Shared Antigen-specific CD8⁺ T cell Responses Against the SARS-COV-2 Spike Protein in HLA A*02:01 COVID-19 Participants

We report here on antigens from the SARS-CoV-2 virus spike protein, that when presented by Class I MHC, can lead to cytotoxic CD8⁺ T cell anti-viral responses in COVID-19 patients. We present a method in which the SARS-CoV-2 spike protein is converted into a library of peptide antigen-Major Histocompatibility Complexes (pMHCs) as single chain trimers that contain the peptide antigen, the MHC HLA allele, and the β-2 microglobulin sub-unit. That library is used to detect the evolution of virus-specific T cell populations from two COVID-19 patients, at two time points over the course of infection. Both patients exhibit similar virus-specific T cell populations, but very different time-trajectories of those populations. These results can be used to track those virus-specific T cell populations over the course of an infection, thus providing deep insight into the variations in immune system trajectories observed in different COVID-19 patients

Genetic Variability of Human Respiratory Syncytial Virus A Strains Circulating in Ontario: A Novel Genotype with a 72 Nucleotide G Gene Duplication

Human respiratory syncytial virus (HRSV) is the main cause of acute lower respiratory infections in children under 2 years of age and causes repeated infections throughout life. We investigated the genetic variability of RSV-A circulating in Ontario during 2010–2011 winter season by sequencing and phylogenetic analysis of the G glycoprotein gene

Socio-demographic predictors of not having private dental insurance coverage: machine-learning algorithms may help identify the disadvantaged

Abstract Background For accessing dental care in Canada, approximately 62% of the population has employment-based insurance, 6% have some publicly funded coverage, and 32% have to pay out-of pocket. Those with no insurance or public coverage find dental care more unaffordable compared to those with private insurance. To support the development of more comprehensive publicly funded dental care programs, it is important to understand the socio-demographic attributes of all those, who find dental care unaffordable. Methods This study is a secondary analysis of the data collected from Ontarians during the latest available cycle of the Canadian Community Health Survey (2017-18), a cross-sectional survey that collects information on health status, health care utilization, and health determinants for the Canadian population. First, bivariate analysis was conducted to determine the characteristics of Ontarians who lack dental insurance. Afterwards, we employed machine learning (ML) to analyze data and identify risk indicators for not having private dental insurance. Specifically, we trained several supervised ML models and utilized Shapley additive explanations (SHAP) to determine the relative feature importance for not having private dental insurance from the best ML model [the gradient boosting (GBM)]. Results Approximately one-third of Ontarians do not have private insurance coverage for dental care. Individuals with an income below $20,000, those unemployed or working part-time, seniors aged above 70, and those unable to afford to have their own housing are more at risk of not having private dental insurance, leading to financial barriers in accessing dental care. Conclusion In the future, government-funded programs can incorporate these identified risk indicators when determining eligible populations for publicly funded dental programs. Understanding these attributes is critical for developing targeted and effective interventions, ensuring equitable access to dental care for Canadians

Computational Approaches and Challenges to Developing Universal Influenza Vaccines

The traditional design of effective vaccines for rapidly-evolving pathogens, such as influenza A virus, has failed to provide broad spectrum and long-lasting protection. With low cost whole genome sequencing technology and powerful computing capabilities, novel computational approaches have demonstrated the potential to facilitate the design of a universal influenza vaccine. However, few studies have integrated computational optimization in the design and discovery of new vaccines. Understanding the potential of computational vaccine design is necessary before these approaches can be implemented on a broad scale. This review summarizes some promising computational approaches under current development, including computationally optimized broadly reactive antigens with consensus sequences, phylogenetic model-based ancestral sequence reconstruction, and immunomics to compute conserved cross-reactive T-cell epitopes. Interactions between virus-host-environment determine the evolvability of the influenza population. We propose that with the development of novel technologies that allow the integration of data sources such as protein structural modeling, host antibody repertoire analysis and advanced phylodynamic modeling, computational approaches will be crucial for the development of a long-lasting universal influenza vaccine. Taken together, computational approaches are powerful and promising tools for the development of a universal influenza vaccine with durable and broad protection

T cell memory to evolutionarily conserved and shared hemagglutinin epitopes of H1N1 viruses: a pilot scale study

Abstract Background The 2009 pandemic influenza was milder than expected. Based on the apparent lack of pre-existing cross-protective antibodies to the A (H1N1)pdm09 strain, it was hypothesized that pre-existing CD4+ T cellular immunity provided the crucial immunity that led to an attenuation of disease severity. We carried out a pilot scale study by conducting in silico and in vitro T cellular assays in healthy population, to evaluate the pre-existing immunity to A (H1N1)pdm09 strain. Methods Large-scale epitope prediction analysis was done by examining the NCBI available (H1N1) HA proteins. NetMHCIIpan, an eptiope prediction tool was used to identify the putative and shared CD4+ T cell epitopes between seasonal H1N1 and A (H1N1)pdm09 strains. To identify the immunogenicity of these putative epitopes, human IFN-γ-ELISPOT assays were conducted using the peripheral blood mononuclear cells from fourteen healthy human donors. All donors were screened for the HLA-DRB1 alleles. Results Epitope-specific CD4+ T cellular memory responses (IFN-γ) were generated to highly conserved HA epitopes from majority of the donors (93%). Higher magnitude of the CD4+ T cell responses was observed in the older adults. The study identified two HA2 immunodominant CD4+ T cell epitopes, of which one was found to be novel. Conclusions The current study provides a compelling evidence of HA epitope specific CD4+ T cellular memory towards A (H1N1)pdm09 strain. These well-characterized epitopes could recruit alternative immunological pathways to overcome the challenge of annual seasonal flu vaccine escape

Preexisting CD4+ T-Cell Immunity in Human Population to Avian Influenza H7N9 Virus: Whole Proteome-Wide Immunoinformatics Analyses

<div><p>In 2013, a novel avian influenza H7N9 virus was identified in human in China. The antigenically distinct H7N9 surface glycoproteins raised concerns about lack of cross-protective neutralizing antibodies. Epitope-specific preexisting T-cell immunity was one of the protective mechanisms in pandemic 2009 H1N1 even in the absence of cross-protective antibodies. Hence, the assessment of preexisting CD4+ T-cell immunity to conserved epitopes shared between H7N9 and human influenza A viruses (IAV) is critical. A comparative whole proteome-wide immunoinformatics analysis was performed to predict the CD4+ T-cell epitopes that are commonly conserved within the proteome of H7N9 in reference to IAV subtypes (H1N1, H2N2, and H3N2). The CD4+ T-cell epitopes that are commonly conserved (∼556) were further screened against the Immune Epitope Database (IEDB) to validate their immunogenic potential. This analysis revealed that 45.5% (253 of 556) epitopes are experimentally proven to induce CD4+ T-cell memory responses. In addition, we also found that 23.3% of CD4+ T-cell epitopes have ≥90% of sequence homology with experimentally defined CD8+ T-cell epitopes. We also conducted the population coverage analysis across different ethnicities using commonly conserved CD4+ T-cell epitopes and corresponding HLA-DRB1 alleles. Interestingly, the indigenous populations from Canada, United States, Mexico and Australia exhibited low coverage (28.65% to 45.62%) when compared with other ethnicities (57.77% to 94.84%). In summary, the present analysis demonstrate an evidence on the likely presence of preexisting T-cell immunity in human population and also shed light to understand the potential risk of H7N9 virus among indigenous populations, given their high susceptibility during previous pandemic influenza events. This information is crucial for public health policy, in targeting priority groups for immunization programs.</p></div

The role of cellular immunity in Influenza H1N1 population dynamics

Abstract Background Pre-existing cellular immunity has been recognized as one of the key factors in determining the outcome of influenza infection by reducing the likelihood of clinical disease and mitigates illness. Whether, and to what extent, the effect of this self-protective mechanism can be captured in the population dynamics of an influenza epidemic has not been addressed. Methods We applied previous findings regarding T-cell cross-reactivity between the 2009 pandemic H1N1 strain and seasonal H1N1 strains to investigate the possible changes in the magnitude and peak time of the epidemic. Continuous Monte-Carlo Markov Chain (MCMC) model was employed to simulate the role of pre-existing immunity on the dynamical behavior of epidemic peak. Results From the MCMC model simulations, we observed that, as the size of subpopulation with partially effective pre-existing immunity increases, the mean magnitude of the epidemic peak decreases, while the mean time to reach the peak increases. However, the corresponding ranges of these variations are relatively small. Conclusions Our study concludes that the effective role of pre-existing immunity in alleviating disease outcomes (e.g., hospitalization) of novel influenza virus remains largely undetectable in population dynamics of an epidemic. The model outcome suggests that rapid clinical investigations on T-cell assays remain crucial for determining the protection level conferred by pre-existing cellular responses in the face of an emerging influenza virus

Developing a temperature-driven map of the basic reproductive number of the emerging tick vector of Lyme disease Ixodes scapularis in Canada. J Theor Biol. 2013; 319: 50–61. doi: 10.1016/j.jtbi.2012.11.014 PMID: 23206385

c A deterministic model of the Lyme disease vector, I. scapularis, was developed. c The model was used to estimate R 0 for I scapularis under different climatic conditions. c A map of R 0 was developed for I scapularis in Canada, where this tick is emerging. c Estimation of R 0 for I. scapularis will assist public health responses to emerging Lyme disease. a r t i c l e i n f o a b s t r a c t A mechanistic model of the tick vector of Lyme disease, Ixodes scapularis, was adapted to a deterministic structure. Using temperature normals smoothed by Fourier analysis to generate seasonal temperaturedriven development rates and host biting rates, and a next generation matrix approach, the model was used to obtain values for the basic reproduction number (R 0 ) for I. scapularis at locations in southern Canada where the tick is established and emerging. The R 0 at Long Point, Point Pelee and Chatham sites where I. scapularis are established, was estimated at 1.5, 3.19 and 3.65, respectively. The threshold temperature conditions for tick population survival (R 0 ¼ 1) were shown to be the same as those identified using the mechanistic model (2800-3100 cumulative annual degree days 4 0 1C), and a map of R 0 for I. scapularis, the first such map for an arthropod vector, was drawn for Canada east of the Rocky Mountains. This map supports current risk assessments for Lyme disease risk emergence in Canada. Sensitivity analysis identified host abundance, tick development rates and summer temperatures as highly influential variables in the model, which is consistent with our current knowledge of the biology of this tick. The development of a deterministic model for I. scapularis that is capable of providing values for R 0 is a key step in our evolving ability to develop tools for assessment of Lyme disease risk emergence and for development of public health policies on surveillance, prevention and control

Temporal changes in respiratory adenovirus serotypes circulating in the greater Toronto area, Ontario, during December 2008 to April 2010

Abstract Background Certain adenovirus serotypes cause severe infections, especially in children. It is important to monitor temporal changes in serotypes causing clinical disease. The objective of this study was to document circulating respiratory adenovirus serotypes by sequencing adenovirus culture isolates from the Greater Toronto Area, Ontario, during December 2008 to April 2010. Methods Nucleic acid extraction was performed on 90 respiratory tract adenovirus culture isolates. PCR amplification was conducted with primers targeting the adenovirus hexon gene hypervariable region 7. Sanger sequencing and phylogenetic analyses were performed to determine serotype identities. Results Among 90 clinical respiratory isolates sequenced, eight different serotypes were identified. Serotype 3 (34, 38%), serotype 2 (30, 30%), and serotype 1 (14, 16%) isolates were most common; serotypes 5, 6, 11, 17 and 21 were also observed. Seventeen (50%) of the 34 HAdV-3 isolates were identified between December 2008 and February 2009, while none were identified from December 2009 to February 2010. Between December 2008 and April 2009, the two most common serotypes were HAdV-3 and HAdV-2, detected in 18 (53%) and 8 (24%) of the 34 cultures isolates, respectively. However, from December 2009 to April 2010, there was an increase in HAdV-2, which became the most prevalent serotype, detected in 10 (50%) of the 20 isolates identified (p = 0.05). Conclusions There was a gradual shift in prevailing adenovirus serotypes during the 17 month study period, from predominantly HAdV-3 to HAdV-2. If an adenovirus vaccine were to be broadly implemented, multiple serotypes should be included