Engineering Microglial Cells to Promote Spinal Cord Injury Recovery
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eLife Assessment
The study is useful for advancing understanding of spinal cord injuries, but it presents inadequate evidence due to the use of multiple datasets. Data were collected from different models of spinal cord injury, various regions of the spinal cord, and an iPSC model, with the differences between these models making it difficult to draw reliable conclusions.
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Abstract
Spinal cord injury (SCI) can result in irreversible damage, leading to lifelong paralysis for affected individuals. Microglia’s dual impact on neuronal regeneration after SCI, driven by their distinct roles at different stages, merits further study. We conducted a bioinformatic analysis of single-cell transcriptomes (scRNA), spatial transcriptomic (ST) data, and bulk RNA-seq data from Gene Expression Omnibus (GEO) datasets. The data were processed using R packages such as “Seurat”, “DESeq2”,“limma” and “GSVA.” Additionally, we utilized Gene Set Enrichment Analysis (GSEA) and the Enrichr web servers. Analysis of single-cell data and spatial transcriptomics has revealed notable changes in the microglial cell landscape in SCI. These changes encompass the inhibition of innate microglial cells, while reactive microglial cells exhibit pronounced reactive hyperplasia. Moreover, the TGFβ signaling pathway plays a crucial role in regulating the migration of innate microglial cells to enhance SCI recovery. However, reactive microglial cells exhibiting high Trem2 expression contribute to the neuroinflammatory response and can effectively modulate neural cell death in SCI. In particular, inhibiting Trem2 in reactive microglial cells not only reduces inflammation but also mitigates spinal cord injury, and enhancing the TGFβ signaling pathway. What’s more, the use of iPSC-derived microglial cells, which have demonstrated their capacity to augment the potential for replacing the functions of naive microglial cells, iPSC-derived microglia have the potential to replace the functions of naive microglial cells, holds significant promise in addressing SCI. Therefore, we posit that the engineering of microglial cells to promote the SCI recovery. The approach of i nhibiting Trem2-mediated neuroinflammatory responses and transplanting iPSC-derived microglia with long-term TGFβ stimulation may offer potential improvements in SCI recovery.
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eLife Assessment
The study is useful for advancing understanding of spinal cord injuries, but it presents inadequate evidence due to the use of multiple datasets. Data were collected from different models of spinal cord injury, various regions of the spinal cord, and an iPSC model, with the differences between these models making it difficult to draw reliable conclusions.
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Reviewer #1 (Public review):
Summary:
The work of Zhou's team is to perform bioinformatics analysis of single-cell transcriptomes (scRNA), spatial transcriptomic (ST) data, and bulk RNA-seq data from Gene Expression Omnibus (GEO) datasets, published or not in different journals from other teams, about spinal cord injury and/or microglia cells derived human iPSC. Based on their analysis, the authors claim that innate microglial cells are inhibited. They postulate that TGF beta signaling pathways play a role in the regulation of migration to enhance SCI recovery and that Trem2 expression contributes to neuroinflammation response by modulating cell death in spinal cord injury. Finally, they suggest a therapeutic strategy to inhibit Trem2 responses and transplant iPSC-derived microglia with long-term TGF beta stimulation.
Although the idea …
Reviewer #1 (Public review):
Summary:
The work of Zhou's team is to perform bioinformatics analysis of single-cell transcriptomes (scRNA), spatial transcriptomic (ST) data, and bulk RNA-seq data from Gene Expression Omnibus (GEO) datasets, published or not in different journals from other teams, about spinal cord injury and/or microglia cells derived human iPSC. Based on their analysis, the authors claim that innate microglial cells are inhibited. They postulate that TGF beta signaling pathways play a role in the regulation of migration to enhance SCI recovery and that Trem2 expression contributes to neuroinflammation response by modulating cell death in spinal cord injury. Finally, they suggest a therapeutic strategy to inhibit Trem2 responses and transplant iPSC-derived microglia with long-term TGF beta stimulation.
Although the idea of using already available data and reanalyzing them is remarkable, I have major concerns about the paper. The authors have used data from different models of injury, regions, as well as IPSC. It is not possible to mix and draw conclusions when the models used are different. This raises doubts about the authors' expertise in the field of spinal cord injury. Furthermore, the innovativeness of the results is of little significance, especially as no hypothesis is confirmed by experimental data.
Strengths:
Analysis of already large-scale existing data.
Weaknesses:
Mixing data from different models, unfounded conclusions, and over-interpretations, little expertise in the field of spinal cord injury.
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Reviewer #2 (Public review):
Summary:
The authors present an intriguing study utilizing datasets from spinal cord injury (SCI) research to identify potential microglial genes involved in SCI-induced neuronal damage. They identify that inhibiting TREM2 and enhancing the TGF-b signal pathway can inhibit reactive microglia-mediated neuroinflammation. Microglia transplantation using iPSC-derived microglia could also be beneficial for SCI recovery.
Strengths:
This research aims to identify potential genes and signaling pathways involved in microglia-mediated inflammation in spinal cord injury (SCI) models. Meanwhile, analyzing transplanted microglia gene expression provides an extra layer of potential in SCI therapy. The approach represents a good data mining strategy for identifying potential targets to combat neurological diseases.
Weakness…
Reviewer #2 (Public review):
Summary:
The authors present an intriguing study utilizing datasets from spinal cord injury (SCI) research to identify potential microglial genes involved in SCI-induced neuronal damage. They identify that inhibiting TREM2 and enhancing the TGF-b signal pathway can inhibit reactive microglia-mediated neuroinflammation. Microglia transplantation using iPSC-derived microglia could also be beneficial for SCI recovery.
Strengths:
This research aims to identify potential genes and signaling pathways involved in microglia-mediated inflammation in spinal cord injury (SCI) models. Meanwhile, analyzing transplanted microglia gene expression provides an extra layer of potential in SCI therapy. The approach represents a good data mining strategy for identifying potential targets to combat neurological diseases.
Weaknesses:
Microglial gene expression patterns may vary significantly between these models. Without proper normalization or justification, combining these datasets to draw conclusions is problematic. Moreover, other factors also need to be considered, like the gender of the microglia source. Are there any gender differences? How were the iPSC-derived microglia generated? Different protocols may affect microglia gene expression.
While the concept is interesting, the data presented in this study appears preliminary. Without further experiments to support their findings, the conclusions are not convincing.
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Reviewer #3 (Public review):
Summary:
In this study, the authors perform a meta-analysis of existing transcriptomic data describing the responses of cells in the mouse spinal cord to traumatic injury (SCI). They identify two subclasses of microglia, which they term 'innate' and 'reactive' microglia, in the dataset, with the majority of microglia in the uninjured spinal cord being 'innate' and the majority of microglia in the injured region being 'reactive'. The authors propose that, during injury, the population of innate microglia is depleted and replaced by the population of reactive microglia. Using DEG and gene ontology pipelines, the authors suggest that TGF signaling is a positive force that helps recruit healthy microglia to enhance recovery in the context of SCI. In contrast, the microglial phagocytic receptor Trem2 contributes …
Reviewer #3 (Public review):
Summary:
In this study, the authors perform a meta-analysis of existing transcriptomic data describing the responses of cells in the mouse spinal cord to traumatic injury (SCI). They identify two subclasses of microglia, which they term 'innate' and 'reactive' microglia, in the dataset, with the majority of microglia in the uninjured spinal cord being 'innate' and the majority of microglia in the injured region being 'reactive'. The authors propose that, during injury, the population of innate microglia is depleted and replaced by the population of reactive microglia. Using DEG and gene ontology pipelines, the authors suggest that TGF signaling is a positive force that helps recruit healthy microglia to enhance recovery in the context of SCI. In contrast, the microglial phagocytic receptor Trem2 contributes to neuroinflammation and neuronal death. Finally, the authors suggest replacing reactive microglia with innate microglia as a potential therapeutic approach to treat SCI in humans.
Strengths:
The work utilizes numerous and multi-modal datasets describing transcriptomic changes in the mouse CNS following SCI.
The topic is translationally relevant.
Weaknesses:
There is not enough information about how each of the datasets re-analyzed by the authors was obtained and processed both by the group generating the data and by the group re-analyzing it.
The conclusions drawn by the authors are not sufficiently supported by the evidence.
Whether the study represents a significant conceptual advance in our understanding of microglial contributions to SCI is not clear.
My specific concerns and suggestions to address these weaknesses are provided below.
Major comments:
(1) Questions remain about the nature, quality, and features of the datasets re-analyzed in the study. For example, how were these datasets obtained? Were the same animal models and time points used in each? What modality of RNA sequencing was done? What criteria did the authors consider in deciding which datasets to include in the study? Since the study is entirely reliant on data generated elsewhere, a more thorough description of these datasets within the text is needed.
(2) Relatedly, the authors chose to filter out some cells from the datasets based on quality, but this information is incomplete. For example, the authors omit cells with 10% mitochondrial genes, but this value is higher than most investigators use (typically between 1%-5%). Why is 10% the appropriate limit in this particular study? Further, how did the authors ensure the removal of doublets from the dataset?
(3) A principal finding of the paper is that microglia in the uninjured CNS mostly have an 'innate' transcriptomic phenotype, while microglia in the injured CNS mostly have a 'reactive' phenotype. However, there are some issues here that require further discussion. First, while historically microglia were thought to possess distinct 'homeostatic' versus 'activated' profiles which would be consistent with the authors' interpretations here, these differences are now thought of more as changes in a given microglial cell's transcriptomic status. Thus, while the authors interpret their results as meaning that innate microglia are depleted and replaced by a different set of reactive microglia following SCI (or at least this is how the paper is written), it is equally if not more likely that the microglia within the injured regions themselves become more reactive as a result of the insult. The authors should clarify why their interpretation is more likely to be correct.
(4) Related to the above point, the authors base the manuscript on the idea that microglia are mostly 'innate' in the uninjured CNS and 'reactive' after injury, however, the UMAP plots in Figures 1A and 1C suggest that both classes of microglia cluster together and may not actually represent distinct subclasses. Have the authors tried sub-clustering just the myeloid clusters and seeing how well they separate? Even if they do technically represent distinct clusters, the UMAP could be interpreted to mean that their transcriptomic differences are not particularly robust.
(5) I appreciate the authors' use of loss-of-function data to explore the roles of microglial TGF and Trem2 signaling to glean some mechanistic insights into SCI. However, many of the conclusions reached by the authors in the manuscript are insufficiently supported by the data and would require additional experiments to rigorously confirm. A couple of examples are the following:
5a. Lines 160-162: "Hence, we conclude that the cascade of injury events in SCI significantly influences microglia, leading to the replacement of innate microglial cells by reactive microglia." That SCI influences microglia is well-supported by the study, but whether reactive microglia replace innate microglia, versus whether innate microglia in the region transition to a reactive state, needs to be tested experimentally.
5b. Lines 321-323: "Taken together, iPSC-derived microglia have the potential to replace the functions of naïve microglial cells, and they perform even more effectively in the in vivo CNS." Again, the first part of the sentence is supported, but whether iPSCs are more effective than other populations in vivo would need to be tested experimentally.(6) As microglia have long been appreciated as contributors to the CNS injury response, the conceptual advance here isn't particularly clear to me. For example, Gao et al, 2023 (*cited by the authors) describe the role of Trem2+ microglia in SCI versus demyelinating disease with major conceptual overlap with the current study. It would be helpful for the authors to include a discussion of what we now know about SCI based on this study that we did not know (or strongly suspect) before.
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