Early detection of emerging viral variants through analysis of community structure of coordinated substitution networks.

The emergence of viral variants with altered phenotypes is a public health challenge underscoring the need for advanced evolutionary forecasting methods. Given extensive epistatic interactions within viral genomes and known viral evolutionary history, efficient genomic surveillance necessitates early detection of emerging viral haplotypes rather than commonly targeted single mutations. Haplotype inference, however, is a significantly more challenging problem precluding the use of traditional approaches. Here, using SARS-CoV-2 evolutionary dynamics as a case study, we show that emerging haplotypes with altered transmissibility can be linked to dense communities in coordinated substitution networks, which become discernible significantly earlier than the haplotypes become prevalent. From these insights, we develop a computational framework for inference of viral variants and validate it by successful early detection of known SARS-CoV-2 strains. Our methodology offers greater scalability than phylogenetic lineage tracing and can be applied to any rapidly evolving pathogen with adequate genomic surveillance data.

Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants may have different characteristics, e.g., in transmission, mortality, and the effectiveness of vaccines, indicating the importance of variant detection at the population level. Wastewater-based surveillance of SARS-CoV-2 RNA fragments has been shown to be an effective way to monitor the COVID-19 pandemic at the population level. Wastewater is a complex sample matrix affected by environmental factors and PCR inhibitors, causing insufficient coverage in sequencing, for example. Subsequently, results where part of the genome does not have sufficient coverage are not uncommon. To identify variants and their proportions in wastewater over time, we utilized next-generation sequencing with the ARTIC Network's primer set and bioinformatics pipeline to evaluate the presence of variants in partial genome data. Based on the wastewater data from November 2021 to February 2022, the Delta variant was dominant until mid-December in Helsinki, Finland's capital, and thereafter in late December 2022 Omicron became the most common variant. At the same time, the Omicron variant of SARS-CoV-2 outcompeted the previous Delta variant in Finland in new COVID-19 cases. The SARS-CoV-2 variant findings from wastewater are in agreement with the variant information obtained from the patient samples when visually comparing trends in the sewerage network area. This indicates that the sequencing of wastewater is an effective way to monitor temporal and spatial trends of SARS-CoV-2 variants at the population level.

SARS-CoV-2 variant with the spike protein mutation F306L in the southern border provinces of Thailand.

The southernmost part of Thailand is a unique and culturally diverse region that has been greatly affected by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak during the coronavirus disease-2019 pandemic. To gain insights into this situation, we analyzed 1942 whole-genome sequences of SARS-CoV-2 obtained from the five southernmost provinces of Thailand between April 2021 and March 2022, together with those publicly available in the Global Initiative on Sharing All Influenza Data database. Our analysis revealed evidence for transboundary transmissions of the virus in and out of the five southernmost provinces during the study period, from both domestic and international sources. The most prevalent viral variant in our sequence dataset was the Delta B.1.617.2.85 variant, also known as the Delta AY.85 variant, with many samples carrying a non-synonymous mutation F306L in their spike protein. Protein-protein docking and binding interface analyses suggested that the mutation may enhance the binding between the spike protein and host cell receptor protein angiotensin-converting enzyme 2, and we found that the mutation was significantly associated with an increased fatality rate. This mutation has also been observed in other SARS-CoV-2 variants, suggesting that it is of particular interest and should be monitored.

A long-term cohort study: the immune evasion and decreasing neutralization dominated the SARS-CoV-2 breakthrough infection.

Most of vaccinees and COVID-19 convalescents can build effective anti-SARS-CoV-2 humoral immunity, which helps preventing infection and alleviating symptoms. However, breakthrough viral infections caused by emerging SARS-CoV-2 variants, especially Omicron subvariants, still pose a serious threat to global health. By monitoring the viral infections and the sera neutralization ability of a long-tracked cohort, we found out that the immune evasion of emerging Omicron subvariants and the decreasing neutralization led to the mini-wave of SARS-CoV-2 breakthrough infections. Meanwhile, no significant difference had been found in the infectivity of tested SARS-CoV-2 variants, even though the affinity between human angiotensin-converting enzyme 2 (hACE2) and receptor-binding domain (RBDs) of tested variants showed an increasing trend. Notably, the immune imprinting of inactivated COVID-19 vaccine can be relieved by infections of BA.5.2 and XBB.1.5 variants sequentially. Our data reveal the rising reinfection risk of immune evasion variants like Omicron JN.1 in China, suggesting the importance of booster with updated vaccines.

First Molecular Detection of SARS-CoV-2 in Sewage and Wastewater in Ghana.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is shed in the stool of infected individuals and can be detected in sewage and wastewater contaminated with infected stool. This study is aimed at detecting the virus and its potential survival in sewage and wastewater in Ghana. The cross-sectional study included samples from 16 validated environmental surveillance sites in 7 regions of Ghana. A total of 354 samples composed of wastewater (280) and sewage (74) were collected from November 2020 to November 2022. Overall, 17% of the samples were positive for SARS-CoV-2 by real-time PCR, with 6% in sewage and 11% in wastewater. The highest number of positive samples was collected from the Greater Accra Region (7.3%) with the least recorded in the Bono East Region (0.6%). Further characterization of the positive samples using the next-generation sequencing (NGS) approach yielded two variants: Alpha (B.1.1.7) and Delta (AY.36). Attempts to isolate SARS-CoV-2 in the Vero cell line were not successful probably due to the low viral load concentrations (Ct values > 35) or prolonged exposure to high temperatures rendering the virus noninfectious. Our findings suggest that SARS-CoV-2 RNA in sewage and wastewater may not be infectious, but the prevalence shows that the virus persists in the communities within Ghana.

Disappearance of Imported Cases of Omicron Lineage BA.2.40 in West Kalimantan, Indonesia.

Background: The World Health Organization has declared Omicron as the fifth variant of concern with more than 50 mutations, particularly in the spike protein. Given increased viral infectivity due to mutations, worldwide genomic surveillance and detection of severe acute respiratory syndrome 2 (SARS-CoV-2) is essential. The present study aimed to track Omicron lineage BA.2.40 in West Kalimantan, Indonesia. Methods: In May-August 2022, nasopharyngeal swab samples (n=3,642) were collected from international travelers to West Kalimantan (active surveillance), and patients hospitalized due to SARS-CoV-2 infection (baseline surveillance). The samples were tested for Omicron lineages based on ORF1ab, N, and HV69-70del genes, followed by whole-genome sequencing. The sequences were then identified using two genomic databases, aligned against the reference genome (Wuhan/Hu-1/2019), and then compared with BA.2.40 lineage detected across the world. Phylogenetic analysis between the samples and other SARS-CoV-2 isolates was performed using molecular evolutionary genetics analysis software. Results: Based on the genomic databases, 10 isolates were identified as BA.2.40. All samples tested positive for the ORF1ab and N genes, but negative for the HV69-70del gene, which is a marker to detect the Omicron variant. Phylogenetic analysis showed the isolates were closely related to an isolate from Malaysia, an area dominated by BA.2.40. Conclusion: Omicron lineage BA.2.40 has no HV69-70 deletion in the spike protein, a marker used to screen for the Omicron variant. BA.2.40 showed a high similarity to an isolate from Malaysia and was detected only during certain periods, indicating the effect of internationally imported cases.

Expression of the SARS-CoV-2 receptor-binding domain by live attenuated influenza vaccine virus as a strategy for designing a bivalent vaccine against COVID-19 and influenza.

Influenza and SARS-CoV-2 are two major respiratory pathogens that cocirculate in humans and cause serious illness with the potential to exacerbate disease in the event of co-infection. To develop a bivalent vaccine, capable of protecting against both infections, we inserted the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein into hemagglutinin (HA) molecule or into the open reading frame of the truncated nonstructural protein 1 (NS1) of live attenuated influenza vaccine (LAIV) virus and assessed phenotypic characteristics of the rescued LAIV-RBD viruses, as well as their immunogenicity in mouse and Syrian hamster animal models. A panel of 9 recombinant LAIV-RBD viruses was rescued using the A/Leningrad/17 backbone. Notably, only two variants with RBD insertions into the HA molecule could express sufficient quantities of RBD protein in infected MDCK cells. Intranasal immunization of mice induced high levels of anti-influenza antibody responses in all chimeric LAIV-RBD viruses, which was comparable to the LAIV virus vector. The RBD-specific antibody responses were most pronounced in the variant expressing RBD194 fragment as a chimeric HA protein. This candidate was further tested in Syrian hamsters and was shown to be immunogenic and capable of protecting animals against both infections.

A mass balance approach for quantifying the role of natural decay and fate mechanisms on SARS-CoV-2 genetic marker removal during water reclamation.

The recent SARS-CoV-2 outbreak yielded substantial data regarding virus fate and prevalence at water reclamation facilities (WRFs), identifying influential factors as natural decay, adsorption, light, pH, salinity, and antagonistic microorganisms. However, no studies have quantified the impact of these factors in full scale WRFs. Utilizing a mass balance approach, we assessed the impact of natural decay and other fate mechanisms on genetic marker removal during water reclamation, through the use of sludge and wastewater genetic marker loading estimates. Results indicated negligible removal of genetic markers during P/PT (primary effluent (PE) p value: 0.267; preliminary and primary treatment (P/PT) accumulation p value: 0.904; and thickened primary sludge (TPS) p value: 0.076) indicating no contribution of natural decay and other fate mechanisms toward removal in P/PT. Comparably, adsorption and decomposition was found to be the dominant pathway for genetic marker removal (thickened waste activated sludge (TWAS) log loading 9.75 log10 GC/day); however, no estimation of log genetic marker accumulation could be carried out due to high detections in TWAS. PRACTITIONER POINTS: The mass balance approach suggested that the contribution of natural decay and other fate mechanisms to virus removal during wastewater treatment are negligible compared with adsorption and decomposition in P/PT (p value: 0.904). During (P/PT), a higher viral load remained in the (PE) (14.16 log10 GC/day) compared with TPS (13.83 log10 GC/day); however, no statistical difference was observed (p value: 0.280) indicting that adsorption/decomposition most probably did not occur. In secondary treatment (ST), viral genetic markers in TWAS were consistently detected (13.41 log10 GC/day) compared with secondary effluent (SE), indicating that longer HRT and the potential presence of extracellular polymeric substance-containing enriched biomass enabled adsorption/decomposition. Estimations of total solids and volatile solids for TPS and TWAS indicated that adsorption affinity was different between solids sampling locations (p value: <0.0001).

Computational analysis of affinity dynamics between the variants of SARS-CoV-2 spike protein (RBD) and human ACE-2 receptor.

The novel coronavirus SARS-CoV-2 resulted in a significant worldwide health emergency known as the COVID-19 pandemic. This crisis has been marked by the widespread of various variants, with certain ones causing notable apprehension. In this study, we harnessed computational techniques to scrutinize these Variants of Concern (VOCs), including various Omicron subvariants. Our approach involved the use of protein structure prediction algorithms and molecular docking techniques, we have investigated the effects of mutations within the Receptor Binding Domain (RBD) of SARS-CoV-2 and how these mutations influence its interactions with the human angiotensin-converting enzyme 2 (hACE-2) receptor. Further we have predicted the structural alterations in the RBD of naturally occurring SARS-CoV-2 variants using the tr-Rosetta algorithm. Subsequent docking and binding analysis employing HADDOCK and PRODIGY illuminated crucial interactions occurring at the Receptor-Binding Motif (RBM). Our findings revealed a hierarchy of increased binding affinity between the human ACE2 receptor and the various RBDs, in the order of wild type (Wuhan-strain) < Beta < Alpha < Gamma < Omicron-B.1.1.529 < Delta < Omicron-BA.2.12.1 < Omicron-BA.5.2.1 < Omicron-BA.1.1. Notably, Omicron-BA.1.1 demonstrated the highest binding affinity of -17.4 kcal mol-1 to the hACE2 receptor when compared to all the mutant complexes. Additionally, our examination indicated that mutations occurring in active residues of the Receptor Binding Domain (RBD) consistently improved the binding affinity and intermolecular interactions in all mutant complexes. Analysis of the differences among variants has laid a foundation for the structure-based drug design targeting the RBD region of SARS-CoV-2.

Computational methods in the analysis of SARS-CoV-2 in mammals: A systematic review of the literature.

SARS-CoV-2 is an enveloped RNA virus that causes severe respiratory illness in humans and animals. It infects cells by binding the Spike protein to the host's angiotensin-converting enzyme 2 (ACE2). The bat is considered the natural host of the virus, and zoonotic transmission is a significant risk and can happen when humans come into close contact with infected animals. Therefore, understanding the interconnection between human, animal, and environmental health is important to prevent and control future coronavirus outbreaks. This work aimed to systematically review the literature to identify characteristics that make mammals suitable virus transmitters and raise the main computational methods used to evaluate SARS-CoV-2 in mammals. Based on this review, it was possible to identify the main factors related to transmissions mentioned in the literature, such as the expression of ACE2 and proximity to humans, in addition to identifying the computational methods used for its study, such as Machine Learning, Molecular Modeling, Computational Simulation, between others. The findings of the work contribute to the prevention and control of future outbreaks, provide information on transmission factors, and highlight the importance of advanced computational methods in the study of infectious diseases that allow a deeper understanding of transmission patterns and can help in the development of more effective control and intervention strategies.

An outbreak of COVID-19 after a pilgrimage to Medjugorje due to Delta sub-lineages.

INTRODUCTION: A COVID-19 outbreak occurred at the end of October 2021 among pilgrims returning from Medjugorje (Bosnia and Herzegovina). METHODOLOGY: Whole genome sequencing (WGS) of SARS-CoV-2, epidemiological data, and phylogenetic analysis were used to reconstruct outbreak dynamics. RESULTS: The results suggest that only in one case, associated with the SARS-CoV-2 sub-lineage AY.9.2, it is possible to trace back the place of contagion to Medjugorje, while the other cases were likely to be acquired in the country of origin. CONCLUSIONS: The combined use of phylogenetic data derived from WGS, and epidemiological data allowed us to study epidemic dynamics and to formulate a possible hypothesis on the place of exposure to SARS-CoV-2. The identification of different sub-lineages of the SARS-CoV-2 Delta variant also suggested that different chains of transmission contributed to the outbreak.

Correlation of SARS-CoV-2 in Wastewater and Individual Testing Results in a Jail, Atlanta, Georgia, USA.

Institution-level wastewater-based surveillance was implemented during the COVID-19 pandemic, including in carceral facilities. We examined the relationship between COVID-19 diagnostic test results of residents in a jail in Atlanta, Georgia, USA (average population ≈2,700), and quantitative reverse transcription PCR signal for SARS-CoV-2 in weekly wastewater samples collected during October 2021‒May 2022. The jail offered residents rapid antigen testing at entry and periodic mass screenings by reverse transcription PCR of self-collected nasal swab specimens. We aggregated individual test data, calculated the Spearman correlation coefficient, and performed logistic regression to examine the relationship between strength of SARS-CoV-2 PCR signal (cycle threshold value) in wastewater and percentage of jail population that tested positive for COVID-19. Of 13,745 nasal specimens collected, 3.9% were COVID-positive (range 0%-29.5% per week). We observed a strong inverse correlation between diagnostic test positivity and cycle threshold value (r = -0.67; p<0.01). Wastewater-based surveillance represents an effective strategy for jailwide surveillance of COVID-19.

Rapid identification of SARS-CoV-2 strains via isothermal enzymatic recombinase amplification and nanopore sequencing.

Surveillance of the SARS-CoV-2 genome has become a crucial technique in the management of COVID-19, aiding the pandemic response and supporting effective public health interventions. Typically, whole-genomic sequencing is used along with PCR-based target enrichment techniques to identify SARS-CoV-2 variants, which is a complicated and time-consuming process that requires central laboratory facilities. Thus, there is an urgent need to develop rapid and cost-effective tools for precise on-site detection and identification of SARS-CoV-2 strains. In this study, we demonstrate the rapid diagnosis of COVID-19 and identification of SARS-CoV-2 variants by amplification and sequencing of the entire SARS-CoV-2 S gene using isothermal enzymatic recombinase amplification combined with the advanced Oxford nanopore sequencing technique. The entire procedure, from sampling to sequencing, takes less than 8 hours and can be performed with limited resources. The newly developed method has noteworthy implications for examining the transmission dynamics of the virus, detecting novel genetic variants, and assessing the effect of mutations on diagnostic approaches, antiviral treatments, and vaccines.

Immune features revealed by single-cell RNA and single-cell TCR/BCR sequencing in patients with rheumatoid arthritis receiving COVID-19 booster vaccination.

Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, have profoundly affected human health. Booster COVID-19 vaccines have demonstrated significant efficacy in reducing infection and severe cases. However, the effects of booster COVID-19 vaccines on key immune cell subsets and their responses in rheumatoid arthritis (RA) are not well understood. By using single-cell RNA sequencing (scRNA-seq) combined with scTCR/BCR-seq analysis, a total of 8 major and 27 minor cell clusters were identified from paired peripheral blood mononuclear cells (PBMCs) which were collected 1 week before and 4 weeks after booster vaccination in stable RA patients. Booster vaccination only had limited impact on the composition and proportions of PBMCs cell clusters. CD8+ cytotoxic T cells (CD8+T_CTL) showed a trend toward an increase after vaccination, while naive B cells and conventional dendritic cells (cDCs) showed a trend toward a decrease. Transcriptomic changes were observed after booster vaccination, primarily involving T/B cell receptor signaling pathways, phagosome, antigen processing and presenting, and viral myocarditis pathways. Interferon (IFN) and pro-inflammatory response gene sets were slightly upregulated across most major cell subpopulations in COVID-19 booster-vaccinated RA individuals. Plasma neutralizing antibody titers significantly increased after booster COVID-19 vaccination (p = 0.037). Single-cell TCR/BCR analysis revealed increased B cell clone expansion and repertoire diversity postvaccination, with no consistent alterations in T cells. Several clonotypes of BCRs and TCRs were identified to be significantly over-represented after vaccination, such as IGHV3-15 and TRBV28. Our study provided a comprehensive single-cell atlas of the peripheral immune response and TCR/BCR immune repertoire profiles to inactivated SARS-CoV-2 booster vaccination in RA patients, which helps us to understand vaccine-induced immune responses better.

Infection kinetics, syncytia formation, and inflammatory biomarkers as predictive indicators for the pathogenicity of SARS-CoV-2 Variants of Concern in Calu-3 cells.

The ongoing COVID-19 pandemic has led to the emergence of new SARS-CoV-2 variants as a result of continued host-virus interaction and viral genome mutations. These variants have been associated with varying levels of transmissibility and disease severity. We investigated the phenotypic profiles of six SARS-CoV-2 variants (WT, D614G, Alpha, Beta, Delta, and Omicron) in Calu-3 cells, a human lung epithelial cell line. In our model demonstrated that all variants, except for Omicron, had higher efficiency in virus entry compared to the wild-type. The Delta variant had the greatest phenotypic advantage in terms of early infection kinetics and marked syncytia formation, which could facilitate cell-to-cell spreading, while the Omicron variant displayed slower replication and fewer syncytia formation. We also identified the Delta variant as the strongest inducer of inflammatory biomarkers, including pro-inflammatory cytokines/chemokines (IP-10/CXCL10, TNF-α, and IL-6), anti-inflammatory cytokine (IL-1RA), and growth factors (FGF-2 and VEGF-A), while these inflammatory mediators were not significantly elevated with Omicron infection. These findings are consistent with the observations that there was a generally more pronounced inflammatory response and angiogenesis activity within the lungs of COVID-19 patients as well as more severe symptoms and higher mortality rate during the Delta wave, as compared to less severe symptoms and lower mortality observed during the current Omicron wave in Thailand. Our findings suggest that early infectivity kinetics, enhanced syncytia formation, and specific inflammatory mediator production may serve as predictive indicators for the virulence potential of future SARS-CoV-2 variants.

Effectiveness and durability of mRNA-1273 BA.4/BA.5 bivalent vaccine (mRNA-1273.222) against SARS-CoV-2 BA.4/BA.5 and XBB sublineages.

Emerging SARS-CoV-2 sublineages continue to cause serious COVID-19 disease, but most individuals have not received any COVID-19 vaccine for >1 year. Assessment of long-term effectiveness of bivalent COVID-19 vaccines against circulating sublineages is important to inform the potential need for vaccination with updated vaccines. In this test-negative study at Kaiser Permanente Southern California, sequencing-confirmed BA.4/BA.5- or XBB-related SARS-CoV-2-positive cases (September 1, 2022 to June 30, 2023), were matched 1:3 to SARS-CoV-2-negative controls. We assessed mRNA-1273 bivalent relative (rVE) and absolute vaccine effectiveness (VE) compared to ≥2 or 0 doses of original monovalent vaccine, respectively. The rVE analysis included 20,966 cases and 62,898 controls. rVE (95%CI) against BA.4/BA.5 at 14-60 days and 121-180 days was 52.7% (46.9-57.8%) and 35.5% (-2.8-59.5%) for infection, and 59.3% (49.7-67.0%) and 33.2% (-28.2-68.0%) for Emergency Department/Urgent Care (ED/UC) encounters. For BA.4/BA.5-related hospitalizations, rVE was 71.3% (44.9-85.1%) and 52.0% (-1.2-77.3%) at 14-60 days and 61-120 days, respectively. rVE against XBB at 14-60 days and 121-180 days was 48.8% (33.4-60.7%) and -3.9% (-18.1-11.3%) for infection, 70.7% (52.4-82.0%) and 15.7% (-6.0-33.2%) for ED/UC encounters, and 87.9% (43.8-97.4%) and 57.1% (17.0-77.8%) for hospitalization. VE and subgroup analyses (age, immunocompromised status, previous SARS-CoV-2 infection) results were similar to rVE analyses. rVE of mRNA-1273 bivalent vaccine against BA.4/BA.5 and XBB infections, ED/UC encounters, and hospitalizations waned over time. Periodic revaccination with vaccines targeting emerging variants may be important in reducing COVID-19 morbidity and mortality.

Properties and Mechanisms of Deletions, Insertions, and Substitutions in the Evolutionary History of SARS-CoV-2.

SARS-CoV-2 has accumulated many mutations since its emergence in late 2019. Nucleotide substitutions leading to amino acid replacements constitute the primary material for natural selection. Insertions, deletions, and substitutions appear to be critical for coronavirus's macro- and microevolution. Understanding the molecular mechanisms of mutations in the mutational hotspots (positions, loci with recurrent mutations, and nucleotide context) is important for disentangling roles of mutagenesis and selection. In the SARS-CoV-2 genome, deletions and insertions are frequently associated with repetitive sequences, whereas C>U substitutions are often surrounded by nucleotides resembling the APOBEC mutable motifs. We describe various approaches to mutation spectra analyses, including the context features of RNAs that are likely to be involved in the generation of recurrent mutations. We also discuss the interplay between mutations and natural selection as a complex evolutionary trend. The substantial variability and complexity of pipelines for the reconstruction of mutations and the huge number of genomic sequences are major problems for the analyses of mutations in the SARS-CoV-2 genome. As a solution, we advocate for the development of a centralized database of predicted mutations, which needs to be updated on a regular basis.

Positive selection underlies repeated knockout of ORF8 in SARS-CoV-2 evolution.

Knockout of the ORF8 protein has repeatedly spread through the global viral population during SARS-CoV-2 evolution. Here we use both regional and global pathogen sequencing to explore the selection pressures underlying its loss. In Washington State, we identified transmission clusters with ORF8 knockout throughout SARS-CoV-2 evolution, not just on novel, high fitness viral backbones. Indeed, ORF8 is truncated more frequently and knockouts circulate for longer than for any other gene. Using a global phylogeny, we find evidence of positive selection to explain this phenomenon: nonsense mutations resulting in shortened protein products occur more frequently and are associated with faster clade growth rates than synonymous mutations in ORF8. Loss of ORF8 is also associated with reduced clinical severity, highlighting the diverse clinical impacts of SARS-CoV-2 evolution.

Comprehensive analysis of immunogenic cell death-related gene and construction of prediction model based on WGCNA and multiple machine learning in severe COVID-19.

The death of coronavirus disease 2019 (COVID-19) is primarily due to from critically ill patients, especially from ARDS complications caused by SARS-CoV-2. Therefore, it is essential to contribute an in-depth understanding of the pathogenesis of the disease and to identify biomarkers for predicting critically ill patients at the molecular level. Immunogenic cell death (ICD), as a specific variant of regulatory cell death driven by stress, can induce adaptive immune responses against cell death antigens in the host. Studies have confirmed that both innate and adaptive immune pathways are involved in the pathogenesis of SARS-CoV-2 infection. However, the role of ICD in the pathogenesis of severe COVID-19 has rarely been explored. In this study, we systematically evaluated the role of ICD-related genes in COVID-19. We conducted consensus clustering, immune infiltration analysis, and functional enrichment analysis based on ICD differentially expressed genes. The results showed that immune infiltration characteristics were altered in severe and non-severe COVID-19. In addition, we used multiple machine learning methods to screen for five risk genes (KLF5, NSUN7, APH1B, GRB10 and CD4), which are used to predict COVID-19 severity. Finally, we constructed a nomogram to predict the risk of severe COVID-19 based on the classification and recognition model, and validated the model with external data sets. This study provides a valuable direction for the exploration of the pathogenesis and progress of COVID-19, and helps in the early identification of severe cases of COVID-19 to reduce mortality.

Computational identification and experimental verification of a novel signature based on SARS-CoV-2-related genes for predicting prognosis, immune microenvironment and therapeutic strategies in lung adenocarcinoma patients.

Background: Early research indicates that cancer patients are more vulnerable to adverse outcomes and mortality when infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Nonetheless, the specific attributes of SARS-CoV-2 in lung Adenocarcinoma (LUAD) have not been extensively and methodically examined. Methods: We acquired 322 SARS-CoV-2 infection-related genes (CRGs) from the Human Protein Atlas database. Using an integrative machine learning approach with 10 algorithms, we developed a SARS-CoV-2 score (Cov-2S) signature across The Cancer Genome Atlas and datasets GSE72094, GSE68465, and GSE31210. Comprehensive multi-omics analysis, including assessments of genetic mutations and copy number variations, was conducted to deepen our understanding of the prognosis signature. We also analyzed the response of different Cov-2S subgroups to immunotherapy and identified targeted drugs for these subgroups, advancing personalized medicine strategies. The expression of Cov-2S genes was confirmed through qRT-PCR, with GGH emerging as a critical gene for further functional studies to elucidate its role in LUAD. Results: Out of 34 differentially expressed CRGs identified, 16 correlated with overall survival. We utilized 10 machine learning algorithms, creating 101 combinations, and selected the RFS as the optimal algorithm for constructing a Cov-2S based on the average C-index across four cohorts. This was achieved after integrating several essential clinicopathological features and 58 established signatures. We observed significant differences in biological functions and immune cell statuses within the tumor microenvironments of high and low Cov-2S groups. Notably, patients with a lower Cov-2S showed enhanced sensitivity to immunotherapy. We also identified five potential drugs targeting Cov-2S. In vitro experiments revealed a significant upregulation of GGH in LUAD, and its knockdown markedly inhibited tumor cell proliferation, migration, and invasion. Conclusion: Our research has pioneered the development of a consensus Cov-2S signature by employing an innovative approach with 10 machine learning algorithms for LUAD. Cov-2S reliably forecasts the prognosis, mirrors the tumor's local immune condition, and supports clinical decision-making in tumor therapies.