The relevant information about the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using the five-question approach (when, where, what, why, and how) and its impact on the environment.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is regarded as a threat because it spreads quickly across the world without requiring a passport or establishing an identity. This tiny virus has wreaked havoc on people's lives, killed people, and created psychological problems all over the world. The viral spike protein (S) significantly contributes to host cell entry, and mutations associated with it, particularly in the receptor-binding protein (RBD), either facilitate the escape of virus from neutralizing antibodies or enhance its transmission by increasing the affinity for cell entry receptor, angiotensin-converting enzyme 2 (ACE2). The initial variants identified in Brazil, South Africa, and the UK have spread to various countries. On the other hand, new variants are being detected in India and the USA. The viral genome and proteome were applied for molecular detection techniques, and nanotechnology particles and materials were utilized in protection and prevention strategies. Consequently, the SARS-CoV-2 pandemic has resulted in extraordinary scientific community efforts to develop detection methods, diagnosis tools, and effective antiviral drugs and vaccines, where prevailing academic, governmental, and industrial institutions and organizations continue to engage themselves in large-scale screening of existing drugs, both in vitro and in vivo. In addition, COVID-19 pointed on the possible solutions for the environmental pollution globe problem. Therefore, this review aims to address SARS-CoV-2, its transmission, where it can be found, why it is severe in some people, how it can be stopped, its diagnosis and detection techniques, and its relationship with the environment.

Efficient CRISPR-Cas13d-Based Antiviral Strategy to Combat SARS-CoV-2.

The current SARS-CoV-2 pandemic forms a major global health burden. Although protective vaccines are available, concerns remain as new virus variants continue to appear. CRISPR-based gene-editing approaches offer an attractive therapeutic strategy as the CRISPR-RNA (crRNA) can be adjusted rapidly to accommodate a new viral genome sequence. This study aimed at using the RNA-targeting CRISPR-Cas13d system to attack highly conserved sequences in the viral RNA genome, thereby preparing for future zoonotic outbreaks of other coronaviruses. We designed 29 crRNAs targeting highly conserved sequences along the complete SARS-CoV-2 genome. Several crRNAs demonstrated efficient silencing of a reporter with the matching viral target sequence and efficient inhibition of a SARS-CoV-2 replicon. The crRNAs that suppress SARS-CoV-2 were also able to suppress SARS-CoV, thus demonstrating the breadth of this antiviral strategy. Strikingly, we observed that only crRNAs directed against the plus-genomic RNA demonstrated antiviral activity in the replicon assay, in contrast to those that bind the minus-genomic RNA, the replication intermediate. These results point to a major difference in the vulnerability and biology of the +RNA versus -RNA strands of the SARS-CoV-2 genome and provide important insights for the design of RNA-targeting antivirals.

Molecular determinants associated with temporal succession of SARS-CoV-2 variants in Uttar Pradesh, India.

The emergence and rapid evolution of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused a global crisis that required a detailed characterization of the dynamics of mutational pattern of the viral genome for comprehending its epidemiology, pathogenesis and containment. We investigated the molecular evolution of the SASR-CoV-2 genome during the first, second and third waves of COVID-19 in Uttar Pradesh, India. Nanopore sequencing of the SARS-CoV-2 genome was undertaken in 544 confirmed cases of COVID-19, which included vaccinated and unvaccinated individuals. In the first wave (unvaccinated population), the 20A clade (56.32%) was superior that was replaced by 21A Delta in the second wave, which was more often seen in vaccinated individuals in comparison to unvaccinated (75.84% versus 16.17%, respectively). Subsequently, 21A delta got outcompeted by Omicron (71.8%), especially the 21L variant, in the third wave. We noticed that Q677H appeared in 20A Alpha and stayed up to Delta, D614G appeared in 20A Alpha and stayed in Delta and Omicron variants (got fixed), and several other mutations appeared in Delta and stayed in Omicron. A cross-sectional analysis of the vaccinated and unvaccinated individuals during the second wave revealed signature combinations of E156G, F157Del, L452R, T478K, D614G mutations in the Spike protein that might have facilitated vaccination breach in India. Interestingly, some of these mutation combinations were carried forward from Delta to Omicron. In silico protein docking showed that Omicron had a higher binding affinity with the host ACE2 receptor, resulting in enhanced infectivity of Omicron over the Delta variant. This work has identified the combinations of key mutations causing vaccination breach in India and provided insights into the change of [virus's] binding affinity with evolution, resulting in more virulence in Delta and more infectivity in Omicron variants of SARS-CoV-2. Our findings will help in understanding the COVID-19 disease biology and guide further surveillance of the SARS-CoV-2 genome to facilitate the development of vaccines with better efficacies.

A SARS-CoV-2 full genome sequence of the B.1.1 lineage sheds light on viral evolution in Sicily in late 2020.

To investigate the influence of geographic constrains to mobility on SARS-CoV-2 circulation before the advent of vaccination, we recently characterized the occurrence in Sicily of viral lineages in the second pandemic wave (September to December 2020). Our data revealed wide prevalence of the then widespread through Europe B.1.177 variant, although some viral samples could not be classified with the limited Sanger sequencing tools used. A particularly interesting sample could not be fitted to a major variant then circulating in Europe and has been subjected here to full genome sequencing in an attempt to clarify its origin, lineage and relations with the seven full genome sequences deposited for that period in Sicily, hoping to provide clues on viral evolution. The obtained genome is unique (not present in databases). It hosts 20 single-base substitutions relative to the original Wuhan-Hu-1 sequence, 8 of them synonymous and the other 12 encoding 11 amino acid substitutions, all of them already reported one by one. They include four highly prevalent substitutions, NSP12:P323L, S:D614G, and N:R203K/G204R; the much less prevalent S:G181V, ORF3a:G49V and N:R209I changes; and the very rare mutations NSP3:L761I, NSP6:S106F, NSP8:S41F and NSP14:Y447H. GISAID labeled this genome as B.1.1 lineage, a lineage that appeared early on in the pandemic. Phylogenetic analysis also confirmed this lineage diagnosis. Comparison with the seven genome sequences deposited in late 2020 from Sicily revealed branching leading to B.1.177 in one branch and to Alpha in the other branch, and suggested a local origin for the S:G118V mutation.

A high scale SARS-CoV-2 profiling by its whole-genome sequencing using Oxford Nanopore Technology in Kazakhstan.

Severe acute respiratory syndrome (SARS-CoV-2) is responsible for the worldwide pandemic, COVID-19. The original viral whole-genome was sequenced by a high-throughput sequencing approach from the samples obtained from Wuhan, China. Real-time gene sequencing is the main parameter to manage viral outbreaks because it expands our understanding of virus proliferation, spread, and evolution. Whole-genome sequencing is critical for SARS-CoV-2 variant surveillance, the development of new vaccines and boosters, and the representation of epidemiological situations in the country. A significant increase in the number of COVID-19 cases confirmed in August 2021 in Kazakhstan facilitated a need to establish an effective and proficient system for further study of SARS-CoV-2 genetic variants and the development of future Kazakhstan's genomic surveillance program. The SARS-CoV-2 whole-genome was sequenced according to SARS-CoV-2 ARTIC protocol (EXP-MRT001) by Oxford Nanopore Technologies at the National Laboratory Astana, Kazakhstan to track viral variants circulating in the country. The 500 samples kindly provided by the Republican Diagnostic Center (UMC-NU) and private laboratory KDL "Olymp" were collected from individuals in Nur-Sultan city diagnosed with COVID-19 from August 2021 to May 2022 using real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). All samples had a cycle threshold (Ct) value below 20 with an average Ct value of 17.03. The overall average value of sequencing depth coverage for samples is 244X. 341 whole-genome sequences that passed quality control were deposited in the Global initiative on sharing all influenza data (GISAID). The BA.1.1 (n = 189), BA.1 (n = 15), BA.2 (n = 3), BA.1.15 (n = 1), BA.1.17.2 (n = 1) omicron lineages, AY.122 (n = 119), B.1.617.2 (n = 8), AY.111 (n = 2), AY.126 (n = 1), AY.4 (n = 1) delta lineages, one sample B.1.1.7 (n = 1) belongs to alpha lineage, and one sample B.1.637 (n = 1) belongs to small sublineage were detected in this study. This is the first study of SARS-CoV-2 whole-genome sequencing by the ONT approach in Kazakhstan, which can be expanded for the investigation of other emerging viral or bacterial infections on the country level.

Whole genome sequencing analysis of SARS-CoV-2 from Malaysia: From alpha to Omicron.

Countries around the world are gearing for the transition of the coronavirus disease 2019 (COVID-19) from pandemic to endemic phase but the emergence of new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants could lead to a prolonged pandemic. SARS-CoV-2 has continued to evolve as it optimizes its adaptation to the human host and the successive waves of COVID-19 have been linked to the explosion of particular variant of concern. As the genetic diversity and epidemiological landscape of SARS-CoV-2 differ from country to country, this study aims to provide insights into the variants that are circulating in Malaysia. Whole genome sequencing was performed for 204 SARS-CoV-2 from COVID-19 cases and an additional 18,667 SARS-CoV-2 genome sequences were retrieved from the GISAID EpiCoV database for clade, lineage and genetic variation analyses. Complete genome sequences with high coverage were then used for phylogeny investigation and the resulting phylogenetic tree was constructed from 8,716 sequences. We found that the different waves of COVID-19 in Malaysia were dominated by different clades with the L and O clade for first and second wave, respectively, whereas the progressive replacement by G, GH, and GK of the GRA clade were observed in the subsequence waves. Continuous monitoring of the genetic diversity of SARS-CoV-2 is important to identify the emergence and dominance of new variant in different locality so that the appropriate countermeasures can be taken to effectively contain the spread of SARS-CoV-2.

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.

Computational Pipeline for Reference-Free Comparative Analysis of RNA 3D Structures Applied to SARS-CoV-2 UTR Models.

RNA is a unique biomolecule that is involved in a variety of fundamental biological functions, all of which depend solely on its structure and dynamics. Since the experimental determination of crystal RNA structures is laborious, computational 3D structure prediction methods are experiencing an ongoing and thriving development. Such methods can lead to many models; thus, it is necessary to build comparisons and extract common structural motifs for further medical or biological studies. Here, we introduce a computational pipeline dedicated to reference-free high-throughput comparative analysis of 3D RNA structures. We show its application in the RNA-Puzzles challenge, in which five participating groups attempted to predict the three-dimensional structures of 5'- and 3'-untranslated regions (UTRs) of the SARS-CoV-2 genome. We report the results of this puzzle and discuss the structural motifs obtained from the analysis. All simulated models and tools incorporated into the pipeline are open to scientific and academic use.

Assessment and Molecular Docking of SARS-CoV-2 NSP3 and NSP12 Mutants in Iranian Patients in Golestan Province

Background: Molecular analysis of SARS-CoV-2 genome is important to predict viral pathogenicity. In addition to transmission, replication is a key factor in pathogenicity of the virus. Notably, mutations in non-structural proteins (NSP3 and NSP12) can affect host immune response and viral replication. Therefore, this study was conducted to investigate different mutations of SARS-CoV-2 NSP3, and NSP12 during different waves of COVID-19 infection. Methods: We recruited 57 NGS sequences including 8 NGS sequences from Golestan SARS-CoV-2 RNA samples, obtained as part of clinical testing in different referral centers of Iran. After obtaining sequences from the global initiative on sharing all influenza data (GISAID), and evaluating and processing data, all sequences were aligned to the Wuhan variant genome (NC_045512.2) using MEGA6. The HDOCK server was used for molecular docking. Results: In NSP3, mutations in positions (nts 315, 545, 2666, 3264) were more frequent and among them mutation in positions including nt 545 (aa182) and nt 2666 (aa889) were associated with an increase in codon usage. In the term of NSP12, mutations in positions such as nts 406 (aa137), 965 (aa323), 1233, 1653, 1836, 2733 were more frequent. The molecular docking results showed more affinity in some variants of NSP3 and NSP12 as well. Conclusion: This study has assessed mutation in SARS-CoV-2 Nsp3, and NSP12 which are viral protease, and viral polymerase (RdRp). The mutations reported in this study may help this virus to replicate faster and evade the pharmaceutical agents which target viral polymerase activity and be very effective in viral pathogenesis. In addition, this study highlights the importance of ongoing genomic variation studies to be performed on SARS-CoV-2 variants.

The Effects of SARS CoV-2 nsp13 Mutations on the Structure and Stability of Helicase in Chinese Isolates

Objective: Coronavirus Disease 2019 (COVID19) is a viral disease caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS CoV-2). The high mutation propensity of the SARS CoV-2 genome is one of the biggest threats to the long-term validity of treatment options. Helicases are anti-viral targets because of the vital role they play in the viral life cycle. In this study, changes in the protein structure caused by SARS CoV-2 nsp13 mutations were investigated to contribute to the development of effective antiviral drugs. Materials and Methods: Genome data of 298 individuals located in the China location were examined. The mutant model was built using deep learning algorithms. Model quality assessment was done with QMEAN. Protein stability analyses were performed with DynaMut2 and Cutoff Scanning Matrix stability. Changes in substrate affinity were performed with Haddock v2.4. Results: In this study, twenty-eight mutations in nsp13 were identified (23 sense, 5 missense). The changes in protein structure caused by the five missense mutations (Leu14Phe, Arg15Ser, Arg21Ser, Leu235Phe, Ala454Thr) were modeled. The mutations caused a decrease in the stability of SARS CoV-2 helicase (-0.99, -1.66, -1.15, -0.54, and -0.73 for Leu14Phe, Arg15Ser, Arg21Ser, Leu235Phe, Ala454Thr, respectively). The mutations reduced the helicase's affinity to the substrate. The docking scores for wild-type and mutant helicase were -84.4±1.4 kcal.mol-1 and -71.1±6.7 kcal.mol-1, respectively. Conclusion: Helicase mutations caused a decrease in the protein stability and nucleic acid affinity of the SARS CoV-2 helicase. The results provide important data on the development of potential antivirals and the effect of mutation on the functions of viral proteins. © European Journal of Biology.All rights reserved.

Efficient compression of SARS-CoV-2 genome data using Nucleotide Archival Format.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome data are essential for epidemiology, vaccine development, and tracking emerging variants. Millions of SARS-CoV-2 genomes have been sequenced during the pandemic. However, downloading SARS-CoV-2 genomes from databases is slow and unreliable, largely due to suboptimal choice of compression method. We evaluated the available compressors and found that Nucleotide Archival Format (NAF) would provide a drastic improvement compared with current methods. For Global Initiative on Sharing Avian Flu Data's (GISAID) pre-compressed datasets, NAF would increase efficiency 52.2 times for gzip-compressed data and 3.7 times for xz-compressed data. For DNA DataBank of Japan (DDBJ), NAF would improve throughput 40 times for gzip-compressed data. For GenBank and European Nucleotide Archive (ENA), NAF would accelerate data distribution by a factor of 29.3 times compared with uncompressed FASTA. This article provides a tutorial for installing and using NAF. Offering a NAF download option in sequence databases would provide a significant saving of time, bandwidth, and disk space and accelerate biological and medical research worldwide.

Optimizing the Illumina COVIDSeq laboratorial and bioinformatics pipeline on thousands of samples for SARS-CoV-2 Variants of Concern tracking.

The SARS-CoV-2 Variants of Concern tracking via Whole Genome Sequencing represents a pillar of public health measures for the containment of the pandemic. The ability to track down the lineage distribution on a local and global scale leads to a better understanding of immune escape and to adopting interventions to contain novel outbreaks. This scenario poses a challenge for NGS laboratories worldwide that are pressed to have both a faster turnaround time and a high-throughput processing of swabs for sequencing and analysis. In this study, we present an optimization of the Illumina COVID-seq protocol carried out on thousands of SARS-CoV-2 samples at the wet and dry level. We discuss the unique challenges related to processing hundreds of swabs per week such as the tradeoff between ultra-high sensitivity and negative contamination levels, cost efficiency and bioinformatics quality metrics.

Cover Feature: The Extended Hadamard Transform: Sensitivity-Enhanced NMR Experiments Among Labile and Non-Labile 1Hs of SARS-CoV-2-derived RNAs (ChemPhysChem 4/2022)

The Cover Feature illustrates how artifact-free 2D NOE correlations between labile protons can be obtained from an extended Hadamard encoding/decoding matrix, which supersedes problems in conventional Hadamard schemes. The sensitivity-enhancing abilities of extended Hadamard encoding operating in conjunction with solvent repolarization mechanisms are demonstrated on GHz NMR studies on SARS-CoV-2 RNA fragments. More information can be found in the Article by Lucio Frydman and co-workers.

In Silico Prediction and Selection of Target Sequences in the SARS-CoV-2 RNA Genome for an Antiviral Attack.

The SARS-CoV-2 pandemic has urged the development of protective vaccines and the search for specific antiviral drugs. The modern molecular biology tools provides alternative methods, such as CRISPR-Cas and RNA interference, that can be adapted as antiviral approaches, and contribute to this search. The unique CRISPR-Cas13d system, with the small crRNA guide molecule, mediates a sequence-specific attack on RNA, and can be developed as an anti-coronavirus strategy. We analyzed the SARS-CoV-2 genome to localize the hypothetically best crRNA-annealing sites of 23 nucleotides based on our extensive expertise with sequence-specific antiviral strategies. We considered target sites of which the sequence is well-conserved among SARS-CoV-2 isolates. As we should prepare for a potential future outbreak of related viruses, we screened for targets that are conserved between SARS-CoV-2 and SARS-CoV. To further broaden the search, we screened for targets that are conserved between SARS-CoV-2 and the more distantly related MERS-CoV, as well as the four other human coronaviruses (OC43, 229E, NL63, HKU1). Finally, we performed a search for pan-corona target sequences that are conserved among all these coronaviruses, including the new Omicron variant, that are able to replicate in humans. This survey may contribute to the design of effective, safe, and escape-proof antiviral strategies to prepare for future pandemics.

Could Small Neurotoxins-Peptides be Expressed during SARS-CoV-2 Infection?

SARS-CoV-2 pathogenesis has been recently extended to human central nervous system (CNS), in addition to nasopharyngeal truck, eye, lung and gut. The recent literature highlights that some SARS-CoV-2 spike glycoprotein regions homologous to neurotoxin-like peptides might bind to human nicotinic Acetyl-Choline Receptors (nAChRs). Spike-nAChR interaction can probably cause dysregulation of CNS and cholinergic anti-inflammatory pathways and uncontrolled immune-response, both associated to a severe COVID-19 pathophysiology. Herein, we hypothesize that inside the Open Reading Frame (ORF) region of spike glycoprotein, the RNA polymerase can translate small neurotoxic peptides by means of a "jumping mechanism" already demonstrated in other coronaviruses. These small peptides can bind the snAChRs instead of Spike glycoproteins. A striking homology occurred between these small peptides observed by sequence retrieval and proteins alignment. Acting as nAChRs antagonists, these small peptides (conotoxins) could be the explanation for the extrapulmonary clinical manifestations (neurological, hemorrhagic and thrombotic expressions, the prolonged apnea, the cardiocirculatory collapse, the heart arrhythmias, the ventricular tachycardia, the body temperature alteration, the electrolyte K+ imbalance and finally the significant reduction of butyryl cholinesterase (BuChE) plasma levels, as observed in COVID-19 patients. Several factors might induce the expression of these small peptides, including microbiota. The main hypothesis regarding the presence of these small peptides opens a new scenario on the etiology of COVID-19 clinical symptoms observed so far, including the neurological manifestations.

The Extended Hadamard Transform: Sensitivity-Enhanced NMR Experiments Among Labile and Non-Labile 1 Hs of SARS-CoV-2-derived RNAs.

Hadamard encoded saturation transfer can significantly improve the efficiency of NOE-based NMR correlations from labile protons in proteins, glycans and RNAs, increasing the sensitivity of cross-peaks by an order of magnitude and shortening experimental times by ≥100-fold. These schemes, however, fail when tackling correlations within a pool of labile protons - for instance imino-imino correlations in RNAs or amide-amide correlations in proteins. Here we analyze the origin of the artifacts appearing in these experiments and propose a way to obtain artifact-free correlations both within the labile pool as well as between labile and non-labile 1 Hs, while still enjoying the gains arising from Hadamard encoding and solvent repolarizations. The principles required for implementing what we define as the extended Hadamard scheme are derived, and its clean, artifact-free, sensitivity-enhancing performance is demonstrated on RNA fragments derived from the SARS-CoV-2 genome. Sensitivity gains per unit time approaching an order of magnitude are then achieved in both imino-imino and imino-amino/aromatic protons 2D correlations; similar artifact-free sensitivity gains can be observed when carrying out extended Hadamard encodings of 3D NOESY/HSQC-type experiments. The resulting spectra reveal significantly more correlations than their conventionally acquired counterparts, which can support the spectral assignment and secondary structure determination of structured RNA elements.

The Development of SARS-CoV-2 Variants: The Gene Makes the Disease.

A novel coronavirus (SARS-CoV-2) emerged towards the end of 2019 that caused a severe respiratory disease in humans called COVID-19. It led to a pandemic with a high rate of morbidity and mortality that is ongoing and threatening humankind. Most of the mutations occurring in SARS-CoV-2 are synonymous or deleterious, but a few of them produce improved viral functions. The first known mutation associated with higher transmissibility, D614G, was detected in early 2020. Since then, the virus has evolved; new mutations have occurred, and many variants have been described. Depending on the genes affected and the location of the mutations, they could provide altered infectivity, transmissibility, or immune escape. To date, mutations that cause variations in the SARS-CoV-2 spike protein have been among the most studied because of the protein's role in the initial virus-cell contact and because it is the most variable region in the virus genome. Some concerning mutations associated with an impact on viral fitness have been described in the Spike protein, such as D614G, N501Y, E484K, K417N/T, L452R, and P681R, among others. To understand the impact of the infectivity and antigenicity of the virus, the mutation landscape of SARS-CoV-2 has been under constant global scrutiny. The virus variants are defined according to their origin, their genetic profile (some characteristic mutations prevalent in the lineage), and the severity of the disease they produce, which determines the level of concern. If they increase fitness, new variants can outcompete others in the population. The Alpha variant was more transmissible than previous versions and quickly spread globally. The Beta and Gamma variants accumulated mutations that partially escape the immune defenses and affect the effectiveness of vaccines. Nowadays, the Delta variant, identified around March 2021, has spread and displaced the other variants, becoming the most concerning of all lineages that have emerged. The Delta variant has a particular genetic profile, bearing unique mutations, such as T478K in the spike protein and M203R in the nucleocapsid. This review summarizes the current knowledge of the different mutations that have appeared in SARS-CoV-2, mainly on the spike protein. It analyzes their impact on the protein function and, subsequently, on the level of concern of different variants and their importance in the ongoing pandemic.

A fractal scaling analysis of the SARS-CoV-2 genome sequence.

An approach based on fractal scaling analysis to characterize the organization of the SARS-CoV-2 genome sequence was used. The method is based on the detrended fluctuation analysis (DFA) implemented on a sliding window scheme to detect variations of long-range correlations over the genome sequence regions. The nucleotides sequence is mapped in a numerical sequence by using four different assignation rules: amino-keto, purine-pyrimidine, hydrogen-bond and hydrophobicity patterns. The originally reported sequence from Wuhan isolates (Wuhan Hu-1) was considered as a reference to contrast the structure of the 2002-2004 SARS-CoV-1 strain. Long-range correlations, quantified in terms of a scaling exponent, depended on both the mapping rule and the sequence region. Deviations from randomness were attributed to serial correlations or anti-correlations, which can be ascribed to ordered regions of the genome sequence. It was found that the Wuhan Hu-1 sequence was more random than the SARS-CoV-1 sequence, which suggests that the SARS-CoV-2 possesses a more efficient genomic structure for replication and infection. In general, the virus isolated in the early 2020 months showed slight correlation differences with the Wuhan Hu-1 sequence. However, early isolates from India and Italy presented visible differences that led to a more ordered sequence organization. It is apparent that the increased sequence order, particularly in the spike region, endowed some early variants with a more efficient mechanism to spreading, replicating and infecting. Overall, the results showed that the DFA provides a suitable framework to assess long-term correlations hidden in the internal organization of the SARS-CoV-2 genome sequence.

Comparative studies on the high-performance compression of SARS-CoV-2 genome collections.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is fast mutating worldwide. The mutated strains have been timely sequenced by worldwide labs, accumulating a huge amount of viral genome sequences open to public for biomedicine research such as mRNA vaccine design and drug recommendation. It is inefficient to transmit the millions of genome sequences without compression. In this study, we benchmark the performance of reference-free and reference-based compression algorithms on SARS-CoV-2 genome collections extracted from NCBI. Experimental results show that reference-based two-level compression is the most suitable approach to the compression, achieving the best compression ratio 1019.33-fold for compressing 132 372 genomes and 949.73-fold for compressing 416 238 genomes. This enormous file size reduction and efficient decompression have enabled a 5-min download and decompression of $10^5$ SARS-CoV-2 genomes. As compression on datasets containing such big numbers of genomes has been explored seldom before, our comparative analysis of the state-of-the-art compression algorithms provides practical guidance for the selection of compression tools and their parameters such as reference genomes to compress viral genome databases with similar characteristics. We also suggested a genome clustering approach using multiple references for a better compression. It is anticipated that the increased availability of SARS-CoV-2 genome datasets will make biomedicine research more productive.

Relative Consolidation of the Kappa Variant Pre-Dates the Massive Second Wave of COVID-19 in India.

India experienced a tragic second wave after the end of March 2021, which was far more massive than the first wave and was driven by the emergence of the novel delta variant (B.1.617.2) of the SARS-CoV-2 virus. In this study, we explored the local and national landscape of the viral variants in the period immediately preceding the second wave to gain insight into the mechanism of emergence of the delta variant and thus improve our understanding of the causation of the second wave. We randomly selected 20 SARS-CoV-2 positive samples diagnosed in our lab between 3 February and 8 March 2021 and subjected them to whole genome sequencing. Nine of the 20 sequenced genomes were classified as kappa variant (B.1.617.1). The phylogenetic analysis of pan-India SARS-CoV-2 genome sequences also suggested the gradual replacement of the α variant with the kappa variant during this period. This relative consolidation of the kappa variant was significant, since it shared 3 of the 4 signature mutations (L452R, E484Q and P681R) observed in the spike protein of delta variant and thus was likely to be the precursor in its evolution. This study demonstrates the predominance of the kappa variant in the period immediately prior to the second wave and underscores its role as the "bridging variant" between the α and delta variants that drove the first and second waves of COVID-19 in India, respectively.