key: cord-0843099-a7ve0dud authors: Dee, Kieran; Goldfarb, Daniel M; Haney, Joanne; Amat, Julien A R; Herder, Vanessa; Stewart, Meredith; Szemiel, Agnieszka M; Baguelin, Marc; Murcia, Pablo R title: Human rhinovirus infection blocks SARS-CoV-2 replication within the respiratory epithelium: implications for COVID-19 epidemiology date: 2021-03-23 journal: J Infect Dis DOI: 10.1093/infdis/jiab147 sha: 0d3bad819324b204c21d460a91c4cbacc536e4d1 doc_id: 843099 cord_uid: a7ve0dud Virus-virus interactions influence the epidemiology of respiratory infections. However, the impact of viruses causing upper respiratory infections on SARS-CoV-2 replication and transmission is currently unknown. Human rhinoviruses cause the common cold and are the most prevalent respiratory viruses of humans. Interactions between rhinoviruses and co-circulating respiratory viruses have been shown to shape virus epidemiology at the individual host and population level. Here, we examined the replication kinetics of SARS-CoV-2 in the human respiratory epithelium in the presence or absence of rhinovirus. We show that human rhinovirus triggers an interferon response that blocks SARS-CoV-2 replication. Mathematical simulations show that this virus-virus interaction is likely to have a population-wide effect as an increasing prevalence of rhinovirus will reduce the number of new COVID-19 cases. A c c e p t e d M a n u s c r i p t 5 The rapid spread of COVID-19 and its impact on global health highlights the importance of viral respiratory diseases. The human respiratory tract hosts a community of viruses that includes members of the Orthomyxoviridae (e.g., influenza virus A and B), Pneumoviridae (e.g., respiratory syncytial virus), Picornaviridae (e.g., rhinovirus), Coronaviridae (e.g., severe acute respiratory syndrome coronavirus 2) and others [1, 2] . We and others showed that interactions between co-circulating, taxonomically different respiratory viruses, can influence patterns of infection [3, 4] . We showed that human rhinoviruses (HRVs) and influenza A viruses (IAVs) interact negatively at the individual patient and population level. Additionally, it has been postulated that the circulation of HRV delayed the spread of pandemic H1N1 influenza virus in France in 2009 [5] . Viral interference interactions at the host level are considered important in influencing observed population dynamics. Wu et al. demonstrated that HRV induces an interferon (IFN) response that protects against subsequent IAV infection in differentiated airway cultures [4] , whereas Gonzalez et al. showed that RV attenuates influenza severity in a mouse model [6] . Non-pharmacological interventions have hampered our ability to determine the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the epidemiology of respiratory viruses. However, it is possible that the emergence of SARS-CoV-2 will affect their ecology. Co-infection studies using air-liquid interface cultures of differentiated respiratory epithelial cells can shed light on the nature of SARS-CoV-2 interactions with other viruses and their effect on virus replication. Here, we examined the replication kinetics of SARS-CoV-2 in the presence of HRV in the human respiratory epithelium. HRV was selected due to i) its high prevalence in the human population [7] ; ii) its negative interaction with IAV at the host and population level [3, 4] ; iii) its ability to induce a strong IFN response [4] ; and iv) the sensitivity of SARS-CoV-2 to IFN [8] . We used our experimental results as a proxy of within-host coinfection dynamics to simulate the impact of HRV circulation on the epidemiology of SARS-CoV-2 under different scenarios of HRV prevalence. A c c e p t e d M a n u s c r i p t assessed for cytopathic effect. Plates were scanned using a using the Celigo platform (Nexcelcom). Infection of 3 of 288 clones resulted in the clearance of the monolayer (2H6, 5F3 and 6F5). These clones were further assessed for changes in plaque morphology, and whether the well-clearance assay generated representative titers. They were further assessed for growth characteristics. Two of the three clones were discarded due and immunohistochemistry, anti-hACE2 was detected using EnVision+ anti-rabbit HRP (Agilent K4003). IF sections were imaged using a Zeiss LSM880 confocal microscope and IHC sections were imaged with an Olympus BX51 microscope. Statistical analysis and data visualisation were carried out in R 3.5.1 [12] . Multivariable logistic regression models were used to investigate significance among the different conditions. Those models accounted for biological replicates as this parameter was uneven, as well as treatment, and time post-infection. When biological replicate was not a significant parameter, this latter was removed to simplify the model. Models were run using the lme4 package [13] . Data visualisation and figures were generated using ggplot2 package [14] . M a n u s c r i p t 9 To determine if SARS-CoV-2 and HRV interact within the human respiratory epithelium, we and were undetectable at 48 hpi ( Figure 1A ). In contrast, HRV titers displayed the same kinetics in single and coinfections: they increased rapidly during the first 24 hours, followed by a gradual and sustained decline ( Figure 1B) . As simultaneous coinfections might not occur frequently during natural infection, we performed staggered coinfections of ALIcultures of HBECs as follows: cells were infected with HRV, and 24 hours later they were infected with SARS-CoV-2. This experiment was also repeated in the reverse order (i.e., SARS-CoV-2 first, followed by HRV). As observed in simultaneous coinfections, SARS-CoV-2 growth was severely impaired in both staggered coinfections: when SARS-CoV-2 inoculation was followed by HRV infection (p= 0.0260) SARS-CoV-2 replication increased between 24 and 48 hpi as seen in SARS-CoV-2 single infection, but a subsequent sharp decrease was observed between 48 and 96 hpi (Fig, 1C) . When HRV inoculation was followed by SARS-CoV-2 infection, SARS-CoV-2 replication did not exceed the inoculum titer and viral titers quickly declined (p= 0.0063) ( Figure 1D ). In contrast, the growth of HRV was unaffected by SARS-CoV-2 (p= 0.2027) regardless of the sequence order of infections ( Figure 1C and 1D) . When SARS-CoV-2 was inoculated first, the growth curve of HRV shifted and peaked at 72 hpi ( Figure 1C ), reflecting the delay in HRV inoculation. We tested if the observed reduction of SARS-CoV-2 titers was due to a block in virus entry due to HRV-A c c e p t e d M a n u s c r i p t 10 induced downregulation of the SARS-CoV-2 receptor, ACE2 [15] . To this end, we used immunohistochemistry to detect ACE2 in HRV or SARS-CoV-2 single infected and coinfected epithelial cells. We observed high levels of ACE2 expression on the apical surface of the epithelium regardless of the infection status of the cells ( Figure S1 ) suggesting that HRV blocks SARS-CoV-2 infection via mechanisms that are independent of virus entry. SARS-CoV-2 is susceptible to IFN and encodes multiple genes that alter signaling pathways upstream and downstream of IFN production [8] . As HRV induces an interferon-mediated innate immune response that blocks IAV in ALI-cultures [4] we hypothesized that the observed block in SARS-CoV-2 replication was due to an HRV-triggered IFN response. To test this, we used fluorescence microscopy to examine the IFN-mediated innate immune activation induced by each virus. Specifically, we compared the in situ expression of MxA, a protein encoded by an IFN-stimulated gene that is highly upregulated upon IFN production [11] . Figure 4A ). This confirms that the observed block in SARS-CoV-2 replication in coinfections with HRV was the result of negative interactions driven by the innate immune response induced by HRV. Interestingly, HRV replication was also increased in the presence of BX795 and titers plateau between 48 and 96 hpi, rather than declining as observed in the DMSO control coinfection and HRV single infection (Fig 4B) . This indicates that virus-induced innate immune signaling also hampers HRV replication in HBECs. Given the high prevalence of HRV, we wanted to test if the observed within-host interference could have an impact on the number of new COVID-19 cases in the population. We performed mathematical simulations using the moment generating function equation [16] to derive the change in the growth rate of SARS-CoV-2 infections as a result from having a fraction of the population refractory to COVID-19 due to an episode of HRV infection (Data analysis S1 in Supplementary Material). Our results show that the number of new SARS-CoV-2 infections decreases as the number of HRV infections increase, and this reduction increases with higher HRV prevalences and longer duration of the interference effect ( Figure 5 ). When SARS-CoV-2 growth rates are low, HRV circulation can lead to SARS-CoV-2 infections not spreading, whereas exponential growth is expected in the absence of HRV. Respiratory explants and ALI-cultures of human airway epithelium provide a highly controlled cellular environment that mimics to a considerable extent the natural site of infection and thus enables us to model the impact of virus tropism and innate immune responses on within-host infection dynamics [17] . Here we showed that HRV infection impairs SARS-CoV-2 replication and spread within the human respiratory epithelium. Our study shows that HRV exerts an indirect negative interaction, with a dominant inhibitory phenotype against SARS-CoV-2. Specifically, we showed that HRV triggers an IFN response that makes most cells nonpermissive to SARS-Cov-2 infection, while HRV is unaffected by the presence of SARS-A c c e p t e d M a n u s c r i p t 12 CoV-2. The susceptibility of SARS-CoV-2 to the IFN response is illustrated by the number of genes present in its genome that are devoted to overcome the innate immune response (reviewed in [18] ). We also showed that HRV hampers SARS-CoV-2 replication even when the former was inoculated 24 hours after SARS-CoV-2. Overall, our results demonstrate that viral interference interactions induced by HRV infection can inhibit SARS-CoV-2 replication in the respiratory epithelium and builds on previous epidemiological, modelling, and experimental work on virus-virus interactions [3] [4] [5] 19] . Future studies to elucidate the molecular mechanisms of viral interference could enable us to wield virus-virus interactions to our advantage and use them as control strategies or therapeutic measures. For example, screening for HRV-induced genes with anti-SARS-CoV-2 activity might constitute a future research avenue to develop antiviral therapies against coronaviruses. Recently, Wu et al. [4] showed that the IFN response triggered by HRV also interferes with 13 the gut virome [20] and also affect the immunogenicity of the live attenuated polio vaccine [21] . The nature of such interactions (i.e., positive, negative, or neutral) is largely unknown and likely to be influenced by the specific viruses involved, the timing of each infection and the interplay between the host's response to each virus. There is a vast body of knowledge on the impact of evolution on virus-host interactions [22] [23] [24] [25] . Many studies have focused on the evolutionary arms race between viruses and hosts, where the host's immune system evolves antiviral mechanisms to stop viral replication and viruses evolve to evade antiviral proteins. We propose that virus-virus interactions influence this arms race and contribute to shaping their molecular interplay. For example, it is feasible to think that HRV infections in humans might be mutually beneficial: from a HRV perspective, humans evolved a tightly regulated immune response that allows HRV to replicate and transmit while it blocks other potentially competing viruses. From a host's perspective, HRV infections, which are usually associated with mild disease, stimulate an antiviral response that prevents infections by more severe (and sometimes lethal) viruses such as SARS-CoV- Transmission routes of respiratory viruses among humans Extensive multiplex PCR diagnostics reveal new insights into the epidemiology of viral respiratory infections Virus-virus interactions impact the population dynamics of influenza and the common cold Interference between rhinovirus and influenza A virus: a clinical data analysis and experimental infection study Rhinoviruses delayed the circulation of the pandemic influenza A (H1N1) 2009 virus in France Attenuation of Influenza A Virus Disease Severity by Viral Coinfection in a Mouse Model Rhinoviruses and Respiratory Enteroviruses: Not as Simple as ABC Activation and evasion of type I interferon responses by SARS-CoV-2 Elevated temperature inhibits SARS-CoV-2 replication in respiratory epithelium independently of the induction of IFN-mediated innate immune defences Virology methods manual Mx genes: host determinants controlling influenza virus infection and trans-species transmission R: A language and environment for statistical computing Fitting linear mixed-effects models using lme4 ggplot2: elegant graphics for data analysis Structural and Functional Basis of SARS-CoV-2 Entry by Using Human ACE2 How generation intervals shape the relationship between growth rates and reproductive numbers Tropism, replication competence, and innate immune responses of the coronavirus SARS-CoV-2 in human respiratory tract and conjunctiva: an analysis in ex-vivo and in-vitro cultures Interplay between SARS-CoV-2 and the type I interferon response Possible interference between seasonal epidemics of influenza and other respiratory viruses in Hong Kong Viral complementation of immunodeficiency confers protection against enteric pathogens via interferon-lambda Influence of enteric infections on response to oral poliovirus vaccine: a systematic review and meta-analysis An evolutionary perspective on the broad antiviral specificity of MxA Evolution-guided functional analyses reveal diverse antiviral specificities encoded by IFIT1 genes in mammals Mutational resilience of antiviral restriction favors primate TRIM5alpha in host-virus evolutionary arms races The Evolution of Antiviral Defense Systems A c c e p t e d M a n u s c r i p t 14 A c c e p t e d M a n u s c r i p t 15 A c c e p t e d M a n u s c r i p t