key: cord-1033215-1tx3tl0f
authors: Clark, Jordan J.; Penrice-Randal, Rebekah; Sharma, Parul; Kipar, Anja; Dong, Xiaofeng; Davidson, Andrew; Williamson, Maia Kavanagh; Matthews, David A.; Turtle, Lance; Prince, Tessa; Hughes, Grant L.; Patterson, Edward I.; Shawli, Ghada; Subramaniam, Krishanthi; Sharp, Jo; McLaughlin, Lynn; Zhou, En-Min; Turner, Joseph D.; Marriott, Amy E.; Colombo, Stefano; Pennington, Shaun H.; Biagini, Giancarlo; Owen, Andrew; Hiscox, Julian A.; Stewart, James P.
title: Sequential infection with influenza A virus followed by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to more severe disease and encephalitis in a mouse model of COVID-19
date: 2020-10-13
journal: bioRxiv
DOI: 10.1101/2020.10.13.334532
sha: f659d286695bc9b92408dc2293cd4c173223e997
doc_id: 1033215
cord_uid: 1tx3tl0f

COVID-19 is a spectrum of clinical symptoms in humans caused by infection with SARS-CoV-2, a recently emerged coronavirus that has rapidly caused a pandemic. Coalescence of a second wave of this virus with seasonal respiratory viruses, particularly influenza virus is a possible global health concern. To investigate this, transgenic mice expressing the human ACE2 receptor driven by the epithelial cell cytokeratin-18 gene promoter (K18-hACE2) were first infected with IAV followed by SARS-CoV-2. The host response and effect on virus biology was compared to K18-hACE2 mice infected with IAV or SARS-CoV-2 only. Infection of mice with each individual virus resulted in a disease phenotype compared to control mice. Although SARS-CoV-2 RNA synthesis appeared significantly reduced in the sequentially infected mice, these mice had a more rapid weight loss, more severe lung damage and a prolongation of the innate response compared to singly infected or control mice. The sequential infection also exacerbated the extrapulmonary manifestations associated with SARS-CoV-2. This included a more severe encephalitis. Taken together, the data suggest that the concept of ‘twinfection’ is deleterious and mitigation steps should be instituted as part of a comprehensive public health response to the COVID-19 pandemic.

Coronaviruses were once described as the backwater of virology but the last two decades have seen the emergence of three major coronavirus threats 1 Infection of humans with SARS-CoV-2 results in a range of clinical symptoms, from asymptomatic to severe infection and subsequent death in both at risk individuals but also a small proportion of otherwise healthy individuals across all age groups. Severe infection in humans is typified by cytokine storms 2,3 , pneumonia and kidney failure.

Examination of post-mortem tissue reveals a disconnect between viral replication and immune pathology 4 . A range of other symptoms also occur, including gastrointestinal symptoms such as vomiting, diarrhoea, abdominal pain and loss of appetite. A small number of patients present without any overt respiratory symptoms at all. Typically, patients with severe COVID-19 present to hospital in the second week of illness. There is often a precipitous decline in respiratory function, without necessarily much in the way of "air hunger." Once intubated, these patients have unique ventilatory characteristics, where they can be ventilated with relatively low inspired oxygen concentrations but need high positive end expiratory pressures.

Respiratory infections in humans and animals can also be synergistic in which an initial infection can exacerbate a secondary infection or vice versa. When multiple pathogens are in circulation at the same time this can lead to cooperative or competitive forms of pathogen-pathogen interactions 5 . This was evident during the 1918 Spanish influenza A virus outbreak (IAV) where secondary bacterial pneumonia was thought to be a leading cause of death 6 . Co-infections in other viral diseases, such as patients with Ebola virus disease, have also been shown to contribute to the host response and outcome 7 . As many countries move from a period of lock down from the summer months the incidence of SARS-CoV-2 infection is likely to increase in frequency as is currently being witnessed in several European countries. The onset of winter in the Northern Hemisphere has coincided with a second and possible seasonal wave of SARS-CoV-2 that is likely to be co-incident with other respiratory pathogens. In most temperate sites the usual seasonal respiratory coronavirus peak occurs either slightly before or simultaneously with the IAV and influenza B virus peaks, and this may occur with SARS-CoV-2. Generally, human coronaviruses display winter seasonality between the months of December and April and are not detected in summer months 8 . This is a similar pattern seen with influenza viruses. Between 11 to 41% of patients with normal human coronavirus infection test positive for other respiratory viruses 8 . Our hypothesis was that co-circulation of SARS-CoV-2 and IAV could lead to co-infection, and if so, this may exacerbate clinical disease and potentially outcome.

Previous work has shown co-infections are present in patients with severe coronavirus infection. For SARS-CoV co-circulation of human metapneumovirus was reported in an outbreak in Hong Kong. However, data suggested that outcomes were not different between patients with identified co-infections and those with SARS-CoV alone 9 . For MERS-CoV, four cases of co-infection with influenza A virus were described, and although no data was presented on the severity of symptoms this sample size would be too small to generate any meaningful conclusions 10 . Post-mortem studies from patients with COVID-19 in Beijing (n=85) identified IAV in 10% of patients, influenza B virus in 5% of patients and 3% of patients had RSV, but the absence of a carefully selected control arm prohibits conclusions to be drawn 11 . Recently there have been several case reports of coinfections with IAV and SARS-CoV-2 in humans with severe outcomes [12] [13] [14] [15] [16] [17] with one study from the UK reporting that patients with a coinfection exhibiting a ~6 times higher risk of death 18 . Whilst this suggests that coinfection is synergistic, this study also found that the risk of testing positive for SARS-CoV-2 was 68% lower among individuals who were positive for IAV infection, implying that the two viruses may competitively exclude each other 18 .

Whilst the analysis of post-mortem tissue is extremely informative in what may have led to severe coronavirus infection and death, the analysis of the disease in severe (but living cases) is naturally restricted by what tissues can be sampled (e.g. blood, nasopharyngeal swabs and bronchial alveolar lavages). Therefore, animal models of COVID-19 present critical tools to fill knowledge gaps for the disease in humans and for screening therapeutic or prophylactic interventions. Compatibility with a more extensive longitudinal tissue sampling strategy and a controlled nature of infection are key advantages of animal models 19 . Studies in an experimental mouse model of SARS-CoV showed that co-infection of a respiratory bacterium exacerbated pneumonia 20 . Different animal species can be infected with wild-type SARS-CoV-2 to serve as models of COVID-19 and these include mice, hamsters, ferrets, rhesus macaques and cynomolgus macaques. The K18-hACE2 transgenic (K18-hACE2) mouse, where hACE2 expression is driven by the epithelial cell cytokeratin-18 (K18) promoter, was developed to study SARS-CoV pathogenesis 21 . This mouse is now being used as a model that mirrors many features of severe COVID-19 infection in humans to develop understanding of the mechanistic basis of lung disease and to test pharmacological interventions 22, 23 .

With the approaching flu season in the Northern hemisphere concomitant with a second wave of SARS-CoV-2 infections there is an obvious public health concern about the possibility of enhanced morbidity and mortality in co-infected individuals.

The aim of this work was to use an established pre-clinical model of COVID-19 to study the consequences of co-infection with SARS-CoV-2 and IAV, defining the associated clinical, pathological and transcriptomic signatures.

To assess how co-infection with influenza virus affected COVID-19, the established K18-hACE2 mouse model of SARS-CoV-2 was utilised 21 . We sued a clinical isolate of SARS-CoV-2 (strain hCoV-19/England/Liverpool_REMRQ0001/2020) 24 .

Importantly, sequence of the virus stock demonstrated that this isolate did not contain the recently observed deletion or mutations of the furin cleavage site in the S protein 25 . A schematic of the experimental design is shown in Fig. 1A . Four groups of mice (n = 8 per group) were used. At day 0, two groups were inoculated intranasally with 10 2 PFU IAV (strain A/X31) and two groups with PBS. After three days, two groups were inoculated intranasally with 10 4 PFU of SARS-CoV-2. This generated four experimental groups: Control, IAV only, SARS-CoV-2 and IAV + SARS-CoV-2 only (Fig. 1B) . Control mice maintained their body weight throughout. Mice infected with IAV displayed a typical pattern of weight loss, reaching a nadir (mean 17% loss) at 7 dpi before starting recovery. SARS-CoV-2-infected animals started to lose weight at day 7 (4 dpi) and carried on losing weight up to day 10 (mean 15% loss). Mice infected with IAV then SARS-CoV-2 had a significantly-accelerated weight loss as compared with IAV-infected mice from day 4 which was most severe at day 6 (mean 19%), followed by a recovery to day 8 (mean 14% loss) before losing weight again (mean 17% loss) ( Fig. 2A) . As well as accelerated weight loss, IAV + SARS-CoV-2-infected mice exhibited more severe respiratory symptoms and a significantly more rapid mortality, (assessed by a humane endpoint of 20% weight loss) as compared with mice infected with either virus alone (Fig. 2B ). In order to determine whether the coinfection of SARS-CoV-2 and IAV was cooperative or competitive total RNA was extracted from the lungs of the K18-hACE2 mice and viral loads were quantified using qRT-PCR. At day 6 (3 dpi), the SARS-CoV-2 infected mice exhibited 10,000-fold higher levels of viral load than at day 10 (7 dpi) (mean 6 x 10 12 vs 2.8 x 10 8 copies of N/µg of RNA) indicating that peak viral replication takes place before the onset of symptoms at 4 dpi (Fig, 3A) . At this timepoint the mice infected with SARS-CoV-2 alone displayed significantly higher levels of viral RNA than the mice coinfected with IAV and SARS-COoV-2 (mean 6 x 10 12 vs ~2 x 1 0 9 copies of N/µg of RNA) (Fig. 3A) . However, by day 10 the coinfected and singly infected mice exhibited nearly identical levels of SARS-CoV-2 RNA (mean 2 x 10 8 vs 8.1 x 10 8 copies of N/µg of RNA) (Fig. 3A) . Conversely, at day 6, the mice infected with IAV alone showed similar levels of IAV RNA compared to the coinfected mice (mean 1.3 x 10 7 vs 1 x 10 7 copies of M/µg of RNA) and by day 10 both the singly infected mice and coinfected mice did not display any detectable IAV RNA, demonstrating similar levels of IAV clearance (Fig. 3C) . In order to investigate viral replication qPCR was employed to quantify viral subgenomic mRNA (sgRNA) transcripts. Unlike viral genomes, sgRNAs are not incorporated into virions, and can therefore be utilised to measure active virus infection. The amount of sgRNA in the SARS-CoV-2 infected mice was concomitant with the viral load, appearing to be 100-fold higher at day 6 (3dpi) than day 10 (7dpi) (mean 6.2 x 10 6 vs 5.4 x 10 4 copies of E sgRNA/µg of RNA) (Fig. 3B) .

Similarly, the amount of sgRNA was significantly lower in the coinfected mice compared to the SARS-CoV-2 singly infected mice (mean 6. K18-hACE2 mice were challenged intranasally with IAV strain X31 (10 2 pfu) and 3 days later with 10 4 PFU SARS-CoV2 (n = 4). RNA extracted from lungs was analysed for virus levels by qRT-PCR. Assays were normalised relative to levels of 18S RNA. Data for individual animals are shown with the median value represented by a black line (A) SARS-CoV-2 viral load was determined using qRT-PCR for the N gene. (B) Levels of SARS-CoV-2 sub-genomic RNA (sgRNA) for the E gene. (C) IAV load was determined using RT-PCR for the M gene. Comparisons were made using two-way ANOVA (Bonferroni post-test). * represents p < 0.05

Transgenic mice carrying the human ACE2 receptor under the control of the keratin 18 promoter (K18-hACE2) have been reported as a suitable COVID-19 model 22 . As a basis for the assessment of the effect of IAV and SARS-CoV-2 in these mice, a histological examination of major organs/tissues was performed. This confirmed that the transgenic approach had not resulted in phenotypic changes. Comparative staining of wild type and transgenic mice for ACE2, using an antibody against human ACE2 that also cross-reacted with mouse ACE2, also confirmed that transgenesis had not altered the ACE2 expression pattern (respiratory epithelial cells and very rare type II pneumocytes (Supplementary Fig. 1 A, B) , endothelial cells in brain capillaries ( Single IAV infection had by then almost entirely resolved, however, the lungs exhibited changes consistent with a regenerative process, i.e. mild to moderate hyperplasia of the bronchiolar epithelium with adjacent multifocal respiratory epithelial metaplasia/type II pneumocyte hyperplasia, together with mild to moderate lymphocyte dominated perivascular infiltration (Fig. 6A) . Interestingly, the hyperplastic epithelium was found to lack ACE2 expression (Supplemental Fig. 1 E) . At this stage, the effect of SARS-CoV-2 infection was more evident. Single infection had resulted in multifocal areas with distinct type II pneumocyte activation and syncytial cell formation In three of the four single SARS-CoV-infected and two of the four double infected mice at the later time point (7 days post SARS-CoV-2 infection), we observed a mild or moderate non-suppurative meningoencephalitis mainly affecting the midbrain and brainstem (Fig. 7B, C) . This was more severe in the double infected mice, where the perivascular infiltrates contained degenerate leukocytes and appeared to be associated with focal loss of integrity of the endothelial cell layer (Fig. 7C2, 3 ). There is mild perivascular mononuclear infiltration (V: vessel), and the parenchyma exhibits mild multifocal activation of type II pneumocytes (inset). A2, A3. Staining for SARS-CoV-2 reveals random multifocal areas of SARS-CoV-2 infection, affecting both individual alveoli (A2: arrowheads) and large parenchymal areas. Viral antigen expression is seen in type I pneumocytes (A2: arrowheads), type II pneumocytes (A2: arrows) and vascular endothelial cells (A2: small, short arrows). B. IAV (6 dpi) and Sars-CoV-2 (3 dpi) double infection. B1. The IAV-associated changes dominate (see also Fig. 4E ). This is confirmed by staining for IAV antigen expression (B2). IAV antigen is detected in bronchiolar epithelial cells (arrow), occasional type I pneumocytes (arrowhead) and disseminated type II pneumocytes (short, small arrows). B3. SARS-CoV-2 infection is seen in areas not affected by IAV-induced changes (B: bronchioles with IAV changes) and mainly in individual alveoli where both type I and type II pneumocytes are found to express viral antigen (inset). B -bronchiole; V -vessel. Immunohistology, hematoxylin counterstain. Bars = 20 µm. These comprise type II pneumocyte activation and syncytia formation (D: arrowheads) and desquamative pneumonia (E, F), with desquamation of alveolar macrophages/type II pneumocytes (arrows) and type II pneumocyte activation (arrowheads). In more severe cases, alveoli occasionally contain fibrin and hyaline membranes (*). HE stain; Bars = 20 µm. Higher magnification highlighting the one-layered perivascular infiltrate (arrow). B3. Endothelial ACE2 staining shows an intact endothelial layer (arrowheads) also in areas of perivascular infiltration (arrow). C. IAV and SARS-CoV-2 double infected hACE transgenic mouse. The perivascular mononuclear infiltrate is slightly more intense than in the SARS-CoV-2 single infected mouse (C1: arrows), consistent with a mild to moderate non-suppurative meningoencephalitis. Among the perivascular infiltrate are several degenerate cells (C2: arrowheads). C3. Endothelial ACE2 expression (arrowheads) is lost in areas of more intense infiltration (arrows). HE stain and immunohistology, hematoxylin counterstain. Bars = 20 µm.

The transcriptional profile of lung samples can provide a window on the host response to infection for a respiratory pathogen. Therefore, lung samples were taken at Day 6 and Day 10 post IAV infection from all four groups of mice (Fig. 1B) . Total RNA was purified from cells and both host and viral mRNA (and genomic RNA in the case of SARS-CoV-2) were sequenced using the Oxford Nanopore oligo-dT cDNA synthesis approach to identify and quantify mRNA. A multiplex of 5-10 sequencing libraries were loaded onto a flow cell and sequenced on an Oxford Nanopore GridION for up to 72 hours.

Genes were counted against the Mus musculus annotated genome using Salmon 26 .

Gene counts were normalised using the edgeR package before identifying differentially expressed genes using the transcription profile from mock infected mice as the control profile. A total of 970 differentially expressed gene transcripts were observed in comparison to mock infected animals out of a total of 3495 gene transcripts identified. Principle component analysis (PCA) revealed overlapping transcriptional profiles between infection groups (Fig. 8A) . Overlapping signatures were likely to be indicative of the non-specific anti-viral response. Contrast matrices were made between mice that were coinfected versus mice that were mock infected and mice that were singly infected ( Table 1 ). The transcriptomic profile in mice 10 days post infection with IAV showed overlap with the healthy controls, consistent with resolution of infection and regeneration seen in the pathology (Supplementary Fig 2) .

The data indicated that coinfection at day 10 versus IAV day 10 had more differences with 36 gene transcripts at higher abundance, highlighted in the top 75 differentially expressed genes (Fig. 8B ). fold change more than 2 and less than -2 compared to mock infected mice. Coinfection day 6 and day 10 were compared to day 6 and 10 of individual IAV and SARS-CoV-2 infection. I  I  I  I  I  I  I Gene ontology analysis of gene transcripts that were significantly different in abundance at all time points revealed enrichment of gene clusters involved in the innate immune response, immune system regulation and cellular response to cytokine stimulus, interferon beta and interferon gamma (supplementary Fig. 4 ). The differentially expressed gene transcripts between coinfection day 10 versus IAV day 10 were associated with interferon responses according to biological process terms (supplementary Fig. 5 ).

I Bpifb1 Kif21a Scgb3a1 Nav2 Srsf5 Myh11 Ccdc88c AC149090.1 Sec14l3 Cfap126 Cyp2f2 Apex2 Scd1 Scn7a Cavin1 Tspan8 Dyrk2 Lrp2 Ly6c1 Cotl1 C1qa Spp1 Ctsd C1qc Rsad2 Slfn2 Herc6 Ifit2 Isg15 Oasl2 Gbp3 Tap1 Mx1 Apobec3 Ddx60 Rnf213 Cmpk2 H2−Q7 Ifi211 Ifi44 Zbp1 Trim30d Samd9l Slfn5 Eif2ak2 Ube2l6 Ly6i Retnla Bst2 Lgals9 B2m Psmb8 Ddx58 Cd274 Igtp Stat1 Apod Ifit1 Mndal Phf11d Usp18 Irf7 Ifi204 Gbp6 Gbp7 Iigp1 Lgals3bp Ly6e Ifi27l2a Ifitm3 Parp14 Ly6a Ifit3b Ifit3 Trim30a

Following gene ontology analysis, gene transcripts were grouped by biological process terms and presented as heatmaps to allow for direct comparison of their abundance across the experimental groups. SARS-CoV-2 infection resulted in the increased abundance of gene transcripts involved in the interferon and cytokine signalling pathways. When mice were infected with both SARS-CoV-2 and IAV, certain gene transcripts within these pathways remained increased in abundance at later time points, in comparison to individual IAV infection at day 10 ( Fig. 9 ). These included Ifit1, Ifit3, Ifit3b, Isg15, Irf7 and Cxcl10. This suggested a sustained innate/interferon response in these animals.

In this study, sequential infection with IAV followed by SARS-CoV-2 and led to more severe pulmonary disease than infections with IAV or SARS-CoV-2 alone. Following shown to enter the brain earlier at 3dpi but does not elicit notable inflammation in this secondary site of infection 31 . Interestingly, the coinfected mice displayed more severe brain pathology, with perivascular infiltration and epithelial breakdown. The mechanism through which co-infection with IAV may enhance SARS-CoV-2 neurological infection is unclear. While brain infection has been well documented in cases of influenza [32] [33] [34] , this is predominantly limited to neurotropic and highly pathogenic strains and occurs via breakdown of the blood brain barrier (BBB) following high levels of viremia 33, 35 . BBB integrity is also reduced by proinflammatory cytokines such as IL-6, IL-1β and IFN-γ which disrupt the tight-junctions maintained by brain microvascular endothelial cells (reviewed in 36 ). While the IAV X31 strain used herein did not result in brain pathology in singly infected animals, it is possible that the increased cytokine response present in coinfected animals further compromised BBB integrity and therefore induced enhanced brain pathology. 

The upper lobes of the right lung were dissected and homogenised in 1ml of TRIzol reagent (Thermofisher) using a Bead Ruptor 24 (Omni International) at 2 meters per second for 30 sec. The homogenates were clarified by centrifugation at 12,000xg for 5 min before full RNA extraction was carried out according to manufacturer's instructions. RNA was quantified and quality assessed using a Nanodrop (Thermofisher) before a total of 1ug was DNase treated using the TURBO DNA-free™ Kit (Thermofisher) as per manufacturer's instructions.

Viral loads were quantified using the GoTaq® Probe 1-Step RT-qPCR System Similarly, the E sgRNA standard was generated by PCR using the qPCR primers.

cDNA was generated using the SuperScript IV reverse transcriptase kit (Thermofisher) and PCR carried out using Q5® High-Fidelity 2X Master Mix (New England Biolabs) as per manufacturer's instructions. Both PCR products were purified using the QIAquick PCR Purification Kit (Qiagen) and serially diluted 10-fold from 10 10 to 10 4 copies/reaction to form the standard curve.

cDNA sequencing with Oxford Nanopore cDNA libraries were made starting with 50ng of total RNA which was accurately quantified using a Qubit 3.0 fluorometer (Thermofisher) and the Qubit RNA HS Assay

Kit (Thermofisher). The cDNA was generated using the PCR-cDNA Barcoding (SQK- 

Multiplexed sequencing reads were basecalled and demultiplexed by guppy.

Minimap2 was used to index and map reads to the reference genome (Mus_musculus.GRCm38.cdna.all.fa) to generate alignment files using the -ax mapont -N 100 -p 1.0 parameters 49 . Alignment files were sorted and indexed with samtools before counting reads using Salmon with the corresponding annotation file (Mus_musculus.GRCm38.gtf) from Ensembl using -noErrorModel -l U parameters 26, 50 . The edgeR package was used to normalise sequencing libraries and identify differentially expressed genes, defined as at least a 2-fold difference from the mock infected group (n=5) and a false discovery rate (FDR) less than 0.05 51 . Principle component Analysis (PCA), volcano plots, heatmaps and Venn diagrams were produced in R studio using the following packages: edgeR, ggplot2 and pheatmap.

Differential gene expression data was used for gene ontology enrichment analysis of biological process terms in each group using enrichGO in the ClusterProfiler programme in R 52 . A q-value cut-off of 0.05 was used with a Benjamini-Hochberg-FDR correction. GOSemSim was used to simplify and remove redundant GO terms 53 and the top 20 biological processes are presented for each condition.

Statistical analysis. Data were analysed using the Prism package (version 5.04

Graphpad Software). P values were set at 95% confidence interval. A repeatedmeasures two-way ANOVA (Bonferroni post-test) was used for time-courses of weight loss; two-way ANOVA (Bonferroni post-test) was used for other time-courses; log-rank (Mantel-Cox) test was used for survival curves. All differences not specifically stated to be significant were not significant (p > 0.05). For all figures, *p < 0.05, **p <0.01, ***p < 0.001.

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