Host-Pathogen Interactions During Pathogenic Human Coronavirus Infection: 2nd Edition

A special issue of Pathogens (ISSN 2076-0817). This special issue belongs to the section "Viral Pathogens".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 5065

Special Issue Editor


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Guest Editor
School of Medicine and Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA
Interests: host-pathogen interactions; RSV; SARS-CoV-2; cytoskeletal inflammation; respiratory diseases; live-attenuated vaacine; HMPV; HPIV; IAV; organ-on-chip; air-liquid interface
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Special Issue Information

Dear Colleagues,

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, a causative agent of coronavirus disease 2019 (COVID-19)), is an enveloped virus responsible for the current never-ending pandemic, which began when the virus emerged in December 2019 in Wuhan, China. SARS-CoV-2 spreads from human to human through aerosol and respiratory droplet-based virus transmission. SARS-CoV-2 contains a non-segmented, positive-sense, single-strand RNA genome. With this genome, two-thirds of viral RNA is translated into large polyproteins, and a discontinuous transcription process transcribes the remainder of the viral genome into a nested set of subgenomic mRNAs, thus making it unique. Respiratory viruses appear to be diverse in cellular tropism, resulting in differences in virus-induced pathobiology, e.g., respiratory syncytial virus causes bronchiolitis, but SARS-COV-2 primarily causes pneumonia. Unlike many respiratory viruses, SARS-CoV-2 causes a systemic infection, resulting in multiorgan infection and severe pathophysiology.

This Special Issue will cover a broad understanding of SARS-CoV-2 infection, including cell tropism, strain and variants, pathophysiology, ARDS, vaccine and therapeutics, vaccine injury, treatment, animal models, viral protein characterization, genome, immune response, cytoskeletal signaling, and the convalescent stage of SARS-CoV-2 infection.

Dr. Masfique Mehedi
Guest Editor

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Keywords

  • COVID-19
  • spike
  • mRNA
  • goblet cell
  • viremia
  • pneumonia
  • convalescent
  • antibody
  • transmission

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Related Special Issue

Published Papers (3 papers)

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Research

14 pages, 1428 KB  
Article
Estimating the Optimal COVID-19 Booster Timing Using Surrogate Correlates of Protection: A Longitudinal Antibody Study in Naïve and Previously Infected Individuals
by Yoshihiro Fujiya, Ryo Kobayashi, Makito Tanaka, Ema Suzuki, Shiro Hinotsu, Mami Nakae, Yuki Sato, Yuki Katayama, Masachika Saeki, Yuki Yakuwa, Shinya Nirasawa, Akemi Endoh, Koji Kuronuma and Satoshi Takahashi
Pathogens 2025, 14(11), 1138; https://doi.org/10.3390/pathogens14111138 - 10 Nov 2025
Viewed by 465
Abstract
Standardized, one-size-fits-all COVID-19 booster schedules may be suboptimal due to individual variation in immune backgrounds, particularly prior infection, which induces robust hybrid immunity. This study estimated optimal booster timing by modeling antibody decay in relation to surrogate correlates of protection (CoP). In a [...] Read more.
Standardized, one-size-fits-all COVID-19 booster schedules may be suboptimal due to individual variation in immune backgrounds, particularly prior infection, which induces robust hybrid immunity. This study estimated optimal booster timing by modeling antibody decay in relation to surrogate correlates of protection (CoP). In a prospective cohort of 177 Japanese healthcare workers, we longitudinally monitored anti-spike receptor-binding domain (S-RBD) antibody titers following BNT162b2 vaccination. Participants were stratified into SARS-CoV-2-naïve and previously infected groups. Mixed-effects models were developed to predict when antibody titers would decline below predefined CoP thresholds. The model estimated optimal booster timing after a two-dose primary series to be 3–5 months for naïve individuals and approximately one year for those with prior infection. Following a third dose, the estimated interval extended to 8–12 months for the naïve group and 1.5–2 years for the previously infected group. These substantial differences underscore the limitations of uniform booster schedules. Our findings provide a quantitative framework for personalized vaccination strategies based on individual antibody profiles and immune status, thereby optimizing protection. Full article
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9 pages, 1150 KB  
Communication
The Overlooked Nucleocapsid Response: A Cohort Study of SARS-CoV-2 Vaccines in Brazil
by Fatima de Cássia Evangelista de Oliveira, Ana Carolina Matias Dinelly Pinto, Maria Francilene Souza Silva, Max Moreira Lizano Garcia, Maria da Conceição Rodrigues Fernandes, Gabriela Alexandria Damasceno, Amanda Campelo Lima de Melo, Tamires Cardoso Matsui, Tamiris de Fátima Goebel de Souza, Fernanda Gadelha Severino, Virgínia Angélica Silveira Reis, Caroline Passaes, Fernanda Montenegro de Carvalho Araújo, Luiz Odorico Monteiro de Andrade and Marcela Helena Gambim Fonseca
Pathogens 2025, 14(5), 445; https://doi.org/10.3390/pathogens14050445 - 30 Apr 2025
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Abstract
SARS-CoV-2 has caused global disruptions, prompting studies on immune responses to COVID-19 vaccines, particularly antibodies against the Spike (S) protein. However, responses to the Nucleocapsid (N) protein remain less explored. This study evaluated whether CoronaVac induces anti-N antibodies, and analyzed antibody dynamics after [...] Read more.
SARS-CoV-2 has caused global disruptions, prompting studies on immune responses to COVID-19 vaccines, particularly antibodies against the Spike (S) protein. However, responses to the Nucleocapsid (N) protein remain less explored. This study evaluated whether CoronaVac induces anti-N antibodies, and analyzed antibody dynamics after a BNT162b2 booster, given that CoronaVac targets both S and N proteins, while BNT162b2 targets only the S protein. Serum samples were collected at multiple intervals post-vaccination. The percentage of participants with positive anti-N antibodies increased from 40.26% to 62.09% after two doses of CoronaVac, but declined over time, reaching 29.07% and 18.87% after the second and third doses, respectively. However, seropositivity rose to 43.48% three months after the booster. Anti-S antibody levels peaked at 31,394 AU/mL after the booster, compared to 723.4 AU/mL after the first dose. These findings indicate that CoronaVac stimulates antibody responses against both S and N proteins. Monitoring antibody dynamics is crucial for optimizing vaccination strategies, particularly for high-risk populations, to help control COVID-19. Full article
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17 pages, 1084 KB  
Article
Interleukin-1 Beta rs16944 and rs1143634 and Interleukin-6 Receptor rs12083537 Single Nucleotide Polymorphisms as Potential Predictors of COVID-19 Severity
by Inas A. Ahmed, Taghrid G. Kharboush, Hiba S. Al-Amodi, Hala F. M. Kamel, Ehab Darwish, Asmaa Mosbeh, Hossam A. Galbt, Amal M. Abdel-Kareim and Shimaa Abdelsattar
Pathogens 2024, 13(10), 915; https://doi.org/10.3390/pathogens13100915 - 21 Oct 2024
Cited by 2 | Viewed by 2862
Abstract
Host genetic variation has been recognized as a key predictor of diverse clinical sequelae among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients. Insights into the link between the Interleukin-6 receptor (IL-6R) and Interleukin-1 beta (IL-1β) genetic variation and severe coronavirus disease 2019 [...] Read more.
Host genetic variation has been recognized as a key predictor of diverse clinical sequelae among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected patients. Insights into the link between the Interleukin-6 receptor (IL-6R) and Interleukin-1 beta (IL-1β) genetic variation and severe coronavirus disease 2019 (COVID-19) are crucial for developing new predictors and therapeutic targets. We aimed to investigate the association of IL-6R rs12083537, IL-1β rs16944, and IL-1β rs1143634 SNPs with the severity of COVID-19. Our study was conducted on 300 COVID-19-negative individuals (control group) and 299 COVID-19-positive cases, classified into mild, moderate, and severe subgroups. Analyses of IL-1β (rs16944, rs1143634) and IL-6R (rs12083537) SNPs’ genotypes were performed using qPCR genotyping assays. The IL-1β (rs16944) CC genotype and IL-6R (rs12083537) GG genotype were substantially related to COVID-19 severity, which was also associated with comorbidities and some laboratory parameters (p < 0.001). The IL-1β (rs1143634) TT genotype was found to be protective. Likewise, the IL-1β (rs16944) CC genotype was associated with increased mortality. IL-1β rs16944 and IL-6R rs12083537 SNPs are promising potential predictors of SARS-CoV-2 disease severity. Meanwhile, the rs1143634 SNP T allele was protective against severity and mortality risk. Full article
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