Adult stem cell-derived complete lung organoid models emulate lung disease in COVID-19

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    Evaluation Summary:

    The manuscript by Tindle et al describes generation of adult lung organoids (ALO) from human lung biopsies and their use to study the changes in gene expression as a result of SARS-CoV-2 infection. In this particular case the authors report the presence of AT1, AT2 cells, Basal cells, Goblet cells, Ciliated cells and Club cells. The authors were able to cultivate the cells at the air-liquid interface and to establish cultures of predominately proximal and predominately distal airway cells. The main finding is that proximal cells are more prone to viral infection, while distal cells are governing the exuberant inflammatory response, with both cells required for the exuberant response to occur. Useful information provided by the paper is the analysis gene signatures of various cellular models, in comparison to the infected human lung.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

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Abstract

SARS-CoV-2, the virus responsible for COVID-19, causes widespread damage in the lungs in the setting of an overzealous immune response whose origin remains unclear.

Methods:

We present a scalable, propagable, personalized, cost-effective adult stem cell-derived human lung organoid model that is complete with both proximal and distal airway epithelia. Monolayers derived from adult lung organoids (ALOs), primary airway cells, or hiPSC-derived alveolar type II (AT2) pneumocytes were infected with SARS-CoV-2 to create in vitro lung models of COVID-19.

Results:

Infected ALO monolayers best recapitulated the transcriptomic signatures in diverse cohorts of COVID-19 patient-derived respiratory samples. The airway (proximal) cells were critical for sustained viral infection, whereas distal alveolar differentiation (AT2→AT1) was critical for mounting the overzealous host immune response in fatal disease; ALO monolayers with well-mixed proximodistal airway components recapitulated both.

Conclusions:

Findings validate a human lung model of COVID-19, which can be immediately utilized to investigate COVID-19 pathogenesis and vet new therapies and vaccines.

Funding:

This work was supported by the National Institutes for Health (NIH) grants 1R01DK107585-01A1, 3R01DK107585-05S1 (to SD); R01-AI141630, CA100768 and CA160911 (to PG) and R01-AI 155696 (to PG, DS and SD); R00-CA151673 and R01-GM138385 (to DS), R01- HL32225 (to PT), UCOP-R00RG2642 (to SD and PG), UCOP-R01RG3780 (to P.G. and D.S) and a pilot award from the Sanford Stem Cell Clinical Center at UC San Diego Health (P.G, S.D, D.S). GDK was supported through The American Association of Immunologists Intersect Fellowship Program for Computational Scientists and Immunologists. L.C.A's salary was supported in part by the VA San Diego Healthcare System. This manuscript includes data generated at the UC San Diego Institute of Genomic Medicine (IGC) using an Illumina NovaSeq 6000 that was purchased with funding from a National Institutes of Health SIG grant (#S10 OD026929).

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  1. Author Response:

    Reviewer #2:

    The manuscript "Adult Stem Cell-derived Complete Lung Organoid Models Emulate Lung Disease in COVID-19" by Das and colleagues introduces a new model system of airway epithelium derived from adult lung organoids (ALO) to be utilised for the study of COVID-19-related processes. In this manuscript two main novelties are claimed: the development of a new model system which represents both proximal as distal airway epithelium and a computationally acquired gene signature that identifies SARS-CoV-2-infected individuals. While interesting data are presented, the novelty claim is questionable and the data is not always convincing.

    Strengths:

    Multiple model systems have been developed for COVID-19. The lack of a complete ex vivo system is still hampering quick development of efficient therapies. The authors in this manuscript describe a new model system which allows for both proximal and distal airway infectious studies. While their claim is not completely novel, the method used can be used in other studies for the discovery of potential new therapies against COVID-19. Moreover, their computational analyses shows the promise of bioinformatics in discovering important features in COVID-19 diseased patients which might elucidate new therapeutic targets.

    Weaknesses:

    Although the paper does have strengths in principle, the weaknesses of the paper are that these strengths are not directly demonstrated and their model system is not completely novel. That is, insufficient analyses are performed to fully support the key claims in the manuscript by the data presented. In particular:

    The characterisation of the adult lung organoids and their monolayers is insufficient and sometimes incorrect. Their claims are based on contradicting data which includes cell composition in the culture system. Therefore, the claim of a novel model system seems invalid and rushed. Moreover, the characterisation of a new gene signature is based on this model system which has been infected with SARS-CoV-2. The infection however is hard to interpret and therefore claims are hard to validate.

    First of all, we thank the reviewer for a very thoughtful and in-depth review that inspired us to do additional analyses to address the criticisms that we believe are not just fair and justified, but also constructive. Coming from a thought leader in the field, they also squarely point at essential areas where we needed to make improvements with additional analyses. For that, we are grateful.

    There appears to be three major critiques:

    (i) NOVELTY: The reviewer questions whether the model itself is novel, and asked how this is any different from the previously published manuscript (Lamers et al., in EMBO J (2021)40:e105912) describing lung organoids with mixed cellularity, also claimed as complete with proximal and distal components that was publicly released after ours was submitted to eLife.

    (ii) INCOMPLETE: The reviewer noted that the model system was not fully characterized to have reached that potential and the impact of culture systems on cell composition and such details were incompletely analyzed (hence, rushed and incomplete).

    (iii) CLARITY ON GENE SIGNATURE: Characterization of organoids with new gene signature was added to interpret.

    Overview of how we tackled these three points head on:

    (i) NOVELTY: As for what is novel in our model (i.e., ALO), and how does it compare to the model described by Lamers et al., in EMBO J, 2021, we provide metrics for which is closer to the human disease when infected with SARS-CoV-2. Figure 6H was added.

    (ii) INCOMPLETE: We agree about the ‘rushed’ aspect. We were working amidst a pandemic to race to the finish line. But during the revision we could add much more characterization data, which we hope mitigates the concerns raised by this reviewer. Three new figures (Figure 2- Figure Supplement 3-4-5) and some IF panels in main Figure 3 were added.

    (iii) GENE SIGNATURE: As for the characterization of the SARS-CoV-2 infected ALO-derived monolayers using a new gene signature, we apologize that we might not have written with sufficient clarity as to what was the source of the signature. In the revised version of the manuscript, we have now explicitly stated in the edited Figure panel 6A that the signature (166-gene viral pandemic signature, a.k.a. ViP) was derived from human clinical samples, after a comprehensive analysis of > 45,000 datasets. This paper has been accepted in eBioMedicine in April 2021, and the preprint is available in BioRxiv 2020-PMID: 32995790.

    Reviewer #3:

    The authors have developed a new culture method to expand adult lung cells in vitro as 3-D organoids. This culture system is different from previous organoid cultures which include either bronchiolar, or alveolar, lineages. Rather, the authors attempted to preserve both lineages over long-term passaging. The 3-D cultured organoids can be dissociated and re-plated as 2D monolayers, which can be either cultured immersed in medium or in air-liquid interface (ALI) conditions, exhibiting a different bias towards alveolar and airway lung cell types respectively. The 2D monolayer cultures can be infected by COVID-19 virus and showed a progressive increase in virus load, which was distinct from iPSC- derived alveolar type 2 (AT2) cell and bronchiolar epithelial cell culture control infections. Through bioinformatics analysis, the authors were able to show that their monolayer cultures acquired similar immune response features to an in vivo COVID infection dataset, indicating that this culture system may be suitable for modeling COVID infection in vitro. It is particularly interesting that the bioinformatics analyses suggested that this adult human lung organoid system, with both airway and alveolar phenotypes, showed greater resemblance to the transcriptional immune response of severely COVID-infected lungs than either cultured cell type alone. This aspect of the manuscript strongly suggests that the authors' approach of developing a mixed lung organoid model is an extremely good one.

    However, the data presented in figures 2 and 3 cast serious doubts over the long-term reproducibility of the organoid system. That individual organoids contain both airway and alveolar lineages has not yet been convincingly demonstrated (Fig 2). In addition, bulk RNAseq experiments illustrate that the overall cell composition of the cultures drifts significantly during long-term passaging (Fig 3). Due to this variability, the organoids' ability to act as a suitable model for viral infections that would be amenable to drug screening approaches is also questionable.

    We thank the reviewer for the generally positive nature of the comments. The reviewer made some key and thoughtful suggestions on how to improve the manuscript; we greatly appreciate the effort and time that went into making them. Besdes the encouraging comments and the suggestions, the reviewer also raised some criticisms that are along the same lines as those that were raised also by Reviewers 1 and 2. We have tried our best to address these criticisms and agree that mitigating these are essential for widespread acceptance of the model by others.

  2. Reviewer #3 (Public Review):

    The authors have developed a new culture method to expand adult lung cells in vitro as 3-D organoids. This culture system is different from previous organoid cultures which include either bronchiolar, or alveolar, lineages. Rather, the authors attempted to preserve both lineages over long-term passaging. The 3-D cultured organoids can be dissociated and re-plated as 2D monolayers, which can be either cultured immersed in medium or in air-liquid interface (ALI) conditions, exhibiting a different bias towards alveolar and airway lung cell types respectively. The 2D monolayer cultures can be infected by COVID-19 virus and showed a progressive increase in virus load, which was distinct from iPSC- derived alveolar type 2 (AT2) cell and bronchiolar epithelial cell culture control infections. Through bioinformatics analysis, the authors were able to show that their monolayer cultures acquired similar immune response features to an in vivo COVID infection dataset, indicating that this culture system may be suitable for modeling COVID infection in vitro. It is particularly interesting that the bioinformatics analyses suggested that this adult human lung organoid system, with both airway and alveolar phenotypes, showed greater resemblance to the transcriptional immune response of severely COVID-infected lungs than either cultured cell type alone. This aspect of the manuscript strongly suggests that the authors' approach of developing a mixed lung organoid model is an extremely good one.

    However, the data presented in figures 2 and 3 cast serious doubts over the long-term reproducibility of the organoid system. That individual organoids contain both airway and alveolar lineages has not yet been convincingly demonstrated (Fig 2). In addition, bulk RNAseq experiments illustrate that the overall cell composition of the cultures drifts significantly during long-term passaging (Fig 3). Due to this variability, the organoids' ability to act as a suitable model for viral infections that would be amenable to drug screening approaches is also questionable.

  3. Reviewer #2 (Public Review):

    The manuscript "Adult Stem Cell-derived Complete Lung Organoid Models Emulate Lung Disease in COVID-19" by Das and colleagues introduces a new model system of airway epithelium derived from adult lung organoids (ALO) to be utilised for the study of COVID-19-related processes. In this manuscript two main novelties are claimed: the development of a new model system which represents both proximal as distal airway epithelium and a computationally acquired gene signature that identifies SARS-CoV-2-infected individuals. While interesting data are presented, the novelty claim is questionable and the data is not always convincing.

    Strengths:

    Multiple model systems have been developed for COVID-19. The lack of a complete ex vivo system is still hampering quick development of efficient therapies. The authors in this manuscript describe a new model system which allows for both proximal and distal airway infectious studies. While their claim is not completely novel, the method used can be used in other studies for the discovery of potential new therapies against COVID-19. Moreover, their computational analyses shows the promise of bioinformatics in discovering important features in COVID-19 diseased patients which might elucidate new therapeutic targets.

    Weaknesses:

    Although the paper does have strengths in principle, the weaknesses of the paper are that these strengths are not directly demonstrated and their model system is not completely novel. That is, insufficient analyses are performed to fully support the key claims in the manuscript by the data presented. In particular:

    The characterisation of the adult lung organoids and their monolayers is insufficient and sometimes incorrect. Their claims are based on contradicting data which includes cell composition in the culture system. Therefore, the claim of a novel model system seems invalid and rushed. Moreover, the characterisation of a new gene signature is based on this model system which has been infected with SARS-CoV-2. The infection however is hard to interpret and therefore claims are hard to validate.

  4. Reviewer #1 (Public Review):

    The manuscript by Tindle et al describes generation of adult lung organoids (ALO) from human lung biopsies and their use to study the changes in gene expression as a result of SARS-CoV-2 infection. The main advantage of the use of organoids is the ability to generate many cell types that make up the lung. In this particular case the authors report the presence of AT1, AT2 cells, Basal cells, Goblet cells, Ciliated cells and Club cells. The authors were able to cultivate the cells at the air-liquid interface and to establish cultures of predominately proximal and predominately distal airway cells. The main finding is that proximal cells are more prone to viral infection, while distal cells are governing the exuberant inflammatory response, with both cells required for the exuberant response to occur. A useful information provided by the paper is the analysis gene signatures of various cellular models, in comparison to the infected human lung.

  5. Evaluation Summary:

    The manuscript by Tindle et al describes generation of adult lung organoids (ALO) from human lung biopsies and their use to study the changes in gene expression as a result of SARS-CoV-2 infection. In this particular case the authors report the presence of AT1, AT2 cells, Basal cells, Goblet cells, Ciliated cells and Club cells. The authors were able to cultivate the cells at the air-liquid interface and to establish cultures of predominately proximal and predominately distal airway cells. The main finding is that proximal cells are more prone to viral infection, while distal cells are governing the exuberant inflammatory response, with both cells required for the exuberant response to occur. Useful information provided by the paper is the analysis gene signatures of various cellular models, in comparison to the infected human lung.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

  6. SciScore for 10.1101/2020.10.17.344002: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementConsent: All donations to this trial were obtained after telephone consent followed by written email confirmation by the next of kin/power of attorney per California state law (no in-person visitation could be allowed into our COVID-19 ICU during the pandemic).
    RandomizationFields of view that were representative and/or of interest were determined by randomly imaging 3 different fields.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Sections were incubated with horse anti-rabbit IgG secondary antibodies for 30 min at room temperature and then washed with TBS or PBS 3 times for 5 min each.
    anti-rabbit IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    The HBEpC and HSAEpC were cultured in human bronchial/tracheal epithelial cell media and small airway epithelial cell media, respectively, following the instructions of Cell Application.
    HSAEpC
    suggested: None
    Software and Algorithms
    SentencesResources
    Z-slices of a Z-stack were overlaid to create maximum intensity projection images; all images were processed using FIJI (Image J) software.
    FIJI
    suggested: (Fiji, RRID:SCR_002285)
    Image J
    suggested: (ImageJ, RRID:SCR_003070)
    Samples were demultiplexed using bcl2fastq v2.20 Conversion Software (Illumina, San Diego, CA).
    bcl2fastq
    suggested: (bcl2fastq , RRID:SCR_015058)
    RNASeq data was processed using kallisto (version 0.45.0), and human genome GRCh38 Ensembl version 94 annotation (Homo_sapiens GRCh38.94 chr_patch_hapl_scaff.gtf).
    Ensembl
    suggested: (Ensembl, RRID:SCR_002344)
    The raw data and processed data are deposited in Gene Expression Omnibus under accession no GSE157055, and GSE157057.
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)
    Analysis of RNA seq Datasets: DESeq2 28 was applied to uninfected and infected samples to identify Up- and Down-regulated genes.
    DESeq2
    suggested: (DESeq, RRID:SCR_000154)
    Pathway analysis of gene lists was carried out via the Reactome database and algorithm 29.
    Reactome
    suggested: (Reactome, RRID:SCR_003485)
    Violin, Swarm and Bubble plots are created using python seaborn package version 0.10.1. Single Cell RNA Seq data analysis: Single Cell RNASeq data from GSE145926 was downloaded from GEO in the HDF5 Feature Barcode Matrix Format.
    seaborn
    suggested: (seaborn, RRID:SCR_018132)
    All statistical analyses were performed using GraphPad prism 6.1.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Standard t-tests were performed using python scipy.stats.ttest_ind package (version 0.19.0).
    python
    suggested: (IPython, RRID:SCR_001658)
    scipy
    suggested: (SciPy, RRID:SCR_008058)

    Results from OddPub: Thank you for sharing your data.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Limitations of the study: Our adult stem-cell-derived lung organoids, complete with all epithelial cell types, can model COVID-19, but still remains a simplified/rudimentary version compared to the adult human organ. Simultaneous addition of endothelial cells and immune cells could be useful to better understand the pathophysiologic basis for DAD, microangiopathy, and even organizing fibrosis with loss of lung capacity that has been observed in many patients38; these insights should be valuable to fight some of the long-term sequelae of COVID-19. Future work with flow cytometry and cell sorting of our lung organoids would help understand each cell type’s role in viral pathogenesis. Larger living biobanks of genotyped and phenotyped ALOs, representing donors of different age, ethnicity, predisposing conditions and co-existing comorbidities, will advance our understanding of why SARS-CoV-2 and possibly other infectious agents may trigger different disease course in different hosts. Although we provide proof-of-concept studies in low throughput mode demonstrating the usefulness of the ALOs as human pre-clinical models for screening therapeutics in Phase ‘0’ trials, optimization for the same to be adapted in HTP mode was not attempted here.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.