The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ-dependent but monocyte-independent process
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Abstract
Synovial joints harbor a protective lining layer, consisting of fibroblasts and macrophages, which form an epithelial-like barrier. In inflamed joints, lining macrophages regulate both early inflammatory cell influx and resolution. Despite these critical functions, it is currently unknown at what stage during development the synovial macrophage lining is established, and which signals drive this process. Here, we use a combination of genetic models and in vivo perturbations, single cell transcriptomics and imaging to delineate the process of lining formation in mice. We find that the synovial lining is immature at birth and becomes established within the first 3 weeks of life. In this window, the lining is gradually populated with macrophages that originate from fetal sources, proliferate and acquire the lining-specific transcriptional identity. In contrast, monocytes contribute only minimally to the developing lining, and their input remains limited in healthy adulthood. We identify CSF1 and TGFβ as key signals in this process, which also involves mechanosensing through PIEZO1. Our study thus identifies the early postnatal window as a critical period for lining macrophage development, with potential lifelong impact on joint health and disease.
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Reply to the reviewers
Proposed revision plan
Based on the below reviews, we propose the following revision plan. Briefly:
- We will remove the functional data on TGFβ signaling and mechanical loading/mechanosensing. We agree with the reviewers that we would need to generate additional histological and molecular data from conditional knockout mice, antibody and (ant)agonist treatments and the optogenetic model to determine their exact involvement in lining macrophage maturation. These experiments require significant time and other resources.
- We would therefore like to uncouple this question for a follow-on manuscript.We will re-focus the manuscript on the developmental data …
Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.
Learn more at Review Commons
Reply to the reviewers
Proposed revision plan
Based on the below reviews, we propose the following revision plan. Briefly:
- We will remove the functional data on TGFβ signaling and mechanical loading/mechanosensing. We agree with the reviewers that we would need to generate additional histological and molecular data from conditional knockout mice, antibody and (ant)agonist treatments and the optogenetic model to determine their exact involvement in lining macrophage maturation. These experiments require significant time and other resources.
- We would therefore like to uncouple this question for a follow-on manuscript.We will re-focus the manuscript on the developmental data providing a molecular and cellular blueprint of lining macrophage development. This will include our data on CSF1 as a key signal. The novelty and relevance of our developmental data have been highlighted by all three reviewers, and they have also praised the rigor of these experiments and their interpretation. We thus believe that this re-focus will improve the manuscript message.
- To further enhance this, we are proposing to include additional data delineating the developmental dynamics of synovial fibroblasts. We have generated an in-depth single cell RNAsequencing dataset but did not include fibroblast-specific analyses in the original manuscript. This is not a change proposed by the reviewers, but we are proposing this because we believe this would be an impactful addition to a revised version of our study, providing data also on the maturation of the synovial (lining) macrophage niche.
- We will otherwise respond to all individual reviewer comments and implement the requested changes, unless technically not possible. Please find below detailed point-by-point answers.
Reviewer #1
Evidence, reproducibility and clarity
In their manuscript entitled "The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ-dependent but monocyte-independent process," the authors explore the developmental trajectory of synovial lining macrophages. They demonstrate that the formation of this specialized macrophage layer is age-dependent and governed by a distinct developmental program that proceeds independently of circulating monocytes. Through scRNA-Seq, the authors show that synovial lining macrophages originate locally from Aqp1⁺ macrophages and are marked by the expression of Csf1r, Tgfbr, and Piezo1. Notably, genetic ablation of each of these factors impaired the development of lining macrophages to varying degrees, suggesting differential contributions of CSF1, TGFβ, and PIEZO1 signaling pathways to their maturation and maintenance.
The manuscript is well written, and the data quality and representation is of a high standard. The authors have employed a sophisticated array of state-of-the-art mouse models and cutting-edge technologies to elucidate the developmental origin of synovial lining macrophages. Notably, the supporting scRNA-Seq datasets are of excellence and provide valuable insights that will likely be of significant interest to researchers in the field of immunology and joint biology. Accordingly, the experimental approach and interpretations regarding macrophage origin are well-founded and compelling. However, in the eye of the reviewer, the section addressing the underlying molecular mechanisms is a bit less convincing. This part of the study appears slightly underdeveloped, and some of the mechanistic claims lack sufficient experimental clarity. A more rigorous experimental investigation would be essential to reinforce the manuscript's conclusions, particularly concerning the data related to Tgfbr and Piezo1, where the current evidence appears insufficiently substantiated.
We thank the reviewer for their positive and constructive evaluation of our manuscript. We agree with them (and the other reviewers) that our functional data on the involvement of TGFβ signaling and mechanical loading/mechanosensing are comparably less convincing and substantiated than our developmental data. We are very grateful for their (and the other reviewers’) suggestions to provide more support for the involvement of these factors in lining macrophage development. However, we think that carrying this out to the same high standard will require substantial time and other resources. We have therefore decided to uncouple this from the developmental data and pursue this in follow-up work. We will re-focus the current manuscript on the developmental data. We have proposed to the editors to instead include additional data on synovial fibroblast development, to complement our macrophage data and also delineate the maturation of their niche, thereby providing a conclusive developmental atlas.
Major point:
The numbers of VSIG4⁺ macrophages appear either unaffected or only minimally altered in both Csf1rMerCreMer Tgfbr2floxed and Fcgr1Cre Piezo1floxed mouse models, respectively. This raises an important question: was the gene deletion efficiency sufficient in each model? Accordingly, the authors are encouraged to include quantitative data on gene deletion efficiency for both mouse models, as this information is critical for interpreting the observed phenotypic outcomes and validating the conclusions regarding gene function. Furthermore, to better assess the impact of Tgfbr2 and Piezo1 disruption, the authors should provide more comprehensive flow cytometry analyses and histological data for these mouse models. Given the apparent homogeneity of VSIG4⁺ macrophages (as shown by the authors themselves), bulk RNA-Seq of sorted Tgfbr2- and Piezo1-deficient VSIG4⁺ macrophages (or from TGFβ-treated animals) would offer valuable insights into both the effectiveness of gene deletion and the molecular pathways governed by TGFβ and PIEZO1 in lining macrophages.
As outlined above, we have decided to uncouple our functional data on TGFβ, Piezo1 and mechanical loading. The points raised here are all very valid, and we will implement your suggestions in our follow-up functional work focusing on signaling events regulating lining macrophage development. On the suggestion to perform bulk RNA sequencing for VSIG4+ macrophages: This is a good one in principle – although we will not be able to use this strategy where we want to assess the consequences of experimental treatments or genetic models on lining macrophage maturation, because acquisition of VSIG4 is a key maturation event that might be impaired in these conditions.
Minor points:
Consistent usage of Cx3cr1-GFP+ nomenclature (for instance: Fig. S1 legend "adult mouse synovial tissue, showing PDGFRα⁺ fibroblasts (yellow) and CX3CR1-GFP⁺ cells (cyan)." versus Fig. 1 legend "Automated spot detection highlights Cx3cr1-GFP⁺ macrophages)".
We will implement these changes.
Unclear Fig. 3 legend: "Representative immunofluorescence images of synovial tissue from Clec9aCre:Rosa26lsl-tdT mice at 3 weeks and in adulthood, showing and tdTomato (yellow) and stained for DAPI (blue), VSIG4 (cyan)" Check 'showing and tdTomato.'
We will implement these changes.
For greater clarity, it would have been helpful if the transcript names had been directly included within Figures 3C, S3A, and S3C.
We will implement these changes.
Page 24: "(Mki67CreERT2:Rosa26lsl-tdT)" Last bracket not superscript.
We will implement these changes.
Page 25: "we again leveraged our scRNAsequencing dataset" Missing punctuation.
We will implement these changes.
Page 27: Fig. 5C legend: " of synovial tissue of 1 week-old, 3 weeks-old and adult mice." Please specify and change to 'adult Csf1rΔFIRE/ΔFIRE mice'.
We will implement these changes.
Page 30: The outcome observed in the Acta1-rtTA:tetO-Cre:ChR2-V5fl mouse model appears to be inconclusive: "This approach resulted in an increased density of VSIG4+ and total (F4/80+) macrophages in the exposed leg of some 5 days-old pups, but others showed the opposite trend (Figure S5D)." This variability may reflect low efficiency of the model or other technical limitations (e.g. muscle contractions frequency or time point of analysis). Given this ambiguity, it is worth reconsidering whether the data are sufficiently robust to warrant inclusion. Should the authors choose to include these findings, further experimentation of appropriate depth and precision is required to allow a conclusive interpretation (either it increases the density of VSIG4+ macrophages or not). The same applies to the Yoda1-treated mice, for which additional data are needed to determine whether VSIG4⁺ macrophage density is truly affected.
We have decided to remove the data on the optogenetic mouse model and Yoda1 treatment and follow-on separately, implementing these suggestions, including proof of concept data for optogenetically induced muscle contractions.
Significance
General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed? This is a well-designed study that uses cutting-edge methodologies to investigate the developmental trajectory of synovial lining macrophages under homeostatic conditions. The authors present robust experimental evidence and compelling interpretations concerning synovial macrophage origin, which are both well-substantiated and impactful. Nonetheless, from the reviewer's perspective, the section exploring the molecular mechanisms underlying macrophage differentiation is comparatively less convincing. This section appears somewhat underdeveloped, as some of the mechanistic claims lack sufficient depth and experimental rigor to fully substantiate the conclusions.
Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field: In contrast to earlier studies (PMID: 31391580, 32601335), the inclusion of fate-mapping experiments adds an important dimension, offering novel insight into the ontogeny of synovial macrophages. This expanded perspective may prove particularly valuable in advancing our understanding of joint immunology, especially regarding the local origins and lineage relationships of macrophage populations.
Furthermore, the authors present novel insights into the molecular pathways underlying the differentiation and development of synovial lining macrophages. By demonstrating previously unrecognized regulatory mechanisms, this work significantly deepens our understanding of the cellular and transcriptional programs that drive macrophage specialization within the joint microenvironment.
Place the work in the context of the existing literature (provide references, where appropriate): This study builds upon previous work characterizing the macrophage compartment in the joint (PMID: 31391580, 32601335), yet provides a substantially more comprehensive dataset that spans multiple developmental time points and data on the origin of this specialized macrophage subset.
State what audience might be interested in and influenced by the reported findings: Immunologist, clinicians
Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. This study falls well within the scope of the reviewer's expertise in innate immunity.
Reviewer #2
Evidence, reproducibility and clarity
In the manuscript „The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ- dependent but monocyte-independent process", Magalhaes Pinto and colleagues carefully employ a wide range of technologies including single cell profiling, imaging and an exceptional combination of fate mapping models to characterize the ontogeny and development of lining macrophages in the joint, thus dissecting their maturation during postnatal development. Over the last decade, several landmark studies highlighted the imprinting of tissue-resident macrophages by a combination of ontogenetic and tissue-specific niche factors during development. So far, the ontogeny and the tissue niche factors governing the development and maturation of lining macrophages have not been described. Therefore, the results of this study offers insights on a small highly adapted macrophage population with relevance in many disease settings in the joint. Furthermore, the findings are nicely showcasing how macrophages are specializing to even very small tissue niches across development within one bigger anatomical compartment to serve dedicated functions within this niche.
This manuscript is beautifully written and highlights many novel, highly relevant findings on lining macrophage biology and the authors employ a wide range of different technologies to carefully dissect the postnatal development of lining macrophages.
In particular, the combination of scRNA-seq and fate mapping is providing a unique the link of transcriptional programs to ontogeny within the tissue niche. Furthermore, the integrative use of distinct fate mapping strategies, transgenic mouse lines, and treatment paradigms to elucidate key niche factors guiding the development and maturation of lining macrophages provides many interesting findings and data that are highly relevant to the field. I really enjoyed reading this manuscript.
Thank you for your complimentary and constructive assessment of our manuscript, and the detailed comments below, which are very helpful. Please find point-by-point responses below.
Major points:
The authors show dynamic regulation of VSIG4 in lining macrophages during development, therefore VSIG4 is maybe not an ideal choice for gating strategies to define lining macrophages or to show as a single markers in immunofluorescence (IF) stainings to demonstrate their abundance across development (even though it is clear that this is the reason why the F4/80 staining is shown next to it). To demonstrate the increase of lining macrophages during development in IF, it would be more helpful if the authors would show quantifications of all F4/80+ cells and additionally VSIG4+ as a proportion of F4/80+ cells (or VSIG4+ F4/80+ and all F4/80+ in a stacked bar plot). We agree with the assessment of VSIG4 not being ideal since this is a key marker of mature lining macrophages only.
We will provide these additional analyses.
In Figure 1C, the authors nicely demonstrate that the lining macrophages get closer in their distance across development to build the epithelial-like macrophage structure along the adult lining. Is the close proximity between lining macrophages already fully "matured" at 3 weeks of age and comparable to adults? Please quantify the distance in adult linings.
We will provide data for adult joints.
Can the authors explain how the grouping was performed between the analyzed human fetal joints? It is not clear why the cut was chosen between the groups at 16/17 weeks of age. Maybe it would be also beneficial if the authors would consider not grouping these samples but rather show the specific quantifications for each samples individually and estimate via linear regression the expansion over time across human development. Furthermore, can the authors give additional information about the distancing of lining macrophages in the human fetal samples, it would be great to see if they follow the same dynamics as in mouse. Maybe comparison to human juvenile/adult joints would also add on to substantiate the findings in human samples (if possible).
We will show samples ungrouped and perform linear regression analysis as suggested.
The scRNA-seq analysis leaves several questions open and some conclusions and workflows cannot be easily followed.
We appreciate this comment and the complexity of the data, and will implement the below recommendations, and clarify the issues raised.
It is not clear how and especially why the signature genes to define macrophages vs. monocytes were chosen. Especially as the signature genes for monocytes would not include patrolling monocytes and the macrophage signature genes seem to be highly regulated during development, see also Apoe expression in NB vs. adult in Figure S2e. Why did the authors not take classical markers such as Itgam, Fcgr1a, Csf1r?
Can dendritic cell signatures be excluded? Cluster 11 and 12 show indeed some DC markers, are these really macrophages?
The authors provide several figure panels showing TOP marker genes or key marker genes for the identified clusters, however it is not clear if these are TOP DE genes or if the genes were hand chosen. Somehow, the authors give the impression that the clusters were chosen and labeled not based on DE genes, but more on existing literature that previously reported these macrophage populations. DE gene lists for all annotated cell types and macrophage clusters need to be provided within the manuscript.
The authors claim that Clusters 1 and 4 are "developing" macrophages. How is this defined? Why are these developing cells compared to other clusters? And why are these clusters later on not considered as progenitors of Aqp1 macrophages and Vsig4 macrophages? Why are Aqp1+ macrophages not labeled as developing when they are later on in the manuscript shown as potential intermediate progenitors of lining macrophages?
Furthermore, it is again confusing that markers are used throughout Figure 2 which are labeled as "key marker genes" for a population and then later on they are claimed to be regulated during development within this population, see for example Figure 2D and 2H.
It is appreciated that the authors distinguished cycling clusters such as 8, 9, and 10 based on their cycling gene signature. Here it would be very exciting to see a cell cycle analysis across all clusters and time points to see when exactly the cells are expanding during development; this would also substantiate the data later shown for the Mki67-CreERT2 mouse model.
Can the authors identify certain gene modules during development of lining macrophages (and/or their progenitors) which are associated with certain functions (e.g. GO terms, GSEA enrichment)?
To determine the actual presence of the identified macrophage clusters from the scRNA-seq as macrophage populations in the joint, the authors should perform IF or FACS for key markers. Especially, Aqp1+ macrophages should be shown in the developing joint.
We will provide additional data, but would also like to reference a study by collaborators currently in revision at Immunity, which characterizes the Aqp1+ population in detail. We are hoping to have a doi available during our revision process.
The authors used a wide range of fate mapping models, which is quite unique and highly appreciated. The obtained results and the conclusions made from the models raise a couple of questions: Whereas contribution of HSC-derived/monocyte-derived macrophages to the lining compartment seems to be minor, there is still labeling across different models. Various aspects would need to be clarified.
We will clarify these data throughout as per below suggestions.
For example, the authors employ Ms4a3-Cre as a tracing model for GMP-derived monocytes, however all quantifications of the labeling efficiency are not normalized to the labeling in monocytes or another highly recombined cell population. This should be shown, similar to the other fate mapping models (Figure 3 F-I).
Labelling efficacy for Ms4a3-Cre is near complete for GMP-derived monocytes (and neutrophils) with the Rosa-lsl-tdT (aka Ai14) reporter we have used (see also PMID: 31491389 and doi: 10.1101/2024.12.03.626330); but we will include normalized data as requested.
Please show Ms4a3 expression across clusters across time points, to exclude expression in fetal-derived clusters.
We will include this in the revised supplementary information, but there is indeed very little at birth (in line with the original report for other tissues PMID: 31491389).
In line with the question raised above, if the authors can exclude a development of the Egfr1+ and Clec4n+ developing macrophages into Aqp1+ macrophages and subsequently into Vsig4 lining macrophages, the obtained data from the Ms4a3-Cre model highly suggests a correlative labeling across these clusters what could implicate a relation. However, the authors do not discuss throughout the manuscript the role of these developing macrophages. It is highly encouraged to include this into the manuscript and it would be of high relevance to understand lining macrophage development.
This is an interesting point and we agree it deserves consideration in the revised manuscript. Indeed, our trajectory analyses do not predict differentiation of the Egfr1+ and Clec4n+ developing macrophages into Aqp1+ macrophages, and hence, ultimately lining macrophages. Conversely, Aqp1+ cells might also convert into Egfr1+ and Clec4n+ developing macrophages. We will elaborate on this more in the revised manuscript.
The authors conclude from the pseudo bulk transcriptomic profiling of the different macrophage clusters that TdT+ and TdT- macrophages do not differ in their gene expression profile and that this is due to niche imprinting rather than origin imprinting. Even though the data supports that conclusion, the authors should verify if inkling cells early during development also show this similar gene expression profile and gene expression should be compared at the different developmental time points. Tissue niche imprinting is happening within the niche during development, most likely in a stepwise progress, and therefore there should be differences in the beginning.
This is another important point that we will address in the revised manuscript by performing additional differential gene expression analyses at the different developmental time points, including the earliest stages, as suggested.
The trajectorial analysis using different pseudotime pipelines is very interesting and nicely points out the potential role of Aqp1 macrophages as intermediates of Vsig4 lining macrophages. From my point of view, all trajectories seem to suggest that Egfr1 developing macrophages and Clec4n developing macrophages might differentiate into Aqp1 macrophages, however the authors are not exploring this further and the role of both developing macrophage clusters is not further discussed (see also comments above).
We will address and discuss this in the revised manuscript.
How was the starting point of the trajectorial analyses defined and is it the same for each pipeline used?
We will clarify this in the revised manuscript.
Are there potentially two trajectories? It looks like there is one in the beginning of postnatal life and a second one appearing from the monocyte-compartment later in life. If this is true, that would rather speak for a dual ontogeny of Vsig4+ macrophages, wouldn't it?
We will discuss this in the revised manuscript.
A heatmap (transcriptional shift) of trajectories between more clusters should be shown at least for Cluster 0,1,2, and 3. It is not sufficient to demonstrate this only between two clusters.
We will add these analyses during revision.
To show the similarity between Aqp1 macrophages and proliferating macrophage clusters, the authors should remove the cycling signature and compare these clusters to show that the cycling cells might be Aqp1 macrophages or earlier developing macrophage progenitors aka Clec4n or Egfr1 macrophages.
We will address this in the revised manuscript.
The conclusions made from the Mki67-CreERT2 data are a bit difficult to understand, whereas all progenitors (monocyte progenitors and macrophage progenitors will proliferate at the neonatal time point and no conclusions can be made if the cells expand in the niche. The authors should employ Confetti mice or other models (Ubow mice) to analyze clonal expansion in the niche.
We agree that interpretation of the Mki67-CreERT2 data is complicated by labeling of other cells, and notably, labeling observed in BM-derived cells. We will highlight this better in the revised manuscript. We have tried using Ubow mice to address this issue, but the recombination efficacy we yielded was too low to draw conclusions. We will address this during revision.
All predicted cell-cell interactions between macrophages and fibroblasts should be provided in a supplementary table. Are the interactions shown in Figure 5 chosen interactions or the TOP predicted ones? Whereas the authors show different numbers of interactions, it is most likely hand-picked and therefore biased.
We will provide a full list of all predicted interactions in the revised supplementary material in addition to a list of the full differential gene expression analysis.
The authors further aim to dissect the factors involved in the developmental niche imprinting of lining macrophages. Even though it is highly appreciated that the authors used so many experimental setups to show the reliance of lining macrophages on Csf1 and TGF-beta as well as mechanosensation, the wide range of models the different methods used and selected developmental time points make it very difficult to really interpret the data. The authors should carefully choose time points and methods (either FACS analysis across all models or IF across all, or both). Often deletion efficiencies for transgenic models and proof of concept that the inhibitors and agonists are working in the treatment paradigm are not provided. For example, Csf1rMer-iCre-Mer Tgfbr2fl/fl mice are used but no deletion efficiency is shown or different time points of analysis, maybe the macrophages are not properly targeted in the set up.
We have decided to uncouple our experimental data on Tgfb, Piezo1 and mechanosensing/mechanical loading, but are taking this into consideration for revision. In many cases, we have in fact performed flow cytometry and imaging analyses, and agree, we should be showing this consistently.
The authors have shown the role of Csf1 and Tgfbr2 only for lining macrophages, is this specific in the joint to this population of are subliming macrophages affected in a similar manner.
We will include data on sublining macrophages in the revised figure (for CSF1; Tgfb data will be uncoupled from this current manuscript).
Can the authors confirm their results in CSF1R-FIRE mice with anti-Csf1 injections or in Csf1op/op mice?
We will expand our discussion of the Csf1 findings, and will consider including anti-CSF1 data during revision. Phenotypes on other Csf1(r) deficient mice are published, if not with the same developmental resolution as our time course in Csf1rFIRE knockout mice and with simpler readouts. Csf1op/op mice are indeed deficient in synovial lining macrophages, from 2 days of age onwards (PMID: 8050349), and lining macrophages are also absent from 2-weeks-old and adult Csf1r-/- mice (PMID: 11756160).
The setup in Figure S5G is very interesting to test the role of movement and mechanical load on the joint, however, there is basically no data on the model provided showing the efficiency of the induced optogenetic muscle contractions, and only one time point is shown.
Data on mechanical loading will be uncoupled from the current manuscript and substantiated in a separate follow-up.
The results regarding the role of Piezo1 and mechanosensation vary a lot. Could it be that analyses were done too early or that actually proper weight load on the joint must be applied for the maturation of the macrophages? The authors should test this to.
We will uncouple these data from the current manuscript during revision. However, this is a possibility that we have discussed. In fact, the most appropriate experimental approach to address the involvement of mechanical loading, onset of walking and specifically, weight bearing would be a loss-of-function approach (i.e. paralysis at the newborn stage), for which we unfortunately could not obtain ethics approval from the UK Home Office.
The Rolipram experiment is shown in Figure S5G, but is not described in the result section. It only appears at some point in the discussion part. The authors should move it to results or remove it from the manuscript.
We will incorporate these data with the revised section on developing synovial macrophage populations.
Minor points:
Please reference the Figure panels in numeric order throughout the text.
We will change this where not the case.
Figure 2a and 2b are a bit out of the storyline, it is not obvious why this is shown here and maybe it would be good to move it to the supplements. Gating strategy is also not used for scRNA-seq. Therefore, it would better fit to the later analysis of joint macrophages across different transgenic mouse models and treatment paradigms. The gating strategies are changing across different experiments throughout the figures, it would be nice to have a similar gating strategy for all experiments, see also Figure 3 where the defining markers for joint macrophages are changing between models.
We will revise Figures 2, 3 and the related supplementary figures.
A lot of figure panels have very small labeling that is basically unreadable. Axes at FACS plots for example. Sometimes, it is even impossible to distinguish cluster labels especially when they have similar colors.
We will revise this, thanks for pointing it out.
In the text on page 14, many markers are named which are specifically regulated during development in lining macrophages, but these factors are not labeled anywhere in the volcano plot. It would be good to showcase at least some of these named genes in the figure panel, e.g. Trem2.
We will do this for revision.
Figure 2F and Figure S2F are really nicely showing the percentage of cells per cluster in each analyzed biological sample. Maybe the authors could additionally consider to show a stacked bar plot with the mean percentage of cells per cluster and how the clusters are distributed across time points?
We will include this in the revised manuscript.
Figure 3A: IF for adult lining macrophages and the quantification are missing.
This will be included in the revised version.
Significance
This manuscript highlights novel, highly relevant findings on lining macrophage biology and the authors employ a wide range of different technologies to carefully dissect the postnatal development of lining macrophages. Furthermore, this study showcases in a very elegant and detailed way the adaptation of macrophage progenitors to a highly specific anatomical tissue niche.
The manuscript is of high interest to basic scientists focussing on macrophage biology and immune cell development and clinicians and clinician scientists focussing on joint diseases such as RA.
Therefore the manuscript is of interest to a wide community working in immunology.
Reviewer #3
Summary:
Magalhaes Pinto, Malengier-Devlies, and co-authors investigated the developmental origins and maturation of synovial (lining and sublining) macrophages across embryonic, newborn, and postnatal stages in mouse. The authors used multiple transgenic reporter lines, lineage tracing, scRNA-seq, 2D confocal and 3D lightsheet imaging, and perturbations to delineate the macrophage states and ontogeny. They propose a model in which the majority of the joint lining macrophages has a fetal (EMP-derived) origin and a small proportion has a definitive HSC-derived monocyte origin, which both seed and mature within the synovial space in the postnatal period in the first 3 weeks of life. Using cell-cell communication analysis on their scRNA-seq data, they identified Fgf2, Csf1, and Tgfb as candidate signaling pathways that support (lining) macrophage development and maturation. Functional experiments indicate that the process is CSF1 and TGFb-dependent and also partly dependent on mechanosensing through Piezo1.
The key conclusions on the composition of the synovial macrophages are convincing based on the presented results, and are carefully phrased. The study is very comprehensive, yet the description and organization of the results of the different mouse models could be altered to improve the storyline. Several refinements in data presentation, formulation, and minor validation experiments would further improve the clarity of the story, as well as summary recaps of the major findings throughout the text.
We thank this reviewer for their detailed review. We will be implementing the requested changes wherever technically feasible.
Major comments:
Generally, the story could be more streamlined by introducing earlier reporter lines and lineage-origin logic. Clearly state which reporter/CreERT2 lines and acrosses are used. It was unclear in Figure 2 that cells of the cross of the Cx3cr1-GFP and Ms4a3Cre:Rosa26lsl-tdT reporter lines were used for the scRNA-seq. The principle that there are fetal-derived and bone marrow (GMP)-derived monocytes and macrophages doesn't need to be "hidden" until Figure 3. For example, also the imaging of Ms4a3Cre could be introduced before the scRNA-seq.
We will revise the structure and order of the manuscript during revision.
Figure 1 could benefit from a cartoon visualizing the anatomy of the knee joint. The terms "sublining" and "synovium" are now a bit unclear, as it appears that sometimes the synovium is indicated as sublining and vice versa. Additionally, a schematic developmental timeline could be added to indicate the parallels between mouse and human development (fetal and postnatal development in mouse versus gestational age in human). Also, the various waves of hematopoiesis could be indicated in this timeline, which would be particularly helpful for Figure 3 for the lineage-tracing readouts. Lastly, the authors could end the manuscript (a new Figure 6) with a general cartoon summarizing all the results presented.
We will include illustrations as suggested.
Figure 1 could be rearranged: first introduce the markers CX3CR1 and VSIG4 (Figure 1D) and then present the quantifications (Figure 1B/E). Where possible, co-visualization CX3CR1-GFP and VSIG4 on tissue sections to strengthen the claims on the relationship between these 2 markers. Tying the scRNA-seq insights (Figure 2) to the imaging would be elegant. Moreover, it would be informative to represent the CX3CR1+ and VSIG4+ macrophages as a percentage of F4/80+ macrophages (Figure 1B/E). Similarly, for the flow cytometry data in Figure 2, the relationship between the markers CX3CR1 and VSIG4 on macrophages could be more clearly displayed and discussed.
Thanks for this remark. We will endeavor to show co-localization and analysis of both markers wherever possible. However, where we did not use Cx3cr1gfp mice, co-staining was limited by antibody choice.
The 3D imaging of the joint is a nice addition to the manuscript, as it provides more context to the anatomical structure; however, while the text suggests several newborn joints were imaged, Figure 1F visualizes (again) the knee joint. Could other joints also be represented by 3D imaging? If the knee joint is the only joint available for imaging, and previous confocal imaging focused specifically on the meniscus in the knee joint, could the meniscus also be highlighted in the lightsheet imaging?
Apologies if this was not clear from the original manuscript text, but we have only imaged the knee joint in 3D. We will clarify this during revision and consider inclusion of additional imaging data.
Clarification is requested regarding the imaging quantification representation. The M&M section under "Statistical analysis and reproducibility" states that individual data points are displayed, and bars represent the mean. However, some of the Figure legends (e.g., Figures 1B and S1C) specify that each dot corresponds to an individual mouse, with quantification based on 2-3 sections per mouse. While this appears to be a very reasonable representation of the data, does this mean that for each dot, the mean value from the 2-3 sections per mouse was calculated and plotted?
We will clarify this.
It is not clear how the differential expression analysis was performed on the Vsig4+ cells. Please specify if Cluster 0 was used for analysis, or all Vsig4-expressing cells? Not all cells in Cluster 0 have Vsig4+ expression. The authors described the expression dynamics of Aqp1 as intriguing, but lack a reasoning on why this is interesting.
We will revise this section.
Figure S3E: In line with the previous comment, can the authors justify that the tdTomato+/- comparisons are not biased by scRNA-seq dropout (scRNA-seq is zero-inflated, so some tdTomato- cells could be false negatives), and provide methodological details (thresholds, ambient RNA correction, etc.) to support this?
We will clarify this and include additional representations of the tdTomato transcript data.
Although the sex-related differences in macrophage composition and the absence of differential expression are interesting, they distract from the manuscript's main messages. Moreover, the Discussion does not elaborate on how these observations relate to joint (disease) biology. Consider removing this section or integrating it clearly into the relevant biological context.
We will remove this section as suggested.
CreERT2 transgenic lines are often not 100% efficient in recombination, also depending on whether tamoxifen or 4-OHT is used. Could the authors report the percentage of tdTomato+ cells in the joints and compare them to the recombination efficiencies in the monocytes/microglia under the same tamoxifen or 4-OHT conditions? This would help clarify how the interpret the macrophage labeling %'s.
We will report labelling efficacies and/or show normalized data in the revised manuscript.
Could the authors draw parallels between the observations in the mouse knee joint macrophage populations and literature on other joints in mouse and the knee joint in human (for example, as described in Alivernini et al., 2020 and in the very recent Raut et al., 2025)?
We will include a section on this in the revised manuscript.
Minor comments:
In general, the authors should clarify in the Results what each marker used for imaging, flow cytometry, or in the mouse reporter lines delineates. For example, mention that F4/80 is a marker for tissue-resident macrophages (correct?) in immunofluorescence, that IBA1 is a marker for macrophages on human tissue sections (Figure S1), and PDPN is GP38 (Figure S2 - align usage of marker reference across main text and figures).
We will implement this request.
For clarity in the microscopy representation, the single channels should be represented in a grey scale.
We will revise image presentation.
Figure S1B: Is CX3CR1 also restricted to the lining macrophages in human? Could a co-staining with IBA1 be performed to strengthen the species similarities?
To our knowledge, there is no antibody available that works for imaging of human CX3CR1. Moreover, CX3CR1 is only limited to the lining population in adult joints, in fetal and newborn (mouse) joints, all macrophages express this receptor, as do fetal progenitors to macrophages. However, Alivernini and colleagues have reported that TREM2high macrophages are the human counterpart of the mouse CX3CR1+ lining population (PMID: 32601335).
Adipocyte diameter quantification: Avoid plotting individual adipocytes from 2 mice without per-mouse visualization. Instead, report the mean adipocyte diameter per mouse and plot those means.
We will implement this change.
A little typo was spotted in the "Statistical analysis and reproducibility" section: it is Dunn's, not Bunn's multiple-comparison correction.
Thanks for spotting this.
Figure 2A: The gating strategy for the CX3CR1-GFP cells is missing.
We will provide this in the revised manuscript or supplementary material.
Improve the visualization of some plots. For example, Figure 2F is hard to read because of the big dot size. The dots seem to add no information to the graph and could be removed. Additionally, for comparing the clusters across the different time points, one could project the cells from the other time points in grey in the background.
We will revise the presentation of these data.
Figure S2: The dotplot is more informative than the heatmap, consider removing the heatmap.
We will do that.
Figure 3A: If technically feasible, image and visualize both the GFP and tdTomato expression. It would be informative to see the Cx3cr1+ and Ms4a3-derived cells in the same specimen.
We will thrive to show this in the revised manuscript.
Figure 3C: Highlight that tdTomato expression is visualized here.
We will do that.
Figure 3G,F: The authors should place the schematics and graphs next to each other, so the data points can be more easily compared.
We aim to do this in the revised manuscript.
Figure 4B: Which co-staining was performed for the immunofluorescence to quantify the % of tdTomato+ cells?
We co-stained for F4/80 and assessed localization in the lining or sublining. This will be clarified in the revised Figure legend.
Figure 4C: The trajectory analysis appears to have an arrow pointing from the Ccr2+ macrophages to the Ly6c+ monocytes. Please verify this directionality, as its seems against the known biology.
This will be addressed during revision.
Figure 5 mentions that the Csfr1 levels were reduced in a tissue-specific manner, but it is unclear how this tissue specificity was achieved.
We apologize for this misunderstanding. Csfr1FIRE mice are not tissue-specific knockouts, but they are more specific than global knockout mice, since only a (myeloid-specific) enhancer is affected. We will clarify this in the relevant section.
For the TGFb perturbations (Tgfbr2 KO and systemic TGFb depletion): did the authors validate reduced TGFb pathway activity in the macrophages, for example, reduced pSMAD2/3 levels? This would validate the effectiveness of the perturbations. This is an important point, and assessing signaling events downstream of TGFb is a very good suggestion.
As per above comment, we have decided to uncouple the functional data with exception of CSF1 from the revised version of the current manuscript, but we will be taking this into account for substantiating our functional data in follow-up work.
Figure 5F could benefit from a timeline of the treatment.
As for the previous point raised, we will be taking this into account for follow-up work on the uncoupled functional data.
The Methods mention that Gene Ontology analysis was performed on the single-cell data, but the results are not plotted in a figure. It would be informative to include this GO/pathway analysis in the appropriate figure(s).
We will include this in the revised (supplementary) information.
Significance:
This work provides a high temporal-resolution and "spatial" resolution reference map of the ontogeny and maturation of the synovial lining macrophages in the knee joint. It complements existing literature that demonstrated the presence of tissue-resident macrophages in the synovial space and lining (Culemann, et al., 2019 and others) by charting the embryonic-to-postnatal emergence of lining and sublining subsets. In particular, this mouse work identified some key signaling pathways in shaping this tissue compartment. This dataset serves as a robust, steady-state reference for joint pathology and can be implemented with human studies on disease biology of the knee joint (e.g., Alivernini et al., 2020; Raut et al., 2025). Insights into the exact developmental origins, mechanisms contributing to diverse or seemingly similar cell types, and distinct maturation processes are crucial to understanding disease biology, in which developmental processes can be hijacked/reactivated.
These findings will interest researchers in joint disease biology (osteoarthritis and immune-mediated arthritides such as RA and psoriasis), macrophage development (tissue-resident vs monocyte-derived lineages), the bone/joint microenvironment, and joint mechanobiology.
The reviewer's expertise is in developmental biology, mesoderm, bone biology, hematopoiesis, and monocyte/macrophage biology in disease
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Referee #3
Evidence, reproducibility and clarity
Summary:
Magalhaes Pinto, Malengier-Devlies, and co-authors investigated the developmental origins and maturation of synovial (lining and sublining) macrophages across embryonic, newborn, and postnatal stages in mouse. The authors used multiple transgenic reporter lines, lineage tracing, scRNA-seq, 2D confocal and 3D lightsheet imaging, and perturbations to delineate the macrophage states and ontogeny. They propose a model in which the majority of the joint lining macrophages has a fetal (EMP-derived) origin and a small proportion has a definitive HSC-derived monocyte origin, which both seed and mature within the synovial space in …
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Referee #3
Evidence, reproducibility and clarity
Summary:
Magalhaes Pinto, Malengier-Devlies, and co-authors investigated the developmental origins and maturation of synovial (lining and sublining) macrophages across embryonic, newborn, and postnatal stages in mouse. The authors used multiple transgenic reporter lines, lineage tracing, scRNA-seq, 2D confocal and 3D lightsheet imaging, and perturbations to delineate the macrophage states and ontogeny. They propose a model in which the majority of the joint lining macrophages has a fetal (EMP-derived) origin and a small proportion has a definitive HSC-derived monocyte origin, which both seed and mature within the synovial space in the postnatal period in the first 3 weeks of life. Using cell-cell communication analysis on their scRNA-seq data, they identified Fgf2, Csf1, and Tgfb as candidate signaling pathways that support (lining) macrophage development and maturation. Functional experiments indicate that the process is CSF1 and TGFb-dependent and also partly dependent on mechanosensing through Piezo1. The key conclusions on the composition of the synovial macrophages are convincing based on the presented results, and are carefully phrased. The study is very comprehensive, yet the description and organization of the results of the different mouse models could be altered to improve the storyline. Several refinements in data presentation, formulation, and minor validation experiments would further improve the clarity of the story, as well as summary recaps of the major findings throughout the text.
Major comments:
- Generally, the story could be more streamlined by introducing earlier reporter lines and lineage-origin logic. Clearly state which reporter/CreERT2 lines and acrosses are used. It was unclear in Figure 2 that cells of the cross of the Cx3cr1-GFP and Ms4a3Cre:Rosa26lsl-tdT reporter lines were used for the scRNA-seq. The principle that there are fetal-derived and bone marrow (GMP)-derived monocytes and macrophages doesn't need to be "hidden" until Figure 3. For example, also the imaging of Ms4a3Cre could be introduced before the scRNA-seq.
- Figure 1 could benefit from a cartoon visualizing the anatomy of the knee joint. The terms "sublining" and "synovium" are now a bit unclear, as it appears that sometimes the synovium is indicated as sublining and vice versa. Additionally, a schematic developmental timeline could be added to indicate the parallels between mouse and human development (fetal and postnatal development in mouse versus gestational age in human). Also, the various waves of hematopoiesis could be indicated in this timeline, which would be particularly helpful for Figure 3 for the lineage-tracing readouts. Lastly, the authors could end the manuscript (a new Figure 6) with a general cartoon summarizing all the results presented.
- Figure 1 could be rearranged: first introduce the markers CX3CR1 and VSIG4 (Figure 1D) and then present the quantifications (Figure 1B/E). Where possible, co-visualization CX3CR1-GFP and VSIG4 on tissue sections to strengthen the claims on the relationship between these 2 markers. Tying the scRNA-seq insights (Figure 2) to the imaging would be elegant. Moreover, it would be informative to represent the CX3CR1+ and VSIG4+ macrophages as a percentage of F4/80+ macrophages (Figure 1B/E). Similarly, for the flow cytometry data in Figure 2, the relationship between the markers CX3CR1 and VSIG4 on macrophages could be more clearly displayed and discussed.
- The 3D imaging of the joint is a nice addition to the manuscript, as it provides more context to the anatomical structure; however, while the text suggests several newborn joints were imaged, Figure 1F visualizes (again) the knee joint. Could other joints also be represented by 3D imaging? If the knee joint is the only joint available for imaging, and previous confocal imaging focused specifically on the meniscus in the knee joint, could the meniscus also be highlighted in the lightsheet imaging?
- Clarification is requested regarding the imaging quantification representation. The M&M section under "Statistical analysis and reproducibility" states that individual data points are displayed, and bars represent the mean. However, some of the Figure legends (e.g., Figures 1B and S1C) specify that each dot corresponds to an individual mouse, with quantification based on 2-3 sections per mouse. While this appears to be a very reasonable representation of the data, does this mean that for each dot, the mean value from the 2-3 sections per mouse was calculated and plotted?
- It is not clear how the differential expression analysis was performed on the Vsig4+ cells. Please specify if Cluster 0 was used for analysis, or all Vsig4-expressing cells? Not all cells in Cluster 0 have Vsig4+ expression. The authors described the expression dynamics of Aqp1 as intriguing, but lack a reasoning on why this is interesting.
- Figure S3E: In line with the previous comment, can the authors justify that the tdTomato+/- comparisons are not biased by scRNA-seq dropout (scRNA-seq is zero-inflated, so some tdTomato- cells could be false negatives), and provide methodological details (thresholds, ambient RNA correction, etc.) to support this?
- Although the sex-related differences in macrophage composition and the absence of differential expression are interesting, they distract from the manuscript's main messages. Moreover, the Discussion does not elaborate on how these observations relate to joint (disease) biology. Consider removing this section or integrating it clearly into the relevant biological context.
- CreERT2 transgenic lines are often not 100% efficient in recombination, also depending on whether tamoxifen or 4-OHT is used. Could the authors report the percentage of tdTomato+ cells in the joints and compare them to the recombination efficiencies in the monocytes/microglia under the same tamoxifen or 4-OHT conditions? This would help clarify how the interpret the macrophage labeling %'s.
- Could the authors draw parallels between the observations in the mouse knee joint macrophage populations and literature on other joints in mouse and the knee joint in human (for example, as described in Alivernini et al., 2020 and in the very recent Raut et al., 2025)?
Minor comments:
- In general, the authors should clarify in the Results what each marker used for imaging, flow cytometry, or in the mouse reporter lines delineates. For example, mention that F4/80 is a marker for tissue-resident macrophages (correct?) in immunofluorescence, that IBA1 is a marker for macrophages on human tissue sections (Figure S1), and PDPN is GP38 (Figure S2 - align usage of marker reference across main text and figures).
- For clarity in the microscopy representation, the single channels should be represented in a grey scale.
- Figure S1B: Is CX3CR1 also restricted to the lining macrophages in human? Could a co-staining with IBA1 be performed to strengthen the species similarities?
- Adipocyte diameter quantification: Avoid plotting individual adipocytes from 2 mice without per-mouse visualization. Instead, report the mean adipocyte diameter per mouse and plot those means.
- A little typo was spotted in the "Statistical analysis and reproducibility" section: it is Dunn's, not Bunn's multiple-comparison correction.
- Figure 2A: The gating strategy for the CX3CR1-GFP cells is missing.
- Improve the visualization of some plots. For example, Figure 2F is hard to read because of the big dot size. The dots seem to add no information to the graph and could be removed. Additionally, for comparing the clusters across the different time points, one could project the cells from the other time points in grey in the background.
- Figure S2: The dotplot is more informative than the heatmap, consider removing the heatmap.
- Figure 3A: If technically feasible, image and visualize both the GFP and tdTomato expression. It would be informative to see the Cx3cr1+ and Ms4a3-derived cells in the same specimen.
- Figure 3C: Highlight that tdTomato expression is visualized here.
- Figure 3G,F: The authors should place the schematics and graphs next to each other, so the data points can be more easily compared.
- Figure 4B: Which co-staining was performed for the immunofluorescence to quantify the % of tdTomato+ cells?
- Figure 4C: The trajectory analysis appears to have an arrow pointing from the Ccr2+ macrophages to the Ly6c+ monocytes. Please verify this directionality, as its seems against the known biology.
- Figure 5 mentions that the Csfr1 levels were reduced in a tissue-specific manner, but it is unclear how this tissue specificity was achieved.
- For the TGFb perturbations (Tgfbr2 KO and systemic TGFb depletion): did the authors validate reduced TGFb pathway activity in the macrophages, for example, reduced pSMAD2/3 levels? This would validate the effectiveness of the perturbations.
- Figure 5F could benefit from a timeline of the treatment.
- The Methods mention that Gene Ontology analysis was performed on the single-cell data, but the results are not plotted in a figure. It would be informative to include this GO/pathway analysis in the appropriate figure(s).
Significance
This work provides a high temporal-resolution and "spatial" resolution reference map of the ontogeny and maturation of the synovial lining macrophages in the knee joint. It complements existing literature that demonstrated the presence of tissue-resident macrophages in the synovial space and lining (Culemann, et al., 2019 and others) by charting the embryonic-to-postnatal emergence of lining and sublining subsets. In particular, this mouse work identified some key signaling pathways in shaping this tissue compartment. This dataset serves as a robust, steady-state reference for joint pathology and can be implemented with human studies on disease biology of the knee joint (e.g., Alivernini et al., 2020; Raut et al., 2025). Insights into the exact developmental origins, mechanisms contributing to diverse or seemingly similar cell types, and distinct maturation processes are crucial to understanding disease biology, in which developmental processes can be hijacked/reactivated.
These findings will interest researchers in joint disease biology (osteoarthritis and immune-mediated arthritides such as RA and psoriasis), macrophage development (tissue-resident vs monocyte-derived lineages), the bone/joint microenvironment, and joint mechanobiology.
The reviewer's expertise is in developmental biology, mesoderm, bone biology, hematopoiesis, and monocyte/macrophage biology in disease
-
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Referee #2
Evidence, reproducibility and clarity
In the manuscript „The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ- dependent but monocyte-independent process", Magalhaes Pinto and colleagues carefully employ a wide range of technologies including single cell profiling, imaging and an exceptional combination of fate mapping models to characterize the ontogeny and development of lining macrophages in the joint, thus dissecting their maturation during postnatal development. Over the last decade, several landmark studies highlighted the imprinting of tissue-resident macrophages by a combination of ontogenetic and tissue-specific niche …
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Referee #2
Evidence, reproducibility and clarity
In the manuscript „The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ- dependent but monocyte-independent process", Magalhaes Pinto and colleagues carefully employ a wide range of technologies including single cell profiling, imaging and an exceptional combination of fate mapping models to characterize the ontogeny and development of lining macrophages in the joint, thus dissecting their maturation during postnatal development. Over the last decade, several landmark studies highlighted the imprinting of tissue-resident macrophages by a combination of ontogenetic and tissue-specific niche factors during development. So far, the ontogeny and the tissue niche factors governing the development and maturation of lining macrophages have not been described. Therefore, the results of this study offers insights on a small highly adapted macrophage population with relevance in many disease settings in the joint. Furthermore, the findings are nicely showcasing how macrophages are specializing to even very small tissue niches across development within one bigger anatomical compartment to serve dedicated functions within this niche.
This manuscript is beautifully written and highlights many novel, highly relevant findings on lining macrophage biology and the authors employ a wide range of different technologies to carefully dissect the postnatal development of lining macrophages.
In particular, the combination of scRNA-seq and fate mapping is providing a unique the link of transcriptional programs to ontogeny within the tissue niche. Furthermore, the integrative use of distinct fate mapping strategies, transgenic mouse lines, and treatment paradigms to elucidate key niche factors guiding the development and maturation of lining macrophages provides many interesting findings and data that are highly relevant to the field. I really enjoyed reading this manuscript.
Major points:
The authors show dynamic regulation of VSIG4 in lining macrophages during development, therefore VSIG4 is maybe not an ideal choice for gating strategies to define lining macrophages or to show as a single markers in immunofluorescence (IF) stainings to demonstrate their abundance across development (even though it is clear that this is the reason why the F4/80 staining is shown next to it). To demonstrate the increase of lining macrophages during development in IF, it would be more helpful if the authors would show quantifications of all F4/80+ cells and additionally VSIG4+ as a proportion of F4/80+ cells (or VSIG4+ F4/80+ and all F4/80+ in a stacked bar plot).
In Figure 1C, the authors nicely demonstrate that the lining macrophages get closer in their distance across development to build the epithelial-like macrophage structure along the adult lining. Is the close proximity between lining macrophages already fully "matured" at 3 weeks of age and comparable to adults? Please quantify the distance in adult linings.
Can the authors explain how the grouping was performed between the analyzed human fetal joints? It is not clear why the cut was chosen between the groups at 16/17 weeks of age. Maybe it would be also beneficial if the authors would consider not grouping these samples but rather show the specific quantifications for each samples individually and estimate via linear regression the expansion over time across human development. Furthermore, can the authors give additional information about the distancing of lining macrophages in the human fetal samples, it would be great to see if they follow the same dynamics as in mouse. Maybe comparison to human juvenile/adult joints would also add on to substantiate the findings in human samples (if possible).
The scRNA-seq analysis leaves several questions open and some conclusions and workflows cannot be easily followed.
a. It is not clear how and especially why the signature genes to define macrophages vs. monocytes were chosen. Especially as the signature genes for monocytes would not include patrolling monocytes and the macrophage signature genes seem to be highly regulated during development, see also Apoe expression in NB vs. adult in Figure S2e. Why did the authors not take classical markers such as Itgam, Fcgr1a, Csf1r?
b. Can dendritic cell signatures be excluded? Cluster 11 and 12 show indeed some DC markers, are these really macrophages?
c. The authors provide several figure panels showing TOP marker genes or key marker genes for the identified clusters, however it is not clear if these are TOP DE genes or if the genes were hand chosen. Somehow, the authors give the impression that the clusters were chosen and labeled not based on DE genes, but more on existing literature that previously reported these macrophage populations. DE gene lists for all annotated cell types and macrophage clusters need to be provided within the manuscript.
d. The authors claim that Clusters 1 and 4 are "developing" macrophages. How is this defined? Why are these developing cells compared to other clusters? And why are these clusters later on not considered as progenitors of Aqp1 macrophages and Vsig4 macrophages? Why are Aqp1+ macrophages not labeled as developing when they are later on in the manuscript shown as potential intermediate progenitors of lining macrophages?
e. Furthermore, it is again confusing that markers are used throughout Figure 2 which are labeled as "key marker genes" for a population and then later on they are claimed to be regulated during development within this population, see for example Figure 2D and 2H.
f. It is appreciated that the authors distinguished cycling clusters such as 8, 9, and 10 based on their cycling gene signature. Here it would be very exciting to see a cell cycle analysis across all clusters and time points to see when exactly the cells are expanding during development; this would also substantiate the data later shown for the Mki67-CreERT2 mouse model.
g. Can the authors identify certain gene modules during development of lining macrophages (and/or their progenitors) which are associated with certain functions (e.g. GO terms, GSEA enrichment)?
To determine the actual presence of the identified macrophage clusters from the scRNA-seq as macrophage populations in the joint, the authors should perform IF or FACS for key markers. Especially, Aqp1+ macrophages should be shown in the developing joint.
The authors used a wide range of fate mapping models, which is quite unique and highly appreciated. The obtained results and the conclusions made from the models raise a couple of questions: Whereas contribution of HSC-derived/monocyte-derived macrophages to the lining compartment seems to be minor, there is still labeling across different models. Various aspects would need to be clarified.
a. For example, the authors employ Ms4a3-Cre as a tracing model for GMP-derived monocytes, however all quantifications of the labeling efficiency are not normalized to the labeling in monocytes or another highly recombined cell population. This should be shown, similar to the other fate mapping models (Figure 3 F-I).
b. Please show Ms4a3 expression across clusters across time points, to exclude expression in fetal-derived clusters.
c. In line with the question raised above, if the authors can exclude a development of the Egfr1+ and Clec4n+ developing macrophages into Aqp1+ macrophages and subsequently into Vsig4 lining macrophages, the obtained data from the Ms4a3-Cre model highly suggests a correlative labeling across these clusters what could implicate a relation. However, the authors do not discuss throughout the manuscript the role of these developing macrophages. It is highly encouraged to include this into the manuscript and it would be of high relevance to understand lining macrophage development.
d. The authors conclude from the pseudo bulk transcriptomic profiling of the different macrophage clusters that TdT+ and TdT- macrophages do not differ in their gene expression profile and that this is due to niche imprinting rather than origin imprinting. Even though the data supports that conclusion, the authors should verify if inkling cells early during development also show this similar gene expression profile and gene expression should be compared at the different developmental time points. Tissue niche imprinting is happening within the niche during development, most likely in a stepwise progress, and therefore there should be differences in the beginning.
The trajectorial analysis using different pseudotime pipelines is very interesting and nicely points out the potential role of Aqp1 macrophages as intermediates of Vsig4 lining macrophages. From my point of view, all trajectories seem to suggest that Egfr1 developing macrophages and Clec4n developing macrophages might differentiate into Aqp1 macrophages, however the authors are not exploring this further and the role of both developing macrophage clusters is not further discussed (see also comments above).
How was the starting point of the trajectorial analyses defined and is it the same for each pipeline used?
Are there potentially two trajectories? It looks like there is one in the beginning of postnatal life and a second one appearing from the monocyte-compartment later in life. If this is true, that would rather speak for a dual ontogeny of Vsig4+ macrophages, wouldn't it?
A heatmap (transcriptional shift) of trajectories between more clusters should be shown at least for Cluster 0,1,2, and 3. It is not sufficient to demonstrate this only between two clusters.
To show the similarity between Aqp1 macrophages and proliferating macrophage clusters, the authors should remove the cycling signature and compare these clusters to show that the cycling cells might be Aqp1 macrophages or earlier developing macrophage progenitors aka Clec4n or Egfr1 macrophages.
The conclusions made from the Mki67-CreERT2 data are a bit difficult to understand, whereas all progenitors (monocyte progenitors and macrophage progenitors will proliferate at the neonatal time point and no conclusions can be made if the cells expand in the niche. The authors should employ Confetti mice or other models (Ubow mice) to analyze clonal expansion in the niche.
All predicted cell-cell interactions between macrophages and fibroblasts should be provided in a supplementary table. Are the interactions shown in Figure 5 chosen interactions or the TOP predicted ones? Whereas the authors show different numbers of interactions, it is most likely hand-picked and therefore biased.
The authors further aim to dissect the factors involved in the developmental niche imprinting of lining macrophages. Even though it is highly appreciated that the authors used so many experimental setups to show the reliance of lining macrophages on Csf1 and TGF-beta as well as mechanosensation, the wide range of models the different methods used and selected developmental time points make it very difficult to really interpret the data. The authors should carefully choose time points and methods (either FACS analysis across all models or IF across all, or both). Often deletion efficiencies for transgenic models and proof of concept that the inhibitors and agonists are working in the treatment paradigm are not provided. For example, Csf1rMer-iCre-Mer Tgfbr2fl/fl mice are used but no deletion efficiency is shown or different time points of analysis, maybe the macrophages are not properly targeted in the set up.
The authors have shown the role of Csf1 and Tgfbr2 only for lining macrophages, is this specific in the joint to this population of are subliming macrophages affected in a similar manner.
Can the authors confirm their results in CSF1R-FIRE mice with anti-Csf1 injections or in Csf1op/op mice?
The setup in Figure S5G is very interesting to test the role of movement and mechanical load on the joint, however, there is basically no data on the model provided showing the efficiency of the induced optogenetic muscle contractions, and only one time point is shown.
The results regarding the role of Piezo1 and mechanosensation vary a lot. Could it be that analyses were done too early or that actually proper weight load on the joint must be applied for the maturation of the macrophages? The authors should test this to
The Rolipram experiment is shown in Figure S5G, but is not described in the result section. It only appears at some point in the discussion part. The authors should move it to results or remove it from the manuscript.
Minor points:
Please reference the Figure panels in numeric order throughout the text.
Figure 2a and 2b are a bit out of the storyline, it is not obvious why this is shown here and maybe it would be good to move it to the supplements. Gating strategy is also not used for scRNA-seq. Therefore, it would better fit to the later analysis of joint macrophages across different transgenic mouse models and treatment paradigms. The gating strategies are changing across different experiments throughout the figures, it would be nice to have a similar gating strategy for all experiments, see also Figure 3 where the defining markers for joint macrophages are changing between models.
A lot of figure panels have very small labeling that is basically unreadable. Axes at FACS plots for example. Sometimes, it is even impossible to distinguish cluster labels especially when they have similar colors.
In the text on page 14, many markers are named which are specifically regulated during development in lining macrophages, but these factors are not labeled anywhere in the volcano plot. It would be good to showcase at least some of these named genes in the figure panel, e.g. Trem2.
Figure 2F and Figure S2F are really nicely showing the percentage of cells per cluster in each analyzed biological sample. Maybe the authors could additionally consider to show a stacked bar plot with the mean percentage of cells per cluster and how the clusters are distributed across time points?
Figure 3A: IF for adult lining macrophages and the quantification are missing
Significance
This manuscript highlights novel, highly relevant findings on lining macrophage biology and the authors employ a wide range of different technologies to carefully dissect the postnatal development of lining macrophages. Furthermore, this study showcases in a very elegant and detailed way the adaptation of macrophage progenitors to a highly specific anatomical tissue niche.
The manuscript is of high interest to basic scientists focussing on macrophage biology and immune cell development and clinicians and clinician scientists focussing on joint diseases such as RA
Therefore the manuscript is of interest to a wide community working in immunology.
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Referee #1
Evidence, reproducibility and clarity
In their manuscript entitled "The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ-dependent but monocyte-independent process," the authors explore the developmental trajectory of synovial lining macrophages. They demonstrate that the formation of this specialized macrophage layer is age-dependent and governed by a distinct developmental program that proceeds independently of circulating monocytes. Through scRNA-Seq, the authors show that synovial lining macrophages originate locally from Aqp1⁺ macrophages and are marked by the expression of Csf1r, Tgfbr, and Piezo1. Notably, genetic ablation …
Note: This preprint has been reviewed by subject experts for Review Commons. Content has not been altered except for formatting.
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Referee #1
Evidence, reproducibility and clarity
In their manuscript entitled "The synovial lining macrophage layer develops in the first weeks of life in a CSF1- and TGFβ-dependent but monocyte-independent process," the authors explore the developmental trajectory of synovial lining macrophages. They demonstrate that the formation of this specialized macrophage layer is age-dependent and governed by a distinct developmental program that proceeds independently of circulating monocytes. Through scRNA-Seq, the authors show that synovial lining macrophages originate locally from Aqp1⁺ macrophages and are marked by the expression of Csf1r, Tgfbr, and Piezo1. Notably, genetic ablation of each of these factors impaired the development of lining macrophages to varying degrees, suggesting differential contributions of CSF1, TGFβ, and PIEZO1 signaling pathways to their maturation and maintenance.
The manuscript is well written, and the data quality and representation is of a high standard. The authors have employed a sophisticated array of state-of-the-art mouse models and cutting-edge technologies to elucidate the developmental origin of synovial lining macrophages. Notably, the supporting scRNA-Seq datasets are of excellence and provide valuable insights that will likely be of significant interest to researchers in the field of immunology and joint biology. Accordingly, the experimental approach and interpretations regarding macrophage origin are well-founded and compelling. However, in the eye of the reviewer, the section addressing the underlying molecular mechanisms is a bit less convincing. This part of the study appears slightly underdeveloped, and some of the mechanistic claims lack sufficient experimental clarity. A more rigorous experimental investigation would be essential to reinforce the manuscript's conclusions, particularly concerning the data related to Tgfbr and Piezo1, where the current evidence appears insufficiently substantiated.
Major point:
- The numbers of VSIG4⁺ macrophages appear either unaffected or only minimally altered in both Csf1rMerCreMer Tgfbr2floxed and Fcgr1Cre Piezo1floxed mouse models, respectively. This raises an important question: was the gene deletion efficiency sufficient in each model? Accordingly, the authors are encouraged to include quantitative data on gene deletion efficiency for both mouse models, as this information is critical for interpreting the observed phenotypic outcomes and validating the conclusions regarding gene function. Furthermore, to better assess the impact of Tgfbr2 and Piezo1 disruption, the authors should provide more comprehensive flow cytometry analyses and histological data for these mouse models. Given the apparent homogeneity of VSIG4⁺ macrophages (as shown by the authors themselves), bulk RNA-Seq of sorted Tgfbr2- and Piezo1-deficient VSIG4⁺ macrophages (or from TGFβ-treated animals) would offer valuable insights into both the effectiveness of gene deletion and the molecular pathways governed by TGFβ and PIEZO1 in lining macrophages.
Minor points:
- Consistent usage of Cx3cr1-GFP+ nomenclature (for instance: Fig. S1 legend "adult mouse synovial tissue, showing PDGFRα⁺ fibroblasts (yellow) and CX3CR1-GFP⁺ cells (cyan)." versus Fig. 1 legend "Automated spot detection highlights Cx3cr1-GFP⁺ macrophages)"
- Unclear Fig. 3 legend: "Representative immunofluorescence images of synovial tissue from Clec9aCre:Rosa26lsl-tdT mice at 3 weeks and in adulthood, showing and tdTomato (yellow) and stained for DAPI (blue), VSIG4 (cyan)" Check 'showing and tdTomato.'
- For greater clarity, it would have been helpful if the transcript names had been directly included within Figures 3C, S3A, and S3C.
- Page 24: "(Mki67CreERT2:Rosa26lsl-tdT)" Last bracket not superscript.
- Page 25: "we again leveraged our scRNAsequencing dataset" Missing punctuation.
- Page 27: Fig. 5C legend: " of synovial tissue of 1 week-old, 3 weeks-old and adult mice." Please specify and change to 'adult Csf1rΔFIRE/ΔFIRE mice'.
- Page 30: The outcome observed in the Acta1-rtTA:tetO-Cre:ChR2-V5fl mouse model appears to be inconclusive: "This approach resulted in an increased density of VSIG4+ and total (F4/80+) macrophages in the exposed leg of some 5 days-old pups, but others showed the opposite trend (Figure S5D)." This variability may reflect low efficiency of the model or other technical limitations (e.g. muscle contractions frequency or time point of analysis). Given this ambiguity, it is worth reconsidering whether the data are sufficiently robust to warrant inclusion. Should the authors choose to include these findings, further experimentation of appropriate depth and precision is required to allow a conclusive interpretation (either it increases the density of VSIG4+ macrophages or not). The same applies to the Yoda1-treated mice, for which additional data are needed to determine whether VSIG4⁺ macrophage density is truly affected.
Significance
- General assessment: provide a summary of the strengths and limitations of the study. What are the strongest and most important aspects? What aspects of the study should be improved or could be developed?
This is a well-designed study that uses cutting-edge methodologies to investigate the developmental trajectory of synovial lining macrophages under homeostatic conditions. The authors present robust experimental evidence and compelling interpretations concerning synovial macrophage origin, which are both well-substantiated and impactful. Nonetheless, from the reviewer's perspective, the section exploring the molecular mechanisms underlying macrophage differentiation is comparatively less convincing. This section appears somewhat underdeveloped, as some of the mechanistic claims lack sufficient depth and experimental rigor to fully substantiate the conclusions.
- Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field:
In contrast to earlier studies (PMID: 31391580, 32601335), the inclusion of fate-mapping experiments adds an important dimension, offering novel insight into the ontogeny of synovial macrophages. This expanded perspective may prove particularly valuable in advancing our understanding of joint immunology, especially regarding the local origins and lineage relationships of macrophage populations. Furthermore, the authors present novel insights into the molecular pathways underlying the differentiation and development of synovial lining macrophages. By demonstrating previously unrecognized regulatory mechanisms, this work significantly deepens our understanding of the cellular and transcriptional programs that drive macrophage specialization within the joint microenvironment. -Place the work in the context of the existing literature (provide references, where appropriate):
This study builds upon previous work characterizing the macrophage compartment in the joint (PMID: 31391580, 32601335), yet provides a substantially more comprehensive dataset that spans multiple developmental time points and data on the origin of this specialized macrophage subset.
- State what audience might be interested in and influenced by the reported findings:
Immunologist, clinicians
- Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.
This study falls well within the scope of the reviewer's expertise in innate immunity.
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