Cytoarchitecture of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography: imaging workflow and classification for drug testing (preprint)

X-ray Phase Contrast Tomography (XPCT) based on wavefield propagation has been established as a high resolution three-dimensional (3D) imaging modality, suitable to reconstruct the intricate structure of soft tissues, and the corresponding pathological alterations. However, for biomedical research, more is needed than 3D visualisation and rendering of the cytoarchitecture in a few selected cases. First, the throughput needs to be increased to cover a statistically relevant number of samples. Second, the cytoarchitecture has to be quantified in terms of morphometric parameters, independent of visual impression. Third, dimensionality reduction and classification are required for identification of effects and interpretation of results. To address these challenges, we here design and implement a novel integrated and high throughput XPCT imaging and analysis workflow for 3D histology, pathohistology and drug testing. Our approach uses semi-automated data acquisition, reconstruction and statistical quantification. We demonstrate its capability for the example of lung pathohistology in Covid-19. Using a small animal model, different Covid-19 drug candidates are administered after infection and tested in view of restoration of the physiological cytoarchitecture, specifically the alveolar morphology. To this end, we then use morphometric parameter determination followed by a dimensionality reduction and classification based on optimal transport. This approach allows efficient discrimination between physiological and pathological lung structure, thereby providing quantitative insights into the pathological progression and partial recovery due to drug treatment. Finally, we stress that the XPCT image chain implemented here only used synchrotron radiation for validation, while the data used for analysis was recorded with laboratory µCT radiation, more easily accessible for pre-clinical research.

Cytoarchitecture of SARS-CoV-2 infected hamster lungs by X-ray phase contrast tomography: imaging workflow and classification for drug testing (preprint)

X-ray Phase Contrast Tomography (XPCT) based on wavefield propagation has been established as a high resolution three-dimensional (3D) imaging modality, suitable to reconstruct the intricate structure of soft tissues, and the corresponding pathological alterations. However, for biomedical research, more is needed than 3D visualisation and rendering of the cytoarchitecture in a few selected cases. First, the throughput needs to be increased to cover a statistically relevant number of samples. Second, the cytoarchitecture has to be quantified in terms of morphometric parameters, independent of visual impression. Third, dimensionality reduction and classification are required for identification of effects and interpretation of results. In this work, we present a workflow implemented at a laboratory CT setup, using semi-automated data acquisition, reconstruction and statistical quantification of lung tissue in an early screen of Covid-19 drug candidates. Different drugs were tested in a hamster model after SARS-CoV-2 infection. To make full use of the recorded high-throughput XPCT data, we then used morphometric parameter determination followed by a dimensionality reduction and classification based on optimal transport. This approach allows efficient discrimination between physiological and pathological lung structure, thereby providing invaluable insights into the pathological progression and partial recovery due to drug treatment.

Spatiotemporal analysis of SARS-CoV-2 infection reveals an expansive wave of monocyte-derived macrophages associated with vascular damage and virus clearance in hamster lungs (preprint)

Factors of the innate immune response to SARS-CoV-2 in the lungs are pivotal for the ability of the host to deal with the infection. In humans, excessive macrophage infiltration is associated with disease severity. Using 3D spatiotemporal analysis of optically cleared hamster lung slices in combination with virological, immunohistochemical and RNA sequence analyses, we visualized the spread of SARS-CoV-2 through the lungs and the rapid anti-viral response in infected lung epithelial cells, followed by a wave of monocyte-derived macrophage (MDM) infiltration and virus elimination from the tissue. These SARS-CoV-2 induced innate immune processes are closely related to the onset of necrotizing inflammatory and consecutive remodelling responses in the lungs, which manifests as extensive cell death, vascular damage, thrombosis, and cell proliferation. Here we show that MDM are directly linked to virus clearance, and appear in connection with tissue injury and blood vessel damage. Rapid initiation of prothrombotic factor upregulation, tissue repair and alveolar cell proliferation results in tissue remodelling, which is followed by fibrosis development despite a decrease in inflammatory and anti-viral activities. Thus, although the hamsters are able to resolve the infection following the MDM influx and repair lung tissue integrity, longer-term alterations of the lung tissues arise as a result of concurrent tissue damage and regeneration processes.

Compellingly high SARS-CoV-2 susceptibility of Golden Syrian hamsters suggests multiple zoonotic infections of pet hamsters during the COVID-19 pandemic (preprint)

Golden Syrian hamsters (Mesocricetus auratus) are used as a research model for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2). Millions of Golden Syrian hamsters are also kept as pets in close contact to humans. To determine the minimum infective dose (MID) for assessing the zoonotic transmission risk, and to define the optimal infection dose for experimental studies, we orotracheally inoculated hamsters with SARS-CoV-2 doses from 1*105 to 1*10-4 tissue culture infectious dose 50 (TCID50). Body weight and virus shedding were monitored daily. 1*10-3 TCID50 was defined as the MID, and this was still sufficient to induce virus shedding at levels up to 102.75 TCID50/ml, equaling the estimated MID for humans. Virological and histological data revealed 1*102 TCID50 as the optimal dose for experimental infections. This compellingly high susceptibility resulting in productive infections in Golden Syrian hamsters needs to be considered also as a source of SARS-CoV-2 infections in humans.

Multi-species ELISA for the detection of antibodies against SARS-CoV-2 in animals (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic with millions of infected humans and hundreds of thousands of fatalities. As the novel disease - referred to as COVID-19 - unfolded, occasional anthropozoonotic infections of animals by owners or caretakers were reported in dogs, felid species and farmed mink. Further species were shown to be susceptible under experimental conditions. The extent of natural infections of animals, however, is still largely unknown. Serological methods will be useful tools for tracing SARS-CoV-2 infections in animals once test systems are validated for use in different species. Here, we developed an indirect multi-species ELISA based on the receptor-binding domain (RBD) of SARS-CoV-2. The newly established ELISA was validated using 59 sera of infected or vaccinated animals including ferrets, raccoon dogs, hamsters, rabbits, chickens, cattle and a cat, and a total of 220 antibody-negative sera of the same animal species. Overall, a diagnostic specificity of 100.0% and sensitivity of 98.31% was achieved, and the functionality with every species included in this study could be demonstrated. Hence, a versatile and reliable ELISA protocol was established that enables high-throughput antibody detection in a broad range of animal species, which may be used for outbreak investigations, to assess the seroprevalence in susceptible species or to screen for reservoir or intermediate hosts.

What if we perceive SARS-CoV-2 genomes as documents? Topic modelling using Latent Dirichlet Allocation to identify mutation signatures and classify SARS-CoV-2 genomes (preprint)

Topic modeling is frequently employed for discovering structures (or patterns) in a corpus of documents. Its utility in text-mining and document retrieval tasks in various fields of scientific research is rather well known. An unsupervised machine learning approach, Latent Dirichlet Allocation (LDA) has particularly been utilized for identifying latent (or hidden) topics in document collections and for deciphering the words that define one or more topics using a generative statistical model. Here we describe how SARS-CoV-2 genomic mutation profiles can be structured into a Bag of Words to enable identification of signatures (topics) and their probabilistic distribution across various genomes using LDA. Topic models were generated using ~47000 novel corona virus genomes (considered as documents), leading to identification of 16 amino acid mutation signatures and 18 nucleotide mutation signatures (equivalent to topics) in the corpus of chosen genomes through coherence optimization. The document assumption for genomes also helped in identification of contextual nucleotide mutation signatures in the form of conventional N-grams (e.g. bi-grams and tri-grams). We validated the signatures obtained using LDA driven method against the previously reported recurrent mutations and phylogenetic clades for genomes. Additionally, we report the geographical distribution of the identified mutation signatures in SARS-CoV-2 genomes on the global map. Use of the non-phylogenetic albeit classical approaches like topic modeling and other data centric pattern mining algorithms is therefore proposed for supplementing the efforts towards understanding the genomic diversity of the evolving SARS-CoV-2 genomes (and other pathogens/microbes).

Susceptibility of raccoon dogs for experimental SARS-CoV-2 infection (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in China at the end of 2019, and became pandemic. The zoonotic virus most likely originated from bats, but definite intermediate hosts have not yet been identified. Raccoon dogs (Nyctereutes procyonoides) are kept for fur production, in particular in China, and were suspected as potential intermediate host for both SARS-CoV6 and SARS-CoV2. Here we demonstrate susceptibility of raccoon dogs for SARS-CoV-2 infection after intranasal inoculation and transmission to direct contact animals. Rapid, high level virus shedding, in combination with minor clinical signs and pathohistological changes, seroconversion and absence of viral adaptation highlight the role of raccoon dogs as a potential intermediate host. The results are highly relevant for control strategies and emphasize the risk that raccoon dogs may represent a potential SARS-CoV-2 reservoir. Our results support the establishment of adequate surveillance and risk mitigation strategies for kept and wild raccoon dogs. Article Summary LineRaccoon dogs are susceptible to and efficiently transmit SARS-CoV2 and may serve as intermediate host

Experimental Transmission Studies of SARS-CoV-2 in Fruit Bats, Ferrets, Pigs and Chickens (preprint)

Background: A novel zoonotic SARS-related coronavirus emerged in China at the end of 2019. The novel SARS-CoV-2 became pandemic within weeks and the number of human infections and severe cases is increasing. The role of potential animal hosts is still understudied.Methods: We intranasally inoculated fruit bats (Rousettus aegyptiacus; n=9), ferrets (n=9), pigs (n=9) and chickens (n=17) with 105 TCID50 of a SARS-CoV-2 isolate per animal. Animals were monitored clinically and for virus shedding. Direct contact animals (n=3) were included. Animals were humanely sacrificed for virological and immune-pathohistological analysis at different time points.Findings: Under these settings, pigs and chickens were not susceptible to SARS-CoV-2. All swabs as well as organ samples and contact animals remained negative for viral RNA, and none of the animals seroconverted. Rousettus aegyptiacus fruit bats experienced a transient infection, with virus detectable by RT-qPCR, immunohistochemistry (IHC) and in situ hybridization (ISH) in the nasal cavity, associated with rhinitis. Viral RNA was also identified in the trachea, lung and lung associated lymphatic tissue. One of three contact bats became infected. More efficient virus replication but no clinical signs were observed in ferrets with transmission to all direct contact animals. Prominent viral RNA loads of up to 104 viral genome copies/ml were detected in the upper respiratory tract. Mild rhinitis was associated with viral antigen detection in the respiratory and olfactory epithelium. Both fruit bats and ferrets developed SARS-CoV-2 reactive antibodies reaching neutralizing titers of up to 1:1024.Interpretation: Pigs and chickens could not be infected intranasally by SARS-CoV-2, whereas fruit bats showed characteristics of a reservoir host. Virus replication in ferrets resembled a subclinical human infection with efficient spread. These animals might serve as a useful model for further studies e.g. testing vaccines or antivirals.Funding Statement: Intramural funding of the German Federal Ministry of Food and Agriculture provided to the Friedrich-Loeffler-Institut.Declaration of Interests: All authors declare no competing interest.Ethics Approval Statement: The animal experiments were evaluated and approved by the ethics committee of the State Office of Agriculture, Food safety, and Fishery in Mecklenburg – Western Pomerania (LALLF M-V: LVL MV/TSD/7221.3-2-010/18-12). All procedures were carried out in approved biosafety level 3 (BSL3) facilities.