The epitranscriptome of Vero cells infected with SARS-CoV-2 assessed by direct RNA sequencing reveals m6A pattern changes and DRACH motif biases in viral and cellular RNAs.

The epitranscriptomics of the SARS-CoV-2 infected cell reveals its response to viral replication. Among various types of RNA nucleotide modifications, the m6A is the most common and is involved in several crucial processes of RNA intracellular location, maturation, half-life and translatability. This epitranscriptome contains a mixture of viral RNAs and cellular transcripts. In a previous study we presented the analysis of the SARS-CoV-2 RNA m6A methylation based on direct RNA sequencing and characterized DRACH motif mutations in different viral lineages. Here we present the analysis of the m6A transcript methylation of Vero cells (derived from African Green Monkeys) and Calu-3 cells (human) upon infection by SARS-CoV-2 using direct RNA sequencing data. Analysis of these data by nonparametric statistics and two computational methods (m6anet and EpiNano) show that m6A levels are higher in RNAs of infected cells. Functional enrichment analysis reveals increased m6A methylation of transcripts involved in translation, peptide and amine metabolism. This analysis allowed the identification of differentially methylated transcripts and m6A unique sites in the infected cell transcripts. Results here presented indicate that the cell response to viral infection not only changes the levels of mRNAs, as previously shown, but also its epitranscriptional pattern. Also, transcriptome-wide analysis shows strong nucleotide biases in DRACH motifs of cellular transcripts, both in Vero and Calu-3 cells, which use the signature GGACU whereas in viral RNAs the signature is GAACU. We hypothesize that the differences of DRACH motif biases, might force the convergent evolution of the viral genome resulting in better adaptation to target sequence preferences of writer, reader and eraser enzymes. To our knowledge, this is the first report on m6A epitranscriptome of the SARS-CoV-2 infected Vero cells by direct RNA sequencing, which is the sensu stricto RNA-seq.

Direct RNA Sequencing Reveals SARS-CoV-2 m6A Sites and Possible Differential DRACH Motif Methylation among Variants.

The causative agent of COVID-19 pandemic, SARS-CoV-2, has a 29,903 bases positive-sense single-stranded RNA genome. RNAs exhibit about 150 modified bases that are essential for proper function. Among internal modified bases, the N6-methyladenosine, or m6A, is the most frequent, and is implicated in SARS-CoV-2 immune response evasion. Although the SARS-CoV-2 genome is RNA, almost all genomes sequenced thus far are, in fact, reverse transcribed complementary DNAs. This process reduces the true complexity of these viral genomes because the incorporation of dNTPs hides RNA base modifications. Here, we present an initial exploration of Nanopore direct RNA sequencing to assess the m6A residues in the SARS-CoV-2 sequences of ORF3a, E, M, ORF6, ORF7a, ORF7b, ORF8, N, ORF10 and the 3'-untranslated region. We identified fifteen m6A methylated positions, of which, six are in ORF N. Additionally, because m6A is associated with the DRACH motif, we compared its distribution in major SARS-CoV-2 variants. Although DRACH is highly conserved among variants, we show that variants Beta and Eta have a fourth position C > U change in DRACH at 28,884b that could affect methylation. This is the first report of direct RNA sequencing of a Brazilian SARS-CoV-2 sample coupled with the identification of modified bases.

Nitric oxide stimulates a PKC-Src-Akt signaling axis which increases human immunodeficiency virus type 1 replication in human T lymphocytes.

Human immunodeficiency virus (HIV) infections are typically accompanied by high levels of secreted inflammatory cytokines and generation of high levels of reactive oxygen species (ROS). To elucidate how HIV-1 alters the cellular redox environment during viral replication, we used human HIV-1 infected CD4+T lymphocytes and uninfected cells as controls. ROS and nitric oxide (NO) generation, antioxidant enzyme activity, protein phosphorylation, and viral and proviral loads were measured at different times (2-36 h post-infection) in the presence and absence of the NO donor S-nitroso-N-acetylpenicillamine (SNAP). HIV-1 infection increased ROS generation and decreased intracellular NO content. Upon infection, we observed increases in copper/zinc superoxide dismutase (SOD1) and glutathione peroxidase (GPx) activities, and a marked decrease in glutathione (GSH) concentration. Exposure of HIV-1 infected CD4+T lymphocytes to SNAP resulted in an increasingly oxidizing intracellular environment, associated with tyrosine nitration and SOD1 inhibition. In addition, SNAP treatment promoted phosphorylation and activation of the host's signaling proteins, PKC, Src kinase and Akt. Inhibition of PKC leads to inhibition of Src kinase strongly suggesting that PKC is the upstream element in this signaling cascade. Changes in the intracellular redox environment after SNAP treatment had an effect on HIV-1 replication as reflected by increases in proviral and viral loads. In the absence or presence of SNAP, we observed a decrease in viral load in infected CD4+T lymphocytes pre-incubated with the PKC inhibitor GF109203X. In conclusion, oxidative/nitrosative stress conditions derived from exposure of HIV-1-infected CD4+T lymphocytes to an exogenous NO source trigger a signaling cascade involving PKC, Src kinase and Akt. Activation of this signaling cascade appears to be critical to the establishment of HIV-1 infection.

Estimation of genetic diversity in viral populations from next generation sequencing data with extremely deep coverage.

BACKGROUND: In this paper we propose a method and discuss its computational implementation as an integrated tool for the analysis of viral genetic diversity on data generated by high-throughput sequencing. The main motivation for this work is to better understand the genetic diversity of viruses with high rates of nucleotide substitution, as HIV-1 and Influenza. Most methods for viral diversity estimation proposed so far are intended to take benefit of the longer reads produced by some next-generation sequencing platforms in order to estimate a population of haplotypes which represent the diversity of the original population. The method proposed here is custom-made to take advantage of the very low error rate and extremely deep coverage per site, which are the main features of some neglected technologies that have not received much attention due to the short length of its reads, which precludes haplotype estimation. This approach allowed us to avoid some hard problems related to haplotype reconstruction (need of long reads, preliminary error filtering and assembly). RESULTS: We propose to measure genetic diversity of a viral population through a family of multinomial probability distributions indexed by the sites of the virus genome, each one representing the distribution of nucleic bases per site. Moreover, the implementation of the method focuses on two main optimization strategies: a read mapping/alignment procedure that aims at the recovery of the maximum possible number of short-reads; the inference of the multinomial parameters in a Bayesian framework with smoothed Dirichlet estimation. The Bayesian approach provides conditional probability distributions for the multinomial parameters allowing one to take into account the prior information of the control experiment and providing a natural way to separate signal from noise, since it automatically furnishes Bayesian confidence intervals and thus avoids the drawbacks of preliminary error filtering. CONCLUSIONS: The methods described in this paper have been implemented as an integrated tool called Tanden (Tool for Analysis of Diversity in Viral Populations) and successfully tested on samples obtained from HIV-1 strain NL4-3 (group M, subtype B) cultivations on primary human cell cultures in many distinct viral propagation conditions. Tanden is written in C# (Microsoft), runs on the Windows operating system, and can be downloaded from: http://tanden.url.ph/.

HIV-1 Tropism Determines Different Mutation Profiles in Proviral DNA.

In order to establish new infections HIV-1 particles need to attach to receptors expressed on the cellular surface. HIV-1 particles interact with a cell membrane receptor known as CD4 and subsequently with another cell membrane molecule known as a co-receptor. Two major different co-receptors have been identified: C-C chemokine Receptor type 5 (CCR5) and C-X-C chemokine Receptor type 4 (CXCR4) Previous reports have demonstrated cellular modifications upon HIV-1 binding to its co-receptors including gene expression modulations. Here we investigated the effect of viral binding to either CCR5 or CXCR4 co-receptors on viral diversity after a single round of reverse transcription. CCR5 and CXCR4 pseudotyped viruses were used to infect non-stimulated and stimulated PBMCs and purified CD4 positive cells. We adopted the SOLiD methodology to sequence virtually the entire proviral DNA from all experimental infections. Infections with CCR5 and CXCR4 pseudotyped virus resulted in different patterns of genetic diversification. CCR5 virus infections produced extensive proviral diversity while in CXCR4 infections a more localized substitution process was observed. In addition, we present pioneering results of a recently developed method for the analysis of SOLiD generated sequencing data applicable to the study of viral quasi-species. Our findings demonstrate the feasibility of viral quasi-species evaluation by NGS methodologies. We presented for the first time strong evidence for a host cell driving mechanism acting on the HIV-1 genetic variability under the control of co-receptor stimulation. Additional investigations are needed to further clarify this question, which is relevant to viral diversification process and consequent disease progression.