Fat body-derived cytokine Upd2 controls disciplined migration of tracheal stem cells in Drosophila

Joint Public Reviews:

Summary

In this manuscript, Dong et al. study the directed cell migration of tracheal stem cells in Drosophila pupae. The authors study how the directionality of these cells is regulated along the dorsal trunk. They show that inter-organ communication between the tracheal stem cells and the nearby fat body plays a role in posterior migration. They provide compelling evidence that Upd2 production in the fat body and JAK/STAT activation in the tracheal stem cells play a role. Moreover, they show that JAK/STAT signalling might induce the expression of apicobasal and planar cell polarity genes in the tracheal stem cells which appear to be needed to ensure unidirectional migration. Finally, the authors suggest that trafficking and vesicular transport of Upd2 from the fat body towards the tracheal cells might be important.

Strengths

The manuscript is well written and presents extensive and varied experimental data to show a link between Upd2-JAK/STAT signaling from the fat body and tracheal progenitor cell migration. The authors provide convincing evidence that the fat body, located near the trachea, secretes vesicles containing the Upd2 cytokine and that affecting JAK-STAT signaling results in aberrant migration of some of the tracheal stem cells towards the anterior. Using ChIP-seq as well as analysis of GFP-protein trap lines of planar cell polarity genes in combination with RNAi experiments, the authors show that STAT92E likely regulates the transcription of planar cell polarity genes and some apicobasal cell polarity genes in tracheal stem cells which appear to be needed for unidirectional migration. The work presented here provides some novel insights into the mechanism that ensures polarized migration of tracheal stem cells, preventing bidirectional migration. This might have important implications for other types of directed cell migration in invertebrates or vertebrates including cancer cell migration. Overall, the authors have substantially improved their manuscript since the first submission but there are still some weaknesses.

Weaknesses

Overall, the manuscript lacks insights into the potential significance of the observed phenotypes and of the proposed new signaling model. Most of our concerns could be dealt with by adjusting the text (explaining some parts better and toning down some statements).

(1) Directional migration of tracheal progenitors is only partially compromised, with some cells migrating anteriorly and others maintaining their posterior migration, a quite discrete phenotype. The strongest migration defects quantified in graphs (e.g. 100 μm) are not shown in images, since they would be out of frame, it would be beneficial to see them. In addition, the consequence of defects in polarized migration on tracheal development is not clear and data showing phenotypes on the final trachea morphology in pupae are not explained nor linked to the previous phenotypes.

(2) Some important information is lacking, such as the origin of mutant and UAS-RNAi lines, which are not reported in the material and methods. For instance, mutants for components of the JAK-STAT pathway are used but not described. Are they all viable at the pupal stage? Otherwise, pupae would not be homozygous mutants. From the figure legend, it seems that the Stat92EF allele has been used, which is a point mutation, thus not leading to an absence of protein. If the hopTUM allele has been used, as mentioned in the legend, it is a gain-of-function allele. Thus, the authors should not conclude that "The aberrant anterior migration of tracheal progenitors in the absence of JAK/STAT components led to impairment of tracheal integrity and caused melanization in the trachea (Figure 3-figure supplement 1E-I)".

(3) The authors observe that tracheal progenitors display a polarized distribution of Fat that is controlled by JAK-STAT signaling. However, this conclusion is made from a single experiment using only 3 individuals with no statistics. This is insufficient to support the claim that "JAK/STAT signaling promotes the expression of genes involved in planar cell polarity leading to asymmetric localization of Fat in progenitor cells", as mentioned in the abstract, or that "the activated tracheal progenitors establish a disciplined migration through the asymmetrical distribution of polarity proteins which is directed by an Upd2-JAK/STAT signaling stemming from the remote organ of fat body."

(4) The authors demonstrate that Upd2 is transported through vesicles from the fat body to the tracheal progenitors. It remains somewhat unclear in the proposed model how Upd2 activates JAK-STAT signaling. Are vesicles internalized, as it seems to be proposed, and thus how does Upd2 activate JAK-STAT signaling intracellularly? Or is Upd2 released from vesicles to bind Dome extracellularly to activate the JAK-STAT pathway? Moreover, it is not clear nor discussed what would be the advantage of transporting the ligand in vesicles compared to classical ligand diffusion.

Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, Dong et al. study the directed cell migration of tracheal stem cells in Drosophila pupae. The migration of these cells which are found in two nearby groups of cells normally happens unidirectionally along the dorsal trunk towards the posterior. Here, the authors study how this directionality is regulated. They show that inter-organ communication between the tracheal stem cells and the nearby fat body plays a role. They provide compelling evidence that Upd2 production in the fat body and JAK/STAT activation in the tracheal stem cells play a role. Moreover, they show that JAK/STAT signalling might induce the expression of apicobasal and planar cell polarity genes in the tracheal stem cells which appear to be needed to ensure unidirectional migration. Finally, the authors suggest that trafficking and vesicular transport of Upd2 from the fat body towards the tracheal cells might be important.

Strengths:

The manuscript is well written. This novel work demonstrates a likely link between Upd2JAK/STAT signalling in the fat body and tracheal stem cells and the control of unidirectional cell migration of tracheal stem cells. The authors show that hid+rpr or Upd2RNAi expression in a fat body or Dome RNAi, Hop RNAi, or STAT92E RNAi expression in tracheal stem cells results in aberrant migration of some of the tracheal stem cells towards the anterior. Using ChIP-seq as well as analysis of GFP-protein trap lines of planar cell polarity genes in combination with RNAi experiments, the authors show that STAT92E likely regulates the transcription of planar cell polarity genes and some apicobasal cell polarity genes in tracheal stem cells which appear to be needed for unidirectional migration. Moreover, the authors hypothesise that extracellular vesicle transport of Upd2 might be involved in this Upd2-JAK/STAT signalling in the fat body and tracheal stem cells, which, if true, would be quite interesting and novel.

Overall, the work presented here provides some novel insights into the mechanism that ensures unidirectional migration of tracheal stem cells that prevents bidirectional migration. This might have important implications for other types of directed cell migration in invertebrates or vertebrates including cancer cell migration.

Weaknesses:

It remains unclear to what extent Upd2-JAK/STAT signalling regulates unidirectional migration. While there seems to be a consistent phenotype upon genetic manipulation of Upd2-JAK/STAT signalling and planar cell polarity genes, as in the aberrant anterior migration of a fraction of the cells, the phenotype seems to be rather mild, with the majority of cells migrating towards the posterior.

We agree that the phenotype is mild, as perturbing JAK/STAT signaling in the progenitors specifically affects the coordinated migration of the cells rather than alters their direction or completely blocks migration. Our data indicate that inter-organ communication ensures coordinated behavior of the progenitor cells, although the differential responses exhibited by individual cells represent an interesting unresolved issue that awaits future in-depth investigation.

While I am not an expert on extracellular vesicle transport, the data presented here regarding Upd2 being transported in extracellular vesicles do not appear to be very convincing.

We performed additional PLA experiments which support the interaction between Upd2 and the core components of extracellular vesicles (revised Figure 8). Furthermore, we performed electron microscopy to visualize the Lbm-containing vesicles in fat body (Figure 8-figure supplement 1D).

These data are now provided in the revised manuscript.

Major comments:

(1) The graphs showing the quantification of anterior (and in some cases also posterior migration) are quite confusing. E.g. Figure 1F (and 5E and all others): These graphs are difficult to read because the quantification for the different conditions is not shown separately. E.g. what is the migration distance for Fj RNAi anterior at 3h in Fig5E? Around -205micron (green plus all the other colors) or around -70micron (just green, even though the green bar goes to -205micron). If it's -205micron, then the images in C' or D' do not seem to show this strong phenotype. If it's around -70, then the way the graph shows it is misleading, because some readers will interpret the result as -205. Moreover, it's also not clear what exactly was quantified and how it was quantified. The details are also not described in the methods. It would be useful, to mark with two arrowheads in the image (e.g. 5 A' -D') where the migration distance is measured (anterior margin and point zero).

Overall, it would be better, if the graph showed the different conditions separately. Also, n numbers should be shown in the figure legend for all graphs.

We apologize for those inappropriate presentation and insufficient description and thank you for kindly pointing them out. We used different colors to represent different genotypes, and the columns were superimposed. we chose to show the quantification in different conditions separately in the revised Figures. The anterior migration distance for Fj RNAi is around 70 µm.

We now provided detailed description in the revised methods. For migration distance measurement, we took snapshots at 0hr\ 1hr\ 2hr and 3hr, and measured the distance from the starting point (the junction of TC and DT) to the leading edge of progenitor clusters. The velocity formula: v=d (micrometer)/t (min). As you kindly suggested, we indicated the anterior margin and point zero in the corresponding panels. We have added n number in the legends.

(2) Figure 2-figure supplement 1: C-L and M: From these images and graph it appears that Upd2 RNAi results in no aberrant anterior migration. Why is this result different from Figures 2D-F where it does?

The fat body-expressing lsp2-Gal4 was used in Figure 2-figure supplement 1C-L and Figure 2D-F, while trachea specific btl-Gal4 was used in Figure 2-figure supplement 1K-L. The lsp2-Gal4-driven but not btl-Gal4-driven upd2RNAi causes aberrant anterior migration, suggesting that fat bodyderived Upd2 plays a role. We have further clarified this in the text.

(3) Figure 5F: The data on the localisation of planar cell polarity proteins in the tracheal stem cell group is rather weak. Figure 5G and J should at least be quantified for several animals of the same age for each genotype. Is there overall more Ft-GFP in the cells on the posterior end of the cell group than on the opposite side? Or is there a more classic planar cell polarity in each cell with FtGFP facing to the posterior side of the cell in each cell? Maybe it would be more convincing if the authors assessed what the subcellular localisation of Ft is through the expression of Ft-GFP in clones to figure out whether it localises posteriorly or anteriorly in individual cells.

We staged the animals, measured several animals for each genotype and provided the quantifications in the revised manuscript. The level of Ft-GFP is higher in the cells at the frontal edge. We tried to examine the expression of Ft-GFP at single-cell level. However, this turned out to be technically difficult because the tracheal stem cells are not regularly arranged as epithelial cells and the proximal-distant axis of the tracheal stem cells remains unclear. We thus decided to measure the fluorescence signal of groups of stem cells along the DT regardless of their individual polarity within cells.

(4) Regarding the trafficking of Upd2 in the fat body, is it known, whether Grasp65, Lbm, Rab5, and 7 are specifically needed for extracellular vesicle trafficking rather than general intracellular trafficking? What is the evidence for this?

In our experiments, knocking down rab5, rab7, grasp65 or lbm in trachea using btl-Gal4 did not cause abnormality in the disciplined migration, which excludes their intracellular contribution in the trachea (Figure 7-figure supplement 1). Perturbation of Grasp65 or Lbm in fat body increased intracellular upd2-containing vesicles, indicating that intracellular production is functional (Figure 6J). The Grasp65 is specifically required for Upd2 production. Lbm, Rab5 and Rab7 are important of vesicle trafficking. Our conclusion does not pertain to extracellular or intracellular compartment.

(5) Figure 8A-B: The data on the proximity of Rab5 and 7 to the Upd2 blobs are not very convincing.

The confocal images indicate the proximity of Rab5 and Rab7 to the Upd2 vesicles. We interpret the proximity together with the results from Co-IP and PLA data (Figure 8E-K).

(6) The authors should clarify whether or not their work has shown that "vesicle-mediated transport of ligands is essential for JAK/STAT signaling". In its current form, this manuscript does not appear to provide enough evidence for extracellular vesicle transport of Upd2.

Lbm belongs to the tetraspanin protein family that contains four transmembrane domains, which are the principal components of extracellular vesicles. We show that Lbm interacts with Upd2. The JAK/STAT signaling depends on the Upd2 in the fat body as well as vesicle trafficking machinery. Furthermore, we performed electron microscopy and show the presence of Lbm-containing vesicles in fat body (Figure 8-figure supplement 1D).

(7) What is the long-term effect of the various genetic manipulations on migration? The authors don't show what the phenotype at later time points would be, regarding the longer-term migration behaviour (e.g. at 10h APF when the cells should normally reach the posterior end of the pupa). And what is the overall effect of the aberrant bidirectional migration phenotype on tracheal remodelling?

We observed that the integrity of tracheal network especially the dorsal trunk was impaired, which may be due to incomplete regeneration (Figure 3-figure supplement1E-I).

(8) The RNAi experiments in this manuscript are generally done using a single RNAi line. To rule out off-target effects, it would be important to use two non-overlapping RNAi lines for each gene.

We validated the phenotype using several independent RNAi alleles.

Reviewer #2 (Public review):

Summary:

This work by Dong and colleagues investigates the directed migration of tracheal stem cells in Drosophila pupae, essential for tissue homeostasis. These cells, found in two nearby groups, migrate unidirectionally along the dorsal trunk towards the posterior to replenish degenerating branches that disperse the FGF mitogen. The authors show that inter-organ communication between tracheal stem cells and the neighboring fat body controls this directionality. They propose that the fat body-derived cytokine Upd2 induces JAK/STAT signaling in tracheal progenitors, maintaining their directional migration. Disruption of Upd2 production or JAK/STAT signaling results in erratic, bidirectional migration. Additionally, JAK/STAT signaling promotes the expression of planar cell polarity genes, leading to asymmetric localization of Fat in progenitor cells. The study also indicates that Upd2 transport depends on Rab5- and Rab7-mediated endocytic sorting and Lbm-dependent vesicle trafficking. This research addresses inter-organ communication and vesicular transport in the disciplined migration of tracheal progenitors.

Strengths:

This manuscript presents extensive and varied experimental data to show a link between Upd2JAK/STAT signaling and tracheal progenitor cell migration. The authors provide convincing evidence that the fat body, located near the trachea, secretes vesicles containing the Upd2 cytokine. These vesicles reach tracheal progenitors and activate the JAK-STAT pathway, which is necessary for their polarized migration. Using ChIP-seq, GFP-protein trap lines of planar cell polarity genes, and RNAi experiments, the authors demonstrate that STAT92E likely regulates the transcription of planar cell polarity genes and some apicobasal cell polarity genes in tracheal stem cells, which seem to be necessary for unidirectional migration.

Weaknesses:

Directional migration of tracheal progenitors is only partially compromised, with some cells migrating anteriorly and others maintaining their posterior migration.

Our results suggest that Upd2-JAK/STAT signaling is required for the consistency of disciplined migration. Although only a few tracheal progenitors display anterior migration, these cells lose the commitment of directional movement. We acknowledge that the phenotype is moderate.

Additionally, the authors do not examine the potential phenotypic consequences of this defective migration.

We examined the long-term effects of the aberrant migration and observed an impairment of tracheal integrity and melanized tracheal branches (Figure 3-figure supplement1E-I).

It is not clear whether the number of tracheal progenitors remains unchanged in the different genetic conditions. If there are more cells, this could affect their localization rather than migration and may change the proposed interpretation of the data.

We examined the progenitor cell number in bidirectional movement samples and control group. The results show that cell number does not exhibit a significant difference between control and bidirectional movement groups (Figure 3-figure supplement 1).

Upd2 transport by vesicles is not convincingly shown.

We performed additional PLA experiments to further support the interaction between Upd2 and the core components of extracellular vesicles. Furthermore, we performed electron microscopy and show the presence of Lbm-containing vesicles in fat body (Figure 8-supplement 1D). Additional experiments such as colocalization and Co-IP assay and better quantification are provided in the revised manuscript (see revised Figure 8).

Data presentation is confusing and incomplete.

We used different colors to represent different genotypes, and the columns were superimposed. we changed the graphs to show the quantification in different conditions separately. We revised data presentation to avoid confusing.

Reviewer #3 (Public review):

Summary:

Dong et al tackle the mechanism leading to polarized migration of tracheal progenitors during Drosophila metamorphosis. This work fits in the stem cell research field and its crucial role in growth and regeneration. While it has been previously reported by others that tracheal progenitors migrate in response to FGF and Insulin signals emanating from the fat body in order to regenerate tracheal branches, the authors identified an additional mechanism involved in the communication of the fat body and tracheal progenitors.

Strengths:

The data presented were obtained using a wide range of complementary techniques combining genetics, molecular biology, quantitative, and live imaging techniques. The authors provide convincing evidence that the fat body, found in close proximity to the trachea, secrete vesicles containing the Upd2 cytokine that reach tracheal progenitors leading to JAK-STAT pathway activation, which is required for their polarized migration. In addition, the authors show that genes regulating planar cell polarity are also involved in this inter-organ communication.

Weaknesses:

(1) Affecting this inter-organ communication leads to a quite discrete phenotype where polarized migration of tracheal progenitors is partially compromised. The study lacks data showing the consequences of this phenotype on the final trachea morphology, function, and/or regeneration capacities at later pupal and adult stages. This could potentially increase the significance of the findings.

Regarding your kind suggestion, we examined the long-term effects of the aberrant migration and observed the impairment of tracheal integrity and melanized tracheal branches (Figure 3-figure supplement1E-I).

(2) The conclusions of this paper are mostly well supported by data, but some aspects of data acquisition and analysis need to be clarified and corrected, such as recurrent errors in plotting of tracheal progenitor migration distance that mislead the reader regarding the severity of the phenotype.

We used different colors to represent different genotypes, and the columns were superimposed. we changed the graphs to show the quantification in different conditions separately. We thank you for kindly pointing it out.

(3) The number of tracheal progenitors should be assessed since they seem to be found in excess in some genetic conditions that affect their behavior. A change in progenitor number could lead to crowding, thus affecting their localization rather than migration capacities, thereby changing the proposed interpretation. In addition, the authors show data suggesting a reduced progenitor migration speed when the fat body is affected, which would also be consistent with a crowding of progenitors.

We examined the cell number in bidirectional movement samples and control group. We examined cell number and cell proliferation and observed that there was no significance between control and bidirectional movement groups (Figure 3-figure supplement 2).

(4) The authors claim that tracheal progenitors display a polarized distribution of PCP proteins that is controlled by JAK-STAT signaling. However, this conclusion is made from a single experiment that is not quantified and for which there is no explanation of how the plot profile measurements were performed. It also seems that this experiment was done only once. Altogether, this is insufficient to support the claim. Finally, a quantification of the number of posterior edges presenting filopodia rather than the number of filopodia at the anterior and posterior leading edges would be more appropriate.

We staged the animals, measured several animals for each genotype and provided the quantifications in the revised manuscript. The level of Ft-GFP is higher in the cells at the frontal edge. We tried to examine the expression of Ft-GFP at single-cell level. However, this turned out to be difficult due to the fact that the tracheal stem cells are not regularly patterned as epithelial cells and the proximaldistant axis of tracheal stem cells is not well defined. We thus decided to measure the fluorescence signal of groups of stem cells along the DT regardless of their individual polarity.

(5) The authors demonstrate that Upd2 is transported through vesicles from the fat body to the tracheal progenitors where they propose they are internalized. Since the Upd2 receptor Dome ligand binding sites are exposed to the extracellular environment, it is difficult to envision in the proposed model how Upd2 would be released from vesicles to bind Dome extracellularly and activate the JAK-STAT pathway. Moreover, data regarding the mechanism of the vesicular transport of Upd2 are not fully convincing since the PLA experiments between Upd2 and Rab5, Rab7, and Lbm are not supported by proper positive and negative controls and co-immunoprecipitation data in the main figure do not always correlate to the raw data.

We use molecular modeling to show that Upd2 and Lbm intermingle, and Upd2 is not entirely encapsulated in vesicles (Figure 8-supplement 1E). We performed PLA experiments using the animals not expressing upd2-Cherry as negative control (Figure 8 E-J). We corrected the Co-IP panel and apologize for this error.

Recommendations for the authors:

Reviewer #1 (Recommendations for the authors):

Minor comments:

(1) Figure 1-figure supplement 1: E: How was the migration velocity assessed? By live imaging individual cells or following the cell front of the group? Over what time period? Do the data points in the graph correspond to individual cells or the cell group? It would be important to show confocal images that go along with this quantification.

We took snapshots of pupae at 0hr\ 1hr\ 2hr and 3hr, and measured the distance covered by the migrating progenitor cells from the start place (the junction of TC and DT) to the leading edge of progenitor groups. We then calculated the migration rate by v=d (micrometer)/t (min). As the progenitor cells revolve around and migrate along the DT, tracking single tracheoblast through intact cuticle is technically challenging. We have therefore measured the leading edge as a proxy to the whole cell group. We agree with you that time-lapse imaging is favorable for analysis of migration.

(2) Figure 1-figure supplement 1: F: Why is there Gal80ts in the genotype? (and in Figure 1H). Also, what pupal age was used for this quantification?

Expression of hid and rpr in L3 stage impaired fat body integrity and adipocyte abundance, and caused lethality. Gal80ts was used for controlling the expression of rpr.hid. The pupal at 0hr APF were used in EdU experiment.

(3) Figure 2C: what is shown in the 6 columns (why 3 each for control and rpr/hid)?

We conducted 3 replicates of each group for control and rpr.hid.

(4) In the methods, several Drosophila stocks are listed as 'source:" from a particular person (e.g. Dr Ma). Please list the real source of this stock, e.g. Bloomington stock number, or the lab and publication in which the stock was originally made.

We provide the information on these stocks in the revised methods.

(5) The SKOV3 carcinoma cell and S2 cell work is not described in the methods.

We added detailed description of this experiment in the revised method-Cell culture and transfection.

(6) Figure 6 (F) 'Bar graph plots the abundance of Upd2-mCherry-containing vesicles in progenitors.' What does abundance mean? What was quantified, the number of vesicles, or the mean intensity? This is also not mentioned in the methods.

We counted the number of Upd2-mCherry-containing vesicles in fat body cells and trachea progenitors and added the description of measurement in the method.

(7) There are a few language mistakes throughout the manuscript. E.g.

(a) Line 117 and other places: Language: 'fat body' should be 'the fat body'.

We thank you for pointing out these errors and corrected it accordingly.

(b) Line 1276 Language mistakes: 'Video 1 3D-view of confocal image stacks of tracheal progenitors and fat body. Scale bar: 100 μm. Genotypes: UAS-mCD8-GFP/+;lsp2-Gal4,P[B123]-RFP-moe/+.' :stacks and genotypes should be singular.

We fixed these errors and thank you for kindly pointing them out. We also proofread the entire manuscript to assure accuracy.

(8) In general, it is hard to figure out the exact genotypes used in experiments. This is mostly not written very clearly in the figure legends. E.g. Figure 2: genotype for A-C missing in figure legend (is B from control animals?)

We added genotypes in the figure legends. For Figure 2, A and C lsp2-Gal4,P[B123]-RFP-moe/+ for control, UAS-rpr-hid/+;Gal80ts/+;lsp2-Gal4,P[B123]-RFP-moe/+ for rpr.hid; B from control animals.

Reviewer #2 (Recommendations for the authors):

Major comments:

(1) The phenotype resulting from Upd2 downregulation by RNAi is subtle and shown by unconvincing images. In addition, these phenotypes are analyzed using only one RNAi line.

We used two independent alleles of upd2RNAi from THFC (THU1288 and THU1331), and observed similar phenotype. For RNAi experiments, we always use multiple independent alleles.

(2) The authors should analyze the phenotypic consequences of directional migration changes. Is there an effect on tracheal remodeling?

We observed that the integrity of tracheal network especially the dorsal trunk was impaired and that melanized tracheal branches were present, which may be due to incomplete regeneration (Figure 3figure supplement1E-I).

(3) The number of tracheal progenitors should be quantified, as some genetic conditions may affect cell numbers, as is apparent in some panels.

We examined cell number and cell proliferation and observed that there was no significance between control and bidirectional movement groups (Figure 3-figure supplement 1).

(4) The data on PCP protein distribution are unconvincing, unquantified, and insufficient to support one of the main conclusions of the study, which is stated in the abstract: "JAK/STAT signaling promotes the expression of genes involved in planar cell polarity, leading to asymmetric localization of Fat in progenitor cells."

We staged the animals, measured several animals for each genotype and provided the quantifications in the revised manuscript. The level of Ft-GFP is higher in the cells at the frontal edge. We tried to examine the expression of Ft-GFP at single-cell level. However, this turned out to be difficult due to the fact that the tracheal stem cells are not regularly patterned as epithelial cells and the proximaldistant axis of tracheal stem cells is not well defined. We thus decided to measure the fluorescence signal of groups of stem cells along the DT regardless of their individual polarity.

Minor comments:

(1) Language should be revised. In many places in the manuscript, starting in line 113, "fat body" should be "the fat body".

Thank you for pointing out this error. We corrected it accordingly.

(2) Genotypes used in experiments should be described.

We added all the genotypes. We proofread the entire manuscript to complete the figure legends for genotypes.

(3) Line 67, the reference to "The progenitor cells reside in Tr4 and Tr5 metameres and start to move along the tracheal branch" should include (Chen and Krasnow, Science 2014).

We added the reference in the manuscript.

(4) Line 1081, Figure 7 Legend. "Bar graph plots the abundance of Upd2-mCherry-containing vesicles" Abundance is the number of vesicles? The graph displays the average number of vesicles? Please explain and describe the quantification.

The bar graph represents the number of Upd2-mCherry-containing vesicles in different conditions. We quantified the number of vesicles per area.

(5) Figure 1 (I-J) What is shown on the panels? Progenitors marked with? This information is not present in the figure or figure legend. Same for Figure 2 (D-E).

Figure 1I-J show the vector of migrating progenitors. We added the information in the legends. The tracheal cells were labeled by nls-mCherry in Figure 1I-J. In Figure 2D-E, the progenitors were marked with P[B123]-RFP-moe.

(6) Figure 3 Q, Stat92E-GFP values in the graph are not well-explained. What do the numbers in the y-axis refer to?

y-axis represents the intensity of Stat92E-GFP normalized to control. We have changed the y-axis label to ‘normalized Stat92E-GFP intensity’ in the legends.

(7) In general, figures and figure legends must be revised. Sometimes stainings are not well-defined, some scale bars are missing and plots do not say what the values are.

We apologized for inadequate information and have revised the figures and legends accordingly.

Reviewer #3 (Recommendations for the authors):

Several points should be addressed by the authors in order to improve their manuscript.

Major points:

(1) The phenotype obtained from decreasing the inter-organ signaling is quite discrete. It is further weakened by the fact that the images chosen to illustrate the measures are not really convincing. No image at 1h APF shows any clear anterior migration. Based on the scale, most of the images at 3h APF do not show a striking difference compared to the control, and in any case, stronger phenotypes would be missed anteriorly since they would thus be out of frame. In addition, at 3h APF, progenitors migrating anteriorly from Tr5 position get mixed with those migrating posteriorly from Tr4 so it is not clear how measurements were made. Given that most phenotypes are observed upon the use of RNAis, it is possible that phenotypes are weak due to persistent gene expression. Using null clones for dome, hop, or stat in progenitors could therefore aggravate the phenotypes and support further the significance of the study. Finally, assessing the consequences of compromised fat body-tracheal communication on trachea morphology, function, and regeneration later in pupal development and on adult flies would also help strengthen the importance of the findings.

We agree with you that anteriorly migrated Tr5 progenitors adjoining Tr4 progenitor hinders measurements and that mutants may give stronger phenotype than RNAi lines. We only measured Tr4 progenitors (instead of Tr5) when assessing anterior migration. Thus, we performed experiments using mutant alleles, which gave aberrant migration of tracheal progenitors (Figure 3-figure supplement1A-D). We can now show that the integrity of tracheal network especially dorsal trunk was impaired, which may be due to incomplete regeneration (Figure 3-figure supplement1E-I).

(2) Although the authors did not observe defects in tracheal progenitor proliferation, progenitors seem to be present in excess in some key genetic background (e.g, upon expression of rpr.hid, statRNAi, Rab-RNAi or in the presence of BFA). This excess could be the result of another mechanism than proliferation (recruitment of extra progenitors since it is not clear how they originate, defect in apoptosis...) and could impact the localization of progenitors, those being pushed anteriorly as a consequence of crowding. A proper characterization of tracheal progenitor number would thus help to discriminate between defects in migration or crowding. This point could also be addressed by performing individual tracking of tracheal progenitors, to find out whether each progenitor is indeed migrating in the wrong direction or if the movement assessed by the global tracking method that is used is just a consequence of progenitor excess.

We examined the cell number in bidirectional movement samples and control group. The results show that there was no significance between control and bidirectional movement groups (Figure 3figure supplement 1). We also tried to follow every progenitor, but were unable to obtain convincing results with P[B123]-RFP-moe, as tracking single tracheoblast through intact cuticle is technically challenging.

(3) Regarding the ChIP-seq experiment, an explanation of why choosing the "establishment of planar polarity" family should be provided since data indicate a quite low GeneRatio. Indeed, the "cell adhesion" family seems a more obvious candidate, which would be further supported by the fact that the JAK-STAT pathway has been shown to affect cell adhesion components such as ECadherin and FAK (Silver and Montell 2001, Mallart et al 2024). Also, have these known targets of JAK-STAT signaling been found in the ChIP-seq data? Since filopodia polarization is affected in tracheal progenitors when JAK-STAT signaling is decreased, the same question also applies to enabled, which is involved in filopodia formation and has been recently identified as a target of JAK-STAT signaling.

As you kindly suggested, we tested a number of cell adhesion-related genes such as E-Cadherin (shg), fak, robo2 and enabled (ena). We did not observe an apparent aberrancy in the migration of tracheal progenitors (Figure 5-supplement 1J).

(4) Data investigating PCP protein distribution is not convincing, not quantified, and not sufficient to draw one of the main conclusions of the study, which is even written in the abstract "JAK/STAT signaling promotes the expression of genes involved in planar cell polarity leading to asymmetric localization of Fat in progenitor cells."

We better quantified the abundance of Ft in in the progenitors in the frontal edge and those lagging behind. The traces plot multiple replicates in the figures. The level of Ft-GFP is higher in the cells at the frontal edge.

(5) Overall, the figures together with their caption and/or the material and methods section lack some important information for the reader to fully understand the data. In addition, some errors are found in multiple plots throughout the article and must be corrected. Here are some examples:

According to your suggestion, we revised legends and methods section to include sufficient information.

(a) Migration distance plots from Figure 3E do not match the data presented in the source data file. It seems that, when creating the plot, instead of superimposing the bars, bars were stacked. This should be corrected for all migration distance plots from Figure 3E onward, including in supplementary figures.

We apologized for misleading representation. We revised it accordingly and show the quantification in different conditions separately.

(b) The number of analyzed flies and/or clusters of tracheal progenitors from different flies should be stated for all quantification or observations made on images. This information is lacking for all migration distance plots, for progenitor migration tracking (Figure 1 I, J), for DIPF reporter in Figure 2J, for plot profiles (Figure 5G, J), for Upd2-Rab5/Rab7/Lbm co-detections, PLA, CoIP, and lbm-pHluorin experiments. This also applies to RNA seq, ChIP seq, and surface proteomics, for which the number of pupae and number of replicates is not indicated.

We changed the graphs to show the quantification and n number in different conditions separately.

We also added the n number of replicates in methods.

(c) How quantifications were performed is not sufficiently explained. For example, the reference point for migration distance measurement is not defined, and neither is whether the measures were made on fixed or live imaging samples. In fluorescence intensity measurements and Upd2 vesicle counting, information on whether measures were made on a single z slice or on a projection of several z slices should be stated together with what ROI and which FIJI tool for quantification were used. For plot profiles, the same information regarding z slices misses together with how the orientation, the thickness, and the length of the line were chosen, and again the number of times the experiment was conducted should be mentioned and error bars should appear on graphs.

We thank this reviewer for the suggestions which help clarify the methodology of our experiments and improve presentation of our data. We have made the changes according to the suggestions and modified our methods section and the related figures to incorporate these changes.

For measuring the migration distance of tracheal progenitors, we took snapshots of living pupae at 0hr\ 1hr\ 2hr and 3hr APF, and measured the migration distance of tracheal progenitors from the start place (the junction of TC and DT) to the leading edge of progenitor groups.

For the measurements of fluorescent intensity of stat92E-GFP and DIPF, we took z-stack confocal images of samples and quantified the fluorescent intensity using FIJI. Specifically, intensity was quantified for regions of interest, using the Analysis and Measurement tools. To quantify Upd2mCherry vesicles, z-stack confocal images of fat body were taken and the cell counting function of FIJI was used to measure the vesicle number.

To quantify the fluorescent intensity of in vivo tagged Ds, Ft and Fj proteins, a single z slice was used. The expression level of the protein was assessed as the integrated fluorescent intensity normalized to area.

For the measurement of Ft-GFP distribution, a single z slice of the progenitors immediately proximal to the DT was imaged. An arbitrary line was drawn along the migration direction from the starting TC-DT junction to the leading front (the length of the line corresponds to the distribution range of tracheal stem cell clusters). Then, fluorescent intensity along the line was automatically calculated with the imbedded measurement function of Zeiss confocal software.

Minor points:

(1) In several instances, the authors generalize that stem cells migrate to leave their niche, but this is not the case for all stem cells.

The phenomenon that stem cells leave their niche when they are activated is commonly observed. We interpreted the general mechanism from our system of tracheal stem cells. We fully agree with you that it may not be the case for all stem cells. We modified the text accordingly.

(2) Line 122 -a reference paper or an image showing the expression pattern of the lsp2-Gal4 driver is missing.

We added the reference in the manuscript.

(3) Line 136 - The term "traces of individual progenitors" is overstated and should be reformulated as the method used does not seem to be individual cell tracking.

We rephrased accordingly in the revised manuscript.

(4) Line 146 - Fat body and tracheal progenitors are qualified as interdependent organs, in which aspect do tracheal progenitors affect the fat body?

Current knowledge suggests a close inter-organ crosstalk between trachea and fat body: The fly trachea provides oxygen to the body and influences the oxidation and metabolism of the whole body. When the trachea is perturbed, the body is in hypoxia, which causes inflammatory response in adipose tissue as an important immune organ (Shin et al., 2024).

(5) Line 163 - Not all the genes tested are cytokines, so the sentence should be reformulated. In addition, in supplementary Fig2-1 C-J, the KD of hh seems to abolish completely tracheal progenitor migration, which is not commented on.

According to your suggestion, we revised the description on information of the genes tested. We added comments in the revised manuscript regarding phenotypes of hh knockdown.

(6) Line 180 - Conclusion is made on Dome expression while using a dome-Gal4 construct, which does not necessarily recapitulate the endogenous pattern of dome expression, so it should be reformulated. Ideally, dome expression should be assessed in another way. Also, it is not clear whether GFP is present only in progenitors since images are zoomed.

We revised statement and provided larger view of dome>GFP that shows an enriched expression in the tracheal progenitors (Figure 2-figure supplement 2E), an expression pattern that is consistent with FlyBase.

(7) Line 199 - Is it upd-Gal4 or upd2-Gal4 that is used? Since the conclusion of the experiment is made on upd2, the use of upd-gal4 would not be relevant. If upd2-gal4 is used, it should be corrected. In general, the provenance of the Gal4 lines should be provided. In addition, a strong GFP signal in the trachea is visible on the image in Supplementary Figure 2-2F but not commented on and seems contradictory with the conclusion mentioning that fat body and gut are the main source of Upd2 production.

We removed data obtained from the use of this irrelevant upd-Gal4 line.

(8) Figures:

- Figure 1 G, H - Scale bar is missing.

We added it accordingly.

- Figure 1 I, J - The information on the staining is missing.

We added it in the revised manuscript.

- Figure 2A - Providing explanations of the terms "Count" and "Gene ratio" in the caption would be helpful for readers who are not used to this kind of data. In addition, the color code is confusing since the same color is used for the selected gene family and for high p-values (the same applies to other similar graphs).

Gene ratio refers to the proportion of genes in a dataset that are associated with a particular biological process, function, or pathway. Count indicates the number of genes from input gene list that are associated with a specific GO term. We used redness to indicate a smaller p-value and a higher significance.

- Figure 2 B, C - What does the color scale represent? What do the columns in C correspond to, different time points, different replicates?

The color scale represents the normalized expression. The columns in C correspond to different replicates of control and rpr.hid.

- Figure 2 F - The error bars on the 3h APF posterior bars are missing.

We added error bars accordingly.

- Figure 2 G - The legend "Down-Stable-Up" is in comparison to what?

The control group was generated from the reaction without H2O2. The comparison was relative to the control group.

- Figure 2 J - The specificity of the DIPF tool that has been created should be validated in other tissues displaying known JAK-STAT activity and/or in conditions of decreased JAK-STAT signaling. In addition, the added value of the tool as compared to the JAK-STAT activity reporter used later, which has been well characterized, is not obvious.

We added the signal of DIPF in fat body and salivary gland, both of which harbor active JAK/STAT signaling (Figure 2-figure supplement 2F-H). As opposed to the well characterized Stat92E-GFP reporter that assays the downstream transcription activity, the DIPF reporter measures the upstream event of receptor dimerization.

- Figure 3 I-P - Reporter tool validation in Images I-L could be moved to supplementary data. In images M-P, staining of nuclei and/or membranes would be useful to assess cell integrity.

We revised the figures accordingly.

- Figure 3Q and similar plots in the following figures do not explain the normalization performed and how it can be higher than 1 in control conditions.

In these figures, we normalized the signal relative to control groups, e.g., The value of Stat92E-GFP in btl-GFP control group was set to 1 in the previous Figure 3Q (revised Figure 3-supplementary

Figure B-J).

- Figure 4C - These representations lack explanations to be fully understood by a broad audience.

The figure showing that Stat92E binding was detected in the promoters and intronic regions (the orange peaks) of genes functioning in distal-to-proximal signaling, such as ds, fj, fz, stan, Vang and fat2. We added the information in figure legend according to your suggestion.

- Figure 5 K,L - What is the x-axis missing, together with the method of tracking used?

The x-axis refers to time of recording from a t stack series with a time interval of 5 min. We revised method section and provide detailed procedure of this experiment.

- Figures 6 and 8- The overall figures lack a wider view of the cells/tissues/organs and/or additional staining to understand what is presented.

We showed preparation of fat body. In order to obtain the high resolution of vesicles, we used high magnification. We now added wider views of the tissues under investigation (e.g. Figure 6-figure supplement 1).

- Figure 6 D,E - The scale bar is missing.

We added it accordingly.

- Figure 8 O-S - What is the blue staining?

The blue staining shows DAPI-stained nuclei. We have added the information in the legend.

- PLA experiments can give a lot of non-specific background. What kind of controls have been used in Figure 8 F-J? Negative controls should be done on cells that do not express upd2-mCherry using both antibodies to detect non-specific background, which does not usually appear completely black.

If possible, a positive control using a known protein interacting with Rab5-GFP should be included.

We used the control samples without one of the primary antibodies in previous Figure 8. In the revised Figure 8, we conducted experiment as you suggested with controls that do not express upd2mCherry (Figure 8 E-J).

- Co-IP experiments - The raw data file for blots is quite hard to read through. Some legends are not facing the right lane and some blots presented in the main figure are difficult to track since several blots are presented in the raw data file. e.g.

(a) Raw blot for Figure 8 K: the band for mCherry in the IP anti-GFP blot (lane one in K) is not convincing, it is not distinguishable from other aspecific bands. On the reverse IP presented only in raw data, on the input from blot IB anti-mCherry, both lanes present exactly the same bands at 72kb when one of the lanes corresponds to extract from flies not expressing upd2-mCherry.

We thank you for pointing out the incorrect labels. We apologized for the errors and corrected it accordingly.

(b) Raw blot for Figure 8 L: on the input blot IB anti-GFP, there is a band corresponding to Rab7-GFP in the lane of the extract from flies not expressing Rab7-GFP.

We corrected it.

(c) Raw data for Figure 8 M: on the last blot, legends are missing above the input Ib anti-GFP blot.

We added the missing legends in the figure.

Shin, M., Chang, E., Lee, D., Kim, N., Cho, B., Cha, N., Koranteng, F., Song, J.J., and Shim, J. (2024). Drosophila immune cells transport oxygen through PPO2 protein phase transition. Nature 631, 350-359.