Microneedles: An Emerging Vaccine Delivery Tool and a Prospective Solution to the Challenges of SARS-CoV-2 Mass Vaccination.

Vaccination is an effective measure to prevent infectious diseases. Protective immunity is induced when the immune system is exposed to a vaccine formulation with appropriate immunogenicity. However, traditional injection vaccination is always accompanied by fear and severe pain. As an emerging vaccine delivery tool, microneedles overcome the problems associated with routine needle vaccination, which can effectively deliver vaccines rich in antigen-presenting cells (APCs) to the epidermis and dermis painlessly, inducing a strong immune response. In addition, microneedles have the advantages of avoiding cold chain storage and have the flexibility of self-operation, which can solve the logistics and delivery obstacles of vaccines, covering the vaccination of the special population more easily and conveniently. Examples include people in rural areas with restricted vaccine storage facilities and medical professionals, elderly and disabled people with limited mobility, infants and young children afraid of pain. Currently, in the late stage of fighting against COVID-19, the main task is to increase the coverage of vaccines, especially for special populations. To address this challenge, microneedle-based vaccines have great potential to increase global vaccination rates and save many lives. This review describes the current progress of microneedles as a vaccine delivery system and its prospects in achieving mass vaccination against SARS-CoV-2.

Gene function and cell surface protein association analysis based on single-cell multiomics data.

Single-cell transcriptomics provides researchers with a powerful tool to resolve the transcriptome heterogeneity of individual cells. However, this method falls short in revealing cellular heterogeneity at the protein level. Previous single-cell multiomics studies have focused on data integration rather than exploiting the full potential of multiomics data. Here we introduce a new analysis framework, gene function and protein association (GFPA), that mines reliable associations between gene function and cell surface protein from single-cell multimodal data. Applying GFPA to human peripheral blood mononuclear cells (PBMCs), we observe an association of epithelial mesenchymal transition (EMT) with the CD99 protein in CD4 T cells, which is consistent with previous findings. Our results show that GFPA is reliable across multiple cell subtypes and PBMC samples. The GFPA python packages and detailed tutorials are freely available at https://github.com/studentiz/GFPA.

A Multivalent and Thermostable Nanobody Neutralizing SARS-CoV-2 Omicron (B.1.1.529).

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants have risen to dominance, which contains far more mutations in the spike protein in comparison to previously reported variants, compromising the efficacy of most existing vaccines or therapeutic monoclonal antibodies. Nanobody screened from high-throughput naïve libraries is a potential candidate for developing preventive and therapeutic antibodies. Methods: Four nanobodies specific to the SARS-CoV-2 wild-type receptor-binding domain (RBD) were screened from a naïve phage display library. Their affinity and neutralizing activity were evaluated by surface plasmon resonance assays, surrogate virus neutralization tests, and pseudovirus neutralization assays. Preliminary identification of the binding epitopes of nanobodies by peptide-based ELISA and competition assay. Then four multivalent nanobodies were engineered by attaching the monovalent nanobodies to an antibody-binding nanoplatform constructed based on the lumazine synthase protein cage nanoparticles isolated from the Aquifex aeolicus (AaLS). Finally, the differences in potency between the monovalent and multivalent nanobodies were compared using the same methods. Results: Three of the four specific nanobodies could maintain substantial inhibitory activity against the Omicron (B.1.1.529), of them, B-B2 had the best neutralizing activity against the Omicron (B.1.1.529) pseudovirus (IC50 = 1.658 µg/mL). The antiviral ability of multivalent nanobody LS-B-B2 was improved in the Omicron (B.1.1.529) pseudovirus assays (IC50 = 0.653 µg/mL). The results of peptide-based ELISA indicated that LS-B-B2 might react with the linear epitopes in the SARS-CoV-2 RBD conserved regions, which would clarify the mechanisms for the maintenance of potent neutralization of Omicron (B.1.1.529) preliminary. Conclusion: Our study indicated that the AaLS could be used as an antibody-binding nanoplatform to present nanobodies on its surface and improve the potency of nanobodies. The multivalent nanobody LS-B-B2 may serve as a potential agent for the neutralization of SARS-CoV-2 variants.

A Multivalent and Thermostable Nanobody Neutralizing SARS-CoV-2 Omicron (B.1.1.529)

Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants have risen to dominance, which contains far more mutations in the spike protein in comparison to previously reported variants, compromising the efficacy of most existing vaccines or therapeutic monoclonal antibodies. Nanobody screened from high-throughput naïve libraries is a potential candidate for developing preventive and therapeutic antibodies. Methods Four nanobodies specific to the SARS-CoV-2 wild-type receptor-binding domain (RBD) were screened from a naïve phage display library. Their affinity and neutralizing activity were evaluated by surface plasmon resonance assays, surrogate virus neutralization tests, and pseudovirus neutralization assays. Preliminary identification of the binding epitopes of nanobodies by peptide-based ELISA and competition assay. Then four multivalent nanobodies were engineered by attaching the monovalent nanobodies to an antibody-binding nanoplatform constructed based on the lumazine synthase protein cage nanoparticles isolated from the Aquifex aeolicus (AaLS). Finally, the differences in potency between the monovalent and multivalent nanobodies were compared using the same methods. Results Three of the four specific nanobodies could maintain substantial inhibitory activity against the Omicron (B.1.1.529), of them, B-B2 had the best neutralizing activity against the Omicron (B.1.1.529) pseudovirus (IC50 = 1.658 μg/mL). The antiviral ability of multivalent nanobody LS-B-B2 was improved in the Omicron (B.1.1.529) pseudovirus assays (IC50 = 0.653 μg/mL). The results of peptide-based ELISA indicated that LS-B-B2 might react with the linear epitopes in the SARS-CoV-2 RBD conserved regions, which would clarify the mechanisms for the maintenance of potent neutralization of Omicron (B.1.1.529) preliminary. Conclusion Our study indicated that the AaLS could be used as an antibody-binding nanoplatform to present nanobodies on its surface and improve the potency of nanobodies. The multivalent nanobody LS-B-B2 may serve as a potential agent for the neutralization of SARS-CoV-2 variants.

Modeling and analyzing single-cell multimodal data with deep parametric inference.

The proliferation of single-cell multimodal sequencing technologies has enabled us to understand cellular heterogeneity with multiple views, providing novel and actionable biological insights into the disease-driving mechanisms. Here, we propose a comprehensive end-to-end single-cell multimodal analysis framework named Deep Parametric Inference (DPI). DPI transforms single-cell multimodal data into a multimodal parameter space by inferring individual modal parameters. Analysis of cord blood mononuclear cells (CBMC) reveals that the multimodal parameter space can characterize the heterogeneity of cells more comprehensively than individual modalities. Furthermore, comparisons with the state-of-the-art methods on multiple datasets show that DPI has superior performance. Additionally, DPI can reference and query cell types without batch effects. As a result, DPI can successfully analyze the progression of COVID-19 disease in peripheral blood mononuclear cells (PBMC). Notably, we further propose a cell state vector field and analyze the transformation pattern of bone marrow cells (BMC) states. In conclusion, DPI is a powerful single-cell multimodal analysis framework that can provide new biological insights into biomedical researchers. The python packages, datasets and user-friendly manuals of DPI are freely available at https://github.com/studentiz/dpi.

Effects of COVID-19 Non-Pharmacological Interventions on Dengue Infection: A Systematic Review and Meta-Analysis.

Non-pharmacological interventions (NPIs) implemented during the coronavirus disease 2019 (COVID-19) pandemic have demonstrated significant positive effects on other communicable diseases. Nevertheless, the response for dengue fever has been mixed. To illustrate the real implications of NPIs on dengue transmission and to determine the effective measures for preventing and controlling dengue, we performed a systematic review and meta-analysis of the available global data to summarize the effects comprehensively. We searched Embase, PubMed, and Web of Science in line with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines from December 31, 2019, to March 30, 2022, for studies of NPI efficacy on dengue infection. We obtained the annual reported dengue cases from highly dengue-endemic countries in 2015-2021 from the European Centre for Disease Prevention and Control to determine the actual change in dengue cases in 2020 and 2021, respectively. A random-effects estimate of the pooled odds was generated with the Mantel-Haenszel method. Between-study heterogeneity was assessed using the inconsistency index (I2 ) and subgroup analysis according to country (dengue-endemic or non-endemic) was conducted. This review was registered with PROSPERO (CRD42021291487). A total of 17 articles covering 32 countries or regions were included in the review. Meta-analysis estimated a pooled relative risk of 0.39 (95% CI: 0.28-0.55), and subgroup revealed 0.06 (95% CI: 0.02-0.25) and 0.55 (95% CI: 0.44-0.68) in dengue non-endemic areas and dengue-endemic countries, respectively, in 2020. The majority of highly dengue-endemic countries in Asia and Americas reported 0-100% reductions in dengue cases in 2020 compared to previous years, while some countries (4/20) reported a dramatic increase, resulting in an overall increase of 11%. In contrast, there was an obvious reduction in dengue cases in 2021 in almost all countries (18/20) studied, with an overall 40% reduction rate. The overall effectiveness of NPIs on dengue varied with region and time due to multiple factors, but most countries reported significant reductions. Travel-related interventions demonstrated great effectiveness for reducing imported cases of dengue fever. Internal movement restrictions of constantly varying intensity and range are more likely to mitigate the entire level of dengue transmission by reducing the spread of dengue fever between regions within a country, which is useful for developing a more comprehensive and sustainable strategy for preventing and controlling dengue fever in the future.

Bioinformatics and System Biology Approach to Identify the Influences of COVID-19 on Rheumatoid Arthritis.

Background: Severe coronavirus disease 2019 (COVID -19) has led to a rapid increase in mortality worldwide. Rheumatoid arthritis (RA) was a high-risk factor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, whereas the molecular mechanisms underlying RA and CVOID-19 are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19 and RA using bioinformatics and a systems biology approach. Methods: Two Differentially expressed genes (DEGs) sets extracted from GSE171110 and GSE1775544 datasets were intersected to generate common DEGs, which were used for functional enrichment, pathway analysis, and candidate drugs analysis. Results: A total of 103 common DEGs were identified in the two datasets between RA and COVID-19. A protein-protein interaction (PPI) was constructed using various combinatorial statistical methods and bioinformatics tools. Subsequently, hub genes and essential modules were identified from the PPI network. In addition, we performed functional analysis and pathway analysis under ontological conditions and found that there was common association between RA and progression of COVID-19 infection. Finally, transcription factor-gene interactions, protein-drug interactions, and DEGs-miRNAs coregulatory networks with common DEGs were also identified in the datasets. Conclusion: We successfully identified the top 10 hub genes that could serve as novel targeted therapy for COVID-19 and screened out some potential drugs useful for COVID-19 patients with RA.

Pre-Existing Cross-Reactive Antibody Responses Do Not Significantly Impact Inactivated COVID-19 Vaccine-Induced Neutralization.

Recent exposure to seasonal coronaviruses (sCoVs) may stimulate cross-reactive antibody responses against severe acute respiratory syndrome CoV 2 (SARS-CoV-2). However, previous studies have produced divergent results regarding protective or damaging immunity induced by prior sCoV exposure. It remains unknown whether pre-existing humoral immunity plays a role in vaccine-induced neutralization and antibody responses. In this study, we collected 36 paired sera samples from 36 healthy volunteers before and after immunization with inactivated whole-virion SARS-CoV-2 vaccines for COVID-19, and analyzed the distribution and intensity of pre-existing antibody responses at the epitope level pre-vaccination as well as the relationship between pre-existing sCoV immunity and vaccine-induced neutralization. We observed large amounts of pre-existing cross-reactive antibodies in the conserved regions among sCoVs, especially the S2 subunit. Excep t for a few peptides, the IgG and IgM fluorescence intensities against S, M and N peptides did not differ significantly between pre-vaccination and post-vaccination sera of vaccinees who developed a neutralization inhibition rate (%inhibition) <40 and %inhibition ≥40 after two doses of the COVID-19 vaccine. Participants with strong and weak pre-existing cross-reactive antibodies (strong pre-CRA; weak pre-CRA) had similar %inhibition pre-vaccination (10.9% ± 2.9% vs. 12.0% ± 2.2%, P=0.990) and post-vaccination (43.8% ± 25.1% vs. 44.6% ± 21.5%, P=0.997). Overall, the strong pre-CRA group did not show a significantly greater increase in antibody responses to the S protein linear peptides post-vaccination compared with the weak pre-CRA group. Therefore, we found no evidence for a significant impact of pre-existing antibody responses on inactivated vaccine-induced neutralization and antibody responses. Our research provides an important basis for inactivated SARS-CoV-2 vaccine use in the context of high sCoV seroprevalence.

Advances in Neutralization Assays for SARS-CoV-2

Abstract The coronavirus disease 2019 (COVID-19) pandemic has triggered a global health emergency and brought disaster to humans. Tremendous efforts have been made to control the pandemic, among which neutralizing antibodies (NAbs) are of specific interest to researchers. Neutralizing antibodies are generated within weeks after infection or immunization, and can protect cells from virus intrusion and confer protective immunity to cells. Thus, production of NAbs is considered as a main goal for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines and NAbs may be used for patient treatment in the form of monoclonal antibodies. Neutralization assays are capable of quantitatively detecting NAbs against SARS-CoV-2, allowing to explore the relationship between the level of NAbs and the severity of the disease, and may predict the possibility of re-infection in COVID-19 patients. They can also be used to test the effects of monoclonal antibodies, convalescent plasma and vaccines. At present, wild-type virus neutralization assay remains the gold standard for measuring NAbs;while pseudovirus neutralization assays, Surrogate virus neutralization test (sVNT), and high-throughput versions of neutralization assays are popular alternatives with their own advantages and disadvantages. In this review article, we summarize the characteristics and recent progress of SARS-CoV-2 neutralization assays. Special attention is given to the current limitations of various neutralization assays so as to promote new possible strategies with NAbs by which rapid SARS-CoV-2 serological diagnosis and antiviral screening in the future will be achieved.

Preliminary analysis on the early epidemic and spatiotemporal distribution of COVID-19 in Guangdong Province

Objective: The epidemic of Corona Virus disease 20l9 (COVID-l9) in Guangdong province during January 19, and February 7, 2020 was evaluated to provide evidence for the prevention and control of the COVID- l9 outbreak.

Epidemiologic Characteristics, Transmission Chain, and Risk Factors of Severe Infection of COVID-19 in Tianjin, a Representative Municipality City of China.

This study was performed to describe the epidemiologic characteristics of coronavirus disease 2019 (COVID-19) and explore risk factors for severe infection. Data of all 131 confirmed cases in Tianjin before February 20 were collected. By February 20, a total of 14/16 districts reported COVID-19 cases, with Baodi district reporting the most cases (n = 56). A total of 22 (16.8%) cases had a Wuhan-related exposure. Fever was the most common symptom (82.4%). The median duration of symptom onset to treatment was [1.0 (0.0-4.0) days], the duration of symptom onset to isolation [2.0 (0.0-6.0) days], and the duration of symptom onset to diagnosis [5.0 (2.0-8.0) days]. The analysis of the transmission chain showed two cluster infections with 62 cases infected. Transmission from a family member constituted 42%, usually at the end of transmission chain. Compared with patients with non-severe infections, patients with severe infections were more likely to be male (46.2 vs. 77.3%, P = 0.009) and had a Wuhan-related exposure (14.0 vs. 40.9%, P = 0.004). Multivariate logistic regression showed that male (OR 3.913, 95% CI 1.206, 12.696; P = 0.023) was an independent risk factor for severe infection. This study provides evidence on the epidemic of COVID-19 by analyzing the epidemiological characteristics of confirmed cases in Tianjin. Self-quarantine at an outbreak's early stage, especially for those with high-risk exposures, is conducive to prevent the transmission of infection. Further investigation is needed to confirm the risk factors for severe COVID-19 infection and investigate the mechanisms involved.