The roles of APOBEC-mediated RNA editing in SARS-CoV-2 mutations, replication and fitness

RNA editing in host lncRNAs as potential modulator in SARS-CoV-2 variants-host immune response dynamics

Both host and viral RNA editing plays a crucial role in host's response to infection, yet our understanding of host RNA editing remains limited. In this study of in-house generated RNA sequencing (RNA-seq) data of 211 hospitalized COVID-19 patients with PreVOC, Delta, and Omicron variants, we observed a significant differential editing frequency and patterns in long non-coding RNAs (lncRNAs), with Delta group displaying lower RNA editing compared to PreVOC/Omicron patients. Notably, multiple transcripts of UGDH-AS1 and NEAT1 exhibited high editing frequencies. Expression of ADAR1/APOBEC3A/APOBEC3G and differential abundance of repeats were possible modulators of differential editing across patient groups. We observed a shift in crucial infection-related pathways wherein the pathways were downregulated in Delta compared to PreVOC and Omicron. Our genomics-based evidence suggests that lncRNA editing influences stability, miRNA binding, and expression of both lncRNA and target genes. Overall, the study highlights the role of lncRNAs and how editing within host lncRNAs modulates the disease severity.

PHDtools: A platform for pathogen detection and multi-dimensional genetic signatures decoding to realize pathogen genomics data analyses online

OBJECTIVES

Facing the emerging diseases, rapid identification of the pathogen and multi-dimensional characterization of the genomic features at both isolate-level and population-level through high-throughput sequencing data can provide invaluable information to guide the development of antiviral agents and strategies. However, a user-friendly program is in urgent need for clinical laboratories without bioinformatics background to decode the complex big genomics data.

METHODS

In this study, we developed an interactive online platform named PHDtools with a total of 15 functions to analyze metagenomics data to identify the potential pathogen and decode multi-dimensional genetic signatures including intra-/inter-host variations and lineage-level variations. The platform was applied to analyze the meta-genomic data of the samples collected from the 172 imported COVID-19 cases.

RESULTS

According to the analytical results of mNGS, 27 patients were found to have the co-infections of SARS-CoV-2 with either influenza virus (n = 9) or human picobirnavirus (n = 19). Enough coverages of all the assembled SARS-CoV-2 genomes provided the sub-lineages of Omicron variant, and the number of mutations in the non-structural genes and M gene was increased, as well as the intra-host variations occurred in E and M gene were under positive selection (Ka/Ks > 1). These findings of increased or changed mutations in the SARS-CoV-2 genome characterized the current adaptive evolution patterns of Omicron sub-lineages, and revealed the evolution speed of these sub-lineages might increase.

CONCLUSIONS

Consequently, the application of PHDtools has proved that this platform is accurate, user-friendly and convenient for clinical users who are deficient in bioinformatics, and the clinical monitor of SARS-CoV-2 genomes by PHDtools also highlighted the potential evolution features of current SARS-CoV-2 and indicated that the development of anti-SARS-CoV-2 agents and new-designed vaccines should incorporate the gene variations other than S gene.

Targeted accurate RNA consensus sequencing (tARC-seq) reveals mechanisms of replication error affecting SARS-CoV-2 divergence

RNA viruses, like SARS-CoV-2, depend on their RNA-dependent RNA polymerases (RdRp) for replication, which is error prone. Monitoring replication errors is crucial for understanding the virus's evolution. Current methods lack the precision to detect rare de novo RNA mutations, particularly in low-input samples such as those from patients. Here we introduce a targeted accurate RNA consensus sequencing method (tARC-seq) to accurately determine the mutation frequency and types in SARS-CoV-2, both in cell culture and clinical samples. Our findings show an average of 2.68 × 10-5 de novo errors per cycle with a C > T bias that cannot be solely attributed to APOBEC editing. We identified hotspots and cold spots throughout the genome, correlating with high or low GC content, and pinpointed transcription regulatory sites as regions more susceptible to errors. tARC-seq captured template switching events including insertions, deletions and complex mutations. These insights shed light on the genetic diversity generation and evolutionary dynamics of SARS-CoV-2.

Role of SARS-CoV-2 mutations in the evolution of the COVID-19 pandemic

OBJECTIVES

The SARS-CoV-2 pandemic and large-scale genomic surveillance provided an exceptional opportunity to analyze mutations that appeared over three years in viral genomes. Here we studied mutations and their epidemic consequences for SARS-CoV-2 genomes from our center.

METHODS

We analyzed 61,397 SARS-CoV-2 genomes we sequenced from respiratory samples for genomic surveillance. Mutations frequencies were calculated using Nextclade, Microsoft Excel, and an in-house Python script.

RESULTS

A total of 22,225 nucleotide mutations were identified, 220 (1.0%) being each at the root of ≥836 genomes, classifying mutations as 'hyperfertile'. Two seeded the European pandemic: P323L in RNA polymerase, associated with an increased mutation rate, and D614G in spike that improved fitness. Most 'hyperfertile' mutations occurred in areas not predicted with increased virulence. Their mean number was 8±6 (0-22) per 1000 nucleotides per gene. They were 3.7-times more frequent in accessory than informational genes (13.8 versus 3.7/1000 nucleotides). Particularly, they were 4.1-times more frequent in ORF8 than in the RNA polymerase gene. Interestingly, stop codons were present in 97 positions, almost only in accessory genes, including ORF8 (21/100 codons).

CONCLUSIONS

most 'hyperfertile' mutations did not predict emergence of a new epidemic, and some were stop codons indicating the existence of so-named 'non-virulence' genes.

Sequence signatures within the genome of SARS-CoV-2 can be used to predict host source

We conducted an in silico analysis to better understand the potential factors impacting host adaptation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in white-tailed deer, humans, and mink due to the strong evidence of sustained transmission within these hosts. Classification models trained on single nucleotide and amino acid differences between samples effectively identified white-tailed deer-, human-, and mink-derived SARS-CoV-2. For example, the balanced accuracy score of Extremely Randomized Trees classifiers was 0.984 ± 0.006. Eighty-eight commonly identified predictive mutations are found at sites under strong positive and negative selective pressure. A large fraction of sites under selection (86.9%) or identified by machine learning (87.1%) are found in genes other than the spike. Some locations encoded by these gene regions are predicted to be B- and T-cell epitopes or are implicated in modulating the immune response suggesting that host adaptation may involve the evasion of the host immune system, modulation of the class-I major-histocompatibility complex, and the diminished recognition of immune epitopes by CD8+ T cells. Our selection and machine learning analysis also identified that silent mutations, such as C7303T and C9430T, play an important role in discriminating deer-derived samples across multiple clades. Finally, our investigation into the origin of the B.1.641 lineage from white-tailed deer in Canada discovered an additional human sequence from Michigan related to the B.1.641 lineage sampled near the emergence of this lineage. These findings demonstrate that machine-learning approaches can be used in combination with evolutionary genomics to identify factors possibly involved in the cross-species transmission of viruses and the emergence of novel viral lineages.IMPORTANCESevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly transmissible virus capable of infecting and establishing itself in human and wildlife populations, such as white-tailed deer. This fact highlights the importance of developing novel ways to identify genetic factors that contribute to its spread and adaptation to new host species. This is especially important since these populations can serve as reservoirs that potentially facilitate the re-introduction of new variants into human populations. In this study, we apply machine learning and phylogenetic methods to uncover biomarkers of SARS-CoV-2 adaptation in mink and white-tailed deer. We find evidence demonstrating that both non-synonymous and silent mutations can be used to differentiate animal-derived sequences from human-derived ones and each other. This evidence also suggests that host adaptation involves the evasion of the immune system and the suppression of antigen presentation. Finally, the methods developed here are general and can be used to investigate host adaptation in viruses other than SARS-CoV-2.

Properties and Mechanisms of Deletions, Insertions, and Substitutions in the Evolutionary History of SARS-CoV-2

SARS-CoV-2 has accumulated many mutations since its emergence in late 2019. Nucleotide substitutions leading to amino acid replacements constitute the primary material for natural selection. Insertions, deletions, and substitutions appear to be critical for coronavirus's macro- and microevolution. Understanding the molecular mechanisms of mutations in the mutational hotspots (positions, loci with recurrent mutations, and nucleotide context) is important for disentangling roles of mutagenesis and selection. In the SARS-CoV-2 genome, deletions and insertions are frequently associated with repetitive sequences, whereas C>U substitutions are often surrounded by nucleotides resembling the APOBEC mutable motifs. We describe various approaches to mutation spectra analyses, including the context features of RNAs that are likely to be involved in the generation of recurrent mutations. We also discuss the interplay between mutations and natural selection as a complex evolutionary trend. The substantial variability and complexity of pipelines for the reconstruction of mutations and the huge number of genomic sequences are major problems for the analyses of mutations in the SARS-CoV-2 genome. As a solution, we advocate for the development of a centralized database of predicted mutations, which needs to be updated on a regular basis.

Molecular mechanism for regulating APOBEC3G DNA editing function by the non-catalytic domain

APOBEC3G (A3G) belongs to the AID/APOBEC cytidine deaminase family and is essential for antiviral immunity. It contains two zinc-coordinated cytidine-deaminase (CD) domains. The N-terminal CD1 domain is non-catalytic but has a strong affinity for nucleic acids, whereas the C-terminal CD2 domain catalyzes C-to-U editing in single-stranded DNA. The interplay between the two domains in DNA binding and editing is not fully understood. Here, our studies on rhesus macaque A3G (rA3G) show that the DNA editing function in linear and hairpin loop DNA is greatly enhanced by AA or GA dinucleotide motifs present downstream (in the 3'-direction) but not upstream (in the 5'-direction) of the target-C editing sites. The effective distance between AA/GA and the target-C sites depends on the local DNA secondary structure. We present two co-crystal structures of rA3G bound to ssDNA containing AA and GA, revealing the contribution of the non-catalytic CD1 domain in capturing AA/GA DNA and explaining our biochemical observations. Our structural and biochemical findings elucidate the molecular mechanism underlying the cooperative function between the non-catalytic and the catalytic domains of A3G, which is critical for its antiviral role and its contribution to genome mutations in cancer.

The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19

BACKGROUND

The evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.

RESULTS

The prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.

CONCLUSION

Identified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.

SARS-CoV-2 rapidly evolves lineage-specific phenotypic differences when passaged repeatedly in immune-naïve mice

The persistence of SARS-CoV-2 despite the development of vaccines and a degree of herd immunity is partly due to viral evolution reducing vaccine and treatment efficacy. Serial infections of wild-type (WT) SARS-CoV-2 in Balb/c mice yield mouse-adapted strains with greater infectivity and mortality. We investigate if passaging unmodified B.1.351 (Beta) and B.1.617.2 (Delta) 20 times in K18-ACE2 mice, expressing the human ACE2 receptor, in a BSL-3 laboratory without selective pressures, drives human health-relevant evolution and if evolution is lineage-dependent. Late-passage virus causes more severe disease, at organism and lung tissue scales, with late-passage Delta demonstrating antibody resistance and interferon suppression. This resistance co-occurs with a de novo spike S371F mutation, linked with both traits. S371F, an Omicron-characteristic mutation, is co-inherited at times with spike E1182G per Nanopore sequencing, existing in different within-sample viral variants at others. Both S371F and E1182G are linked to mammalian GOLGA7 and ZDHHC5 interactions, which mediate viral-cell entry and antiviral response. This study demonstrates SARS-CoV-2's tendency to evolve with phenotypic consequences, its evolution varying by lineage, and suggests non-dominant quasi-species contribution.

Gene expression profiling of host lipid metabolism in SARS-CoV-2 infected patients: a systematic review and integrated bioinformatics analysis

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown.

METHODS

Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.

RESULTS

The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.

CONCLUSIONS

Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.

Coronavirus takeover of host cell translation and intracellular antiviral response: a molecular perspective

Coronaviruses are a group of related RNA viruses that cause respiratory diseases in humans and animals. Understanding the mechanisms of translation regulation during coronaviral infections is critical for developing antiviral therapies and preventing viral spread. Translation of the viral single-stranded RNA genome in the host cell cytoplasm is an essential step in the life cycle of coronaviruses, which affects the cellular mRNA translation landscape in many ways. Here we discuss various viral strategies of translation control, including how members of the Betacoronavirus genus shut down host cell translation and suppress host innate immune functions, as well as the role of the viral non-structural protein 1 (Nsp1) in the process. We also outline the fate of viral RNA, considering stress response mechanisms triggered in infected cells, and describe how unique viral RNA features contribute to programmed ribosomal -1 frameshifting, RNA editing, and translation shutdown evasion.

Regulatory variants of APOBEC3 genes potentially associate with COVID-19 severity in populations with African ancestry

Since November 2019, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused the worldwide pandemic of the coronavirus disease 2019 (COVID-19), the impact of which is huge to the lives of world populations. Many studies suggested that such situation will continue due to the endless mutations in SARS-CoV-2 genome that result in complexity of the efforts for the control of SARS-CoV-2, since the special enrichment of nucleotide substitution C>U in SARS-CoV-2 sequences were discovered mainly due to the editing by human host factors APOBEC3 genes. The observation of SARS-CoV-2 variants Beta (B.1.351) and Omicron (B.1.1.529) firstly spreading in South Africa promoted us to hypothesize that genetic variants of APOBEC3 special in African populations may be attributed to the higher mutation rate of SARS-CoV-2 variants in Africa. Current study was conducted to search for functional variants of APOBEC3 genes associate with COVID-19 hospitalization in African population. By integrating data from the 1000 Genomes Project, Genotype-Tissue Expression (GTEx), and Host Genetics Initiative (HGI) of COVID-19, we identified potential functional SNPs close to APOBEC3 genes that are associated with COVID-19 hospitalization in African but not with other populations. Our study provides new insights on the potential contribution of APOBEC3 genes on the evolution of SARS-CoV-2 mutations in African population, but further replication is needed to confirm our results.

Identification of RBM46 as a novel APOBEC1 cofactor for C-to-U RNA-editing activity

Cytidine (C) to Uridine (U) RNA editing is a post-transcription modification that is involved in diverse biological processes. APOBEC1 (A1) catalyzes the conversion of C-to-U in RNA, which is important in regulating cholesterol metabolism through its editing activity on ApoB mRNA. However, A1 requires a cofactor to form an "editosome" for RNA editing activity. A1CF and RBM47, both RNA-binding proteins, have been identified as cofactors that pair with A1 to form editosomes and edit ApoB mRNA and other cellular RNAs. SYNCRIP is another RNA-binding protein that has been reported as a potential regulator of A1, although it is not directly involved in A1 RNA editing activity. Here, we describe the identification and characterization of a novel cofactor, RBM46 (RNA-Binding-Motif-protein-46), that can facilitate A1 to perform C-to-U editing on ApoB mRNA. Additionally, using the low-error circular RNA sequencing technique, we identified novel cellular RNA targets for the A1/RBM46 editosome. Our findings provide further insight into the complex regulatory network of RNA editing and the potential new function of A1 with its cofactors.

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.

From viral democratic genomes to viral wild bunch of quasispecies

The tremendous majority of RNA genomes from pathogenic viruses analyzed and deposited in databases are consensus or "democratic" genomes. They represent the genomes most frequently found in the clinical samples of patients but do not account for the huge genetic diversity of coexisting genomes, which is better described as quasispecies. A viral quasispecies is defined as the dynamic distribution of nonidentical but closely related mutants, variants, recombinant, or reassortant viral genomes. Viral quasispecies have collective behavior and dynamics and are the subject of internal interactions that comprise interference, complementation, or cooperation. In the setting of SARS-CoV-2 infection, intrahost SARS-CoV-2 genetic diversity was recently notably reported for immunocompromised, chronically infected patients, for patients treated with monoclonal antibodies targeting the viral spike protein, and for different body compartments of a single patient. A question that deserves attention is whether such diversity is generated postinfection from a clonal genome in response to selection pressure or is already present at the time of infection as a quasispecies. In the present review, we summarize the data supporting that hosts are infected by a "wild bunch" of viruses rather than by multiple virions sharing the same genome. Each virion in the "wild bunch" may have different virulence and tissue tropisms. As the number of viruses replicated during host infections is huge, a viral quasispecies at any time of infection is wide and is also influenced by host-specific selection pressure after infection, which accounts for the difficulty in deciphering and predicting the appearance of more fit variants and the evolution of epidemics of novel RNA viruses.

HSV-1 miRNAs are post-transcriptionally edited in latently infected human ganglia

IMPORTANCE

Herpes simplex virus 1 is an important human pathogen that has been intensively studied for many decades. Nevertheless, the molecular mechanisms regulating its establishment, maintenance, and reactivation from latency are poorly understood. Here, we show that HSV-1-encoded miR-H2 is post-transcriptionally edited in latently infected human tissues. Hyperediting of viral miRNAs increases the targeting potential of these miRNAs and may play an important role in regulating latency. We show that the edited miR-H2 can target ICP4, an essential viral protein. Interestingly, we found no evidence of hyperediting of its homolog, miR-H2, which is expressed by the closely related virus HSV-2. The discovery of post-translational modifications of viral miRNA in the latency phase suggests that these processes may also be important for other non-coding viral RNA in the latency phase, including the intron LAT, which in turn may be crucial for understanding the biology of this virus.

Long-term dynamic shifts in genomic base content and evolutionary trajectories of SARS-CoV-2 variants

The rapid spread and remarkable mutations of SARS-CoV-2 variants, particularly Omicron, necessitate an understanding of their evolutionary characteristics. In this study, we analyzed representative high-quality whole-genome sequences of 2008 SARS-CoV-2 variants to explore long-term dynamic changes in genomic base (especially GC) content and variations during viral evolution. Our results demonstrated a highly negative correlation between GC content and variant emergence time (r = -0.765, p < 2.22e-16). Major gene partitions (S, N, ORF1ab) displayed similar trends. Omicron exhibited a significantly lower GC content than non-Omicron variants (p < 2.22e-16). Notably, we observed a robust negative correlation between C and T content (r = -0.778, p < 2.22e-16) and between G and A content (r = -0.773, p < 2.22e-16). Among all strains, Omicron showed the greatest base variation, with C->T mutations being the most frequent (median [interquartile range [IQR]]: 29 (27, 31), 37.67%), succeeded by G->A mutations (11 (9, 13), 14.63%). Over a 3-year span, an annual decline rate of 0.12% in SARS-CoV-2 GC content was observed and could become more pronounced in future emerging variants. These findings provided insights into the evolutionary trajectory of SARS-CoV-2, underscoring the significance of continuous genomic surveillance for effective prediction of and response to future variants.

Unraveling the Enzyme-Substrate Properties for APOBEC3A-Mediated RNA Editing

The APOBEC3 family of human cytidine deaminases is involved in various cellular processes, including the innate and acquired immune system, mostly through inducing C-to-U in single-stranded DNA and/or RNA mutations. Although recent studies have examined RNA editing by APOBEC3A (A3A), its intracellular target specificity are not fully characterized. To address this gap, we performed in-depth analysis of cellular RNA editing using our recently developed sensitive cell-based fluorescence assay. Our findings demonstrate that A3A and an A3A-loop1-containing APOBEC3B (A3B) chimera are capable of RNA editing. We observed that A3A prefers to edit specific RNA substrates which are not efficiently deaminated by other APOBEC members. The editing efficiency of A3A is influenced by the RNA sequence contexts and distinct stem-loop secondary structures. Based on the identified RNA specificity features, we predicted potential A3A-editing targets in the encoding region of cellular mRNAs and discovered novel RNA transcripts that are extensively edited by A3A. Furthermore, we found a trend of increased synonymous mutations at the sites for more efficient A3A-editing, indicating evolutionary adaptation to the higher editing rate by A3A. Our results shed light on the intracellular RNA editing properties of A3A and provide insights into new RNA targets and potential impact of A3A-mediated RNA editing.

Accelerated evolution of SARS-CoV-2 in free-ranging white-tailed deer

The zoonotic origin of the COVID-19 pandemic virus highlights the need to fill the vast gaps in our knowledge of SARS-CoV-2 ecology and evolution in non-human hosts. Here, we detected that SARS-CoV-2 was introduced from humans into white-tailed deer more than 30 times in Ohio, USA during November 2021-March 2022. Subsequently, deer-to-deer transmission persisted for 2-8 months, disseminating across hundreds of kilometers. Newly developed Bayesian phylogenetic methods quantified how SARS-CoV-2 evolution is not only three-times faster in white-tailed deer compared to the rate observed in humans but also driven by different mutational biases and selection pressures. The long-term effect of this accelerated evolutionary rate remains to be seen as no critical phenotypic changes were observed in our animal models using white-tailed deer origin viruses. Still, SARS-CoV-2 has transmitted in white-tailed deer populations for a relatively short duration, and the risk of future changes may have serious consequences for humans and livestock.

COVID-19 annual update: a narrative review

Three and a half years after the pandemic outbreak, now that WHO has formally declared that the emergency is over, COVID-19 is still a significant global issue. Here, we focus on recent developments in genetic and genomic research on COVID-19, and we give an outlook on state-of-the-art therapeutical approaches, as the pandemic is gradually transitioning to an endemic situation. The sequencing and characterization of rare alleles in different populations has made it possible to identify numerous genes that affect either susceptibility to COVID-19 or the severity of the disease. These findings provide a beginning to new avenues and pan-ethnic therapeutic approaches, as well as to potential genetic screening protocols. The causative virus, SARS-CoV-2, is still in the spotlight, but novel threatening virus could appear anywhere at any time. Therefore, continued vigilance and further research is warranted. We also note emphatically that to prevent future pandemics and other world-wide health crises, it is imperative to capitalize on what we have learnt from COVID-19: specifically, regarding its origins, the world's response, and insufficient preparedness. This requires unprecedented international collaboration and timely data sharing for the coordination of effective response and the rapid implementation of containment measures.

Increased interregional virus exchange and nucleotide diversity outline the expansion of chikungunya virus in Brazil

The emergence and reemergence of mosquito-borne diseases in Brazil such as yellow fever, zika, chikungunya, and dengue have had serious impacts on public health. Concerns have been raised due to the rapid dissemination of the chikungunya virus across the country since its first detection in 2014 in Northeast Brazil. In this work, we carried out on-site training activities in genomic surveillance in partnership with the National Network of Public Health Laboratories that have led to the generation of 422 chikungunya virus genomes from 12 Brazilian states over the past two years (2021-2022), a period that has seen more than 312 thousand chikungunya fever cases reported in the country. These genomes increased the amount of available data and allowed a more comprehensive characterization of the dispersal dynamics of the chikungunya virus East-Central-South-African lineage in Brazil. Tree branching patterns revealed the emergence and expansion of two distinct subclades. Phylogeographic analysis indicated that the northeast region has been the leading hub of virus spread towards other regions. Increased frequency of C > T transitions among the new genomes suggested that host restriction factors from the immune system such as ADAR and AID/APOBEC deaminases might be driving the genetic diversity of the chikungunya virus in Brazil.

Proteomic applications in identifying protein-protein interactions

There are many things that can be used to characterize a protein. Size, isoelectric point, hydrophobicity, structure (primary to quaternary), and subcellular location are just a few parameters that are used. The most important feature of a protein, however, is its function. While there are many experiments that can indicate a protein's role, identifying the molecules it interacts with is probably the most definitive way of determining its function. Owing to technology limitations, protein interactions have historically been identified on a one molecule per experiment basis. The advent of high throughput multiplexed proteomic technologies in the 1990s, however, made identifying hundreds and thousands of proteins interactions within single experiments feasible. These proteomic technologies have dramatically increased the rate at which protein-protein interactions (PPIs) are discovered. While the improvement in mass spectrometry technology was an early driving force in the rapid pace of identifying PPIs, advances in sample preparation and chromatography have recently been propelling the field. In this chapter, we will discuss the importance of identifying PPIs and describe current state-of-the-art technologies that demonstrate what is currently possible in this important area of biological research.

The Mutational Landscape of SARS-CoV-2

Mutation research is crucial for detecting and treating SARS-CoV-2 and developing vaccines. Using over 5,300,000 sequences from SARS-CoV-2 genomes and custom Python programs, we analyzed the mutational landscape of SARS-CoV-2. Although almost every nucleotide in the SARS-CoV-2 genome has mutated at some time, the substantial differences in the frequency and regularity of mutations warrant further examination. C>U mutations are the most common. They are found in the largest number of variants, pangolin lineages, and countries, which indicates that they are a driving force behind the evolution of SARS-CoV-2. Not all SARS-CoV-2 genes have mutated in the same way. Fewer non-synonymous single nucleotide variations are found in genes that encode proteins with a critical role in virus replication than in genes with ancillary roles. Some genes, such as spike (S) and nucleocapsid (N), show more non-synonymous mutations than others. Although the prevalence of mutations in the target regions of COVID-19 diagnostic RT-qPCR tests is generally low, in some cases, such as for some primers that bind to the N gene, it is significant. Therefore, ongoing monitoring of SARS-CoV-2 mutations is crucial. The SARS-CoV-2 Mutation Portal provides access to a database of SARS-CoV-2 mutations.

The evolution of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of deaths and substantial morbidity worldwide. Intense scientific effort to understand the biology of SARS-CoV-2 has resulted in daunting numbers of genomic sequences. We witnessed evolutionary events that could mostly be inferred indirectly before, such as the emergence of variants with distinct phenotypes, for example transmissibility, severity and immune evasion. This Review explores the mechanisms that generate genetic variation in SARS-CoV-2, underlying the within-host and population-level processes that underpin these events. We examine the selective forces that likely drove the evolution of higher transmissibility and, in some cases, higher severity during the first year of the pandemic and the role of antigenic evolution during the second and third years, together with the implications of immune escape and reinfections, and the increasing evidence for and potential relevance of recombination. In order to understand how major lineages, such as variants of concern (VOCs), are generated, we contrast the evidence for the chronic infection model underlying the emergence of VOCs with the possibility of an animal reservoir playing a role in SARS-CoV-2 evolution, and conclude that the former is more likely. We evaluate uncertainties and outline scenarios for the possible future evolutionary trajectories of SARS-CoV-2.

Increased interregional virus exchange and nucleotide diversity outline the expansion of the chikungunya virus ECSA lineage in Brazil

The emergence and reemergence of mosquito-borne diseases in Brazil such as Yellow Fever, Zika, Chikungunya, and Dengue have had serious impacts on public health. Concerns have been raised due to the rapid dissemination of the chikungunya virus (CHIKV) across the country since its first detection in 2014 in Northeast Brazil. Faced with this scenario, on-site training activities in genomic surveillance carried out in partnership with the National Network of Public Health Laboratories have led to the generation of 422 CHIKV genomes from 12 Brazilian states over the past two years (2021-2022), a period that has seen more than 312 thousand chikungunya fever cases reported in the country. These new genomes increased the amount of available data and allowed a more comprehensive characterization of the dispersion dynamics of the CHIKV East-Central-South-African (ECSA) lineage in Brazil. Tree branching patterns revealed the emergence and expansion of two distinct subclades. Phylogeographic analysis indicated that the northeast region has been the leading hub of virus spread towards other regions. Increased frequency of C>T transitions among the new genomes suggested that host restriction factors from the immune system such as ADAR and AID/APOBEC deaminases might be driving CHIKV ECSA lineage genetic diversity in Brazil.

Cellular APOBEC3A deaminase drives mutations in the SARS-CoV-2 genome

The number of genetic variations in the SARS-CoV-2 genome has been increasing primarily due to continuous viral mutations. Here, we report that the human APOBEC3A (A3A) cytidine deaminase plays a critical role in the induction of C-to-U substitutions in the SARS-CoV-2 genome. Bioinformatic analysis of the chronological genetic changes in a sequence database indicated that the largest UC-to-UU mutation signature, consistent with APOBEC-recognized nucleotide motifs, was predominant in single-stranded RNA regions of the viral genome. In SARS-CoV-2-infected cells, exogenous expression of A3A but not expression of other APOBEC proteins induced UC-to-UU mutations in viral RNA (vRNA). Additionally, the mutated C bases were often located at the tips in bulge or loop regions in the vRNA secondary structure. Interestingly, A3A mRNA expression was drastically increased by interferons (IFNs) and tumour necrosis factor-α (TNF-α) in epithelial cells derived from the respiratory system, a site of efficient SARS-CoV-2 replication. Moreover, the UC-to-UU mutation rate was increased in SARS-CoV-2 produced from lung epithelial cells treated with IFN-ß and TNF-α, but not from CRISPR/Cas9-based A3A knockout cells. Collectively, these findings demonstrate that A3A is a primary host factor that drives mutations in the SARS-CoV-2 RNA genome via RNA editing.

Control of Human Anelloviruses by Cytosine to Uracil Genome Editing

Anelloviruses are the most common viruses infecting humans. Every human carries a nonpathogenic personal anellovirus virome (anellome), yet it is unknown which mechanisms contribute to its stability. Here, we assessed the dynamics and impact of a host antiviral defense mechanism-cytidine deaminase activity leading to C to U editing in anelloviruses-on the stability of the anellome. We investigated anellome sequence data obtained from serum samples collected every 6 months from two healthy subjects followed for more than 30 years. The subjects were infected by a total of 64 anellovirus lineages. Minus-stranded C to U editing was observed in lineages belonging to the Alpha-, Beta-, and Gammatorquevirus genera. The edited genomes were present within virus particles, therefore editing must have occurred at the late stages of the virus life cycle. Editing was favored by 5'-TC contexts in the virus genome, indicating that apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-like, catalytic subunit 3 or A3 (APOBEC3) proteins are involved. Within a lineage, mutational dynamics varied over time and few fixations of mutations were detected, indicating that C to U editing is a dead end for a virus genome. We detected an editing coldspot in the GC-rich regions, suggesting that the GC-rich region is crucial for genome packaging, since only packaged virus particles were included in the analysis. Finally, we noticed a lineage-specific reduced concentration after an editing event, yet no clearance. In conclusion, cytidine deaminase activity does not clear anelloviruses, nor does it play a major role in virus evolution, but it does contribute to the stability of the anellome. IMPORTANCE Despite significant attention on anellovirus research, the interaction between the anellovirus virome and the human host remains unknown. We show the dynamics of APOBEC3-mediated cytidine deaminase activity on anelloviruses during a 30-year period of chronic infection and postulate that this antiviral mechanism controls anelloviruses. These results expand our knowledge of anellovirus-host interactions, which may be important for the design of gene therapies.

Prediction of Recurrent Mutations in SARS-CoV-2 Using Artificial Neural Networks

Predicting SARS-CoV-2 mutations is difficult, but predicting recurrent mutations driven by the host, such as those caused by host deaminases, is feasible. We used machine learning to predict which positions from the SARS-CoV-2 genome will hold a recurrent mutation and which mutations will be the most recurrent. We used data from April 2021 that we separated into three sets: a training set, a validation set, and an independent test set. For the test set, we obtained a specificity value of 0.69, a sensitivity value of 0.79, and an Area Under the Curve (AUC) of 0.8, showing that the prediction of recurrent SARS-CoV-2 mutations is feasible. Subsequently, we compared our predictions with updated data from January 2022, showing that some of the false positives in our prediction model become true positives later on. The most important variables detected by the model's Shapley Additive exPlanation (SHAP) are the nucleotide that mutates and RNA reactivity. This is consistent with the SARS-CoV-2 mutational bias pattern and the preference of some host deaminases for specific sequences and RNA secondary structures. We extend our investigation by analyzing the mutations from the variants of concern Alpha, Beta, Delta, Gamma, and Omicron. Finally, we analyzed amino acid changes by looking at the predicted recurrent mutations in the M-pro and spike proteins.