Deciphering the co-adaptation of codon usage between respiratory coronaviruses and their human host uncovers candidate therapeutics for COVID-19

Investigation of CaMV-host co-evolution through synonymous codon pattern

Cauliflower mosaic virus (CaMV) has a double-stranded DNA genome and is globally distributed. The phylogeny tree of 121 CaMV isolates was categorized into two primary groups, with Iranian isolates showing the greatest genetic variations. Nucleotide A demonstrated the highest percentage (36.95%) in the CaMV genome and the dinucleotide odds ratio analysis revealed that TC dinucleotide (1.34 ≥ 1.23) and CG dinucleotide (0.63 ≤ 0.78) are overrepresented and underrepresented, respectively. Relative synonymous codon usage (RSCU) analysis confirmed codon usage bias in CaMV and its hosts. Brassica oleracea and Brassica rapa, among the susceptible hosts of CaMV, showed a codon adaptation index (CAI) value above 0.8. Additionally, relative codon deoptimization index (RCDI) results exhibited the highest degree of deoptimization in Raphanus sativus. These findings suggest that the genes of CaMV underwent codon adaptation with its hosts. Among the CaMV open reading frames (ORFs), genes that produce reverse transcriptase and virus coat proteins showed the highest CAI value of 0.83. These genes are crucial for the creation of new virion particles. The results confirm that CaMV co-evolved with its host to ensure the optimal expression of its genes in the hosts, allowing for easy infection and effective spread. To detect the force behind codon usage bias, an effective number of codons (ENC)-plot and neutrality plot were conducted. The results indicated that natural selection is the primary factor influencing CaMV codon usage bias.

Immune landscape and redox imbalance during neurological disorders in COVID-19

The outbreak of Coronavirus Disease 2019 (COVID-19) has prompted the scientific community to explore potential treatments or vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes the illness. While SARS-CoV-2 is mostly considered a respiratory pathogen, several neurological complications have been reported, raising questions about how it may enter the Central Nervous System (CNS). Receptors such as ACE2, CD147, TMPRSS2, and NRP1 have been identified in brain cells and may be involved in facilitating SARS-CoV-2 entry into the CNS. Moreover, proteins like P2X7 and Panx-1 may contribute to the pathogenesis of COVID-19. Additionally, the role of the immune system in the gravity of COVID-19 has been investigated with respect to both innate and adaptive immune responses caused by SARS-CoV-2 infection, which can lead to a cytokine storm, tissue damage, and neurological manifestations. A redox imbalance has also been linked to the pathogenesis of COVID-19, potentially causing mitochondrial dysfunction, and generating proinflammatory cytokines. This review summarizes different mechanisms of reactive oxygen species and neuro-inflammation that may contribute to the development of severe COVID-19, and recent progress in the study of immunological events and redox imbalance in neurological complications of COVID-19, and the role of bioinformatics in the study of neurological implications of COVID-19.

Cauliflower mosaic virus: Virus-host interactions and its uses in biotechnology and medicine

Cauliflower mosaic virus (CaMV) was the first discovered plant virus with genomic DNA that uses reverse transcriptase for replication. The CaMV 35S promoter is a constitutive promoter and thus, an attractive driver of gene expression in plant biotechnology. It is used in most transgenic crops to activate foreign genes which have been artificially inserted into the host plant. In the last century, producing food for the world's population while preserving the environment and human health is the main topic of agriculture. The damage caused by viral diseases has a significant negative economic impact on agriculture, and disease control is based on two strategies: immunization and prevention to contain virus spread, so correct identification of plant viruses is important for disease management. Here, we discuss CaMV from different aspects: taxonomy, structure and genome, host plants and symptoms, transmission and pathogenicity, prevention, control and application in biotechnology as well as in medicine. Also, we calculated the CAI index for three ORFs IV, V, and VI of the CaMV virus in host plants, the results of which can be used in the discussion of gene transfer or antibody production to identify the CaMV.

Human genes with relative synonymous codon usage analogous to that of polyomaviruses are involved in the mechanism of polyomavirus nephropathy

Human polyomaviruses (HPyVs) can cause serious and deleterious infections in human. Yet, the molecular mechanism underlying these infections, particularly in polyomavirus nephropathy (PVAN), is not well-defined. In the present study, we aimed to identify human genes with codon usage bias (CUB) similar to that of HPyV genes and explore their potential involvement in the pathogenesis of PVAN. The relative synonymous codon usage (RSCU) values of genes of HPyVs and those of human genes were computed and used for Pearson correlation analysis. The involvement of the identified correlation genes in PVAN was analyzed by validating their differential expression in publicly available transcriptomics data. Functional enrichment was performed to uncover the role of sets of genes. The RSCU analysis indicated that the A- and T-ending codons are preferentially used in HPyV genes. In total, 5400 human genes were correlated to the HPyV genes. The protein-protein interaction (PPI) network indicated strong interactions between these proteins. Gene expression analysis indicated that 229 of these genes were consistently and differentially expressed between normal kidney tissues and kidney tissues from PVAN patients. Functional enrichment analysis indicated that these genes were involved in biological processes related to transcription and in pathways related to protein ubiquitination pathway, apoptosis, cellular response to stress, inflammation and immune system. The identified genes may serve as diagnostic biomarkers and potential therapeutic targets for HPyV associated diseases, especially PVAN.

Using codon usage analysis to speculate potential animal hosts of hepatitis E virus: An exploratory study

There has been an increase in the reported number of animals worldwide that carry the hepatitis E virus (HEV). This study aimed to explore potential animal hosts for HEV through codon usage analysis. Full-length HEV sequences of six genotypes as well as codon usage of potential animal hosts were collected. Moreover, nucleotide composition and codon usage bias were compared across HEV genotypes and animal hosts. Based on the analysis for human HEV-1 and humans, the results were basically consistent with epidemiology evidence. Among 17 potential animal hosts, all HEV genotypes exhibited a preference for guanine/cytosine in the third position of synonymous codons. Furthermore, non-human primates and humans have large high-frequency codons identical to HEV in addition to a high correlation of codon fraction with HEV. Some animals in close contact with humans showed high preference for HEV, including cattle, dogs, and rats with HEV-A, cats, dogs, and swine with HEV-C1. Codon usage bias has limited efficiency in determining the hosts for HEV, but it may provide indicative clues for potential animal hosts when combined with experimental and epidemiological evidence.

Comprehensive analysis of codon usage pattern in Withania somnifera and its associated pathogens: Meloidogyne incognita and Alternaria alternata

Meloidogyne incognita (Root-knot nematode) and Alternaria alternata (fungus) were among the dominant parasites of the medicinal plant Withania somnifera. Despite the fatal nature of their infection, a comprehensive study to explore their evolution and adaptation is lacking. The present study elucidates evolutionary and codon usage bias analysis of W. somnifera (host plant), M. incognita (root-knot nematode) and A. alternata (fungal parasite). The results of the present study revealed a weak codon usage bias prevalent in all the three organisms. Based on the nucleotide analysis, genome of W. somnifera and M. incognita was found to be A-T biased while A. alternata had GC biased genome. We found high similarity of CUB pattern between host and its nematode pathogen as compared to the fungal pathogen. Inclusively, both the evolutionary forces influenced the CUB in host and its associated pathogens. However, neutrality plot indicated the pervasiveness of natural selection on CUB of the host and its pathogens. Correspondence analysis revealed the dominant effect of mutation on CUB of W. somnifera and M. incognita while natural selection was the main force affecting CUB of A. alternata. Taken together the present study would provide some prolific insight into the role of codon usage bias in the adaptability of pathogens to the host’s environment for establishing parasitic relationship.

Human genes with codon usage bias similar to that of the nonstructural protein 1 gene of influenza A viruses are conjointly involved in the infectious pathogenesis of influenza A viruses

Molecular mechanisms of the non-structural protein 1 (NS1) in influenza A-induced pathological changes remain ambiguous. This study explored the pathogenesis of human infection by influenza A viruses (IAVs) through identifying human genes with codon usage bias (CUB) similar to NS1 gene of these viruses based on the relative synonymous codon usage (RSCU). CUB of the IAV subtypes H1N1, H3N2, H3N8, H5N1, H5N2, H5N8, H7N9 and H9N2 was analyzed and the correlation of RSCU values of NS1 sequences with those of the human genes was calculated. The CUB of NS1 was uneven and codons ending with A/U were preferred. The ENC-GC3 and neutrality plots suggested natural selection as the main determinant for CUB. The RCDI, CAI and SiD values showed that the viruses had a high degree of adaptability to human. A total of 2155 human genes showed significant RSCU-based correlation (p < 0.05 and r > 0.5) with NS1 coding sequences and was considered as human genes with CUB similar to NS1 gene of IAV subtypes. Differences and similarities in the subtype-specific human protein–protein interaction (PPI) networks and their functions were recorded among IAVs subtypes, indicating that NS1 of each IAV subtype has a specific pathogenic mechanism. Processes and pathways involved in influenza, transcription, immune response and cell cycle were enriched in human gene sets retrieved based on the CUB of NS1 gene of IAV subtypes. The present work may advance our understanding on the mechanism of NS1 in human infections of IAV subtypes and shed light on the therapeutic options.

Analysis of SARS-CoV-2 synonymous codon usage evolution throughout the COVID-19 pandemic

SARS-CoV-2, the seventh coronavirus known to infect humans, can cause severe life-threatening respiratory pathologies. To better understand SARS-CoV-2 evolution, genome-wide analyses have been made, including the general characterization of its codons usage profile. Here we present a bioinformatic analysis of the evolution of SARS-CoV-2 codon usage over time using complete genomes collected since December 2019. Our results show that SARS-CoV-2 codon usage pattern is antagonistic to, and it is getting farther away from that of the human host. Further, a selection of deoptimized codons over time, which was accompanied by a decrease in both the codon adaptation index and the effective number of codons, was observed. All together, these findings suggest that SARS-CoV-2 could be evolving, at least from the perspective of the synonymous codon usage, to become less pathogenic.

Transmission cluster of COVID-19 cases from Uruguay: emergence and spreading of a novel SARS-CoV-2 ORF6 deletion

BACKGROUND

Evolutionary changes in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) include indels in non-structural, structural, and accessory open reading frames (ORFs) or genes.

OBJECTIVES

We track indels in accessory ORFs to infer evolutionary gene patterns and epidemiological links between outbreaks.

METHODS

Genomes from Coronavirus disease 2019 (COVID-19) case-patients were Illumina sequenced using ARTIC_V3. The assembled genomes were analysed to detect substitutions and indels.

FINDINGS

We reported the emergence and spread of a unique 4-nucleotide deletion in the accessory ORF6, an interesting gene with immune modulation activity. The deletion in ORF6 removes one repeat unit of a two 4-nucleotide repeat, which shows that directly repeated sequences in the SARS-CoV-2 genome are associated with indels, even outside the context of extended repeat regions. The 4-nucleotide deletion produces a frameshifting change that results in a protein with two inserted amino acids, increasing the coding information of this accessory ORF. Epidemiological and genomic data indicate that the deletion variant has a single common ancestor and was initially detected in a health care outbreak and later in other COVID-19 cases, establishing a transmission cluster in the Uruguayan population.

MAIN CONCLUSIONS

Our findings provide evidence for the origin and spread of deletion variants and emphasise indels’ importance in epidemiological studies, including differentiating consecutive outbreaks occurring in the same health facility.

Bioinformatics Analysis of the MicroRNA-Metabolic Gene Regulatory Network in Neuropathic Pain and Prediction of Corresponding Potential Therapeutics

Neuropathic pain (NP) involves metabolic processes that are regulated by metabolic genes and their non-coding regulator genes such as microRNAs (miRNAs). Here, we aimed at exploring the key miRNA signatures regulating metabolic genes involved in NP pathogenesis. We downloaded NP-related data from public databases and identified differentially expressed microRNAs (miRNAs) and mRNAs through differential gene expression analysis. The miRNA target prediction was performed, and integration with the differentially expressed metabolic genes (DEMGs) was used for constructing the miRNA-DEMG network. Subsequently, functional enrichment analysis and protein–protein interaction (PPI) analysis were performed to explore the role of DEMGs in the regulatory network. The drug prediction was performed based on the DEMGs in the miRNA-DEMG network. A total of 8251 differentially expressed mRNAs (4193 upregulated and 4058 downregulated), and 959 differentially expressed miRNAs (455 upregulated and 504 downregulated) were identified. Moreover, after target gene prediction, a miRNA-DEMG network composed of 22 miRNAs and 113 mRNAs was constructed. The network was constituted of 135 nodes and 236 edges. We found that DEMGs in the network were mainly enriched in metabolic pathways and metabolic processes. A total of 1200 drugs were predicted as potential therapeutics for NP based on the differentially expressed genes, while 170 drugs were predicted for the DEMGs in the miRNA-DEMG network. Conclusively, our study predicted drugs that may be effective against the metabolic changes induced by miRNA dysregulation in NP. This information will help further reveal the pathological mechanism of NP and provide more treatment options for NP patients.

Weighted gene co-expression network analysis and drug-gene interaction bioinformatics uncover key genes associated with various presentations of malaria infection in African children and major drug candidates

Malaria is a fatal parasitic disease with unelucidated pathogenetic mechanism. Herein, we aimed to uncover genes associated with different clinical aspects of malaria based on the GSE1124 dataset that is publicly accessible by using WGCNA. We obtained 16 co-expression modules and their correlations with clinical features. Using the MCODE tool, we identified THEM4, STYX, VPS36, LCOR, KIAA1143, EEA1, RAPGEF6, LOC439994, ZBTB33, PTPN22, ESCO1, and KLF3 as hub genes positively associated with Plasmodium falciparum infection (ASPF). These hub genes were involved in the biological processes of endosomal transport, regulation of natural killer cell proliferation, and KEGG pathways of endocytosis and fatty acid elongation. For the purple module negatively correlated with ASPF, we identified 19 hub genes that were involved in the biological processes of positive regulation of cellular protein catabolic process and KEGG pathways of other glycan degradation. For the salmon module positively correlated with severe malaria anemia (SMA), we identified 17 hub genes that were among those driving the biological processes of positive regulation of erythrocyte differentiation. For the brown module positively correlated with cerebral malaria (CM), we identified eight hub genes and these genes participated in phagolysosome assembly and positive regulation of exosomal secretion, and animal mitophagy pathway. For the tan module negatively correlated with CM, we identified four hub genes that were involved in CD8-positive, alpha-beta T cell differentiation and notching signaling pathway. These findings may provide new insights into the pathogenesis of malaria and help define new diagnostic and therapeutic approaches for malaria patients.

The nucleotide usages significantly impact synonymous codon usage in Mycoplasma hyorhinis

Five annotated genomes of Mycoplasma hyorhinis were analyzed for clarifying evolutionary dynamics driving the overall codon usage pattern. Information entropy used for estimating nucleotide usage pattern at the gene level indicates that multiple evolutionary dynamics participate in forcing nucleotide usage bias at every codon position. Moreover, nucleotide usage bias directly contributes to synonymous codon usage biases with two different extremes. The overrepresented codons tended to have A/T in the third codon position, and the underrepresented codons strongly used G/C in the third position. Furthermore, correspondence analysis and neutrality plot reflect an obvious interplay between mutation pressure and natural selection mediating codon usage in M. hyorhinis genome. Due to significant bias in usages between A/T and G/C at the gene level, different selective forces have been proposed to contribute to codon usage preference in M. hyorhinis genome, including nucleotide composition constraint derived from mutation pressure, translational selection involved in natural selection, and strand-specific mutational bias represented by different nucleotide skew index. The systemic analyses of codon usage for M. hyorhinis can enable us to better understand the mechanisms of evolution in this species.

Computational Analysis of SARS-CoV-2 and SARS-Like Coronavirus Diversity in Human, Bat and Pangolin Populations

In 2019, a novel coronavirus, SARS-CoV-2/nCoV-19, emerged in Wuhan, China, and has been responsible for the current COVID-19 pandemic. The evolutionary origins of the virus remain elusive and understanding its complex mutational signatures could guide vaccine design and development. As part of the international "CoronaHack" in April 2020, we employed a collection of contemporary methodologies to compare the genomic sequences of coronaviruses isolated from human (SARS-CoV-2; n = 163), bat (bat-CoV; n = 215) and pangolin (pangolin-CoV; n = 7) available in public repositories. We have also noted the pangolin-CoV isolate MP789 to bare stronger resemblance to SARS-CoV-2 than other pangolin-CoV. Following de novo gene annotation prediction, analyses of gene-gene similarity network, codon usage bias and variant discovery were undertaken. Strong host-associated divergences were noted in ORF3a, ORF6, ORF7a, ORF8 and S, and in codon usage bias profiles. Last, we have characterised several high impact variants (in-frame insertion/deletion or stop gain) in bat-CoV and pangolin-CoV populations, some of which are found in the same amino acid position and may be highlighting loci of potential functional relevance.

Evolution of Transmissible Gastroenteritis Virus (TGEV): A Codon Usage Perspective

Transmissible gastroenteritis virus (TGEV) is a coronavirus associated with diarrhea and high mortality in piglets. To gain insight into the evolution and adaptation of TGEV, a comprehensive analysis of phylogeny and codon usage bias was performed. The phylogenetic analyses of maximum likelihood and Bayesian inference displayed two distinct genotypes: genotypes I and II, and genotype I was classified into subtypes Ia and Ib. The compositional properties revealed that the coding sequence contained a higher number of A/U nucleotides than G/C nucleotides, and that the synonymous codon third position was A/U-enriched. The principal component analysis based on the values of relative synonymous codon usage (RSCU) showed the genotype-specific codon usage patterns. The effective number of codons (ENC) indicated moderate codon usage bias in the TGEV genome. Dinucleotide analysis showed that CpA and UpG were over-represented and CpG was under-represented in the coding sequence of the TGEV genome. The analyses of Parity Rule 2 plot, ENC-plot, and neutrality plot displayed that natural selection was the dominant evolutionary driving force in shaping codon usage preference in genotypes Ia and II. In addition, natural selection played a major role, while mutation pressure had a minor role in driving the codon usage bias in genotype Ib. The codon adaptation index (CAI), relative codon deoptimization index (RCDI), and similarity index (SiD) analyses suggested that genotype I might be more adaptive to pigs than genotype II. Current findings contribute to understanding the evolution and adaptation of TGEV.