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Despite the availability of effective vaccines, the persistence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suggests that cocirculation with other pathogens and resulting multiepidemics (of, for example, COVID-19 and influenza) may become increasingly frequent. To better forecast and control the risk of such multiepidemics, it is essential to elucidate the potential interactions of SARS-CoV-2 with other pathogens; these interactions, however, remain poorly defined. Here, we aimed to review the current body of evidence about SARS-CoV-2 interactions. Our review is structured in four parts. To study pathogen interactions in a systematic and comprehensive way, we first developed a general framework to capture their major components: sign (either negative for antagonistic interactions or positive for synergistic interactions), strength (i.e., magnitude of the interaction), symmetry (describing whether the interaction depends on the order of infection of interacting pathogens), duration (describing whether the interaction is short-lived or long-lived), and mechanism (e.g., whether interaction modifies susceptibility to infection, transmissibility of infection, or severity of disease). Second, we reviewed the experimental evidence from animal models about SARS-CoV-2 interactions. Of the 14 studies identified, 11 focused on the outcomes of coinfection with nonattenuated influenza A viruses (IAVs), and 3 with other pathogens. The 11 studies on IAV used different designs and animal models (ferrets, hamsters, and mice) but generally demonstrated that coinfection increased disease severity compared with either monoinfection. By contrast, the effect of coinfection on the viral load of either virus was variable and inconsistent across studies. Third, we reviewed the epidemiological evidence about SARS-CoV-2 interactions in human populations. Although numerous studies were identified, only a few were specifically designed to infer interaction, and many were prone to multiple biases, including confounding. Nevertheless, their results suggested that influenza and pneumococcal conjugate vaccinations were associated with a reduced risk of SARS-CoV-2 infection. Finally, fourth, we formulated simple transmission models of SARS-CoV-2 cocirculation with an epidemic viral pathogen or an endemic bacterial pathogen, showing how they can naturally incorporate the proposed framework. More generally, we argue that such models, when designed with an integrative and multidisciplinary perspective, will be invaluable tools to resolve the substantial uncertainties that remain about SARS-CoV-2 interactions.
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http://dx.doi.org/10.1371/journal.ppat.1011167 | DOI Listing |
J Virol
September 2025
Université catholique de Louvain, de Duve Institute, Brussels, Belgium.
Unrelated pathogens, including viruses and bacteria, use a common short linear motif (SLiM) to interact with cellular kinases of the RSK (p90 S6 ribosomal kinase) family. Such a "DDVF" (D/E-D/E-V-F) SLiM occurs in the leader (L) protein encoded by picornaviruses of the genus , including Theiler's murine encephalomyelitis virus (TMEV), Boone cardiovirus (BCV), and Encephalomyocarditis virus (EMCV). The L-RSK complex is targeted to the nuclear pore, where RSK triggers FG-nucleoporins hyperphosphorylation, thereby causing nucleocytoplasmic trafficking disruption.
View Article and Find Full Text PDFInfect Dis Poverty
September 2025
Faculty of Medicine and Pharmaceutical Sciences, University of Douala, Douala, Cameroon.
Background: Little is documented on key community-based One Health (OH) approach implementation, pro-activeness and effectiveness of interactions and strategies against Mpox outbreak public health emergency in international concern (PHEIC) in various African countries in order to stamp out the persisting Mpox outbreak threat and burden. Prioritizing critical community-based interventions and lessons learned from previous COVID-19, Mpox, Ebola, COVID-19, Rift Valley Fever and Marburg virus outbreaks revealed critical shortcomings in funding, surveillance, and community engagement that plague public health initiatives across the continent. The article provides critical insights and benefits of community-based One Health approaches implementation against Mpox outbreak management in Africa.
View Article and Find Full Text PDFBMC Public Health
September 2025
Department of Mathematics, Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau, Gottlieb-Daimler-Str.48, Kaiserslautern, 67663, Germany.
We study the dynamics of coexisting influenza and SARS-CoV-2 by adapting a well-established age-specific COVID-19 model to a multi-pathogen framework. Sensitivity analysis and adjustment of the model to real-world data are used to investigate the influence of age-related factors on disease dynamics. Our findings underscore the critical role that transmission rates play in shaping the spread of influenza and COVID-19.
View Article and Find Full Text PDFEMBO J
September 2025
New York University Grossman School of Medicine, Microbiology Department, New York, NY, USA.
Serine protease inhibitors (SERPINs) are involved in various physiological processes and diseases, such as inflammation, cancer metastasis, and neurodegeneration. Their role in viral infections is poorly understood, as their expression patterns during infection and the range of proteases they target have yet to be fully characterized. Here, we show widespread expression of human SERPINs in response to respiratory virus infections, both in bronchioalveolar lavages from COVID-19 patients and in polarized human airway epithelial cultures.
View Article and Find Full Text PDFCell Rep Methods
September 2025
Lingang Laboratory, Shanghai 201306, China. Electronic address:
While affinity purification-mass spectrometry (AP-MS) has significantly advanced protein-protein interaction (PPI) studies, its limitations in detecting weak, transient, and membrane-associated interactions remain. To address these challenges, we introduced a proteomic method termed affinity purification coupled proximity labeling-mass spectrometry (APPLE-MS), which combines the high specificity of Twin-Strep tag enrichment with PafA-mediated proximity labeling. This method achieves improved sensitivity while maintaining high specificity (4.
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