Whole genome analysis of more than 10 000 SARS-CoV-2 virus unveils global genetic diversity and target region of NSP6

AND-Logic Cascade Rolling Circle Amplification for Optomagnetic Detection of Dual Target SARS-CoV-2 Sequences

DNA logic operations are accurate and specific molecular strategies that are appreciated in target multiplexing and intelligent diagnostics. However, most of the reported DNA logic operation-based assays lack amplifiers prior to logic operation, resulting in detection limits at the subpicomolar to nanomolar level. Herein, a homogeneous and isothermal AND-logic cascade amplification strategy is demonstrated for optomagnetic biosensing of two different DNA inputs corresponding to a variant of concern sequence (containing spike L452R) and a highly conserved sequence from SARS-CoV-2. With an "amplifiers-before-operator" configuration, two input sequences are recognized by different padlock probes for amplification reactions, which generate amplicons used, respectively, as primers and templates for secondary amplification, achieving the AND-logic operation. Cascade amplification products can hybridize with detection probes grafted onto magnetic nanoparticles (MNPs), leading to hydrodynamic size increases and/or aggregation of MNPs. Real-time optomagnetic MNP analysis offers a detection limit of 8.6 fM with a dynamic detection range spanning more than 3 orders of magnitude. The accuracy, stability, and specificity of the system are validated by testing samples containing serum, salmon sperm, a single-nucleotide variant, and biases of the inputs. Clinical samples are tested with both quantitative reverse transcription-PCR and our approach, showing highly consistent measurement results.

Genetic conservation across SARS-CoV-2 non-structural proteins - Insights into possible targets for treatment of future viral outbreaks

The majority of SARS-CoV-2 therapeutic development work has focussed on targeting the spike protein, viral polymerase and proteases. As the pandemic progressed, many studies reported that these proteins are prone to high levels of mutation and can become drug resistant. Thus, it is necessary to not only target other viral proteins such as the non-structural proteins (NSPs) but to also target the most conserved residues of these proteins. In order to understand the level of conservation among these viruses, in this review, we have focussed on the conservation across RNA viruses, conservation across the coronaviruses and then narrowed our focus to conservation of NSPs across coronaviruses. We have also discussed the various treatment options for SARS-CoV-2 infection. A synergistic melding of bioinformatics, computer-aided drug-design and in vitro/vivo studies can feed into better understanding of the virus and therefore help in the development of small molecule inhibitors against the viral proteins.

Unveiling the Biomarkers of Cancer and COVID-19 and Their Regulations in Different Organs by Integrating RNA-Seq Expression and Protein-Protein Interactions

Cancer and COVID-19 have killed millions of people worldwide. COVID-19 is even more dangerous to people with comorbidities such as cancer. Thus, it is imperative to identify the key human genes or biomarkers that can be targeted to develop novel prognosis and therapeutic strategies. The transcriptomic data provided by the next-generation sequencing technique makes this identification very convenient. Hence, mRNA (messenger ribonucleic acid) expression data of 2265 cancer and 282 normal patients were considered, while for COVID-19 assessment, 784 and 425 COVID-19 and normal patients were taken, respectively. Initially, volcano plots were used to identify the up- and down-regulated genes for both cancer and COVID-19. Thereafter, protein-protein interaction (PPI) networks were prepared by combining all the up- and down-regulated genes for each of cancer and COVID-19. Subsequently, such networks were analyzed to identify the top 10 genes with the highest degree of connection to provide the biomarkers. Interestingly, these genes were all up-regulated for cancer, while they were down-regulated for COVID-19. This study had also identified common genes between cancer and COVID-19, all of which were up-regulated in both the diseases. This analysis revealed that FN1 was highly up-regulated in different organs for cancer, while EEF2 was dysregulated in most organs affected by COVID-19. Then, functional enrichment analysis was performed to identify significant biological processes. Finally, the drugs for cancer and COVID-19 biomarkers and the common genes between them were identified using the Enrichr online web tool. These drugs include lucanthone, etoposide, and methotrexate, targeting the biomarkers for cancer, while paclitaxel is an important drug for COVID-19.

Bioinformatics pipeline unveils genetic variability to synthetic vaccine design for Indian SARS-CoV-2 genomes

In the worrisome scenarios of various waves of SARS-CoV-2 pandemic, a comprehensive bioinformatics pipeline is essential to analyse the virus genomes in order to understand its evolution, thereby identifying mutations as signature SNPs, conserved regions and subsequently to design epitope based synthetic vaccine. We have thus performed multiple sequence alignment of 4996 Indian SARS-CoV-2 genomes as a case study using MAFFT followed by phylogenetic analysis using Nextstrain to identify virus clades. Furthermore, based on the entropy of each genomic coordinate of the aligned sequences, conserved regions are identified. After refinement of the conserved regions, based on its length, one conserved region is identified for which the primers and probes are reported for virus detection. The refined conserved regions are also used to identify T-cell and B-cell epitopes along with their immunogenic and antigenic scores. Such scores are used for selecting the most immunogenic and antigenic epitopes. By executing this pipeline, 40 unique signature SNPs are identified resulting in 23 non-synonymous signature SNPs which provide 28 amino acid changes in protein. On the other hand, 12 conserved regions are selected based on refinement criteria out of which one is selected as the potential target for virus detection. Additionally, 22 MHC-I and 21 MHC-II restricted T-cell epitopes with 10 unique HLA alleles each and 17 B-cell epitopes are obtained for 12 conserved regions. All the results are validated both quantitatively and qualitatively which show that from genetic variability to synthetic vaccine design, the proposed pipeline can be used effectively to combat SARS-CoV-2.

Human miRNAs to Identify Potential Regions of SARS-CoV-2

It is two years now but the world is still struggling against COVID-19 due to the havoc created by the SARS-CoV-2 virus and its multiple variants. Considering this perspective, in this work, we have hypothesized a new approach in order to identify potential regions in SARS-CoV-2 similar to the human miRNAs. Thus, they may have similar consequences as caused by the human miRNAs in human body. Therefore, the same way by which human miRNAs are inhibited can be applied for such potential regions of virus as well by administering drugs to the interacting human proteins. In this regard, the multiple sequence alignment technique Clustal Omega is used to align 2656 human miRNAs with the SARS-CoV-2 reference genome to identify the potential regions within the virus reference genome which have high similarities with the human miRNAs. The potential regions in virus genome are identified based on the highest number of nucleotide match, greater than or equal to 5 at a genomic position, for the aligned miRNAs. As a result, 38 potential SARS-CoV-2 regions are identified consisting of 249 human miRNAs. Among these 38 potential regions, some top regions belong to nucleocapsid, RdRp, helicase, and ORF8. To understand the biological significance of these potential regions, the targets of the human miRNAs are considered for KEGG pathways and protein-protein and drug-protein interaction analysis as the human miRNAs are similar to the potential regions of SARS-CoV-2. Significant pathways are found which lead to comorbidities. Subsequently, drugs like emodin, bicalutamide, vorinostat, etc. are identified that may be used for clinical trials.

Phylogenetic analysis of 17271 Indian SARS-CoV-2 genomes to identify temporal and spatial hotspot mutations

The second wave of SARS-CoV-2 has hit India hard and though the vaccination drive has started, moderate number of COVID affected patients is still present in the country, thereby leading to the analysis of the evolving virus strains. In this regard, multiple sequence alignment of 17271 Indian SARS-CoV-2 sequences is performed using MAFFT followed by their phylogenetic analysis using Nextstrain. Subsequently, mutation points as SNPs are identified by Nextstrain. Thereafter, from the aligned sequences temporal and spatial analysis are carried out to identify top 10 hotspot mutations in the coding regions based on entropy. Finally, to judge the functional characteristics of all the non-synonymous hotspot mutations, their changes in proteins are evaluated as biological functions considering the sequences by using PolyPhen-2 while I-Mutant 2.0 evaluates their structural stability. For both temporal and spatial analysis, there are 21 non-synonymous hotspot mutations which are unstable and damaging.

Highlight of potential impact of new viral genotypes of SARS-CoV-2 on vaccines and anti-viral therapeutics

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of the coronavirus disease (COVID-19) pandemic, has infected millions of people globally. Genetic variation and selective pressures lead to the accumulation of single nucleotide polymorphism (SNP) within the viral genome that may affect virulence, transmission rate, viral recognition and the efficacy of prophylactic and interventional measures. To address these concerns at the genomic level, we assessed the phylogeny and SNPs of the SARS-CoV-2 mutant population collected to date in Iran in relation to globally reported variants. Phylogenetic analysis of mutant strains revealed the occurrence of the variants known as B.1.1.7 (Alpha), B.1.525 (Eta), and B.1.617 (Delta) that appear to have delineated independently in Iran. SNP analysis of the Iranian sequences revealed that the mutations were predominantly positioned within the S protein-coding region, with most SNPs localizing to the S1 subunit. Seventeen S1-localizing SNPs occurred in the RNA binding domain that interacts with ACE2 of the host cell. Importantly, many of these SNPs are predicted to influence the binding of antibodies and anti-viral therapeutics, indicating that the adaptive host response appears to be imposing a selective pressure that is driving the evolution of the virus in this closed population through enhancing virulence. The SNPs detected within these mutant cohorts are addressed with respect to current prophylactic measures and therapeutic interventions.

An entropy-based study on mutational trajectory of SARS-CoV-2 in India

The pandemic of COVID-19 has been haunting us for almost the past two years. Although, the vaccination drive is in full swing throughout the world, different mutations of the SARS-CoV-2 virus are making it very difficult to put an end to the pandemic. The second wave in India, one of the worst sufferers of this pandemic, can be mainly attributed to the Delta variant i.e. B.1.617.2. Thus, it is very important to analyse and understand the mutational trajectory of SARS-CoV-2 through the study of the 26 virus proteins. In this regard, more than 17,000 protein sequences of Indian SARS-CoV-2 genomes are analysed using entropy-based approach in order to find the monthly mutational trajectory. Furthermore, Hellinger distance is also used to show the difference of the mutation events between the consecutive months for each of the 26 SARS-CoV-2 protein. The results show that the mutation rates and the mutation events of the viral proteins though changing in the initial months, start stabilizing later on for mainly the four structural proteins while the non-structural proteins mostly exhibit a more constant trend. As a consequence, it can be inferred that the evolution of the new mutative configurations will eventually reduce.

Hotspot Mutations in SARS-CoV-2

Since its emergence in Wuhan, China, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has spread very rapidly around the world, resulting in a global pandemic. Though the vaccination process has started, the number of COVID-affected patients is still quite large. Hence, an analysis of hotspot mutations of the different evolving virus strains needs to be carried out. In this regard, multiple sequence alignment of 71,038 SARS-CoV-2 genomes of 98 countries over the period from January 2020 to June 2021 is performed using MAFFT followed by phylogenetic analysis in order to visualize the virus evolution. These steps resulted in the identification of hotspot mutations as deletions and substitutions in the coding regions based on entropy greater than or equal to 0.3, leading to a total of 45 unique hotspot mutations. Moreover, 10,286 Indian sequences are considered from 71,038 global SARS-CoV-2 sequences as a demonstrative example that gives 52 unique hotspot mutations. Furthermore, the evolution of the hotspot mutations along with the mutations in variants of concern is visualized, and their characteristics are discussed as well. Also, for all the non-synonymous substitutions (missense mutations), the functional consequences of amino acid changes in the respective protein structures are calculated using PolyPhen-2 and I-Mutant 2.0. In addition to this, SSIPe is used to report the binding affinity between the receptor-binding domain of Spike protein and human ACE2 protein by considering L452R, T478K, E484Q, and N501Y hotspot mutations in that region.

Characterisation of SARS-CoV-2 clades based on signature SNPs unveils continuous evolution

Since the emergence of SARS-CoV-2 in Wuhan, China more than a year ago, it has spread across the world in a very short span of time. Although, different forms of vaccines are being rolled out for vaccination programs around the globe, the mutation of the virus is still a cause of concern among the research communities. Hence, it is important to study the constantly evolving virus and its strains in order to provide a much more stable form of cure. This fact motivated us to conduct this research where we have initially carried out multiple sequence alignment of 15359 and 3033 global dataset without Indian and the dataset of exclusive Indian SARS-CoV-2 genomes respectively, using MAFFT. Subsequently, phylogenetic analyses are performed using Nextstrain to identify virus clades. Consequently, the virus strains are found to be distributed among 5 major clades or clusters viz. 19A, 19B, 20A, 20B and 20C. Thereafter, mutation points as SNPs are identified in each clade. Henceforth, from each clade top 10 signature SNPs are identified based on their frequency i.e. number of occurrences in the virus genome. As a result, 50 such signature SNPs are individually identified for global dataset without Indian and dataset of exclusive Indian SARS-CoV-2 genomes respectively. Out of each 50 signature SNPs, 39 and 41 unique SNPs are identified among which 25 non-synonymous signature SNPs (out of 39) resulted in 30 amino acid changes in protein while 27 changes in amino acid are identified from 22 non-synonymous signature SNPs (out of 41). These 30 and 27 amino acid changes for the non-synonymous signature SNPs are visualised in their respective protein structure as well. Finally, in order to judge the characteristics of the identified clades, the non-synonymous signature SNPs are considered to evaluate the changes in proteins as biological functions with the sequences using PROVEAN and PolyPhen-2 while I-Mutant 2.0 is used to evaluate their structural stability. As a consequence, for global dataset without Indian sequences, G251V in ORF3a in clade 19A, F308Y and G196V in NSP4 and ORF3a in 19B are the unique amino acid changes which are responsible for defining each clade as they are all deleterious and unstable. Such changes which are common for both global dataset without Indian and dataset of exclusive Indian sequences are R203M in Nucleocapsid for 20B, T85I and Q57H in NSP2 and ORF3a respectively for 20C while for exclusive Indian sequences such unique changes are A97V in RdRp, G339S and G339C in NSP2 in 19A and Q57H in ORF3a in 20A.

Strategies for COVID-19 Epidemiological Surveillance in India: Overall Policies Till June 2021

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has gripped the entire world, almost paralysing the human race in its entirety. The virus rapidly transmits via human-to-human medium resulting in a massive increase of patients with COVID-19. In order to curb the spread of the disease, an immediate action of complete lockdown was implemented across the globe. India with a population of over 1.3 billion was not an exception and took the challenge to execute phase-wise lockdown, unlock and partial lockdown activities. In this study, we intend to summarise these different phases that the Government of India (GoI) imposed to fight against SARS-CoV-2 so that it can act as a reference guideline to help controlling future waves of COVID-19 and similar pandemic situations in India.