA editing or replication errors? This debate lasts for 2 years. In this piece, we will retrospect the 2-year debate on RNA editing versus SNPs.

Host-mediated RNA editing in viruses

Viruses rely on hosts for life and reproduction, cause a variety of symptoms from common cold to AIDS to COVID-19 and provoke public health threats claiming millions of lives around the globe. RNA editing, as a crucial co-/post-transcriptional modification inducing nucleotide alterations on both endogenous and exogenous RNA sequences, exerts significant influences on virus replication, protein synthesis, infectivity and toxicity. Hitherto, a number of host-mediated RNA editing sites have been identified in diverse viruses, yet lacking a full picture of RNA editing-associated mechanisms and effects in different classes of viruses. Here we synthesize the current knowledge of host-mediated RNA editing in a variety of viruses by considering two enzyme families, viz., ADARs and APOBECs, thereby presenting a landscape of diverse editing mechanisms and effects between viruses and hosts. In the ongoing pandemic, our study promises to provide potentially valuable insights for better understanding host-mediated RNA editing on ever-reported and newly-emerging viruses.

The efficacy and safety of SARS-CoV-2 vaccines mRNA1273 and BNT162b2 might be complicated by rampant C-to-U RNA editing

The SARS-CoV-2 RNA vaccines are smartly designed to increase the synonymous codon usage by introducing multiple U-to-C mutations. This design would elevate the translation efficiency of vaccine RNAs. However, we found evidence to reason that the designed cytidines might be converted to uridines again by C-to-U RNA deamination in host cells. This C-to-U mechanism might be a main factor that affects the efficacy and safety of RNA vaccines.

Evidence Supporting That C-to-U RNA Editing Is the Major Force That Drives SARS-CoV-2 Evolution

Mutations of DNA organisms are introduced by replication errors. However, SARS-CoV-2, as an RNA virus, is additionally subjected to rampant RNA editing by hosts. Both resources contributed to SARS-CoV-2 mutation and evolution, but the relative prevalence of the two origins is unknown. We performed comparative genomic analyses at intra-species (world-wide SARS-CoV-2 strains) and inter-species (SARS-CoV-2 and RaTG13 divergence) levels. We made prior predictions of the proportion of each mutation type (nucleotide substitution) under different scenarios and compared the observed versus the expected. C-to-T alteration, representing C-to-U editing, is far more abundant that all other mutation types. Derived allele frequency (DAF) as well as novel mutation rate of C-to-T are the highest in SARS-CoV-2 population, and C-T substitution dominates the divergence sites between SARS-CoV-2 and RaTG13. This is compelling evidence suggesting that C-to-U RNA editing is the major source of SARS-CoV-2 mutation. While replication errors serve as a baseline of novel mutation rate, the C-to-U editing has elevated the mutation rate for orders of magnitudes and accelerates the evolution of the virus.

C-to-U RNA deamination is the driving force accelerating SARS-CoV-2 evolution

Understanding the molecular mechanism underlying the rampant mutation of SARS-CoV-2 would help us control the COVID-19 pandemic. The APOBEC-mediated C-to-U deamination is a major mutation type in the SARS-CoV-2 genome. However, it is unclear whether the novel mutation rate u is higher for C-to-U than for other mutation types, and what the detailed driving force is. By analyzing the time course SARS-CoV-2 global population data, we found that C-to-U has the highest novel mutation rate u among all mutation types and that this u is still increasing with time (du/dt > 0). Novel C-to-U events, rather than other mutation types, have a preference over particular genomic regions. A less local RNA structure is correlated with a high novel C-to-U mutation rate. A cascade model nicely explains the du/dt > 0 for C-to-U deamination. In SARS-CoV-2, the RNA structure serves as the molecular basis of the extremely high and continuously accelerating C-to-U deamination rate. This mechanism is the driving force of the mutation, adaptation, and evolution of SARS-CoV-2. Our findings help us understand the dynamic evolution of the virus mutation rate.

(Epi)transcriptomics in cardiovascular and neurological complications of COVID-19

Although systemic inflammation and pulmonary complications increase the mortality rate in COVID-19, a broad spectrum of cardiovascular and neurological complications can also contribute to significant morbidity and mortality. The molecular mechanisms underlying cardiovascular and neurological complications during and after SARS-CoV-2 infection are incompletely understood. Recently reported perturbations of the epitranscriptome of COVID-19 patients indicate that mechanisms including those derived from RNA modifications and non-coding RNAs may play a contributing role in the pathogenesis of COVID-19. In this review paper, we gathered recently published studies investigating (epi)transcriptomic fluctuations upon SARS-CoV-2 infection, focusing on the brain-heart axis since neurological and cardiovascular events and their sequelae are of utmost prevalence and importance in this disease.

Rampant C-to-U deamination accounts for the intrinsically high mutation rate in SARS-CoV-2 spike gene

The high mutation rate of SARS-CoV-2 largely complicates our control of the pandemic. In particular, it is currently unclear why the spike (S) gene has an extraordinarily high mutation rate among all SARS-CoV-2 genes. By analyzing the occurrence of fixed synonymous mutations between SARS-CoV-2 and RaTG13, and profiling the DAF (derived allele frequency) of polymorphic synonymous sites among millions of worldwide SARS-CoV-2 strains, we found that both fixed and polymorphic mutations show higher mutation rates in the S gene than other genes. The majority of mutations are C-to-T, representing the APOBEC-mediated C-to-U deamination instead of the previously proposed A-to-I deamination. Both in silico and in vivo evidence indicated that the S gene is more likely to be single-stranded compared to other SARS-CoV-2 genes, agreeing with the APOBEC preference of ssRNA. We conclude that the single-stranded property of the S gene makes it a favorable target for C-to-U deamination, leading to its excessively high mutation rate compared to other non-S genes. In conclusion, APOBEC, rather than ADAR, is the "editor-in-chief" of SARS-CoV-2 RNAs. This work helps us to understand the molecular mechanism underlying the mutation and evolution of SARS-CoV-2, and we believe it will contribute to the control of the pandemic.

RNA editing increases the nucleotide diversity of SARS-CoV-2 in human host cells

SARS-CoV-2 is a positive-sense, single-stranded RNA virus responsible for the COVID-19 pandemic. It remains unclear whether and to what extent the virus in human host cells undergoes RNA editing, a major RNA modification mechanism. Here we perform a robust bioinformatic analysis of metatranscriptomic data from multiple bronchoalveolar lavage fluid samples of COVID-19 patients, revealing an appreciable number of A-to-I RNA editing candidate sites in SARS-CoV-2. We confirm the enrichment of A-to-I RNA editing signals at these candidate sites through evaluating four characteristics specific to RNA editing: the inferred RNA editing sites exhibit (i) stronger ADAR1 binding affinity predicted by a deep-learning model built from ADAR1 CLIP-seq data, (ii) decreased editing levels in ADAR1-inhibited human lung cells, (iii) local clustering patterns, and (iv) higher RNA secondary structure propensity. Our results have critical implications in understanding the evolution of SARS-CoV-2 as well as in COVID-19 research, such as phylogenetic analysis and vaccine development.

The COVID-19 pandemic is caused by SARS-CoV-2, an RNA virus. In the cells of COVID-19 patients, SARS-CoV-2 interacts with human proteins and is potentially subjected to their enzymatic activities. Here we investigated whether human protein enzymes can change the nucleotide sequence of SARS-CoV-2, thereby leaving a unique molecular footprint. We developed a robust computational algorithm to analyze the sequence data of SARS-CoV-2 obtained from lung fluid samples of COVID-19 patients and found that the virus contains new nucleotide changes that are likely induced by ADAR1, a powerful human protein that can modify specific nucleotide positions in many human transcripts. We further confirmed that the characteristics of the nucleotide changes detected in SARS-CoV-2 are similar to those observed in the human genes. Thus, these ADAR1-induced nucleotide changes may represent an under-appreciated force that can affect the evolution of SARS-CoV-2. Our study helps researchers better understand the evolutionary trajectory of SARS-CoV-2.

Commentary on “Poor evidence for host-dependent regular RNA editing in the transcriptome of SARS-CoV-2”

Analysis of the SARS-CoV-2 transcriptome has revealed a background of low-frequency intra-host genetic changes with a strong bias towards transitions. A similar pattern is also observed when inter-host variability is considered. We and others have shown that the cellular RNA editing machinery based on ADAR and APOBEC host-deaminases could be involved in the onset of SARS-CoV-2 genetic variability. Our hypothesis is based both on similarities with other known forms of viral genome editing and on the excess of transition changes, which is difficult to explain with errors during viral replication. Zong et al. criticize our analysis on both conceptual and technical grounds. While ultimate proof of an involvement of host deaminases in viral RNA editing will depend on experimental validation, here, we address the criticism to suggest that viral RNA editing is the most reasonable explanation for the observed intra- and inter-host variability.

Functions and consequences of AID/APOBEC-mediated DNA and RNA deamination

The AID/APOBEC polynucleotide cytidine deaminases have historically been classified as either DNA mutators or RNA editors based on their first identified nucleic acid substrate preference. DNA mutators can generate functional diversity at antibody genes but also cause genomic instability in cancer. RNA editors can generate informational diversity in the transcriptome of innate immune cells, and of cancer cells. Members of both classes can act as antiviral restriction factors. Recent structural work has illuminated differences and similarities between AID/APOBEC enzymes that can catalyse DNA mutation, RNA editing or both, suggesting that the strict functional classification of members of this family should be reconsidered. As many of these enzymes have been employed for targeted genome (or transcriptome) editing, a more holistic understanding will help improve the design of therapeutically relevant programmable base editors.

In this Perspective, Pecori et al. provide an overview of the AID/APOBEC cytidine deaminase family, discussing key structural features, how they contribute to viral and tumour evolution and how they can be harnessed for (potentially therapeutic) base-editing purposes.

Evolutionary trend of SARS-CoV-2 inferred by the homopolymeric nucleotide repeats

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the current global COVID-19 pandemic, in which millions of lives have been lost. Understanding the zoonotic evolution of the coronavirus may provide insights for developing effective vaccines, monitoring the transmission trends, and preventing new zoonotic infections. Homopolymeric nucleotide repeats (HP), the most simple tandem repeats, are a ubiquitous feature of eukaryotic genomes. Yet the HP distributions and roles in coronavirus genome evolution are poorly investigated. In this study, we characterize the HP distributions and trends in the genomes of bat and human coronaviruses and SARS-CoV-2 variants. The results show that the SARS-CoV-2 genome is abundant in HPs, and has augmented HP contents during evolution. Especially, the disparity of HP poly-(A/T) and ploy-(C/G) of coronaviruses increases during the evolution in human hosts. The disparity of HP poly-(A/T) and ploy-(C/G) is correlated to host adaptation and the virulence level of the coronaviruses. Therefore, we propose that the HP disparity can be a quantitative measure for the zoonotic evolution levels of coronaviruses. Peculiarly, the HP disparity measure infers that SARS-CoV-2 Omicron variants have a high disparity of HP poly-(A/T) and ploy-(C/G), suggesting a high adaption to the human hosts.