SARS-CoV-2 infection leads to acute infection with dynamic cellular and inflammatory flux in the lung that varies across nonhuman primate species
bioinformatics immunology/immunity inflammation virology
Authors: Dhiraj Kumar Singh et al.,
Link to paper: https://www.biorxiv.org/content/10.1101/2020.06.05.136481v1
Journal/ Pre-Print: BioRxiv
Tags: Immunology/Immunity, Inflammation, Virology, In Vivo Modelling
1. Detailed examination of the differences in immune response to SARS-CoV2 by rhesus macaques, baboons, and marmosets.
2. Rhesus macaques and baboons display differential pathologies making them complimentary models to test different disease attributes.
3. This provides a clear frame work of how rhesus macaques, baboons, and marmosets respond to SARS-CoV2 and paves the way for future non-human primate work.
This paper compares the immune responses upon SARS-CoV-2 infection between rhesus macaques, baboons, and marmosets. It provides data on viral replication in the lungs and throat, pneumonia development by both X-Ray sand CT scans, broad cytokine production, and finally immune cell infiltration by both flow cytometry and immunohistochemistry. The authors find marmosets have limited pathology whereas Rhesus macaques develop a moderate progressive pneumonia. Baboons show the greatest lung pathology with prolonged viral shedding. This extensive data set is a useful resource to anyone looking to start SARS-CoV-2 non-human primate work.
Impact for SARS-CoV2/COVID19 research efforts
Understand the immune response to SARS-CoV2/COVID19 in non-human primates
Establishes in vivo models for SARS-CoV2 research
· In vivo study (NHP)
Strengths and limitations of the paper
Novelty: Although non-human primate models of SARS-CoV2 infection already exist, this paper specifically compares the immune response between different primate models (rhesus macaques, baboons and marmosets) during SARS-CoV2 infection.
Appropriate statistics: Details of statistical tests are provided, however, in several figures the statistical test is described in the legend but no statistical tests are shown on the figures. In addition, throughout the manuscript data are described as significant without statistical tests to support this. It should also be noted that in several places data are described as significant when the statistical comparison shown is between the wrong groups.
Viral model used: SARS-CoV-2 USA-WA1/2020
Main limitations: - There is no discussion of the reasoning behind choosing the 3 day time point post infection for the acute infection model.
- A number of the conclusions are not supported by the data shown. Also ‘significant’ is used to describe data when no statistical tests are used.
- Figure S7 has a number of issues, in particular the description of data in the text is not in agreement with the data shown. Also, the tCO2 measurements at D3 are not consistent with the data shown in Figure S1 for the same timepoint. There is no evidence from this figure that the disease ‘markedly improved over time’ as stated in text.
- The data shown in Figure S13 are confused, do not support their conclusions and are missing statistical tests. In particular, it is unclear how alveolar macrophages can be quantified in the peripheral blood when they are an exclusively lung-resident population. Data are also missing, such as for the classical monocytes.
- The conclusion that ACE2 expression is significantly higher in the lungs of younger macaques v older macaques is not supported by the data presented in Figure S17. Also, the only statistical test shown here is between naïve and young macaques.
- The authors state that their data suggest that in humans underlying conditions play more of role than aging in the increased mortality and morbidity of COVID19. However, in many of the analyses of the longitudinal data presented here, the individual macaques are not separated into age groups.
- The RNAseq dataset is under-used. Only expression of viral receptors/co-receptors is discussed. The data shown in the heatmap does not match the data shown in the box plot or the description in the text. It is unclear why RNAseq was performed on the samples from 14-17 d.p.i. rather than the 3 d.p.i. samples.
- Comparisons of pathologies between the three species is difficult with the data presented in the current format.
- Supplementary tables are not available in the pre-print
- Throughout the manuscript, there are incorrect references to figures which make this lengthy document difficult to read. The manuscript requires extensive editing
- The quality of a number of figures is poor so it is difficult to view them. In addition, many are lacking annotation