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.

A novel approach to designing viral precision vaccines applied to SARS-CoV-2.

Efficient precision vaccines against several highly pathogenic zoonotic viruses are currently lacking. Proteolytic activation is instrumental for a number of these viruses to gain host-cell entry and develop infectivity. For SARS-CoV-2, this process is enhanced by the insertion of a furin cleavage site at the junction of the spike protein S1/S2 subunits upstream of the metalloprotease TMPRSS2 common proteolytic site. Here, we describe a new approach based on specific epitopes selection from the region involved in proteolytic activation and infectivity for the engineering of precision candidate vaccinating antigens. This approach was developed through its application to the design of SARS-CoV-2 cross-variant candidates vaccinating antigens. It includes an in silico structural analysis of the viral region involved in infectivity, the identification of conserved immunogenic epitopes and the selection of those eliciting specific immune responses in infected people. The following step consists of engineering vaccinating antigens that carry the selected epitopes and mimic their 3D native structure. Using this approach, we demonstrated through a Covid-19 patient-centered study of a 500 patients' cohort, that the epitopes selected from SARS-CoV-2 protein S1/S2 junction elicited a neutralizing antibody response significantly associated with mild and asymptomatic COVID-19 (p<0.001), which strongly suggests protective immunity. Engineered antigens containing the SARS-CoV-2 selected epitopes and mimicking the native epitopes 3D structure generated neutralizing antibody response in mice. Our data show the potential of this combined computational and experimental approach for designing precision vaccines against viruses whose pathogenicity is contingent upon proteolytic activation.

Evidence of antigenic drift in the fusion machinery core of SARS-CoV-2 spike.

Antigenic drift of SARS-CoV-2 is typically defined by mutations in the N-terminal domain and receptor binding domain of spike protein. In contrast, whether antigenic drift occurs in the S2 domain remains largely elusive. Here, we perform a deep mutational scanning experiment to identify S2 mutations that affect binding of SARS-CoV-2 spike to three S2 apex public antibodies. Our results indicate that spatially diverse mutations, including D950N and Q954H, which are observed in Delta and Omicron variants, respectively, weaken the binding of spike to these antibodies. Although S2 apex antibodies are known to be nonneutralizing, we show that they confer protection in vivo through Fc-mediated effector functions. Overall, this study indicates that the S2 domain of SARS-CoV-2 spike can undergo antigenic drift, which represents a potential challenge for the development of more universal coronavirus vaccines.

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.

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.

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.

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.

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.

Exploring viral aetiology in upper respiratory tract infections: insights from metagenomic next-generation sequencing in Swiss outpatients before and during the SARS-CoV-2 pandemic.

AIMS OF THE STUDY: Upper respiratory tract infections are among the most common reasons for primary care consultations. They are diagnosed predominantly based on clinical assessment. Here, we investigated the benefit of viral metagenomic next-generation sequencing (mNGS) in an outpatient setting. METHODS: This prospective cross-sectional study included immunocompetent patients with acute upper respiratory tract infections. General practitioners collected pharyngeal swabs and demographic and clinical data. Specimens were analysed using viral mNGS and conventional tests. RESULTS: Two hundred seventy-seven patients were recruited by 21 general practitioners between 10/2019 and 12/2020, of which 91% had a suspected viral aetiology. For 138 patients (49.8%), mNGS identified one or more respiratory viruses. The mNGS showed a high overall agreement with conventional routine diagnostic tests. Rhinoviruses were the most frequently detected respiratory viruses (20.2% of patients). Viral mNGS reflected the influenza wave in early 2020 and the SARS-CoV-2 pandemic outbreak in Switzerland in March 2020. Notably, rhinoviruses continued to circulate despite non-pharmaceutical hygiene measures. CONCLUSIONS: Viral mNGS allowed the initial diagnosis to be retrospectively re-evaluated. Assuming reduced turnaround times, mNGS has the potential to directly guide the treatment of upper respiratory tract infections. On an epidemiological level, our study highlights the utility of mNGS in respiratory infection surveillance, allowing early detection of epidemics and providing information crucial for prevention.

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.

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.

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.

Dynamic changes of Bacterial Microbiomes in Oropharynx during Infection and Recovery of COVID-19 Omicron Variant.

Oropharyngeal microbiomes play a significant role in the susceptibility and severity of COVID-19, yet the role of these microbiomes play for the development of COVID-19 Omicron variant have not been reported. A total of 791 pharyngeal swab samples were prospectively included in this study, including 297 confirmed cases of Omicron variant (CCO), 222 confirmed case of Omicron who recovered (CCOR), 73 confirmed cases of original strain (CCOS) and 199 healthy controls (HC). All samples completed MiSeq sequencing. The results showed that compared with HC, conditional pathogens increased in CCO, while acid-producing bacteria decreased. Based on six optimal oropharyngeal operational taxonomy units (OTUs), we constructed a marker microbial classifier to distinguish between patients with Omicron variant and healthy people, and achieved high diagnostic efficiency in both the discovery queue and the verification queue. At same time, we introduced a group of cross-age infection verification cohort and Omicron variant subtype XBB.1.5 branch, which can be accurately distinguished by this diagnostic model. We also analyzed the characteristics of oropharyngeal microbiomes in two subgroups of Omicron disease group-severity of infection and vaccination times, and found that the change of oropharyngeal microbiomes may affect the severity of the disease and the efficacy of the vaccine. In addition, we found that some genera with significant differences gradually increased or decreased with the recovery of Omicron variant infection. The results of Spearman analysis showed that 27 oropharyngeal OTUs were closely related to 6 clinical indexes in CCO and HC. Finally, we found that the Omicron variant had different characterization of oropharyngeal microbiomes from the original strain. Our research characterizes oropharyngeal microbiomes of Omicron variant cases and rehabilitation cases, successfully constructed and verified the non-invasive diagnostic model of Omicron variant, described the correlation between microbial OTUs and clinical indexes. It was found that the infection of Omicron variant and the infection of original strain have different characteristics of oropharyngeal microbiomes.

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).

Broad-spectrum Delta-BA.2 tandem-fused heterodimer mRNA vaccine delivered by lipopolyplex.

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, continues to mutate and generates new variants with increasingly severe immune escape, urging the upgrade of COVID-19 vaccines. Here, based on a similar dimeric RBD design as our previous ZF2001 vaccine, we developed a novel broad-spectrum COVID-19 mRNA vaccine, SWIM516, with chimeric Delta-BA.2 RBD dimer delivered by lipopolyplex (LPP). Unlike the popular lipid nanoparticle (LNP), this LPP-delivered mRNA expresses only in the injection site, which avoids potential toxicity to the liver. We demonstrated the broad-spectrum humoral and cellular immunogenicity of this vaccine to Delta and Omicron sub-variants in naïve mice and as booster shots. When challenged with Delta or Omicron live virus, vaccinated human angiotensin-converting enzyme (hACE2) transgenic mice and rhesus macaques were both protected, displaying significantly reduced viral loads and markedly relieved pathological damages. We believe the SWIM516 vaccine qualifies as a candidate for the next-generation broad-spectrum COVID-19 vaccine.

Label-free and amplification-free viral RNA quantification from primate biofluids using a trapping-assisted optofluidic nanopore platform.

Viral outbreaks can cause widespread disruption, creating the need for diagnostic tools that provide high performance and sample versatility at the point of use with moderate complexity. Current gold standards such as PCR and rapid antigen tests fall short in one or more of these aspects. Here, we report a label-free and amplification-free nanopore sensor platform that overcomes these challenges via direct detection and quantification of viral RNA in clinical samples from a variety of biological fluids. The assay uses an optofluidic chip that combines optical waveguides with a fluidic channel and integrates a solid-state nanopore for sensing of individual biomolecules upon translocation through the pore. High specificity and low limit of detection are ensured by capturing RNA targets on microbeads and collecting them by optical trapping at the nanopore location where targets are released and rapidly detected. We use this device for longitudinal studies of the viral load progression for Zika and Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infections in marmoset and baboon animal models, respectively. The up to million-fold trapping-based target concentration enhancement enables amplification-free RNA quantification across the clinically relevant concentration range down to the assay limit of RT-qPCR as well as cases in which PCR failed. The assay operates across all relevant biofluids, including semen, urine, and whole blood for Zika and nasopharyngeal and throat swab, rectal swab, and bronchoalveolar lavage for SARS-CoV-2. The versatility, performance, simplicity, and potential for full microfluidic integration of the amplification-free nanopore assay points toward a unique approach to molecular diagnostics for nucleic acids, proteins, and other targets.

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.