The evolution of SARS-CoV-2

Lessons learnt on infectious bronchitis virus lineage GI-23

Infectious bronchitis virus (IBV) is the first coronavirus discovered in the world in the early 1930s and despite decades of extensive immunoprophylaxis efforts, it remains a major health concern to poultry producers worldwide. Rapid evolution due to large poultry population sizes coupled with high mutation and recombination events and the reliance of the antiviral immune response on specific antibodies against the epitopes of the S1 glycoprotein, render the control of IBV extremely challenging. The numerous and rapidly evolving genetic and antigenic IBV types are currently classified based on the whole S1 gene sequence, into 36 lineages clustered in eight genotypes. Most lineages (29) are grouped in genotype I (GI). "Variant 2" (Israel/Variant 2/1998) is the prototype strain of lineage GI-23 and, since this lineage emerged during the mid-1990s in the Middle East, it has evolved into numerous genetically related strains and disseminated to five continents. The hallmarks of IBV Variant 2-like strain infections are high virulence and remarkable nephrotropism and nephropathogenicity; however, the molecular mechanisms of these traits remain to be elucidated. Limited protection from previously utilized vaccine strains and accumulated losses to poultry producers have urged the development and implementation of homologous Variant 2-like vaccine strains. The latest avian coronavirus biology with specific emphasis on the cumulative knowledge about IBV "Variant 2" and emergence of related strains, characteristics and control are reviewed.

Diverse genetic conflicts mediated by molecular mimicry and computational approaches to detect them

In genetic conflicts between intergenomic and selfish elements, driver and killer elements achieve biased survival, replication, or transmission over sensitive and targeted elements through a wide range of molecular mechanisms, including mimicry. Driving mechanisms manifest at all organismal levels, from the biased propagation of individual genes, as demonstrated by transposable elements, to the biased transmission of genomes, as illustrated by viruses, to the biased transmission of cell lineages, as in cancer. Targeted genomes are vulnerable to molecular mimicry through the conserved motifs they use for their own signaling and regulation. Mimicking these motifs enables an intergenomic or selfish element to control core target processes, and can occur at the sequence, structure, or functional level. Molecular mimicry was first appreciated as an important phenomenon more than twenty years ago. Modern genomics technologies, databases, and machine learning approaches offer tremendous potential to study the distribution of molecular mimicry across genetic conflicts in nature. Here, we explore the theoretical expectations for molecular mimicry between conflicting genomes, the trends in molecular mimicry mechanisms across known genetic conflicts, and outline how new examples can be gleaned from population genomic datasets. We discuss how mimics involving short sequence-based motifs or gene duplications can evolve convergently from new mutations. Whereas, processes that involve divergent domains or fully-folded structures occur among genomes by horizontal gene transfer. These trends are largely based on a small number of organisms and should be reevaluated in a general, phylogenetically independent framework. Currently, publicly available databases can be mined for genotypes driving non-Mendelian inheritance patterns, epistatic interactions, and convergent protein structures. A subset of these conflicting elements may be molecular mimics. We propose approaches for detecting genetic conflict and molecular mimicry from these datasets.

Phylogeogenomic analysis of the earliest reported sequences of SARS-CoV-2 from 161 countries

The SARS-CoV-2 is the causative agent of COVID-19 whose evolutionary path with geographical context forms the focus of present study. The first reported sequence from each of the 161 countries was downloaded from the GISAID database. Multiple sequence alignment was performed using MAFFT v.7, and a TCS-based network was constructed using PopART v.1.7. A total of 27 proteins were analyzed including structural and non-structural proteins. NSP3 and NSP12, responsible for viral replication and RNA synthesis, respectively, had the highest mutation incidence and frequency among non-structural proteins. The spike (S) protein, critical for viral attachment and entry, had the highest prevalence and frequency of mutations. ORF3a had the highest mutation incidence and frequency among accessory proteins. The phylogeogenomic network identified six haplogroups containing 35 sequences, while the remaining sequences belonged to different haplotypes. The virus's genetic distinctiveness was higher in European genomes, with four haplogroups dominated by Europe-linked sequences. The triangular-shaped pattern observed in the virus's evolutionary path suggests that it spread to different continents from Asia. Multiple transmission pathways connecting different countries affirm the virus's ability to emerge in multiple countries by early 2020. The possibility of new species emergence through "saltation" due to the pandemic is also discussed.

Safety and immunogenicity of a modified mRNA-lipid nanoparticle vaccine candidate against COVID-19: Results from a phase 1, dose-escalation study

This phase 1, open-label, dose-escalation, multi-center study (NCT05477186) assessed the safety and immunogenicity of a booster dose of an mRNA COVID-19 vaccine (CV0501) encoding the SARS-CoV-2 Omicron BA.1 spike protein. Participants aged ≥ 18 years previously vaccinated with ≥ 2 doses of an mRNA COVID-19 vaccine received CV0501 doses ranging from 12 to 200 μg. After assessment of safety and immunogenicity of the 12 μg dose in 30 adults, 30 adults ≤ 64 years were randomized to receive either a 3 or 6 μg dose. Solicited adverse events (AEs) were collected for 7 days, unsolicited AEs for 28 days, and serious AEs (SAEs), medically attended AEs (MAAEs), and AEs of special interest (AESIs) until day (D) 181 post-vaccination. Serum neutralizing titers specific to SARS-CoV-2 BA.1, wild-type, Delta, and additional Omicron subvariants were assessed at D1, D15, D29, D91, and D181. Of 180 vaccinated participants (mean age: 49.3 years; 57.8% women), 70.6% had prior SARS-CoV-2 infection. Most solicited local (98.1%) and systemic (96.7%) AEs were of mild-to-moderate severity; the most common were injection site pain (57.5%; 33.3-73.3% across groups) and myalgia (36.9%; 13.3-56.7%). Unsolicited AEs were reported by 14.4% (6.7-26.7%) of participants (mild-to-moderate severity in 88.5% of the participants). Three participants (1.7%) reported SAEs, 16.7% (6.7-30.0%) reported MAAEs, and 8.3% (0.0-13.3%) reported AESIs (15 COVID-19 cases), none related to vaccination. Geometric means of serum neutralizing titers increased from baseline to D15 and D29 (dose-dependent), and then decreased over time. The safety and immunogenicity results supported advancement to a phase 2 trial.

SARS-CoV-2 introductions to the island of Ireland: a phylogenetic and geospatiotemporal study of infection dynamics

BACKGROUND

Ireland's COVID-19 response combined extensive SARS-CoV-2 testing to estimate incidence, with whole genome sequencing (WGS) for genome surveillance. As an island with two political jurisdictions-Northern Ireland (NI) and Republic of Ireland (RoI)-and access to detailed passenger travel data, Ireland provides a unique setting to study virus introductions and evaluate public health measures. Using a substantial Irish genomic dataset alongside global data from GISAID, this study aimed to trace the introduction and spread of SARS-CoV-2 across the island.

METHODS

We recursively searched for 29,518 SARS-CoV-2 genome sequences collected in Ireland from March 2020 to June 2022 within the global SARS-CoV-2 phylogenetic tree and identified clusters based on shared last common non-Irish ancestors. A maximum parsimony approach was used to assign a likely country of origin to each cluster. The geographic locations and collection dates of the samples in each introduction cluster were used to map the spread of the virus across Ireland. Downsampling was used to model the impact of varying levels of sequencing and normalisation for population permitted comparison between jurisdictions.

RESULTS

Six periods spanning the early introductions and the emergence of Alpha, Delta, and Omicron variants were studied in detail. Among 4439 SARS-CoV-2 introductions to Ireland, 2535 originated in England, with additional cases largely from the rest of Great Britain, United States of America, and Northwestern Europe. Introduction clusters ranged in size from a single to thousands of cases. Introductions were concentrated in the densely populated Dublin and Belfast areas, with many clusters spreading islandwide. Genetic phylogeny was able to effectively trace localised transmission patterns. Introduction rates were similar in NI and RoI for most variants, except for Delta, which was more frequently introduced to NI.

CONCLUSIONS

Tracking individual introduction events enables detailed modelling of virus spread patterns and clearer assessment of the effectiveness of control measures. Stricter travel restrictions in RoI likely reduced Delta introductions but not infection rates, which were similar across jurisdictions. Local and global sequencing levels influence the information available from phylogenomic analyses and we describe an approach to assess the ability of a chosen WGS level to detect virus introductions.

Recombination across distant coronavirid species and genera is a rare event with distinct genomic features

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; family Coronaviridae, genus Betacoronavirus, subgenus Sarbecovirus) has caused millions of deaths, prompting a need for better understanding of coronavirid emergence and spillover to humans. As an evaluation of how some features of SARS-CoV-2, unique among sarbecoviruses, may have been acquired from related viruses, we conducted phylogenetic and recombination analyses to compare the frequency of recombination among coronavirids across vs within genera, subgenera, and species. Among known betacoronaviruses, we identified 199 (183 intraspecies, 16 interspecies, but no intersubgenera) recombination events. Phylogenetic analyses revealed that the ancestry of interspecies events was limited and less prone to affect 5' regions of coronavirid genome open reading frame 1 (ORF1) than intraspecies events. On the contrary, interspecies events were significantly more prone to impact the 3' end (ORF6-ORF8 and the nucleocapsid protein [N] ORF), suggesting the existence of region-specific constraints on recombination. This work substantiated that recombination among betacoronaviruses is limited by the genome similarity between their parental viruses. We conclude that SARS-CoV-2 likely acquired unique features through recombination with closely related circulating sarbecoviruses (most likely from the same species) that co-existed geographically.

IMPORTANCE

Understanding the evolutionary events that led to SARS-CoV-2 emergence, spillover, and spread is crucial to prevent, or at least be prepared for, the same type of occurrence in the future. Given that SARS-CoV-2 has some characteristics not found in other closely related viruses, we aimed to systematically assess how likely these unique features may have been acquired through recombination. We found that, although recombination is a frequent phenomenon among betacoronaviruses, it is mostly limited to closely related members of the same species. Therefore, we conclude that the most likely scenario involved feature acquisition from recombination with a closely related virus that was circulating in a geographically overlapping area or through a different biological process, but not recombination from a virus of a different species, genus, or subgenus.

C→U transition biases in SARS-CoV-2: still rampant 4 years from the start of the COVID-19 pandemic

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pandemic and post-pandemic periods has been characterized by rapid adaptive changes that confer immune escape and enhanced human-to-human transmissibility. Sequence change is additionally marked by an excess number of C→U transitions suggested as being due to host-mediated genome editing. To investigate how these influence the evolutionary trajectory of SARS-CoV-2, 2,000 high-quality, coding complete genome sequences of SARS-CoV-2 variants collected pre-September 2020 and from each subsequently appearing alpha, delta, BA.1, BA.2, BA.5, XBB, EG, HK, and JN.1 lineages were downloaded from NCBI Virus in April 2024. C→U transitions were the most common substitution during the diversification of SARS-CoV-2 lineages over the 4-year observation period. A net loss of C bases and accumulation of U's occurred at a constant rate of approximately 0.2%-0.25%/decade. C→U transitions occurred in over a quarter of all sites with a C (26.5%; range 20.0%-37.2%) around five times more than observed for the other transitions (5.3%-6.8%). In contrast to an approximately random distribution of other transitions across the genome, most C→U substitutions occurred at statistically preferred sites in each lineage. However, only the most C→U polymorphic sites showed evidence for a preferred 5'U context previously associated with APOBEC 3A editing. There was a similarly weak preference for unpaired bases suggesting much less stringent targeting of RNA than mediated by A3 deaminases in DNA editing. Future functional studies are required to determine editing preferences, impacts on replication fitness in vivo of SARS-CoV-2 and other RNA viruses, and impact on host tropism.

IMPORTANCE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the pandemic and post-pandemic periods has shown a remarkable capacity to adapt and evade human immune responses and increase its human-to-human transmissibility. The genome of SARS-CoV-2 is also increasingly scarred by the effects of multiple C→U mutations from host genome editing as a cellular defense mechanism akin to restriction factors for retroviruses. Through the analysis of large data sets of SARS-CoV-2 isolate sequences collected throughout the pandemic period and beyond, we show that C→U transitions have driven a base compositional change over time amounting to a net loss of C bases and accumulation of U's at a rate of approximately 0.2%-0.25%/decade. Most C→U substitutions occurred in the absence of the preferred upstream-base context or targeting of unpaired RNA bases previously associated with the host RNA editing protein, APOBEC 3A. The analyses provide a series of testable hypotheses that can be experimentally investigated in the future.

Sex-Specific HLA Alleles Contribute to the Modulation of COVID-19 Severity

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, responsible for Coronavirus Disease 2019 (COVID-19), exhibits a spectrum of clinical manifestations, ranging from asymptomatic to severe pulmonary dysfunction or death. The variability in COVID-19 severity has largely been attributed to the host's genetic characteristics, suggesting a polygenic genetic architecture, without significant strong evidence of sex-related genetic differences. In this Italian retrospective case-control study, we investigated the association between COVID-19 severity (severe vs. asymptomatic/oligosymptomatic healed individuals) and HLA gene variants, analyzed by next-generation sequencing (NGS). We identified significant HLA alleles (according to the conventional nomenclature), SNPs and haplotypes in the HLA-B, -C, -F, -DQA1, -DRB1, and -DRB5 genes associated with COVID-19 severity. Interestingly, these variants showed biological sex-related effects. Also, we identified specific haplotypes associated with COVID-19 severity that are shared by different conventional HLA alleles, indicated here as "super-haplotypes". These haplotypes had a biological sex-specific impact on disease severity and markedly increased the risk of severe COVID-19 compared to the conventional HLA alleles (odds ratio of up to 15). Our data suggest that the revision of the current HLA nomenclature may help to identify variants with a stronger effect on disease susceptibility and that association studies could benefit from the stratification of patients by biological sex. If replicated in other disease models, these findings could help to define the functional diversity in immune response between sexes, also based on the HLA system. Finally, due to the global pandemic's mortality rate, we hypothesize here that SARS-CoV-2 may have acted as a natural selection trigger, leading to a drift in HLA allelic frequencies in the general population.

Risk Factors for Long-Term Nutritional Disorders One Year After COVID-19: A Post Hoc Analysis of COVID-19 Recovery Study II

Background/Objectives: COVID-19 patients develop various clinical symptoms, including malnutrition. However, the risk factors for long-term nutritional disorders remain unclear. Identifying these factors is crucial for preventing nutritional disorders by initiating early nutritional interventions. Methods: This was a post hoc analysis of COVID-19 Recovery Study II (CORESII). The study included adult patients hospitalized for COVID-19 and discharged from the hospital. Information, including post-COVID-19 symptoms one month after onset and changes in daily life during the first year, was collected using a self-administered questionnaire sent one year after hospital discharge. We examined the association between baseline characteristics, disease severity, and symptoms that persisted one month after onset with malnutrition disorders one year after onset, defined as a Malnutrition Universal Screening Tool score ≥1, using a logistic regression analysis. Results: A total of 1081 patients (mean age of 56.0 years; 34% females; 38% admitted to the intensive care unit) were analyzed. Of these patients, 266 patients (24.6%) had malnutrition one year after onset. In a multivariable logistic regression analysis using variables that were significant in a univariate logistic regression analysis, the following factors were independently associated with malnutrition: BMI < 18.5 kg/m2 (odds ratio [95% confidence interval (CI)], 48.9 [14.3-168]), 18.5 ≤ BMI ≤ 20 (10.5 [5.89-18.8]), 30 < BMI (2.64 [1.84-3.75]), length of hospital stay (1.01 [1.00-1.02]), maintenance dialysis (3.19 [1.19-8.61]), and difficulty concentrating one month after onset (1.73 [1.07-2.79]). Conclusions: Being underweight or obese, prolonged hospitalization, maintenance dialysis, and difficulty concentrating one month after onset were associated with a risk of malnutrition one year post-illness. Patients with these factors may be at a high risk of long-term nutritional disorders.

Tissue-resident memory T cells contribute to protection against heterologous SARS-CoV-2 challenge

New vaccine formulations are based on circulating strains of virus, which have tended to evolve to more readily transmit human to human and to evade the neutralizing antibody response. An assumption of this approach is that ancestral strains of virus will not recur. Recurrence of these strains could be a problem for individuals not previously exposed to ancestral spike protein. Here, we addressed this by infecting mice with recent SARS-CoV-2 variants and then challenging them with a highly pathogenic mouse-adapted virus closely related to the ancestral Wuhan-1 strain (SARS2-N501YMA30). We found that challenged mice were protected from severe disease, despite having low or no neutralizing antibodies against SARS2-N501YMA30. T cell depletion from previously infected mice did not diminish infection against clinical disease, although it resulted in delayed virus clearance in the nasal turbinate and, in some cases, in the lungs. Levels of tissue-resident memory T cells were significantly elevated in the nasal turbinate of previously infected mice compared with that of naive mice. However, this phenotype was not seen in lung tissues. Together, these results indicate that the immune response to newly circulating variants afforded protection against reinfection with the ancestral virus that was in part T cell based.

Impact analysis of SARS-CoV-2 vaccination in patients treated with monoclonal antibodies: A monocentric experience

BACKGROUND

Since the discovery of SARS-CoV-2, no treatment has been able to completely eradicate the virus. The study aimed to evaluate the virological and clinical impact of the vaccination in SARS-CoV-2 infected patients treated with monoclonal antibodies (mAbs).

METHODS

This single-centre, observational, retrospective, real-life study was performed on SARS-CoV-2 symptomatic outpatients and inpatients treated with mAbs from March 2021 to November 2022 includes 726 patients. Each patient received available mAbs (bamlanivimab-etesevimab or casirivimab-indevimab or sotrovimab or tixagevimab-cilgavimab) according to the circulating virus strains. Age, comorbidities, vaccination status, death rates, duration of virological clearance, average length of stay, risk factors, and hospitalization or ICU admission were recorded.

RESULTS

Of 726 patients with complete data analyzed (median age 64), 516 outpatients and 210 inpatients were included. Vaccination status was known for all participants: 74.4 % and 51.7 % were vaccinated against SARS-CoV-2 among inpatients and outpatients, respectively. A shorter duration of virological clearance was observed in the vaccinated group, with a median of 16 days (IQR 15-17), compared to 19 days (IQR 18-21) in the unvaccinated group [HR 1.21; p < 0.032]. Multivariate analysis of virological clearance also showed statistical significance with tixagevimab cilgavimab 300 mg/300 mg (HR 2.73, p value < 0.001). No significant difference was found in worsening [OR 1,29; p = 0.57] and mortality [OR 0.65; p = 0.81] rates between vaccinated and unvaccinated patients treated with mAbs.

CONCLUSIONS

Key findings include a shorter duration of virological clearance in vaccinated outpatients but no significant differences in worsening or mortality rates between vaccinated and unvaccinated patients treated with mAbs. The study suggests a potential synergistic role of mAbs in accelerating virological clearance in vaccinated patients with mild to moderate COVID-19, with differing effects in hospitalized patients. Therefore, it is essential to implement health surveillance in high-risk patients with comorbidities in order to identify early any variants that might otherwise escape neutralizing antibodies.

Human behavior-based COVID-19 transmission in two dining spaces

Since December 2019, the COVID-19 pandemic has rapidly disseminated globally, posing significant threats to the world. The dining spaces are high-risk indoor environments for the transmission of SARS-CoV-2, posing challenges for intervention and control. This study, based on surveillance videos from two COVID-19 outbreak cases in restaurants, obtained real data on human behaviors of close contact and surface touch. A respiratory infectious disease transmission model was developed, incorporating four transmission routes: short-range airborne, long-range airborne, fomite and large droplet. The results indicate that diners and staff spent 21.9 %-28.7 % and 17.5 %-27.8 % of their time on speaking, respectively, while spending 85.9 %-90.7 % and 83.4 %-87.6 % of their time on surface touching. The primary transmission routes were short-range (contributing 5.8 %-70.9 %) and long-range airborne (contributing 28.4 %-93.0 %), with fomite and large droplet routes contributing less than 12.0 %. Staff-only mask wearing reduced infection risk by 12.8 %-31.8 %. It is recommended that mandatory mask wearing for staff is necessary, while diners should wear masks as much as possible, and that the equivalent ventilation rate of clean fresh air is suggested to 30.0 m3/ (h·person). This study provides a scientific support to make non-pharmaceutical interventions in dinning spaces.

Low Risk of Prolonged SARS-CoV-2 Shedding and Molecular Evolution in Kidney Transplant Recipients during the Omicron Era: A Prospective Observational Study

The aim of this prospective study was to assess the duration of culture-viable SARS-CoV-2 and to monitor the emergence of mutations in a cohort of 23 kidney transplant recipients (KTRs) from June 2022 to June 2023. Combined nares/oropharyngeal swabs were performed weekly starting as soon as possible after symptom onset. The time from symptom onset to a negative culture was (11 days (IQR 8-14), while time to negative RT-qPCR was 18 days (IQR 15-30). 21.7% had a positive culture beyond the first swab and 8.7% replicated viable virus for longer than 30 days. T-cell depletion (rate ratio 2.5, 95% CI 1.9, 3.3; p<0.001) and time from transplantation (rate ratio 0.93, 95% CI 0.90, 0.97; p=0.006) were associated with time of viable virus shedding. A cycle threshold (Ct) value of 24.2 demonstrated a 91.3% negative predictive value of viability (95% CI 76, 100). The odds of viability decreased by 69% per week of infection (OR 0.31, 95% CI 0.12, 0.76). Overall, RNA sequencing did not show accelerated molecular evolution though mutation rate could be increased in molnupiravir-treated KTRs. In conclusion, viable SARS-CoV-2 is eliminated rapidly, risk of virus evolution is low, and prolonged self-isolation is generally unnecessary for most KTRs.

A substitution at the cytoplasmic tail of the spike protein enhances SARS-CoV-2 infectivity and immunogenicity

BACKGROUND

Global dissemination of SARS-CoV-2 Omicron sublineages has provided a sufficient opportunity for natural selection, thus enabling beneficial mutations to emerge. Characterisation of these mutations uncovers the underlying machinery responsible for the fast transmission of Omicron variants and guides vaccine development for combating the COVID-19 pandemic.

METHODS

Through systematic bioinformatics analysis of 496,606 sequences of Omicron variants, we obtained 40 amino acid substitutions that occurred with high frequency in the S protein. Utilising pseudoviruses and a trans-complementation system of SARS-CoV-2, we identified the effect of high-frequency mutations on viral infectivity and elucidated the molecular mechanisms. Finally, we evaluated the impact of a key emerging mutation on the immune protection induced by the SARS-CoV-2 VLP mRNA vaccine in a murine model.

FINDINGS

We identified a proline-to-leucine substitution at the 1263rd residue of the Spike protein, and upon investigating the relative frequencies across multiple Omicron sublineages, we found a trend of increasing frequency for P1263L. The substitution significantly enhances the capacity for S-mediated viral entry and improves the immunogenicity of a virus-like particle mRNA vaccine. Mechanistic studies showed that this mutation is located in the FERM binding motif of the cytoplasmic tail and impairs the interaction between the S protein and the Ezrin/Radixin/Moesin proteins. Additionally, this mutation facilitates the incorporation of S proteins into SARS-CoV-2 virions.

INTERPRETATION

This study offers mechanistic insight into the constantly increasing transmissibility of SARS-CoV-2 Omicron variants and provides a meaningful optimisation strategy for vaccine development against SARS-CoV-2.

FUNDING

This study was supported by grants from the National Key Research and Development Plan of China (2021YFC2302405, 2022YFC2303200, 2021YFC2300200 and 2022YFC2303400), the National Natural Science Foundation of China (32188101, 32200772, 82422049, 82241082, 32270182, 82372254, 82271872, 82341046, 32100755 and 82102389), Shenzhen Medical Research Fund (B2404002, A2303036), the Shenzhen Bay Laboratory Startup Fund (21330111), Shenzhen San-Ming Project for Prevention and Research on Vector-borne Diseases (SZSM202211023), Yunnan Provincial Science and Technology Project at Southwest United Graduate School (202302AO370010). The New Cornerstone Science Foundation through the New Cornerstone Investigator Program, and the Xplorer Prize from Tencent Foundation.

Effect of vaccinations and school restrictions on the spread of COVID-19 in different age groups in Germany

With the emergence of SARS-CoV-2, various non-pharmaceutical interventions were adopted to control virus transmission, including school closures. Subsequently, the introduction of vaccines mitigated not only disease severity but also the spread of SARS-CoV-2. This study leveraged an adapted SIR model and non-linear mixed-effects modeling to quantify the impact of remote learning, school holidays, the emergence of Variants of Concern (VOCs), and the role of vaccinations in controlling SARS-CoV-2 spread across 16 German federal states with an age-stratified approach. Findings highlight a significant inverse correlation (Spearman's ρ = -0.92, p < 0.001) between vaccination rates and peak incidence rates across all age groups. Model-parameter estimation using the observed number of cases stratified by federal state and age allowed to assess the effects of school closure and holidays, considering adjustments for vaccinations and spread of VOCs over time. Here, modeling revealed significant (p < 0.001) differences in the virus's spread among pre-school children (0-4), children (5-11), adolescents (12-17), adults (18-59), and the elderly (60+). The transition to remote learning emerged as a critical measure in significantly reducing infection rates among children and adolescents (p < 0.001), whereas an increased infection risk was noted among the elderly during these periods, suggesting a shift in infection networks due to altered caregiving roles. Conversely, during school holiday periods, infection rates among adolescents mirrored those observed when schools were open. Simulation exercises based on the model provided evidence that COVID-19 vaccinations might serve a dual purpose: they protect the vaccinated individuals and contribute to the broader community's safety.

Effectiveness of a broad-spectrum bivalent mRNA vaccine against SARS-CoV-2 variants in preclinical studies

Vaccines utilizing modified messenger RNA (mRNA) technology have shown robust protective efficacy against SARS-CoV-2 in humans. As the virus continues to evolve in both human and non-human hosts, risk remains that the performance of the vaccines can be compromised by new variants with strong immune escape abilities. Here we present preclinical characterizations of a novel bivalent mRNA vaccine RQ3025 for its safety and effectiveness in animal models. The mRNA sequence of the vaccine is designed to incorporate common mutations on the SARS-CoV-2 spike protein that have been discovered along the evolutionary paths of different variants. Broad-spectrum, high-titer neutralizing antibodies against multiple variants were induced in mice (BALB/c and K18-hACE2), hamsters and rats upon injections of RQ3025, demonstrating advantages over the monovalent mRNA vaccines. Effectiveness in protection against several newly emerged variants is also evident in RQ3025-vaccinated rats. Analysis of splenocytes derived cytokines in BALB/c mice suggested that a Th1-biased cellular immune response was induced by RQ3025. Histological analysis of multiple organs in rats following injection of a high dose of RQ3025 showed no evidence of pathological changes. This study proves the safety and effectiveness of RQ3025 as a broad-spectrum vaccine against SARS-CoV-2 variants in animal models and lays the foundation for its potential clinical application in the future.

Dynamic expedition of leading mutations in SARS-CoV-2 spike glycoproteins

The continuous evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which caused the recent pandemic, has generated countless new variants with varying fitness. Mutations of the spike glycoprotein play a particularly vital role in shaping its evolutionary trajectory, as they have the capability to alter its infectivity and antigenicity. We present a time-resolved statistical method, Dynamic Expedition of Leading Mutations (deLemus), to analyze the evolutionary dynamics of the SARS-CoV-2 spike glycoprotein. The proposed L -index of the deLemus method is effective in quantifying the mutation strength of each amino acid site and outlining evolutionarily significant sites, allowing the comprehensive characterization of the evolutionary mutation pattern of the spike glycoprotein.

Integrated analyses of the transmission history of SARS-CoV-2 and its association with molecular evolution of the virus underlining the pandemic outbreaks in Italy, 2019-2023

BACKGROUND

Italy was significantly affected by the COVID-19 pandemic, experiencing multiple waves of infection following the sequential emergence of new variants. Understanding the transmission patterns and evolution of SARS-CoV-2 is vital for future preparedness.

METHODS

We conducted an analysis of viral genome sequences, integrating epidemiological and phylodynamic approaches, to characterize how SARS-CoV-2 variants have spread within the country.

RESULTS

Our findings indicate bidirectional international transmission, with Italy transitioning between importing and exporting the virus. Italy experienced four distinct epidemic waves, each associated with a significant reduction in fatalities from 2021 to 2023. These waves were primarily driven by the emergence of VOCs such as Alpha, Delta, and Omicron, which were reflected in observed transmission dynamics and effectiveness of public health measures.

CONCLUSIONS

The changing patterns of viral spread and variant prevalence throughout Italy's pandemic response underscore the continued importance of flexible public health strategies and genomic surveillance, both of which are crucial for tracking the evolution of variants and adapting control measures effectively to ensure preparedness for future outbreaks.

Dynamics of SARS-CoV-2 variants during the XBB wave in the Republic of Korea

As COVID-19 has become endemic, SARS-CoV-2 variants are becoming increasingly diverse, underscoring the escalating importance of global genomic surveillance. This study analyzed 86,762 COVID-19 samples identified in the Republic of Korea from September 2022 to November 2023. The results revealed a consistent increase in the prevalence of the XBB variants following the dominance of BN.1, with various XBB sub-lineages co-circulating in the Republic of Korea. The overall nucleotide diversity (π) among the SARS-CoV-2 genomes was 0.00155. Evolutionary analysis revealed that the average time interval between the first detection and estimated date of the most recent common ancestor of Korean XBB sub-lineages was 47 d, suggesting that the novel variants were efficiently identified in the Korean surveillance system. The mutation rate was determined to be in the range of 5.6 × 10-4 to 9.1 × 10-4 substitutions/site/year. In conclusion, this study provides insights into the genetic diversity and evolutionary interpretation of the XBB sub-lineages during the XBB wave in the Republic of Korea, highlighting the importance of continued genomic surveillance for emerging variants.

In silico prediction of pathogen's pandemic potential using the viral trait assessment for pandemics (ViTAP) model

Our world is ever evolving and interconnected, creating constant opportunities for disease outbreaks and pandemics to occur, making pandemic preparedness and pathogen management crucial for global health security. Early pathogen identification and intervention play a key role in mitigating the impacts of disease outbreaks. In this perspective, we present the Viral Trait Assessment for Pandemics (ViTAP) model to aid in the early identification of high-risk viruses that have pandemic potential, which incorporates lessons from past pandemics, including which key viral characteristics are important such as genetic makeup, transmission modes, mutation rates, and symptom severity. This model serves as the foundation for the development of powerful, quantitative tools for the early prediction of pandemic pathogens. The use of such a tool, in conjunction with other pandemic preparedness measures, can allow for early intervention and containment of the virus. This proactive approach could enable timely interventions, guiding public health responses, and resource allocation to prevent widespread outbreaks and mitigate the impact of emerging pathogens.

Revealing SARS-CoV-2 Mpro mutation cold and hot spots: Dynamic residue network analysis meets machine learning

Deciphering the effect of evolutionary mutations of viruses and predicting future mutations is crucial for designing long-lasting and effective drugs. While understanding the impact of current mutations on protein drug targets is feasible, predicting future mutations due to natural evolution of viruses and environmental pressures remains challenging. Here, we leveraged existing mutation data during the evolution of the SARS-CoV-2 protein drug target main protease (Mpro) to test the predictive power of dynamic residue network (DRN) analysis in identifying mutation cold and hot spots. We conducted molecular dynamics simulations on the Mpro of SARS-CoV-2 (Wuhan strain) and calculated eight DRN metrics (averaged BC, CC, DC, EC, ECC, KC, L, PR), each of which identifies a unique network feature within the protein. The sets of residues with the highest and lowest values for each metric, comprising potential cold and hot spots, were compared to published biochemical analyses and per residue mutation frequencies observed across five SARS-CoV-2 lineages, encompassing a total of 191,878 sequences. Individual DRN metrics displayed only modest power to predict the mutation frequency of individual residues. However, integrating the eight DRN metrics with additional structural and sequence-derived metrics allowed us to develop machine learning models which significantly improved the prediction of residue mutation frequency. While further refinements should enhance accuracy, we demonstrated a robust method to understand pathogen evolution. This approach can also guide the development of long-lasting drugs by targeting functional residues located in and near active site, and allosteric sites, that are less prone to mutations.

Unveiling the dynamics of respiratory infections revealed by multiplex PCR testing during the COVID-19 pandemic in Taiwan, 2020-2023

BACKGROUND

The emergence of SARS-CoV-2 in late 2019 sparked the global COVID-19 pandemic, leading to varied vaccine policies worldwide. The evolving patterns of respiratory pathogens, aside from SARS-CoV-2, during the pandemic have had a significant impact on the development of vaccine strategies.

METHODS

This study explores the landscape of respiratory pathogens, encompassing SARS-CoV-2, respiratory syncytial virus (RSV), and influenza viruses, through a retrospective analysis of data obtained from the BioFire Respiratory Panel 2.1 (RP 2.1) at China Medical University Hospital (Taichung, Taiwan) spanning from January 2020 to November 2023.

RESULTS

Among the 7950 respiratory samples studied, pediatric cases exhibited higher positivity (64.9%, 2488/3835) and mixed detection rates (43.8%, 1090/2488) than adults. Annual mixed detection rates increased (27.9-48%). Prevalence analysis revealed diverse patterns across age groups, with higher rates in pediatrics. Notably, human rhinovirus/enterovirus predominated (48.1%). Mixed detection illustrated viral co-detections, notably with parainfluenza viruses and adenovirus. Government policies and pandemic dynamics influenced infection patterns, with RSV resurgence after May 2022. Age-specific RSV detection demonstrated a shift, influencing vaccine considerations. Amid global vaccine initiatives, RSV's increasing trend in adults warrants attention.

CONCLUSIONS

This comprehensive analysis emphasizes the importance of multiplex PCR testing in shaping targeted vaccination strategies during evolving respiratory pathogen landscapes.

Antiviral combination treatment strategies for SARS-CoV-2 infection in immunocompromised patients

PURPOSE OF REVIEW

The purpose of this review is to report the available evidence regarding the use of combination regimens of antivirals and/or antibody-based therapy in the treatment of SARS-CoV-2 in immunocompromised patients.

RECENT FINDINGS

Literature search identified 24 articles, excluding single case reports, which included mainly patients with hematological malignancies and/or B-cell depletion. Data were divided based on the timing and reason for administration of combination treatment, that is, early treatment to prevent progression to severe COVID-19 and treatment of prolonged or relapsed infection. We described the treated populations, treatment duration and composition of combination treatment. We briefly addressed new treatment options and we proposed an algorithm for the management of COVID-19 infection in patients affected by hematological malignancies.

SUMMARY

Combination treatment seems an effective (73-100%) and well tolerated (<5% reported bradycardia, hepatotoxicity, neutropenia) strategy for treating prolonged/relapsed SARS-CoV-2 infections in the immunocompromised host, although its optimal composition and duration cannot be defined based on the currently available evidence. The role of combination treatment as an early treatment strategy for immunocompromised patients at a high risk of progression to severe disease/persistent shedding requires further evidence from comparison with monotherapy, even though high efficacy was reported for combinations of antivirals plus mAbs in case of previous viral variants.

Confounding amplifies the effect of environmental factors on COVID-19

The global COVID-19 pandemic has severely impacted human health and socioeconomic development, posing an enormous public health challenge. Extensive research has been conducted into the relationship between environmental factors and the transmission of COVID-19. However, numerous factors influence the development of pandemic outbreaks, and the presence of confounding effects on the mechanism of action complicates the assessment of the role of environmental factors in the spread of COVID-19. Direct estimation of the role of environmental factors without removing the confounding effects will be biased. To overcome this critical problem, we developed a Double Machine Learning (DML) causal model to estimate the debiased causal effects of the influencing factors in the COVID-19 outbreaks in Chinese cities. Comparative experiments revealed that the traditional multiple linear regression model overestimated the impact of environmental factors. Environmental factors are not the dominant cause of widespread outbreaks in China in 2022. In addition, by further analyzing the causal effects of environmental factors, it was verified that there is significant heterogeneity in the role of environmental factors. The causal effect of environmental factors on COVID-19 changes with the regional environment. It is therefore recommended that when exploring the mechanisms by which environmental factors influence the spread of epidemics, confounding factors must be handled carefully in order to obtain clean quantitative results. This study offers a more precise representation of the impact of environmental factors on the spread of the COVID-19 pandemic, as well as a framework for more accurately quantifying the factors influencing the outbreak.

Learning from the COVID-19 pandemic: A systematic review of mathematical vaccine prioritization models

As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.

Exposure to obinutuzumab does not affect outcomes of SARS-CoV-2 infection in vaccinated patients with newly diagnosed advanced-stage follicular lymphoma

URBAN is a multicentric, ambispective study evaluating the effectiveness and safety of obinutuzumab-based immuno-chemotherapy and maintenance in patients with untreated advanced follicular lymphoma (FL). The study began before the COVID-19 emergency declaration in Italy. It is currently ongoing for follow-up, and the enrolment timeline encompassed different stages of the pandemic, various vaccination roll-out phases and prevalence of SARS-CoV-2 variants. Outcomes of interest of the present sub-analysis included SARS-CoV-2 infection rates and COVID-19-related hospitalizations/deaths. At data cut-off, 86 (28.8%) and 213 patients (71.2%) were treated before and during/after the COVID-19 outbreak respectively; 294 (98.3%) completed the induction, 31 (10.4%) completed maintenance and 170 (56.9%) were still on maintenance. Overall, 245 patients (81.9%) received at least one SARS-CoV-2 vaccine dose: 13.5%, 31.4% and 55.1% received one, two and three doses respectively. We observed a substantial decrease in COVID-19-related mortality rates in pre- versus post-vaccination phases, along with a reduction in COVID-19-related outcomes due to the shift from alpha/delta to omicron variant predominance. No differences emerged between patients given maintenance or not, although the schedule was modified in 65% of cases. To our knowledge, URBAN represents the largest dataset of COVID-19-related outcomes in FL patients extensively exposed to obinutuzumab. ClinicalTrials.gov identifier: NCT04034056.

Emerging mutation in SARS-CoV-2 facilitates escape from NK cell recognition and associates with enhanced viral fitness

In addition to adaptive immunity, natural killer (NK) cells of the innate immune system contribute to the control of viral infections. The HLA-E-restricted SARS-CoV-2 Nsp13232-240 epitope VMPLSAPTL renders infected cells susceptible to NK cells by preventing binding to the inhibitory receptor NKG2A. Here, we report that a recently emerged methionine to isoleucine substitution at position 2 (pM2I) of Nsp13232-240 impairs binding of the mutated epitope to HLA-E and diminishes HLA-E/peptide complex stability. Structural analyses revealed altered occupancy of the HLA-E B-pocket as the underlying cause for reduced presentation and stability of the mutated epitope. Functionally, the reduced presentation of the mutated epitope correlated with elevated binding to NKG2A as well as with increased NK cell inhibition. Moreover, the pM2I mutation associated with enhanced estimated viral fitness and was transmitted to descendants of the SARS-CoV-2 BQ.1 variant. Interestingly, the mutated epitope resembles sequences of related peptides found in endemic common cold-causing human coronaviruses. Altogether, these findings indicate compromised peptide presentation as a viral adaptation to evade NK cell-mediated immunosurveillance by enabling enhanced presentation of self-peptide and restoring NKG2A-dependent inhibition of NK cells.

(R)evolution of Viruses: Introduction to biothermodynamics of viruses

As of 26 April 2024, the International Committee on Taxonomy of Viruses has registered 14690 virus species. Of these, only several dozen have been chemically and thermodynamically characterized. Every virus species is characterized by a specific empirical formula and thermodynamic properties - enthalpy, entropy and Gibbs energy. These physical properties are used in a mechanistic model of virus-host interactions at the cell membrane and in the cytoplasm. This review article presents empirical formulas and Gibbs energies for all major variants of SARS-CoV-2. This article also reports and suggests a mechanistic model of evolutionary changes, with the example of time evolution of SARS-CoV-2 from 2019 to 2024.

Spatiotemporal evolution and transmission dynamics of Alpha and Delta SARS-CoV-2 variants contributing to sequential outbreaks in Cambodia during 2021

BACKGROUND

Tracking the emergence, introduction and spread of SARS-CoV-2 variants of concern are essential for informing public health strategies. In 2021, Cambodia faced two major epidemic waves of SARS-CoV-2 triggered by the successive rise of the Alpha and Delta variants.

METHODS

Phylodynamic analysis of 1,163 complete SARS-CoV-2 genomes from Cambodia, along with global sequences, were conducted between February and September 2021 to infer viral introductions, molecular epidemiology and population dynamics. The relationship between epidemic trends and control strategies were evaluated. Bayesian phylogeographic reconstruction was employed to estimate and contrast the spatiotemporal dynamics of the Alpha and Delta variants over time.

RESULTS

Here we reveal that the Alpha variant displays rapid lineage diversification, accompanied by the acquisition of a spike E484K mutation that coincides with the national implementation of mass COVID-19 vaccination. Despite nationwide control strategies and increased vaccination coverage, the Alpha variant was quickly displaced by Delta variants that exhibits a higher effective reproductive number. Phylogeographic inference indicates that the Alpha variant was introduced through south-central region of Cambodia, with strong diffusion rates from the capital of Phnom Penh to other provinces, while the Delta variant likely entered the country via the northern border provinces.

CONCLUSIONS

Continual genomic surveillance and sequencing efforts, in combination with public health strategies, play a vital role in effectively tracking and responding to the emergence, evolution and dissemination of future emerging variants.

Optimal Annual COVID-19 Vaccine Boosting Dates Following Previous Booster Vaccination or Breakthrough Infection

BACKGROUND

COVID-19 booster vaccinations mitigate transmission and reduce the morbidity and mortality associated with infection. However, the optimal date for booster administration remains uncertain. Geographic variation in infection rates throughout the year makes it challenging to intuit the best yearly booster administration date to effectively prevent infection, and also challenging to provide best guidance on how to alter booster administration in response to a breakthrough infection.

METHODS

We leveraged longitudinal antibody and reinfection probabilities with spatiotemporal projections of COVID-19 incidence to develop a geographically informed approach to optimizing the timing of booster vaccination. We assessed the delay in booster vaccination that is warranted following breakthrough infections whenever they occur during the year, enabling a personalized assessment of optimal timing that acknowledges and respects diversity of COVID-19 immune status, addressing a substantial barrier to uptake.

RESULTS

Yearly booster vaccination on any date is beneficial to prevention of infection. However, each location exhibits as much as a 3-4-fold range in degree of protection by date of uptake. Optimal COVID-19 booster vaccination dates are location-specific, typically in early autumn in the Northern Hemisphere. Infection late in the interval between boosts substantially alters the optimal boosting date.

CONCLUSIONS

Considerable benefit accrues from aptly timing COVID-19 booster vaccination campaigns, which can be tailored to specific locations. Individuals can acquire the greatest benefit from booster vaccination by timing it optimally, including delaying in cases of infection late in the interval between boosts. These results provide location-specific guidance for public health policy, healthcare provider recommendations, and individual decision-making.

Predicting survival in patients with SARS-CoV-2 based on cytokines and soluble immune checkpoint regulators

Background

Coronavirus disease 2019 (COVID-19) has been widespread for over four years and has progressed to an endemic stage. Accordingly, the evaluation of host immunity in infected patients and the development of markers for prognostic prediction in the early stages have been emphasized. Soluble immune checkpoints (sICs), which regulate T cell activity, have been reported as promising biomarkers of viral infections.

Methods

In this study, quantitative values of 17 sICs and 16 cytokines (CKs) were measured using the Luminex multiplex assay. A total of 148 serum samples from 100 patients with COVID-19 were collected and the levels were compared between survivors vs. non-survivors and pneumonic vs. non-pneumonic conditions groups. The impact of these markers on overall survival were analyzed using a machine learning algorithm.

Results

sICs, including sCD27, sCD40, herpes virus entry mediator (sHVEM), T-cell immunoglobulin and mucin-domain containing-3 (sTIM-3), and Toll-like receptor 2 (sTLR-2) and CKs, including chemokine CC motif ligand 2 (CCL2), interleukin-6 (IL-6), IL-8, IL-10, IL-13, granulocyte-macrophage colony-stimulating factor (GM-CSF), and tumor necrosis factor-α (TNF- α), were statistically significantly increased in the non-survivors compared to those of in the survivors. IL-6 showed the highest area under the receiver-operating curve (0.844, 95% CI = 0.751-0.913) to discriminate non-survival, with a sensitivity of 78.9% and specificity of 82.4%. In Kaplan-Meier analysis, patients with procalcitonin over 0.25 ng/mL, C-reactive protein (CRP) over 41.0 mg/dL, neutrophil-to-lymphocyte ratio over 18.97, sCD27 over 3828.8 pg/mL, sCD40 over 1283.6 pg/mL, and IL-6 over 21.6 pg/mL showed poor survival (log-rank test). In the decision tree analysis, IL-6, sTIM-3, and sCD40 levels had a strong impact on survival. Moreover, IL-6, CD40, and CRP levels were important to predict the probability of 90-d mortality using the SHapley Additive exPlanations method.

Conclusion

sICs and CKs, especially IL-6, sCD27, sCD40, and sTIM-3 are expected to be useful in predicting patient outcomes when used in combination with existing markers.

Outcome of SARS-CoV-2 reinfection depends on genetic background in female mice

Antigenically distinct SARS-CoV-2 variants increase the reinfection risk for vaccinated and previously exposed population due to antibody neutralization escape. COVID-19 severity depends on many variables, including host immune responses, which differ depending on genetic predisposition. To address this, we perform immune profiling of female mice with different genetic backgrounds -transgenic K18-hACE2 and wild-type 129S1- infected with the severe B.1.351, 30 days after exposure to the milder BA.1 or severe H1N1. Prior BA.1 infection protects against B.1.351-induced morbidity in K18-hACE2 but aggravates disease in 129S1. H1N1 protects against B.1.351-induced morbidity only in 129S1. Enhanced severity in B.1.351 re-infected 129S1 is characterized by an increase of IL-10, IL-1β, IL-18 and IFN-γ, while in K18-hACE2 the cytokine profile resembles naïve mice undergoing their first viral infection. Enhanced pathology during 129S1 reinfection cannot be attributed to weaker adaptive immune responses to BA.1. Infection with BA.1 causes long-term differential remodeling and transcriptional changes in the bronchioalveolar CD11c+ compartment. K18-hACE2 CD11c+ cells show a strong antiviral defense expression profile whereas 129S1 CD11c+ cells present a more pro-inflammatory response upon restimulation. In conclusion, BA.1 induces cross-reactive adaptive immune responses in K18-hACE2 and 129S1, but reinfection outcome correlates with differential CD11c+ cells responses in the alveolar space.

The links between dietary diversity and RNA virus diversity harbored by the great evening bat (Ia io)

BACKGROUND

Predator‒prey interactions and their dynamic changes provide frequent opportunities for viruses to spread among organisms and thus affect their virus diversity. However, the connections between dietary diversity and virus diversity in predators have seldom been studied. The avivorous bats, Ia io, show a seasonal pattern of dietary diversity. Although most of them primarily prey on insects in summer, they mainly prey on nocturnally migrating birds in spring and autumn.

RESULTS

In this study, we characterized the RNA virome of three populations of I. io in Southwest China during summer and autumn using viral metatranscriptomic sequencing. We also investigated the relationships between dietary diversity and RNA virus diversity by integrating DNA metabarcoding and viral metatranscriptomic sequencing techniques at the population level of I. io. We found 55 known genera belonging to 35 known families of RNA viruses. Besides detecting mammal-related viruses, which are the usual concern, we also found a high abundance of insect-related viruses and some bird-related viruses. We found that insect-related viruses were more abundant in summer, while the bird-related viruses were predominantly detected in autumn, which might be caused by the seasonal differences in prey selection by I. io. Additionally, a significant positive correlation was identified between prey diversity and total virus diversity. The more similar the prey composition, the more similar the total virus composition and the higher the count of potential new viruses. We also found that the relative abundance of Picornaviridae increased with increasing prey diversity and body mass.

CONCLUSIONS

In this study, significant links were found between RNA virus diversity and dietary diversity of I. io. The results implied that dynamic changes in predator-prey interactions may facilitate frequent opportunities for viruses to spread among organisms. Video Abstract.

Cross-Section of Neurological Manifestations Among SARS-CoV-2 Omicron Subvariants-Single-Center Study

Background/Objectives: The Omicron variant of SARS-CoV-2 is undergoing constant mutation. New strains vary in neuropathogenicity and the neurological spectrum of disease. The aim of this study was to assess the frequency and clinical characteristics of neurological manifestations during the Omicron dominance among hospitalized patients, including the differences between three subsequent periods. Methods: This retrospective single-center study included 426 hospitalized adults with confirmed COVID-19 divided into three periods (O1, O2, and O3) dependent on the dominance of Omicron subvariants in Poland. Demographic and clinical data, in particular neurological manifestations, were collected and compared. Results: The median age of the group was 74, older in subsequent (later) periods. The number of patients with a history of previous SARS-CoV-2 infection or vaccination increased with the duration of the pandemic. The severity of COVID-19 became lower in successive periods. Neurological manifestations were observed in 55.4% of patients, and the most frequent were delirium, headache, myalgia, dizziness, cerebrovascular diseases, and encephalopathy. In subsequent periods of Omicron dominance, a higher frequency of neurological manifestations such as delirium, transient ischemic attack (TIA), and encephalopathy was observed. Headache or myalgia was related to a shorter hospitalization while delirium, cerebrovascular diseases, and ischemic stroke were linked with an increased risk of death. Conclusions: The Omicron variant of SARS-CoV-2 presents a wide spectrum of neurological manifestations. Although there is an improvement in the survival rate of patients with COVID-19, the frequency of neurological manifestations increases. The occurrence of delirium, cerebrovascular diseases, and ischemic stroke results in higher mortality.

Rapid Development of Small Rodent Animal Models for Infectious Disease Research Through Vectorized Receptor Molecule Expression

The emergence and re-emergence of pathogens with pandemic potential has been a persistent issue throughout history. Recent decades have seen significant outbreaks of zoonotic viruses from members of the Coronaviridae, Filoviridae, Paramyxoviridae, Flaviviridae, and Togaviridae families, resulting in widespread infections. The continual emergence of zoonotic viral pathogens and associated infections highlights the need for prevention strategies and effective treatments. Central to this effort is the availability of suitable animal models, which are essential for understanding pathogenesis and assessing transmission dynamics. These animals are also critical for evaluating the safety and efficacy of novel vaccines or therapeutics and are essential in facilitating regulatory approval of new products. Rapid development of animal models is an integral aspect of pandemic response and preparedness; however, their establishment is fraught by several rate-limiting steps, including selection of a suitable species, the logistical challenges associated with sharing and disseminating transgenic animals (e.g., the time-intensive nature of breeding and maintaining colonies), the availability of technical expertise, as well as ethical and regulatory approvals. A method for the rapid development of relevant animal models that has recently gained traction, in large part due to the COVID-19 pandemic, is the use of gene therapy vectors to express human viral receptors in readily accessible laboratory animals to enable virus infection and development of clinical disease. These models can be developed rapidly on any genetic background, making mechanistic studies and accelerated evaluation of novel countermeasures possible. In this review, we will discuss important considerations for the effective development of animal models using viral vector approaches and review the current vector-based animal models for studying viral pathogenesis and evaluating prophylactic and therapeutic strategies, with an emphasis on models of SARS-CoV-2 infection based on the vectorized expression of human angiotensin-converting enzyme 2.

Structure-guided mutations in CDRs for enhancing the affinity of neutralizing SARS-CoV-2 nanobody

The optimization of antibodies to attain the desired levels of affinity and specificity holds great promise for the development of next generation therapeutics. This study delves into the refinement and engineering of complementarity-determining regions (CDRs) through in silico affinity maturation followed by binding validation using isothermal titration calorimetry (ITC) and pseudovirus-based neutralization assays. Specifically, it focuses on engineering CDRs targeting the epitopes of receptor-binding domain (RBD) of the spike protein of SARS-CoV-2. A structure-guided virtual library of 112 single mutations in CDRs was generated and screened against RBD to select the potential affinity-enhancing mutations. Protein-protein docking analysis identified 32 single mutants of which nine mutants were selected for molecular dynamics (MD) simulations. Subsequently, biophysical ITC studies provided insights into binding affinity, and consistent with in silico findings, six mutations that demonstrated better binding affinity than native nanobody were further tested in vitro for neutralization activity against SARS-CoV-2 pseudovirus. Leu106Thr mutant was found to be most effective in virus-neutralization with IC50 values of ∼0.03 μM, as compared to the native nanobody (IC50 ∼0.77 μM). Thus, in this study, the developed computational pipeline guided by structure-aided interface profiles and thermodynamic analysis holds promise for the streamlined development of antibody-based therapeutic interventions against emerging variants of SARS-CoV-2 and other infectious pathogens.

Hydrogen-Bond-Induced Melem Assemblies to Resist Aggregation-Caused Quenching for Ultrasensitive ECL Detection of COVID-19 Antigen

Nowadays, aggregation-caused quenching (ACQ) of organic molecules in aqueous media seriously restricts their analytical and biomedical applications. In this work, hydrogen bond (H-bond) was utilized to resist the ACQ effect of 2,5,8-triamino-1,3,4,6,7,9,9b-heptaazaphenalene (Melem) as an advanced electrochemiluminescence (ECL) luminophore, whose ECL process was carefully studied in an aqueous K2S2O8 system coupled with electron paramagnetic resonance (EPR) measurements. Notably, the H-bond-induced Melem assemblies (Melem-H) showed 16.6-fold enhancement in the ECL signals as compared to the Melem aggregates (Melem-A), combined by elaborating the enhanced mechanism. On such basis, the effective ECL signal transduction was in situ achieved through the specific recognition of the double-stranded DNA embedded in Melem-H assemblies (Me-dsDNA) with spike protein (SP) of coronavirus disease 2019 (COVID-19). For that, such an ECL biosensor showed a wider linear range (1.0-125.0 pg mL-1) with a lower limit of detection (LOD) down to 0.45 pg mL-1, which also displayed acceptable results in analysis of human nasal swab samples. Therefore, the work provides a distinctive insight on addressing the ACQ effect and broadening the application scope of the organic emitter and offers a simple platform for biomedical detection.

CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting

With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.

Variation and evolution analysis of SARS-CoV-2 using self-game sequence optimization

Introduction

The evolution of SARS-CoV-2 has precipitated the emergence of new mutant strains, some exhibiting enhanced transmissibility and immune evasion capabilities, thus escalating the infection risk and diminishing vaccine efficacy. Given the continuous impact of SARS-CoV-2 mutations on global public health, the economy, and society, a profound comprehension of potential variations is crucial to effectively mitigate the impact of viral evolution. Yet, this task still faces considerable challenges.

Methods

This study introduces DARSEP, a method based on Deep learning Associates with Reinforcement learning for SARS-CoV-2 Evolution Prediction, combined with self-game sequence optimization and RetNet-based model.

Results

DARSEP accurately predicts evolutionary sequences and investigates the virus's evolutionary trajectory. It filters spike protein sequences with optimal fitness values from an extensive mutation space, selectively identifies those with a higher likelihood of evading immune detection, and devises a superior evolutionary analysis model for SARS-CoV-2 spike protein sequences. Comprehensive downstream task evaluations corroborate the model's efficacy in predicting potential mutation sites, elucidating SARS-CoV-2's evolutionary direction, and analyzing the development trends of Omicron variant strains through semantic changes.

Conclusion

Overall, DARSEP enriches our understanding of the dynamic evolution of SARS-CoV-2 and provides robust support for addressing present and future epidemic challenges.

Modified PEG-Lipids Enhance the Nasal Mucosal Immune Capacity of Lipid Nanoparticle mRNA Vaccines

BACKGROUND/OBJECTIVES

Omicron, the predominant variant of SARS-CoV-2, exhibits strong immune-evasive properties, leading to the reduced efficacy of existing vaccines. Consequently, the development of versatile vaccines is imperative. Intranasal mRNA vaccines offer convenient administration and have the potential to enhance mucosal immunity. However, delivering vaccines via the nasal mucosa requires overcoming complex physiological barriers. The aim of this study is to modify PEGylated lipids to enhance the mucosal immune efficacy of the vaccine.

METHODS

The PEGylated lipid component of lipid nanoparticle (LNP) delivery vectors was modified with chitosan or mannose to generate novel LNPs that enhance vaccine adhesion or targeting on mucosal surfaces. The impact of the mRNA encoding the receptor-binding domain of Omicron BA.4/BA.5 on the immune response was examined.

RESULTS

Compared to the unmodified LNP group, the IgG and IgA titers in the chitosan or mannose-modified LNP groups showed an increasing trend. The chitosan-modified group showed better effects. Notably, the PEGylated lipid with 1.5 mol% of chitosan modification produced high levels of IgG1 and IgG2a antibodies, promoting Th1/Th2 responses while also generating high levels of IgA, which can induce stronger cellular immunity, humoral immunity, and mucosal immunity.

CONCLUSIONS

The 1.5 mol% of chitosan-modified LNPs (mRNA-LNP-1.5CS) can serve as a safe and effective carrier for intranasal mRNA vaccines, offering a promising strategy for combating the Omicron variant.

Severity of respiratory syncytial virus compared with SARS-CoV-2 and influenza among hospitalised adults ≥65 years

INTRODUCTION

Our aim was to estimate the risk of pneumonia, admission to intensive care unit (ICU) or death in individuals ≥65 years old admitted to hospital with RSV, compared to influenza or COVID-19.

METHODS

We included hospitalised patients from Severe Acute Respiratory Infection Surveillance in Spain between 2021-2024, aged ≥65 years, laboratory confirmed for RSV, influenza or SARS-CoV-2. Using a binomial regression with logarithmic link, we estimated the relative risk (RR) of pneumonia, ICU admission and in-hospital mortality, in patients with RSV compared to influenza or SARS-CoV-2, adjusting for age, sex, season and comorbidities. We stratified the estimates by vaccination status for influenza or SARS-CoV2.

RESULTS

Among patients unvaccinated for influenza or SARS-CoV-2, those with RSV had similar or lower risk of pneumonia [vs. influenza: RR= 0.91 (95% Confidence Interval: 0.72-1.16); vs. SARS-CoV-2: 0.81 (0.67-0.98)], ICU admission [vs. influenza: 0.93 (0.41-2.08); vs. SARS-CoV-2: 1.10 (0.61-1.99)] and mortality [vs. influenza: 0.64 (0.32-1.28); vs. SARS-CoV-2: 0.56 (0.30-1.04)]. Among the vaccinated, results were largely similar except for a higher risk of ICU admission with RSV [vs. influenza: 2.13(1.16-3.89); vs. SARS-CoV-2: 1.83 (1.02-3.28)] CONCLUSIONS: RSV presented similar or lower intrinsic severity than influenza or SARS-CoV2. Among vaccinated patients, RSV was associated to higher ICU-admission, suggesting the potential for preventive RSV vaccination.

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases

Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanisms-are in dire need of more versatile and practical analytical approaches. Mass spectrometry (MS)-based molecular profiling methods can deliver a wealth of information on a range of functional molecules, including nucleic acids, proteins, and metabolites. While MS-driven omics analyses can yield vast datasets, the sheer complexity and multi-dimensionality of MS data can significantly hinder the identification and characterization of functional molecules within specific biological processes and events. Artificial intelligence (AI) emerges as a potent complementary tool that can substantially enhance the processing and interpretation of MS data. AI applications in this context lead to the reduction of spurious signals, the improvement of precision, the creation of standardized analytical frameworks, and the increase of data integration efficiency. This critical review emphasizes the pivotal roles of MS based omics strategies in the discovery of biomarkers and the clarification of infectious diseases. Additionally, the review underscores the transformative ability of AI techniques to enhance the utility of MS-based molecular profiling in the field of infectious diseases by refining the quality and practicality of data produced from omics analyses. In conclusion, we advocate for a forward-looking strategy that integrates AI with MS-based molecular profiling. This integration aims to transform the analytical landscape and the performance of biological molecule characterization, potentially down to the single-cell level. Such advancements are anticipated to propel the development of AI-driven predictive models, thus improving the monitoring of diagnostics and therapeutic discovery for the ongoing challenge related to infectious diseases.

Comparative analysis of mental health impairment among COVID-19 confirmed cases across the pandemic period in South Korea

OBJECTIVES

South Korea operates a complete enumeration surveillance of coronavirus disease 2019 (COVID-19). Online mental health survey links were distributed to all COVID-19 confirmed patients within three days of confirmation of infection. This study evaluates the trend of depressive symptoms, anxiety symptoms, post-traumatic stress symptoms, somatic symptoms, and suicidal ideation of COVID-19 confirmed cases across the pandemic from January 2020 to July 2022.

METHODS

A total of 99,055 responses were analyzed. Validated questionnaires were used to assess depressive symptoms (Patient Health Questionnaire-9), anxiety symptoms (Generalized Anxiety Disorder-7), post-traumatic stress symptoms (Primary Care Post Traumatic Stress Disorder screen), somatic symptoms (Patient Health Questionnaire-15), and suicidal ideation (P4 suicidality screener). Log-binomial regression was used to estimate prevalence ratio across 11 quarters (Q) of the year (2020Q1 to 2022Q3). Stratified analysis was conducted by sex to compare risk between males and females when adjusted prevalence was high.

RESULTS

Compared to 2022Q1 (January-March), all symptoms had their highest prevalence ratio during 2020Q1 to 2020Q3 (January-September). The difference in adjusted symptom prevalence between males and females was nonsignificant during high-risk periods.

CONCLUSIONS

Adverse mental health symptoms were most prevalent during the early pandemic, with a nonsignificant difference in prevalence observed between males and females. Greater attention should be given to individuals who experienced COVID-19 infection during the early stages of the pandemic.

Single-particle rotational sensing for analyzing the neutralization activity of antiviral antibodies

Due to the pathogen-specific targeting, neutralization capabilities, and enduring efficacy, neutralizing antibodies (NAs) have received widespread attentions as a critical immunotherapeutic strategy against infectious viruses. However, because of the high variability and complexity of pathogens, rapid determination of neutralization activity of antiviral antibodies remains a challenge. Here, we report a new method, named as out-of-plane polarization imaging based single-particle rotational sensing, for rapid analysis of neutralization activity of antiviral antibody against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Using the spike protein functionalized gold nanorods (AuNRs) and angiotensin-converting enzyme 2 (ACE2) coated gold nanoparticles (AuNPs) as the rotational sensors and chaperone probes, we demonstrated the single-particle rotational sensing strategy for the measurement of rotational diffusion coefficient of the chaperone-bound rotational sensors caused by the specific spike protein-ACE2 interactions. This enables us to measure the neutralizing activity of neutralizing antibody from the analysis of dose-dependent changes in rotational diffusion coefficient (Dr) of the rotational sensors upon the treatment of SARS-CoV-2 antibody. With this technique, we achieved the quantitative determination of neutralization activity of a commercially available SARS-CoV-2 antibody (IC50, 294.1 ng/mL) with satisfying accuracy and anti-interference ability. This simple and robust method holds the potential for rapid and accurate evaluation of neutralization activity against different pathogenic viruses.

Dissecting the dynamics of SARS-CoV-2 reinfections in blood donors with pauci- or asymptomatic COVID-19 disease course at initial infection

BACKGROUND

Understanding the dynamics of SARS-CoV-2 reinfections is crucial for public health policy, vaccine development, and long-term disease management. However, data on reinfections in the general population remains scarce.

OBJECTIVES

This study aimed to investigate SARS-CoV-2 antibody dynamics among Austrian blood donors, representing healthy adults, over two years following primary infection and to evaluate the reinfection risk.

METHODS

117,895 blood donations were analysed for SARS-CoV-2 total anti-N levels from June 2020 to December 2023. We examined anti-N and anti-S antibody dynamics and in vitro functionality in 230 study participants at five defined times during 24 months, assessing associations with demographics, vaccination status, and reinfection awareness.

RESULTS

The seroprevalence of SARS-CoV-2 infection-derived anti-N antibodies increased over time, reaching 90% by February 2023 and remaining at that level since then. According to serological screenings, we found an 88% reinfection rate, which is in contrast to participants' reports indicating a reinfection rate of 59%. Our data further reveal that about 26% of reinfections went completely unnoticed. Antibody dynamics were independent of age, sex, and ABO blood group. Interestingly, individuals with multiple reinfections reported symptoms more frequently during their primary infection. Our results further show that vaccination modestly affected reinfection risk and disease course.

CONCLUSION

SARS-CoV-2 reinfections were uncommon until the end of 2021 but became common with the advent of Omicron. This study highlights the underestimation of reinfection rates in healthy adults and underscores the need for continued surveillance, which is an important support for public health policies and intervention strategies.

Prevalence and Risk Factors of COVID-19 Reinfection in Patients with Rheumatoid Arthritis: A Retrospective Observational Study

PURPOSE

To identify the prevalence and risk factors of coronavirus disease 2019 (COVID-19) reinfection in patients with rheumatoid arthritis (RA).

MATERIALS AND METHODS

This study retrospectively analyzed patients with RA with a documented COVID-19 infection between January 2021 and December 2022 at a tertiary hospital in Seoul, South Korea. Reinfection was defined as a subsequent positive test result for severe acute respiratory syndrome coronavirus 2 at least 3 months after the initial infection. Cox proportional hazards models with backward elimination were employed to assess the association between potential risk factors and risk of reinfection.

RESULTS

Of 351 included patients with RA {female, 81.5%; median age, 58.0 years [interquartile range (IQR), 48.0-66.0]}, 252 (71.8%) were treated with methotrexate and 12 (3.4%) received leflunomide during the initial infection. Over a median follow-up of 1.5 (IQR, 1.1-1.6) years, 43 (12.3%) patients experienced reinfection, equating to an incidence rate of 8.97 per 100 patient-years. The median time interval between infections was 0.8 (IQR, 0.6-1.2) years. Among the risk factors, leflunomide use showed a significant association with reinfection (hazard ratio, 2.968; 95% confidence interval, 1.057-8.335; p=0.039). However, no significant changes occurred in disease activity following reinfection [disease activity score using 28 joints: baseline median, 2.3 (IQR, 1.9-2.8); post-reinfection median, 2.3 (IQR, 1.8-2.6), p for change=0.895].

CONCLUSION

In this retrospective cohort study of patients with RA with COVID-19 infection, approximately 12% of patients experienced reinfection without significant change in disease activity. Leflunomide use was associated with a higher risk of reinfection.

[Risk factors for a severe course of COVID-19 in a hotspot clinic during the first and second wave of the SARS-CoV-2 pandemic in Germany]

BACKGROUND

During the first wave of the SARS-CoV-2 pandemic, Weiden Hospital was a hotspot and was thus in an exceptional medical situation. This study deals with the question of whether the recognized risk factors for a severe course of COVID-19 also apply to the patients treated in Weiden Hospital during this time or whether other factors could have influenced patient outcomes.

METHODS

In a retrospective analysis, data on 669 patients of Weiden Hospital with proven SARS-CoV-2 infections in the first year of the pandemic were evaluated. Risk factors for a severe case of COVID-19 were determined from medical and demographic information in a univariate analysis and subjected to logistic regression. The logistic regression analysis was performed for the overall collective as well as separately for patients from Wave 1 (3-6/2020) and 2 (7-12/2020).

RESULTS

Looking at all of 2020, significant risk factors for severe COVID-19 included being male, being a smoker, being 71 years or older, and a history of depression. All other commonly recognized risk factors were not applicable for the Weiden collective. When looking at both waves separately, in Wave 1 age was not a significant risk factor, whereas in Wave 2 an age of 61 years or older was associated with an increased risk of severe progression. For patients who were admitted to hospital in Wave 2, the risk of severe progression was reduced almost by half.

CONCLUSION

It can be assumed that patient outcomes in Weiden's hotspot collective were predominantly determined by non-individual factors, like the difficult care situation in a hotspot clinic at the beginning of the pandemic. In preparation for future pandemics, provision of sufficient resources might significantly contribute to better patient outcomes.

Into the Cauldron of the Variant Soup: Insights into the Molecular Epidemiology and Transition to Endemicity of SARS-CoV-2 in Cyprus (November 2022-February 2024)

The coronavirus disease 2019 (COVID-19) pandemic, driven by the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been characterized by the virus's ongoing evolution, leading to the appearance of more transmissible variants that have often triggered infection surges. In this study, we analyzed the SARS-CoV-2 epidemic in Cyprus, utilizing 1627 viral sequences from infected individuals between November 2022 and February 2024. Over this period, 251 distinct lineages and sublineages were identified, predominantly categorized into three groups: Omicron 5, XBB, and JN.1 (parental lineage BA.2.86), all of which harbor S protein mutations linked to enhanced transmissibility and immune escape. Despite the relatively low numbers of new infections during this period, and the lack of any major waves, unlike earlier phases of the pandemic, these lineages demonstrated varying periods of dominance, with Omicron 5 prevailing from November 2022 to February 2023, XBB variants leading from March to November 2023, and JN.1 generating a wavelet from December 2023 to February 2024. These findings suggest that the SARS-CoV-2 epidemic in Cyprus has reached endemicity, with new variants gradually replacing previously circulating variants irrespective of seasonal patterns. This study highlights the critical importance of ongoing surveillance of SARS-CoV-2 evolution in Cyprus and emphasizes the role of preventive measures in limiting virus transmission, providing valuable insights for safeguarding public health.