Article activity feed

  1. Author Response:

    Reviewer #1 (Public Review):

    The manuscript presented describes the transcriptome of primitive hematopoietoc stem and progenitor cells harvested from untreated control or mice treated with either PGE2, G-CSF, pIpC or indomethacin. These are some of the drugs commonly used to generate experimental models of stressed hematopoiesis. Having observed some patterns of responses and the transcriptomic level, the authors ask whether these may be driven by specific chromatin accessibility patterns in stem and progenitor cells subset. However, ATAC-seq reveals that this is not the case when directly responsive genes are analyzed, and rather differences can be found in the promoter accessibility of genes further downstream.

    Strengths. The authors analyze large and challenging datasets, where relatively minor differences in transcription and chromatin accessibility patterns are highlighted.

    Weaknesses. The choice of stimuli is somehow arbitrary, and the description of the data presented in the figures is often hard to follow, with some contradictions present and text and figures being ordered differently.

    We thank reviewer #1 for the positive evaluation of our work highlighting our analysis of a large and challenging dataset. In our updated manuscript we have addressed all the weaknesses indicated. We have clarified the rationale for using different stimuli and reorganized our manuscript to more clearly delineate figures discussing HSCs (1 and 2) versus figures with comparative analysis of LSKs vs HSCs (3 and 4).

    Reviewer #2 (Public Review):

    Fast et al here describe responses by hematopoietic stem and progenitor cells to niche signals using scRNseq and ATACseq. The data provide a rich resource to the research community demonstrating a number of distinct cell states, and heterogeneity between cell clusters in their responses to external stimuli. Notable observations are the continuum in cell states among HSCs and LSK cells, and the distinct clusters that are marked by interferon signaling response as opposed to AP-1 family / PGE signaling. This paper is a resource paper that will serve as a starting point for future studies - in depth studies were not undertaken to validate or understand the implications of these findings on disease states or developmental outcomes, although such studies would certainly increase the impact of the work if they were available.

    We are very pleased that Reviewer #2 feels that our data “provide a rich resource to the research community” and that our paper could “serve as a starting point for future studies”. We are fully aware of the limitations of our study especially the absence of functional validation of specific hypotheses generated from our genomics data. Carefully executed HSC reconstitution experiments take between months and years and we opted to not hold back the dataset until we would have completed these experiments. Our goal is to make our data available while it is current as a resource for the broader research community. We hope our dataset provides the opportunity for replication of existing datasets and stimulates new follow up experiments.

    Reviewer #3 (Public Review):

    Understanding the molecular determinants controlling hematopoietic stem cell (HSC) biology is critical for myriad clinically-relevant interventions; however, because HSC are rare, this information is limited. Here the authors exploit their considerable facility with HSC isolation and apply single-cell genomics to provide a profile of both normal HSC transcriptional clusters and HSC relevant perturbations (di-methyl-PGE2 vs. the Cox1/2 inhibitor indomethacin, and G-CSF stimulating mobilization, or the TLR3 ligand poly(I:C)) and identify potential underlying regulatory transcription factors based on in silico analyses. They note that they can understand the perturbations as shifts in cells within the unperturbed clusters (with modest gene expression changes in each cluster). There are some aspects of the work that could be changed to improve impact and to clarify the take-home message.

    The manuscript leaves the reader with the expectation that the work will biologically dissect the normal and perturbed cluster/populations. This is probably because the authors do not sufficiently clarify the biological impact of the manipulations, the depth of the published record on them, and then convey the expected versus observed transcriptional changes based on that prior published record. In addition, the transcriptional changes in each cluster within the heatmaps relegated to supplementary data probably provide the essential information, but they fail to represent the data across all clusters with all differentially expressed genes to demonstrate common or distinct gene expression changes. This would best be consolidated to a heatmap of differentials instead of the current method of clustering the actual expression metric. To be clear, it would significantly improve the work to show all differentially expressed genes in each HSC cluster across all perturbed clusters in a single heatmap. A viewer other than a genome browser session (which is not easily maintained) would be an essential improvement.

    The central claim is that "niche signals regulate continuous transcriptional states in hematopoietic stem cells". As an experimental paradigm, the authors inject mice with different molecules and then purify HSC two hours later to examine changes in gene expression. This experimental paradigm does not represent specific perturbations of niche signaling.

    We thank the reviewer for the critical and constructive feedback of our manuscript. We further value the assessment that ‘understanding the molecular determinants controlling hematopoietic stem cell (HSC) biology is critical for myriad clinically-relevant interventions’ which was one of the driving forces for us to undertake this investigation. We have substantially reorganized our manuscript and added additional analysis responding to the concerns raised by the reviewer.

    Specifically we have compared our stimulant induced gene signatures to prior publications to provide additional context for our results in light of previous findings. As suggested we have compiled a unified heatmap (Figure 1D) showing differentially expressed genes between clusters and treatments, which provided additional insights into the crosstalk between cluster defining and treatment induced genes. We have chosen to only display selected genes as opposed to all differentially expressed genes in the main Figure, to increase readability and allow easy referencing from the main text. We have added a heatmap encompassing a larger number of genes to Figure 1 – figure supplement 2I. In addition we have added visualizations of pairwise comparisons of cluster-defining and stimulant-induced genes (Figure 1H and 3F). Source tables contain the complete set of differentially regulated genes for treatments and clusters.

    We have deliberately chosen not to add another interactive visualization application to this manuscript. Currently our data is hosted externally for interactive exploration on the UCSC Cell Browser website (https://cells.ucsc.edu/) which provides a free resource for scientists to make their single-cell datasets available (378 single-cell datasets - July 2021). In addition, we plan to make all source datasets (such as differential expression analyses, cluster enrichments, cluster-treatment overlaps) available in a tabular format that ensures both persistence into the future as well as easy data accessibility for non-computational biologists.

    We agree that the original terminology of ‘niche stimulants regulating HSC transcriptional states’ was not fully accurate. We have revised this terminology throughout the manuscript to ‘external stimulation’ or equivalent wording. While our pharmacological perturbations certainly have limitations (discussed in detail below and in the discussion) we do believe that our results provide novel findings about HSC response to external stressors and the relationship to baseline transcriptional heterogeneity. Because of the cost and time required of single cell genomics studies we believe that our work serves as an important starting ground for more fine-tuned investigations of the niche-HSC interaction using genetic models.

    Read the original source
    Was this evaluation helpful?
  2. Evaluation Summary:

    This is an interesting resource paper, describing the response of hematopoietic stem and progenitor cells to a few drugs commonly used to stress hematopoiesis. Transcriptomic analyses reveal interesting patterns, and the authors use ATAC-seq to investigate whether stem and progenitor subpopulations may be primed to respond in specific ways based on their chromatin accessibility. This turns out not to be the case when directly responsive genes are analyzed, and rather differences can be found in the promoter accessibility of genes further downstream.

    (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. The reviewers remained anonymous to the authors.)

    Read the original source
    Was this evaluation helpful?
  3. Reviewer #1 (Public Review):

    The manuscript presented describes the transcriptome of primitive hematopoietoc stem and progenitor cells harvested from untreated control or mice treated with either PGE2, G-CSF, pIpC or indomethacin. These are some of the drugs commonly used to generate experimental models of stressed hematopoiesis. Having observed some patterns of responses and the transcriptomic level, the authors ask whether these may be driven by specific chromatin accessibility patterns in stem and progenitor cells subset. However, ATAC-seq reveals that this is not the case when directly responsive genes are analyzed, and rather differences can be found in the promoter accessibility of genes further downstream.

    Strengths. The authors analyze large and challenging datasets, where relatively minor differences in transcription and chromatin accessibility patterns are highlighted.

    Weaknesses. The choice of stimuli is somehow arbitrary, and the description of the data presented in the figures is often hard to follow, with some contradictions present and text and figures being ordered differently.

    Read the original source
    Was this evaluation helpful?
  4. Reviewer #2 (Public Review):

    Fast et al here describe responses by hematopoietic stem and progenitor cells to niche signals using scRNseq and ATACseq. The data provide a rich resource to the research community demonstrating a number of distinct cell states, and heterogeneity between cell clusters in their responses to external stimuli. Notable observations are the continuum in cell states among HSCs and LSK cells, and the distinct clusters that are marked by interferon signaling response as opposed to AP-1 family / PGE signaling. This paper is a resource paper that will serve as a starting point for future studies - in depth studies were not undertaken to validate or understand the implications of these findings on disease states or developmental outcomes, although such studies would certainly increase the impact of the work if they were available.

    Read the original source
    Was this evaluation helpful?
  5. Reviewer #3 (Public Review):

    Understanding the molecular determinants controlling hematopoietic stem cell (HSC) biology is critical for myriad clinically-relevant interventions; however, because HSC are rare, this information is limited. Here the authors exploit their considerable facility with HSC isolation and apply single-cell genomics to provide a profile of both normal HSC transcriptional clusters and HSC relevant perturbations (di-methyl-PGE2 vs. the Cox1/2 inhibitor indomethacin, and G-CSF stimulating mobilization, or the TLR3 ligand poly(I:C)) and identify potential underlying regulatory transcription factors based on in silico analyses. They note that they can understand the perturbations as shifts in cells within the unperturbed clusters (with modest gene expression changes in each cluster). There are some aspects of the work that could be changed to improve impact and to clarify the take-home message.

    The manuscript leaves the reader with the expectation that the work will biologically dissect the normal and perturbed cluster/populations. This is probably because the authors do not sufficiently clarify the biological impact of the manipulations, the depth of the published record on them, and then convey the expected versus observed transcriptional changes based on that prior published record. In addition, the transcriptional changes in each cluster within the heatmaps relegated to supplementary data probably provide the essential information, but they fail to represent the data across all clusters with all differentially expressed genes to demonstrate common or distinct gene expression changes. This would best be consolidated to a heatmap of differentials instead of the current method of clustering the actual expression metric. To be clear, it would significantly improve the work to show all differentially expressed genes in each HSC cluster across all perturbed clusters in a single heatmap. A viewer other than a genome browser session (which is not easily maintained) would be an essential improvement.

    The central claim is that "niche signals regulate continuous transcriptional states in hematopoietic stem cells". As an experimental paradigm, the authors inject mice with different molecules and then purify HSC two hours later to examine changes in gene expression. This experimental paradigm does not represent specific perturbations of niche signaling.

    Read the original source
    Was this evaluation helpful?