Hypoxia impedes differentiation of cranial neural crest cells into derivatives relevant for craniofacial development

  1. Theresa Schmid
  2. Gabriele Rodrian
  3. Alexander Kohler
  4. Michael Wegner
  5. Lina Gölz
  6. Matthias Weider

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Abstract

Orofacial clefts are the second-most prevalent congenital malformation. Risk factors are multifactorial and include genetic components but also environmental factors. One environmental factor is hypoxia during pregnancy, caused for instance by tobacco smoking, medication or living at high altitudes. Knowledge about the molecular link between hypoxia and orofacial clefts is at large. We here show that hypoxia has only modest effects on proliferating cranial neural crest cells, but dramatically influences their differentiation potential. We detected massive perturbations in their differentiation to chondrocytes, osteoblasts and smooth muscle cells. The transcriptional induction of the majority of regulated genes during each of these processes was grossly impaired by hypoxic conditions, as evidenced by genome-wide transcriptomic analyses. Bioinformatic analyses pointed to cytoskeletal organization and amino acid metabolism as two main processes compromised during all three differentiation pathways, and several orofacial cleft risk genes were among the genes with impaired induction during hypoxia. Our analyses reveal a drastic influence of hypoxia on the differentiation potential of cranial neural crest cells as a possible source for the occurrence of orofacial clefts.

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    Reply to the reviewers

    1. General Statements

    We thank the editor for handling our manuscript and the reviewers for their constructive critiques. We are deeply convinced that the reviewers’ suggestions have substantially raised the quality and possible impact of our manuscript. We also like to thank the reviewers for their judgements that the subject of our manuscript is biologically and clinically significant and of high importance, and that our manuscript might help to increase focus and visibility for affected individuals.

    New text passages in the manuscript are colored in red. Below is a point-by-point response to the reviewers’ comments.

    2. Point-by-point description of the revisions

    Response to reviewer 1 comments

    Major comments

    Point 1-1

    The authors performed qRT-PCR validation for markers of differentiation and hypoxia, with a major absence of VEGF and HIF1a. The paper would be strengthened by mention of these factors, especially by qRT-PCR or Western blot.

    We thank the reviewer for the suggestion to include the bona fide hypoxia markers Vegfa and Hif1-alpha. We followed the suggestion and performed qRT-PCR on Vegfa transcripts at each tested condition (Figs. 1A,2A,3A,4A,5A,5D,5I,5N). As Hif1α is rather regulated on protein than on transcript level, we followed the advice to perform Western blots. We analyzed Hif1α protein levels on proliferating cells and quantified by normalization to actin (Figs. 1B,C and 5 B,C).

    Point 1-2

    Please provide justification of selection 0.5% as their hypoxic condition or perhaps repeat experiments in a less extreme environment to see if their conclusions still hold true.

    We admit that our approach to use 0.5% hypoxia was a drastic challenge for the cells. It should be noted, however, that physiologic oxygen levels during pregnancy at times drop to lower than 1% (Hansen* et al, 2020; Ng et al*, 2017). In the first place, we had used oxygen levels lower than this, because we had wanted to ensure that we can detect responses by bulk RNA-seq with a limited number of samples. As we had many conditions to compare, we did not want to use more than 3-4 samples per condition. The fact that the cells showed normal proliferation underscores the fact that 0.5% O2 *per se *was not so low that it would be overly stressful to the cells.

    Nevertheless, we are very grateful to the reviewer for the suggestion to include a milder hypoxic condition. We chose 2% O2, because this equals the physiological oxygen concentration shortly before the onset of cranial neural crest cell (CNCC) differentiation. We could recapitulate the phenomenon of impaired differentiation to chondrocytes, osteoblasts and smooth muscle cells at these mild hypoxic conditions, as shown by qRT-PCR and immunofluorescence of typical markers (Figs. 5D-R). Moreover, the differentiation-specific induction of the two central hypoxia-attenuated risk genes associated with orofacial clefts that we had identified by our bioinformatic analyses at 0.5% O2 (Boc and Cdo1), was still observable at 2% O2 (Figs. S6C,D). Interestingly, in some rare cases, the attenuation of induction was lost or not as drastic as in 0.5% O2.

    We are convinced that the experiments at 2% O2 strongly increased the relevance of our manuscript, because we thus detected that oxygen levels prevailing shortly before the onset of CNCC differentiation still can influence their differentiation. This leads to the conclusion that only slight decreases of intra-uterine oxygen levels indeed might interfere with correct differentiation of CNCC.

    Point 1-3

    Standard immunohistochemistry or histology of differentiated cells would strengthen the authors' claims of reduced differentiation under hypoxic conditions, e.g., Alcian blue, alk-phos or Alizarin red, and smooth muscle actin or other indicator.

    We are grateful to the reviewer for the suggestion to include stainings of cells, as these stainings visualized the drastic effects of hypoxia on the cells. We performed immunofluorescent stainings against at least one marker protein for each differentiation paradigm. At 0.5% O2, each protein signals were nearly completely absent and cell morphology was disrupted (Figs. 2E,F, 3E, 4E). At 2% O2, we detected some more protein deposition than at 0.5%. Importantly, cells had retained their normal shape at mild hypoxia (Figs. 5H,M,R, S5A).

    Point 1-4

    The authors identify a few genes that appear down-regulated in all three differentiation conditions. If it is within the scope of the study, it would strengthen the claim of these genes' function to show the effect of knock-down or knock-out for validation.

    We thank the reviewer for the suggestion of gene knock-down or knock-out in order to prove functional relevance of our findings. As this would have been too much effort and beyond the scope of our study, we rather followed the suggestion of reviewer 2 (cf. points 2-6, and 2-8) that headed to the same direction: we mined publicly available sequence data on orofacial development for gene expression or marks of active enhancers. We found robust expression of the two central hypoxia-attenuated OFC risk genes Boc and Cdo1 during human craniofacial development (Fig. 7A) and we identified enhancers that are active in embryonic craniofacial mouse tissue (Fig. 7B). Moreover, we detected expression of both genes during murine craniofacial development in undifferentiated mesenchymal cells, osteoblasts, chondrocytes and smooth muscle cells with the help of a single cell RNA-seq dataset (Figs. 7C-E, S6B).

    Thus, we found evidence for the in vivo relevance of Boc and Cdo1 and could rule out a possible important role of Actg2, the third gene we had identified. We therefore are grateful for the suggestion to circumvent gene knockouts by reviewer 2, as we think these data strongly emphasized the importance of our findings.

    Point 1-5

    Another major critique lies in the initial claim that proliferation of O9-1 cells is not significantly impacted by hypoxia. In figures 1E-H, photograms of the cells cultured 24 -72 hours and quantifications of live vs dead cells are shown as evidence for this argument. However, the increased density of cells in normoxic conditions may be a confounding variable in this assay. It would be interesting for the researchers to assess the percent of dead vs alive cells between normoxic and hypoxic conditions when the plates reach equivalent densities.

    We apologize for the use of image sections from photographs with different cell densities. Of course, as demonstrated by our quantification, cell densities between 0.5% and 21% O2 in total were equal (cf. Figs. 1D,E). We therefore replaced the formerly used sections with new image sections with equal cell numbers.

    We thank the reviewer for the suggestion to examine if cell numbers influence cell death rates. We followed this advice by several approaches: first, we seeded cells at different densities, incubated them for 72 h (the same time span where a minimal difference had been detected) and performed live/dead stainings (Fig. S1B). The seeding density did not affect percentages of dead cells and the values were in the same range as in our initial experiment (Fig. 1J). Moreover, we performed TUNEL stainings of apoptotic cells at different time points to have an additional readout of cell death (Figs. 1K,L). As expected, the percentages of TUNEL-positive cells were identical between hypoxic and normoxic cells at all analyzed time points.

    We therefore concluded that hypoxia does not influence the rate of cell death of proliferating CNCC and accordingly specified our wording in the results section.

    Point 1-6

    At end of Fig 1 section authors attempt to tie phenotypes observed in a cell line in vitro to the complex biological processes. They are not comparable and in vivo models would be better suited for these types of comparisons.

    We apologize for the overconfident wording in our manuscript. Of course, our in vitro experiments cannot fully simulate the complex developmental processes taking place in vivo. We therefore changed the text to a more careful formulation. Moreover, we kept the wording in the discussion section that we cannot exclude that in the in vivo situation proliferation of CNCC is also affected by low oxygen levels because nutrients might not be available in such excess as they are in cell culture.

    Point 1-7

    Fig 2: if qRT-PCR did not show statistically different results between experimental and control groups why move on to bulk RNA seq?

    We apologize that the sentence about statistical significance was misleading. What we wanted to express is that there was only a little difference (if any at all) between differentiated cells at 0.5% O2 and proliferating cells at 0.5% O2 or 21% O2. For the sake of clarity and readability, we deleted this misleading sentence.

    Point 1-8

    Fig 5: hypoxia this intense is going to affect broad range of biological processes and genes. Finding a few genes that are affected in extreme hypoxia that are also risk genes is highly unlikely. How can the authors be assured that these overlaps are actually significant and not just by chance?

    We thank the reviewer for the suggestion to test for statistical significance. We tested significance of the overlap of respective gene sets (nsOFC vs. hyp-a; OFC vs. hyp-a) by Fisher’s exact test. We included Venn diagrams depicting the overlap and present the exact p-values (Figs. S5C,D). In each case where overlap of genes occurred, p-values indicated significance.

    Point 1-9

    Would appreciate discussion on how examination of neural crest is relevant for OFC, as most animal models of OFC demonstrate the pathogenesis in embryonic epithelium or periderm, not in the neural crest. Defects in neural crest are associated with other congenital craniofacial anomalies such as craniosynostosis or complex (Tessier) clefts, not the typical orofacial cleft. Please revise rationale of study, interpretation of data and Discussion to specifically state how neural crest cells are involved in the pathogenesis of orofacial cleft.

    We apologize for not pointing out enough the role of epithelial cells in the emergence of orofacial clefts. We revised our introduction, results and discussion sections in this regard and emphasized the role of epithelial cells. Importantly, we addressed the possible influence of the results gained in CNCC on epithelial cells by analyzing scRNA-seq data with the algorithm CellChat, as suggested by reviewer 2 (cf. point 2-8). We detected several cell communication pathways from CNCC to epithelial cells which contain components that are misexpressed upon hypoxia in our dataset (Figs. 7F-I). Therefore, during hypoxia, these pathways might influence epithelial cells and therefore indirectly cause orofacial clefts. We outlined this possible interplay in the discussion and briefly mentioned it in the abstract.

    We have not discussed more strongly the role of CNCC in the emergence of OFC in the revised manuscript, because we did not want to put even more emphasis on this matter. Numerous studies have proven the contribution of cranial neural crest tissue to the emergence of orofacial clefts. This fact is also pointed out in several review articles about orofacial clefts. In most cases, this knowledge was achieved by mouse models, because tissue-specific conditional knockouts are feasible (in contrast to genetic studies on patients), usually via deletion with the Wnt1-Cre driver. Funato et al. give an excellent (but quite old) overview of mouse models in which the neural crest-specific knockout of a gene leads to emergence of OFC and lists 17 genes for which this is the case (Funato* et al, 2015). Moreover, several recent studies also report on the emergence of orofacial clefts upon neural crest-specific deletion (Forman et al, 2024; Li et al, 2025). These include genes responsible for DNA methylation (Ulschmid et al, 2024), and a study on subunits of chromatin remodeling complexes that are necessary for correct transcription of their target genes, which was conducted by our group (Gehlen-Breitbach et al*, 2023).

    Minor comments

    __Point 1-10 __

    The author should replace "Final proof" in the introduction with "further evidence supporting."

    We apologize for the incorrect wording. Of course, it is highly questionable if there is such a thing as final proof in life sciences. We re-phrased the text according to the reviewer’s suggestion.

    Point 1-11

    Authors are inconsistent when referring to Figures- sometimes they capitalize (i.e. 1J) and other times they leave lower case (i.e. 1i). Needs to be consistent throughout. Figures are not numbered.

    We apologize for the inconsistency. We corrected the references to figures. Moreover, we apologize for the missing figure numbers. We also corrected this and included figure numbers.

    Point 1-12

    In figures authors would sometimes list 21% O2 first then 0.5% O2 or vice versa. (i.e. Fig on page 21 panels I, J, K). Needs to be consistent.

    We again apologize for being inconsistent. We corrected the inconsistency in Fig. 1D. Now, 21% O2 is presented before/above 0.5% O2.

    Point 1-13

    Figures on pages 28, 29, 30 panel J and page 31 panel F: there is no legend on what the scale/measurement is for the difference in expression level other than it ranges from -1 to +3.

    We thank the reviewer for the hint. We are aware that from the heatmaps we used one cannot infer relative expression rates of different genes or similar. If we would have considered expression strength of single genes, many of the gene-specific differing expression rates under the different conditions would have been hard to detect, as presentation would have been dominated by the differences in expression rates between genes. We therefore plotted gene-wise scaled expression.

    We included an explanation of the procedure in the materials and methods section.

    Point 1-14

    Will the authors please comment on the one normoxic sample in Figure 1I that did not cluster with the others? Did this meet the standards to merit exclusion as an outlier?

    We regret that the default scale of our plot of the principal component analysis is a bit misleading. This is the case because x-axis accounts for 80.3% of variance and y-axis only accounts for 6.1%. Therefore, the sample that might seem as an outlier actually met our standards. Nevertheless, we decided to keep the default scaling as is, in order not to embellish the graph (Fig. 1M).

    Point 1-15

    The authors refer to DEG as deregulated genes; while not strictly incorrect, the more standard usage is "differentially expressed genes." Please address.

    We apologize for the incorrect explanation of the acronym. Of course, this was corrected in the revised manuscript.

    Significance

    This work on neural crest cells and hypoxia are biologically and clinically significant.

    We are deeply grateful to the reviewer for considering our manuscript significant for both biologists and clinicians. We are convinced that the additional data we gathered in the course of the revision has significantly increased the importance of our work. Therefore, we once again express our gratitude to the reviewer for the valuable suggestions.

    Response to reviewer 2 comments

    Major comments

    Point 2-1

    The conclusions drawn from the experimental data are carefully formulated for the most part. One of the main concerns is that the cells were subjected to extreme hypoxic conditions, while it may be more biologically relevant to include a condition representing more mild hypoxia (e.g. 10%).

    Please refer to the response to point 1-2.

    Point 2-2

    One of the opening claims regarding severe hypoxia only mildly affecting cell proliferation is not shown clearly, since no mitotic markers have been analyzed (i.e. KI67 or PCNA staining or a simple EdU incorporation assay). Thus, the claim that they assessed cell proliferation is not very convincing, even though cell death was analyzed.

    We appreciate the reviewer’s suggestion to include a more thorough analysis of proliferation rates. We followed the advice and performed immunofluorescent stainings against Ki67 (accounting for cells in proliferative state) and phospho-histone H3 (accounting for cells undergoing mitosis). We performed this assay at different time points of culture in order to address the question if cell density might influence proliferation rates (Figs. 1F-H). Neither for Ki67 nor for pHH3 a difference was detected between 21% and 0.5% O2.

    We are convinced that these analyses strengthened our initial findings and provide strong evidence that hypoxia does not influence proliferation rates of CNCC.

    Point 2-3

    Additionally, cellular morphology of the cells could be assessed (brightfield images), since previous studies observed that hypoxia can be an inducive factor in cranial neural crest and driving EMT (Scully et al. 2016; Barriga et al. 2013).

    We thank the reviewer’s hint and followed the advice. We analyzed cellular morphology by the parameters cell length, total number of pseudopodia, number of filopodia and number of lobopodia (Figs. S1C-F). As outlined in the results section, we did not detect a difference in these parameters between 21% and 0.5% O2.

    We included the second reference mentioned by the reviewer (Barriga* et al*, 2013) additionally to Scully et al. 2016 that had already been cited.

    Point 2-4

    Furthermore, in the RNA seq analysis of chondrogenic fate biased cells the authors draw a conclusion based on the proximity of the samples on the PCA plot, which is not very convincing. More careful analysis of the bulk RNA seq data sets they have generated for key marker genes will be more convincing (for example, a heatmap with selected genes would be a helpful representation).

    We apologize for the rash and inaccurate conclusion based on proximity on PCA plots. We are grateful to the reviewer for the suggestion to include heatmaps with selected marker genes. Following this advice, we generated heatmaps on our bulk RNA-seq data with the GO terms specific for each differentiation paradigm (Figs. S2F, S3F, S4F).

    We are convinced that these maps are perfect additions to the heatmaps of the 200 top differentially-expressed genes that already had been included in the manuscript (Figs. 2K, 3J, 4J) and helped to strengthen our findings. For chondrocytes and smooth muscle cells, the new, GO-specific heatmaps perfectly recapitulated the phenomenon of hypoxia-attenuated induction. Interestingly, for osteoblasts, about half of the induced genes were hypoxia-attenuated, while the other half was induced stronger than under normoxia. This pointed to gene-specific mechanisms of hypoxia-dependent attenuation of transcription. Moreover, it shed light on a hypoxia-evoked complete dysregulation of transcriptional induction in osteoblasts, as nearly none of the genes was induced similar to normoxia.

    __ __

    Point 2-5

    As mentioned above, a straight-forward and not time consuming experiment (given that it was assessed for a maximum of 72 hrs) would be to repeat the culture of NCCs and stain for mitotic markers, and quantify the number of positively stained cells over total cell numbers. Furthermore, it is not that demanding to add an experimental condition of less severe hypoxia in this assay.

    We thank the reviewer for the suggestion and followed the advice (cf. point 2-2). The conducted experiments straightened our results, because the initially detected slight tendency to lower cell numbers at 0.5% O2 could thus be falsified: We did not detect any difference for Ki67 and pHH3 between 0.5% and 21% O2 at any analyzed time point (Figs. 1F-H). Moreover, percentages of dead or apoptotic cells at 0.5% O2 did not vary from 21% (Figs. 1I-L, S1B). As we could not detect any difference in proliferation between 21% and 0.5% O2, we skipped the analysis of proliferating cells at 2% O2.

    Point 2-6

    Without underestimating how time consuming this would be, a major lack of experimental validation of the key genes they identify as important across all conditions may be the limitation of the study (this would be the difference between correlation and a probable underlying mechanism). This can be circumvented by more extensive reference to in situ data sets from mouse or existing data sets of single cell and spatial transcriptomics. A suggested targeted knock-down (for example with siRNA, shRNA or CRISPR) to validate a few of the key genes revealed as important could take a few months, with an estimated cost up to 5,000 euros per targeted gene and replicate.

    We thank the reviewer for the notion that targeted knockdowns are beyond the scope of our manuscript. We are deeply grateful for the reviewer’s constructive criticism and for the suggestion to analyze publicly available data sets in order to gather data depicting in vivo relevance of our identified central hypoxia-attenuated OFC risk genes Boc, Cdo1 and Actg2 (cf. point 1-4). We detected robust expression of Boc and Cdo1 during human craniofacial development (Fig. 7A) and we identified enhancers that are active in embryonic craniofacial mouse tissue (Fig. 7B). Moreover, we detected expression of both genes during murine craniofacial development in undifferentiated mesenchymal cells, osteoblasts, chondrocytes and smooth muscle cells by reanalysis of a scRNA-seq dataset (Figs. 7C-E, S6B). This data comprised scRNA-seq of mouse embryonic maxillary prominence at stages E11.5 and E14.5 (Sun* et al*, 2023).

    Thus, we found evidence for the in vivo relevance of Boc and Cdo1 and could rule out a possible important role of Actg2, the third gene we had identified. We therefore are deeply grateful for the suggestion, as we think these data strongly emphasize the importance of our findings.

    Point 2-7

    On methods, replicates and statistics: The experimental methods and approach are described efficiently and seem reproducible. All biological and technical replicates are of a minimum of N=3 from independent experiments and statistical tests have been run in all cases.

    We thank the reviewer for the appreciation of our methodology, descriptions and statistical analyses.

    Minor points

    Point 2-8

    One of the key implications of NCCs in palate formation is interaction with orofacial epithelial cells, which the authors also mention. It may be interesting to check if any signaling pathways involved in this crosstalk are affected under hypoxic conditions in their existing data sets of bulk RNA SEQ. This can be done by using available algorithms such as CellChat (Jin et al. 2021; Jin, Plikus, and Nie 2023), which has been reported to work also in bulk RNA seq data analysis (according to GitHub). The authors could mine the literature for existing RNA sequencing data that include osteoblasts, chondrocytes and epithelial cells (Ozekin, O'Rourke, and Bates 2023; Piña et al. 2023).

    We are very grateful to the reviewer for this suggestion. Moreover, we like to thank the reviewer for mentioning exemplary references. We followed the advice by the methodology lined out in results and materials and methods sections: we applied the CellChat algorithm on a scRNA-seq dataset (Pina* et al, 2023; Sun et al.*, 2023) to identify pathways containing components that are hypoxia-attenuated (and associated with a risk for OFC) in our bulk RNA-seq dataset (Figs. 7F-I). We did not use the datasets the reviewer had suggested, because the data were not available for us or the file format was not well-suited for the analysis with CellChat. Importantly, the dataset from Sun et al. has the following advantages over the suggested references: the complete maxillary prominence was used (instead of palatal shelves only), and different time points were included. Thus, we were able to follow the expression of genes of interest at different developmental stages before the onset of differentiation and after (Figs. 7C-E and S6B). By our approach, we identified several OFC-related pathways that contain hypoxia-attenuated components such as BMP and FGF signaling and deposition of collagen and fibronectin (Figs. 7F-I). Importantly, the named pathways (and others) send outgoing communication patterns to epithelial cells. Therefore, hypoxia-attenuated gene induction in CNCC could influence epithelial cells via these pathways.

    We believe that the use of the CellChat algorithm has brought a deeper understanding of how hypoxia can have indirect consequences on the important topic of epithelial cells and thus could also evoke OFC. We therefore once again like to express our gratitude to the reviewer.

    Point 2-9

    Additionally, another process that may be affected is EMT (epithelial-to-mesenchymal-transition) and is possible to assess by re-analysis of bulk RNA-seq data while focusing on key genes implicated in this process (i.e. E-cadherin, vimentin, EpCAM, Snail, Twist, PRRX1).

    We thank the reviewer for the advice. We followed the advice and analyzed cellular morphology by the parameters cell length, total number of pseudopodia, number of filopodia and number of lobopodia (Figs. S1C-F) (cf. point 2-3). As we did not detect any differences between 21% and 0.5% O2, and because the cells we used for our analyses represent mesenchymal cells, i.e. cells that had already undergone EMT, we did not re-analyze our dataset with the focus on EMT.

    Point 2-10

    Lastly, when the authors report on the significantly up- or down-regulated genes, it may be interesting to categorize them by ligands, receptors, intracellular molecules and transcription factors (and use separate plots to visualize them). While a big focus of the manuscript are down-regulated genes, less emphasis was given in upregulated genes (other than the response to hypoxia gene module).

    We thank the reviewer for the advice. Following this advice, we categorized genes according to Panther protein classes "intercellular signal molecule" (PC00207), "transmembrane signal receptor" (PC00197) and "gene-specific transcriptional regulator" (PC00264) and depicted the results with violin plots (Fig. S5B). We could not analyze intracellular molecules, because this protein class does not exist in the Panther database. We had not focused on the genes with stronger induction in hypoxic condition, because the number of genes was low in each differentiation paradigm (7 in chondrocytes, less than 30 in osteoblasts, none in smooth muscle cells) and the transcriptional changes were mostly not as drastic as for the attenuated genes. In order to achieve a broader overview of deregulated processes, we now included GO term analyses of genes downregulated during the differentiation regimes both at 21% and 0.5% O2 (Figs. S2D,E, S3D,E, S4D,E).

    Point 2-11

    The authors are referencing extensively and accurately existing studies in the field and the manuscript is exceptionally well-written, with only a few points of limited clarity or increased complexity. Such an example is when the authors refer to OFC risk genes, because it is not clearly stated how the referenced studies reached their conclusions (for example, are they mouse studies, do they involve mutants, are any of these studies based on GWAS on human cohorts). This matter would significantly improve the flow of the text and highlight the importance of the study and their findings.

    We would like to thank the reviewer very much for the appreciation of our scientific writing. We apologize for not explaining exactly how our OFC risk gene lists had been curated. We included this information for both non-syndromic and other OFC risk genes at the respective sites in the results section. Moreover, we included the Human Phenotype Ontology terms that had been used in the search in the materials and methods section.

    We thank the reviewer for this suggestion, as we agree that this information significantly highlights the importance of our findings.

    Point 2-12

    The figures could be redesigned to be more intuitive to interpret. For example, using violin plots and heatmaps, as discussed, and including references or re-analysis/re-use of existing spatial transcriptomics and in situs for marker genes.

    In all cases where there is a comparison of gene expression levels, violin plots would be a better representation of up- and down-regulated genes (i.e. selected genes from Fig1K, comparison of gene expression between normoxic and hypoxic NCCs, Fig 2G when analyzing chondrogenesis and the respective analysis for osteoblasts and smooth muscle cells, as well as when comparing the three fate-biasing conditions to identify common genes that are misregulated).

    We thank the reviewer for the advice and for the appreciation of the usage of heatmaps (Figs. 2K, 3J, 4J, 6F). Unfortunately, as the number of biological replicates is only three to four, the visualization of gene expression data from our bulk RNA-seq data with violin plots was not intuitive. We therefore retained the heatmaps rather than choosing bar graphs, because they are much clearer when presenting expression data of several to many genes. We included violin plots whenever possible due to high numbers of data points (Figs. S1C, S1D, S1E, S1F, S5B). Moreover, we added additional heatmaps to depict transcriptional changes of genes associated with GO terms with the various differentiation regimes (Figs. S2F, S3F, S4F). Unfortunately, we did not detect the three central hypoxia-attenuated genes in spatial transcriptomics data on craniofacial development. But we used scRNA-seq data of different stages of orofacial mouse tissue where we could identify expression of Boc and Cdo1 (cf. points 1-4 and 2-6). These data helped, together with other in vivo data to gain evidence for the in vivo function of Boc and Cdo1 during CNCC differentiation and helped to dismiss Actg2 as another central player.

    Significance

    Several pieces of evidence have pointed to hypoxia as an environmental factor contributing to congenital orofacial clefts, ranging from studies in mouse to observations in human. The authors are doing an excellent job in putting this information together and the question they are trying to answer is of high importance, given the prevalence of such congenital syndromes.

    We are deeply grateful to the reviewer for the appreciation of our work and for classifying our research topic as highly important.

    In terms of the methods and model employed, there are some limitations, related to the choice of a mouse cell line over one from human, the severe hypoxia induced (over a more mild), and the conditions of directed differentiation not allowing for simultaneous examination of more complex lineage transitions. The methods as a whole are not that up-to-date, given the single cell and multiplexed transcriptomic advances the last couple of decades, advanced bioinformatics that could be used in combination with in vitro lineage tracing methods.

    We thank the reviewer for the honest evaluation of our methods, especially for the constructive suggestions that were given to address our hypotheses with more up-to-date methods and at milder hypoxic conditions. As outlined above, we followed the advice and re-analyzed existing scRNA-seq datasets (cf. points 2-6 and 2-8) and checked our central hypotheses at milder hypoxic conditions (cf. response to point 1-3).

    We are deeply convinced that both significantly increased the biological relevance of our results, because we thus (1) gathered evidence for the in vivo function of Boc and Cdo1 and (2) were able to show that the phenomenon of hypoxia-attenuated gene induction still holds true at biologically relevant hypoxic conditions.

    The audience this work will reach are neural crest experts, developmental biologists, and potentially clinical doctors. The general public outreach of such a paper is also diverse, as more focus and visibility is required for the individuals affected by those syndromes and their families.

    We thank the reviewer for the judgement that our manuscript will not only reach neural crest experts, but also developmental biologists in general and potentially also clinicians. We are very much pleased that the reviewer shares our opinion that affected individuals should be more in the focus of public attention. We like to express our gratitude for the judgement that our manuscript might help to increase focus and visibility for them.

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    Sun J, Lin Y, Ha N, Zhang J, Wang W, Wang X, Bian Q (2023) Single-cell RNA-Seq reveals transcriptional regulatory networks directing the development of mouse maxillary prominence. J Genet Genomics 50: 676-687, 10.1016/j.jgg.2023.02.008.

    Ulschmid CM, Sun MR, Jabbarpour CR, Steward AC, Rivera-González KS, Cao J, Martin AA, Barnes M, Wicklund L, Madrid A* et al* (2024) Disruption of DNA methylation-mediated cranial neural crest proliferation and differentiation causes orofacial clefts in mice. Proc Natl Acad Sci U S A 121: e2317668121, 10.1073/pnas.2317668121.

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    Referee #2

    Evidence, reproducibility and clarity

    Schmidt and colleagues are addressing the effects of severe hypoxia on proliferation and differentiation potential of (mouse) cranial neural crest, using a neural crest cell line subjected to hypoxic conditions, assessed by transcriptomics analysis (quantitative reverse transcription PCR, bulk RNA sequencing and bioinformatics). They are reporting a mild effect of cell proliferation and an extensive inhibition of differentiation towards osteoblasts, chondrocytes and smooth muscle cells. They reveal affected biological processes shared between the three fate biasing conditions related to cytoskeleton organization and amino acid metabolism. Lastly, among affected genes upon hypoxic conditions in vitro, they authors identified risk genes linked to non-syndromic (non-genetic) orofacial clefts exclusively downregulated in osteoblasts and smooth muscle cells, namely Fgfr2, Gstt1 and Tbxa2. Similarly, hypoxia-driven downregulation of genes implicated in syndromic orofacial clefts was observed in all three chondrocyte, osteoblast and smooth muscle differentiation scenarios. Lastly, STRING analysis of downregulated genes cross-validated their findings related to affected differentiation.

    Major comments:

    The conclusions drawn from the experimental data are carefully formulated for the most part. One of the main concerns is that the cells were subjected to extreme hypoxic conditions, while it may be more biologically relevant to include a condition representing more mild hypoxia (e.g. 10%). One of the opening claims regarding severe hypoxia only mildly affecting cell proliferation is not shown clearly, since no mitotic markers have been analyzed (i.e. KI67 or PCNA staining or a simple EdU incorporation assay). Thus, the claim that they assessed cell proliferation is not very convincing, even though cell death was analyzed. Additionally, cellular morphology of the cells could be assessed (brightfield images), since previous studies observed that hypoxia can be an inducive factor in cranial neural crest and driving EMT (Scully et al. 2016; Barriga et al. 2013).

    Furthermore, in the RNA seq analysis of chondrogenic fate biased cells the authors draw a conclusion based on the proximity of the samples on the PCA plot, which is not very convincing. More careful analysis of the bulk RNA seq data sets they have generated for key marker genes will be more convincing (for example, a heatmap with selected genes would be a helpful representation). As mentioned above, a straight-forward and not time consuming experiment (given that it was assessed for a maximum of 72 hrs) would be to repeat the culture of NCCs and stain for mitotic markers, and quantify the number of positively stained cells over total cell numbers. Furthermore, it is not that demanding to add an experimental condition of less severe hypoxia in this assay. Without underestimating how time consuming this would be, a major lack of experimental validation of the key genes they identify as important across all conditions may be the limitation of the study (this would be the difference between correlation and a probable underlying mechanism). This can be circumvented by more extensive reference to in situ data sets from mouse or existing data sets of single cell and spatial transcriptomicsA suggested targeted knock-down (for example with siRNA, shRNA or CRISPR) to validate a few of the key genes revealed as important could take a few months, with an estimated cost up to 5,000 euros per targeted gene and replicate. On methods, replicates and statistics: The experimental methods and approach are described efficiently and seem reproducible.All biological and technical replicates are of a minimum of N=3 from independent experiments and statistical tests have been run in all cases.

    Minor comments:

    One of the key implications of NCCs in palate formation is interaction with orofacial epithelial cells, which the authors also mention. It may be interesting to check if any signaling pathways involved in this crosstalk are affected under hypoxic conditions in their existing data sets of bulk RNA SEQ. This can be done by using available algorithms such as CellChat (Jin et al. 2021; Jin, Plikus, and Nie 2023), which has been reported to work also in bulk RNA seq data analysis (according to GitHub). The authors could mine the literature for existing RNA sequencing data that include osteoblasts, chondrocytes and epithelial cells (Ozekin, O'Rourke, and Bates 2023; Piña et al. 2023).

    Additionally, another process that may be affected is EMT (epithelial-to-mesenchymal-transition) and is possible to assess by re-analysis of bulk RNA-seq data while focusing on key genes implicated in this process (i.e. E-cadherin, vimentin, EpCAM, Snail, Twist, PRRX1). Lastly, when the authors report on the significantly up- or down-regulated genes, it may be interesting to categorize them by ligands, receptors, intracellular molecules and transcription factors (and use separate plots to visualize them). While a big focus of the manuscript are down-regulated genes, less emphasis was given in upregulated genes (other than the response to hypoxia gene module).

    The authors are referencing extensively and accurately existing studies in the field and the manuscript is exceptionally well-written, with only a few points of limited clarity or increased complexity. Such an example is when the authors refer to OFC risk genes, because it is not clearly stated how the referenced studies reached their conclusions (for example, are they mouse studies, do they involve mutants, are any of these studies based on GWAS on human cohorts). This matter would significantly improve the flow of the text and highlight the importance of the study and their findings. The figures could be redesigned to be more intuitive to interpret. For example, using violin plots and heatmaps, as discussed, and including references or re-analysis/re-use of existing spatial transcriptomics and in situs for marker genes.

    In all cases where there is a comparison of gene expression levels, violin plots would be a better representation of up- and down-regulated genes (i.e. selected genes from Fig1K, comparison of gene expression between normoxic and hypoxic NCCs, Fig 2G when analyzing chondrogenesis and the respective analysis for osteoblasts and smooth muscle cells, as well as when comparing the three fate-biasing conditions to identify common genes that are misregulated).

    References:

    Barriga, Elias H., Patrick H. Maxwell, Ariel E. Reyes, and Roberto Mayor. 2013. "The Hypoxia Factor Hif-1α Controls Neural Crest Chemotaxis and Epithelial to Mesenchymal Transition." The Journal of Cell Biology 201 (5): 759-76. https://doi.org/10.1083/jcb.201212100.

    Jin, Suoqin, Christian F. Guerrero-Juarez, Lihua Zhang, Ivan Chang, Raul Ramos, Chen-Hsiang Kuan, Peggy Myung, Maksim V. Plikus, and Qing Nie. 2021. "Inference and Analysis of Cell-Cell Communication Using CellChat." Nature Communications 12 (1). https://doi.org/10.1038/s41467-021-21246-9.

    Jin, Suoqin, Maksim V. Plikus, and Qing Nie. 2023. "CellChat for Systematic Analysis of Cell-Cell Communication from Single-Cell and Spatially Resolved Transcriptomics." bioRxiv. https://doi.org/10.1101/2023.11.05.565674.

    Ozekin, Yunus H., Rebecca O'Rourke, and Emily Anne Bates. 2023. "Single Cell Sequencing of the Mouse Anterior Palate Reveals Mesenchymal Heterogeneity." Developmental Dynamics : An Official Publication of the American Association of Anatomists 252 (6): 713-27. https://doi.org/10.1002/dvdy.573.

    Piña, Jeremie Oliver, Resmi Raju, Daniela M. Roth, Emma Wentworth Winchester, Parna Chattaraj, Fahad Kidwai, Fabio R. Faucz, et al. 2023. "Multimodal Spatiotemporal Transcriptomic Resolution of Embryonic Palate Osteogenesis." Nature Communications 14 (September):5687. https://doi.org/10.1038/s41467-023-41349-9.

    Scully, Deirdre, Eleanor Keane, Emily Batt, Priyadarssini Karunakaran, Debra F. Higgins, and Nobue Itasaki. 2016. "Hypoxia Promotes Production of Neural Crest Cells in the Embryonic Head." Development 143 (10): 1742-52. https://doi.org/10.1242/dev.131912.

    Significance

    Several pieces of evidence have pointed to hypoxia as an environmental factor contributing to congenital orofacial clefts, ranging from studies in mouse to observations in human. The authors are doing an excellent job in putting this information together and the question they are trying to answer is of high importance, given the prevalence of such congenital syndromes. In terms of the methods and model employed, there are some limitations, related to the choice of a mouse cell line over one from human, the severe hypoxia induced (over a more mild), and the conditions of directed differentiation not allowing for simultaneous examination of more complex lineage transitions. The methods as a whole are not that up-to-date, given the single cell and multiplexed transcriptomic advances the last couple of decades, advanced bioinformatics that could be used in combination with in vitro lineage tracing methods.

    The audience this work will reach are neural crest experts, developmental biologists, and potentially clinical doctors. The general public outreach of such a paper is also diverse, as more focus and visibility is required for the individuals affected by those syndromes and their families.

    Reviewer's expertise: mouse neural crest lineage and multipotency, lineage tracing, single cell transcriptomics, NGS, immunofluorescence, molecular methods (RNA, DNA based). Limited expertise with in vitro studies.

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    Referee #1

    Evidence, reproducibility and clarity

    Title: Hypoxia impedes differentiation of cranial neural crest cells into derivatives relevant for craniofacial development

    Synopsis: Cleft lip w/ or w/o cleft palate is the second-most common birth defect worldwide. Defects are often traceable to cranial neural crest cells through genetics or environmental factors. Schmid and coauthors focus on the environmental factor of hypoxia and investigate the effects of hypoxic conditions on the ability of CNCCs to differentiate and migrate. They performed RNA-seq analysis with qRT-PCR validation for specific markers and show that hypoxia appears to repress differentiation without markedly affecting proliferation. Hypoxic conditions did not demonstrated significant perturbations in cell proliferation; however, chondrocyte, osteoblast, and smooth muscle differentiation was significantly reduced for cell lines cultured under hypoxia. Bulk RNA-seq and PCA revealed dysregulation of genes implicated in cytoskeletal integrity (such as actin γ-2), neural crest cell migration (hedgehog co-receptor brother of CDO) and amino acid metabolism (cysteine dioxygenase), which Schmid and colleagues termed OFC risk genes.

    Major comments

    • The authors performed qRT-PCR validation for markers of differentiation and hypoxia, with a major absence of VEGF and HIF1a. The paper would be strengthened by mention of these factors, especially by qRT-PCR or Western blot.
    • Please provide justification of selection 0.5% as their hypoxic condition or perhaps repeat experiments in a less extreme environment to see if their conclusions still hold true.
    • standard immunohistochemistry or histology of differentiated cells would strengthen the authors' claims of reduced differentiation under hypoxic conditions, e.g., Alcian blue, alk-phos or Alizarin red, and smooth muscle actin or other indicator.
    • The authors identify a few genes that appear down-regulated in all three differentiation conditions. If it is within the scope of the study, it would strengthen the claim of these genes' function to show the effect of knock-down or knock-out for validation.
    • Another major critique lies in the initial claim that proliferation of O9-1 cells is not significantly impacted by hypoxia. In figures 1E-H, photograms of the cells cultured 24 -72 hours and quantifications of live vs dead cells are shown as evidence for this argument. However, the increased density of cells in normoxic conditions may be a confounding variable in this assay. It would be interesting for the researchers to assess the percent of dead vs alive cells between normoxic and hypoxic conditions when the plates reach equivalent densities.
    • At end of Fig 1 section authors attempt to tie phenotypes observed in a cell line in vitro to the complex biological processes. They are not comparable and in vivo models would be better suited for these types of comparisons.
    • Fig 2: if qRT-PCR did not show statistically different results between experimental and control groups why move on to bulk RNA seq?
    • Fig 5: hypoxia this intense is going to affect broad range of biological processes and genes. Finding a few genes that are affected in extreme hypoxia that are also risk genes is highly unlikely. How can the authors be assured that these overlaps are actually significant and not just by chance?
    • Would appreciate discussion on how examination of neural crest is relevant for OFC, as most animal models of OFC demonstrate the pathogenesis in embryonic epithelium or periderm, not in the neural crest. Defects in neural crest are associated with other congenital craniofacial anomalies such as craniosynostosis or complex (Tessier) clefts, not the typical orofacial cleft. Please revise rationale of study, interpretation of data and Discussion to specifically state how neural crest cells are involved in the pathogenesis of orofacial cleft.

    Minor comments

    • The author should replace "Final proof" in the introduction with "further evidence supporting."
    • Authors are inconsistent when referring to Figures- sometimes they capitalize (i.e. 1J) and other times they leave lower case (i.e. 1i). Needs to be consistent throughout. Figures are not numbered
    • In figures authors would sometimes list 21% O2 first then 0.5% O2 or vice versa. (i.e. Fig on page 21 panels I, J, K). Needs to be consistent.
    • Figures on pages 28, 29, 30 panel J and page 31 panel F: there is no legend on what the scale/measurement is for the difference in expression level other than it ranges from -1 to +3.
    • Will the authors please comment on the one normoxic sample in Figure 1I that did not cluster with the others? Did this meet the standards to merit exclusion as an outlier?
    • The authors refer to DEG as deregulated genes; while not strictly incorrect, the more standard usage is "differentially expressed genes." Please address.

    Significance

    This work on neural crest cells and hypoxia are biologically and clinically significant.

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    Reply to the reviewers

    1. General Statements

    We thank the editor for handling our manuscript and the reviewers for their constructive critiques. We are deeply convinced that the reviewers’ suggestions have substantially raised the quality and possible impact of our manuscript. We also like to thank the reviewers for their judgements that the subject of our manuscript is biologically and clinically significant and of high importance, and that our manuscript might help to increase focus and visibility for affected individuals.

    New text passages in the manuscript are colored in red. Below is a point-by-point response to the reviewers’ comments.

    2. Point-by-point description of the revisions

    Response to reviewer 1 comments

    Major comments

    Point 1-1

    The authors performed qRT-PCR validation for markers of differentiation and hypoxia, with a major absence of VEGF and HIF1a. The paper would be strengthened by mention of these factors, especially by qRT-PCR or Western blot.

    We thank the reviewer for the suggestion to include the bona fide hypoxia markers Vegfa and Hif1-alpha. We followed the suggestion and performed qRT-PCR on Vegfa transcripts at each tested condition (Figs. 1A,2A,3A,4A,5A,5D,5I,5N). As Hif1α is rather regulated on protein than on transcript level, we followed the advice to perform Western blots. We analyzed Hif1α protein levels on proliferating cells and quantified by normalization to actin (Figs. 1B,C and 5 B,C).

    Point 1-2

    Please provide justification of selection 0.5% as their hypoxic condition or perhaps repeat experiments in a less extreme environment to see if their conclusions still hold true.

    We admit that our approach to use 0.5% hypoxia was a drastic challenge for the cells. It should be noted, however, that physiologic oxygen levels during pregnancy at times drop to lower than 1% (Hansen* et al, 2020; Ng et al*, 2017). In the first place, we had used oxygen levels lower than this, because we had wanted to ensure that we can detect responses by bulk RNA-seq with a limited number of samples. As we had many conditions to compare, we did not want to use more than 3-4 samples per condition. The fact that the cells showed normal proliferation underscores the fact that 0.5% O2 *per se *was not so low that it would be overly stressful to the cells.

    Nevertheless, we are very grateful to the reviewer for the suggestion to include a milder hypoxic condition. We chose 2% O2, because this equals the physiological oxygen concentration shortly before the onset of cranial neural crest cell (CNCC) differentiation. We could recapitulate the phenomenon of impaired differentiation to chondrocytes, osteoblasts and smooth muscle cells at these mild hypoxic conditions, as shown by qRT-PCR and immunofluorescence of typical markers (Figs. 5D-R). Moreover, the differentiation-specific induction of the two central hypoxia-attenuated risk genes associated with orofacial clefts that we had identified by our bioinformatic analyses at 0.5% O2 (Boc and Cdo1), was still observable at 2% O2 (Figs. EV6C,D). Interestingly, in some rare cases, the attenuation of induction was lost or not as drastic as in 0.5% O2.

    We are convinced that the experiments at 2% O2 strongly increased the relevance of our manuscript, because we thus detected that oxygen levels prevailing shortly before the onset of CNCC differentiation still can influence their differentiation. This leads to the conclusion that only slight decreases of intra-uterine oxygen levels indeed might interfere with correct differentiation of CNCC.

    Point 1-3

    Standard immunohistochemistry or histology of differentiated cells would strengthen the authors' claims of reduced differentiation under hypoxic conditions, e.g., Alcian blue, alk-phos or Alizarin red, and smooth muscle actin or other indicator.

    We are grateful to the reviewer for the suggestion to include stainings of cells, as these stainings visualized the drastic effects of hypoxia on the cells. We performed immunofluorescent stainings against at least one marker protein for each differentiation paradigm. At 0.5% O2, each protein signals were nearly completely absent and cell morphology was disrupted (Figs. 2E,F, 3E, 4E). At 2% O2, we detected some more protein deposition than at 0.5%. Importantly, cells had retained their normal shape at mild hypoxia (Figs. 5H,M,R, EV5A).

    Point 1-4

    The authors identify a few genes that appear down-regulated in all three differentiation conditions. If it is within the scope of the study, it would strengthen the claim of these genes' function to show the effect of knock-down or knock-out for validation.

    We thank the reviewer for the suggestion of gene knock-down or knock-out in order to prove functional relevance of our findings. As this would have been too much effort and beyond the scope of our study, we rather followed the suggestion of reviewer 2 (cf. points 2-6, and 2-8) that headed to the same direction: we mined publicly available sequence data on orofacial development for gene expression or marks of active enhancers. We found robust expression of the two central hypoxia-attenuated OFC risk genes Boc and Cdo1 during human craniofacial development (Fig. 7A) and we identified enhancers that are active in embryonic craniofacial mouse tissue (Fig. 7B). Moreover, we detected expression of both genes during murine craniofacial development in undifferentiated mesenchymal cells, osteoblasts, chondrocytes and smooth muscle cells with the help of a single cell RNA-seq dataset (Figs. 7C-E, EV6B).

    Thus, we found evidence for the in vivo relevance of Boc and Cdo1 and could rule out a possible important role of Actg2, the third gene we had identified. We therefore are grateful for the suggestion to circumvent gene knockouts by reviewer 2, as we think these data strongly emphasized the importance of our findings.

    Point 1-5

    Another major critique lies in the initial claim that proliferation of O9-1 cells is not significantly impacted by hypoxia. In figures 1E-H, photograms of the cells cultured 24 -72 hours and quantifications of live vs dead cells are shown as evidence for this argument. However, the increased density of cells in normoxic conditions may be a confounding variable in this assay. It would be interesting for the researchers to assess the percent of dead vs alive cells between normoxic and hypoxic conditions when the plates reach equivalent densities.

    We apologize for the use of image sections from photographs with different cell densities. Of course, as demonstrated by our quantification, cell densities between 0.5% and 21% O2 in total were equal (cf. Figs. 1D,E). We therefore replaced the formerly used sections with new image sections with equal cell numbers.

    We thank the reviewer for the suggestion to examine if cell numbers influence cell death rates. We followed this advice by several approaches: first, we seeded cells at different densities, incubated them for 72 h (the same time span where a minimal difference had been detected) and performed live/dead stainings (Fig. EV1B). The seeding density did not affect percentages of dead cells and the values were in the same range as in our initial experiment (Fig. 1J). Moreover, we performed TUNEL stainings of apoptotic cells at different time points to have an additional readout of cell death (Figs. 1K,L). As expected, the percentages of TUNEL-positive cells were identical between hypoxic and normoxic cells at all analyzed time points.

    We therefore concluded that hypoxia does not influence the rate of cell death of proliferating CNCC and accordingly specified our wording in the results section.

    Point 1-6

    At end of Fig 1 section authors attempt to tie phenotypes observed in a cell line in vitro to the complex biological processes. They are not comparable and in vivo models would be better suited for these types of comparisons.

    We apologize for the overconfident wording in our manuscript. Of course, our in vitro experiments cannot fully simulate the complex developmental processes taking place in vivo. We therefore changed the text to a more careful formulation. Moreover, we kept the wording in the discussion section that we cannot exclude that in the in vivo situation proliferation of CNCC is also affected by low oxygen levels because nutrients might not be available in such excess as they are in cell culture.

    Point 1-7

    Fig 2: if qRT-PCR did not show statistically different results between experimental and control groups why move on to bulk RNA seq?

    We apologize that the sentence about statistical significance was misleading. What we wanted to express is that there was only a little difference (if any at all) between differentiated cells at 0.5% O2 and proliferating cells at 0.5% O2 or 21% O2. For the sake of clarity and readability, we deleted this misleading sentence.

    Point 1-8

    Fig 5: hypoxia this intense is going to affect broad range of biological processes and genes. Finding a few genes that are affected in extreme hypoxia that are also risk genes is highly unlikely. How can the authors be assured that these overlaps are actually significant and not just by chance?

    We thank the reviewer for the suggestion to test for statistical significance. We tested significance of the overlap of respective gene sets (nsOFC vs. hyp-a; OFC vs. hyp-a) by Fisher’s exact test. We included Venn diagrams depicting the overlap and present the exact p-values (Figs. EV5C,D). In each case where overlap of genes occurred, p-values indicated significance.

    Point 1-9

    Would appreciate discussion on how examination of neural crest is relevant for OFC, as most animal models of OFC demonstrate the pathogenesis in embryonic epithelium or periderm, not in the neural crest. Defects in neural crest are associated with other congenital craniofacial anomalies such as craniosynostosis or complex (Tessier) clefts, not the typical orofacial cleft. Please revise rationale of study, interpretation of data and Discussion to specifically state how neural crest cells are involved in the pathogenesis of orofacial cleft.

    We apologize for not pointing out enough the role of epithelial cells in the emergence of orofacial clefts. We revised our introduction, results and discussion sections in this regard and emphasized the role of epithelial cells. Importantly, we addressed the possible influence of the results gained in CNCC on epithelial cells by analyzing scRNA-seq data with the algorithm CellChat, as suggested by reviewer 2 (cf. point 2-8). We detected several cell communication pathways from CNCC to epithelial cells which contain components that are misexpressed upon hypoxia in our dataset (Figs. 7F-I). Therefore, during hypoxia, these pathways might influence epithelial cells and therefore indirectly cause orofacial clefts. We outlined this possible interplay in the discussion and briefly mentioned it in the abstract.

    We have not discussed more strongly the role of CNCC in the emergence of OFC in the revised manuscript, because we did not want to put even more emphasis on this matter. Numerous studies have proven the contribution of cranial neural crest tissue to the emergence of orofacial clefts. This fact is also pointed out in several review articles about orofacial clefts. In most cases, this knowledge was achieved by mouse models, because tissue-specific conditional knockouts are feasible (in contrast to genetic studies on patients), usually via deletion with the Wnt1-Cre driver. Funato et al. give an excellent (but quite old) overview of mouse models in which the neural crest-specific knockout of a gene leads to emergence of OFC and lists 17 genes for which this is the case (Funato* et al, 2015). Moreover, several recent studies also report on the emergence of orofacial clefts upon neural crest-specific deletion (Forman et al, 2024; Li et al, 2025). These include genes responsible for DNA methylation (Ulschmid et al, 2024), and a study on subunits of chromatin remodeling complexes that are necessary for correct transcription of their target genes, which was conducted by our group (Gehlen-Breitbach et al*, 2023).

    Minor comments

    __Point 1-10 __

    The author should replace "Final proof" in the introduction with "further evidence supporting."

    We apologize for the incorrect wording. Of course, it is highly questionable if there is such a thing as final proof in life sciences. We re-phrased the text according to the reviewer’s suggestion.

    Point 1-11

    Authors are inconsistent when referring to Figures- sometimes they capitalize (i.e. 1J) and other times they leave lower case (i.e. 1i). Needs to be consistent throughout. Figures are not numbered.

    We apologize for the inconsistency. We corrected the references to figures. Moreover, we apologize for the missing figure numbers. We also corrected this and included figure numbers.

    Point 1-12

    In figures authors would sometimes list 21% O2 first then 0.5% O2 or vice versa. (i.e. Fig on page 21 panels I, J, K). Needs to be consistent.

    We again apologize for being inconsistent. We corrected the inconsistency in Fig. 1D. Now, 21% O2 is presented before/above 0.5% O2.

    Point 1-13

    Figures on pages 28, 29, 30 panel J and page 31 panel F: there is no legend on what the scale/measurement is for the difference in expression level other than it ranges from -1 to +3.

    We thank the reviewer for the hint. We are aware that from the heatmaps we used one cannot infer relative expression rates of different genes or similar. If we would have considered expression strength of single genes, many of the gene-specific differing expression rates under the different conditions would have been hard to detect, as presentation would have been dominated by the differences in expression rates between genes. We therefore plotted gene-wise scaled expression.

    We included an explanation of the procedure in the materials and methods section.

    Point 1-14

    Will the authors please comment on the one normoxic sample in Figure 1I that did not cluster with the others? Did this meet the standards to merit exclusion as an outlier?

    We regret that the default scale of our plot of the principal component analysis is a bit misleading. This is the case because x-axis accounts for 80.3% of variance and y-axis only accounts for 6.1%. Therefore, the sample that might seem as an outlier actually met our standards. Nevertheless, we decided to keep the default scaling as is, in order not to embellish the graph (Fig. 1M).

    Point 1-15

    The authors refer to DEG as deregulated genes; while not strictly incorrect, the more standard usage is "differentially expressed genes." Please address.

    We apologize for the incorrect explanation of the acronym. Of course, this was corrected in the revised manuscript.

    Significance

    This work on neural crest cells and hypoxia are biologically and clinically significant.

    We are deeply grateful to the reviewer for considering our manuscript significant for both biologists and clinicians. We are convinced that the additional data we gathered in the course of the revision has significantly increased the importance of our work. Therefore, we once again express our gratitude to the reviewer for the valuable suggestions.

    Response to reviewer 2 comments

    Major comments

    Point 2-1

    The conclusions drawn from the experimental data are carefully formulated for the most part. One of the main concerns is that the cells were subjected to extreme hypoxic conditions, while it may be more biologically relevant to include a condition representing more mild hypoxia (e.g. 10%).

    Please refer to the response to point 1-2.

    Point 2-2

    One of the opening claims regarding severe hypoxia only mildly affecting cell proliferation is not shown clearly, since no mitotic markers have been analyzed (i.e. KI67 or PCNA staining or a simple EdU incorporation assay). Thus, the claim that they assessed cell proliferation is not very convincing, even though cell death was analyzed.

    We appreciate the reviewer’s suggestion to include a more thorough analysis of proliferation rates. We followed the advice and performed immunofluorescent stainings against Ki67 (accounting for cells in proliferative state) and phospho-histone H3 (accounting for cells undergoing mitosis). We performed this assay at different time points of culture in order to address the question if cell density might influence proliferation rates (Figs. 1F-H). Neither for Ki67 nor for pHH3 a difference was detected between 21% and 0.5% O2.

    We are convinced that these analyses strengthened our initial findings and provide strong evidence that hypoxia does not influence proliferation rates of CNCC.

    Point 2-3

    Additionally, cellular morphology of the cells could be assessed (brightfield images), since previous studies observed that hypoxia can be an inducive factor in cranial neural crest and driving EMT (Scully et al. 2016; Barriga et al. 2013).

    We thank the reviewer’s hint and followed the advice. We analyzed cellular morphology by the parameters cell length, total number of pseudopodia, number of filopodia and number of lobopodia (Figs. EV1C-F). As outlined in the results section, we did not detect a difference in these parameters between 21% and 0.5% O2.

    We included the second reference mentioned by the reviewer (Barriga* et al*, 2013) additionally to Scully et al. 2016 that had already been cited.

    Point 2-4

    Furthermore, in the RNA seq analysis of chondrogenic fate biased cells the authors draw a conclusion based on the proximity of the samples on the PCA plot, which is not very convincing. More careful analysis of the bulk RNA seq data sets they have generated for key marker genes will be more convincing (for example, a heatmap with selected genes would be a helpful representation).

    We apologize for the rash and inaccurate conclusion based on proximity on PCA plots. We are grateful to the reviewer for the suggestion to include heatmaps with selected marker genes. Following this advice, we generated heatmaps on our bulk RNA-seq data with the GO terms specific for each differentiation paradigm (Figs. EV2F, EV3F, EV4F).

    We are convinced that these maps are perfect additions to the heatmaps of the 200 top differentially-expressed genes that already had been included in the manuscript (Figs. 2K, 3J, 4J) and helped to strengthen our findings. For chondrocytes and smooth muscle cells, the new, GO-specific heatmaps perfectly recapitulated the phenomenon of hypoxia-attenuated induction. Interestingly, for osteoblasts, about half of the induced genes were hypoxia-attenuated, while the other half was induced stronger than under normoxia. This pointed to gene-specific mechanisms of hypoxia-dependent attenuation of transcription. Moreover, it shed light on a hypoxia-evoked complete dysregulation of transcriptional induction in osteoblasts, as nearly none of the genes was induced similar to normoxia.

    __ __

    Point 2-5

    As mentioned above, a straight-forward and not time consuming experiment (given that it was assessed for a maximum of 72 hrs) would be to repeat the culture of NCCs and stain for mitotic markers, and quantify the number of positively stained cells over total cell numbers. Furthermore, it is not that demanding to add an experimental condition of less severe hypoxia in this assay.

    We thank the reviewer for the suggestion and followed the advice (cf. point 2-2). The conducted experiments straightened our results, because the initially detected slight tendency to lower cell numbers at 0.5% O2 could thus be falsified: We did not detect any difference for Ki67 and pHH3 between 0.5% and 21% O2 at any analyzed time point (Figs. 1F-H). Moreover, percentages of dead or apoptotic cells at 0.5% O2 did not vary from 21% (Figs. 1I-L, EV1B). As we could not detect any difference in proliferation between 21% and 0.5% O2, we skipped the analysis of proliferating cells at 2% O2.

    Point 2-6

    Without underestimating how time consuming this would be, a major lack of experimental validation of the key genes they identify as important across all conditions may be the limitation of the study (this would be the difference between correlation and a probable underlying mechanism). This can be circumvented by more extensive reference to in situ data sets from mouse or existing data sets of single cell and spatial transcriptomics. A suggested targeted knock-down (for example with siRNA, shRNA or CRISPR) to validate a few of the key genes revealed as important could take a few months, with an estimated cost up to 5,000 euros per targeted gene and replicate.

    We thank the reviewer for the notion that targeted knockdowns are beyond the scope of our manuscript. We are deeply grateful for the reviewer’s constructive criticism and for the suggestion to analyze publicly available data sets in order to gather data depicting in vivo relevance of our identified central hypoxia-attenuated OFC risk genes Boc, Cdo1 and Actg2 (cf. point 1-4). We detected robust expression of Boc and Cdo1 during human craniofacial development (Fig. 7A) and we identified enhancers that are active in embryonic craniofacial mouse tissue (Fig. 7B). Moreover, we detected expression of both genes during murine craniofacial development in undifferentiated mesenchymal cells, osteoblasts, chondrocytes and smooth muscle cells by reanalysis of a scRNA-seq dataset (Figs. 7C-E, EV6B). This data comprised scRNA-seq of mouse embryonic maxillary prominence at stages E11.5 and E14.5 (Sun* et al*, 2023).

    Thus, we found evidence for the in vivo relevance of Boc and Cdo1 and could rule out a possible important role of Actg2, the third gene we had identified. We therefore are deeply grateful for the suggestion, as we think these data strongly emphasize the importance of our findings.

    Point 2-7

    On methods, replicates and statistics: The experimental methods and approach are described efficiently and seem reproducible. All biological and technical replicates are of a minimum of N=3 from independent experiments and statistical tests have been run in all cases.

    We thank the reviewer for the appreciation of our methodology, descriptions and statistical analyses.

    Minor points

    * *

    Point 2-8

    One of the key implications of NCCs in palate formation is interaction with orofacial epithelial cells, which the authors also mention. It may be interesting to check if any signaling pathways involved in this crosstalk are affected under hypoxic conditions in their existing data sets of bulk RNA SEQ. This can be done by using available algorithms such as CellChat (Jin et al. 2021; Jin, Plikus, and Nie 2023), which has been reported to work also in bulk RNA seq data analysis (according to GitHub). The authors could mine the literature for existing RNA sequencing data that include osteoblasts, chondrocytes and epithelial cells (Ozekin, O'Rourke, and Bates 2023; Piña et al. 2023).

    We are very grateful to the reviewer for this suggestion. Moreover, we like to thank the reviewer for mentioning exemplary references. We followed the advice by the methodology lined out in results and materials and methods sections: we applied the CellChat algorithm on a scRNA-seq dataset (Pina* et al, 2023; Sun et al.*, 2023) to identify pathways containing components that are hypoxia-attenuated (and associated with a risk for OFC) in our bulk RNA-seq dataset (Figs. 7F-I). We did not use the datasets the reviewer had suggested, because the data were not available for us or the file format was not well-suited for the analysis with CellChat. Importantly, the dataset from Sun et al. has the following advantages over the suggested references: the complete maxillary prominence was used (instead of palatal shelves only), and different time points were included. Thus, we were able to follow the expression of genes of interest at different developmental stages before the onset of differentiation and after (Figs. 7C-E and EV6B). By our approach, we identified several OFC-related pathways that contain hypoxia-attenuated components such as BMP and FGF signaling and deposition of collagen and fibronectin (Figs. 7F-I). Importantly, the named pathways (and others) send outgoing communication patterns to epithelial cells. Therefore, hypoxia-attenuated gene induction in CNCC could influence epithelial cells via these pathways.

    We believe that the use of the CellChat algorithm has brought a deeper understanding of how hypoxia can have indirect consequences on the important topic of epithelial cells and thus could also evoke OFC. We therefore once again like to express our gratitude to the reviewer.

    Point 2-9

    Additionally, another process that may be affected is EMT (epithelial-to-mesenchymal-transition) and is possible to assess by re-analysis of bulk RNA-seq data while focusing on key genes implicated in this process (i.e. E-cadherin, vimentin, EpCAM, Snail, Twist, PRRX1).

    We thank the reviewer for the advice. We followed the advice and analyzed cellular morphology by the parameters cell length, total number of pseudopodia, number of filopodia and number of lobopodia (Figs. EV1C-F) (cf. point 2-3). As we did not detect any differences between 21% and 0.5% O2, and because the cells we used for our analyses represent mesenchymal cells, i.e. cells that had already undergone EMT, we did not re-analyze our dataset with the focus on EMT.

    Point 2-10

    Lastly, when the authors report on the significantly up- or down-regulated genes, it may be interesting to categorize them by ligands, receptors, intracellular molecules and transcription factors (and use separate plots to visualize them). While a big focus of the manuscript are down-regulated genes, less emphasis was given in upregulated genes (other than the response to hypoxia gene module).

    We thank the reviewer for the advice. Following this advice, we categorized genes according to Panther protein classes "intercellular signal molecule" (PC00207), "transmembrane signal receptor" (PC00197) and "gene-specific transcriptional regulator" (PC00264) and depicted the results with violin plots (Fig. EV5B). We could not analyze intracellular molecules, because this protein class does not exist in the Panther database. We had not focused on the genes with stronger induction in hypoxic condition, because the number of genes was low in each differentiation paradigm (7 in chondrocytes, less than 30 in osteoblasts, none in smooth muscle cells) and the transcriptional changes were mostly not as drastic as for the attenuated genes. In order to achieve a broader overview of deregulated processes, we now included GO term analyses of genes downregulated during the differentiation regimes both at 21% and 0.5% O2 (Figs. EV2D,E, EV3D,E, EV4D,E).

    Point 2-11

    The authors are referencing extensively and accurately existing studies in the field and the manuscript is exceptionally well-written, with only a few points of limited clarity or increased complexity. Such an example is when the authors refer to OFC risk genes, because it is not clearly stated how the referenced studies reached their conclusions (for example, are they mouse studies, do they involve mutants, are any of these studies based on GWAS on human cohorts). This matter would significantly improve the flow of the text and highlight the importance of the study and their findings.

    We would like to thank the reviewer very much for the appreciation of our scientific writing. We apologize for not explaining exactly how our OFC risk gene lists had been curated. We included this information for both non-syndromic and other OFC risk genes at the respective sites in the results section. Moreover, we included the Human Phenotype Ontology terms that had been used in the search in the materials and methods section.

    We thank the reviewer for this suggestion, as we agree that this information significantly highlights the importance of our findings.

    Point 2-12

    The figures could be redesigned to be more intuitive to interpret. For example, using violin plots and heatmaps, as discussed, and including references or re-analysis/re-use of existing spatial transcriptomics and in situs for marker genes.

    In all cases where there is a comparison of gene expression levels, violin plots would be a better representation of up- and down-regulated genes (i.e. selected genes from Fig1K, comparison of gene expression between normoxic and hypoxic NCCs, Fig 2G when analyzing chondrogenesis and the respective analysis for osteoblasts and smooth muscle cells, as well as when comparing the three fate-biasing conditions to identify common genes that are misregulated).

    We thank the reviewer for the advice and for the appreciation of the usage of heatmaps (Figs. 2K, 3J, 4J, 6F). Unfortunately, as the number of biological replicates is only three to four, the visualization of gene expression data from our bulk RNA-seq data with violin plots was not intuitive. We therefore retained the heatmaps rather than choosing bar graphs, because they are much clearer when presenting expression data of several to many genes. We included violin plots whenever possible due to high numbers of data points (Figs. EV1C, EV1D, EV1E, EV1F, EV5B). Moreover, we added additional heatmaps to depict transcriptional changes of genes associated with GO terms with the various differentiation regimes (Figs. EV2F, EV3F, EV4F). Unfortunately, we did not detect the three central hypoxia-attenuated genes in spatial transcriptomics data on craniofacial development. But we used scRNA-seq data of different stages of orofacial mouse tissue where we could identify expression of Boc and Cdo1 (cf. points 1-4 and 2-6). These data helped, together with other in vivo data to gain evidence for the in vivo function of Boc and Cdo1 during CNCC differentiation and helped to dismiss Actg2 as another central player.

    Significance

    Several pieces of evidence have pointed to hypoxia as an environmental factor contributing to congenital orofacial clefts, ranging from studies in mouse to observations in human. The authors are doing an excellent job in putting this information together and the question they are trying to answer is of high importance, given the prevalence of such congenital syndromes.

    We are deeply grateful to the reviewer for the appreciation of our work and for classifying our research topic as highly important.

    In terms of the methods and model employed, there are some limitations, related to the choice of a mouse cell line over one from human, the severe hypoxia induced (over a more mild), and the conditions of directed differentiation not allowing for simultaneous examination of more complex lineage transitions. The methods as a whole are not that up-to-date, given the single cell and multiplexed transcriptomic advances the last couple of decades, advanced bioinformatics that could be used in combination with in vitro lineage tracing methods.

    We thank the reviewer for the honest evaluation of our methods, especially for the constructive suggestions that were given to address our hypotheses with more up-to-date methods and at milder hypoxic conditions. As outlined above, we followed the advice and re-analyzed existing scRNA-seq datasets (cf. points 2-6 and 2-8) and checked our central hypotheses at milder hypoxic conditions (cf. response to point 1-3).

    We are deeply convinced that both significantly increased the biological relevance of our results, because we thus (1) gathered evidence for the in vivo function of Boc and Cdo1 and (2) were able to show that the phenomenon of hypoxia-attenuated gene induction still holds true at biologically relevant hypoxic conditions.

    The audience this work will reach are neural crest experts, developmental biologists, and potentially clinical doctors. The general public outreach of such a paper is also diverse, as more focus and visibility is required for the individuals affected by those syndromes and their families.

    We thank the reviewer for the judgement that our manuscript will not only reach neural crest experts, but also developmental biologists in general and potentially also clinicians. We are very much pleased that the reviewer shares our opinion that affected individuals should be more in the focus of public attention. We like to express our gratitude for the judgement that our manuscript might help to increase focus and visibility for them.

    References

    Barriga EH, Maxwell PH, Reyes AE, Mayor R (2013) The hypoxia factor Hif-1α controls neural crest chemotaxis and epithelial to mesenchymal transition. The Journal of cell biology 201: 759-776, 10.1083/jcb.201212100.

    Forman TE, Sajek MP, Larson ED, Mukherjee N, Fantauzzo KA (2024) PDGFRα signaling regulates Srsf3 transcript binding to affect PI3K signaling and endosomal trafficking. Elife 13, 10.7554/eLife.98531.

    Funato N, Nakamura M, Yanagisawa H (2015) Molecular basis of cleft palates in mice. World journal of biological chemistry 6: 121-138, 10.4331/wjbc.v6.i3.121.

    Gehlen-Breitbach S, Schmid T, Fröb F, Rodrian G, Weider M, Wegner M, Gölz L (2023) The Tip60/Ep400 chromatin remodeling complex impacts basic cellular functions in cranial neural crest-derived tissue during early orofacial development. International Journal of Oral Science 15: 16, 10.1038/s41368-023-00222-7.

    Hansen JM, Jones DP, Harris C (2020) The Redox Theory of Development. Antioxid Redox Signal 32: 715-740, 10.1089/ars.2019.7976.

    Li D, Tian Y, Vona B, Yu X, Lin J, Ma L, Lou S, Li X, Zhu G, Wang Y* et al* (2025) A TAF11 variant contributes to non-syndromic cleft lip only through modulating neural crest cell migration. Hum Mol Genet 34: 392-401, 10.1093/hmg/ddae188.

    Ng KYB, Mingels R, Morgan H, Macklon N, Cheong Y (2017) In vivo oxygen, temperature and pH dynamics in the female reproductive tract and their importance in human conception: a systematic review. Human Reproduction Update 24: 15-34, 10.1093/humupd/dmx028.

    Pina JO, Raju R, Roth DM, Winchester EW, Chattaraj P, Kidwai F, Faucz FR, Iben J, Mitra A, Campbell K* et al* (2023) Multimodal spatiotemporal transcriptomic resolution of embryonic palate osteogenesis. Nature communications 14: 5687, 10.1038/s41467-023-41349-9.

    Sun J, Lin Y, Ha N, Zhang J, Wang W, Wang X, Bian Q (2023) Single-cell RNA-Seq reveals transcriptional regulatory networks directing the development of mouse maxillary prominence. J Genet Genomics 50: 676-687, 10.1016/j.jgg.2023.02.008.

    Ulschmid CM, Sun MR, Jabbarpour CR, Steward AC, Rivera-González KS, Cao J, Martin AA, Barnes M, Wicklund L, Madrid A* et al* (2024) Disruption of DNA methylation-mediated cranial neural crest proliferation and differentiation causes orofacial clefts in mice. Proc Natl Acad Sci U S A 121: e2317668121, 10.1073/pnas.2317668121.

  5. Review Commons

    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 #2

    Evidence, reproducibility and clarity

    Schmidt and colleagues are addressing the effects of severe hypoxia on proliferation and differentiation potential of (mouse) cranial neural crest, using a neural crest cell line subjected to hypoxic conditions, assessed by transcriptomics analysis (quantitative reverse transcription PCR, bulk RNA sequencing and bioinformatics). They are reporting a mild effect of cell proliferation and an extensive inhibition of differentiation towards osteoblasts, chondrocytes and smooth muscle cells. They reveal affected biological processes shared between the three fate biasing conditions related to cytoskeleton organization and amino acid metabolism. Lastly, among affected genes upon hypoxic conditions in vitro, they authors identified risk genes linked to non-syndromic (non-genetic) orofacial clefts exclusively downregulated in osteoblasts and smooth muscle cells, namely Fgfr2, Gstt1 and Tbxa2. Similarly, hypoxia-driven downregulation of genes implicated in syndromic orofacial clefts was observed in all three chondrocyte, osteoblast and smooth muscle differentiation scenarios. Lastly, STRING analysis of downregulated genes cross-validated their findings related to affected differentiation.

    Major comments:

    The conclusions drawn from the experimental data are carefully formulated for the most part. One of the main concerns is that the cells were subjected to extreme hypoxic conditions, while it may be more biologically relevant to include a condition representing more mild hypoxia (e.g. 10%). One of the opening claims regarding severe hypoxia only mildly affecting cell proliferation is not shown clearly, since no mitotic markers have been analyzed (i.e. KI67 or PCNA staining or a simple EdU incorporation assay). Thus, the claim that they assessed cell proliferation is not very convincing, even though cell death was analyzed. Additionally, cellular morphology of the cells could be assessed (brightfield images), since previous studies observed that hypoxia can be an inducive factor in cranial neural crest and driving EMT (Scully et al. 2016; Barriga et al. 2013).

    Furthermore, in the RNA seq analysis of chondrogenic fate biased cells the authors draw a conclusion based on the proximity of the samples on the PCA plot, which is not very convincing. More careful analysis of the bulk RNA seq data sets they have generated for key marker genes will be more convincing (for example, a heatmap with selected genes would be a helpful representation). As mentioned above, a straight-forward and not time consuming experiment (given that it was assessed for a maximum of 72 hrs) would be to repeat the culture of NCCs and stain for mitotic markers, and quantify the number of positively stained cells over total cell numbers. Furthermore, it is not that demanding to add an experimental condition of less severe hypoxia in this assay. Without underestimating how time consuming this would be, a major lack of experimental validation of the key genes they identify as important across all conditions may be the limitation of the study (this would be the difference between correlation and a probable underlying mechanism). This can be circumvented by more extensive reference to in situ data sets from mouse or existing data sets of single cell and spatial transcriptomicsA suggested targeted knock-down (for example with siRNA, shRNA or CRISPR) to validate a few of the key genes revealed as important could take a few months, with an estimated cost up to 5,000 euros per targeted gene and replicate. On methods, replicates and statistics: The experimental methods and approach are described efficiently and seem reproducible.All biological and technical replicates are of a minimum of N=3 from independent experiments and statistical tests have been run in all cases.

    Minor comments:

    One of the key implications of NCCs in palate formation is interaction with orofacial epithelial cells, which the authors also mention. It may be interesting to check if any signaling pathways involved in this crosstalk are affected under hypoxic conditions in their existing data sets of bulk RNA SEQ. This can be done by using available algorithms such as CellChat (Jin et al. 2021; Jin, Plikus, and Nie 2023), which has been reported to work also in bulk RNA seq data analysis (according to GitHub). The authors could mine the literature for existing RNA sequencing data that include osteoblasts, chondrocytes and epithelial cells (Ozekin, O'Rourke, and Bates 2023; Piña et al. 2023).

    Additionally, another process that may be affected is EMT (epithelial-to-mesenchymal-transition) and is possible to assess by re-analysis of bulk RNA-seq data while focusing on key genes implicated in this process (i.e. E-cadherin, vimentin, EpCAM, Snail, Twist, PRRX1). Lastly, when the authors report on the significantly up- or down-regulated genes, it may be interesting to categorize them by ligands, receptors, intracellular molecules and transcription factors (and use separate plots to visualize them). While a big focus of the manuscript are down-regulated genes, less emphasis was given in upregulated genes (other than the response to hypoxia gene module).

    The authors are referencing extensively and accurately existing studies in the field and the manuscript is exceptionally well-written, with only a few points of limited clarity or increased complexity. Such an example is when the authors refer to OFC risk genes, because it is not clearly stated how the referenced studies reached their conclusions (for example, are they mouse studies, do they involve mutants, are any of these studies based on GWAS on human cohorts). This matter would significantly improve the flow of the text and highlight the importance of the study and their findings. The figures could be redesigned to be more intuitive to interpret. For example, using violin plots and heatmaps, as discussed, and including references or re-analysis/re-use of existing spatial transcriptomics and in situs for marker genes.

    In all cases where there is a comparison of gene expression levels, violin plots would be a better representation of up- and down-regulated genes (i.e. selected genes from Fig1K, comparison of gene expression between normoxic and hypoxic NCCs, Fig 2G when analyzing chondrogenesis and the respective analysis for osteoblasts and smooth muscle cells, as well as when comparing the three fate-biasing conditions to identify common genes that are misregulated).

    References:

    Barriga, Elias H., Patrick H. Maxwell, Ariel E. Reyes, and Roberto Mayor. 2013. "The Hypoxia Factor Hif-1α Controls Neural Crest Chemotaxis and Epithelial to Mesenchymal Transition." The Journal of Cell Biology 201 (5): 759-76. https://doi.org/10.1083/jcb.201212100.

    Jin, Suoqin, Christian F. Guerrero-Juarez, Lihua Zhang, Ivan Chang, Raul Ramos, Chen-Hsiang Kuan, Peggy Myung, Maksim V. Plikus, and Qing Nie. 2021. "Inference and Analysis of Cell-Cell Communication Using CellChat." Nature Communications 12 (1). https://doi.org/10.1038/s41467-021-21246-9.

    Jin, Suoqin, Maksim V. Plikus, and Qing Nie. 2023. "CellChat for Systematic Analysis of Cell-Cell Communication from Single-Cell and Spatially Resolved Transcriptomics." bioRxiv. https://doi.org/10.1101/2023.11.05.565674.

    Ozekin, Yunus H., Rebecca O'Rourke, and Emily Anne Bates. 2023. "Single Cell Sequencing of the Mouse Anterior Palate Reveals Mesenchymal Heterogeneity." Developmental Dynamics : An Official Publication of the American Association of Anatomists 252 (6): 713-27. https://doi.org/10.1002/dvdy.573.

    Piña, Jeremie Oliver, Resmi Raju, Daniela M. Roth, Emma Wentworth Winchester, Parna Chattaraj, Fahad Kidwai, Fabio R. Faucz, et al. 2023. "Multimodal Spatiotemporal Transcriptomic Resolution of Embryonic Palate Osteogenesis." Nature Communications 14 (September):5687. https://doi.org/10.1038/s41467-023-41349-9.

    Scully, Deirdre, Eleanor Keane, Emily Batt, Priyadarssini Karunakaran, Debra F. Higgins, and Nobue Itasaki. 2016. "Hypoxia Promotes Production of Neural Crest Cells in the Embryonic Head." Development 143 (10): 1742-52. https://doi.org/10.1242/dev.131912.

    Significance

    Several pieces of evidence have pointed to hypoxia as an environmental factor contributing to congenital orofacial clefts, ranging from studies in mouse to observations in human. The authors are doing an excellent job in putting this information together and the question they are trying to answer is of high importance, given the prevalence of such congenital syndromes. In terms of the methods and model employed, there are some limitations, related to the choice of a mouse cell line over one from human, the severe hypoxia induced (over a more mild), and the conditions of directed differentiation not allowing for simultaneous examination of more complex lineage transitions. The methods as a whole are not that up-to-date, given the single cell and multiplexed transcriptomic advances the last couple of decades, advanced bioinformatics that could be used in combination with in vitro lineage tracing methods.

    The audience this work will reach are neural crest experts, developmental biologists, and potentially clinical doctors. The general public outreach of such a paper is also diverse, as more focus and visibility is required for the individuals affected by those syndromes and their families.

    Reviewer's expertise: mouse neural crest lineage and multipotency, lineage tracing, single cell transcriptomics, NGS, immunofluorescence, molecular methods (RNA, DNA based). Limited expertise with in vitro studies.

  6. Review Commons

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    Referee #1

    Evidence, reproducibility and clarity

    Title: Hypoxia impedes differentiation of cranial neural crest cells into derivatives relevant for craniofacial development

    Synopsis: Cleft lip w/ or w/o cleft palate is the second-most common birth defect worldwide. Defects are often traceable to cranial neural crest cells through genetics or environmental factors. Schmid and coauthors focus on the environmental factor of hypoxia and investigate the effects of hypoxic conditions on the ability of CNCCs to differentiate and migrate. They performed RNA-seq analysis with qRT-PCR validation for specific markers and show that hypoxia appears to repress differentiation without markedly affecting proliferation. Hypoxic conditions did not demonstrated significant perturbations in cell proliferation; however, chondrocyte, osteoblast, and smooth muscle differentiation was significantly reduced for cell lines cultured under hypoxia. Bulk RNA-seq and PCA revealed dysregulation of genes implicated in cytoskeletal integrity (such as actin γ-2), neural crest cell migration (hedgehog co-receptor brother of CDO) and amino acid metabolism (cysteine dioxygenase), which Schmid and colleagues termed OFC risk genes.

    Major comments

    • The authors performed qRT-PCR validation for markers of differentiation and hypoxia, with a major absence of VEGF and HIF1a. The paper would be strengthened by mention of these factors, especially by qRT-PCR or Western blot.
    • Please provide justification of selection 0.5% as their hypoxic condition or perhaps repeat experiments in a less extreme environment to see if their conclusions still hold true.
    • standard immunohistochemistry or histology of differentiated cells would strengthen the authors' claims of reduced differentiation under hypoxic conditions, e.g., Alcian blue, alk-phos or Alizarin red, and smooth muscle actin or other indicator.
    • The authors identify a few genes that appear down-regulated in all three differentiation conditions. If it is within the scope of the study, it would strengthen the claim of these genes' function to show the effect of knock-down or knock-out for validation.
    • Another major critique lies in the initial claim that proliferation of O9-1 cells is not significantly impacted by hypoxia. In figures 1E-H, photograms of the cells cultured 24 -72 hours and quantifications of live vs dead cells are shown as evidence for this argument. However, the increased density of cells in normoxic conditions may be a confounding variable in this assay. It would be interesting for the researchers to assess the percent of dead vs alive cells between normoxic and hypoxic conditions when the plates reach equivalent densities.
    • At end of Fig 1 section authors attempt to tie phenotypes observed in a cell line in vitro to the complex biological processes. They are not comparable and in vivo models would be better suited for these types of comparisons.
    • Fig 2: if qRT-PCR did not show statistically different results between experimental and control groups why move on to bulk RNA seq?
    • Fig 5: hypoxia this intense is going to affect broad range of biological processes and genes. Finding a few genes that are affected in extreme hypoxia that are also risk genes is highly unlikely. How can the authors be assured that these overlaps are actually significant and not just by chance?
    • Would appreciate discussion on how examination of neural crest is relevant for OFC, as most animal models of OFC demonstrate the pathogenesis in embryonic epithelium or periderm, not in the neural crest. Defects in neural crest are associated with other congenital craniofacial anomalies such as craniosynostosis or complex (Tessier) clefts, not the typical orofacial cleft. Please revise rationale of study, interpretation of data and Discussion to specifically state how neural crest cells are involved in the pathogenesis of orofacial cleft.

    Minor comments

    • The author should replace "Final proof" in the introduction with "further evidence supporting."
    • Authors are inconsistent when referring to Figures- sometimes they capitalize (i.e. 1J) and other times they leave lower case (i.e. 1i). Needs to be consistent throughout. Figures are not numbered
    • In figures authors would sometimes list 21% O2 first then 0.5% O2 or vice versa. (i.e. Fig on page 21 panels I, J, K). Needs to be consistent.
    • Figures on pages 28, 29, 30 panel J and page 31 panel F: there is no legend on what the scale/measurement is for the difference in expression level other than it ranges from -1 to +3.
    • Will the authors please comment on the one normoxic sample in Figure 1I that did not cluster with the others? Did this meet the standards to merit exclusion as an outlier?
    • The authors refer to DEG as deregulated genes; while not strictly incorrect, the more standard usage is "differentially expressed genes." Please address.

    Significance

    This work on neural crest cells and hypoxia are biologically and clinically significant.

  7. Version published to 10.1101/2024.09.10.610634v1 on bioRxiv