SARS-CoV-2 genomic variations associated with mortality rate of COVID-19

Molecular/antigenic mimicry and immunological cross-reactivity explains SARS-CoV-2-induced autoimmunity

COVID-19 pandemic is over, but its effects on chronic illnesses remain a challenging issue. Understanding the influence of SARS-COV-2-mediated autoimmunity and overt autoimmune disease is of paramount importance, as it can provide a critical mass of information regarding both infection-mediated (and vaccination-induced) autoimmune phenomena in susceptible individuals during the disease course, and short or long-term post-disease sequelae. The high prevalence of organ and non-organ specific autoantibody positivity in patients with COVID-19 led to studies attempting to delineate the origin and the underlying mechanism responsible for their induction nature, identifying novel autoantigens, and the self-epitope sequences which could be the impetus for the initiating autoreactive responses. Herein, we provide a meticulous review of the studies reporting those mimicking sequences that have been experimentally validated, based on the assumption that molecular mimicry and immunological crossreactivity may account for autoantibody development. Most reports are based on bioinformatics approaches, and only a disproportionally small number of studies currently demonstrate immunological crossreactivity. We took the opportunity to further review and searched for the linear human epitope sequences of human, through the epitopes deposited at the Immune Epitope Database. This included an analysis of autoimmune disease as the disease data to comprehensively understand the subject matter. The critical overview of the findings underscore the urgent and immense need for further research to gain a comprehensive understanding of the mechanisms involved and the anticipated appraisal that molecular mimicry and immunological crossreactivity is indeed central to the loss of immunological tolerance during SARS-COV-2 infection.

In Silico and In Vitro development of novel small interfering RNAs (siRNAs) to inhibit SARS-CoV-2

SARS-CoV-2 is causing severe to moderate respiratory tract infections, posing global health, social life, and economic threats. Our design strategy for siRNAs differs from existing studies through a step-by-step filtration process utilizing integrative bioinformatics protocols and web tools. Stage one: Multiple Sequence Alignment was employed to identify the most conserved areas. Stage two involves using various online tools, among the most reputable tools for building siRNA. The first filtration step of siRNA uses the Huesken dataset, estimating a 90 % experimental inhibition. The second filtration stage involves choosing the most suitable and targeted siRNA by utilizing thermodynamics and Target Accessibility of siRNAs. The final filtration step is off-target filtration using BLAST with specific parameters. Four of the 258 siRNAs were chosen for their potency and specificity, targeting conserved regions (NSP8, NSP12, and NSP14) with minimal human transcripts off-targets. We conducted in-vitro experiments, including cytotoxicity, TCID50, and RT-PCR assays. When tested on the SARS-CoV-2 strain hCoV-19/Egypt/NRC-03/2020 at 100 nM, none showed cellular toxicity. The TCID50 assay confirmed viral replication reduction at 12 h.p.i; the efficacy of the four siRNAs and their P value were highly significant. siRNA2 maintaining efficacy at 24, 36, and 48 h.p.i, while siRNA4 had a significant P value (≤0.0001) at 48 h.p.i. At 24 h.p.i, siRNA2 and siRNA4 showed statistical significance in viral knockdown of the virus's S gene and ORF1b gene by 95 %, 89 %, and 96 %, 97 %, respectively. Our computational method and experimental assessment of specific siRNAs have led us to conclude that siRNA2 and siRNA4 could be promising new therapies for SARS-CoV-2 that need further development.

Exploring the Relationship Between Humoral and Cellular T Cell Responses Against SARS-CoV-2 in Exposed Individuals From Emilia Romagna Region and COVID-19 Severity

COVID-19 remains a significant global health problem with uncertain long-term consequences for convalescents. We investigated the relationships between anti-N protein antibody levels, severe acute respiratory syndrome (SARS)-CoV-2-associated TCR repertoire parameters, HLA type and epidemiological information from three cohorts of 524 SARS-CoV-2-infected subjects subgrouped in acute phase, seronegative and seropositive convalescents from the Emilia Romagna region. Epidemiological information and anti-N antibody index were associated with TCR repertoire data. HLA type was inferred from TCR repertoire using the HLA3 tool and its association with clonal breadth (CB) and clonal depth (CD) was assessed. Age above 58 years, male and COVID-19 hospitalisation were significantly and independently associated with seropositivity (p = 0.004; p = 0.004; p = 0.04), suggesting an association between high antibody titres and symptoms' severity. As for the TCR repertoire analysis, we found no difference in CB among the cohorts, while CD was higher in seronegative than acute (p = 0.04). However, clustering analysis supported that seronegative patients are endowed with broader CB and deeper CD indicating a compensatory mechanism without effective seroconversion. The CD calculated on the TCRs associated with the single SARS-CoV-2 ORFs in convalescents is higher when compared to the acute. Lastly, we identified and reported on novel HLAs significantly associated with increased risk of hospitalisation such as HLA-C*07:02 carriers (OR = 3.9, CI = 1.1-13.4, p = 0.03) and on HLAs that associate significantly with lower or higher TCR repertoire parameters in a population exposed for the first time to SARS-CoV-2.

Associations Between Clinical Manifestations of SARS-CoV-2 Infection and HLA Alleles in a Caucasian Population: A Molecular HLA Typing Study

Background and Objectives: Severe COVID-19 still constitutes an important health problem. Taking into account the crucial role of HLA in immune reactions, evaluation of the impact of HLA on COVID-19 risk and clinical course seemed necessary, as the already available data are inconsistent. The aim of the present study was to compare the HLA profiles of patients with symptomatic SARS-CoV-2 infection and a healthy control group, as well as to compare HLA allele frequencies in patients with severe and non-severe courses of COVID-19. Materials and Methods: HLA classes were genotyped using a next-generation sequencing method in 2322 persons, including 2217 healthy hematopoietic stem cell potential donors and 105 patients with symptomatic COVID-19. Results: Symptomatic course of SARS-CoV-2 infection appeared to be associated with the presence of HLA-A*30:01, B*44:02, B*52:01, C*05:01, C*17:01, and DRB1*11:02, while HLA-C*07:04 and DQB1*03:03 seem to play a protective role. Moreover, we demonstrated that the severe symptomatic course of COVID-19 can be associated with the presence of HLA-B*08:01, C*04:01, DRB1*03:01, and DQB1*03:01, while HLA-DRB1*08:01 appeared to be protective against severe COVID-19 disease. Conclusions: Identification of alleles that are potentially associated with symptomatic SARS-CoV-2 infection as well as the severe course of COVID-19 broadens the knowledge on the genetic background of COVID-19 course and can constitute an important step in the development of personalized medicine.

Genomic Surveillance and Molecular Characterization of SARS-CoV-2 Variants During the Peak of the Pandemic in Türkiye

SARS-CoV-2 is a highly transmissible coronavirus and has caused a pandemic of acute respiratory disease. Genomic characterization of SARS-CoV-2 is important for monitoring and assessing its evolution. A total of 1.346 nasopharyngeal swab samples were collected but only 879 SARS-CoV-2 high-quality genomes were isolated, subjected to Next Generation Sequencing and analyzed both statistically and regarding mutations comprehensively. The distribution of clades and lineages in different cities of Türkiye and the association of SARS-CoV-2 variants with age groups and clinical characteristics of COVID-19 were also examined. Furthermore, the frequency of the clades and lineages was observed in 10 months. Finally, non-synonymous mutations not defined in specific SARS-CoV-2 variants (during that period) were identified by performing mutation analysis. B.1.1.7 (Alpha) and B.1.617.2 (Delta) SARS-CoV-2 variants which have also been identified in our study from March to December 2021. We observed a significant association of SARS-CoV-2 variants with age groups and cities. Also, E:T9I, S:A27S, S:A67V, S:D796Y, S:K417N, S:N440K, S:R158X, S:S477N (below 1%-frequency) were determined as specific mutations belonging and shared with the Omicron variant that appeared later. Our study has highlighted the importance of constant monitoring of the genetic diversity of SARS-CoV-2 to provide better prevention strategies and it contributes to the understanding of SARS-CoV-2 from the past to the present.

Stimulator of interferon genes (STING) inhibits coronavirus infection by disrupting viral replication organelles

Stimulator of interferon genes (STING) is an endoplasmic reticulum (ER) protein that plays a crucial role in cytosolic DNA-mediated innate immunity. Both STING agonists and antagonists have demonstrated their ability to enhance mouse survival against coronavirus, however, the physiological role of endogenous STING in coronavirus infection remains unclear. Our research unveils that STING inhibits coronavirus replication by impeding the formation of the ER-derived double-membrane vesicles (DMVs), the organelles in which coronavirus replicates. We found that STING was still capable of inhibiting coronavirus OC43 infection in cells, regardless of the knockout of cGAS or MAVS, or blocking type I interferon receptor. Moreover, STING disrupted the interaction between two crucial proteins, NSP4 and NSP6, involved in DMV formation, leading to the disruption of DMV formation. Taken together, our study sheds light on a novel antiviral role of STING in coronavirus infection, elucidating how it disrupts the formation of viral replication organelles, thereby impeding the replication process.

Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family

PURPOSE

In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is achieved through a deep neural network model that relies on convolutional neural networks (CNNs). Since viruses within the same family share similar genetic and structural characteristics, the classification process becomes more challenging, necessitating more robust models. With the rapid evolution of viral genomes and the increasing need for timely classification, we aimed to provide a robust and efficient tool that could increase the accuracy of viral identification and classification processes. Contribute to advancing research in viral genomics and assist in surveilling emerging viral strains.

METHODS

Based on a one-dimensional deep CNN, the proposed tool is capable of training and testing on the Coronaviridae family, including SARS-CoV-2. Our model's performance was assessed using various metrics, including F1-score and AUROC. Additionally, artificial mutation tests were conducted to evaluate the model's generalization ability across sequence variations. We also used the BLAST algorithm and conducted comprehensive processing time analyses for comparison.

RESULTS

DeepVirusClassifier demonstrated exceptional performance across several evaluation metrics in the training and testing phases. Indicating its robust learning capacity. Notably, during testing on more than 10,000 viral sequences, the model exhibited a more than 99% sensitivity for sequences with fewer than 2000 mutations. The tool achieves superior accuracy and significantly reduced processing times compared to the Basic Local Alignment Search Tool algorithm. Furthermore, the results appear more reliable than the work discussed in the text, indicating that the tool has great potential to revolutionize viral genomic research.

CONCLUSION

DeepVirusClassifier is a powerful tool for accurately classifying viral sequences, specifically focusing on SARS-CoV-2 and other subtypes within the Coronaviridae family. The superiority of our model becomes evident through rigorous evaluation and comparison with existing methods. Introducing artificial mutations into the sequences demonstrates the tool's ability to identify variations and significantly contributes to viral classification and genomic research. As viral surveillance becomes increasingly critical, our model holds promise in aiding rapid and accurate identification of emerging viral strains.

Stability of Neutralizing Antibody of PastoCoAd Vaccine Candidates against a Variant of Concern of SARS-CoV-2 in Animal Models

Background

Since the beginning of the SARS-CoV-2 pandemic, there have been mutations caused by new SARS-CoV-2 variants, such as Alpha, Beta, Gamma, Delta, and Omicron, recognized as the variants of concern (VOC) worldwide. These variants can affect vaccine efficacy, disease control, and treatment effectiveness. The present study aimed to evaluate the levels of total and neutralizing antibodies produced by PastoCoAd vaccine candidates against the VOC strains at different time points.

Methods

Two vaccine candidates were employed against SARS-CoV-2 using adenoviral vectors: prime only (a mixture of rAd5-S and rAd5 RBD-N) and heterologous prime-boost (rAd5-S/SOBERANA vaccine). The immunogenicity of these vaccine candidates was assessed in mouse, rabbit, and hamster models using ELISA assay and virus neutralization antibody test.

Results

The immunogenicity results indicated a significant increase in both total and neutralizing antibodies titers in the groups receiving the vaccine candidates at various time points compared to the control group (p < 0.05). The results also showed that the PastoCoAd vaccine candidates Ad5 S & RBD-N and Ad5 S/SOBERANA could neutralize the VOC strains in the animal models.

Conclusion

The ability of vaccine candidate to neutralize the VOC strains in animal models by generating neutralizing antibodies at different time points may be attributed to the use of the platform based on the Adenoviral vector, the N proteins in the Ad5 S & RBD-N vaccine candidate, and the SOBERANA Plus booster in the Ad5 S/SOBERANA vaccine candidate.

HLA-B and C Expression Contributes to COVID-19 Disease Severity within a South African Cohort

Globally, SARS-CoV-2 has negatively impacted many lives and industries due to its rapid spread, severe outcomes, and the need for the implementation of lockdown strategies across the world. SARS-CoV-2 disease severity varies among different populations. Host genetics have been associated with various diseases, and their ability to alter disease susceptibility and severity. In addition, Human Leukocyte Antigen (HLA) expression levels and alleles vary significantly among ethnic groups, which might impact the host's response to SARS-CoV-2. Our previous study highlighted that HLA-A might have an effect on COVID-19 disease severity across ethnicities. Therefore, in this study, we aim to examine the effect of HLA-B and C expression levels on COVID-19 disease severity. To achieve this, we used real-time PCR to measure the HLA mRNA expression levels of SARS-CoV-2-infected individuals from a South African cohort and compared them across ethnic groups, disease outcomes, gender, comorbidities, and age. Our results show (1) that the effect of HLA-B mRNA expression levels was associated with differences in disease severity when we compare symptomatic vs. asymptomatic (p < 0.0001). While HLA-C mRNA expression levels were not associated with COVID-19 disease severity. (2) In addition, we observed that HLA-B and HLA-C mRNA expression levels were significantly different between South African Black individuals and South African Indian individuals (p < 0.0001, p < 0.0001). HLA-B mRNA expression levels among symptomatic South African Black individuals were significantly higher than symptomatic South African Indian individuals (p < 0.0001). In addition, the HLA-B mRNA expression levels of symptomatic South African Black individuals were significantly higher than asymptomatic South African Black individuals (p > 0.0001). HLA-C mRNA expression levels among symptomatic South African Black individuals were significantly higher than among symptomatic South African Indian individuals (p = 0.0217). (3) HLA-C expression levels were significantly different between males and females (p = 0.0052). In addition, the HLA-C expression levels of asymptomatic males are higher than asymptomatic females (p = 0.0375). (4) HLA-B expression levels were significantly different between individuals with and without comorbidities (p = 0.0009). In addition, we observed a significant difference between individuals with no comorbidities and non-communicable diseases (p = 0.0034), in particular, hypertension (p = 0.0487). (5) HLA-B expression levels were significantly different between individuals between 26-35 and 56-65 years (p = 0.0380). Our work is expected to strengthen the understanding of the relationship between HLA and COVID-19 by providing insights into HLA-B and C expression levels across ethnic populations in South Africa among COVID-19-symptomatic and asymptomatic individuals. Our results highlight that HLA-B mRNA expression levels contribute to COVID-19 severity as well as variation in ethnicities associated with COVID-19. Further studies are needed to examine the effect of HLA expression levels across various ethnic groups with contributing factors.

Narrative Review Explaining the Role of HLA-A, -B, and -C Molecules in COVID-19 Disease in and around Africa

The coronavirus disease 2019 (COVID-19) has left a devasting effect on various regions globally. Africa has exceptionally high rates of other infectious diseases, such as tuberculosis (TB), human immunodeficiency virus (HIV), and malaria, and was not impacted by COVID-19 to the extent of other continents Globally, COVID-19 has caused approximately 7 million deaths and 700 million infections thus far. COVID-19 disease severity and susceptibility vary among individuals and populations, which could be attributed to various factors, including the viral strain, host genetics, environment, lifespan, and co-existing conditions. Host genetics play a substantial part in COVID-19 disease severity among individuals. Human leukocyte antigen (HLA) was previously been shown to be very important across host immune responses against viruses. HLA has been a widely studied gene region for various disease associations that have been identified. HLA proteins present peptides to the cytotoxic lymphocytes, which causes an immune response to kill infected cells. The HLA molecule serves as the central region for infectious disease association; therefore, we expect HLA disease association with COVID-19. Therefore, in this narrative review, we look at the HLA gene region, particularly, HLA class I, to understand its role in COVID-19 disease.

Evaluation the frequencies of HLA alleles in moderate and severe COVID-19 patients in Iran: A molecular HLA typing study

Background

Severe acute respiratory syndrome coronavirus 2 was first reported in December 2019 and it has spread globally ever since. The HLA system is crucial in directing anti-viral immunity and recent studies are investigating the possible involvement of the HLA genes on the severity of immune inflammation in different phases of COVID-19.

Methods

In this cross-sectional study, peripheral blood-extracted genomic DNAs of 109 COVID-19 patients and 70 healthy controls were genotyped for different alleles of HLA-A, HLA-B, and HLA-DRB1 loci using sequence-specific primer PCR method.

Results

The results indicated that frequencies of HLA-DRB1*11:01 and HLA-DRB1*04:03 were significantly higher in severe patients rather than moderates (p: <0.001 and 0.004, respectively). Also, it was observed that HLA-DRB1*04:01 was more frequent in moderate patients and healthy controls (p:0.002). In addition, HLA-B*07:35, and HLA-DRB1*07:01 showed higher frequencies in patients compared with controls (p: 0.031 and 0.003 respectively). Inversely, due to the higher frequencies of HLA-B*51:01 (p:0.027), HLA-DRB1*11:05 (p:0.003), HLA-DRB1*13:05 (p:0.022), and HLA-DRB1*14:01 (p:0.006) in healthy individuals rather than patients, they may be associated with COVID-19 resistance.

Conclusion

The results show that, based on the population differences, the type of alleles related to the severity of COVID-19 is different, which should be clarified by designing large-scale studies in order to develop HLA-based treatments and vaccines.

Unraveling the genetic variations underlying virulence disparities among SARS-CoV-2 strains across global regions: insights from Pakistan

Over the course of the COVID-19 pandemic, several SARS-CoV-2 variants have emerged that may exhibit different etiological effects such as enhanced transmissibility and infectivity. However, genetic variations that reduce virulence and deteriorate viral fitness have not yet been thoroughly investigated. The present study sought to evaluate the effects of viral genetic makeup on COVID-19 epidemiology in Pakistan, where the infectivity and mortality rate was comparatively lower than other countries during the first pandemic wave. For this purpose, we focused on the comparative analyses of 7096 amino-acid long polyprotein pp1ab. Comparative sequence analysis of 203 SARS-CoV-2 genomes, sampled from Pakistan during the first wave of the pandemic revealed 179 amino acid substitutions in pp1ab. Within this set, 38 substitutions were identified within the Nsp3 region of the pp1ab polyprotein. Structural and biophysical analysis of proteins revealed that amino acid variations within Nsp3's macrodomains induced conformational changes and modified protein-ligand interactions, consequently diminishing the virulence and fitness of SARS-CoV-2. Additionally, the epistatic effects resulting from evolutionary substitutions in SARS-CoV-2 proteins may have unnoticed implications for reducing disease burden. In light of these findings, further characterization of such deleterious SARS-CoV-2 mutations will not only aid in identifying potential therapeutic targets but will also provide a roadmap for maintaining vigilance against the genetic variability of diverse SARS-CoV-2 strains circulating globally. Furthermore, these insights empower us to more effectively manage and respond to potential viral-based pandemic outbreaks of a similar nature in the future.

The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19

BACKGROUND

The evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19.

RESULTS

The prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19.

CONCLUSION

Identified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.

Single cell RNA-seq: a novel tool to unravel virus-host interplay

Over the last decade, single cell RNA sequencing (scRNA-seq) technology has caught the momentum of being a vital revolutionary tool to unfold cellular heterogeneity by high resolution assessment. It evades the inadequacies of conventional sequencing technology which was able to detect only average expression level among cell populations. In the era of twenty-first century, several epidemic and pandemic viruses have emerged. Being an intracellular entity, viruses totally rely on host. Complex virus-host dynamics result when the virus tend to obtain factors from host cell required for its replication and establishment of infection. As a prevailing tool, scRNA-seq is able to understand virus-host interplay by comprehensive transcriptome profiling. Because of technological and methodological advancement, this technology is capable to recognize viral genome and host cell response heterogeneity. Further development in analytical methods with multiomics approach and increased availability of accessible scRNA-seq datasets will improve the understanding of viral pathogenesis that can be helpful for development of novel antiviral therapeutic strategies.

Oral administration of a recombinant modified RBD antigen of SARS-CoV-2 as a possible immunostimulant for the care of COVID-19

BACKGROUND

Developing effective vaccines against SARS-CoV-2 that consider manufacturing limitations, equitable access, and acceptance is necessary for developing platforms to produce antigens that can be efficiently presented for generating neutralizing antibodies and as a model for new vaccines.

RESULTS

This work presents the development of an applicable technology through the oral administration of the SARS-CoV-2 RBD antigen fused with a peptide to improve its antigenic presentation. We focused on the development and production of the recombinant receptor binding domain (RBD) produced in E. coli modified with the addition of amino acids extension designed to improve antigen presentation. The production was carried out in shake flask and bioreactor cultures, obtaining around 200 mg/L of the antigen. The peptide-fused RBD and peptide-free RBD proteins were characterized and compared using SDS-PAGE gel, high-performance chromatography, and circular dichroism. The peptide-fused RBD was formulated in an oil-in-water emulsion for oral mice immunization. The peptide-fused RBD, compared to RBD, induced robust IgG production in mice, capable of recognizing the recombinant RBD in Enzyme-linked immunosorbent assays. In addition, the peptide-fused RBD generated neutralizing antibodies in the sera of the dosed mice. The formulation showed no reactive episodes and no changes in temperature or vomiting.

CONCLUSIONS

Our study demonstrated the effectiveness of the designed peptide added to the RBD to improve antigen immunostimulation by oral administration.

Comparative Review of the State of the Art in Research on the Porcine Epidemic Diarrhea Virus and SARS-CoV-2, Scope of Knowledge between Coronaviruses

This review presents comparative information corresponding to the progress in knowledge of some aspects of infection by the porcine epidemic diarrhea virus (PEDV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) coronaviruses. PEDV is an alphacoronavirus of great economic importance due to the million-dollar losses it generates in the pig industry. PEDV has many similarities to the SARS-CoV-2 betacoronavirus that causes COVID-19 disease. This review presents possible scenarios for SARS-CoV-2 based on the collected literature on PEDV and the tools or strategies currently developed for SARS-CoV-2 that would be useful in PEDV research. The speed of the study of SARS-CoV-2 and the generation of strategies to control the pandemic was possible due to the knowledge derived from infections caused by other human coronaviruses such as severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS). Therefore, from the information obtained from several coronaviruses, the current and future behavior of SARS-CoV-2 could be inferred and, with the large amount of information on the virus that causes COVID-19, the study of PEDV could be improved and probably that of new emerging and re-emerging coronaviruses.

Machine learning-based approach KEVOLVE efficiently identifies SARS-CoV-2 variant-specific genomic signatures

Machine learning was shown to be effective at identifying distinctive genomic signatures among viral sequences. These signatures are defined as pervasive motifs in the viral genome that allow discrimination between species or variants. In the context of SARS-CoV-2, the identification of these signatures can assist in taxonomic and phylogenetic studies, improve in the recognition and definition of emerging variants, and aid in the characterization of functional properties of polymorphic gene products. In this paper, we assess KEVOLVE, an approach based on a genetic algorithm with a machine-learning kernel, to identify multiple genomic signatures based on minimal sets of k-mers. In a comparative study, in which we analyzed large SARS-CoV-2 genome dataset, KEVOLVE was more effective at identifying variant-discriminative signatures than several gold-standard statistical tools. Subsequently, these signatures were characterized using a new extension of KEVOLVE (KANALYZER) to highlight variations of the discriminative signatures among different classes of variants, their genomic location, and the mutations involved. The majority of identified signatures were associated with known mutations among the different variants, in terms of functional and pathological impact based on available literature. Here we showed that KEVOLVE is a robust machine learning approach to identify discriminative signatures among SARS-CoV-2 variants, which are frequently also biologically relevant, while bypassing multiple sequence alignments. The source code of the method and additional resources are available at: https://github.com/bioinfoUQAM/KEVOLVE.

NYC metropolitan wastewater reveals links between SARS-CoV-2 amino acid mutations and disease outcomes

Since late 2020, diverse SARS-CoV-2 variants with enhanced infectivity and transmissibility have emerged. In contrast to the focus on amino acid mutations in the spike protein, mutations in non-spike proteins and their associated impacts remain relatively understudied. New York City metropolitan wastewater revealed over 60 % of the most frequently occurring amino acid mutations in regions outside the spike protein. Strikingly, ~50 % of the mutations detected herein remain uncharacterized for functional impacts. Our results suggest that there are several understudied mutations within non-spike proteins N, ORF1a, ORF1b, ORF9b, and ORF9c, that could increase transmissibility, and infectivity among human populations. We also demonstrate significant correlations of P314L, D614G, T95I, G50E, G50R, G204R, R203K, G662S, P10S, and P13L with documented mortality rates, hospitalization rates, and percent positivity suggesting that amino acid mutations are likely to be indicators of COVID-19 infection outcomes.

COV2Var, a function annotation database of SARS-CoV-2 genetic variation

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants.

Allele Frequency Net Database

The allele frequency net database (AFND, http://www.allelefrequencies.net ) is an online web-based repository that contains information on the frequencies of immune-related genes and their corresponding alleles in worldwide human populations. At present, the website contains data from 1784 population samples in more than 14 million individuals from 129 countries on the frequency of genes from different polymorphic regions including data for the human leukocyte antigen (HLA) system. In addition, over the last four years, AFND has also incorporated genotype raw data from 85,000 individuals comprising 215 population samples from 39 countries. Moreover, more population data sets containing next generation sequencing data spanning >3 million individuals have been added. This resource has been widely used in a variety of contexts such as histocompatibility, immunology, epidemiology, pharmacogenetics, epitope prediction algorithms for population coverage in vaccine development, population genetics, among many others. In this chapter, we present an update of the most used searching mechanisms as described in a previous volume and some of the latest developments included in AFND.

Paraoxonase 1 rs662 polymorphism, its related variables, and COVID-19 intensity: Considering gender and post-COVID complications

In this study, we aimed to investigate the effect of paraoxonase 1 (PON1) rs662 polymorphism, arylesterase (ARE) activity, and the serum lipid profile in patients with coronavirus disease 2019 (COVID-19) in different stages of the disease considering post-COVID outcomes. A total of 470 COVID-19 patients (235 female and 235 male patients) were recruited into the study, and based on the World Health Organization (WHO) criteria, the patients were divided into three groups: moderate, severe, and critical. PON1 rs662 polymorphism was determined by the Alw 1 enzyme followed by agarose gel electrophoresis. Moreover, serum levels of triglycerides (TG), cholesterol (Chol), high-density lipoprotein-cholesterol (HDL-c), and low-density lipoprotein-cholesterol (LDL-c), as well as the level of the ARE activity of PON1 in the sera of patients were measured at the time of infection and one and three months after hospitalization. There was a significant relationship between the G allele and the severity of the disease. In addition, the probability of death in homozygous individuals (GG) was higher than in heterozygous patients (GA), and it was higher in heterozygous patients than in wild-type individuals (AA). There was also a significant relationship between the decrease in serum lipids and the intensity of COVID-19. On the contrary, at the onset of the disease, the HDL-c level and serum ARE activity were reduced compared to one and three months after COVID-19 infection. The findings of this study indicated the significant impact of PON1 rs662 polymorphism on ARE activity, lipid profiles, disease severity, and mortality in COVID-19 patients.

HLA-B27 did not protect against COVID-19 in patients with axial spondyloarthritis - data from the ReumaCov-Brasil Registry

BACKGROUND

Some studies have suggested the HLA-B27 gene may protect against some infections, as well as it could play a benefit role on the viral clearance, including hepatitis C and HIV. However, there is lack of SARS-CoV-2 pandemic data in spondyloarthritis (SpA) patients.

AIM

To evaluate the impact of HLA-B27 gene positivity on the susceptibility and severity of COVID-19 and disease activity in axial SpA patients.

METHODS

The ReumaCoV-Brasil is a multicenter, observational, prospective cohort designed to monitor immune-mediated rheumatic diseases patients during SARS-CoV-2 pandemic in Brazil. Axial SpA patients, according to the ASAS classification criteria (2009), and only those with known HLA-B27 status, were included in this ReumaCov-Brasil's subanalysis. After pairing them to sex and age, they were divided in two groups: with (cases) and without (control group) COVID-19 diagnosis. Other immunodeficiency diseases, past organ or bone marrow transplantation, neoplasms and current chemotherapy were excluded. Demographic data, managing of COVID-19 (diagnosis, treatment, and outcomes, including hospitalization, mechanical ventilation, and death), comorbidities, clinical details (disease activity and concomitant medication) were collected using the Research Electronic Data Capture (REDCap) database. Data are presented as descriptive analysis and multiple regression models, using SPSS program, version 20. P level was set as 5%.

RESULTS

From May 24th, 2020 to Jan 24th, 2021, a total of 153 axial SpA patients were included, of whom 85 (55.5%) with COVID-19 and 68 (44.4%) without COVID-19. Most of them were men (N = 92; 60.1%) with mean age of 44.0 ± 11.1 years and long-term disease (11.7 ± 9.9 years). Regarding the HLA-B27 status, 112 (73.2%) patients tested positive. There were no significant statistical differences concerning social distancing, smoking, BMI (body mass index), waist circumference and comorbidities. Regarding biological DMARDs, 110 (71.8%) were on TNF inhibitors and 14 (9.15%) on IL-17 antagonists. Comparing those patients with and without COVID-19, the HLA-B27 positivity was not different between groups (n = 64, 75.3% vs. n = 48, 48%, respectively; p = 0.514). In addition, disease activity was similar before and after the infection. Interestingly, no new episodes of arthritis, enthesitis or extra-musculoskeletal manifestations were reported after the COVID-19. The mean time from the first symptoms to hospitalization was 7.1 ± 3.4 days, and although the number of hospitalization days was numerically higher in the B27 positive group, no statistically significant difference was observed (5.7 ± 4.11 for B27 negative patients and 13.5 ± 14.8 for B27 positive patients; p = 0.594). Only one HLA-B27 negative patient died. No significant difference was found regarding concomitant medications, including conventional or biologic DMARDs between the groups.

CONCLUSIONS

No significant difference of COVID-19 frequency rate was observed in patients with axial SpA regarding the HLA-B27 positivity, suggesting a lack of protective effect with SARS-CoV-2 infection. In addition, the disease activity was similar before and after the infection.

TRIAL REGISTRATION

This study was approved by the Brazilian Committee of Ethics in Human Research (CONEP), CAAE 30186820.2.1001.8807, and was registered at the Brazilian Registry of Clinical Trials - REBEC, RBR-33YTQC. All patients read and signed the informed consent form before inclusion.

Impact of SARS-CoV-2 infection on patients with systemic lupus erythematosus in England prior to vaccination: a retrospective observational cohort study

OBJECTIVES

Determine the prevaccination healthcare impact of COVID-19 in patients with systemic lupus erythematosus (SLE) in England.

DESIGN

Retrospective cohort study of adult patients with SLE from 1 May to 31 October 2020.

SETTING

Clinical Practice Research Datalink (CPRD) Aurum and Hospital Episode Statistics (HES) databases from general practitioners across England combining primary care and other health-related data.

PARTICIPANTS

Overall, 6145 adults with confirmed SLE diagnosis ≥1 year prior to 1 May 2020 were included. Most patients were women (91.0%), white (67.1%), and diagnosed with SLE at age <50 (70.8%). Patients were excluded if they had a COVID-19 diagnosis before 1 May 2020.

PRIMARY AND SECONDARY OUTCOME MEASURES

Demographics and clinical characteristics were compared. COVID-19 severity was determined by patient care required and procedure/diagnosis codes. COVID-19 cumulative incidence, hospitalisation rates, lengths of stay and mortality rates were determined and stratified by SLE and COVID-19 severity.

RESULTS

Of 6145 patients, 3927 had mild, 1288 moderate and 930 severe SLE at baseline. The majority of patients with moderate to severe SLE were on oral corticosteroids and antimalarial treatments. Overall, 54/6145 (0.88%) patients with SLE acquired and were diagnosed with COVID-19, with 45 classified as mild, 6 moderate and 3 severe COVID-19. Cumulative incidence was higher in patients with severe SLE (1.4%) compared with patients classified as mild (0.8%) or moderate (0.8%). Ten COVID-19-specific hospital admissions occurred (n=6 moderate; n=4 severe). Regardless of COVID-19 status, hospital admission rates and length of stay increased with SLE severity. Of 54 patients with SLE diagnosed with COVID-19, 1 (1.9%) COVID-19-related death was recorded in a patient with both severe SLE and severe COVID-19.

CONCLUSIONS

SLE severity did not appear to impact COVID-19 outcomes in this study. The COVID-19 pandemic is evolving and follow-up studies are needed to understand the relationship between COVID-19 and SLE.

XCNN-SC: Explainable CNN for SARS-CoV-2 variants classification and mutation detection

The COVID-19 pandemic spread rapidly all over the world in 2019, causing the deaths of millions of people. One of the main challenges in controlling the pandemic was the high rate of virus mutation, which evaded the immune system and reduced the vaccine's effectiveness. Due to the differences in symptoms, transmission and mortality rate, and effective prevention strategies of each variant, identifying and classifying different variants is a great necessity. In the present study, 82802 whole genomes of Alpha, Beta, Delta, Eta, Epsilon, Lota, and Omicron variants of SARS-CoV-2 were obtained from the NCBI database. The label encoding method was applied to convert the genomic sequences to numeric sequences. Then, a single-layer 1D-CNN model was used to classify seven variants of SARS-CoV-2 and achieved 99.78% accuracy, 97.98% precision, 97.66% sensitivity, 99.95% specificity, and 98.68% F1-score. The max pool layer feature maps of this network were investigated to discover the sequence discriminative regions in SARS-CoV-2 variants and their effect on biological functional differences. The feature map examination led to the detection of three mutations; one of them was a missense mutation, which has been reported previously. The rest of the detected mutations were silent mutations. In conclusion, the achieved results indicated that CNN models can extract effective features to discriminate several SARS-CoV-2 variants. Also, investigation of CNN feature maps led to an explainable CNN revealing the learned knowledge of the network from the training database. This knowledge helped us to detect mutations and their functional effects in different variants.

Restoring Trust: The Need for Precision Medicine in Infectious Diseases, Public Health and Vaccines

There are limited data on precision medicine in infectious diseases and vaccines; however, precise management of infectious diseases plays a critical role in trust for government, health-care organizations, science, and pharma. The improvement in biomedical technologies, availability of large clinical and -omic data and appropriate application of artificial intelligence may allow precision in vaccines and public health and restore trust. This is an invited editorial on the role of precision medicine in infectious diseases and vaccines.

Genomic analysis of SARS-CoV-2 in forensic autopsy cases of COVID-19

Numerous genomic analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been conducted, highlighting its variations and lineage transitions. Despite the importance of forensic autopsy in investigating deaths due to coronavirus disease 2019 (COVID-19), including out-of-hospital deaths, viral genomic analysis has rarely been reported due in part to postmortem changes. In this study, various specimens were collected from 18 forensic autopsy cases with SARS-CoV-2 infection. Reverse-transcription quantitative polymerase chain reaction revealed the distribution of the virus in the body, primarily in the respiratory organs. Next-generation sequencing determined the complete genome sequences in 15 of the 18 cases, although some cases showed severe postmortem changes or degradation of tissue RNA. Intrahost genomic diversity of the virus was identified in one case of death due to COVID-19. The accumulation of single-nucleotide variations in the lung of the case suggested the intrahost evolution of SARS-CoV-2. Lung of the case showed diffuse alveolar damage histologically and positivity for SARS-CoV-2 by immunohistochemical analysis and in situ hybridization, indicating virus-associated pneumonia. This study provides insights into the feasibility of genomic analysis of SARS-CoV-2 in forensic autopsy cases and the potential for uncovering important information in COVID-19 deaths, including out-of-hospital deaths.

Differences between Omicron SARS-CoV-2 RBD and other variants in their ability to interact with cell receptors and monoclonal antibodies

SARS-CoV-2 remains a health threat with the continuous emergence of new variants. This work aims to expand the knowledge about the SARS-CoV-2 receptor-binding domain (RBD) interactions with cell receptors and monoclonal antibodies (mAbs). By using constant-pH Monte Carlo simulations, the free energy of interactions between the RBD from different variants and several partners (Angiotensin-Converting Enzyme-2 (ACE2) polymorphisms and various mAbs) were predicted. Computed RBD-ACE2-binding affinities were higher for two ACE2 polymorphisms (rs142984500 and rs4646116) typically found in Europeans which indicates a genetic susceptibility. This is amplified for Omicron (BA.1) and its sublineages BA.2 and BA.3. The antibody landscape was computationally investigated with the largest set of mAbs so far in the literature. From the 32 studied binders, groups of mAbs were identified from weak to strong binding affinities (e.g. S2K146). These mAbs with strong binding capacity and especially their combination are amenable to experimentation and clinical trials because of their high predicted binding affinities and possible neutralization potential for current known virus mutations and a universal coronavirus.Communicated by Ramaswamy H. Sarma.

Quantitative Mutation Analysis of Genes and Proteins of Major SARS-CoV-2 Variants of Concern and Interest

Of various SARS-CoV-2 variants, some have drawn special concern or interest because of their heightened disease threat. The mutability of individual SARS-CoV-2 genes/proteins presumably varies. The present study quantified gene/protein mutations in 13 major SARS-CoV-2 variants of concern/interest, and analyzed viral protein antigenicity using bioinformatics. The results from 187 carefully perused genome clones showed significantly higher mean percent mutations in the spike, ORF8, nucleocapsid, and NSP6 than in other viral proteins. The ORF8 and spike proteins also tolerated higher maximal percent mutations. The omicron variant presented more percent mutations in the NSP6 and structural proteins, whereas the delta featured more in the ORF7a. Omicron subvariant BA.2 exhibited more mutations in ORF6, and omicron BA.4 had more in NSP1, ORF6, and ORF7b, relative to omicron BA.1. Delta subvariants AY.4 and AY.5 bore more mutations in ORF7b and ORF8 than delta B.1.617.2. Predicted antigen ratios of SARS-CoV-2 proteins significantly vary (range: 38-88%). To overcome SARS-CoV-2 immune evasion, the relatively conserved, potentially immunogenic NSP4, NSP13, NSP14, membrane, and ORF3a viral proteins may serve as more suitable targets for molecular vaccines or therapeutics than the mutation-prone NSP6, spike, ORF8, or nucleocapsid protein. Further investigation into distinct mutations of the variants/subvariants may help understand SARS-CoV-2 pathogenesis.

Clinical and laboratory features of SARS-CoV-2 variants across multiple rounds of pandemic waves in hospitalized children in an Iranian referral hospital

BACKGROUND

Since the onset of the COVID-19 pandemic, SARS-CoV-2 has evolved into independent new forms, variants of concern (VOCs). While epidemiological data showed increased transmissibility of VOCs, their impact on clinical outcomes is less clear. This study aimed to investigate the differences between the clinical and laboratory features of children infected with VOCs.

METHODS

This study included all cases with SARS-CoV-2-positive nasopharyngeal swabs obtained from patients referred to Children's Medical Center (CMC), an Iranian referral hospital, between July 2021 and March 2022. The inclusion criteria for this study included all patients, regardless of age, who had a positive test anywhere in the hospital setting. Exclusion criteria for the study included those whose data was obtained from non-hospital outpatient settings, or referred from another hospital. The SARS-CoV-2 genome area encoding the S1 domain was amplified and sequenced. The type of variant in each sample was identified based on the mutations in the S1 gene. Demographic characteristics, clinical data, and laboratory findings were collected from the patient's medical records.

RESULTS

This study included 87 pediatric cases with confirmed COVID-19, with a median age of 3.5 years (IQR: 1-8.12). Data from sequencing reveals the type of variants as 5 (5.7%) alpha, 53 (60.9%) Delta, and 29 (33.3%) Omicron. The incidence of seizure was higher in patients with Alpha and Omicron infection compared to the Delta group. A higher incidence of diarrhea was reported in Alpha-infected patients, and a higher risk of disease severity, distress, and myalgia was associated with Delta infection.

CONCLUSION

Laboratory parameters did not mostly differ among the patients infected with Alpha, Delta, and Omicron. However, these variants may manifest different clinical features. Further studies with larger sample sizes are required to fully understand the clinical manifestations of each variant.

Spotlight on the impact of viral infections on Hematopoietic Stem Cells (HSCs) with a focus on COVID-19 effects

Hematopoietic stem cells (HSCs) are known for their significant capability to reconstitute and preserve a functional hematopoietic system in long-term periods after transplantation into conditioned hosts. HSCs are thus crucial cellular targets for the continual repair of inherited hematologic, metabolic, and immunologic disorders. In addition, HSCs can undergo various fates, such as apoptosis, quiescence, migration, differentiation, and self-renewal. Viruses continuously pose a remarkable health risk and request an appropriate, balanced reaction from our immune system, which as well as affects the bone marrow (BM). Therefore, disruption of the hematopoietic system due to viral infection is essential. In addition, patients for whom the risk-to-benefit ratio of HSC transplantation (HSCT) is acceptable have seen an increase in the use of HSCT in recent years. Hematopoietic suppression, BM failure, and HSC exhaustion are all linked to chronic viral infections. Virus infections continue to be a leading cause of morbidity and mortality in HSCT recipients, despite recent advancements in the field. Furthermore, whereas COVID-19 manifests initially as an infection of the respiratory tract, it is now understood to be a systemic illness that significantly impacts the hematological system. Patients with advanced COVID-19 often have thrombocytopenia and blood hypercoagulability. In the era of COVID-19, Hematological manifestations of COVID-19 (i.e., thrombocytopenia and lymphopenia), the immune response, and HSCT may all be affected by the SARS-CoV-2 virus in various ways. Therefore, it is important to determine whether exposure to viral infections may affect HSCs used for HSCT, as this, in turn, may affect engraftment efficiency. In this article, we reviewed the features of HSCs, and the effects of viral infections on HSCs and HSCT, such as SARS-CoV-2, HIV, cytomegalovirus, Epstein-Barr virus, HIV, etc. Video Abstract.

Exploring m6A-RNA methylation as a potential therapeutic strategy for acute lung injury and acute respiratory distress syndrome

N6-methyladenosine (m6A) is the most common methylation modification in mammalian messenger RNA (mRNA) and noncoding RNAs. m6A modification plays a role in the regulation of gene expression and deregulation of m6A methylation has been implicated in many human diseases. Recent publications suggest that exploitation of this methylation process may possess utility against acute lung injury (ALI). ALI and its more severe form, acute respiratory distress syndrome (ARDS) are acute, inflammatory clinical syndromes characterized by poor oxygenation and diffuse pulmonary infiltrates. This syndrome is associated with microvascular endothelial dysfunction, subsequent pulmonary hypertension and may ultimately lead to mortality without rigorous and acute clinical intervention. Over the years, many attempts have been made to detect novel therapeutic avenues for research without much success. The urgency for the discovery of novel therapeutic agents has become more pronounced recently given the current pandemic infection of coronavirus disease 2019 (COVID-2019), still ongoing at the time that this review is being written. We review the current landscape of literature regarding ALI and ARDS etiology, pathophysiology, and therapeutics and present a potential role of m6A methylation. Additionally, we will establish the axiomatic principles of m6A methylation to provide a framework. In conclusion, METTL3, or methyltransferase-like 3, the selective RNA methyltransferase for m6A, is a hub of proinflammatory gene expression regulation in ALI, and using a modern drug discovery strategy will identify new and effective ALI drug candidates targeting METTTL3.

HLA Variation and SARS-CoV-2 Specific Antibody Response

Differences in SARS-CoV-2-specific immune responses have been observed between individuals following natural infection or vaccination. In addition to already known factors, such as age, sex, COVID-19 severity, comorbidity, vaccination status, hybrid immunity, and duration of infection, inter-individual variations in SARS-CoV-2 immune responses may, in part, be explained by structural differences brought about by genetic variation in the human leukocyte antigen (HLA) molecules responsible for the presentation of SARS-CoV-2 antigens to T effector cells. While dendritic cells present peptides with HLA class I molecules to CD8+ T cells to induce cytotoxic T lymphocyte responses (CTLs), they present peptides with HLA class II molecules to T follicular helper cells to induce B cell differentiation followed by memory B cell and plasma cell maturation. Plasma cells then produce SARS-CoV-2-specific antibodies. Here, we review published data linking HLA genetic variation or polymorphisms with differences in SARS-CoV-2-specific antibody responses. While there is evidence that heterogeneity in antibody response might be related to HLA variation, there are conflicting findings due in part to differences in study designs. We provide insight into why more research is needed in this area. Elucidating the genetic basis of variability in the SARS-CoV-2 immune response will help to optimize diagnostic tools and lead to the development of new vaccines and therapeutics against SARS-CoV-2 and other infectious diseases.

Impact of Changes in Human Airway Epithelial Cellular Composition and Differentiation on SARS-CoV-2 Infection Biology

The consequences of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can range from asymptomatic to fatal disease. Variations in epithelial susceptibility to SARS-CoV-2 infection depend on the anatomical location from the proximal to distal respiratory tract. However, the cellular biology underlying these variations is not completely understood. Thus, air-liquid interface cultures of well-differentiated primary human tracheal and bronchial epithelial cells were employed to study the impact of epithelial cellular composition and differentiation on SARS-CoV-2 infection by transcriptional (RNA sequencing) and immunofluorescent analyses. Changes of cellular composition were investigated by varying time of differentiation or by using specific compounds. We found that SARS-CoV-2 primarily infected not only ciliated cells but also goblet cells and transient secretory cells. Viral replication was impacted by differences in cellular composition, which depended on culturing time and anatomical origin. A higher percentage of ciliated cells correlated with a higher viral load. However, DAPT treatment, which increased the number of ciliated cells and reduced goblet cells, decreased viral load, indicating the contribution of goblet cells to infection. Cell entry factors, especially cathepsin L and transmembrane protease serine 2, were also affected by differentiation time. In conclusion, our study demonstrates that viral replication is affected by changes in cellular composition, especially in cells related to the mucociliary system. This could explain in part the variable susceptibility to SARS-CoV-2 infection between individuals and between anatomical locations in the respiratory tract.

A survival analysis of socio-demographic and clinical predictors among hospitalized COVID-19 patients in Southern Iran

BACKGROUND

This study aimed to evaluate the socio-demographic, clinical, and laboratory risk factors in hospitalized COVID-19 patients during the first 6 months of the SARS-CoV-2 epidemic.

METHOD

This retrospective hospital-based cross-sectional study included all laboratory-confirmed cases of the COVID-19 virus that were admitted to the Shohadaye-Khalije-Fars Hospital in Bushehr, Iran, from February 22, 2020 to September 21, 2020. The patients' records were reviewed during the hospitalization period. The global COVID-19 clinical platform, i.e., the World Health Organization Rapid Case Report Form was used as the data collection tool. We conducted the survival analysis using the Kaplan-Meier and the Stepwise Cox regression analyses.

RESULTS

The analysis included 2108 confirmed cases of COVID-19 with a mean age of 47.81 years (SD 17.78); 56.8% men, 43.2% women and 6.3% (n = 133) deaths. After adjustment, it was found that factors associated with an increased risk of death consisted of chronic kidney disease, intensive care unit admission, cancer, and hemoptysis. The 7-day survival rate was 95.8%, which decreased to 95.1%, 94.0%, and 93.8% on days 14, 21, and 28 of hospitalization, respectively.

DISCUSSION AND CONCLUSION

Older COVID-19 patients with manifestation of hemoptysis and a past medical history of chronic kidney disease and cancer, should be closely monitored to prevent disease deterioration and death, and also should be admitted to the intensive care unit.

Systematic Guidelines for Effective Utilization of COVID-19 Databases in Genomic, Epidemiologic, and Clinical Research

The pandemic has led to the production and accumulation of various types of data related to coronavirus disease 2019 (COVID-19). To understand the features and characteristics of COVID-19 data, we summarized representative databases and determined the data types, purpose, and utilization details of each database. In addition, we categorized COVID-19 associated databases into epidemiological data, genome and protein data, and drug and target data. We found that the data present in each of these databases have nine separate purposes (clade/variant/lineage, genome browser, protein structure, epidemiological data, visualization, data analysis tool, treatment, literature, and immunity) according to the types of data. Utilizing the databases we investigated, we created four queries as integrative analysis methods that aimed to answer important scientific questions related to COVID-19. Our queries can make effective use of multiple databases to produce valuable results that can reveal novel findings through comprehensive analysis. This allows clinical researchers, epidemiologists, and clinicians to have easy access to COVID-19 data without requiring expert knowledge in computing or data science. We expect that users will be able to reference our examples to construct their own integrative analysis methods, which will act as a basis for further scientific inquiry and data searching.

The role of the HLA allelic repertoire on the clinical severity of COVID-19 in Canadians, living in the Saskatchewan province

AIMS

The HLA system has been implicated as an underlying determinant for modulating the immune response to SARS-CoV-2. In this study, we aimed to determine the association of patients' HLA genetic profiles with the disease severity of COVID-19 infection.

METHODS

Prospective study was conducted on COVID-19 patients (n = 40) admitted to hospitals in Saskatoon, Canada, between March and December 2020. Next-generation sequencing was performed on the patient samples to obtain high-resolution HLA typing profiles. The statistical association between HLA allelic frequency and disease severity was examined. The disease severity was categorized based on the length of hospital stay and intensive care needs or demise during the hospital stay.

RESULTS

HLA allelic frequencies of the high and low-severity cohorts were normalized against corresponding background allelic frequencies. In the high-severity cohort, A*02:06 (11.8-fold), B*51:01 (2.4-fold), B*15:01(3.1-fold), C*01:02 (3.3-fold), DRB1*08:02 (31.2-fold), DQ*06:09 (11-fold), and DPB1*04:02(4-fold) were significantly overrepresented (p < 0.05) making these deleterious alleles. In the low-severity cohort, A*24:02 (2.8-fold), B*35:01 (2.8-fold), DRB1*04:07 (5.3-fold), and DRB1*08:11 (22-fold) were found to be significantly overrepresented (p < 0.05) making these protective alleles. These above alleles interact with NK cell antiviral activity via the killer immunoglobulin-like receptors (KIR). The high-severity cohort had a higher predilection for HLA alleles associated with KIR subgroups; Bw4-80I (1.1-fold), and C1 (1.6-fold) which promotes NK cell inhibition, while the low-severity cohort had a higher predilection for Bw4-80T (1.6-fold), and C2 (1.6-fold) which promote NK cell activation.

CONCLUSION

In this study, the HLA allelic repository with the distribution of deleterious and protective alleles was found to correlate with the severity of the clinical course in COVID-19. Moreover, the interaction of specific HLA alleles with the KIR-associated subfamily modulates the NK cell-mediated surveillance of SARS-CoV-2. Both deleterious HLA alleles and inhibitory KIR appear prominently in the severe COVID-19 group focusing on the importance of NK cells in the convalescence of COVID-19.

Characterization of SARS-CoV-2 isolated from a patient in Iran compared to SARS-CoV-2 different variants

Since the onset of the global epidemic of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), whole genome sequencing of virus in all countries has been considered to track and predict virus transmission and variation patterns. In the current study we reported a novel complete genome sequence of SARS-CoV-2 isolated from Iran. Genomics variations and protein sequences were evaluated for the isolated sequence and seven Iranian complete genome sequences of SARS-CoV-2 from NCBI using the reference genome of the SARS-CoV-2 Wuhan-Hu-1. The results showed six nucleotide substitutions. The multiple sequence alignment of the spike protein of the Wuhan-Hu-1 strain and the emerging variants indicated similar its residue pattern in the current sequence to the Wuhan-Hu-1 strain. There were relatively similar binding affinity and residues involved in the interactions of the spike receptor-binding domain (RBD) of the Wuhan-Hu-1 strain, the variants and Hormozgan With angiotensin-converting enzyme 2 (ACE2). Tracing the phylogeny of virus indicated distinct clustering of Iranian variants in branches close to the Asian countries. The mutation effect study on the function of proteins predicted neutral impact of all six nucleotide substitutions. However, the free energy calculations indicated a decreasing the protein stability related to the mutations. This data, consistent with similar studies, showed that despite the high similarity in the nucleotide sequence of the SARS-CoV-2, the mutation pattern varies from country to country. Therefore, any country can benefit from these studies to track and find appropriate strategies for treating and controlling the epidemic.Communicated by Ramaswamy H. Sarma.

Association of the Interleukin 1B-31*C Proinflammatory Allele with the Severity of COVID-19 Patients: A Preliminary Report

Individuals with no known comorbidities or risk factors may develop severe coronavirus disease 2019 (COVID-19). The present study assessed the effect of certain host polymorphisms and viral lineage on the severity of COVID-19 among hospitalized patients with no known comorbidities in Mexico. The analysis included 117 unrelated hospitalized patients with COVID-19. Patients were stratified by whether they required intensive care unit (ICU) admission: the ICU group (n = 40) and non-ICU group (n = 77). COVID-19 was diagnosed on the basis of a positive severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reverse transcription-polymerase chain reaction (RT-PCR) assay and clinical and radiographic criteria. The presence of the IL1B-31 (T/C) polymorphism was determined for all patients using PCR and nucleotide sequencing. Genotyping of the IL-4 (-590, T/C) and IL-8 (-251, T/A) polymorphisms was performed by the amplification refractory mutation system-PCR method. Genotyping of IL1-RN was performed using PCR. Viral genome sequencing was performed using the ARTIC Network amplicon sequencing protocol using a MinION. Logistic regression analysis identified the carriage of IL-1 B*-31 *C as an independent potential risk factor (odds ratio [OR] = 3.1736, 95% confidence interval [CI] = 1.0748-9.3705, p = 0.0366) for ICU admission and the presence of IL-RN*2 as a protective factor (OR = 0.4371, 95% CI = 0.1935-0.9871, p = 0.0465) against ICU admission. Under the codominant model, the CC genotype of IL1B-31 significantly increased the risk of ICU admission (OR: 6.38, 95% CI: 11.57-25.86, p < 0.024). The IL1B-31 *C-IL-4-590 *T haplotype increased the risk of ICU admission (OR = 2.53, 95% CI = 1.02-6.25, p = 0.047). The 42 SARS-CoV-2 genomes sequenced belonged to four clades, 20A-20D. No association was detected between SARS-CoV-2 clades and ICU admission or death. Thus, in patients with no known comorbidities or risk factors, the IL1B-31*C proinflammatory allele was observed to be associated with the risk of ICU admission owing to COVID-19.

State of the art in epitope mapping and opportunities in COVID-19

The understanding of any disease calls for studying specific biological structures called epitopes. One important tool recently drawing attention and proving efficiency in both diagnosis and vaccine development is epitope mapping. Several techniques have been developed with the urge to provide precise epitope mapping for use in designing sensitive diagnostic tools and developing rpitope-based vaccines (EBVs) as well as therapeutics. In this review, we will discuss the state of the art in epitope mapping with a special emphasis on accomplishments and opportunities in combating COVID-19. These comprise SARS-CoV-2 variant analysis versus the currently available immune-based diagnostic tools and vaccines, immunological profile-based patient stratification, and finally, exploring novel epitope targets for potential prophylactic, therapeutic or diagnostic agents for COVID-19.

HLA alleles associated with COVID-19 susceptibility and severity in different populations: a systematic review

Background

COVID-19 is a respiratory disease caused by a novel coronavirus called as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). Detected for the first time in December 2019 in Wuhan and it has quickly spread all over the world in a couple of months and becoming a world pandemic. Symptoms of the disease and clinical outcomes are very different in infected people. These differences highlight the paramount need to study and understand the human genetic variation that occurring viral infections. Human leukocyte antigen (HLA) is an important component of the viral antigen presentation pathway, and it plays an essential role in conferring differential viral susceptibility and severity of diseases. HLA alleles have been involved in the immune response to viral diseases such as SARS-CoV-2.

Main body of the abstract

Herein, we sought to evaluate this hypothesis by summarizing the association between HLA class I and class II alleles with COVID-19 susceptibility and/or severity reported in previous studies among different populations (Chinese, Italian, Iranian, Japanese, Spanish, etc.). The findings of all selected articles showed that several alleles have been found associated with COVID-19 susceptibility and severity. Even results across articles have been inconsistent and, in some cases, conflicting, highlighting that the association between the HLA system and the COVID-19 outcome might be ethnic-dependent, there were some alleles in common between some populations such as HLA-DRB1*15 and HLA-A*30:02.

Conclusion

These contradictory findings warrant further large, and reproducible studies to decipher any possible genetic predisposition underlying susceptibility to SARS-COV-2 and disease progression and host immune response.

Single-cell RNA-seq methods to interrogate virus-host interactions

The twenty-first century has seen the emergence of many epidemic and pandemic viruses, with the most recent being the SARS-CoV-2-driven COVID-19 pandemic. As obligate intracellular parasites, viruses rely on host cells to replicate and produce progeny, resulting in complex virus and host dynamics during an infection. Single-cell RNA sequencing (scRNA-seq), by enabling broad and simultaneous profiling of both host and virus transcripts, represents a powerful technology to unravel the delicate balance between host and virus. In this review, we summarize technological and methodological advances in scRNA-seq and their applications to antiviral immunity. We highlight key scRNA-seq applications that have enabled the understanding of viral genomic and host response heterogeneity, differential responses of infected versus bystander cells, and intercellular communication networks. We expect further development of scRNA-seq technologies and analytical methods, combined with measurements of additional multi-omic modalities and increased availability of publicly accessible scRNA-seq datasets, to enable a better understanding of viral pathogenesis and enhance the development of antiviral therapeutics strategies.

The Clinical Course and Outcomes of Patients Hospitalized Due to COVID-19 during Three Pandemic Waves in Poland: A Single Center Observational Study

Background: The first case of coronavirus disease 2019 (COVID-19) in Poland was reported on 4 March 2020. We aim to compare the clinical course and outcomes of patients hospitalized in the Hospital for Infectious Diseases in Warsaw due to COVID-19 during three pandemic waves. Materials and methods: The medical data were collected for all patients diagnosed with COVID-19 hospitalized in our hospital from 6 March 2020 till 30 November 2021. COVID-19 diagnosis was confirmed by nasopharyngeal swabs using real-time polymerase chain reaction assay (RT-PCR) or SARS-CoV-2 antigen test. COVID-19 waves were defined based on the number and dynamics of cases. Results: Altogether, 2138 patient medical records were analyzed. The majority of the cohort was male (1235/2138, 57.8%), and the median age was 65 years [IQR: 50−74 years]. Patients hospitalized during the third wave had lower oxygen saturation on admission (p < 0.001) and were more likely to receive oxygen supplementation (p < 0.001). Serious complications, including pneumothorax (p < 0.001) and thromboembolic complications (p < 0.001), intensive care unit admission (p = 0.034), and death (p = 0.003), occurred more often in patients of the third wave. Conclusions: During the third wave, patients in our cohort experienced a more severe course of the disease and poorer outcomes.

Statistical analysis supports UTR (untranslated region) deletion theory in SARS-CoV-2

It was noticed that the mortality rate of SARS-CoV-2 infection experienced a significant declination in the early stage of the epidemic. We suspect that the sharp deterioration of virus toxicity is related to the deletion of the untranslated region (UTR) of the virus genome. It was found that the genome length of SARS-CoV-2 engaged a significant truncation due to UTR deletion after a mega-sequence analysis. Sequence similarity analysis further indicated that short UTR strains originated from its long UTR ancestors after an irreversible deletion. A good correlation was discovered between genome length and mortality, which demonstrated that the deletion of the virus UTR significantly affected the toxicity of the virus. This correlation was further confirmed in a significance analysis of the genetic influence on the clinical outcomes. The viral genome length of hospitalized patients was significantly more extensive than that of asymptomatic patients. In contrast, the viral genome length of asymptomatic was considerably longer than that of ordinary patients with symptoms. A genome-level mutation scanning was performed to systematically evaluate the influence of mutations at each position on virulence. The results indicated that UTR deletion was the primary driving force in alternating virus virulence in the early evolution. In the end, we proposed a mathematical model to explain why this UTR deletion was not continuous.

Human antibody recognition and neutralization mode on the NTD and RBD domains of SARS-CoV-2 spike protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). Variants of concern (VOCs) such as Delta and Omicron have developed, which continue to spread the pandemic. It has been reported that these VOCs reduce vaccine efficacy and evade many neutralizing monoclonal antibodies (mAbs) that target the receptor binding domain (RBD) of the glycosylated spike (S) protein, which consists of the S1 and S2 subunits. Therefore, identification of optimal target regions is required to obtain neutralizing antibodies that can counter VOCs. Such regions have not been identified to date. We obtained 2 mAbs, NIBIC-71 and 7G7, using peripheral blood mononuclear cells derived from volunteers who recovered from COVID-19. Both mAbs had neutralizing activity against wild-type SARS-CoV-2 and Delta, but not Omicron. NIBIC-71 binds to the RBD, whereas 7G7 recognizes the N-terminal domain of the S1. In particular, 7G7 inhibited S1/S2 cleavage but not the interaction between the S protein and angiotensin-converting enzyme 2; it suppressed viral entry. Thus, the efficacy of a neutralizing mAb targeting inhibition of S1/2 cleavage was demonstrated. These results suggest that neutralizing mAbs targeting blockade of S1/S2 cleavage are likely to be cross-reactive against various VOCs.

Long-Term Survival among Patients Hospitalized for COVID-19 during the First Three Epidemic Waves: An Observational Study in a Northern Italy Hospital

The mortality rate of hospitalized COVID-19 patients differed strongly between the first three pandemic waves. Nevertheless, their long-term survival has been poorly assessed. The aim of this study was to compare the clinical characteristics and mortality rates of 825 patients with coronavirus disease 2019 (COVID-19) infection who were hospitalized at the Alessandria hub hospital, in Northern Italy, during the first fifty days of the first three pandemic waves. Each subject was followed in terms of vital status for six months from the date of hospital admission or until deceased. Patients admitted during the three waves differed in age (p = 0.03), disease severity (p < 0.0001), Charlson comorbidity index (p = 0.0002), oxygen therapy (p = 0.002), and invasive mechanical ventilation (p < 0.0001). By the end of follow-up, 309 deaths (38.7%) were observed, of which 186 occurred during hub hospitalization (22.5%). Deaths were distributed differently among the waves (p < 0.0001), resulting in being higher amongst those subjects admitted during the first wave. The COVID-19 infection was reported as the main cause of death and patients with a higher mortality risk were those aged ≥65 years [adjusted HR = 3.40 (95% CI 2.20-5.24)], with a higher disease severity [adjusted HR = 1.87 (95%CI 1.43-2.45)], and those requiring oxygen therapy [adjusted HR = 2.30 (95%CI 1.61-3.30)]. In conclusion, COVID-19 patients admitted to our hub hospital during the second and the third waves had a lower risk of long-term mortality than those admitted during the first. Older age, more severe disease, and the need for oxygen therapy were among the strongest risk factors for poor prognosis.

SARS-CoV-2 Variants of Concern and Variations within Their Genome Architecture: Does Nucleotide Distribution and Mutation Rate Alter the Functionality and Evolution of the Virus?

SARS-CoV-2 virus pathogenicity and transmissibility are correlated with the mutations acquired over time, giving rise to variants of concern (VOCs). Mutations can significantly influence the genetic make-up of the virus. Herein, we analyzed the SARS-CoV-2 genomes and sub-genomic nucleotide composition in relation to the mutation rate. Nucleotide percentage distributions of 1397 in-house-sequenced SARS-CoV-2 genomes were enumerated, and comparative analyses (i) within the VOCs and of (ii) recovered and mortality patients were performed. Fisher's test was carried out to highlight the significant mutations, followed by RNA secondary structure prediction and protein modeling for their functional impacts. Subsequently, a uniform dinucleotide composition of AT and GC was found across study cohorts. Notably, the N gene was observed to have a high GC percentage coupled with a relatively higher mutation rate. Functional analysis demonstrated the N gene mutations, C29144T and G29332T, to induce structural changes at the RNA level. Protein secondary structure prediction with N gene missense mutations revealed a differential composition of alpha helices, beta sheets, and coils, whereas the tertiary structure displayed no significant changes. Additionally, the N gene CTD region displayed no mutations. The analysis highlighted the importance of N protein in viral evolution with CTD as a possible target for antiviral drugs.