Comprehensive analysis of genomic diversity of SARS-CoV-2 in different geographic regions of India: an endeavour to classify Indian SARS-CoV-2 strains on the basis of co-existing mutations

Effectiveness of remote ischaemic conditioning is not affected by hyper-inflammation in a rat model of stroke

The inflammation and coagulopathy during coronavirus disease (COVID-19) impairs the efficiency of the current stroke treatments. Remote ischaemic conditioning (RIC) has shown potential in recent years to protect the brain and other organs against pathological conditions. This study aimed to evaluate the efficiency of RIC in brain infarct size using TTC staining and lung injury reduction by H&E staining during the hyper-inflammatory response in rats. The inflammation and coagulopathy were assessed by sedimentation rate, haematocrit, systemic oxidative stress and clotting time. Moreover, we observed changes in the cytokine profile. The results of the first part of the experiment showed that the inflammation and lung injury are fully developed after 24 h of intratracheal LPS administration. At this time, we induced focal brain ischaemia and examined the effect of RIC pre- and post-treatment. Our results showed that RIPre-C reduced the infarct size by about 23%, while RIPost-C by about 30%. The lung injury was also reduced following both treatments. Moreover, RIC modulated systemic inflammation. The level of chemokines CINC-1, LIX and RANTES decreased after 24 h of post-ischaemic reperfusion in treated animals compared to non-treated. The RIC-mediated decrease of inflammation was reflected in improved sedimentation rate and hematocrit, as well as reduced systemic oxidative stress. The results of this work showed neuroprotective and lung protective effects of RIC with a decrease in inflammation response. On the basis of our results, we assume that immunomodulation through the chemokines CINC-1, LIX, and RANTES play a role in RIC-mediated protection.

Comparative Atlas of SARS-CoV-2 Substitution Mutations: A Focus on Iranian Strains Amidst Global Trends

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new emerging coronavirus that caused coronavirus disease 2019 (COVID-19). Whole-genome tracking of SARS-CoV-2 enhanced our understanding of the mechanism of the disease, control, and prevention of COVID-19.

METHODS

we analyzed 3368 SARS-CoV-2 protein sequences from Iran and compared them with 15.6 million global sequences in the GISAID database, using the Wuhan-Hu-1 strain as a reference.

RESULTS

Our investigation revealed that NSP12-P323L, ORF9c-G50N, NSP14-I42V, membrane-A63T, Q19E, and NSP3-G489S were found to be the most frequent mutations among Iranian SARS-CoV-2 sequences. Furthermore, it was observed that more than 94% of the SARS-CoV-2 genome, including NSP7, NSP8, NSP9, NSP10, NSP11, and ORF8, had no mutations when compared to the Wuhan-Hu-1 strain. Finally, our data indicated that the ORF3a-T24I, NSP3-G489S, NSP5-P132H, NSP14-I42V, envelope-T9I, nucleocapsid-D3L, membrane-Q19E, and membrane-A63T mutations might be responsible factors for the surge in the SARS-CoV-2 Omicron variant wave in Iran.

CONCLUSIONS

real-time genomic surveillance is crucial for detecting new SARS-CoV-2 variants, updating diagnostic tools, designing vaccines, and understanding adaptation to new environments.

Overlaid Lateral Flow Immunoassay for the Simultaneous Detection of Two Variant-Specific SARS-CoV-2 Neutralizing Antibodies

COVID-19 vaccines have been provided to the general public to build immunity since the 2019 coronavirus pandemic. Once vaccinated, SARS-CoV-2 neutralizing antibodies (NAbs-COVID-19) are needed for excellent protection against COVID-19. However, monitoring NAbs-COVID-19 is complicated and requires hospital visits. Moreover, the resulting NAbs-COVID-19 are effective against different strains of COVID-19 depending on the type of vaccine received. Here, an overlaid lateral flow immunoassay (O-LFIA) was developed for the simultaneous detection of two NAbs-COVID-19 against different virus strains, Delta and Omicron. The O-LFIA was visualized with two T-lines with a single device using competition between the free antigen and the antigen-binding antibody. Angiotensin-converting enzyme 2 (ACE2) immobilized on the T-line binds to the antigen remaining after antibody binding. Under the optimum conditions, the proposed device exhibited 50% inhibition concentrations (IC50 values) of 45.1 and 53.6 ng/mL for the Delta and Omicron variants, respectively. Additionally, the proposed platform was applied to real-world samples of animal and human serum, and the developed immunoassay provided results that were in good agreement with those obtained with the standard method. In conclusion, this developed O-LFIA can be used as an alternative method to detect NAbs-COVID-19 and can be enabled for future advancements toward commercialization.

Analysis of SARS-CoV-2 genome evolutionary patterns

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

Unraveling the genetic evolution of SARS-CoV-2 Recombinants using mutational dynamics across the different lineages

Introduction

Recombination serves as a common strategy employed by RNA viruses for their genetic evolution. Extensive genomic surveillance during the COVID-19 pandemic has reported SARS-CoV-2 Recombinant strains indicating recombination events during the viral evolution. This study introspects the phenomenon of genome recombination by tracing the footprint of prominent lineages of SARS-CoV-2 at different time points in the context of on-going evolution and emergence of Recombinants.

Method

Whole genome sequencing was carried out for 2,516 SARS-CoV-2 (discovery cohort) and 1,126 (validation cohort) using nasopharyngeal samples collected between the time period of March 2020 to August 2022, as part of the genomic surveillance program. The sequences were classified according to the different lineages of SARS-CoV-2 prevailing in India at respective time points.

Results

Mutational diversity and abundance evaluation across the 12 lineages identified 58 Recombinant sequences as harboring the least number of mutations (n = 111), with 14 low-frequency unique mutations with major chunk of mutations coming from the BA.2. The spontaneously/dynamically increasing and decreasing trends of mutations highlight the loss of mutations in the Recombinants that were associated with the SARS-CoV-2 replication efficiency, infectivity, and disease severity, rendering them functionally with low infectivity and pathogenicity. Linkage disequilibrium (LD) analysis revealed that mutations comprising the LD blocks of BA.1, BA.2, and Recombinants were found as minor alleles or as low-frequency alleles in the LD blocks from the previous SARS-CoV-2 variant samples, especially Pre-VOC. Moreover, a dissipation in the size of LD blocks as well as LD decay along with a high negative regression coefficient (R squared) value was demonstrated in the Omicron and BA.1 and BA.2 lineages, which corroborated with the breakpoint analysis.

Conclusion

Together, the findings help to understand the evolution and emergence of Recombinants after the Omicron lineages, for sustenance and adaptability, to maintain the epidemic spread of SARS-CoV-2 in the host population already high in immunity levels.

Co-evolution of SARS-CoV-2 variants and host immune response trajectories underlie COVID-19 pandemic to epidemic transition

COVID-19 pandemic saw emergence of multiple SAR-CoV-2 variants. Exacerbated risk of severe outcome and hospital admissions led us to comprehend differential host-immune kinetics associated with SARS-CoV-2 variants. Longitudinal investigation was conducted through different time periods of Pre-VOC and VOCs (Delta & Omicron) mapping host transcriptome features. Robust antiviral type-1 interferon response marked Omicron infection, which was largely missing during Pre-VOC and Delta waves. SARS-CoV-2-host protein-protein interactions and docking complexes highlighted N protein to interact with HNRNPA1 in Pre-VOC, demonstrating its functional role for enhanced viral replication. Omicron revealed enhanced binding efficiency of LARP1 to N protein, probably potentiating antiviral effects of LARP1. Differential expression of zinc finger protein genes, especially in Omicron, mechanistically support induction of strong IFN (Interferon) response, thereby strengthening early viral clearance. Study highlights eventual adaptation of host to immune activation patterns that interrupt virus evolution with enhanced immune-evasion mutations and counteraction mechanisms, delimiting the next phase of COVID-19 pandemic.

Genomic epidemiology of SARS-CoV-2 from Uttar Pradesh, India

The various strains and mutations of SARS-CoV-2 have been tracked using several forms of genomic classification systems. The present study reports high-throughput sequencing and analysis of 99 SARS-CoV-2 specimens from Western Uttar Pradesh using sequences obtained from the GISAID database, followed by phylogeny and clade classification. Phylogenetic analysis revealed that Omicron lineages BA-2-like (55.55%) followed by Delta lineage-B.1.617.2 (45.5%) were predominantly circulating in this area Signature substitution at positions S: N501Y, S: D614G, S: T478K, S: K417N, S: E484A, S: P681H, and S: S477N were commonly detected in the Omicron variant-BA-2-like, however S: D614G, S: L452R, S: P681R and S: D950N were confined to Delta variant-B.1.617.2. We have also identified three escape variants in the S gene at codon position 19 (T19I/R), 484 (E484A/Q), and 681 (P681R/H) during the fourth and fifth waves in India. Based on the phylogenetic diversification studies and similar changes in other lineages, our analysis revealed indications of convergent evolution as the virus adjusts to the shifting immunological profile of its human host. To the best of our knowledge, this study is an approach to comprehensively map the circulating SARS-CoV-2 strains from Western Uttar Pradesh using an integrated approach of whole genome sequencing and phylogenetic analysis. These findings will be extremely valuable in developing a structured approach toward pandemic preparedness and evidence-based intervention plans in the future.

SARS2Mutant: SARS-CoV-2 amino-acid mutation atlas database

The coronavirus disease 19 (COVID-19) is a highly pathogenic viral infection of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulted in the global pandemic of 2020. A lack of therapeutic and preventive strategies has quickly posed significant threats to world health. A comprehensive understanding of SARS-CoV-2 evolution and natural selection, how it impacts host interaction, and phenotype symptoms is vital to develop effective strategies against the virus. The SARS2Mutant database (http://sars2mutant.com/) was developed to provide valuable insights based on millions of high-quality, high-coverage SARS-CoV-2 complete protein sequences. Users of this database have the ability to search for information on three amino acid substitution mutation strategies based on gene name, geographical zone, or comparative analysis. Each strategy is presented in five distinct formats which includes: (i) mutated sample frequencies, (ii) heat maps of mutated amino acid positions, (iii) mutation survivals, (iv) natural selections and (v) details of substituted amino acids, including their names, positions, and frequencies. GISAID is a primary database of genomics sequencies of influenza viruses updated daily. SARS2Mutant is a secondary database developed to discover mutation and conserved regions from the primary data to assist with design for targeted vaccine, primer, and drug discoveries.

Early detection of SARS-CoV-2 variants through dynamic co-mutation network surveillance

Background

Precise public health and clinical interventions for the COVID-19 pandemic has spurred a global rush on SARS-CoV-2 variant tracking, but current approaches to variant tracking are challenged by the flood of viral genome sequences leading to a loss of timeliness, accuracy, and reliability. Here, we devised a new co-mutation network framework, aiming to tackle these difficulties in variant surveillance.

Methods

To avoid simultaneous input and modeling of the whole large-scale data, we dynamically investigate the nucleotide covarying pattern of weekly sequences. The community detection algorithm is applied to a co-occurring genomic alteration network constructed from mutation corpora of weekly collected data. Co-mutation communities are identified, extracted, and characterized as variant markers. They contribute to the creation and weekly updates of a community-based variant dictionary tree representing SARS-CoV-2 evolution, where highly similar ones between weeks have been merged to represent the same variants. Emerging communities imply the presence of novel viral variants or new branches of existing variants. This process was benchmarked with worldwide GISAID data and validated using national level data from six COVID-19 hotspot countries.

Results

A total of 235 co-mutation communities were identified after a 120 weeks' investigation of worldwide sequence data, from March 2020 to mid-June 2022. The dictionary tree progressively developed from these communities perfectly recorded the time course of SARS-CoV-2 branching, coinciding with GISAID clades. The time-varying prevalence of these communities in the viral population showed a good match with the emergence and circulation of the variants they represented. All these benchmark results not only exhibited the methodology features but also demonstrated high efficiency in detection of the pandemic variants. When it was applied to regional variant surveillance, our method displayed significantly earlier identification of feature communities of major WHO-named SARS-CoV-2 variants in contrast with Pangolin's monitoring.

Conclusion

An efficient genomic surveillance framework built from weekly co-mutation networks and a dynamic community-based variant dictionary tree enables early detection and continuous investigation of SARS-CoV-2 variants overcoming genomic data flood, aiding in the response to the COVID-19 pandemic.

Comparative efficacy and safety of pharmacological interventions for severe COVID-19 patients: An updated network meta-analysis of 48 randomized controlled trials

BACKGROUND

To date, there has been little agreement on what drug is the "best" drug for treating severe COVID-19 patients. This study aimed to assess the efficacy and safety of different medications available at present for severe COVID-19.

METHODS

We searched databases for randomized controlled trials (RCTs) published up to February 28, 2022, with no language restrictions, of medications recommended for patients (aged 16 years or older) with severe COVID-19 infection. We extracted data on trials and patient characteristics, and the following primary outcomes: all-cause mortality (ACM), and treatment-emergent adverse events (TEAEs).

RESULTS

We identified 4021 abstracts and of these included 48 RCTs comprising 9147 participants through database searches and other sources. For decrease in ACM, we found that ivermectin/doxycycline, C-IVIG (i.e., a hyperimmune anti-COVID-19 intravenous immunoglobulin), methylprednisolone, interferon-beta/standard-of-care (SOC), interferon-beta-1b, convalescent plasma, remdesivir, lopinavir/ritonavir, immunoglobulin gamma, high dosage sarilumab (HS), auxora, and imatinib were effective when compared with placebo or SOC group. We found that colchicine and interferon-beta/SOC were only associated with the TEAEs of severe COVID-19 patients.

CONCLUSION

This study suggested that ivermectin/doxycycline, C-IVIG, methylprednisolone, interferon-beta/SOC, interferon-beta-1b, convalescent plasma (CP), remdesivir, lopinavir/ritonavir, immunoglobulin gamma, HS, auxora, and imatinib were efficacious for treating severe COVID-19 patients. We found that most medications were safe in treating severe COVID-19. More large-scale RCTs are still needed to confirm the results of this study.

Nucleotide-based genetic networks: Methods and applications

Genomic variations have been acclaimed as among the key players in understanding the biological mechanisms behind migration, evolution, and adaptation to extreme conditions. Due to stochastic evolutionary forces, the frequency of polymorphisms is affected by changes in the frequency of nearby polymorphisms in the same DNA sample, making them connected in terms of evolution. This article presents all the ingredients to understand the cumulative effects and complex behaviors of genetic variations in the human mitochondrial genome by analyzing co-occurrence networks of nucleotides, and shows key results obtained from such analyses. The article emphasizes recent investigations of these co-occurrence networks, describing the role of interactions between nucleotides in fundamental processes of human migration and viral evolution. The corresponding co-mutation-based genetic networks revealed genetic signatures of human adaptation in extreme environments. This article provides the methods of constructing such networks in detail, along with their graph-theoretical properties, and applications of the genomic networks in understanding the role of nucleotide co-evolution in evolution of the whole genome.

Development of antibody resistance in emerging mutant strains of SARS CoV-2: Impediment for COVID-19 vaccines

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a highly infectious agent associated with unprecedented morbidity and mortality. A failure to stop growth of COVID-19-linked morbidity rates is caused by SARS-CoV-2 mutations and the emergence of new highly virulent SARS-CoV-2 strains. Several acquired SARS-CoV-2 mutations reflect viral adaptations to host immune defence. Mutations in the virus Spike-protein were associated with the lowered effectiveness of current preventive therapies, including vaccines. Recent in vitro studies detected diminished neutralisation capacity of vaccine-induced antibodies, which are targeted to bind Spike receptor-binding and N-terminal domains in the emerging strains. Lower than expected inhibitory activity of antibodies was reported against viruses with E484K Spike mutation, including B.1.1.7 (UK), P.1 (Brazil), B.1.351 (South African), and new Omicron variant (B.1.1.529) with E484A mutation. The vaccine effectiveness is yet to be examined against new mutant strains of SARS-CoV-2 originating in Europe, Nigeria, Brazil, South Africa, and India. To prevent the loss of anti-viral protection in vivo, often defined as antibody resistance, it is required to target highly conserved viral sequences (including Spike protein) and enhance the potency of antibody cocktails. In this review, we assess the reported mutation-acquiring potential of coronaviruses and compare efficacies of current COVID-19 vaccines against 'parent' and 'mutant' strains of SARS-CoV-2 (Kappa (B.1.617.1), Delta (B.1.617.2), and Omicron (B.1.1.529)).

Molecular epidemiology and genetic characterization of SARS-CoV-2 in Kuwait: A descriptive study

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has been fatal to human health, affecting almost the entire world. Here we reported, for the first time, characterization of the genetic variants of SARS-CoV-2 circulating in Kuwait to understand their genetic diversity and monitor the accumulation of mutations over time. This study randomly enrolled 209 COVID-19 patients whose nasopharyngeal swabs were positive for SARS-CoV-2 between February 2020 and June 2021 using RT-PCR. The whole genomes of SARS-CoV-2 from the nasopharyngeal swabs were sequenced using the Oxford Nanopore sequencing technology following the ARTIC network protocol. Whole-genome sequencing has identified different clades/sub-clades circulating in Kuwait, mimicking the virus’s global spread. Clade 20A was dominant from February 2020 until January 2021, and then clade 20I (Alpha, V1) emerged and dominated. In June 2021, the number of cases infected with clades 21I, 21A, and 21 J (Delta) increased and dominated. We detected several known clade-defining missense and synonymous mutations and other missense mutations in the genes encoding important viral proteins, including ORF1a, S, ORF3a, ORF8 regions and a novel mutation in the N region. ORF1ab region harbored more mutations and deletions (n = 62, 49.2%) compared to the other 12 gene regions, and the most prevalent missense mutations were P314L (97%) in ORF1b and D614G (97%) in the S glycoprotein regions. Detecting and analyzing mutations and monitoring the evolution of SARS-CoV-2 over time is essential to help better understand the spread of various clades/strains of SARS-CoV-2 and their implications for pathogenesis. In addition, knowledge of the circulating variants and genome sequence variability of SARS-CoV-2 may potentially influence the development of vaccines and antiviral drugs to control the COVID-19 pandemic.

A random priming amplification method for whole genome sequencing of SARS-CoV-2 virus

BACKGROUND

Non-targeted whole genome sequencing is a powerful tool to comprehensively identify constituents of microbial communities in a sample. There is no need to direct the analysis to any identification before sequencing which can decrease the introduction of bias and false negatives results. It also allows the assessment of genetic aberrations in the genome (e.g., single nucleotide variants, deletions, insertions and copy number variants) including in noncoding protein regions.

METHODS

The performance of four different random priming amplification methods to recover RNA viral genetic material of SARS-CoV-2 were compared in this study. In method 1 (H-P) the reverse transcriptase (RT) step was performed with random hexamers whereas in methods 2-4 RT incorporating an octamer primer with a known tag. In methods 1 and 2 (K-P) sequencing was applied on material derived from the RT-PCR step, whereas in methods 3 (SISPA) and 4 (S-P) an additional amplification was incorporated before sequencing.

RESULTS

The SISPA method was the most effective and efficient method for non-targeted/random priming whole genome sequencing of SARS-CoV-2 that we tested. The SISPA method described in this study allowed for whole genome assembly of SARS-CoV-2 and influenza A(H1N1)pdm09 in mixed samples. We determined the limit of detection and characterization of SARS-CoV-2 virus which was 103 pfu/ml (Ct, 22.4) for whole genome assembly and 101 pfu/ml (Ct, 30) for metagenomics detection.

CONCLUSIONS

The SISPA method is predominantly useful for obtaining genome sequences from RNA viruses or investigating complex clinical samples as no prior sequence information is needed. It might be applied to monitor genomic virus changes, virus evolution and can be used for fast metagenomics detection or to assess the general picture of different pathogens within the sample.

SARS-CoV-2 Point Mutation and Deletion Spectra and Their Association with Different Disease Outcomes

Mutant spectra of RNA viruses are important to understand viral pathogenesis and response to selective pressures. There is a need to characterize the complexity of mutant spectra in coronaviruses sampled from infected patients. In particular, the possible relationship between SARS-CoV-2 mutant spectrum complexity and disease associations has not been established. In the present study, we report an ultradeep sequencing (UDS) analysis of the mutant spectrum of amplicons from the nsp12 (polymerase)- and spike (S)-coding regions of 30 nasopharyngeal isolates (diagnostic samples) of SARS-CoV-2 of the first COVID-19 pandemic wave (Madrid, Spain, April 2020) classified according to the severity of ensuing COVID-19. Low-frequency mutations and deletions, counted relative to the consensus sequence of the corresponding isolate, were overwhelmingly abundant. We show that the average number of different point mutations, mutations per haplotype, and several diversity indices was significantly higher in SARS-CoV-2 isolated from patients who developed mild disease than in those associated with moderate or severe disease (exitus). No such bias was observed with RNA deletions. Location of amino acid substitutions in the three-dimensional structures of nsp12 (polymerase) and S suggest significant structural or functional effects. Thus, patients who develop mild symptoms may be a richer source of genetic variants of SARS-CoV-2 than patients with moderate or severe COVID-19. IMPORTANCE The study shows that mutant spectra of SARS-CoV-2 from diagnostic samples differ in point mutation abundance and complexity and that significantly larger values were observed in virus from patients who developed mild COVID-19 symptoms. Mutant spectrum complexity is not a uniform trait among isolates. The nature and location of low-frequency amino acid substitutions present in mutant spectra anticipate great potential for phenotypic diversification of SARS-CoV-2.

Air pollution in five Indian megacities during the Christmas and New Year celebration amidst COVID-19 pandemic

Urban air quality and COVID-19 have been considered significant issues worldwide in the last few years. The current study highlighted the variation in air pollutants (i.e., PM2.5, PM10, NO2, and SO2) profile between Christmas and new year celebrations in 2019, 2020, and 2021. It can be seen that the concentration of selected air pollutants shows a substantially higher concentration in celebration periods in all reported years. The results indicate that air pollutants values are always higher than permissible limits. This observation indicates that people gather and reunite during Christmas and new year celebrations than the preceding years (2020 and 2021) amidst the pandemic. In the pandemic year, a higher margin enhanced the transportation and firework-induced air pollutant load in urban city Jodhpur, Rajasthan. In all states, a significant tendency was observed to retain the concentration profile of air pollutants in baseline concentration for almost more than one week after the celebration. This study addresses the pandemic situation, but it also dealt with the air pollutant parameter that brings down the sustainable quality of the environment due to the high usage of private vehicles, and crackers. In addition, a study on COVID-19 (cases and death rate) indicates a clear picture of the increasing trend after the event in probably all states. Thus, this approach suggested that stringent law enforcement is needed to ameliorate gatherings/reunions and pollution levels due to such events.

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.

Learning From Biological and Computational Machines: Importance of SARS-CoV-2 Genomic Surveillance, Mutations and Risk Stratification

The global coronavirus disease 2019 (COVID-19) pandemic has demonstrated the range of disease severity and pathogen genomic diversity emanating from a singular virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2). This diversity in disease manifestations and genomic mutations has challenged healthcare management and resource allocation during the pandemic, especially for countries such as India with a bigger population base. Here, we undertake a combinatorial approach toward scrutinizing the diagnostic and genomic diversity to extract meaningful information from the chaos of COVID-19 in the Indian context. Using methods of statistical correlation, machine learning (ML), and genomic sequencing on a clinically comprehensive patient dataset with corresponding with/without respiratory support samples, we highlight specific significant diagnostic parameters and ML models for assessing the risk of developing severe COVID-19. This information is further contextualized in the backdrop of SARS-CoV-2 genomic features in the cohort for pathogen genomic evolution monitoring. Analysis of the patient demographic features and symptoms revealed that age, breathlessness, and cough were significantly associated with severe disease; at the same time, we found no severe patient reporting absence of physical symptoms. Observing the trends in biochemical/biophysical diagnostic parameters, we noted that the respiratory rate, total leukocyte count (TLC), blood urea levels, and C-reactive protein (CRP) levels were directly correlated with the probability of developing severe disease. Out of five different ML algorithms tested to predict patient severity, the multi-layer perceptron-based model performed the best, with a receiver operating characteristic (ROC) score of 0.96 and an F1 score of 0.791. The SARS-CoV-2 genomic analysis highlighted a set of mutations with global frequency flips and future inculcation into variants of concern (VOCs) and variants of interest (VOIs), which can be further monitored and annotated for functional significance. In summary, our findings highlight the importance of SARS-CoV-2 genomic surveillance and statistical analysis of clinical data to develop a risk assessment ML model.

Geographical Landscape and Transmission Dynamics of SARS-CoV-2 Variants Across India: A Longitudinal Perspective

Globally, SARS-CoV-2 has moved from one tide to another with ebbs in between. Genomic surveillance has greatly aided the detection and tracking of the virus and the identification of the variants of concern (VOC). The knowledge and understanding from genomic surveillance is important for a populous country like India for public health and healthcare officials for advance planning. An integrative analysis of the publicly available datasets in GISAID from India reveals the differential distribution of clades, lineages, gender, and age over a year (Apr 2020–Mar 2021). The significant insights include the early evidence towards B.1.617 and B.1.1.7 lineages in the specific states of India. Pan-India longitudinal data highlighted that B.1.36* was the predominant clade in India until January–February 2021 after which it has gradually been replaced by the B.1.617.1 lineage, from December 2020 onward. Regional analysis of the spread of SARS-CoV-2 indicated that B.1.617.3 was first seen in India in the month of October in the state of Maharashtra, while the now most prevalent strain B.1.617.2 was first seen in Bihar and subsequently spread to the states of Maharashtra, Gujarat, and West Bengal. To enable a real time understanding of the transmission and evolution of the SARS-CoV-2 genomes, we built a transmission map available on https://covid19-indiana.soic.iupui.edu/India/EmergingLineages/April2020/to/March2021. Based on our analysis, the rate estimate for divergence in our dataset was 9.48 e-4 substitutions per site/year for SARS-CoV-2. This would enable pandemic preparedness with the addition of future sequencing data from India available in the public repositories for tracking and monitoring the VOCs and variants of interest (VOI). This would help aid decision making from the public health perspective.

Emergence of a novel SARS-CoV-2 Pango lineage B.1.1.526 in West Bengal, India

BACKGROUND

Since its inception in late 2019, SARS-CoV-2 has been evolving continuously by procuring mutations, leading to emergence of numerous variants, causing second wave of pandemic in many countries including India in 2021. To control this pandemic continuous mutational surveillance and genomic epidemiology of circulating strains is very important to unveil the emergence of the novel variants and also monitor the evolution of existing variants.

METHODS

SARS-CoV-2 sequences were retrieved from GISAID database. Sequence alignment was performed with MAFT version 7. Phylogenetic tree was constructed by using MEGA (version X) and UShER.

RESULTS

In this study, we reported the emergence of a novel variant of SARS-CoV-2, named B.1.1.526, in India. This novel variant encompasses 129 SARS-CoV-2 strains which are characterized by the presence of 11 coexisting mutations including D614G, P681H, and V1230L in S glycoprotein. Out of these 129 sequences, 27 sequences also harbored E484K mutation in S glycoprotein. Phylogenetic analysis revealed strains of this novel variant emerged from the GR clade and formed a new cluster. Geographical distribution showed, out of 129 sequences, 126 were found in seven different states of India. Rest 3 sequences were observed in USA. Temporal analysis revealed this novel variant was first collected from Kolkata district of West Bengal, India.

CONCLUSIONS

The D614G, P618H and E484K mutations have previously been reported to favor increased transmissibility, enhanced infectivity, and immune invasion, respectively. The transmembrane domain (TM) of S2 subunit anchors S glycoprotein to the virus envelope. The V1230L mutation, present within the TM domain of S glycoprotein, might strengthen the interaction of S glycoprotein with the viral envelope and increase S glycoprotein deposition to the virion, resulting in more infectious virion. Therefore, the new variant having D614G, P618H, V1230L, and E484K may have higher infectivity, transmissibility, and immune invasion characteristics, and thus need to be monitored closely.

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.

Molecular Evolution of Severe Acute Respiratory Syndrome Coronavirus 2: Hazardous and More Hazardous Strains Behind the Coronavirus Disease 2019 Pandemic and Their Targeting by Drugs and Vaccines

Within almost the last 2 years, the world has been shaken by the coronavirus disease 2019 (COVID-19) pandemic, which has affected the lives of all people. With nearly 4.92 million deaths by October 19, 2021, and serious health damages in millions of people, COVID-19 has been the most serious global challenge after the Second World War. Besides lost lives and long-term health problems, devastating impact on economics, education, and culture will probably leave a lasting impression on the future. Therefore, the actual extent of losses will become obvious only after years. Moreover, despite the availability of different vaccines and vaccination programs, it is still impossible to forecast what the next steps of the virus are or how near we are to the end of the pandemic. In this article, the route of molecular evolution of the coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is thoroughly compiled, highlighting the changes that the virus has undergone during the last 2 years and discussing the approaches that the medical community has undertaken in the fight against virus-induced damages.

Circulation and Evolution of SARS-CoV-2 in India: Let the Data Speak

The COVID-19 pandemic is a global challenge that impacted 200+ countries. India ranks in the second and third positions in terms of number of reported cases and deaths. Being a populous country with densely packed cities, SARS-CoV-2 spread exponentially. India sequenced ≈0.14% isolates from confirmed cases for pandemic surveillance and contributed ≈1.58% of complete genomes sequenced globally. This study was designed to map the circulating lineage diversity and to understand the evolution of SARS-CoV-2 in India using comparative genomics and population genetics approaches. Despite varied sequencing coverage across Indian States and Union Territories, isolates belonging to variants of concern (VoC) and variants of interest (VoI) circulated, persisted, and diversified during the first seventeen months of the pandemic. Delta and Kappa lineages emerged in India and spread globally. The phylogenetic tree shows lineage-wise monophyletic clusters of VoCs/VoIs and diversified tree topologies for non-VoC/VoI lineages designated as 'Others' in this study. Evolutionary dynamics analyses substantiate a lack of spatio-temporal clustering, which is indicative of multiple global and local introductions. Sites under positive selection and significant variations in spike protein corroborate with the constellation of mutations to be monitored for VoC/VoI as well as substitutions that are characteristic of functions with implications in virus-host interactions, differential glycosylation, immune evasion, and escape from neutralization.

Molecular Analysis and Genome Sequencing of SARS-CoV-2 during Second Wave 2021 Revealed Variant Diversity in India

SARS-CoV-2 variants rapid emergence has posed critical challenge of higher transmission and immune escape causing serious threats to control the pandemic. The present study was carried out in confirmed cases of SARS-CoV-2 patients to elucidate the prevalence of SARS-CoV-2 variant strain. We performed RT-PCR using extracted RNA from the nasopharyngeal swabs of suspected Covid-19 patients. Confirmed positive cases with CT<25 were subjected to whole-genome sequencing to track the prevalence of the virus in the Malwa region of Punjab. The presence of B.1, B.1.1.7, B.1.351, B.1.617.1, B.1.617.2, AY.1 and other unidentified variants of SARS-CoV-2 was found in the studied population. Among all the variants, B.1.1.7 (UK variant) and B.1.617.2 (delta-Indian variant) was found to be the most dominant variant in the population and was found majorly in Patiala followed by Ludhiana, SBS Nagar, Mansa and Sangrur. In addition to this, sequencing results also observed that the dominant trait was more prevalent in male population and age group 21-40 years. The B.1.1.7 and B.1.617.2 variant of SARS-CoV-2 is replacing the wild type (Wuhan Strain) and emerging as the dominant variant in Punjab.

The D614G Virus Mutation Enhances Anosmia in COVID-19 Patients: Evidence from a Systematic Review and Meta-analysis of Studies from South Asia

The prevalence of chemosensory dysfunction in patients with COVID-19 varies greatly between populations. It is unclear whether such differences are due to factors at the level of the human host, or at the level of the coronavirus, or both. At the host level, the entry proteins which allow virus binding and entry have variants with distinct properties, and the frequency of such variants differs between ethnicities. At the level of the virus, the D614G mutation enhances virus entry to the host cell. Since the two virus strains (D614 and G614) coexisted in the first six months of the pandemic in most populations, it has been difficult to distinguish between contributions of the virus and contributions of the host for anosmia. To answer this question, we conducted a systematic review and meta-analysis of studies in South Asian populations when either the D614 or the G614 virus was dominant. We show that populations infected predominantly with the G614 virus had a much higher prevalence of anosmia (pooled prevalence of 31.8%) compared with the same ethnic populations infected mostly with the D614 virus strain (pooled anosmia prevalence of 5.3%). We conclude that the D614G mutation is a major contributing factor that increases the prevalence of anosmia in COVID-19, and that this enhanced effect on olfaction constitutes a previously unrecognized phenotype of the D614G mutation. The new virus strains that have additional mutations on the background of the D614G mutation can be expected to cause a similarly increased prevalence of chemosensory dysfunctions.

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.

An Overview of COVID-19 and the Potential Plant Harboured Secondary Metabolites against SARS-CoV-2: A Review

The SARS-CoV-2 virus causes COVID-19, a pandemic disease, and it is called the novel coronavirus. It belongs to the Coronaviridae family and has been plagued the world since the end of 2019. Viral infection to the lungs causes fluid filling and breathing difficulties, which leads to pneumonia. Pneumonia progresses to ARDS (Acute Respiratory Distress Syndrome), in which fluid fills the air sac and seeps from the pulmonary veins. In the current scenario, several vaccines have been used to control the pandemic worldwide. Even though vaccines are available and their effectiveness is short, it may be helpful to curb the pandemic, but long-term protection is inevitable when we look for other options. Plants have diversified components such as primary and secondary metabolites. These molecules show several activities such as anti-microbial, anti-cancer, anti-helminthic. In addition, these molecules have good binding ability to the SARS-CoV-2 virus proteins such as RdRp (RNA-dependent RNA polymerase), Mpro (Main Protease), etc. Therefore, these herbal molecules could probably be used to control the COVID-19. However, pre-requisite tests, such as cytotoxicity, in vivo, and human experimental studies, are required before plant molecules can be used as potent drugs. Plant metabolites such as alkaloids, isoquinoline ß-carboline, and quinoline alkaloids such as skimmianine, quinine, cinchonine, and dictamine are present in plants and used in a traditional medicinal system.

Evolutionary trajectory of SARS-CoV-2 and emerging variants

The emergence of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and more recently, the independent evolution of multiple SARS-CoV-2 variants has generated renewed interest in virus evolution and cross-species transmission. While all known human coronaviruses (HCoVs) are speculated to have originated in animals, very little is known about their evolutionary history and factors that enable some CoVs to co-exist with humans as low pathogenic and endemic infections (HCoV-229E, HCoV-NL63, HCoV-OC43, HCoV-HKU1), while others, such as SARS-CoV, MERS-CoV and SARS-CoV-2 have evolved to cause severe disease. In this review, we highlight the origins of all known HCoVs and map positively selected for mutations within HCoV proteins to discuss the evolutionary trajectory of SARS-CoV-2. Furthermore, we discuss emerging mutations within SARS-CoV-2 and variants of concern (VOC), along with highlighting the demonstrated or speculated impact of these mutations on virus transmission, pathogenicity, and neutralization by natural or vaccine-mediated immunity.

Genomic Surveillance and Phylodynamic Analyses Reveal the Emergence of Novel Mutations and Co-mutation Patterns Within SARS-CoV-2 Variants Prevalent in India

Identification of the genomic diversity and the phylodynamic profiles of prevalent variants is critical to understand the evolution and spread of SARS-CoV-2 variants. We performed whole-genome sequencing of 54 SARS-CoV-2 variants collected from COVID-19 patients in Kolkata, West Bengal during August-October 2020. Phylogeographic and phylodynamic analyses were performed using these 54 and other sequences from India and abroad that are available in the GISAID database. We estimated the clade dynamics of the Indian variants and compared the clade-specific mutations and the co-mutation patterns across states and union territories of India over the time course. Frequent mutations and co-mutations observed within the major clades across time periods do not show much overlap, indicating the emergence of newer mutations in the viral population prevailing in the country. Furthermore, we explored the possible association of specific mutations and co-mutations with the infection outcomes manifested in Indian patients.

SARS-CoV-2 Spike Mutations, L452R, T478K, E484Q and P681R, in the Second Wave of COVID-19 in Maharashtra, India

As the global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic expands, genomic epidemiology and whole genome sequencing are being used to investigate its transmission and evolution. Against the backdrop of the global emergence of "variants of concern" (VOCs) during December 2020 and an upsurge in a state in the western part of India since January 2021, whole genome sequencing and analysis of spike protein mutations using sequence and structural approaches were undertaken to identify possible new variants and gauge the fitness of the current circulating strains. Phylogenetic analysis revealed that newly identified lineages B.1.617.1 and B.1.617.2 were predominantly circulating. The signature mutations possessed by these strains were L452R, T478K, E484Q, D614G and P681R in the spike protein, including within the receptor-binding domain (RBD). Of these, the mutations at residue positions 452, 484 and 681 have been reported in other globally circulating lineages. The structural analysis of RBD mutations L452R, T478K and E484Q revealed that these may possibly result in increased ACE2 binding while P681R in the furin cleavage site could increase the rate of S1-S2 cleavage, resulting in better transmissibility. The two RBD mutations, L452R and E484Q, indicated decreased binding to select monoclonal antibodies (mAbs) and may affect their neutralization potential. Further in vitro/in vivo studies would help confirm the phenotypic changes of the mutant strains. Overall, the study revealed that the newly emerged variants were responsible for the second wave of COVID-19 in Maharashtra. Lineage B.1.617.2 has been designated as a VOC delta and B.1.617.1 as a variant of interest kappa, and they are being widely reported in the rest of the country as well as globally. Continuous monitoring of these and emerging variants in India is essential.

SARS-CoV-2 presented moderately during two episodes of the infection with lack of antibody responses

The world has gone through the critical phase of SARS-CoV-2 crisis caused by the new variants of the virus. The globally concerted effort to characterize viral genomic mutations across different clades has revealed several changes in the coding and also non-coding regions which might lead to a violent presentation or re-infection occurrence. Here, we studied a COVID-19 subject who represented the symptoms following the full recovery of the first infection. COVID-19 specific IgM and IgG were evaluated in both steps. The viral samples from oropharyngeal/nasopharyngeal were subjected to RT-PCR and full sequencing was done in both incidences. The sequencing data was fully investigated with the reference sequence of SARS-CoV-2 and the changes were detected. The obtained data is in favor of re-infection with 128 days of interval. SARS-CoV-2 presented more severely in the second episode of the disease and the specific antibodies against COVID-19 were not detectable. Both infections were caused by the same clade 20G, however, the mutation rates were higher in the second incidence including 10 nucleotide substitutions which had rarely been reported before. In the present study, the nucleotide mutations in various regions of the viral genome have been presented. The re-infection could have significant effect on clinical implications as well as vaccination.

Co-mutation modules capture the evolution and transmission patterns of SARS-CoV-2

The rapid spread and huge impact of the COVID-19 pandemic caused by the emerging SARS-CoV-2 have driven large efforts for sequencing and analyzing the viral genomes. Mutation analyses have revealed that the virus keeps mutating and shows a certain degree of genetic diversity, which could result in the alteration of its infectivity and pathogenicity. Therefore, appropriate delineation of SARS-CoV-2 genetic variants enables us to understand its evolution and transmission patterns. By focusing on the nucleotides that co-substituted, we first identified 42 co-mutation modules that consist of at least two co-substituted nucleotides during the SARS-CoV-2 evolution. Then based on these co-mutation modules, we classified the SARS-CoV-2 population into 43 groups and further identified the phylogenetic relationships among groups based on the number of inconsistent co-mutation modules, which were validated with phylogenetic trees. Intuitively, we tracked tempo-spatial patterns of the 43 groups, of which 11 groups were geographic-specific. Different epidemic periods showed specific co-circulating groups, where the dominant groups existed and had multiple sub-groups of parallel evolution. Our work enables us to capture the evolution and transmission patterns of SARS-CoV-2, which can contribute to guiding the prevention and control of the COVID-19 pandemic. An interactive website for grouping SARS-CoV-2 genomes and visualizing the spatio-temporal distribution of groups is available at https://www.jianglab.tech/cmm-grouping/.

Tackling COVID-19 with neutralizing monoclonal antibodies

Monoclonal antibodies (mAbs) have revolutionized the treatment of several human diseases, including cancer and autoimmunity and inflammatory conditions, and represent a new frontier for the treatment of infectious diseases. In the last 20 years, innovative methods have allowed the rapid isolation of mAbs from convalescent subjects, humanized mice, or libraries assembled in vitro and have proven that mAbs can be effective countermeasures against emerging pathogens. During the past year, an unprecedentedly large number of mAbs have been developed to fight coronavirus disease 2019 (COVID-19). Lessons learned from this pandemic will pave the way for the development of more mAb-based therapeutics for other infectious diseases. Here, we provide an overview of SARS-CoV-2-neutralizing mAbs, including their origin, specificity, structure, antiviral and immunological mechanisms of action, and resistance to circulating variants, as well as a snapshot of the clinical trials of approved or late-stage mAb therapeutics.

Characterization of SARS-CoV-2 different variants and related morbidity and mortality: a systematic review

INTRODUCTION

Coronavirus Disease-2019 (SARS-CoV-2) started its devastating trajectory into a global pandemic in Wuhan, China, in December 2019. Ever since, several variants of SARS-CoV-2 have been identified. In the present review, we aimed to characterize the different variants of SARS-CoV-2 and explore the related morbidity and mortality.

METHODS

A systematic review including the current evidence related to different variants of SARS-CoV-2 and the related morbidity and mortality was conducted through a systematic search utilizing the keywords in the online databases including Scopus, PubMed, Web of Science, and Science Direct; we retrieved all related papers and reports published in English from December 2019 to September 2020.

RESULTS

A review of identified articles has shown three main genomic variants, including type A, type B, and type C. we also identified three clades including S, V, and G. Studies have demonstrated that the C14408T and A23403G alterations in the Nsp12 and S proteins are the most prominent alterations in the world, leading to life-threatening mutations.The spike D614G amino acid change has become the most common variant since December 2019. From missense mutations found from Gujarat SARS-CoV-2 genomes, C28854T, deleterious mutation in the nucleocapsid (N) gene was significantly associated with patients' mortality. The other significant deleterious variant (G25563T) is found in patients located in Orf3a and has a potential role in viral pathogenesis.

CONCLUSION

Overall, researchers identified several SARS-CoV-2 variants changing clinical manifestations and increasing the transmissibility, morbidity, and mortality of COVID-19. This should be considered in current practice and interventions to combat the pandemic and prevent related morbidity and mortality.

Respiratory Co-Infections: Modulators of SARS-CoV-2 Patients' Clinical Sub-Phenotype

Co-infection with ancillary pathogens is a significant modulator of morbidity and mortality in infectious diseases. There have been limited reports of co-infections accompanying SARS-CoV-2 infections, albeit lacking India specific study. The present study has made an effort toward elucidating the prevalence, diversity and characterization of co-infecting respiratory pathogens in the nasopharyngeal tract of SARS-CoV-2 positive patients. Two complementary metagenomics based sequencing approaches, Respiratory Virus Oligo Panel (RVOP) and Holo-seq, were utilized for unbiased detection of co-infecting viruses and bacteria. The limited SARS-CoV-2 clade diversity along with differential clinical phenotype seems to be partially explained by the observed spectrum of co-infections. We found a total of 43 bacteria and 29 viruses amongst the patients, with 18 viruses commonly captured by both the approaches. In addition to SARS-CoV-2, Human Mastadenovirus, known to cause respiratory distress, was present in a majority of the samples. We also found significant differences of bacterial reads based on clinical phenotype. Of all the bacterial species identified, ∼60% have been known to be involved in respiratory distress. Among the co-pathogens present in our sample cohort, anaerobic bacteria accounted for a preponderance of bacterial diversity with possible role in respiratory distress. Clostridium botulinum, Bacillus cereus and Halomonas sp. are anaerobes found abundantly across the samples. Our findings highlight the significance of metagenomics based diagnosis and detection of SARS-CoV-2 and other respiratory co-infections in the current pandemic to enable efficient treatment administration and better clinical management. To our knowledge this is the first study from India with a focus on the role of co-infections in SARS-CoV-2 clinical sub-phenotype.

Pharmacological Modulators of Autophagy as a Potential Strategy for the Treatment of COVID-19

The family of coronaviruses (CoVs) uses the autophagy machinery of host cells to promote their growth and replication; thus, this process stands out as a potential target to combat COVID-19. Considering the different roles of autophagy during viral infection, including SARS-CoV-2 infection, in this review, we discuss several clinically used drugs that have effects at different stages of autophagy. Among them, we mention (1) lysosomotropic agents, which can prevent CoVs infection by alkalinizing the acid pH in the endolysosomal system, such as chloroquine and hydroxychloroquine, azithromycin, artemisinins, two-pore channel modulators and imatinib; (2) protease inhibitors that can inhibit the proteolytic cleavage of the spike CoVs protein, which is necessary for viral entry into host cells, such as camostat mesylate, lopinavir, umifenovir and teicoplanin and (3) modulators of PI3K/AKT/mTOR signaling pathways, such as rapamycin, heparin, glucocorticoids, angiotensin-converting enzyme inhibitors (IECAs) and cannabidiol. Thus, this review aims to highlight and discuss autophagy-related drugs for COVID-19, from in vitro to in vivo studies. We identified specific compounds that may modulate autophagy and exhibit antiviral properties. We hope that research initiatives and efforts will identify novel or "off-label" drugs that can be used to effectively treat patients infected with SARS-CoV-2, reducing the risk of mortality.