Neutrophil adhesion to vessel walls impairs pulmonary circulation in COVID-19 pathology

Ueki, Hiroshi; Wang, I-Hsuan; Kiso, Maki; Horie, Kenta; Iida, Shun; Mine, Sohtaro; Ujie, Michiko; Hsu, Hung-Wei; Wu, Chen-Hui Henry; Imai, Masaki; Suzuki, Tadaki; Kamitani, Wataru; Kawakami, Eiryo; Kawaoka, Yoshihiro

doi:10.1038/s41467-024-55272-0

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Published: 13 January 2025

Neutrophil adhesion to vessel walls impairs pulmonary circulation in COVID-19 pathology

Nature Communications volume 16, Article number: 455 (2025) Cite this article

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Abstract

Microthrombus formation is associated with COVID-19 severity; however, the detailed mechanism remains unclear. In this study, we investigated mouse models with severe pneumonia caused by SARS-CoV-2 infection by using our in vivo two-photon imaging system. In the lungs of SARS-CoV-2-infected mice, increased expression of adhesion molecules in intravascular neutrophils prolonged adhesion time to the vessel wall, resulting in platelet aggregation and impaired lung perfusion. Re-analysis of scRNA-seq data from peripheral blood mononuclear cells from COVID-19 cases revealed increased expression levels of CD44 and SELL in neutrophils in severe COVID-19 cases compared to a healthy group, consistent with our observations in the mouse model. These findings suggest that pulmonary perfusion defects caused by neutrophil adhesion to pulmonary vessels contribute to COVID-19 severity.

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Introduction

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is the causative virus of COVID-19 (coronavirus disease 2019) and is transmitted via droplets/aerosols containing the virus. SARS-CoV-2 invasion of the lung is initiated by the binding of the virus to the alveolar epithelium using angiotensin-converting enzyme-2 (ACE-2) as a receptor^1,2. Most cases of COVID-19 are mild with respiratory symptoms such as fever, cough, nasal discharge, and pharyngitis; however, the elderly and those with underlying medical conditions such as obesity, diabetes, and hypertension develop severe viral pneumonia, which often leads to serious complications and even death^3,4. Patients presenting with severe viral pneumonia are treated according to their respiratory and systemic symptoms, but the mechanism of COVID-19 severity is not fully understood and an optimal treatment strategy has not been established.

Immunopathology, including neutrophilia and lymphopenia, decreased or delayed type I interferon response, and the cytokine storm caused by dysregulation of monocytes and granulocytes may play a role in the pathogenesis of COVID-19⁵. In addition to these immunopathological events, thrombosis has frequently been reported in patients with severe COVID-19, which may also contribute to the severity of the disease^6,7,8. Platelets bind to neutrophils through neutrophil extracellular traps (NETs) released by the neutrophils to form large thrombus-like aggregates; they also form thrombi independently of neutrophils in response to tissue factors exposed to damaged endothelial cells. Single-cell RNA-seq and proteomic approaches using clinical samples and animal models of SARS-CoV-2 infection have revealed that factors associated with inflammation, coagulation, and NETs release are activated during SARS-CoV-2 infection. The factors involved in thrombus formation are spatiotemporally regulated and the thrombogenic process is thought to be a multistep process; however, these dynamic events are difficult to observe using conventional histological approaches with COVID-19 autopsy samples or SARS-CoV-2-infected animals. Accordingly, it remains unclear how the process of thrombus formation proceeds in patients with severe COVID-19.

To establish an effective treatment for patients with severe COVID-19, we must elucidate the mechanisms involved in the severity of the disease. To understand how SARS-CoV-2 affects the responses of platelets and neutrophils in the pulmonary vasculature and the thrombogenic response, we performed two-photon in vivo imaging analysis of cellular responses after SARS-CoV-2 infection by using SARS-CoV-2 strains and lethal mouse models. Our in vivo imaging analysis revealed increased neutrophil numbers in the pulmonary vasculature, prolonged neutrophil adhesion to pulmonary vessels, and enhanced platelet aggregation in SARS-CoV-2-infected mice. The increased expression of adhesion factors on the neutrophils in pulmonary blood vessels promoted thrombus formation and impaired pulmonary blood flow in the lungs of the SARS-CoV-2-infected mice. In addition, re-analysis of data from human clinical samples⁹ demonstrated the relevance of the findings in mice.

Results

In vivo imaging of SARS-CoV-2-infected lung

To elucidate the pathological changes of SARS-CoV-2-infected lungs in living animals, we examined K18-human angiotensin-converting enzyme-2 transgenic (K18-hACE2 Tg) mice by using an in vivo imaging system we previously established in a biosafety level (BSL) 3 facility^10,11. hACE2 is expressed on the epithelial cells of the lungs, kidneys, liver, intestine, and brain of K18-hACE2 mice, and contributes to the establishment of SARS-CoV-2 infection as a receptor for the S protein^1,2. To visualize SARS-CoV-2-infected cells, K18-hACE2 Tg mice were intranasally inoculated with SARS-CoV-2-Venus, which expresses the Venus fluorescent reporter gene in infected cells. SARS-CoV-2-Venus, generated by reverse genetics in the backbone of pBAC SARS2 WK521 (derived from SARS-CoV-2/JPN/TY/WK521), exhibited lethal infection with an MLD₅₀ (mouse lethal dose 50; the dose required to kill 50% of infected mice) value of 10^3.83 plaque-forming units (PFU) in K18-hACE2 Tg mice (Fig. 1a). To analyze the pathobiological effects of SARS-CoV-2, we infected K18-hACE2 Tg mice with 10⁵ PFU of SARS-CoV-2-Venus. Fluorescent dextran, as well as fluorochrome-conjugated anti-mouse Ly-6G and CD41 antibodies, were also intravenously (i.v.) administered to the mice to visualize lung vascular structures, neutrophils, and platelets, respectively. Virus-infected Venus-positive epithelial cells began to be observed in the lungs of SARS-CoV-2-infected mice on day 4 post-infection (p.i.), and their number had visibly increased at day 6 p.i. (Fig. 1b and Supplementary Movie 1). The Venus-positive infected cells appeared to be morphologically flat type I alveolar epithelial cells surrounding the alveoli, and spherical large type II alveolar epithelial cells were infected with SARS-CoV-2-Venus (Fig. 1c), consistent with previous studies^12,13. Platelets and neutrophils flowed smoothly in the pulmonary capillaries of uninfected mice, whereas in the mice infected with SARS-CoV-2-Venus, their movements were slower in the capillaries (Supplementary Movie 1). On day 6 p.i., an increase in the number of neutrophils was apparent in the pulmonary capillaries of the infected-K18-hACE2 Tg mice (Fig. 1d).

**Fig. 1: In vivo imaging of SARS-CoV-2-infected K18-hACE2 C57BL/6J mice.**

SARS-CoV-2 alters the motility of intravascular neutrophils and impairs blood flow in infected lung

To analyze the functional changes of neutrophils in SARS-CoV-2-infected lungs, we quantitatively assessed the neutrophil movement. In our previous studies, we reported that pulmonary neutrophils in influenza virus-infected mice show two types of motility¹⁰: “slow movement”, which is considered tethering or rolling, in which neutrophils move along the vessel wall at a speed of 50 µm/s or less; and “rapid motion”, which is moving in the blood flow at a speed of more than 50 µm/s. We analyzed the amount of time individual neutrophils engaged in each motion in the lungs of K18-hACE2 Tg mice infected with SARS-CoV-2-Venus. Pulmonary neutrophils observed in SARS-CoV-2-infected lungs were tracked (Fig. 2a left panels) and ordered according to the amount of time they spent in slow motion, and the total time they spent in slow (Fig. 2a right panels, blue bars) and rapid (Fig. 2a right panels, red bars) motion was plotted for each neutrophil (Supplementary Movie 2). In SARS-CoV-2-Venus-infected lung, the amount of time the neutrophils spent in slow motion was significantly increased compared with uninfected lung (Fig. 2b). We also found that the percentage of neutrophils that engaged in rapid motion decreased (Fig. 2b). These results indicate that vascular neutrophils in SARS-CoV-2-infected lungs have increased contact time with the pulmonary vessel wall.

**Fig. 2: Quantitative analysis of pathophysiological changes in SARS-CoV-2-infected lungs.**

Thrombus formation in pulmonary vessels has emerged as a typical clinical feature of COVID-19 pneumonia¹⁴. To assess whether intravascular neutrophils contribute to thrombus formation during SARS-CoV-2 pathogenesis, we performed an in vivo imaging analysis by co-staining platelets and neutrophils. To quantify the size of the platelet aggregates in the infected lungs, we assessed the fluorescent signals of CD41 as a surface marker of platelets¹⁵ from the original image, measured the area of each platelet, and performed a frequency analysis (Fig. 2c). CD41 signals occupying a small area (<50 pixels, which is approximately 8.57 µm² in our imaging setting) and flowing in the blood vessels were considered to be single platelets. In SARS-CoV-2-infected lungs, an increased percentage of aggregated platelets with a large area of CD41 signal (≥50 pixels and <200 pixels, which is approximately 34.28 µm² in our imaging setting) and thrombi (>200 pixels) were also observed to block the vessels as emboli. The percentage of aggregated platelets and thrombi was significantly increased in SARS-CoV-2-infected lungs (Fig. 2c). Interestingly, aggregated platelets frequently interacted with intravascular neutrophils to form microthrombus-like structures (neutrophil-platelet complexes) in the lungs infected with SARS-CoV-2-Venus (Fig. 2d and Supplementary Fig. 1). The ratio of intravascular neutrophils in contact with platelets was significantly increased in SARS-CoV-2-infected lungs compared to that of uninfected mice (Fig. 2d). These observations suggest that neutrophils adhering to pulmonary vessels in SARS-CoV-2-infected lungs participate in the formation of platelet aggregates.

The stagnation of blood neutrophils, aggregation of platelets, and formation of platelet-neutrophil complexes observed in SARS-CoV-2-infected lungs may have a significant effect on pulmonary hemodynamics and oxygen exchange mediated by erythrocytes. To test this concept, we transferred fluorescently labeled erythrocytes into SARS-CoV-2-infected K18-hACE2 Tg mice and observed their trajectories for 10 min. The time-lapse images were overlapped every 50 frames to visualize the areas where labeled erythrocytes flowed (Fig. 2e and Supplementary Movie 3). In naive mice, the blood vessels visualized by use of fluorescent dextran and the trajectories of the labeled erythrocytes almost overlapped, indicating that most pulmonary vessels were functional for oxygen exchange. In contrast, in SARS-CoV-2-infected lungs, there were areas where the vascular structures and the trajectories of the labeled erythrocytes did not overlap, indicating that the availability of functional capillaries for oxygen exchange was reduced. Blood neutrophil stagnation, platelet aggregation, and platelet-neutrophil complexes may disturb the pulmonary microcirculation in the SARS-CoV-2-infected lungs. Our in vivo imaging data revealed that the functional failure of lung capillaries is likely due to microthrombi formation in mice infected with SARS-CoV-2.

Development of a mouse model of severe SARS-CoV-2 pneumonia

Although K18-hACE2 Tg mice have been widely used to study SARS-CoV-2 pathogenesis^16,17, intranasal inoculation of these mice with SARS-CoV-2 can cause severe neurological disease, including encephalitis, with features that differ from severe COVID-19 cases^18,19. We previously established a mouse-adapted (MA) SARS-CoV-2 and its derivative expressing the Venus protein (named MA-SARS-CoV-2-Venus), which causes severe lung inflammation in C57BL/6J mice similar to severe COVID-19 cases²⁰.

To establish an animal model that can mimic the symptoms of severe COVID-19 patients, we used seven mouse strains that are well-established disease models [i.e., obesity/diabetes models, C57BL/6J HamSlc-ob/ob (Ob/Ob) mice and KK-A^y/Ta Jcl mice; a type 1 diabetes model, Streptozotocin (STZ)-induced diabetic C57BL/6J mice; aged models, SAMP8/TaSlc mice and SAMP10-ΔSglt2 mice; a hyperlipidemia model, B6. B6.KOR/StmSlc-Apoe^shl mice; and a hepatitis model, B6-nonalcoholic steato-hepatitis (NASH) mice]. These mice were intranasally infected with 10³ PFU of MA-SARS-CoV-2 and their survival was assessed. MA-SARS-CoV-2-infected Ob/Ob mice showed significantly reduced survival compared to wild-type mice (Fig. 3a). The other six mouse strains did not show any symptoms after SARS-CoV-2 infection (Fig. 3a). We did not perform any additional studies on these other mouse comorbidity models; therefore, we cannot explain why we did not see severe outcomes with them. MA-SARS-CoV-2 exhibited high pathogenicity with an MLD₅₀ value of 10^2.5 PFU and caused virus dose-dependent weight loss in Ob/Ob mice (Fig. 3b). MA-SARS-CoV-2 and MA-SARS-CoV-2-Venus showed comparable virulence in Ob/Ob mice (MLD₅₀; 10^2.5 PFU) (Supplementary Fig. 2).

**Fig. 3: Virulence of MA-SARS-CoV-2 in mouse models of underlying diseases.**

Infection of Ob/Ob mice with MA-SARS-CoV-2 resulted in high virus titers in the lungs and nasal turbinates at 2 dpi, and no substantial difference in viral titers in the respiratory organs at this timepoint was observed between Ob/Ob mice and their control groups (Fig. 4a). Viruses were also recovered from the brain and liver of the infected Ob/Ob mice albeit at low titers (note: the brain samples collected for virus titration included the olfactory bulb). In the lungs of infected Ob/Ob mice at 5 dpi, viral replication was significantly higher than that in the control groups, with a titer of more than 1.0 × 10⁷ PFU/g. In contrast, no difference in viral titers in the nasal turbinates was observed between Ob/Ob mice and their control groups, and the virus was not detected in any other organs tested at 5 dpi. Micro-CT analysis revealed lung abnormalities in MA-SARS-CoV-2-infected Ob/Ob mice, including patchy and ill-defined regions consistent with COVID-19 pneumonia at 4 dpi (Fig. 4b).

**Fig. 4: Characterization of Ob/Ob mice infected with MA-SARS-CoV-2.**

We then examined the histopathologic changes in the organs of Ob/Ob mice after MA-SARS-CoV-2 infection. Histopathological analysis revealed infiltration of inflammatory cells such as neutrophils and mononuclear cells into the alveolar regions in the lungs of both Ob/Ob and their control groups at 2 dpi with MA-SARS-CoV-2 (Fig. 4c). At the same timepoint, viral antigen was immunohistochemically detected mainly on alveolar and bronchiolar epithelial cells in both groups. In addition, the histopathological scores for pneumonia were comparable between the Ob/Ob and control groups (Fig. 4d). On day 5 p.i., the inflammation improved in the control group, but persisted in the Ob/Ob mice. In the control group, there was a clear reduction in the number of virus-positive cells. Conversely, there was no notable reduction in the number of virus-positive cells in the Ob/Ob group. These findings were supported by the histopathological scores for pneumonia, which showed an obvious decline in the control group but no obvious reduction in the Ob/Ob group (Fig. 4d). Consistent with our histopathologic analysis, flow cytometry showed that the number of neutrophils and monocytes infiltrating the lungs was significantly increased in the MA-SARS-CoV-2 infected lungs compared to the control group (Fig. 4e).

These results indicate that Ob/Ob mice infected with MA-SARS-CoV-2 or MA-SARS-CoV-2-Venus are a useful model that reflects the pathogenesis of severe COVID-19.

Neutrophils cause impaired pulmonary perfusion in SARS-CoV-2-infected lungs

To analyze the pathobiological changes in MA-SARS-CoV-2-infected Ob/Ob mice, the mice were intranasally infected with 10⁴ PFU of MA-SARS-CoV-2-Venus. Large numbers of infected cells were observed in the lungs of Ob/Ob mice on day 4 p.i. (Fig. 5a and Supplementary Movie 4). Similar to the pathophysiological changes in the infected K18 hACE2 Tg mice, there was a significant increase in the number of neutrophils, platelet aggregates, thrombi, and the ratio of neutrophils in contact with platelets in the pulmonary vasculature of MA-SARS-CoV-2-Venus-infected Ob/Ob mice (Fig. 5b–d). To investigate the functional changes in the neutrophils, we quantified the motility of the vascular neutrophils of the infected mice. Ob/Ob mice infected with MA-SARS-CoV-2-Venus showed significantly increased slow neutrophil movement in pulmonary vessels compared to control groups, indicating increased adhesion time of neutrophils to the pulmonary vascular wall (Fig. 5e, f). Hemodynamics of the lungs of MA-SARS-CoV-2-Venus-infected Ob/Ob mice showed that pulmonary perfusion was obviously impaired compared with that in infected wild-type mice, with limited capillaries available for oxygen exchange (Fig. 6a and Supplementary Movie 5).

**Fig. 5: In vivo imaging of SARS-CoV-2-infected Ob/Ob mice.**

**Fig. 6: Hemodynamics of the lungs of MA-SARS-CoV-2-Venus-infected Ob/Ob mice.**

To clarify whether aggregates of neutrophils and platelets contribute to the impaired pulmonary perfusion observed in SARS-CoV-2-infected lungs, we performed a five-color multiple labeling analysis using our in vivo imaging method¹¹. Ob/Ob mice were intranasally infected with MA-SARS-CoV-2-Venus and observed at 4 dpi. At this timepoint, fluorescent dextran, two fluorochrome-conjugated antibodies (Ly-6G and CD41), and fluorescently labeled erythrocytes were i.v. administered and then observed by using our imaging system. In the lungs of Ob/Ob mice infected with MA-SARS-CoV-2-Venus, neutrophil, and platelet aggregates obstructed the flow of the transferred erythrocytes, suggesting that these aggregates may be responsible for the impaired pulmonary perfusion (Fig. 6b and Supplementary Movie 6). In addition, in SARS-CoV-2-infected lungs, neutrophils adhered to the pulmonary vasculature; this was followed by platelet aggregation and stasis of the transferred erythrocytes, suggesting that neutrophil adhesion to the vessel wall is the point of origin for thrombus formation and subsequent impaired pulmonary perfusion.

To assess whether neutrophils are involved in the pathogenesis of MA-SARS-CoV-2, we removed the neutrophils in vivo by using antibodies and analyzed the effect on virus susceptibility. Removal of neutrophils from Ob/Ob mice led to a slight increase in the number of single platelets and a decrease in the number of aggregated platelets and thrombi in the pulmonary vasculature after MA-SARS-CoV-2 infection (Fig. 6c). In addition, the survival period for neutrophil-depleted Ob/Ob mice infected with MA-SARS-CoV-2 infection was prolonged (Fig. 6d). These results suggest that thrombi formed upon neutrophil stagnation may exacerbate MA-SARS-CoV-2-Venus pneumonia in Ob/Ob mice.

Altered expression of adhesion molecules in pulmonary neutrophils in relation to COVID-19 severity

Neutrophils infiltrate the site of infection by interacting with vascular endothelial cells via adhesion molecules²¹. We therefore analyzed the expression levels of molecules (i.e., CD62L, CD44, E-selectin, Selplg, and Pecam-1)²² linked to the interaction with vascular endothelial cells during neutrophil infiltration in SARS-CoV-2-infected mice by flow cytometry. Neutrophils in the pulmonary vasculature of Ob/Ob mice infected with MA-SARS-CoV-2 exhibited upregulated expression of CD62L, CD44, and E-selectin (Fig. 7). Analysis in this mouse model suggested that SARS-CoV-2 increases neutrophil adhesion to the vessel wall and induces platelet aggregation, which result in impaired pulmonary perfusion in the lungs.

**Fig. 7: Expression of adhesion molecules on vascular neutrophils in the lungs of MA-SARS-CoV-2-infected mice.**

Finally, to determine whether the increased expression levels of adhesion molecules on the surface of vascular neutrophils in severe infections observed in SARS-CoV-2-infected mice is relevant to the pathogenesis of COVID-19 pneumonia in humans, we analyzed published data obtained with clinical samples from COVID-19 patients for adhesion-related gene expression. Using two published datasets of scRNA-seq analyses^9,23 from peripheral blood mononuclear cells (PBMCs) from healthy volunteers, mild, and severe cases of COVID-19, we analyzed 474 adhesion-related gene²⁴ expression changes and found that the levels of expression of four genes (CD44, SELL, ICAM3, and CD93) in the two datasets frequently differed between the healthy and severe groups (Fig. 8a, b). In the subset corresponding to neutrophils, the expression levels of the CD44 and SELL (which encodes CD62L) genes were significantly increased in COVID-19 severe cases compared to healthy individuals (Fig. 8c). These findings indicate that the expression of adhesion molecules is also increased in the vascular neutrophils in the lungs of severe COVID-19 cases, supporting the relevance of the data obtained in mice. In contrast, the gene expression of ICAM3 and CD93 was significantly decreased in the severe group compared to that in the healthy group. The expression levels of the SELL gene showed a positive correlation with the severity of COVID-19 in both the Wilk et al.⁹ and Xu et al.²³ datasets and the CD44 gene expression level also positively correlated with COVID-19 severity in the Xu et al.²³ dataset; the expression level of the CD44 gene was positively correlated when comparisons were made between healthy and nonventilated patients or ventilated patients in the Wilk et al.⁹. dataset. In contrast, the expression levels of the ICAM3 and CD93 genes negatively correlated with severity, suggesting that they could be molecular markers for the severity of COVID-19. Finally, blocking the function of the adhesion molecules by using anti-CD44 and anti-CD62L antibodies decreased the contact time between neutrophils and the vessel wall in the lungs of Ob/Ob mice infected with SARS-CoV-2-Venus, and increased the percentage of neutrophils flowing into the bloodstream (Fig. 9a, b, and Supplementary Movie 7). In contrast, inhibition of CD44 and CD62L function by using anti-CD44 and anti-CD62L antibodies did not affect the size of the platelet aggregates after SARS-CoV-2 infection (Fig. 9c).

**Fig. 8: Involvement of adhesion molecules in pulmonary neutrophils in COVID-19 pneumonia.**

**Fig. 9: Effects of anti-CD44 and anti-CD62L antibodies on neutrophil motility and platelet aggregates.**

Discussion

In this study, our in vivo imaging system revealed that the number of neutrophils in pulmonary vessels increases and neutrophil motility decreases in SARS-CoV-2-infected lungs. We also found that platelet aggregation is enhanced in infected lungs, with frequent formation of neutrophil-platelet complexes. The number of blood vessels through which erythrocytes flow for oxygen exchange was reduced in the infected mouse lungs, suggesting that this may contribute to SARS-CoV-2 pathogenesis. Moreover, we found that the expression of adhesion molecules is increased in pulmonary neutrophils in COVID-19 patients and mouse models, suggesting the existence of a common mechanism of SARS-CoV-2 virulence in humans and mice. Our in vivo imaging analysis thus revealed a novel mechanism of SARS-CoV-2 pathogenesis that could not be found using conventional histopathological and histochemical analyses, and flow cytometry.

Analysis of mouse models of severe or lethal SARS-CoV-2 infection showed that platelet aggregation is induced by neutrophil adhesion to the pulmonary vascular wall, resulting in impaired pulmonary perfusion. A major mechanism of thrombus formation in COVID-19 patients is thought to be the induction of platelet aggregation and thrombus formation by NETs released from neutrophils²⁵. Complexes of neutrophils, platelets, and citrullinated histone H3, a marker of NETs, have been found during lung autopsies of COVID-19 patients²⁶. Consistent with these findings, an analysis of human scRNA-seq data revealed a difference in the expression of the PADI4 gene (Supplementary Fig. 3), which is responsible for NET release²⁵, suggesting that NET release was induced in severe COVID-19 cases. However, intravascular neutrophils in the infected lungs had a distinct cell membrane shape and slow motility and did not exhibit the apoptotic morphology that is associated with NET release. This discrepancy may reflect the multistep nature of thrombogenesis that has been postulated in vivo²⁷; our findings of thrombus formation induced by neutrophil adhesion to the vessel wall may be an earlier phenomenon than the thrombus formation involving NETs. Since NET release by neutrophils is induced in response to PAMPs and DAMPs²⁷, it is likely that NETs are released in response to the DAMPs that are released upon tissue damage and induce thrombus formation in the late stages of infection when the infection is more advanced. Our in vivo imaging analysis likely revealed an early stage of thrombus formation that was not available in the autopsy cases of COVID-19.

The expression of the adhesion molecules CD44 and CD62L was upregulated in the pulmonary intravascular neutrophils of the SARS-CoV-2-infected mice, and the expression levels of the genes encoding these factors were also upregulated in pulmonary neutrophils from severe COVID-19 cases. CD62L is expressed on leukocytes and is involved in intercellular adhesion; it has been widely implicated in immune cell responses, from cell migration to antigen presentation²⁸. In neutrophils, CD62L is expressed on the membrane surface from the early stage of differentiation from progenitor cells and is involved in adhesion to vascular endothelial cells during migration^21,28. The half-life of mature neutrophils is approximately 6–12 h in the bloodstream, and CD62L expression decreases with neutrophil aging, which is characterized by plasma membrane instability, activation of apoptotic signaling, and other events²⁹. Neutrophil infiltration has been observed in the lungs of patients with COVID-19 and increases in the numbers of both mature and immature neutrophils have been reported^14,30. In addition, it has been reported that immature aberrant neutrophils infiltrate the lungs of SARS-CoV-2-infected mice via the S100A8/A9-TLR4 pathway, and are involved in the pathogenesis³¹. COVID-19 patients have also been reported to have neutropenia, an increase in the number of neutrophils in the blood²⁷, and in our mouse model, SARS-CoV-2 infection increased the number of neutrophils in the pulmonary vessels. Recently, Castanheira et al.³² reported that SARS-CoV-2 infection of a mouse model ubiquitously expressing hACE2 (CAG-AC-70) increased neutrophil numbers in pulmonary vessels. These findings suggest that SARS-CoV-2 infection promotes neutrophil proliferation in the bone marrow and migration to the infected lungs and that immature neutrophils expressing high levels of CD62L are recruited in large numbers to infected pulmonary vessels, leading to susceptibility to thrombus formation and impaired pulmonary perfusion. Consistent with this hypothesis, in the present study, we found that the expression levels of ICAM3, one of the membrane molecules induced by apoptotic signaling³³, are significantly decreased in neutrophils from patients with severe COVID-19 compared to healthy controls.

CD44 is also an adhesion factor expressed on leukocytes and is involved in the adhesion and infiltration of neutrophils into the hepatic sinusoids³⁴. It has been reported that neutrophil adhesion is suppressed in the hepatic sinusoids of Cd44-deficient mice with LPS-induced liver injury³⁵. Although the mechanism of Cd44 gene expression in neutrophils remains unclear, we do know that Cd44 expression is increased in monocytes in response to inflammatory cytokines³⁶. In severe cases of COVID-19, inflammatory mediators induced by SARS-CoV-2 infection may also increase CD44 gene expression in neutrophils, contributing to increased adhesion to pulmonary vessels. In addition, it has been reported that neutrophil adhesion to pulmonary blood vessels increases in the LPS-induced septic mouse model, leading to impaired blood flow and the increased expression of adhesion molecules (CD11b and CD18) in neutrophils³⁷. Therefore, the pathological mechanism by which adhesion molecules that are upregulated in neutrophils induce pulmonary blood flow impairment might be a mechanism common to certain inflammatory conditions.

Our study has several limitations that require further investigation. Changes in the expression levels of membrane molecules in vascular endothelial cells in SARS-CoV-2-infected lungs were not examined in this study, and it is unclear how vascular endothelial cells are involved in neutrophil adhesion to the pulmonary vessel walls. It has been hypothesized that thrombus formation proceeds because of dysfunctional endothelial responses to SARS-CoV-2 infection^38,39. However, at least in our mouse model, neutrophil adhesion to the vessel wall occurred not only in the proximity of the infected vascular endothelial cells but also away from SARS-CoV-2-infected cells (Figs. 1b and 5a). Another limitation is that it is unclear whether the upregulation of the CD44 and SELL genes in the SARS-CoV-2-infected mouse model and in COVID-19 patients occurs in the entire neutrophil populations or in some subpopulations of neutrophils. There have been many reports of neutrophil heterogeneity^23,40,41, suggesting that SARS-CoV-2 infection might induce a subpopulation of neutrophils that express the CD44 or SELL genes at high levels. In addition, the extent to which impaired pulmonary perfusion due to neutrophil adhesion to the pulmonary vascular wall contributes to the lethality of SARS-COV-2 pneumonia is unknown. Finally, blocking the function of adhesion molecules with neutralizing antibodies decreased the contact time between neutrophils and the vessel wall in the lungs of Ob/Ob mice infected with SARS-CoV-2-Venus; however, inhibition of CD44 and CD62L function did not significantly affect platelet aggregate size (Fig. 9a–c). Therefore, it may be possible to improve the pathological condition more significantly by inhibiting the function of adhesion factors in addition to CD44 and CD62L. Since adhesion molecules are involved in the migration and infiltration of neutrophils in response to SARS-CoV-2 infection, dysfunction of adhesion molecules by neutralizing antibodies may also interfere with the protective function of neutrophils against SARS-CoV-2 infection, which has not been fully explored.

Beyond the acute respiratory infection, symptoms such as shortness of breath, cough, arthralgia, myalgia, fatigue, headache, odor/taste disturbance, and palpitations have been reported as COVID-19 sequelae (also called long COVID) even after the infection has resolved⁴². It has been shown that prolonged post-ischemic symptoms are more likely to occur in groups at high risk for severe COVID-19, particularly the elderly and those with a high BMI (obesity)⁴³. It has also been suggested that microembolization-induced tissue damage may contribute to COVID-19 sequelae⁴⁴. In the present study, using in vivo imaging of mouse models, we found that the formation of microthrombi composed of neutrophils and platelets impairs pulmonary blood flow and exacerbates COVID-19 pneumonitis. The pathological mechanisms of COVID-19 revealed by this study will lead to the development of more effective treatments for patients with severe COVID-19 and long COVID.

Methods

Ethics statement. All experiments were performed in enhanced biosafety level 3 (BSL3) containment laboratories at the University of Tokyo, which are approved for such use by the Ministry of Agriculture, Forestry, and Fisheries, Japan. The protocols for the animal studies were approved by the University of Tokyo (approval numbers PA19-72 and PA21-07). The ambient conditions of the animal facilities were set at 25 °C and 50% humidity. Animals were acclimated to the facilities prior to the start of the experiments, maintained on a 12-h on/off light cycle, and given access to food and water ad libitum.

Viruses. We generated SARS-CoV-2-Venus, in which the fluorescent reporter gene Venus was inserted, by using reverse genetics. For the construction of SARS-CoV-2-Venus, we replaced the ORF 8 genes of pBAC SARS2 wk521 with the Venus gene by use of recombination and designated the infectious cDNA clone pBAC SARS-CoV-2-Venus. Mouse-adapted (MA)-SARS-CoV-2 and MA-SARS-CoV-2-Venus were also generated by using reverse genetics previously described²⁰. Virus strains were propagated in VeroE6/TMPRSS2 (JCRB 1819) cells⁴⁵.

Cells. VeroE6/TMPRSS2 (JCRB 1819) cells⁴⁵ were propagated in 1 mg/ml geneticin (G418; Invitrogen) and 5 μg/ml plasmocin prophylactic (Invitrogen) in Dulbecco’s modified Eagle’s medium (DMEM) containing 10% Fetal Calf Serum (FCS). The cells were regularly tested for mycoplasma contamination by using PCR and confirmed to be mycoplasma-free.

Mice. Eight-week-old hemizygous K18-hACE2 C57BL/6J female mice (strain 2B6.Cg-Tg(K18-ACE-2)2Prlmn/J), 24-week-old C57BL/6J HamSlc-ob/ob female mice, and five-week-old Streptozotocin (STZ)-induced diabetic C57BL/6J male mice were purchased from the Jackson Laboratory Japan. In addition, 24-week-old B6-NASH male mice, B6.KOR/StmSlc-Apoe^shl female mice, SAMR1/TaSlc [Senescence-Accelerated Mouse (SAM); senescence-Resistant inbred strains (R)] male mice, SAMP8/TaSlc [Senescence-Accelerated Mouse (SAM); senescence-Prone inbred strains (P)] male mice, and SAMP10-ΔSglt2 male mice were purchased from Japan SLC Inc. KK-A^y/Ta Jcl female mice (24-week-old) were purchased from CLEA Japan Inc. Age- and sex-matched C57BL/6J mice, which served as controls, were purchased from the same vendor as each disease model mouse strain. Eight-week-old k18-hACE2 Tg mice were used in the analyses because they exhibited severe SARS-CoV-2 pneumonia compared to wild-type mice of the same age. The genetically modified mouse strains with underlying diseases were all matched at 24 weeks of age, except for the STZ-induced type 1 diabetes mouse model. STZ-induced type 1 diabetes model mice die within weeks without therapeutic treatment; therefore, we had to use them for the infection experiments immediately after STZ treatment (at 5 weeks of age). In this study, we used female mice to be consistent with our previous studies^20,46. For STZ-induced diabetic mice and SAMR1/P8/P10 mice, we used male mice available from the suppliers.

Experimental infection of mice. Mice were intranasally inoculated with 10¹–10⁵ PFU of SARS-CoV-2-Venus, MA-SARS-CoV-2, or MA-SARS-CoV-2-Venus. Body weights were measured before infection and then daily. C57BL/6J HamSlc-ob/ob mice were infected intranasally with 10⁴ PFU of MA-SARS-CoV-2-Venus, and on days 1, 2, and 3 after infection, 100 µg of anti-mouse CD44 (IM7, Bioxcell) and anti-mouse CD62L (Mel-14, Bioxcell) antibodies, or the corresponding isotype control (2A3 and LTF-2, Bioxcell), was administered intravenously.

Pathological examination. Excised lung tissues were fixed in a 4% paraformaldehyde phosphate buffer solution and processed for paraffin embedding. The paraffin blocks were cut into 3-µm-thick sections and then the sections were stained using a standard hematoxylin and eosin procedure. In addition, tissue sections were stained with a rabbit polyclonal antibody for SARS-CoV nucleocapsid protein (ProSpec; ANT-180, 1:500 dilution, Rehovot) for immunohistochemical analyses. Specific antigen-antibody reactions were visualized by means of 3,3′-diaminobenzidine tetrahydrochloride staining using the Dako Envision system (Dako Cytomation; K4001, 1:1 dilution). Histopathological scores for pneumonia were determined based on the percentage of alveolar inflammation in a given area of a pulmonary section (area score), inflammatory cell density (density score), and the presence of pulmonary edema and/or alveolar hemorrhage (severity score) by using the following scoring system: Area score 0, no inflammation; 1, affected area (≤50%); and 2, affected area (50%). Density score 0, inflammation observed only in the high-power field; 1, inflammation observed in low-power fields; and 2, alveoli filled with inflammatory cells. Severity score 0, absence of pulmonary edema and/or alveolar hemorrhage; and 1, presence of pulmonary edema and/or alveolar hemorrhage. The total score for the five lobes was calculated for each animal; therefore, the scores for individual animals ranged from 0 to 25.

Virus titration assay. C57BL/6J mice and HamSlc-ob/ob mice were intranasally inoculated with 10³ PFU of MA-SARS-CoV-2. Two and five days post-infection (dpi), the animals were euthanized and their organs (lungs, nasal turbinate, brain, heart, liver, spleen, kidneys, and intestine) were collected. Confluent VeroE6/TMPRSS2 cells in 12-well plates were infected with 100 μl of a dilution of the organ homogenate. The virus inoculum was removed after incubation for 1 h at 37 °C, and then 1% agarose solution in DMEM was overlaid on the cells. After incubation for 48 h, the agar-covered cells were fixed with 10% neutral buffered formalin. The plaques were counted after the removal of the agar.

Micro-CT imaging. C57BL/6J mice and HamSlc-ob/ob mice were inoculated intranasally with 10³ PFU of MA-SARS-CoV-2. Lungs of infected mice were imaged by using an in vivo micro-CT scanner (CosmoScan FX; Rigaku). Under ketamine-xylazine anesthesia, the animals were placed in the imaging chamber and scanned for 2 min at 90 kV, 88 μA, FOV 45 mm, and pixel size 90.0 μm. After scanning, the lung images were reconstructed by using the CosmoScan Database software of the micro-CT version 3.5.5.100 (Rigaku Corporation) and analyzed using the manufacturer-supplied software.

In vivo imaging of mouse lung. The in vivo imaging was performed by using an LSM 980 NLO (Carl Zeiss) equipped with an infrared laser (Chameleon Vision II, Coherent)^10,11. K18-hACE2 mice, C57BL/6J mice, and C57BL/6J HamSlc-ob/ob mice were infected with 10⁵ PFU of SARS-CoV-2-Venus or 10⁴ PFU of MA-SARS-CoV-2-Venus. The infected mice were intubated under anesthesia and ventilated at a respiratory rate of 120 breaths per minute. Isoflurane was continuously delivered at 2% to maintain anesthesia. The left lung lobe of the mice was exposed and gently immobilized with a custom-made thoracic suction window. In all experiments, Texas red dextran (70,000 Da, Invitrogen), 5 µg of Phycoerythrin (PE)-conjugated rat anti-mouse CD41 antibody (MWReg30; BD Biosciences), and 5 µg of Alexa Fluor 594-conjugated rat anti-mouse Ly-6G antibody (1A8, Biolegend) were injected i.v. before imaging to visualize the lung vascular structures, platelets, and vascular neutrophils, respectively. For the analyses of pulmonary perfusion, mice infected with SARS-CoV-2-Venus or MA-SARS-CoV-2-Venus were i.v. inoculated with Dio-labeled erythrocytes. A maximal intensity projection of the indicated frames (0–10 min) was generated to show the functional capillary perfused by the erythrocytes, as described previously³⁷. To acquire images in spectral imaging mode, lasers at wavelengths 488 nm, 543 nm, and 910 nm were used for simultaneous excitation of fluorochromes and Venus. All emitted light between 490- and 695-nm wavelengths was detected by using a 20× water-immersion lens (Carl Zeiss). Spectral separation of the acquired lambda stacks was achieved by using the linear unmixing function of the LSM software ZEN blue 3.3 (Carl Zeiss). Processing, assays, and data visualization were performed using CellProfiler 4.2.4 (Broad Institute), and in-house MATLAB (2022a) scripts (MathWorks). Tracking of the neutrophils in the denoised movies was performed by TrackMate (ImageJ, NIH).

Flow cytometry. Mouse lungs were dissociated using a Lung Dissociation Kit (Miltenyi) and gentleMACS Dissociator (Miltenyi) according to the manufacturer’s instructions for flow cytometry (FCM). Samples were then filtered through a 70-μm filter (Miltenyi) after red blood cell lysis and resuspended for subsequent FCM staining. For experiments staining intravascular neutrophils, mice were injected i.v. with 5 µg of PE-conjugated rat anti-mouse Ly-6G antibody (1A8, Biolegend) 5 min before lung collection. For surface staining, cells were stained for 10 min with antibodies in PBS containing 0.5% BSA and 2 mM EDTA. The following antibody clones were diluted 1:100 and used in these studies: Vio-Green-CD45 (REA737, Miltenyi), PE-NK1.1 (REA1162, Miltenyi), PE-Vio615-CD4 (REA604, Miltenyi), PE-Vio770-B220 (REA755, Miltenyi), APC-CD3 (REA641, Miltenyi), APC-Vio770-CD8a (REA601, Miltenyi), Vio-Blue-MHC class II (REA813, Miltenyi), FITC-Ly-6C (REA796, Miltenyi), PE-Vio615-Ly-6G (REA526, Miltenyi), PE-Vio770-CD11c (REA754, Miltenyi), APC-Siglec-F (REA798, Miltenyi), APC-Vio770-CD11b (REA592, Miltenyi), APC-CD44 (IM7 Biolegend), APC- Pecam-1 (W18222B, Biolegend), APC-CD62L (MEL-14, Proteintech), APC-CD62E (P2H3, Invitorogen), and APC-CD162 (4RA10, Elabscience). APC conjugation to the anti-CD62E mouse IgG1 antibody was performed using the APC Labeling Kit-NH2 (Wako) according to the manufacturer’s protocol.

Populations of immune cells were defined as follows: B cells (CD45⁺ CD3⁻ B220⁺), NK cells (CD45⁺ CD3⁻ B220⁻ NK1.1⁺), CD4 T cells (CD45⁺ CD3⁺ B220⁻ CD4⁺ CD8⁻), CD8 T cells (CD45⁺ CD3⁺ B220⁻ CD4⁻ CD8⁺), alveolar macrophages (CD45⁺ CD11b^dim Siglec-F⁺ CD11c⁺ MHC class II⁺), dendritic cells (CD45⁺ CD11b⁻ Siglec-F⁻ CD11c⁺), neutrophils (CD45⁺ CD11b^high Ly-6G⁺), eosinophils (CD45⁺ CD11b^high Siglec-F⁺ Ly-6G⁻ CD11c⁻), and monocytes (CD45⁺ CD11b^high Siglec-F⁻ Ly-6G⁻ MHC class II⁻ Ly-6C^high). Samples were analyzed on a flow cytometer (MACSQuant Tyto, Miltenyi).

Neutrophil motility analysis. To track the movement of neutrophils, 5 µg of PE-conjugated rat anti-mouse Ly-6G antibody was injected i.v. into the mice. Neutrophils were imaged at approximately 4 fps for 230 s. All movies were corrected for respiratory motion artifacts and denoised. Single object tracking was performed by using TrackMate (ImageJ, NIH) to obtain the trajectories of individual neutrophils. For each neutrophil, speeds were measured for individual steps in its trajectory and subsequently defined as slow (≤50 µm/s) or rapid (>50 µm/s). We then examined whether a neutrophil performed rapid movement and calculated the durations it engaged in continuous slow movements without being interrupted by the rapid movement.

Quantification of platelet aggregates. CD41 signals were detected in a semi-automated manner by using CellProfiler (Broad Institute), and then divided into three populations according to their sizes: signals covering <8.57 µm² (50 pixels) were defined as a “single platelet”, signals ≥8.57 µm² and <34.28 µm² (200 pixels) as “aggregated platelets”, and signals ≥34.28 µm² as “thrombocytes”. The frequency analysis of the CD41 signals was conducted using in-house MATLAB scripts (MathWorks).

In vivo depletion of neutrophils. C57BL/6J HamSlc-ob/ob were administered 100 µg of anti-rat Kappa immunoglobulin (MAR18.5, Bioxcell) daily for two days prior to infection as described previously⁴⁷. In addition, 50 µg of Anti-Ly-6G (1A8, Bioxcell) and corresponding isotype control (2A3, Bioxcell) were administered every other day from one day prior to infection. When mice were sequentially injected with two antibodies, an interval of more than 2 h was set between injections.

scRNA-seq data re-analysis. We reanalyzed two published PBMC scRNA-seq datasets for healthy and SARS-CoV-2-infected humans^9,23. For the published data from Wilk et al.⁹ preprocessed scRNA-seq count data with embedding, clustering, and cell-type assignment were obtained as an RDS file from the COVID-19 Cell Atlas (https://www.covid19cellatlas.org/#wilk20) hosted by the Wellcome Sanger Institute. For the published data from Xu et al.²³ we downloaded transcript-by-cell matrices from NCBI (GSE216020) and preprocessed using the Seurat v4⁴⁸ package and DoubletFinder⁴⁹, which identifies and removes potential doublets²³. Cells with less than 500 UMI counts, less than 200 detected genes, and more than 20% mitochondrial gene counts were removed as low-quality cells, as well as potential doublets. Data integration of all samples was performed using the FindIntegrationAnchors and IntegrateData functions in Seurat with the top 3000 most variable genes selected by the FindVariableFeatures function. Cell-type annotation was based on marker genes of each cluster defined by FindAllMarkers functions. The subset corresponding to neutrophils in both datasets (Wilk et al. and Xu et al.) was used for differential gene expression analysis related to cell adhesion²⁴ and neutrophil extracellular trap formation (KEGG: hsa04613), respectively.

Statistics and reproducibility. All animals were randomly allocated to experimental groups. No blinding was performed in any experiment. Sample sizes were based on our previous work. GraphPad Prism 10.3.1, R 4.1.0, and Rstudio 2023.06.1+524 were used to analyze all data, and differences were considered to be statistically significant when the p-value was less than 0.05. No adjustment for multiple comparisons was performed except for the differential gene expression analysis of the scRNA-seq data (Fig. 8c and Supplementary Fig. 3). For Figs. 1d, 2b, d, 5c, d, f, and 9b, data were analyzed by using non-parametric, two-tailed Student’s t-test and p-values are shown in each figure. For Fig. 2c, data were analyzed by using Dunnett’s test and p-values are shown in the figure. For Figs. 4a, e, 5b, and 7, data were analyzed by using Sidak’s test and p-values are shown in each figure. For Fig. 4d, data were analyzed by using the Mann-Whitney test. For Fig. 8c and Supplementary Fig. 3, data were analyzed by using the Wilcoxon signed rank test and the p-values were corrected by using the Benjamini-Hochberg Procedure and are shown in each figure. For Figs. 1b–d, 2d, e, 4b, 5a, and 6a, b, at least three experiments were performed with biologically independent animals and similar results were obtained. Figure 2d is a microphotograph cropped from Fig. 1b.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

The scRNA-seq data used in this study are available in the Gene Expression Omnibus database under accession code GSE150728 and GSE216020. Source data are provided with this paper.

Code availability

The code used in this study is available at: https://github.com/tken18/2024NatCom_Neutrophil.

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Acknowledgements

We thank S. Watson for editing the manuscript. We also thank Yuko Sato and Seiya Ozono for their technical assistance. This research was supported by a Research Program on Emerging and Re-emerging Infectious Diseases from the Japan Agency for Medical Research and Development (AMED) (JP19fk0108113, JP20fk0108412, JP21fk0108552, JP243fa627001) by a Japan Program for Infectious Diseases Research and Infrastructure from AMED (JP24wm0125002), the Japan Society for the Promotion of Science (JSPS) (21K14984), the Japan Science and Technology Agency (JST) (Moonshot R&D) (JPMJMS2025), and by the NIAID-funded Center for Research on Influenza Pathogenesis (CRIP; HHSN272201400008C). H.U. was supported by GSK Japan Research Grant 2020, the Astellas Foundation for Research on Metabolic Disorders, the Naito Foundation, the Sumitomo Foundation, the Ichiro Kanehara Foundation, the Uehara Memorial Foundation, the Okinaka Memorial Institute for Medical Research, a Japanese Respiratory Foundation Grant, the Mochida Memorial Foundation for Medical and Pharmaceutical Research, the SENSHIN Medical Research Foundation, the Takeda Science Foundation and Kao Research Council for the Study of Healthcare Science. IH.W., HW.H., and CH.W. were supported by the National Science and Technology Council, Taiwan (MOST-110-2320-B-001-005-MY3). M.I. was supported by the Takeda Science Foundation.

Author information

These authors contributed equally: Hiroshi Ueki, I-Hsuan Wang.

Authors and Affiliations

Division of Virology, Institute of Medical Science, University of Tokyo, Tokyo, Japan
Hiroshi Ueki, Maki Kiso, Michiko Ujie, Masaki Imai & Yoshihiro Kawaoka
Center for Global Viral Diseases, National Center for Global Health and Medicine Research Institute, Tokyo, Japan
Hiroshi Ueki, Masaki Imai & Yoshihiro Kawaoka
Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
I-Hsuan Wang, Hung-Wei Hsu & Chen-Hui Henry Wu
Department of Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan
Kenta Horie & Eiryo Kawakami
Institute for Advanced Academic Research (IAAR), Chiba University, Chiba, Japan
Kenta Horie & Eiryo Kawakami
Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
Shun Iida, Sohtaro Mine & Tadaki Suzuki
Taiwan International Graduate Program in Molecular Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
Chen-Hui Henry Wu
Department of Infectious Diseases and Host Defense, Gunma University Graduate School of Medicine, Gunma, Japan
Wataru Kamitani
Advanced Data Science Project, RIKEN Information R&D and Strategy Headquarters, RIKEN, Kanagawa, Japan
Eiryo Kawakami
Department of Special Pathogens, International Research Center for Infectious Diseases, Institute of Medical Science, University of Tokyo, Tokyo, Japan
Yoshihiro Kawaoka
Department of Pathobiological Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, USA
Yoshihiro Kawaoka
The University of Tokyo, Pandemic Preparedness, Infection and Advanced Research Center, Tokyo, Japan
Yoshihiro Kawaoka

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Hiroshi Ueki
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Contributions

H.U., M.K., S.I., S.M., and T.S. performed the mouse infection experiments, titrated the virus in organs, and analyzed pathology. M.U. analyzed the micro-CT images. H.U. performed the in vivo imaging analysis and flow cytometry. H.U., IH.W., HW. H., and CH.W. performed image data analyses. W.K. generated the Venus-expressing SARS-CoV-2. H.U., K.H., and E.K. analyzed the single-cell RNA-seq data. H.U., M.I, T.S., and Y.K. obtained funding. H.U. and Y.K. conceived the study and supervised the research. H.U. and Y.K. wrote the initial draft, with all other authors providing editorial comments.

Corresponding authors

Correspondence to Hiroshi Ueki or Yoshihiro Kawaoka.

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Competing interests

Y.K. has ongoing unrelated collaborations and/or sponsored research agreements with Daiichi Sankyo Pharmaceutical, Toyama Chemical, Tauns Laboratories, Inc., Shionogi & Co. Ltd, Otsuka Pharmaceutical, and KM Biologics and has received royalties from MedImmune and Integrated Biotherapeutics. The remaining authors have no competing interests to declare.

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Nature Communications thanks Zhichao Ai, Pradeep Uchil, and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

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Ueki, H., Wang, IH., Kiso, M. et al. Neutrophil adhesion to vessel walls impairs pulmonary circulation in COVID-19 pathology. Nat Commun 16, 455 (2025). https://doi.org/10.1038/s41467-024-55272-0

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Received: 01 February 2024
Accepted: 05 December 2024
Published: 13 January 2025
DOI: https://doi.org/10.1038/s41467-024-55272-0