Persistent alveolar bronchiolization, interstitialbrosis and impaired lung function post-exercise
are features of long-COVID in SARS-CoV-2-Delta
variant infected aged hamsters
Wolfgang Baumgärtner

Department of Pathology, University of Veterinary Medicine, Foundation https://orcid.org/0000-00018151-5644
Laura Heydemann
Department of Pathology, University of Veterinary Medicine, Foundation, Hanover, Germany
https://orcid.org/0000-0002-9958-4872
Małgorzata Ciurkiewicz
Department of Pathology, University of Veterinary Medicine, Foundation, Hanover, Germany
Theresa Störk
University of Veterinary Medicine https://orcid.org/0000-0002-0395-274X
Isabel Zdora
University of Veterinary Medicine
kirsten Hülskötter
Department of Pathology, University of Veterinary Medicine, Foundation, Hanover, Germany
Katharina Gregor
Department of Pathology, University of Veterinary Medicine, Foundation, Hanover, Germany
Lukas Michaely
Department of Pathology, University of Veterinary Medicine, Foundation, Hanover, Germany
Wencke Reineking
University of Veterinary Medicine, Foundation, Hanover, Germany https://orcid.org/0000-0002-82237233
Tom Schreiner
Department of Pathology, University of Veterinary Medicine https://orcid.org/0000-0002-0978-2067
Georg Beythien
Department of Pathology, University of Veterinary Medicine, Foundation https://orcid.org/0000-00022192-2413
Asisa Volz

University of Veterinary Medicine Hanover, Institute for virology https://orcid.org/0000-0001-87573896
Maren von Koeckritz-Blickwede
University of Veterinary Medicine https://orcid.org/0000-0001-7712-9767
Tamara Tuchel
Department of Virology, University of Veterinary Medicine, Foundation, Hanover, Germany
Christian meyer zu natrup
Department of Virology, University of Veterinary Medicine, Foundation, Hanover, Germany
Lisa-Marie Schünemann
Department of Virology, University of Veterinary Medicine, Foundation, Hanover, Germany
Sabrina Clever
Department of Virology, University of Veterinary Medicine, Foundation, Hanover, Germany
Dirk Schaudien
Fraunhofer Institute for Toxicology and Experimental Medicine
Karl Rohn
Department of Biometry, Epidemiology and Data Management, University of Veterinary Medicine,Foundation, Hanover, Germany
Klaus Schughart
Helmholtz Centre for Infection Research https://orcid.org/0000-0002-6824-7523
Robert Geffers
Helmholtz Centre for Infection Research, Braunschweig https://orcid.org/0000-0003-4409-016X
Mika Kaneko
Tohoku University Graduate School of Medicine https://orcid.org/0000-0002-4158-9208
Yukinari Kato
Tohoku University https://orcid.org/0000-0001-5385-8201
Federico Armando
Department of Pathology, University of Veterinary Medicine, Foundation, Hanover, Germany; Pathology
unit, Department of Veterinary Science, University of Parma, Parma, Italy

ArticleKeywords:
Posted Date: July 15th, 2024
DOI: https://doi.org/10.21203/rs.3.rs-4681343/v1
License:   This work is licensed under a Creative Commons Attribution 4.0 International License.
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Additional Declarations: There is NO Competing Interest.

123

Persistent alveolar bronchiolization, interstitial fibrosis and impaired lungfunction post-exercise are features of long-COVID in SARS-CoV-2-Delta variant
infected aged hamsters

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Laura Heydemann1, §, Małgorzata Ciurkiewicz1, §, Theresa Störk1, Isabel Zdora1, Kirsten
Hülskötter1, Katharina Manuela Gregor1, Lukas Mathias Michaely1, Wencke Reineking1,
Tom Schreiner1, Georg Beythien1, Asisa Volz2,4, Maren von Köckritz-Blickwede3,4,
Tamara Tuchel2,4, Christian Meyer zu Natrup2,4, Lisa-Marie Schünemann2,4, Sabrina
Clever2,4, Dirk Schaudien5, Karl Rohn6, Klaus Schughart7,8, Robert Geffers9, Mika k.
Kaneko10, Yukinari Kato10, Wolfgang Baumgärtner1, # and Federico Armando1, 11, #

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1Departmentof Pathology, University of Veterinary Medicine, Foundation, Hanover,Germany
2Department of Virology, University of Veterinary Medicine, Foundation, Hanover,Germany
3Department of Biochemistry, University of Veterinary Medicine, Foundation, Hanover,Germany
4Research Center for Emerging Infections and Zoonoses (RIZ), University of Veterinary
Medicine, Foundation, Hanover, Germany
5Fraunhofer Institute for Toxicology and Experimental Medicine (ITEM), Hanover,Germany
6Department of Biometry, Epidemiology and Data Management, University of Veterinary
Medicine, Foundation, Hanover, Germany
7Department of Microbiology, Immunology and Biochemistry, University of Tennessee
Health Science Center, Memphis, Tennessee, USA,
8Institute of Virology Münster, University of Münster, Münster, Germany
9Helmholtz Centre for Infection Research (HZI), Brunswick, Germany
10 Department of antibody drug development,Tohoku University, Sendai, Miyagi, Japan
11Pathology unit, Department of Veterinary Science, University of Parma, Parma, Italy§ These authors contributed equally as co-first authors# These authors contributed equally as co-last authors

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Correspondence and requests for materials should be addressed to Wolfgang
Baumgärtner. Wolfgang.baumgaertner@tiho-hannover.de

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1

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Abstract37

Long-term consequences of SARS-CoV-2 infection affect the life quality of millions of38

people and pose a heavy burden on the public health sector. The underlying causes,

39

pathomechanisms and morphological correlates are still largely unknown and further

40

research in appropriate animal models is needed. The goal of the study was to41

characterize the trajectory of lung regeneration over a period of 112 days in the hamster

42

model by combining morphological, transcriptome analysis and functional readouts. We

43demonstrate that in the acute phase, SARS-CoV-2 Delta-infected, male, aged hamsters

44

show a severe impairment of lung function in a resting state. In the chronic phase of the45

disease, similar impairments are appreciable until 7 weeks post infection only after46

exercise on a rodent treadmill. The hamster model recapitulates chronic pulmonary fibrotic

47

changes observed in many patients with respiratory long COVID, but does not show extra-

48

pulmonary long term lesions. We show that sub-pleural and interstitial pulmonary fibrosis

49

as well as alveolar bronchiolization persist until 112 dpi. Interestingly, CK8+ alveolar

50

differentiation intermediate (ADI) cells are becoming less prominent in the alveolar

51

proliferation areas from 28 dpi on. Instead, CK14+ airway basal cells and SCGB1A1+ club

52

cells, expressing cell proliferation markers, mainly populate alveolar bronchiolization

53

areas at later time-points. We postulate that pulmonary fibrosis and SCGB1A1+ club cell54

rich areas of alveolar bronchiolization represent potential risk factors for other diseases in

55

long-COVID survivors.

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2

58

Introduction

59

In 2023, the WHO officially declared an end to the public health emergency caused by the60

severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)1. Acute case numbers have61

been on a stable downward trend since the beginning of 2023. However, as the cases of62

acute diseases decline, the concern shifts to sub-acute and persistent, complications of the63

acute infection. Symptoms are frequently observed in multiple organ systems like the64

respiratory tract or the nervous system and can persist for 4 weeks or more2-8. Relapses and65

the development of new symptoms after 30 or more days after the initial infection are also

66

reported7. This condition has been termed “post-acute sequelae of COVID-19” (PASC) or

67

long-COVID. Respiratory PASC is now one of this disease most common phenotypes9.

68

Around 12 % of patients suffer from symptoms like chest pain, ageusia or anosmia,

69

shortness of breath, dyspnea or general fatigue 9. PASC is reported especially in patients70

that suffered from severe acute disease10. Multiple mechanisms of pathogenesis have been

71

proposed, including immunological dysfunction11,12, viral persistence or latent virus

72

reactivation13,14, manipulation of host mitochondria15 and, specifically in the lung, impairment

73

of gas exchange due to dysregulated alveolar regeneration 16 and fibrosis17. Correlating74

pathomorphological changes with in vivo lung function analysis would be helpful to better

75

understand respiratory long-COVID. In our previous work18, we demonstrated that the Syrian

76

golden hamster (Mesocricetus auratus) represents a suitable animal model to study alveolar

77

regenerative mechanisms following SARS-CoV-2 infection in the acute to subacute phase

78

until 14 days post-infection (dpi). We found that foci of peribronchiolar epithelial proliferation

79

derived from airway progenitors and cytokeratin 8 (CK8)+ alveolar differentiation intermediate80(ADI) cells persist until 14 dpi. These foci were accompanied by the onset of lung fibrosis,

81

indicating a dysregulated regeneration. In the current work, we sought to expand these82

findings and determine whether this process is associated with functional impairment and83

whether it resolves over time, and consequently to determine if the hamster model can be84

used for research on respiratory long-COVID. Based on what is known about long-COVID in85

humans and hamsters, we hypothesized: i) SARS-CoV-2 infection induces long lasting lung86

function impairment; ii) akin to what is reported in humans in the chronic phase of the87

disease, physical exercise-induced stress would exacerbate this lung function impairment;

88iii) the underlying cause of this impairment is a dysregulated alveolar regeneration. The

89

current longitudinal study evaluated a series of parameters over a period of 16 weeks (1123

90days), based on the observation that patients suffering from long-COVID tend to have91

symptoms for more than 12 weeks2. Only male, aged (~ 1-year-old) hamsters were chosen

92

for the study due to the reported sex-related increased severity of clinical signs19-21. SARS-93

CoV-2 Delta-variant was chosen since it showed the most prominent pulmonary pathology

94

among the most diffuse variants worldwide at the time 22,23.

95

Our goal was to provide comprehensive insights into the trajectory of post-acute sequelae of96

a respiratory SARS-CoV-2 infection in the hamster model, focusing on correlating

97

pathomorphological findings with lung functional parameters. Serial, non-invasive lung98

function data was gathered using a combination of whole body plethysmography (WBP) with99

respiratory gas analysis combined with exercise on a rodent treadmill. Findings were100

consecutively related to morphological, transcriptomic and protein expression data. Our

101

study shows that (i) in the acute phase, SARS-CoV-2-infected hamsters show a severe102

impairment of lung function in a resting state, which resolves at 10 dpi and is associated with

103

acute pneumonia and transcriptomic changes dominated by immune responses; (ii) an

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altered lung function is detectable after mild physical exercise in the sub-acute and chronic

105

phase, lasting until 7 weeks post infection; (iii) histological alterations of lung architecture106

persist until 112 dpi, including sub-pleural and interstitial fibrosis as well as bronchiolization,107

and are associated with prolonged presence of M2-like macrophages and pro-fibrotic

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transcriptomic changes; (iv) CK8+ ADI cells do not persist beyond 28 dpi; (v) airway

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progenitor cells dominate the cellular composition within the alveolar epithelial proliferation

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areas in the subacute and chronic phase and SCGB1A1+ club cells are the predominant cell

111

type in bronchiolization foci; (vi) Ki67 expression is detectable in bronchiolization areas until

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112 dpi, suggestive of ongoing proliferative activity.

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Results
1. SARS-CoV-2 Delta infection markedly affects lung function during the acutephase of the disease in aged hamsters

117

Male, 1-year old Syrian hamsters were infected with SARS-CoV-2 Delta variant and118

sacrificed at 1, 3, 6, 14, 28, 56 and 112 dpi. During the experiment, repeated lung function

119

measurements were conducted using a combination of whole-body plethysmography

120(WBP) with respiratory gas analysis prior and after exercise on a rodent treadmill (when121

performed). Physical exercise was used to exacerbate possible latent respiratory

122

impairment at the later phase of infection. Accordingly, our study design allowed to123

distinguish three phases of the disease: acute phase (infection – 6 dpi), sub-acute phase124(14 dpi), and chronic phase (28 dpi – 112 dpi). Due to animal welfare reasons, physical

125

exercise-induced stress was only applied to animals from 21 dpi onwards (Supplementary126

Fig. 1). For this reason, the clinical results of the acute and sub-acute phases will be

127

shown separately from the chronic phase. The acute disease presented with weight loss,

128

upper respiratory symptoms and behavioral changes. In the first week after the infection,

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most SARS-CoV-2-infected animals (34/48) lost up to 10 % of their initial body weight.

130

Fewer animals (3/48) lost up to 15 %, while one had a maximum weight loss of 17 % at 6

131

dpi. This weight loss was transient, and the animals began to gain weight from around 7

132

dpi onwards (Fig. 1 a). Upper respiratory signs mainly consisted of mild sneezing and133

nasal discharge, which subsided around day 8 (Fig. 1 a). Mild behavioral changes such134

as reduced grooming and reduced activity were observed in 19/48 animals up until 10 dpi.

135

(Supplementary data 1). Based solely on the weight loss and clinical scoring, we were136

able to monitor acute disease severity according to previously performed COVID-19

137

studies22,24,25. However, lower respiratory tract signs such as dyspnea or labored138

breathing were not clearly evident by clinical monitoring. Assessment of subtle lower

139

respiratory signs and altered breathing is difficult in hamsters, particularly in aged males

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which have a high amount of subcutaneous fat that masks chest movement. To provide a

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more sensitive and precise readout of lung function, WBP was performed.

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WBP revealed marked mechanical and metabolic lung function changes in the acute143

phase of the disease. Here, we focused on specific mechanical metrics such as

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respiratory rate (f), Penh (enhanced pause), EF50 (mid expiratory flow), vO2 (O2 uptake)5

145

and vCO2 (CO2 production). Infected hamsters showed a significantly decreased

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respiratory rate (f) and EF50 as well as a significantly increased Penh at 3 and 6 dpi

147

compared to mock animals, indicating potential perturbation of breathing and limited

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bronchiolar airflow (Fig. 1 b). Moreover, O2 uptake and CO2 production were significantly

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reduced at 3 and 6 dpi in SARSCoV-2-infected hamster compared to mock-animals. This150

could indicate reduced gas exchange capacity, perfusion or metabolic activity. Similar to151

mechanical WBP changes, this difference between SARS-CoV-2 and mock-infected152

animals was not observed from 10 dpi onwards (Fig. 1 b).

153

To summarize, the acute disease induced by SARS-CoV-2 Delta variant infection was154characterized by weight loss, nasal discharge, and reduced activity. While no signs of155

lower respiratory tract distress were detected by clinical monitoring, significant lung156

function changes were detected by WBP. These changes were marked, transient and157

disappeared around 10 dpi. However, based on studies in long-COVID-patients26, we158

hypothesized that an alteration in lung function in the chronic phase of the disease could

159

be underlined in a situation of physical stress. To substantiate our hypothesis, we

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evaluated lung function at later time-points before and after inducing physical stress, i.e.

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running on a rodent treadmill.

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2. Lung function alterations are detectable after physical exercise on a rodent

163

treadmill in aged hamsters recovering from SARS-CoV-2 Delta infection

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After the resolution of acute SARS-CoV-2 infection, hamsters did not show any respiratory

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or behavioral signs at the daily clinical evaluation. However, infected hamsters did not

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recover their initial body weight, which remain stable between 12 and 63 dpi. A gradual167

weight loss was observed in mock and SARS-CoV-2-infected animals, starting from 63

168

dpi (Fig. 1 a). One animal died unexpectedly due to atrial thrombosis. The weight loss at169

the later time-points and atrial thrombosis were interpreted as age-related or spontaneous170

background pathology and considered unrelated to the infection 27-29. In line with the lack171

of clinical signs related to infection, no marked differences between the two groups in172

neither mechanical nor metabolic parameters were detected by WBP in a resting state.

173

Long-COVID-patients often suffer from reduced pulmonary function, which can be

174

exacerbated by physical exercise 26,30. To reproduce this condition experimentally, we

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used a combination of WBP and exercise on a rodent treadmill in the chronic phase of the6176

disease. From 21 dpi onwards, the animals underwent mild physical exercise once a177

week, consisting of 10 minutes of running on a treadmill, with a slight upward slope and178

gradually increasing speed (10 m/min to 15 m/min). The intensity of training was well179

tolerated by the animals, with none of the animals displaying signs of exhaustion.

180

Interestingly, after mild exercise, SARS-CoV-2-infected animals showed a lower

181

respiratory rate (f) compared to the non-infected group until around 7 weeks after infection.

182

A slight increase of Penh was observed after exercise. A mild decrease of EF50 was

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observed in SARS-CoV-2-infected animals compared to controls around similar time-

184

points (Fig. 1c). Moreover, O2 uptake and CO2 production showed the most marked

185

differences with significant differences from 21 dpi until 49-56 dpi. Differences in186mechanical and metabolic values became less prominent around 56 dpi (Fig. 1c) and187

were no longer detectable at 112 dpi.

188

In summary, these results demonstrate that exercise can enable the detection of189

underlying alterations of lung function persisting even 7 weeks after infection with SARS-

190

CoV-2 in the Syrian golden hamster model. These findings mirror the decreased

191

pulmonary capacity observed in long-COVID-patients after physical exercise26,30,

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confirming the hamster as a suitable model for studying long-term pulmonary effects of

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SARS-CoV-2

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pathomorphological and transcriptomic changes associated with these findings.

infection.

Our

next

aim

was

to

characterize

theunderlying

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Fig. 1 SARS-CoV-2 infection causes lung function changes that are exacerbated byexercise in aged hamsters

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a Left panel: Relative body weight (% starting body weight) of SARS-CoV-2 and mockinfected hamsters over time. Right panel: Total clinical score (including weight loss,
respiratory, and behavioral signs) of SARS-CoV-2 and mock-infected hamsters over time.
Data was collected daily until 21 days post infection (dpi) and weekly from 21 to 112 dpi.
b Results of whole body plethysmography (WBP) measurements from 0 to 14 dpi without
exercise prior to the measurement. From left to right: frequency (f), enhanced pause(Penh), mid tidal expiratory flow (EF50), volume of O2 uptake and CO2 production. c
Results of WBP measurements from 21 to 112 dpi. Upper row: measurements taken
before exercise. Lower row: measurements taken immediately after exercise on a rodent
treadmill (10 minutes with accelerating speed starting at 10m/min and ending at 15 m/min
at a 5° upward slope). From left to right: f, Penh, EF50, volume of O2 uptake andCO2.production. In a-c graphs show mean and SEM. Data from WBP measurements were
tested by two-tailed Mann–Whitney U test. A p value of ≤0.05 was chosen as the cutoff
for statistical significance. N= 8 animals/group (a, b) or 6 animals/group (c). Source data
is provided as a Source Data file.
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3. RNA sequencing analysis reveals distinct transcriptomic signatures in acute,215

sub-acute and chronic SARS-CoV-2 Delta infection in aged hamsters

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In order to gain insight into transcriptomic changes associated with sub-acute and217

especially long-term functional sequelae of SARS-CoV-2 infection, we performed bulk

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RNA sequencing (RNAseq) of lung tissues at 1, 3, 6, 14, 28, 56, and 112 dpi. Principal

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component analysis (PCA) of gene expression levels distinctly separated mock-infected

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and SARS-CoV-2-infected hamsters. The most pronounced response to infection was

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observed at 6 dpi. Moreover, SARS-CoV-2-infected animals in the acute phase (1, 3, and222

6 dpi) of the disease clearly separated from animals in the sub-acute (14 dpi) and chronic

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stages (28, 56, and 112 dpi; Fig. 2a).

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Pairwise comparison between mock-treated and infected animals revealed the presence

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of a variable number of up- and down-regulated differentially expressed genes (DEGs) at

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all time-points. Transcriptomic changes indicated a strong response to infection in the227

acute phase, with 75, 2020, and 3007 DEGs at 1, 3, and 6 dpi, respectively. This response228

was lower in the sub-acute phase (566 DEGs at 14 dpi) and further decreased throughout229

the chronic phase (587, 56, and 22 DEGs at 28 dpi, 56 dpi, and 112 dpi, respectively).

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Notably, 6 dpi was the time-point with the highest number of DEGs with 1340 up-regulated

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and 1667 down-regulated (Fig. 2b-c; Supplementary data 2). Pathway enrichment

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analysis showed that at 6 dpi, most of the up-regulated genes were involved in immune

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cell proliferation, activation, regulation, and signaling (Fig. 2d). Most of the down-regulated234

genes play a role in angiogenesis, extracellular matrix organization, and regulation of235

nervous system development (Fig. 2e). It should be noted that RNAseq analysis

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performed in this study was made primarily to validate and support our morphological237

findings, which will be elaborated in detail in the subsequent sections. For this reason, an

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in-depth analysis of all DEGs and pathways at all time-points was not performed.

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However, the full data set is accessible to the research community for any additional

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analyses (see data availability statement).

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For the sub-acute and chronic phases of the disease, we focused on DEGs that were242

unique to each time-point. 504, 534, 22, and 18 DEGs at 14, 28, 56, and 112 dpi,

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respectively (Fig. 3 a).
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Remarkably, among the DEGs unique to 14 dpi, several genes encoding collagen were245

identified, including: Col3a1, Col11a1, Col17a1, Col1a2, Col1a1. In addition, there were246

genes encoding for cytokeratin 14 (Krt14 gene), mainly expressed by airway basal cells,

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as well as Scgb3a2, Scgb3a1 genes mainly expressed by club cells. Also, among the 28

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dpi unique DEGs there were genes encoding for collagen production (i.e. Col6a3, Col6a5,

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Col4a2, Col4a3, Col4a1). Similarly, at 56 dpi, among the unique DEGs were genes

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involved in extracellular matrix remodeling/deposition (i.e.Col9a1, Col2a1, Adam12) as

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well as receptors for GABA-A (Gabrp) and ephrin (Ephb1). Most importantly, Sox9, which252

is reported to play multiple roles in the lung epithelium, balancing proliferation and253

differentiation and regulating the extracellular matrix31, was exclusive at 56 dpi. Among254

the 112 dpi unique DEGs were genes like Mmp9 and Mmp25, which are involved in

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extracellular matrix remodeling/deposition. Other interesting genes upregulated at 112 dpi

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were S100a8 and S100a9. These genes encode for proteins involved in the pathogenesis257

of cystic fibrosis and COVID-1932,33. A full list of Up- and Down-regulated DEGs at the258

given time-points is available in supplementary material (Supplementary data 3).

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Pathway enrichment analysis of the DEGs unique to 14 dpi showed that some of the260

genes were involved either in the modulation of chemical synaptic transmission or in the261

regulation of trans-synaptic signaling (Fig. 3 b). At 28 dpi, some unique DEGs belonged262

to small GTPase-mediated signal transduction, cell-cell adhesion via plasma-membrane

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adhesion molecules, and homophilic cell adhesion via plasma-membrane adhesion

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molecules (Fig. 3 c). In contrast, only three 56 dpi unique DEGs belonged to cell

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aggregation (Fig. 3 d).

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Notably, 14 dpi shared 36 DEGs and 19 DEGs with 28 dpi and 56 dpi, respectively. All

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three time-points together shared 6 DEGs. Similarly, 28 dpi and 56 dpi shared 6 DEGs.

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On the other hand, 112 dpi only shared 2 DEGs with 56 dpi, 1 DEG with 28 dpi and only269

1 DEG with 14, 28, and 56 dpi (Fig. 3 a). In particular, among the 36 shared DEGs between

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14 dpi and 28 dpi were multiple genes involved in neuronal growth, plasticity and signaling,

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such as Slc17a7, Tagln3, Plppr1, Th, Cam2kb, and Grin1. Additionally, there were genes

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involved in extracellular matrix remodeling/deposition like Adamts4 and Lox or in cell273

migration like Map7d2. Among the 19 shared DEGs between 14 dpi and 56 dpi was a274

gene involved in the negative regulation of Notch signaling (Dlk2), a gene encoding for a
10

275

protein associated with collagen (Emilin3), a gene that promotes the cell cycle (Wee1)

276

and most importantly Krt 15 gene which is reported to be also expressed by airway basal277

cells34. Among the 6 DEGs shared by 14 dpi, 28 dpi and 56 dpi there was a gene encoding

278

for a member of the cytochrome P450 superfamily (Cyp2e1) and a gene involved in the279

regulation of interferon-stimulated gene expression (Arntl)35,36. Interestingly, DEGs shared280

by 28 dpi and 56 dpi were Fat2, involved in cell adhesion and cell proliferation, and281

Col9a3, encoding for type IX collagen.

282

Overall, transcriptome analysis reveals the presence of distinct sets of DEGs across all

283

three phases of SARS-CoV-2 infection in hamsters. The strength of the host response in284

terms of DEGs confirmed the three phases of the disease (acute, sub-acute, and chronic).

285

In the acute phase, transcriptomic changes were dominated by immune cell proliferation,286

activation, regulation, and signaling while in the sub-acute and chronic phase, modulation287

of chemical synaptic transmission, extracellular matrix remodeling/deposition, cell288

migration and cell aggregation were more prominent. Our transcriptome data also

289

supported many of our pathomorphological findings and their interpretations elaborated

290

below in the following sections.

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Fig. 2 RNA sequencing analysis reveals the strongest host response at 6 dpi in
SARS-CoV-2 infected aged hamsters

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Bulk RNAseq analysis in lungs of SARS-CoV-2 infected hamsters at 1, 3, 6, 14, 28, 56
and 112 dpi. a Principle Component Analysis (PCA) showing PC1 and PC6, which werecorrelated with infection. Mock and SARS-CoV-2 infected animals are represented by dots
and squares, respectively. Different colors represent different time-points. b Bar plot of
the number of differentially expressed genes (DEGs) in infected versus mock-treatedanimal per dpi. Up-regulated DEGs are shown in red and down-regulated in blue. c
Volcano plot showing the DEGs at 6 dpi. y-axis: -log10 BH multiple testing adjusted pvalues, x-axis: log2-fold change. DEGs (absolute log2-fold change > 1 and adjusted pvalue < 0.05) are colored red and the top 20 up- and down-regulated (by log2-fold change)
DEGs are labeled. Blue: genes with adjusted p-value < 0.05. Yellow: genes with absolutelog2-fold change > 1. d-e Cluster profiler of EnrichGO pathway analysis for up- and downregulated DEGs from the contrasts of infected hamsters versus mock-treated controls at
6 dpi. Left panel: Dot plots of up- (in e) and down- (in d) regulated pathways. The y-axis
shows the enriched pathways and the x-axis shows the GeneRatio (gene-count/total
number of genes). Dot size indicates the number of genes and color indicates the p-value.
Right panel: Gene-concept network depicting the linkages of genes and pathways of thegenes involved in the up- (in e) and down- (in d) regulated pathways at 6 dpi. Dot-size ofthe labeled pathways indicates the size of the gene-count belonging to that pathway andcolor indicates the fold change.

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Fig. 3 Bulk RNAsequencing analysis reveals the presence of distinct DEGs in the
sub-acute and chronic phases of the disease

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a UpSet plot of unique DEGs and overlapping DEGs at different dpi from the sub-acuteand chronic phases (14, 28, 56, 112 dpi). The total number of DEGs associated with eachdpi is depicted in the colored histogram to the left. The scheme below the boxplots depicts
unique or overlapping numbers of DGEs at a given dpi. Connected dots represent DEGs
shared by two or more dpi. The number of unique or overlapping DEGs are shown in thehistogram on top. b-d Cluster profiler of EnrichGO pathway analysis for unique DEGs at
14, 28, 56 dpi shown in the Upset plot. The y-axis shows the enriched pathways and thex-axis shows the GeneRatio (gene-count/total number of genes). Dot size indicates thenumber of genes and color change indicates the p-value.

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4. SARS-CoV-2 Delta infection induces transient inflammation and persistentlung lesions in aged hamsters

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Infection was confirmed by immunohistochemical staining and quantification of SARS-331

CoV-2 nucleoprotein (NP) antigen in the lung. As described previously18, viral antigen was332

present in the alveoli and airways cells as well as in alveolar macrophages

333(Supplementary Fig. 1). Positive cells were detected as early as 1 dpi with a peak at 3 dpi.

334

At 6 dpi, virus clearance was completed in all SARS-CoV-2-infected animals

335(Supplementary Fig. 1). Mock animals showed no positive signal at any time-point.

336

RNAseq revealed no SARS-CoV-2 spike (S) and nucleoprotein (N) transcripts at any time-337

point in the mock-infected animals. Both SARS-CoV-2 S and N transcripts peaked at 1

338

dpi, were marginally present until 6 dpi, and were not detected in samples from the339

following time-points (Supplementary Fig. 2).

340

One of the most prominent pathomorphological features of SARS-CoV-2 infection was341

marked, but transient, broncho-interstitial pneumonia as described previously18,22.

342

Infection-associated histological lesions were present from 1 dpi on and severity peaked343

at 6 dpi. From 28dpi onwards the histopathological lung lesion score was low in almost all344

animals but still present and the only reported lesions were alveolar proliferation areas345

and sub-pleural fibrosis (Fig. 4a, b; Supplementary Data 4).

346

To quantify the extent of inflammation in both groups, Iba1+-, MPO+-, CD3+-, and Pax5+-347

cells were digitally quantified in immunolabelled whole left lung lobe sections. Significantly

348

higher numbers of Iba-1+ histiocytic cells were detected in SARS-CoV-2-infected hamsters

349

from 1 dpi to 28 dpi, with the highest numbers observed at 6 dpi. MPO+ and CD3+ cell

350

numbers were significantly higher at 6 dpi. On the other hand, significantly higher numbers

351

of Pax5+ cells were found from 6 to 28 dpi (Supplementary Fig.1). Transcriptome data352

analysis revealed an increased expression of Cd8a, Cd3d, Cd3e, Cd4, Alf1 (Iba-1) genes

353

in SARS-CoV-2-infected hamsters at 6 dpi. In addition, CybersortX deconvolution showed354

M1-like macrophage signature peaking at 6 dpi confirming this time-point as the most355

active from an inflammatory point of view (Supplementary Fig. 2).

356

From 6 dpi onwards, besides inflammatory changes, there were moderate to marked,

357

multifocal to coalescing areas of epithelial hyperplasia with occasional atypical cells (Fig.
15

358

4a). These alveolar epithelial proliferation foci were present with variable extent in 8/8359

animals at 6 and 14 dpi, 7/8 animals at 28 dpi, 7/8 animals at 56 dpi, and 4/8 animals at

360

112 dpi (Fig. 4b, Supplementary Data 4). Particularly at the late time-points, these alveolar

361

epithelial proliferation foci were present trouhghout the lung and were characterized by an362

airway-like cell morphology, consistent with bronchiolization (Fig. 4a). Another striking

363

histopathological feature was sub-pleural fibrosis. This lesion was present with variable

364

extent in 1/8 animals at 6 dpi, 6/8 animals at 14 dpi, 3/8 animals at 28dpi, 1/8 animals at

365

56 dpi, and 2/8 animals at 112 dpi (Fig. 4 c; Supplementary Data 4).

366

In the following, we aimed to further characterize the fibrosis and alveolar epithelial

367

proliferation foci, since these changes showed persistence over time and could be368

associated with long lasting functional impairment.

369
370

5. SARS-CoV-2 Delta infection induces pulmonary interstitial fibrosis and a pro-371

fibrotic transcriptomic signature up to 112 days post infection in aged372

hamsters

373

To further analyze pulmonary fibrosis in SARS-CoV-2-infected animals, we performed a374

quantification of Azan positive areas in the entire alveolar interstitium and investigated375

features of a pro-fibrotic environment. Besides the more obvious focal areas of sub-pleural376

fibrosis, we speculated that more subtle increases in extracellular matrix deposition within377

alveolar septa could also contribute to impaired lung function. Thus, we used the Azan

378

stain to visualize collagen and performed a digital quantification of the positive area on379

entire lung sections. Analysis of total Azan+ area in the whole lung tissue revealed a380

statistically significant increase of collagen deposition in alveolar septa of SARS-CoV-2-

381

infected animals compared to mock animals from 14 dpi to 112 dpi (Fig. 4 d, e). A pro-382

fibrotic environment in SARS-CoV-2-infected mice37 and hamsters18 seems to be383

associated with the presence of CD204+ M2-like macrophages. Immunohistochemistry384

showed a notable rise in CD204+ macrophages in the whole lung of SARS-CoV-2-infected385

hamsters compared to mock animals from 6 to 56 dpi. At 112 dpi, the CD204+ M2-like386

macrophages were still increased without statistical significance (Fig. 4 f). In the next step,387

we investigated the expression of genes associated with a pro-fibrotic environment
16

388

(Supplementary Table 1), which are known to be upregulated in COVID-19 patients38,39.

389

This analysis revealed that genes involved in extracellular matrix remodeling (Mmp12,

390

Mmp14, Tgfb1, Supplementary Fig. 3) were up-regulated in early time-points (3dpi and 6391dpi), while mostly collagen encoding genes (Col5a1, Col1a1, Col3a1, Supplementary Fig.

392

3) were up-regulated at later stages of the disease (Fig. 4 g), suggestive of a long-lasting393

increase of collagen production.

394

After showing that SARS-CoV-2 Delta variant-infected hamsters exhibited interstitial395

pulmonary fibrosis starting from 14 dpi and that this was supported by a pro-fibrotic

396

transcriptome environment, we aimed to examine alveolar epithelial proliferation foci, with397

a specific focus on ADI cells as well as airway basal cells and club cells.

17

398
399
400

Fig. 4 SARS-CoV-2 infection causes persistent, sub-pleural and interstitial fibrosis
in aged hamsters

401
402
403
404
405
406
407
408
409
410

a Representative images showing epithelial proliferation in the left lung lobe of a SARSCoV-2 infected hamster at 6 days post infection (dpi, left) and 112 dpi (right) on
hematoxylin and eosin (HE) stained sections. At 6 dpi, there is alveolar consolidation andinflammation, with prominent epithelial proliferation around a central bronchiole (arrows),
which shows a cuboidal, airway-like morphology, typical of bronchiolization. At 112 dpi,
inflammation is no longer present, but multifocal areas of alveolar bronchiolization
persisted throughout the lung. In the picture, a representative focus with multiple areas ofalveolar bronchiolization (arrows) is shown. b Results of semi-quantitative scoring of
histopathological lung lesions in mock and SARS-CoV-2 infected hamsters. c-d
representative images showing sub-pleural and interstitial fibrosis in the left lung lobe of
18

411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428

a SARS-CoV-2 infected hamster at 112 dpi. c Representative image of a focus of a welldemarcated area of sub-pleural fibrosis on HE stained section, characterized byaggregates of mesenchymal cells and pale eosinophilic, fibrillary, extracellular matrix.
Insert: same area stained with azan, demonstrating the presence of mature collagen fibers(blue staining). d Representative images of azan-stained sections showing an increased
presence of mature collagen fibers (blue staining) in the thickened alveolar septa (arrows)of SARS-CoV-2 infected animals compared to mock-infected ones. e Digital quantificationof azan-positive areas in relation to the whole lung tissue in mock- and SARS-CoV-2
infected hamsters. f Quantification of CD204+ M2-like macrophages in total lung area ofmock- and SARS-CoV-2 infected hamsters. g Heatmap of expression values for genes
associated with a pro-fibrotic environment (Supplementary Table 1) at each dpi in mockand SARS-CoV-2 infected hamsters. Expression values are scaled by row. Red indicateshigher and blue lower relative expression levels. In b, e, f, data is shown as box andwhisker plots. The bounds of the box plot indicate the 25th and 75th percentiles, the bar
indicates medians, and the whiskers indicate minima and maxima. Dots indicate individual
values. Data from e and f was tested by two-tailed Mann–Whitney U test. A p value of≤0.05 was chosen as the cutoff for statistical significance. N = 8 animals/group (b, e, f) or
4 animals/group (g). Source data is provided as a Source Data file.

429

19

430

6. After 28 dpi the presence of alveolar differentiation intermediate (ADI) cells

431

in lungs of SARS-CoV-2 Delta infected aged hamsters is markedly decreased432

In our previous work, we demonstrated that alveolar regeneration in SARS-CoV-2-

433

infected hamsters involves persistence of ADI cells until 14 dpi, which are believed to play434

a role in the pathogenesis of protracted recovery and lung fibrosis18. In the following, we

435

focused on the detection of the ADI cells in the acute, sub-acute, and chronic phase of436

the disease.

437

CK8+ ADI cells were identified by immunohistochemistry. The apical cytoplasm of luminal

438

cells within bronchi, bronchioles, and terminal bronchioles in all animals expressed CK8439

ubiquitously. Rare, CK8+ cells were observed in the alveoli of mock-infected animals,

440

whereas it was abundantly expressed within alveolar epithelial proliferation foci in SARS-

441

CoV2 infected animals. In the whole alveolar space, there were significantly higher

442

percentages of CK8+ cells in SARS-CoV-2-infected hamsters compared to mock animals

443

from 6 dpi until 28 dpi (Fig. 5a). The highest percentages of CK8+ ADI in the whole alveolar

444

spaces were detected at 6 dpi (16% of total cells). Digital quantification of immunolabeled445

cells exclusively in areas of alveolar epithelial proliferation revealed that CK8+ ADI cells

446

peaked at 6 dpi with a maximum of 55.72% of the total cell population. By 28 dpi, CK8+447

ADI cells still constituted 31.10% of the total cell count in these areas on average, whereas448

at 56 dpi and 112 dpi average percentages dropped down to 10.68% and 6.06%,449

respectively (Fig. 5a).

450

Subsequently, to complete our investigation of ADI cells and the AT2-ADI-AT1 trajectory,

451

different stages of ADI cells were identified using triple-labelling immunofluorescence for

452

proSP-C (AT2), CK8 (ADI), and PDPN (AT1) as shown in Fig. 5b. Briefly, at 3 dpi,

453

numerous round proSP-C+CK8−PDPN- cells and occasional proSP-C+CK8+PDPN- cells

454

were observed within epithelial proliferation areas, whereas proSP-C-CK8+PDPN+

455

elongated cells were very rare. At 6 dpi, epithelial proliferation foci contained occasional

456

proSP-C+CK8-PDPN- or proSP-C+CK8+PDPN- round cells and moderate to numerous

457

proSP-C-CK8+PDPN- cells with typical ADI morphology. Moreover, rare elongated proSP-

458

C-CK8+PDPN+ cells with AT1 morphology were also detected. From 6 dpi to 28 dpi, the459

proSP-C-CK8+PDPN- ADI cells became less prominent and more of the late, elongated460

AT1- like proSP-C-CK8+PDPN+ were present.
20

461

To further support our morphological findings about ADI cells presence, we subsequently

462

investigated the expression of ADI cell-related genes on the transcriptome level based on463

the hamster ADI cells-specific gene list we previously generated (Supplementary Table 1)464

18. The heatmap Fig. 5c shows that at 3 and 6 dpi, there is an up-regulation of many ADI-

465

specific genes, especially genes typical of ADI cells in the full state after differentiation

466

from AT2 or club cells40, including S100a6, Krt8, Anxa1, Tp53, and Hbegf (Fig. 5c;467

Supplementary Fig. 4). From 14 dpi onwards, a variable down-regulation of these genes468

was observed. At the same late time-points, a different subset of genes, typical of the late469

stage of ADI cells, closing the AT2-ADI-AT1 trajectory40 was variably up-regulated over470

time, for instance Sparc, Sox4, and Wwtr1 (Fig. 5c; Supplementary Fig. 4).

471

Taken together, our data showed that ADI cells were a prominent feature of alveolar

472

regeneration processes in SARS-CoV-2 Delta variant infected aged hamsters during the473

acute and sub-acute phase of the disease. However, their presence do not appear to be474

so prominent in the late stage of the disease. Based on the fact that, upon severe damage,475

alveolar regeneration is aided by airway progenitor cells18,39-43, we focused our next

476

analysis on characterizing airway progenitors in the alveolar compartment.

21

477
478
479

Fig. 5 Alveolar differentiation intermediate (ADI) cells in SARS-CoV-2 infected
hamsters

480
481
482
483
484
485
486
487
488
489
490
491
492

a Quantification of cytokeratin 8 (CK8)+ alveolar differentiation intermediate (ADI) cells
within the whole alveolar space and within alveolar proliferation foci (ep. prol.). On theright, representative pictures of immunolabeling (brown signal) in the alveoli of SARSCoV-2 and mock- infected hamsters at 6 days post infection (dpi). b Triple
immunofluorescence in an alveolar proliferation focus at 6 (left panel) and 28 (right panel)
dpi. Cells are labeled with CK8 (green), pro-Surfactant protein C (proSP-C, light blue) andPodoplanin (Pdpn, red). In the left picture at 6 dpi there are either round proSP-C+CK8PDPN- or proSP-C+CK8+PDPN- cells (arrows and inlet) in the alveolar proliferation focus.
In the right picture at 28 dpi there are moderate numbers of elongated proSP-CCK8+PDPN+ (arrow and inlet) in the alveolar proliferation focus. Scattered proSP-CCK8+PDPN- and numerous proSP-C-CK8-PDPN+ cells are seen at both time-points. c
Heatmap of expression values for genes associated with ADI cells (Supplementary Table1) at each dpi in mock- and SARS-CoV-2 infected hamsters. Expression values are scaled
22

493
494
495
496
497
498
499
500

by row. Red indicates higher and blue lower relative expression levels. In a, data is shown
as box and whisker plots. The bounds of the box plot indicate the 25th and 75th
percentiles, the bar indicates medians, and the whiskers indicate minima and maxima.
Dots indicate individual values. Statistical analysis was performed by two-tailed Mann–
Whitney U test. For multiple comparisons between time points (quantification within
alveolar proliferation foci), a Benjamini–Hochberg correction was applied. Pand q values ≤ 0.05 were considered significant. N = 8 animals/group (a) or 4
animals/group (c). Source data is provided as a Source Data file.

501

23

502

7. Multipotent airway-derived CK14+ progenitors and SCGB1A1+ club cells

503

persist in alveolar epithelial proliferation foci up to 112 dpi in SARS-CoV-2

504

Delta infected aged hamsters

505

In our previous work, we demonstrated that CK14+ basal cells are the predominant basal

506

cell type in the airways of hamsters, followed by CK14+ΔNP63+ cells, whereas CK14+

507

ΔNP63+CK5+ cells are rare in the distal airways. We also demonstrated that following

508

SARS-CoV-2 infection, SCGB1A1+cells and CK14+ cells are the main airway progenitors509

in alveolar proliferation foci that contribute to alveolar regeneration. Finally, we postulated

510

that CK14+ basal cells seem to be the hamster equivalent of CK5+ basal cells reported in

511

humans and mice18. Therefore, in the present study, we investigated the number of cells

512expressing CK14 and SCGB1A1 in the airways, in the whole alveolar space, as well as in513

the alveolar epithelial proliferation foci of bronchiolization during the acute, sub-acute, and514

chronic phase of the disease.

515

The number of CK14+ basal cells in the airways of SARS-CoV-2-infected animals was

516

significantly higher from 3 to 28 dpi compared to the mock-infected ones. However, the517

number of SCGB1A1+ club cells did not have any significant variation in the airways upon518

infection (Fig. 6 a, b). In the whole alveolar space, the percentage of CK14+ cells was

519

significantly higher in SARS-CoV-2-infected hamsters compared to mock animals from 3520

dpi until 112 dpi, with a peak at 6 dpi. The percentage of SCGB1A1+ cells in the total

521

alveolar space was significantly higher from 14 dpi to 112 dpi, with a steady level522

throughout the entire period (Fig. 6 a, b). Next, we aimed to further characterize the523

cellular composition of the alveolar proliferation foci, consistent with persistent areas of524

bronchiolization, in more detail. Therefore, we quantified CK14+ basal cells, SCGB1A1+

525

club cells, CK5+ basal cells, ΔNP63+ basal cells, Mucin-5AC (MUC5AC) and Mucin-5B

526(MUC5B)+ secretory cells exclusively in these regions. CK14+ basal cells were elevated527

at 6 and 14 dpi, representing about 40% of the total cell count in these bronchiolization528

areas. This proportion decreased gradually to about 10 % at 112 dpi (Fig. 6 a). Notably,

529

SCGB1A1+ club cell numbers increased at 14 dpi, later than any other cell type within

530

these alveolar epithelial proliferation foci. Moreover, they persisted until 112 dpi,

531

consistently constituting approximately over 40% of the total cell count (Fig. 6 b). ΔNP63+

532

basal cells represented less than 0.6% of the total cell count at all time-points (Fig. 6 d).
24

533

Immunolabeling for CK5, MUC5AC, and MUC5B revealed the presence of rare positive534

cells in the airways but did not detect any cells within the alveolar epithelial proliferation

535

at any time-point (data not shown). This suggests that these cell types are not involved in536

the alveolar regeneration after SARS-CoV-2 infection in hamsters.

537

In our previous work, we postulated the multipotent potential of CK14 + basal cells by538

demonstrating the co-expression of CK14 and AT2 (proSP-C), ADI cell (CK8) and club

539

cell (SCGB1A1) markers in the alveolar epithelial proliferation areas18. In this current work,

540

considering the prominent presence of SCGB1A1+ club cells compared to the CK8+ ADI

541

cells at the later time-points, we mainly focused on the club cell differentiation.

542

Double-labelling immunofluorescence showed that there are moderate numbers of CK14+543

SCGB1A1+ cells in the epithelial proliferation areas at 14 and 28 dpi. This number of544

double positive cells is constant over time with low to moderate numbers of CK14+545

SCGB1A1+ cells in the epithelial proliferation areas until 112 dpi. Nevertheless, CK14-546

SCGB1A1+ cells were the most prominent cells at all time-points (Fig. 6 c). These results

547

are supportive of the hypothesis that SCGB1A1+ club cells seen in the alveolar spaces

548

also originate from a pool of CK14+ basal cells even at the later time-points.

549

To further support our morphological findings concerning the contribution of airway

550

progenitors to alveolar regeneration processes, we subsequently investigated the551

expression of club cell- and airway basal cell-related genes based on our hamster club

552

cell-specific gene list (Supplementary Table 1)18 and literature38,40. The heatmap in Fig.

553

6e-f shows that among club cell genes, Gss and Pigr were the only two with an up-

554

regulation at the later time-points, whereas all the other genes showed a variable up-

555

regulation at different time-points of the acute and sub-acute phase. Similarly, airway

556

basal cell genes like Ngfr or Pou2f3 were variably up-regulated at the later time-points.

557

After peaking at 6 dpi, Krt14 gene showed a slight decrease, but remained up-regulated

558

until the later time-points. Krt5 gene expression was variably stable over time (Fig. 6 e;

559

Supplementary Fig. 5).

560

In summary, airway progenitors, in particular CK14+ basal cells and SCGB1A1+ club cells,

561

dominated the cellular composition within the alveolar epithelial proliferation areas in the562

sub-acute and chronic phase after SARS-CoV-2 Delta infection. In particular, SCGB1A1+
25

563

club cells were the predominant cell type in the bronchiolization foci persisting until 112

564

dpi.

565
566
567

Fig. 6 Airway progenitor cells take part in the alveolar regeneration process after
SARS-CoV-2 infection in hamsters

568
569
570
571
572
573
574
575
576

a-b Quantification of cytokeratin 14 (CK14)+ airway basal cells (a) and secretoglobin 1a1(SCGB1A1)+ club cells (b) within the whole alveolar space, airways, and within alveolar
epithelial proliferation foci (ep. prol.). On the right, representative pictures of
immunolabeling (brown signal) of CK14 (arrows) and SCGB1A1 in the alveoli and airwaysof SARS-CoV-2 and mock- infected hamsters at 112 dpi. c Double immunofluorescencein an alveolar proliferation focus at 14 and 112 dpi. Cells are labeled with SCGB1A1(green) and CK14 (red). In both pictures there are low to moderate numbers of
CK14+SCGB1A1+ cells (arrows and inlets). d Quantification of ΔNP63+ airway basal cells
within alveolar proliferation foci and representative picture of immunolabeling (brown
26

577
578
579
580
581
582
583
584
585
586
587
588

signal, arrows) in an alveolar proliferation focus of a SARS-CoV-2- infected hamster at 6
dpi. e-f Heatmap of expression values for genes associated with airway basal cells andclub cells (Supplementary Table 1) at each dpi in mock- and SARS-CoV-2 infected
hamsters. Expression values are scaled by row. Red indicates higher and blue lower
relative expression levels. In a, b, d quantification data is shown as box and whisker plots.
The bounds of the box plot indicate the 25th and 75th percentiles, the bar indicatesmedians, and the whiskers indicate minima and maxima. Dots indicate individual values.
Statistical analysis was performed by two-tailed Mann–Whitney U test. For multiple
comparisons between time points (quantification within alveolar proliferation foci), a
Benjamini–Hochberg correction was applied. P- and q values ≤ 0.05 were consideredsignificant. N = 8 animals/group for mock and SARS-CoV-2 respectively. Source data areprovided as a Source Data file.

589

27

590

8. CK14+ airway basal cells and SCGB1A1+ club cells express proliferation
markers in the alveolar bronchiolization areas until 112 dpi

591
592

Next, we wanted to assess the expression of proliferation and cell cycle arrest markers in593

the alveolar epithelial proliferation areas.

594

Ki67+ cells peaked at 6 dpi, representing about 40% of the total cell count in these areas.

595

At the following time-points, this proportion decreased to about 10% at 112 dpi (Fig. 7a).

596

Despite representing only about 1% of the total cell count in these areas, p53+ cells were597

also most present at 6 dpi. At the subsequent time-points, only 2 animals still showed p53+598

cells at variable percentages (Fig. 7b). A similar trend was observed with p21+ cells (Fig.

599

7c).

600

Afterwards we wanted to visualize which cell types were expressing proliferation markers.

601

At 6 dpi, moderate numbers of CK8+Ki67+ ADI cells and CK14+Ki67+ airway basal cells

602

were

603

SCGB1A1+Ki67+ nor SCGB1A1+Ki67- club cells were observed. At 14 and 28 dpi, there

604

were minimal to low numbers of CK8+Ki67+ ADI cells. CK14+Ki67+ airway basal cells, and605

SCGB1A1+Ki67+ club cells were present at low to moderate numbers. Notably, at 56 dpi

606

and 112 dpi there were no CK8+Ki67+ ADI cells but moderate numbers of CK14+Ki67+

607

airway basal cells and SCGB1A1+Ki67+ club cells in persistent bronchiolization areas.

608(Fig. 7 d).

609

In conclusion, CK14+ basal cells and SCGB1A1+ club cells in alveolar persistent610

bronchiolization foci expressed Ki67 until 112 dpi, suggesting ongoing proliferative activity

611

long after the initial infection.

present

inthealveolarepithelial

proliferation

areas,

whereasneither

28

29
612

613
614

Fig. 7 Immunolabeling of proliferation and senescence markers in SARS-CoV-2
infected hamsters

615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631

a-c Quantification of Ki-67 (a), p53 (b), and p21 (c) immunolabelled cells within alveolar
epithelial proliferation foci (ep. prol.). On the right, representative pictures of
immunolabeling (brown signal, arrows) in alveolar proliferation foci of SARS-CoV-2
infected hamsters at 6 and 112 dpi. d Double immunofluorescence of Ki-67 in combination
with CK8+ ADI cells, CK14+ airway progenitor cells or SCGB1A1+ club cells in alveolar
proliferation foci at different time-points. In the top panel, cells are labeled with CK8(green) and Ki-67 (red). There are moderate numbers of double labelled cells (arrows) at
6 dpi, whereas they are rare at 28 dpi. In the central panel, airway progenitor cells arelabeled with CK14 (green) and Ki-67 (red). There are moderate numbers of double
labelled cells (arrows) at both 6 and 112 dpi. In the bottom panel, cells are labeled with
SCGB1A1 (green) and Ki-67 (red). There are moderate numbers of double labelled cells(arrows) at both 14 and 112 dpi. In a, b, c quantification data is shown as box and whisker
plots. The bounds of the box plot indicate the 25th and 75th percentiles, the bar indicatesmedians, and the whiskers indicate minima and maxima. Dots indicate individual values.
Statistical analysis was performed by two-tailed Mann–Whitney U test. Pand q values ≤ 0.05 were considered significant. N = 8 animals/group for mock and SARSCoV-2 respectively. Source data is provided as a Source Data file.

632

30

9. SARS-CoV-2 Delta infection does not cause long-term effects in the heart,

633

kidney, liver or spleen of aged hamsters

634
635

Although respiratory deficiencies are among the most common symptoms of long-COVID,

636

the respiratory tract is far from being the only organ system that can be affected by long637

lasting disturbances44. Especially cardiovascular impairment is considered one of the638

main contributors to long-COVID. Since the heart and the respiratory tract are immediately

639

connected, we aimed to investigate this organ in greater detail. Although it has been640

thoroughly studied in acute hamster models for COVID-19 already45,46, data on the sub-641

acute and chronic phase is still sparse46,47.

642

No SARS-CoV-2 NP immunolabeled cells were detected in the heart of any animal at any

643

time-point. Histopathology revealed mild to moderate, mostly sub-epicardial inflammation

644(11/55 SARS-CoV-2-infected animals, 5/56 mock-infected animals), mild fibrosis (3/55645

SARS-CoV-2-infected animals, 1/55 mock-infected animal), focal thrombi in small blood

646

vessels (3/55 SARS-CoV-2-infected animals, 1/56 mock-infected animals) and mild to647

moderate focal mineralization (2/55 SARS-CoV-2-infected animals, 2/55 mock-infected648

animals) (Supplementary Fig. 6; Supplementary Data 5). Since mild inflammatory649

infiltration, thrombosis and calcification are known to occur as age related, non-neoplastic

650

lesions in hamsters28,48, we concluded that our observations were most likely background651

lesions due to the advanced age of the animals. Since myocardial fibrosis has been652

reported in SARS-CoV-2-infected hamsters during the acute and sub-acute phase of the653

disease46, we analyzed the collagen content in heart sections from 1 to 112 dpi. However,654

quantification of the Azan positive areas in the myocardial interstitial spaces revealed no655

significant differences between SARS-CoV-2-infected hamsters and mock-infected656

controls (Supplementary Fig. 6). Since the observed sub-epicardial inflammatory infiltrate

657

appeared predominantly histiocytic on histology, immunolabeling for Iba-1 was performed.

658

Quantification of Iba-1+ cells did not display any significant difference (Supplementary Fig.

659

6).

660

In the next step, we investigated histological lesions and performed SARS-CoV-2 NP

661

immunolabeling in kidneys, liver and spleen. None of the organs displayed SARS-CoV-2

662

NP immunolabeled cells (Supplementary Data 6). Renal lesions were overall mild and663

detected in both SARS-CoV-2 and mock-infected animals. They encompassed mild,
31

664

multifocal tubular dilation or degeneration, mild glomerular vacuolization and focal or665

multifocal chronic infarction. All of the aforementioned lesions affected equally Mock- and666

SARS-CoV-2-infected hamsters (Supplementary Data 6). Azan, Iba-1, MPO, and CD3

667

semi-quantitative scoring of positive cells did not yield any difference (Supplementary

668

Data 6). In the liver, we mainly observed mild periportal lympho-histiocytic inflammation669

in both groups. No lesions were observed in the spleen at any time-point ( Supplementary

670

Data 6).

671

In conclusion, intranasal infection of aged, male hamsters with SARS-CoV-2 Delta variant

672

does not cause pathological changes in heart, kidneys, liver or spleen.

673
674

Discussion

675

Although an end to the global health emergency due to the SARS-CoV-2 pandemic has

676

been declared, a large number of patients still struggle with lasting consequences long

677

after they have recovered from the acute disease2-5. Even if tissue samples from survivors

678

could be acquired, establishing a clear causal connection between the initial SARS-CoV-679

2-infection and lesions observed at later time-points can be challenging. For this reason,680

the use of an appropriate animal model in research is of paramount importance. In our

681

previous work, we showed that hamsters are suitable for modeling alveolar regeneration

682

mechanisms in the acute and subacute phase of SARS-CoV-2 infection18. Based on the683

presence of alveolar proliferation foci, ADI cells displaying cell cycle arrest, alveolar airway

684

progenitors, and sub-pleural fibrosis at 2 weeks after infection, we postulated that an

685

impaired alveolar regeneration and persistent tissue remodeling could account for

686

prolonged respiratory symptoms and impaired lung function reported in patients with687

respiratory long-COVID. As a consequence, this work aimed to characterize the trajectory688

of lung regeneration over the period of 112 days in the hamster model by combining

689

morphological, transcriptome analysis, and functional readouts.

690

The early phase of the disease was characterized morphologically by pneumonia with

691

high numbers of inflammatory cells, and subsequent features of alveolar regeneration with692

high numbers of ADI cells and airway cell proliferation. This was reflected by a markedly

693

altered lung function at 3 and 6 dpi, with significantly decreased respiratory rate as well
32

694

as significantly increased EF50 and Penh compared to controls. These alterations are in

695

agreement with previous studies using WBP to measure lung function in acute SARS-

696

CoV-2 infection in mice and hamsters23,37,49. Additionally, we showed here that O2 uptake

697

and CO2 production are reduced in infected animals in the acute phase.

698

It is interesting to note that, both during the acute phase of the disease and long-COVID,

699

patients often report dyspnea or coughing50. However, hamsters had very mild to700

moderate respiratory signs detectable by clinical scoring, limited only to the acute phase701of the disease despite a marked alteration of lung function. This indicates that clinical702

scoring based on periodic visual inspection alone might be a sub-optimal method to703

assess respiratory impairment in hamsters and that more sensitive methods like WBP

704

have to be applied to accurately assess the impact on the lower respiratory tract.

705

From 14 dpi onwards, the lung function parameters obtained under normal conditions

706

were not altered anymore in both groups. This suggests that the observed functional

707

changes in the acute phase are directly related to the acute damage to alveoli and airways

708

and the associated inflammatory process obliterating large areas of the lung, which are709

mostly resolved within 14 days. Although areas of alveolar proliferation are still prominent

710

after this time-point, they do not obliterate the alveolar space, creating a more subtle

711

alteration that does not seem to affect the measured lung function parameters in a resting

712

state. Similarly, the pulmonary interstitial fibrosis arising from 14 dpi and persisting until

713

112 dpi does not appear to alter lung function in a resting state. Apparently, the relatively714

low degree of fibrosis observed does not impact breathing or can be compensated by715

remaining unaltered lung tissue. Interestingly, variably prominent mechanical value

716

alterations as well as reduced O2 uptake and CO2 production were evident in SARS-CoV-717

2-infected animals after physical exercise prior to the measurement of the lung function.

718

We assume that in the chronic phase of the disease the alveolar impairment is not as719

severe as in the early phase but prominent enough to display a decreased lung function

720

after exercise-induced stress. The use of a rodent treadmill was inspired by the use of721

similar tests in human medicine51 and we think that its use should be taken into

722

consideration in future animal studies modeling long-term respiratory signs induced by

723

SARS-CoV-2.

33

724

The observed changes in lung function after exercise were present until 7 weeks post725

infection. In line with this, the majority of studies in PASC patients show a gradual726

improvement of lung function over time, although this is not always accompanied by a727

regression of symptoms8,52-54. In contrast, a recent study comprised exclusively of patients728with persistent pulmonary PASC shows no improvement of clinical symptoms, diffusion

729

impairment and pulmonary restriction, as measured by percentage predicted diffusion

730

capacity for carbon monoxide and total lung capacity55. The trajectory of clinical731

symptoms, combined with physiologic and radiographic changes, was interpreted to be732

suggestive of fibrosis, which is an irreversible state mainly affecting the pulmonary

733

membrane diffusing capacity. However, studies utilizing lung tissue from PASC patients734

are rare, and therefore the association of lung function with a specific pathotype remains

735

speculative. Therefore, one of the goals in this study was to determine whether there is736

an association of pathomorphological changes (bronchiolization and interstitial fibrosis)

737with lung function alterations. What is puzzling is that the alveolar bronchiolization and738

interstitial fibrosis were stable from 14 until 112 dpi, but lung function recovered after 7739

weeks. This discrepancy could be explained by several factors. One possibility is that a

740

training effect occurred and that the animals adapted to the physical exercise, since the741

treadmill protocol was not altered over the course of the experiment. In this way, the742

magnitude of exercise that induced a respiratory stress at the beginning might have been

743

better tolerated over time, resulting in not impaired lung function similar to the resting

744

state. Alternatively, other factors besides pathomorphological changes in the alveoli

745

contribute to lung function impairment. A recent study found no correlation between gas

746

exchange impairment and chest CT findings indicative of fibrosis in a cohort of patients.

747

Combined measurement of DLNO and DLCO diffusion in this cohort suggested that gas

748

exchange abnormalities were driven by alterations of the vascular function rather than an

749

altered diffusion conductance of the alveolar membrane 56. In another study, in which an

750

improvement of diffusion capacity from 3 to 12 months after infection was found, the751

authors concluded that diffusion improves over time due to an expansion of the perfusion

752

component57. Thus, while fibrosis is an irreversible change that impedes diffusion, it can

753

potentially be compensated by adaptations of the vascular component. Though, we did754

not observe long-lasting morphologic alterations in the lung vessels of hamsters.

755

However, it cannot be excluded completely that functional alterations in lung vessels,
34

756

without a morphologic correlate might have contributed to the impaired lung function

757

observed under physical stress and that this change recovered after 7 weeks.

758

Another possible explanation for the functional recovery of hamsters in contrast to human759

patients could be differences in the persistence of virus in the lung. It has been postulated

760that persistence of SARS-CoV-2 in the lung could be the key to explain lasting symptoms

761

of respiratory long-COVID. In one study, patients showed repeated negative results in

762

nasopharyngeal swabs or bronchioalveolar lavage (BAL) for an average of 105 days, but

763

SARS-CoV-2 Spike and NP immunohistochemistry revealed positive signal in bronchial764

cartilage chondrocytes and parabronchial glands of most patients58. On the other hand, a765

more recent study in macaques showed that SARS-CoV-2 was detectable in BAL

766

macropahges beyond 6 months inducing IFNγ and NK cells dysregulation59. We

767

performed lung bulk RNAseq and immunohistochemistry, but failed to detect any of the768

viral proteins and transcripts at time-points later than 6 dpi. Similarly, we did not detect769

any persistent inflammatory foci in the alveoli. Therefore, we postulate that the ability of770

the hamster to resolve virus infection and associated inflammation could be the cause for771

the recovery of lung function impairment at least in this study design and wih the SARS-

772

CoV-2 variant used in this investigation.

773

During the chronic phase of the disease, we observed mild to moderate but persistent774

pathomorphological changes like sub-pleural and interstitial pulmonary fibrosis as well as775

alveolar epithelial proliferation areas dominated by SCGB1A1+ club cells and fewer CK14+776

basal cells. These alveolar epithelial proliferation foci were morphologically consistent with777

areas of bronchiolization due to their airway-like morphology. It is interesting to note that778

club cells and bronchiolization areas have been associated with the maintenance of a pro-779

fibrotic milieu60 and with idiopathic pulmonary fibrosis61, respectively. Our transcriptome

780

data analysis is supporting the presence of a pro-fibrotic environment with prolonged

781

presence of CD204+ M2-like macrophages at the later time-points and the increased

782

number of Azan positive collagen fibers in the lung interstitial space. In addition, the gene783

Cyp2e1 was an upregulated DEG at 14 dpi, 28 dpi, and 56 dpi in SARS-CoV-2-infected784

animals. Cyp2e1 belongs to the P450 superfamily and in the lung it is mainly expressed785

by club cells62. It has been demonstrated that the up-regulation of Cyp2e1 is involved in786

the pulmonary fibrosis via ER stress- and ROS-dependent mechanisms63. In our previous
35

787

study18, we postulated that the cause of the fibrosis was mainly attributed to the presence788

of ADI cells. However, it is clear now that the pathogenesis of SARS-CoV-2-induced

789

pulmonary fibrosis appears to be more complex and involve multiple cell types. Taking

790

into consideration that ADI cells are not the prominent cell type in the chronic phase of the791

disease, more attention should be focused on the club cells within the bronchiolization

792

areas. It is worth noticing that our transcriptome data analysis displayed the presence of793

a number of DEGs that were either shared or unique of the sub-acute and the chronic794

phases of the disease. As most of these DEGs are involved in cell migration, GABA-A,

795

ephrin, or serotonin receptors, neuronal growth, plasticity and signaling, as well as trans-

796

synaptic signaling hinting towards the presence of a recently described niche of club cells

797

residing in the so-called “neuroepithelial bodies”64. However, future immunohistochemical798

and in situ hybridization studies are warranted to confirm such postulation.

799

Based on our results, it seems that these bronchiolization areas in the alveoli do not cause

800

a marked and long lasting alteration of the lung function. However, given their prolonged

801

presence, we postulate they might play a role in increasing the risk for developing other802

conditions. For instance, it is known that cigarette smokers are prone to many pulmonary

803

alterations, including peribronchiolar alveolar bronchiolization65. Smokers affected by804

long-COVID could potentially be at higher risk for more extensive alveolar bronchiolization

805

due to the combined action of cigarette smoking and SARS-CoV-2 infection. As a

806

consequence, this could increase the risk of pulmonary fibrosis due to the relationship807

between bronchiolization and fibrosis61. In addition, pulmonary fibrosis and alveolar

808

bronchiolization are considered risk factors for lung cancer and a premalignant change,809

respectively66,67. In light of what said above, these patients should be particularly

810

monitored and accounted for a possible increased risk for lung cancer. Interestingly, high-811

mobility group box-1 (HMGB1) protein, which is expressed by club cells in the lung,812

promotes airway hyperresponsiveness and an asthma-like type 2 response. For this813

reason, airway hypersensitivity could represent another condition potentially promoted by814

the persistence of alveolar areas of bronchiolization rich in club cells in long-COVID

815

patients68. This is already demonstrated for other viruses. For instance, respiratory816

syncytial virus infection in early life is considered an important risk factor for the817

development of asthma69.
36

818

The authors recognize that the study has some limitations. First, the use of a single SARS-

819

CoV-2 variant. We recognize the planning and the execution of this study, several other820

variants occurred globally. However, our choice on SARS-CoV-2 Delta variant was based821

on the fact that the risk of developing long-COVID is most often associated with Delta

822

variant infection70,71. By the middle of 2021, Delta variant was the most prevalent variant823

of concern72. Compared to SARS-CoV-2 Omicron BA1, Delta variant is also known to824

cause more severe pulmonary lesions in hamsters22. Second, we used only old male825

animals. We are aware that in an optimal condition the use of male and female as well as

826

young and aged hamsters would have been preferable. However, risk factors for the827

development of long-term sequelae include advanced age3,73 and sex, with males being

828

more likely to develop severe acute disease21,74. Moreover, male sex is associated with829

higher risk for pulmonary long-COVID with diffusion impairment and restriction in830

humans55. To increase the likelihood of observing long lasting pulmonary long-COVID, we

831

used only one year old male hamsters. Third, the conclusions regarding cell fate of CK14+

832

basal cells in this work are based on double-labeling and expression of genes interpreted

833

in the context of published data. Therefore, they have to be interpreted as preliminary

834

observations. Fourth, we did not sub-classify club cells in all the sub-populations that are835

reported in literature. This is mostly due to the fact that several tested antibodies failed to836

specifically recognize club cell sub-populations in hamsters.

837

In conclusion, our study shows that functional long-term respiratory consequences of838

SARS-CoV-2 infection can be modeled in aged male hamsters, using functional tests in

839

combination with exercise. Alveolar bronchiolization and interstitial pulmonary fibrosis

840

persist up to 112 dpi and are likely to represent potential risk factors for other diseases in

841

long-COVID survivors and this should be addressed in future studies. Altogether, these842

results represents further steps towards a more complete understanding of long-COVID

843

pathogenesis.

844

37

845

Materials and methods

846

1. Ethics statement

847

The animal experiment was in accordance with the EU directive 2010/63/EU and848

approved by the relevant local authorities (protocol code TV22-00088, approval849

16.09.2022).

850
851

2. Animal experiment852

During the experiment, the animals were under veterinary observation and all efforts were853

made to minimize distress. Eleven to twelve-month-old male Syrian golden hamsters

854(Mesocricetus auratus) purchased from Janvier Labs were housed under BSL-3

855

conditions for at least 2 weeks prior to the experiment for acclimatization. A total of 112

856

hamsters were randomly assigned to groups of 8 animals per time-point and treatment857(n=16 per dpi). They were housed in isolated ventilated cages under standardized

858

conditions (21 ± 2 °C, 40 – 50 % humidity, 12: 12 inversed light-dark cycle, food and water859

ad libitum) at the Research Center for Emerging Infections and Zoonoses (RIZ) in

860

Hannover, Germany. The animals were injected intranasally with either a suspension of861

104 TCID50 of SARS-CoV2 (SARS-CoV-2 Delta variant) or phosphate-buffered saline

862(PBS, control) as previously described75,76 under general anesthesia. After infection, the863

animals were monitored with daily scoring and weighing until 21 days post-infection (dpi).

864

At chosen time-points, the animals underwent lung function measurements as described865

below. At 1, 3, 6, 14, 28, 56 and 112 dpi, groups of 16 animals were put in deep general

866

anesthesia by inhalation of isoflurane in an induction chamber followed by an867

intraperitoneal administration of 100 mg/kg ketamine and 0,25 mg/kg medetomidine. Final868

euthanasia was performed by abdominal aorta resection. Subsequently, lung, heart,869

kidneys, liver and spleen were collected and fixed in 10 % neutral-buffered formalin. In

870

particular the left lung lobe was pre-fixed by injections of 10% buffered formalin.

871

Furthermore, tissue from the right lung lobes was collected and suspended in 500 μl

872RNAlater (Invitrogen).

873
38

874

3. In vivo lung function measurement875

To measure lung function parameters, a whole body plethysmograph (Buxco small animal876

whole body plethysmography, DSI) connected to a gas analyzer (ADInstruments) was877

used under BSL-3 conditions. From 21 dpi, the animals were additionally placed on a878

rodent treadmill (Ugo Basile) and lung function was measured before and after exercise.

879

No exercise was performed on animals during the acute and sub-acute phase of disease880

due to animal welfare reasons. During the housing phase, the animals were familiarized

881

with the measuring procedure three times. The training sessions consisted of 10 minutes

882

of plethysmography followed by 7 minutes of treadmill. During the first training, the883

treadmill was switched off and the animals were free to explore. Treats (sunflower seeds884

or waffles) were placed inside as a reward. Subsequently, the treadmill was switched on

885

and animals were running for 5 minutes at a slow speed. The speed and duration were886

increased in subsequent training sessions. The treadmill training was only conducted in

887

animals of the 28, 56 or 112 dpi groups. All groups underwent the training with the888plethysmograph. After infection, all animals were measured in the plethysmograph at 0,889

3, 6, 10 and 14 dpi, followed by weekly measurements in combination with exercise on890

the treadmill from 21 dpi until 112dpi. Due to space and time restrain reasons, 6 out of the891

8 animals from each group (SARS-CoV2 and mock-infected) were chosen to undergo

892

exercise according to the behavior on the treadmill during the training sessions. The

893

measurement in the plethysmograph before exercise lasted 25 minutes, which included a894

10-minute acclimatization period. If exercise was performed, the treadmill was set to an

895

accelerating speed starting at 10m/min and ending at 15 m/min at a 5° angle for 10

896

minutes. Immediately afterwards, the animals were transferred back to the897plethysmograph to be measured for another 15 minutes without any acclimatization. The

898

animals running in the treadmill were under constant veterinary observation. Hamsters

899

are considered night-animals, therefore all the procedures of lung function measurements

900

and exercise were performed during the dark period of the light cycle. Measurements were901

collected with the software “FinePointe Respiratory Software” (Version 3.0.1.13370). After

902

acquisition, data were checked for breathing artifacts like sniffing patterns or moments903

when the animals were scratching or moving. These patterns were identified and marked

904

by the software and subsequently reviewed and manually exclude those data from
39

905

recording in order to avoid artifacts. The lung function parameters that were chosen to be906

analyzed were: frequency, Penh, EF50, vO2, and vCO2. Description and unit of the907parameters are listed in Supplementary Table 2. Statistical analysis and graphs design908

were performed using the statistical software SAS® version 9.4 (SAS Institute Inc., Cary,

909

NC, USA) with the SAS Enterprise Guide 7.1 Client and GraphPad Prism 9.3.1 (GraphPad

910

Software, San Diego, CA, USA) for Windows™. The assumption of normal distribution

911

was tested using the Kolmogorov-Smirnov test. Due to the rejection of the assumption of

912

normal distribution, non-parametric methods were used. Pairwise comparison between

913

SARS-CoV-2-infected hamsters and control group at each time-point were tested with a914

two-tailed Mann–Whitney-U test. Statistical significance was accepted at exact p-values915

of ≤0.05.

916
917

4. Virus

918

SARS-CoV-2 (isolate hCoV-19/USA/PHC658/2021, lineage B.1.617.2 Delta variant, NR-

919

55611) was obtained from BEI Resources, NIAID, NIH, and cultured in Vero cells using

920

DMEM (Sigma-Aldrich) with added 2% FBS, 1% penicillin-streptomycin, and 1% L-

921

glutamine at 37°C. All experiments involving SARS-CoV-2 infection were conducted in

922

BSL-3 laboratories and stables at the Research Center for Emerging Infections and923

Zoonoses (RIZ), University of Veterinary Medicine Hannover, Germany.

924
925

5. Histopathology

926

For histopathological evaluation, formalin fixed-paraffin embedded (FFPE) lung samples

927

were cut into 2µm serial sections and stained with hematoxylin and eosin (HE) and Azan

928

trichrome. Qualitative evaluations with special emphasis on inflammatory and epithelial

929

regenerative processes (HE) as well as on fibrosis (Azan) were performed in a blinded

930

fashion by veterinary pathologists (FA, LH) and subsequently reviewed by board certified

931

veterinary pathologist (MCI,WB). Lung samples were scored by a veterinary pathologist

932(FA) in a blinded manner with a semi-quantitative scoring system with special emphasis

933

on inflammation, degeneration and regeneration as previously described 22. Examined934

lung sections included the entire left lung lobe.
40

935

FFPE samples of heart, kidney, liver and spleen were also cut into 2µm serial sections

936

and stained with HE and Azan trichrome (heart, kidney). Qualitative evaluations with937

special emphasis on inflammatory and epithelial regenerative processes were performed

938

in a blinded fashion by veterinary pathologists (IZ, TS) and subsequently reviewed by939

board certified veterinary pathologist (MCI,WB). Examined heart section included 2

940

transversal sections including both the right and the left chamber, one right above the941

atrio-ventricular valves, one in the middle of the ventricles. Kidney were examined in toto

942

in longitudinal sections while 2-3 cross-sections of liver and spleen were used.

943
944

6. Azan trichrome quantification

945

Azan trichrome stained tissue sections were digitized using an Olympus VS200 Digital946

slide scanner (Olympus Deutschland GmbH). Image analysis software (Visiopharm

947

Software Version 2023.01, Hoersholm Denmark) was used to measure the Azan positive948

areas by thresholding (contrast red-blue filter with threshold -50) and tissue area (green

949

filter with threshold 220). Azan positive area per whole lung was calculated by division.

950

Statistical analysis and graphs design were performed using GraphPad Prism 9.3.1

951(GraphPad Software, San Diego, CA, USA) for Windows™. Single comparison between

952

SARS-CoV-2-infected hamsters and control group were tested with a two-tailed Mann–

953

Whitney-U test. Statistical significance was accepted at exact p-values of ≤0.05.

954
955

7. Immunohistochemistry956

Immunohistochemistry was performed to detect SARS-CoV-2 antigen (SARS-CoV-2

957

nucleo protein), macrophages and dendritic cells (ionized calcium-binding adapter

958

molecule 1, Iba-1), T-cells (CD3), B-cells (pax5), neutrophils, (myeloperoxidase, MPO),

959

alveolar differentiation intermediate cells (cytokeratin 8), airway basal cells (cytokeratin

960

14, cytokeratin 5 and ΔNP63), club cells (secretoglobin 1A1) bronchial cells (MUC5AC,

961

MUC5B), senescent cells (p21, p53), proliferating cells (Ki-67), and M2-like macrophages962(CD 204). Immunolabelings were visualized either using the Dako EnVision+ polymer

963

system (Dako Agilent Pathology Solutions) and 3,3´-Diaminobenzidine tetrahydrochloride

964(DAB, Carl Roth) as previously described22 or using avidin–biotin complex (ABC)965

peroxidase kit (Vector Labs) and DAB (Carl Roth) as previously described 77. Nuclei were
41

966

counterstained with hematoxylin. Further details about primary and secondary antibodies,

967

visualization methods and dilutions used can be found in Supplementary Table 3. For

968

negative controls, the primary antibodies were replaced with adjusted protein

969

concentrations of rabbit serum or BALB/cJ mouse ascitic fluid, respectively. Antibodies

970

were tested on murine and hamster lung tissue to confirm specificity for the cells of

971

interest. Subsequently, hamster tissue was used as positive controls.

972
973

8. Immunofluorescence974

Double and triple labelling immunofluorescence was performed to investigate the975

presence of alveolar pneumocytes type 1 (Podoplanin), ADI cells, and alveolar

976

pneumocytes type 2 (pro-SPC). In addition we also investigated CK14+ basal cells fate,977

cell cycle activity, and cell senescence. Reaction was carried out as previously described978with minor modifications18,78. Briefly, after deparaffinization, heat induced epitope retrieval

979

and serum blocking, washing with PBS in between each step, a dilution containing two

980

primary antibodies was added and incubated for 120 minutes at room temperature.

981

Afterwards, a dilution containing two secondary antibodies was incubated for 90 minutes982

at room temperature in the dark. Additionally, on triple-labeled slides, fluorescent983

conjugated antibodies (AlexaFluor®488 CK8, AlexaFluor®488 Scgb1A1) were incubated984

for 120 minutes. After washing with PBS and distilled water, sections were counterstained

985

and

986

(Vectashield®HardSet™, Biozol). Further details about primary and secondary987

antibodies, visualization methods and dilutions used can be found in in Supplementary

988

Table 3. For negative controls, the primary antibodies were replaced with rabbit serum or

989

BALB/cJ mouse ascitic fluid respectively with the dilution chosen according to protein

990

concentration of the exchanged primary antibody.

mountedusing

anti-fade

mounting

mediumcontaining

DAPI

991

42

992

9. Digital image analysis

993

To quantify immunolabeled cells in pulmonary tissue slides were digitized using an

994

Olympus VS200 Digital slide scanner (Olympus Deutschland GmbH). Image analysis was

995

performed using QuPath (version 0.5.0), an open-source software package for digital996

pathology image analysis79. For all animals, immunolabellings for cytokeratin 8 (CK8),997

cytokeratin 14 (CK14), and secretoglobin 1A1 (SCGB1A1) were evaluated on digital

998

whole slide images of the entire left lung as previously described18. Briefly, total lung tissue999

was detected automatically using digital thresholding. Afterwards, regions of interest (ROI)

1000

were defined. The ROIs “airways” (bronchi, bronchioles, terminal bronchioles), "blood

1001

vessels”, “epithelial proliferation” (alveoli that were involved in an epithelial regenerative

1002

process) and “artifacts” were manually outlined. The area denoted as “total alveoli” was1003

defined by subtraction of the “blood vessels”, “airways” and “artifacts” ROIs from the total

1004

lung tissue using an automated script. For p53, p21, ki67 and ΔNP63, only “epithelial

1005

proliferation” was marked manually as a ROI. Using tissue- and marker-specific1006

thresholding parameters, quantification of immunolabeled cells was achieved by1007

automated positive cell detection in all ROI. To analyze SARS-CoV-2 NP, Iba-1, MPO

1008

Pax5, CD3, and CD204 immunolabeling, total lung tissue was automatically detected1009

using digital thresholding. Afterwards, only blood vessels and artifacts were indicated as

1010

ROIs and subtracted from the total lung tissue. Based on tissue and marker specific1011

thresholding parameters, quantification of immunolabeled cells was then achieved by1012

automated positive cell detection. All procedures (tissue detection, indication of ROIs,

1013

positive cell detection) were performed and subsequently reviewed by at least two

1014

veterinary pathologists (FA, GB, LH, MC). Statistical analysis and graphs design were1015

performed using GraphPad Prism 9.3.1 (GraphPad Software, San Diego, CA, USA) for

1016

Windows™. Single comparison between SARS-CoV-2-infected hamsters and control

1017

group were tested with a two-tailed Mann–Whitney-U test. For multiple comparisons

1018

among different time-points data were tested for significant differences using Kruskal–

1019

Wallis tests and corrected for multiple group comparisons using the Benjamini–Hochberg

1020

correction. Statistical significance was accepted at exact p-values of ≤0.05.

1021
1022
43

1023

10. RNA-isolation

1024

Lung tissues from infected hamsters were homogenized in 1 mL of DMEM with penicillin

1025

and streptomycin (Gibco) using the TissueLyser-II (Qiagen). RNA was then extracted from1026

100 µL of the homogenized lung sample using the NucleoMag® RNA kit (MACHERY-

1027

NAGEL) following the manufacturer's protocol.

1028
1029
1030

11. Bulk RNAseq

1031

The quality and integrity of the total RNA were assessed using the Agilent Technologies

1032

2100 Bioanalyzer (Agilent Technologies; Waldbronn, Germany). To prepare the RNA

1033

sequencing library, 500 ng of total RNA was utilized. mRNA purification was carried out

1034

using the Dynabeads® mRNA DIRECT™ Micro Purification Kit (Thermo Fisher), followed1035

by library preparation using the NEBNext® Ultra™ II Directional RNA Library Prep Kit

1036(New England BioLabs) in accordance with the manufacturer’s protocols. The resulting

1037

libraries were sequenced on the Illumina NovaSeq 6000 platform, employing the NovaSeq

1038

6000 S1 Reagent Kit (100 cycles) for paired-end runs. On average, each RNA sample

1039

yielded approximately 3-5 x 107 reads. Subsequently, each FASTQ file underwent quality1040

assessment using the FASTQC tool80. Before alignment to the reference genome, raw

1041

FASTQ files were processed to trim sequences with low base call quality and remove1042

sequencing adapter contamination (fastq-mcf, http://expressionanalysis.github.io/ea-

1043

utils/). Reads shorter than 15 bp were excluded from the FASTQ files. The trimmed reads

1044

were then aligned to the reference genome using the open-source short read aligner

1045

STAR81, with default settings. The reference file for golden hamster (MesAur1.0) was

1046

taken from Ensemble database release 110. The SarsCoV2 reference file was obtained

1047

from Ensembl COVID-19 database (Genome assembly: ASM985889v3). The following

1048

steps of analysis were performed using R software package (version 4.2.1) and RStudio1049(version 2022.02.0 Build 443)82. Feature counts were obtained by Rsubread v2.16.0

1050

followed by feature annotation using biomaRt_2.54.1. In cases where the gene symbol

1051

information for hamster genes was missing, the orthologous human gene symbols were1052

used instead. For the transcriptome analysis, only genes with a biotype of 'protein coding'1053

and counts greater than 10 in at least four samples were included. Differential gene
44

1054

expression analysis was performed using DESeq2 (version 1.36.0) after normalizing gene

1055

counts with the rlog function (regularized log transformation). Normalized gene counts

1056

were expressed as log2 values. Volcano plots were generated with the package

1057

EnhancedVolcano (version 1.14.0)83. Functional analyses of DEGs were performed using1058

the R software package cluster Profiler (version 4.4.4)84. Heatmaps were generated with1059

the function heatmap2 of package gplots (version 3.1.3; https://github.com/talgalili/gplots).

1060

Upset plots were prepared with package UpSetR (version 1.4.0)85. For beeswarm graphs

1061

of expression levels, package beeswarm (version 0.4.0)86 was used.

1062
1063

Statistic and reproducibility1064

The animal experiment, immunolabellings, quantifications, and data analysis were1065

performed once. Sample size was determined with ANOVA and Kruskal–Wallis test.

1066

Allocation to experimental groups was randomized. No data was excluded from the1067

analysis. The investigators were not blinded to group allocation during the animal

1068

experiment. For morphologic analysis, samples were blinded.

1069
1070

Data availability

1071

The data generated in this study are provided in the Supplementary Information and1072

Source Data file. Bulk RNASeq data from the lungs of SARS-CoV-2-infected hamsters

1073

are made publicly available, reference from GEO is provided: GSE271365. Source data1074

are provided with this paper.

1075
1076

Acknowledgments

1077

The authors are grateful to Julia Baskas, Petra Grünig, Jana-Svea Harre, Caroline Schütz,

1078

Kerstin Schöne and Melanie Woischnik for their excellent technical assistance.

1079

Furthermore, the authors would like to thank Henrieke Meyer-Sievers, Katrin Wirz,

1080

Claudia Schulz, Monika Berg, Mathias Herberg, Bernd Vollbrecht and Darren Markillie for

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their assistance during the animal experiment. We thank Cristina-Luminita Baciu from
45

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Data Sciences International (DSI) for her excellent technical support regarding the use of1083

FinePointe Respiratory Software. This project was supported in part by the COVID-19

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Research Network of the State of Lower Saxony (COFONI) with funding from the Ministry1085

of Science and culture of Lower Saxony, Germany (14-76403-184). Additionally, this1086

research was partially supported by the Deutsche Forschungsgemeinschaft (DFG;

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German Research Foundation) -398066876/GRK 2485/2, Wolfgang Baumgärtner, Laura

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Heydemann, Tom Schreiner, Georg Beythien).

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Supplementary Files
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SupplementaryinformationHeydemannetal.docx
nrreportingsummary.pdf
SupplementaryData1.xlsx
SupplementaryData2.xlsx
SupplementaryData3.xlsx
SupplementaryData4.xlsx
SupplementaryData5.xlsx
SupplementaryData6.xlsx