Application of codon usage and context analysis in genes up- or down-regulated in neurodegeneration and cancer to combat comorbidities

IntroductionNeurodegeneration and cancer present in comorbidities with inverse effects due to the expression of genes and pathways acting in opposition. Identifying and studying the genes simultaneously up or downregulated during morbidities helps curb both ailments together.MethodsThis study examines four genes. Three of these (Amyloid Beta Precursor Protein (APP), Cyclin D1 (CCND1), and Cyclin E2 (CCNE2) are upregulated, and one protein phosphatase 2 phosphatase activator (PTPA) is simultaneously downregulated in both disorders. We investigated molecular patterns, codon usage, codon usage bias, nucleotide bias in the third codon position, preferred codons, preferred codon pairs, rare codons, and codon context.ResultsParity analysis revealed that T is preferred over A, and G is preferred over C in the third codon position, suggesting composition plays no role in nucleotide bias in both the upregulated and downregulated gene sets and that mutational forces are stronger in upregulated gene sets than in downregulated ones. Transcript length influenced the overall %A composition and codon bias, and the codon AGG exerted the strongest influence on codon usage in both the upregulated and downregulated gene sets. Codons ending in G/C were preferred for 16 amino acids, and glutamic acid-, aspartic acid-, leucine-, valine-, and phenylalanine-initiated codon pairs were preferred in all genes. Codons CTA (Leu), GTA (Val), CAA (Gln), and CGT (Arg) were underrepresented in all examined genes.DiscussionUsing advanced gene editing tools such as CRISPR/Cas or any other gene augmentation technique, these recoded genes may be introduced into the human body to optimize gene expression levels to augment neurodegeneration and cancer therapeutic regimens simultaneously

Avian Influenza (H5N1) Virus of Clade 2.3.2 in Domestic Poultry in India

South Asia has experienced regular outbreaks of H5N1 avian influenza virus since its first detection in India and Pakistan in February, 2006. Till 2009, the outbreaks in this region were due to clade 2.2 H5N1 virus. In 2010, Nepal reported the first outbreak of clade 2.3.2 virus in South Asia. In February 2011, two outbreaks of H5N1 virus were reported in the State of Tripura in India. The antigenic and genetic analyses of seven H5N1 viruses isolated during these outbreaks were carried out. Antigenic analysis confirmed 64 to 256-fold reduction in cross reactivity compared with clade 2.2 viruses. The intravenous pathogenicity index of the isolates ranged from 2.80–2.95 indicating high pathogenicity to chickens. Sequencing of all the eight gene-segments of seven H5N1 viruses isolated in these outbreaks was carried out. The predicted amino acid sequence analysis revealed high pathogenicity to chickens and susceptibility to the antivirals, amantadine and oseltamivir. Phylogenetic analyses indicated that these viruses belong to clade 2.3.2.1 and were distinct to the clade 2.3.2.1 viruses isolated in Nepal. Identification of new clade 2.3.2 H5N1 viruses in South Asia is reminiscent of the introduction of clade 2.2 viruses in this region in 2006/7. It is now important to monitor whether the clade 2.3.2.1 is replacing clade 2.2 in this region or co-circulating with it. Continued co-circulation of various subclades of the H5N1 virus which are more adapted to land based poultry in a highly populated region such as South Asia increases the risk of evolution of pandemic H5N1 strains

Codon Usage and Context Analysis of Genes Modulated during SARS-CoV-2 Infection and Dental Inflammation

The overexpression of SARS-CoV-2 primary receptors and co-receptors (ACE2, TMPRSS2, FURIN, and CD147) enhance the likeliness of SARS-CoV-2 infection. The genes for same receptors are overexpressed in the periodontal tissues of periodontitis patients. On the other hand, BMAL1 is recognized to play a crucial role in regulating pulmonary inflammation and enhancing susceptibility to viral infection. Silenced BMAL1 disrupts circadian transcriptional regulations, enhances vulnerability to SARS-CoV-2 infections, and may trigger the further production of TNF-α and other pro-inflammatory cytokines that propagate the cytokine storm and exacerbate periodontal inflammation. Therefore ACE2, TMPRSS2, FURIN, CD147, and BMAL1 are the crossroads between SARS-CoV-2 and Periodontitis genes. The enhanced expression of ACE2, TMPRSS2, FURIN, and CD147 and the diminished expression of BMAL1 may be a strategy to check both ailments simultaneously. In gene manipulation techniques, oligos are introduced, which contain all the necessary information to manipulate gene expression. The data are derived from the studies on genes’ molecular patterns, including nucleotide composition, dinucleotide patterns, relative synonymous codon usage, codon usage bias, codon context, and rare and abundant codons. Such information may be used to manipulate the overexpression and underexpression of the genes at the time of SARS-CoV-2 infection and periodontitis to mitigate both ailments simultaneously; it can be explored to uncover possible future treatments

Compositional constraints and selection forces dictate codon usage in human bocavirus

Objectives: Human bocavirus (HBoV), of the genus Bocaparvovirus, is a small, non-enveloped linear single-stranded DNA virus of the Parvoviridae family. The virus is known to cause severe life-threatening respiratory tract infections in pediatric patients. Considering its deleterious impacts on respiratory, gastrointestinal, and hematological health, we prompted to investigate codon usage patterns, parity, neutrality, Nc-GC3 analysis, gene expression, Intrinsic codon bias index (ICDI), Codon bias index (CBI), Relative codon deoptimization index (RCDI), Translational selection (P2), and measure independent of length and composition (MILC) to investigate the role of evolutionary constraints such as selection and mutation and molecular patterns present in HBoV. Methods: 805 HBoV sequences were investigated using various software and statistical tools. Results: The present study demonstrated the predominant governance of selection forces over mutational forces in determining codon usage. The compositional parameters were pivotal in deciding the dinucleotide occurrence and frequently used codons. Since the HBoV genomes were A-and T-nucleotide-rich, A/T ending codons and ApAdinucleotides were overrepresented. Despite the A/T richness, at the non-neutral positions of the codon, the G/C nucleotide content was found to be the highest, again underscoring the selective forces that drive a high percentage of G/C nucleotide. At the non-neutral codon positions, with an increase in GC nucleotide, codon bias also increased, while at the third position of the codon, with an increase in GC content, it was decreased. Overall, there is a low codon bias in HBoV. A total of nine A/T ending codons were overrepresented, while nineteen G/C ending codons were underrepresented. Interestingly, instead of CTG, a commonly overrepresented codon, AGA was the most overrepresented codon. AGA and CGG encoding for arginine showed average maximum and minimum RSCU values in the HBoV genome. Conclusions: The collective inference from the neutrality plot, Nc-GC3 curve, and P2 analysis indicated the prevalence of selection force over mutation force. With that, our study offers a novel perspective on the different molecular patterns present in HBoV, and the results might be implicated in designing efficacious therapeutic modalities against HBoV

COVID-19 and the World with Co-Morbidities of Heart Disease, Hypertension and Diabetes

Newly emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causing coronavirus disease 2019 (COVID-19) pandemic has now spread across the globe in past few months while affecting 26 million people and leading to more than 0.85 million deaths as on 2nd September, 2020. Severity of SARS-CoV-2 infection increases in COVID-19 patients due to pre-existing health co-morbidities. This mini-review has focused on the three significant co-morbidities viz., heart disease, hypertension, and diabetes, which are posing high health concerns and increased mortality during this ongoing pandemic. The observed co-morbidities have been found to be associated with the increasing risk factors for SARS-CoV-2 infection and COVID-19 critical illness as well as to be associated positively with the worsening of the health condition of COVID-19 suffering individuals resulting in the high risk for mortality. SARS-CoV-2 enters host cell via angiotensin-converting enzyme 2 receptors. Regulation of crucial cardiovascular functions and metabolisms like blood pressure and sugar levels are being carried out by ACE2. This might be one of the reasons that contribute to the higher mortality in COVID-19 patients having co-morbidities. Clinical investigations have identified higher levels of creatinine, cardiac troponin I, alanine aminotransferase, NT-proBNP, creatine kinase, D-dimer, aspartate aminotransferase and lactate dehydrogenase in patients who have succumbed to death from COVID-19 as compared to recovered individuals. More investigations are required to identify the modes behind increased mortality in COVID-19 patients having co-morbidities of heart disease, hypertension, and diabetes. This will enable us to design and develop suitable therapeutic strategies for reducing the mortality. More attention and critical care need to be paid to such high risk patients suffering from co-morbidities during COVID-19 pandemic

Circulation of H5N1 viruses in South Asia since 2010.

<p>Circulation of H5N1 viruses in South Asia since 2010.</p

Phylogenetic relationships of the coding sequences of hemagglutinin (HA) genes of representative influenza A viruses.

<p>Analysis was based on full length or near full length sequences. The numbers next to the branch nodes indicate bootstrap values/posterior probabilities expressed as percentages from, respectively, 500 bootstrap replicates of a maximum likelihood tree and posterior probabilities from a MrBayes 3.2 analysis (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031844#s3" target="_blank">methods</a>). Not all support valuess are shown due to space constraints. Numbers labeled on the HA tree refer to the WHO H5N1 clade designations (<a href="http://www.who.int/csr/disease/avian_influenza/guidelines/nomenclature/en" target="_blank">http://www.who.int/csr/disease/avian_influenza/guidelines/nomenclature/en</a>). Viruses isolated in this work are in green and other recent Indian, Bangladesh and Bhutan viruses are in red. Scale bar, indicates nucleotide substitutions per site.</p

Circulation of H5N1 viruses in South Asia till 2009.

<p>Circulation of H5N1 viruses in South Asia till 2009.</p

Phylogenetic relationships of polymerase acidic (PA) genes of representative influenza A viruses.

<p>Details are as in the legends to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031844#pone-0031844-g001" target="_blank">Figures 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0031844#pone-0031844-g002" target="_blank">2</a>.</p

Antigenic characterization of Indian clade 2.3.2 H5N1 viruses.

<p>*- reciprocal of antibody titres by hemagglutination inhibition test.</p