Symmetry breaking and fate divergence during lateral inhibition in Drosophila

  1. Minh-Son Phan
  2. Jang-mi Kim
  3. Cara Picciotto
  4. Lydie Couturier
  5. Nisha Veits
  6. Khallil Mazouni
  7. François Schweisguth

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Abstract

Lateral inhibition by Notch mediates the adoption of alternative cell fates amongst groups of initially equipotent cells, leading to the formation of regular patterns of cell fates in many tissues across species. Genetic and molecular studies have established a model whereby an intercellular negative feedback loop serves to amplify small stochastic differences in Notch activity, thereby generating ordered salt-and-pepper patterns. In Drosophila , lateral inhibition selects Sensory Organ Precursor cells (SOPs) from clusters of proneural cells that are competent to become neural through the expression of proneural transcription factors. When and how symmetry breaking occurs during lateral inhibition remains, however, to be addressed. Here, we have used the pupal abdomen as an experimental model to study the dynamics of lateral inhibition in Drosophila . Using quantitative live imaging, we monitored the accumulation of the transcription factor Scute (Sc), used as a surrogate for proneural competence and adoption of the SOP fate. We found that fate symmetry breaking occurred at low Sc levels and that fate divergence was not preceded by a prolonged phase of low or intermediate level of Sc accumulation. The relative size of the apical area did not appear to bias this fate choice. Unexpectedly, we observed at low frequency (10%) pairs of cells that are in direct contact at the time of SB and that adopt the SOP fate. These lateral inhibition defects were corrected via cellular rearrangements. Analysis of Sc dynamics in wild-type and genetically mosaic pupae further revealed that cell-to-cell variations in Sc levels promoted fate divergence, thereby providing experimental support for the intercellular negative feedback loop model.

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    Reply to the reviewers

    *Reviewer #1 *

    1. The authors conclude that RFP-Ac expression is restricted to emerging SOPs and surroundings cells at 18h APF, indicating that Ac is activated later than Sc. Can the authors provide images for RFP-Ac expression at 10h and 16h APF similar to GFP-Sc as shown in their figures. Do the SOPs that contain high levels of both Ac and Sc (as some SOPs have Sc expression but not Ac) undergo fate divergence and SB faster than the SOPs containing higher levels of only Sc?

    We are now showing the expression pattern of GFP-SC and RFP-Ac/GFP-Ac in fixed samples stained also for E-cad at 13h, 16h and 18h APF (Fig 1I-K' and Fig S1E-G'). Ac and Sc were found to be activated around the same time. However, Ac appeared to accumulate at lower levels than Sc prior to SOP selection in the central domain of the ADHN (Fig 1J-K'). We also confirmed that Ac was more strongly expressed in SOPs. Additionally, SOPs appeared to accumulate both Ac and Sc, i.e. SOPs with high levels of GFP-Sc also showed a strong RFP-Ac signal (Fig S1H-H'). Finally, since RFP-Ac was not detectable in living pupae, possibly due to the rapid turn-over of Ac and the slow maturation of RFP, we could not study more precisely the relative dynamics of Ac and Sc. For the same reason, we could not address whether the rate of fate divergence (measured using GFP-Sc) varied with the level of Ac.

    2. It would be interesting to see the spatial and temporal dynamics of Ac and Sc in Notch mutants or even Notch dynamics in Sc and Ac mutants to better understand the progression fate divergence and its effect on lateral inhibition in real time.

    Following the reviewer's suggestion, we examined the expression pattern of NRE-deGFP, a Notch activity reporter, in ac sc double mutant pupae at 16h and 24h APF (Fig S3A-D). This showed that the initial pattern of NRE-deGFP at 16h APF (signal detected in posterior ADHN cells as well as in the ADHN) did not depend on Ac and Sc. By contrast, the second phase of NRE-deGFP expression (in cells of the proneural ADHN domain, around emerging SOPs) was found to depend on the activity of Ac and Sc. Thus, strong Notch activation observed in cells surrounding emerging SOPs was found to depend on the activity of Ac-Sc, presumably because Ac and Sc are required for SOP specification and SOPs produce Delta, serving as the local source to activate Notch (see also our response to reviewer 3, point #6). Thus, since NRE-deGFP was not up-regulated in the proneural ADHN domain of sc10-1 ac3 mutant pupae, a quantitative analysis of the dynamics of NRE-deGFP may not be informative.

    The reviewer also suggested us to study the dynamics of GFP-Sc in Notch mutants. One can easily predict that most Notch mutant cells would accumulate GFP-Sc, as observed in the notum (PMID: 28386027). Therefore, analysis of fate symmetry breaking is unlikely to be useful in that context. Likewise, a FDI analysis would not be relevant. From a technical point of view, live imaging of GFP-Sc would have to be performed in Notch mutant clones. This is because RNAi against Notch (strong 10xUAS-Notch hp2 construct, PMID: 19487563) driven by escargot-Gal4 to knock down Notch in larval histoblasts only led to a partial loss of Notch function (our unpublished data). Generation of Notch mutant clones in the abdomen would require constructing appropriate GFP-Sc Notch FRT recombinant chromosome as well as generating a new FRT GFP-Sc chromosome with an infrared marker (not currently available) to compare the relative dynamics of GFP-Sc in wild-type and mutant cells. In sum, this proposed experiment would take a significant amount of time and is unlikely to shed new light. Given that this experiment is not essential to support the claims of the paper and that it is not clear to us what would be learnt from this experiment, we opted for not performing this experiment.

    Minor comments

      1. In figure 1F and F', the authors mention GFP-Sc is not expressed prior to 14h, however, there is still GFP signal detected in their imaging. Can the authors comment what would be the cause of this GFP signal or was it due to non-specific background signal during their imaging analysis?*

    We thank the referee for raising this issue. Yes, a strong autofluorescence signal was detected prior to the onset of GFP-Sc expression. We provide below the results of our analysis of the autofluorescence signal (Fig R1) relative to the nuclear signal (Fig R2), and how normalization of the signal was used to measure the specific GFP-Sc signal.

    Analysis of the autofluorescence signal over time

    To estimate the autofluorescence signal, we measured the average intensity of the signal acquired in the GFP channel for each frame and plotted these values over time. The results are shown in Fig R1 below:

    *Fig R1: temporal profile of the autofluorescence signal *

    Each measurement corresponds to the average intensity measured in the GFP channel over the entire field at each z-section and for each time point. Mean and SD values of measured are shown over time in black and grey, respectively. Time is in frame number (dt is 2.5 min). The data shown above corresponds to movie 1 (see also Fig 2).

    This plot indicates that the autofluorescence signal was progressively bleached. We therefore excluded from our analysis the first 50 time points when the autofluorescence signal was initially strong. No nuclear GFP-Sc signal was detectable in these first 50 frames in the cells of the central area of the ADHN which are studied here (see Fig 2A', t=1:12, time frame #29).

    While revising the manuscript, we realized that t=0 corresponded to two distinct time points in the first version of our manuscript: it corresponded to the onset of imaging in Fig 2A-D', and to t=2:08 (time frame #51) in all other figures showing data following removal of the first 50 time points. We have now fixed this issue and are presenting all data with t=0 corresponding to the onset of imaging.

    Analysis of the nuclear fluorescence signal over time

    To detect the nuclear GFP-Sc signal, we measured the average intensity of the signal acquired in the GFP channel (raw intensity values corresponding to the sum of the GFP-Sc and autofluorescence signals) in segmented nuclei (in 3D, within the entire z-stack). These values were plotted over time (pink curve in Fig R2 below; the autofluorescence is plotted in black, as in Fig R1, for the sake of comparison). This showed that the intensity of the signal measured in nuclei was initially identical to the mean intensity measured across the entire field of view, indicative of autofluorescence only. A specific increase in signal intensity in nuclei (relative to the entire field of view) was detectable after 2h of imaging (time frame 48 in Fig R1; dt is 2.5 min). Importantly, mean intensity values of the autofluorescence signal appeared to be approximately 10-fold stronger than the mean intensity associated with the nuclear GFP-Sc signal.

    Fig R2: temporal profile of the GFP-Sc signal

    *The plot in pink corresponds to the average intensity in the GFP channel (raw intensity values corresponding to the GFP-Sc and/or autofluorescence signals) per nucleus (within the entire z-stack) for each time point. Mean and SD values measured in each nucleus are shown over time (in pink; these data correspond to movie 1; shown also in Fig 3). This plot (pink) should be compared with the plot shown in Fig R1 (also in black in Fig R2). The intensity difference between the pink and black curves was attributed to the specific GFP-Sc signal. *

    Signal normalization and analysis of the GFP-Sc signal

    In our study, we normalized the GFP-Sc signal by dividing the averaged value measured in each single nucleus (data corresponding to the pink curve in Fig R2) by the mean value of the signal measured at the same time point in the same channel in the entire image stack (data corresponding to the black curve in Fig R1/R2). Given the low intensity of the GFP-Sc signal, and the small number of pixels corresponding to Scute-expressing nuclei over the entire field of view, this value should closely reflect the autofluorescence noise. Thus, the background autofluorescence signal should be close to 1. This was experimentally verified by measuring the normalized intensity values of the PDHN nuclei that did not express Scute: a mean intensity value of 0.96 +/- 0.10 was measured (at time frame #51; see Fig R1 below). In contrast, the normalized GFP-Sc values measured several hours before SB were found to be close to 1.1 (see Fig 3D). Whether these values reflect very low levels of nuclear GFP-Sc that cannot be detected visually or result from imperfect normalization of the signal remain unclear. Given the intensity and non-uniformity of the autofluorescence signal, we cannot exclude the latter. For this reason, we chose to not over-interpret the initial low intensity values of GFP-Sc.

    In the materials and methods, the authors mention that prior to imaging the larvae and pupae are grown at 18, 21 or 25{degree sign}C. Is there a reason why the larvae and pupae are grown at different temperatures for different experiments? Can the authors specify (i.e. in the figure legends) in which experiments different temperatures were used?

    Larvae and pupae were grown at different temperatures for convenience, i.e. to adapt the time interval between staging at 0h APF and mounting for live imaging. Indeed, it is much easier to obtain 10-14h APF pupae by collecting staged pupae at 0h APF the day before and incubating them overnight at lower temperature to slow-down development. However, all live imaging experiments were performed at 23-25{degree sign}C, and we have no reason to think that this prior incubation would affect the process studied here.

    The citations need to have a better format as they show up as each citation within a single bracket which makes it a little hard to read when multiple references are cited in a single sentence. fixed

    In the abstract, the sentence 'Unexpectedly, we observed at low frequency (10%) pairs of cells that are in direct contact at the time of SB'. SB should be replaced with "Symmetry breaking", as it appeared for the first time in the manuscript and should be written out in full. fixed

    Throughout the manuscript there are instances where the abbreviations are written in full with the abbreviation in brackets after they have already been introduced in the introduction which can be changed to just the abbreviation itself. fixed

    In the discussion on page 11, 'our observation...', our needs to be changed to Our. fixed

    7. It would be nice to have arrow heads or dotted lines around the cells or areas on interest in both, all the figures and movies, so that it will be easier to follow the results. The videos have a lot of background due to fragmented apoptotic nuclei, etc. as mentioned by the authors, hence arrow heads or dotted lines would bring viewers focus on the areas of interest.

    fixed (see for instance Fig 1D, Fig 2A, Fig 5B, Fig 7A, Fig S3D, etc...)

    8. It would be helpful to have anterior - posterior axis (i.e. with an arrow) shown on top of all the figures.

    In our earlier version, we indicated that 'In this and all other figures, dorsal is up and anterior is left' in the legend of Fig 1B. We have now moved this sentence at the end of Fig 1 to have it more apparent. Additionally, the AP axis is now clearly indicated in Fig 1C. We believe that it is not necessary to repeat this orientation in all figures.

    Scale bars are missing in all figures, videos, and figure legends. Added

    Only movies 1 and 3 are referenced in the text. All movies are now referenced in the text

    Keeping the colors in the movies and figures consistent and same would be helpful. For example, Movie 2 Histone3.3-mIFP marker is in blue but in figure 3 it is in magenta. fixed (H3.3-mIFP in magenta in this movie, now numbered 3)

    As mentioned above, it would be helpful if the authors have arrow heads or dotted lines around the cells or areas of interest in both the figures and movies for better representation of their data. For example, movie 1 shows a larger area of imaging than shown in figure 2A, which makes it hard to follow the cells of interest in the movie.

    An additional movie corresponding to the SOP shown in Fig 2A is now provided (new movie 2).

    --

    Reviewer #2

    1. Despite "symmetry breaking" being the main focus of the paper, in the Introduction, the authors do not explain what this term means and do not provide any description of this process. This is a critical point that makes understanding of the goals of the paper difficult. Therefore, the authors are encouraged to provide more information and a clear description of this term/phenomenon. We thank the reviewer for this suggestion, we are now stating in the introduction what symmetry breaking means in the context of lateral inhibition: 'To describe and study the process of SOP selection, we studied fate SB. The latter refers to the transition point when one cell, the future SOP, starts to stably accumulate a higher level of GFP-Sc relative to its immediate neighbors.'

    The role of Achaete in the story is not clear. Even though both factors are required for SOP determination, the authors mainly focus on Scute, so it is not very clear what the role of Achaete in this process is, if there is any. As shown in the paper, Achaete is expressed later when heterogeneity is promoting cell fate divergence. Is Achaete maybe contributing to cell heterogeneity/ cell fate divergence?

    We thank the reviewer for raising this point. We now show in Fig S1A-D that abdominal bristles develop in a protein null allele of sc (scM6 ) as well as in an ac mutant corresponding to a 45 kb deletion that removes ac but not sc (PMID: 16216235))__. Together with our analysis of __sc10-1 ac3 __mutant flies, we can now conclude that __Sc and Ac act redundantly for SOP specification in the pupal abdomen. We have also further studied the expression of Ac relative to Sc and E(spl)HLH-m3 (see our response above to point #1 of reviewer 1). We fully agree with the reviewer that cell-to-cell variations in Ac expression might contribute to proneural heterogeneity and SB. This is now briefly discussed.

    *Minor points: *

      1. Symmetry Breaking (SB) should be abbreviated in the Abstract. The authors initially use the full term without abbreviation, and only on page 5, the abbreviation is finally defined; however, it should be introduced much earlier.*

    fixed

    The second-to-last sentence in the abstract, "These lateral inhibition defects were correlated via cellular rearrangements," is unclear regarding what defects the authors are referring to.

    This sentence was rewritten: 'Live imaging showed that these patterning defects were corrected via cellular rearrangements associated with global tissue fluidity, not via cell fate change.'

    For clarity, being more specific in the text in regards to description of the figure panels would be beneficial (e.g. page 3 Fig 1C-E); referring to C-E together makes it hard to understand what does each panel shows.

    fixed

    In many instances, the movies are not properly referenced (e.g. on page 5, third row simply states "movies"), making it difficult to discern which movie should be checked. On page 8, when authors refer to movie 3, they likely meant movie 5.

    fixed

    Figure S1 requires some corrections.

    We thank the reviewer for helping us improve the presentation of our results.

    The authors use the short name "scute" initially and then switch to the shortened version "sc'.

    fixed

    Additionally, the nlsRFP (blue) is difficult to see; adjusting the levels or changing colors/showing separate channels may improve visibility.

    The authors mention clone borders, but none are shown. It would greatly help to outline the borders in all figures.

    The ubiquitous nlsRFP marker is now shown in magenta in Fig S1I that now shows only 2 channels to outline the ADHN (white dotted line) and the clones (yellow dotted lines).

    We also outlined the clone borders in Fig 4C,C'.

    Genotypes of the samples should be indicated, and clarification is needed regarding what "n" represents (number of cells, clones, or flies).

    The genotype studied in Fig S1 and Fig 4 (which is the only complex genotype studied here) is now indicated in the Methods section. We have clarified what the different 'n' meant, in Fig 4 (see text) and elsewhere (see legend of Fig S2 for instance).

    What do the arrows in the panel B show?

    Thanks for pointing this out. The arrows in Fig S1I' indicate Cut/Hnt-positive cells (SOPs) within the clones (as now explained in the legend).

    It is also recommended to display important channels as separate black and white images.

    Separate channels are now shown in Fig S1 and S3.

    Additionally, the use of RNAi against GFP instead of RNAi against scute should be justified; using RNAi GFP as the genotype on the graph could be interpreted as a control genotype rather than downregulation of scute.

    A RNAi construct against GFP was used because this construct was known to very efficient and specific. Indeed, a strong knock-down of GFP-Sc was obtained by this approach (see Fig 4C'). We did not test sc RNAi constructs in the context of GFP-Sc. To avoid confusion, we are now indicating Sc downregulation (gfp RNAi) in Fig 4C'.

    In the Figure 2 Legend, the authors use "std" as an abbreviation to define standard deviation. Typically, this is abbreviated as SD.

    fixed

    In Figure 4E, the authors do not explain on why there are points on the x-axis that correspond to a decimal number of cells.

    Since heterogeneity was calculated over a 20 min interval, we likewise calculated the number of neighbors over the same time interval. Thus, the number of neighbors for each SOP corresponds to an averaged value calculated over this time interval. This is now explained in the legend.

    --

    Reviewer #3

    1. First and foremost, the authors should state in the first paragraph of the Results that scGFP is a CRISPR knockin and thus it's the only source of Sc protein in the animals imaged (this is stated only in the Methods section). Thanks for this comment, we agree that this is one of the strengths of our work that we should emphasize. We now state in the results section: 'GFP-Sc is produced from the endogenous locus such that all Sc molecules produced in these pupae are GFP-tagged'

    The magnitude of the Sc increase should be commented on. Based on the intensity and FDI plots in Fig. 3B-E, an increase of 15-17% in the amount of Sc is suggested (the FDI plateaus at 0.08, which gives 1.08/0.92 = 1.17x the level of Sc in the SOP vs the surrounding cells). However, in the stills shown in Fig. 2BCD and in Fig. 3A, the intensity differential between SOPs and neighbors seems at least 100% (ie at least double the intensity, which would yield an FDI of >1/3 =0.33). Why is this high contrast never seen in the quantitative measurements?

    Thanks for asking about the fold change of GFP-Sc levels in SOPs, from SB to its plateau. This fold change can be seen in Fig 3D: the normalized value of GFP-Sc is 1.12 at SB, and 1.26 three hours after SB (when the FDI plateaus), indicative of a 2.2x fold increase of GFP-Sc in SOPs (0.26/0.12= 2.2, following background subtraction; see our detailed response to reviewer #1, minor point 1, about background signal analysis and normalization of the signal). This fold-change value is now indicated in the legend of Fig 3D. Obviously, this fold-change value is highly sensitive to signal normalization. Since the autofluorescence signal was stronger than the GFP-Sc signal (see Fig R2 above) and varied over time (due to bleaching; see Figs R1 and R2 above), we feel that this fold-change value should be taken with a grain of salt.

    From Fig. 2A-D it appears that the ScGFP fluorescence intensity is at the same level or weaker than nearby autofluorescence. Please state (1) how you confirmed that the histoblast nest has lower autofluorescence than the larval epidermis and (2) how you corrected for histoblast nest autofluorescence in your quantifications.

    As detailed above (our response to reviewer #1, minor point 1), the specific GFP-Sc signal is ten-times lower than the autofluorescence signal. We did not compare the autofluorescence signal produce by larval and imaginal cells (but note that larval epidermal cells had a stronger autofluorescence signal; see the yellow dots in Fig 2A). Normalization of the signal to correct for autofluorescence was explained in the Methods (and is also detailed above in our response to reviewer #1, minor point 1).

    The paradoxical result of Fig. S1B should be discussed. On the one hand it is stated that "Ac and Sc specify the fate of the Sensory Organ Precursor cells (SOPs)" (p.2) and on the other S1B shows SOP specification in the absence of Sc. Are the SOPs shown in Fig S1B rare exceptions? Do the authors believe that these rare exceptions are there because of inefficient RNAi (since in comparison with S1A, in the null condition almost no SOPs should be formed)? Or they are the SOPs in RNAi clones as rare as the occasional bristles in S1A?

    We do not see the result of Fig S1B as paradoxical but interpreted this result assuming that Ac and Sc were redundant for SOP determination. We now provide clear genetic evidence in support of this view (see our response above to reviewer #2, point 2). Otherwise, we found that RNAi is efficient (see loss of the GFP signal in clone in Fig. 4C'). In adult males, the density of bristles appeared to be quite normal over clonal patches of gfp RNAi cells (not shown), consistent with Ac being redundant with Sc

    One figure that is not straightforward to interpret is Fig. 4E. It plots ScGFP heterogeneity vs. number of RNAi neighbors. Each point in the plot must be an individual SOP (165 total). Therefore, its neighbors (the x-axis) should take integral (not decimal) values. How can a single SOP have a decimal number of RNAi neighbors, especially since heterogeneity was sampled over a 10min time-window, when not much cell rearrangement can take place? Please explain.

    Since heterogeneity was calculated over a 20 min interval, we likewise calculated the number of neighbors over the same time interval. Thus, the number of neighbors for each SOP corresponds to an averaged value calculated over this time interval. This is now explained in the legend: 'Note that the number of neighbors was likewise calculated over this time interval, and the resulting number of neighbors may not take an integral value.'

    *I found the discussion of the Notch reporter dynamics (Fig. 7) confusing in several places. *

    • (6a) Whereas it's clear that there is plenty of Notch signaling going on before SBN, the authors repeatedly imply that Notch signaling starts after SBN. For example, in the Results (p.9) they state "Thus, this quantitative approach failed to detect a phase of reciprocal Notch signaling during which proneural cluster cells would both send and receive a Delta-Notch signal prior to SOP emergence." The fact that the NRE-deGFP gave a robust signal before the start of the movies clearly means that mutual inhibition was going on for quite some time before SB. In fact, an FDI of 0 for >4h prior to SBN (Fig. 7G) means exactly this: that the level of Notch response among the cluster cells is equivalent ("mutual inhibition" lasts for at least 4h before SBN). (6b) In the first paragraph of this section (p.8) they comment that the pre-existence of Notch signaling is unexpected - why? I interpret it to simply be mutual inhibition (see above). Then they go on to quantitate the average Notch response intensity over the entire posterior ADHN (please define the borders the "posterior" ADHN). I question the informational value of this analysis (averaging over a large region), when Notch signaling is known to have intense local cell-to-cell variability (also evident in the stills shown in Fig. 7A,B,C).*

    We apologize for not describing well enough the data shown in Fig 7E, and for not explaining clearly our interpretation of the NRE-deGFP signal.

    While the observation of a strong NRE-deGFP signal indeed indicates that Notch signaling had been active prior to the time of observation (in this sense, Notch is indeed active long before SBN), this does not necessarily imply that Notch is still active at that time. This is because the deGFP protein produced by the NRE-deGFP reporter is stable relative to the time scale of the studied process. Its measured half-life in S2 cells cultured at 25{degree sign}C is 2h (PMID: 31140975). Based on this data, the NRE-deGFP signal is likely to remain detectable several hours after Notch signaling has been switched off. If the rate of production of deGFP is lower than its rate of degradation, then the NRE-deGFP signal is expected to progressively decay over time. We believe that this is what we observed in our movies: while a strong signal was detected over the posterior half of the ADHN at 14-15h APF, this signal decreased over time (Fig 7D). To interpret the temporal dynamics of NRE-deGFP signal in terms of instantaneous Notch activity, we examined the Rate of Change (ROC): an increase of the NRE-deGFP signal over time (positive ROC) would indicate that Notch activity is increasing (more precisely, the production rate of deGFP is higher than its rate of degradation), whereas a decrease (negative ROC) indicates that Notch becomes less active (or inactive if the rate of decrease approximates the decay rate of the deGFP protein). Our data shown in Fig 7D showed that the NRE-deGFP signal (measured in the area indicated with a dotted line in Fig 7A,B; this area was defined by the initial pattern of NRE-deGFP) decreased over time (negative ROC) between t=1 and t=6.5h. We therefore conclude that Notch signaling is decreasing to reach a minimum at t=~3.5h, indicating that the level of Notch activity is at its lowest around the time of SB. At this minimum, the decay rate corresponds to a protein half-life of 4.4h, which is not so different from the measured half-time of deGFP in S2 cells (particularly if one assumes a 1.4x difference between the decay rates measured at 22 and 25{degree sign}C, based on the known temperature-dependent speed of development). This is why we conclude that Notch signaling is very low at this stage. Additionally, no NRE-deGFP signal was detected before t=4:30h (movie 7) in the initially NRE-deGFP negative cells (located anterior to the area indicated with a dotted line in Fig 7A). This indicated that Notch was activated late in this area. Together, our observations are not consistent with the view that Notch mediates a strong mutual inhibition signal over a prolonged time interval prior to SB.

    To further study the pattern of Notch activity, we have monitored over time the accumulation pattern of GFP-tagged E(spl)m3-HLH (GFP-m3) (PMID: 31375669) in fixed sample (Fig S3F-G'). This confirmed that Notch was active in posterior ADHN cells and in the PDHN prior to 14h APF, i.e. prior to the onset of Ac and Sc, and that Notch activation extended to the central ADHN domain at 17-18h APF (Fig S3E-E' and G-G', and Fig 7I-I''), coinciding with SOP emergence.

    Otherwise, the reviewer is correct when stating that a FDI value close to 0 indicates that the level of measured fluorescence among the different cells of the considered cluster is similar. Such a FDI value would be measured if cells did not express NRE-deGFP or had decreasing but similar levels of NRE-deGFP. This FDI value does not, per se, imply that Notch is active.

    And then they move on to a (much more informative) cell-by-cell analysis, without even changing paragraphs, making it hard for the reader to follow. (6c) The conclusion at the end of the second paragraph (p. 9) "It also showed that SB was detected soon after the onset of Notch-mediated inhibitory signaling." is nowhere supported by data. If I understand well, SB refers to Sc and "the onset of Notch-mediated inhibitory signaling" refers to SBN (which is the onset of ASYMMETRY in Notch signaling, not the onset of Notch signaling, which has been going on for hours earlier). I don't see any data comparing SB with SBN. In fact, this is an important question to address (see below - comment 10).

    We apologize for the lack of clarity in our writing, we meant: "It also showed that SBN was detected soon after the onset of Notch-mediated inhibitory signaling."

    Yes, SBN refers to the onset of asymmetry in Notch signaling, as measured using NRE-deGFP. As explained above (but see also our response to point #7 below), our data do not provide evidence for a detectable Notch signal prior to SBN.

    We agree that comparing SB and SBN would be nice. Unfortunately, our current tools do not permit a detailed comparison (see our detailed response below, point #10).

    Mutual inhibition amongst neighboring cells has been proposed to involve (besides mutual Notch signaling) an increase in Sc levels in 2-3 cells in a cluster before the singularization of a single SOP. The authors seem rather biased against such a transient Sc hike based on their results in Fig. 2D, where the neighboring cells stay at rather constant basal Sc levels for several hours, while the Sc SB event happens. However, looking at an individual SOP in Fig. 2B, I do detect a mild hike in the pink curve right around SB in the blue curve. Could the average result from 160 SOPs (in Fig 2D) simply blur such transient Sc hikes, if they happen with different kinetics for different SOPs? Couldn't the 10% of SOP twins (shown in Fig. 6) represent a special case of this transient "subcluster" Sc hike? I would appreciate some discussion on this point. [Whether Sc is transiently upregulated or not, however, does not change my firm conclusion - from the data presented - that Notch-mediated mutual inhibition has been going on long before SBN.]

    First, our data are consistent with the notion that a few proneural cells progressively accumulate higher level of Scute prior to SB (as proposed above). Indeed, the moderate increase in both GFP-Sc levels and coefficient of variation values (GFP-Sc heterogeneity) seen prior to SB correspond to what the reviewer has in mind (higher levels of GFP-Sc in a few proneural cluster cells). We also appreciate the reviewer's comment about the plot shown in Fig 2D. However, we strongly feel that our quantitative analysis of a large dataset is a strength. Thus, we do not find useful to discretize a continuous process by introducing the notion of 'subclusters' of 2-3 cells. Likewise, we believe that it is more informative to focus our analysis on the entire dataset using average and SD values and do not wish to base our interpretation of the process based on selected tracks (the one shown in Fig 2B only served as an illustration of how we performed our analysis and has no interpretation value).

    The reviewer also states that "mutual inhibition amongst neighboring cells has been proposed to involve an increase in Sc levels in 2-3 cells in a cluster before the singularization of a single SOP". Since there is no published description of the pattern of accumulation of Scute in abdominal histoblats (to our best knowledge), we hypothesize that this statement applies to the proneural clusters in the developing wing disc. This is because the accumulation pattern of Sc has been studied in detail in that context by the Modollel and Carroll labs (PMID: 2044965, PMID: 2044964). However, their description of the accumulation pattern of Scute (in fixed samples, using anti-Sc antibodies) did not refer to sub-clusters of 2-3 cells. We would appreciate if the reviewer could direct us to the relevant published observation.

    Finally, we are not sure to follow the reviewer when she/he firmly concluded from our data that Notch-mediated mutual inhibition has been going on long before SBN. Instead, our data clearly showed that the ADHN region that produced SOPs exhibited two distinct NRE-deGFP patterns, with Notch signaling being active prior to imaging (i.e. prior to 14h APF) and decreasing to reach a minimum of Notch activation around 17h APF (i.e. around the time of SB, as determined by GFP-Sc imaging) in the posterior area of the ADHN.

    Thus, our data do not show that mutual inhibition does not take place in this tissue but rather imply that the phase of mutual inhibition (or competition) must be relatively short, or transient, and that competition amongst proneural cluster cells operate at low Notch and Sc levels (probably contrary to what many people have in mind).

    *Some minor points: *

      1. Please change Cad-GFP to Ecad-GFP or shg-GFP, as Cad misdirects to caudal.*

    Thanks, changed into Ecad-GFP and Ecad-mKate

    What is c in "(x,y,z,c,t) movies"? (a fifth independent variable?)

    c stands for channel. This is relatively standard nomenclature.

    The authors show that Sc displays a SB event leading to FDI of 0.08 and the Notch reporter displays another SB (SBN) leading to a much more pronounced FDI of -0.2. Are these two events (the hike of Sc levels and the plummeting of Notch signal) contemporaneous or does one precede the other? Having both tagged with GFP makes it impossible to image simultaneously, but the authors could register each reporter's dynamics relative to the time of SOP division (as done in Fig. 5C) to get a sense of their relative order.

    We do agree with the reviewer that it would be nice to be able to align in time these two data sets. Unfortunately, the temporal correlation between SB and the SOP division is too variable (4.7 +/- 1.1) to confidently align these two datasets using this event as a time reference. New tools are needed (see our response to point #11 below).

    Where in the above timeline is the SOP fate definitively adopted? neur-nlsGFP, Ac-RFP, m3Cherry and Sens detection in Figs. 1 and 7 give us a rough idea that these other markers appear around the time of Sc FDI peaking, around 3h after the initial SB. But this is not presented in an organized fashion - the reader collects this information sporadically. A reanalysis of the already existing data attempting to place these various markers in an integrated timeline would be of great importance in understanding the details of this cell fate specification process. Which is the earliest SB event? sc, neur or Notch? How long does it take from that early SB until definitive SOP markers (Sens) first appear?

    We agree with the reviewer, it would be interesting to extend the approach reported here for Scute to characterize SB and rate of FDI for other key factors governing the selection of SOPs. As pointed out by the reviewer (point #10 above), it would also be important to register in time these various events. Unfortunately, the maturation time of RFP, mCherry, FP670, etc... appeared to be too slow relative to the rapid turnover of the Ac, Sc and E(spl)-HLH factors prevented us from performing two-color imaging. Hence, current tools do not permit to determine which is the earliest SB event.

    More genetic perturbations could be performed to solidify the model of cell-cell communication during lateral inhibition. Two obvious ones come to mind: (a) How would the Sc-GFP dynamics change in a Notch-RNAi background? (b) How would the NRE-deGFP dynamics change in a sc-RNAi background?

    See our detailed response to reviewer #1, major point #2.

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    Referee #3

    Evidence, reproducibility and clarity

    Phan et al present their work on the dynamics of Sc accumulation and Notch signaling in the dorsal abdomen of Drosophila. They use live imaging to provide more detailed knowledge on a well-studied phenomenon of lateral inhibition, where proneural proteins (like Sc) promote a certain fate (like SOP) in groups of equivalent cells. The selection of individual SOPs among these equivalent cells depends on Delta-Notch signaling, which allows neighboring cells to communicate. Cells that accumulate higher levels of Sc acquire an increased ability to inhibit their neighbors and will ultimately become SOPs. This paradigm seems to be used time and again in arthropods and vertebrates alike and its central importance is witnessed by the fact that it has been under intense study over the last 3 decades. The present manuscript adds the temporal dimension to one instance that deploys this proneural-Notch interplay. The authors show that the timecourse from equivalence to singularized SOPs takes 3-8 hours (from 13 to 21 h APF) and is visible as an increase in Sc-GFP levels in one cell of the cluster. They calculated precisely the onset of this increase (which they term "symmetry breaking") and showed that Sc levels plateau approx. 3 h later, although some SOPs are faster than others in reaching that plateau. Sc increase is accompanied by Notch reporter decrease. The apical area of the cells does not seem to bias the level of Notch signaling/ Sc accumulation. What does seem to speed up the process is pre-existing heterogeneity in Sc (and Notch?) levels. Interestingly, when this process of lateral inhibition fails to singularize a single cell (resulting in two adjacent cells with high Sc levels), these two cells move apart by cellular rearrangements. During the 3h that the SOP upregulates its Sc levels after SB, its neighboring cells stay at relatively constant baseline Sc levels and only afterwards do they start reducing their own Sc-GFP. The authors have taken the trouble to collect live data for >100 SOPs in different experimental settings, so there is no doubt about their reproducibility and statistical robustness. In general, the figures are clear and self-explanatory. I found it hard to follow the text, however, and I have some suggestions for its improvement.

    1. First and foremost, the authors should state in the first paragraph of the Results that scGFP is a CRISPR knockin and thus it's the only source of Sc protein in the animals imaged (this is stated only in the Methods section).
    2. The magnitude of the Sc increase should be commented on. Based on the intensity and FDI plots in Fig. 3B-E, an increase of 15-17% in the amount of Sc is suggested (the FDI plateaus at 0.08, which gives 1.08/0.92 = 1.17x the level of Sc in the SOP vs the surrounding cells). However, in the stills shown in Fig. 2BCD and in Fig. 3A, the intensity differential between SOPs and neighbors seems at least 100% (ie at least double the intensity, which would yield an FDI of >1/3 =0.33). Why is this high contrast never seen in the quantitative measurements?
    3. From Fig. 2A-D it appears that the ScGFP fluorescence intensity is at the same level or weaker than nearby autofluorescence. Please state (1) how you confirmed that the histoblast nest has lower autofluorescence than the larval epidermis and (2) how you corrected for histoblast nest autofluorescence in your quantifications.
    4. The paradoxical result of Fig. S1B should be discussed. On the one hand it is stated that "Ac and Sc specify the fate of the Sensory Organ Precursor cells (SOPs)" (p.2) and on the other S1B shows SOP specification in the absence of Sc. Are the SOPs shown in Fig S1B rare exceptions? Do the authors believe that these rare exceptions are there because of inefficient RNAi (since in comparison with S1A, in the null condition almost no SOPs should be formed)? Or they are the SOPs in RNAi clones as rare as the occasional bristles in S1A?
    5. One figure that is not straightforward to interpret is Fig. 4E. It plots ScGFP heterogeneity vs. number of RNAi neighbors. Each point in the plot must be an individual SOP (165 total). Therefore, its neighbors (the x-axis) should take integral (not decimal) values. How can a single SOP have a decimal number of RNAi neighbors, especially since heterogeneity was sampled over a 10min time-window, when not much cell rearrangement can take place? Please explain.
    6. I found the discussion of the Notch reporter dynamics (Fig. 7) confusing in several places. (6a) Whereas it's clear that there is plenty of Notch signaling going on before SBN, the authors repeatedly imply that Notch signaling starts after SBN. For example, in the Results (p.9) they state "Thus, this quantitative approach failed to detect a phase of reciprocal Notch signaling during which proneural cluster cells would both send and receive a Delta-Notch signal prior to SOP emergence." The fact that the NRE-deGFP gave a robust signal before the start of the movies clearly means that mutual inhibition was going on for quite some time before SB. In fact, an FDI of 0 for >4h prior to SBN (Fig. 7G) means exactly this: that the level of Notch response among the cluster cells is equivalent ("mutual inhibition" lasts for at least 4h before SBN). (6b) In the first paragraph of this section (p.8) they comment that the pre-existence of Notch signaling is unexpected - why? I interpret it to simply be mutual inhibition (see above). Then they go on to quantitate the average Notch response intensity over the entire posterior ADHN (please define the borders the "posterior" ADHN). I question the informational value of this analysis (averaging over a large region), when Notch signaling is known to have intense local cell-to-cell variability (also evident in the stills shown in Fig. 7A,B,C). And then they move on to a (much more informative) cell-by-cell analysis, without even changing paragraphs, making it hard for the reader to follow. (6c) The conclusion at the end of the second paragraph (p. 9) "It also showed that SB was detected soon after the onset of Notch-mediated inhibitory signaling." is nowhere supported by data. If I understand well, SB refers to Sc and "the onset of Notch-mediated inhibitory signaling" refers to SBN (which is the onset of ASYMMETRY in Notch signaling, not the onset of Notch signaling, which has been going on for hours earlier). I don't see any data comparing SB with SBN. In fact, this is an important question to address (see below - comment 10).
    7. Mutual inhibition amongst neighboring cells has been proposed to involve (besides mutual Notch signaling) an increase in Sc levels in 2-3 cells in a cluster before the singularization of a single SOP. The authors seem rather biased against such a transient Sc hike based on their results in Fig. 2D, where the neighboring cells stay at rather constant basal Sc levels for several hours, while the Sc SB event happens. However, looking at an individual SOP in Fig. 2B, I do detect a mild hike in the pink curve right around SB in the blue curve. Could the average result from 160 SOPs (in Fig 2D) simply blur such transient Sc hikes, if they happen with different kinetics for different SOPs? Couldn't the 10% of SOP twins (shown in Fig. 6) represent a special case of this transient "subcluster" Sc hike? I would appreciate some discussion on this point. [Whether Sc is transiently upregulated or not, however, does not change my firm conclusion - from the data presented - that Notch-mediated mutual inhibition has been going on long before SBN.] Some minor points:
    8. Please change Cad-GFP to Ecad-GFP or shg-GFP, as Cad misdirects to caudal.
    9. What is c in "(x,y,z,c,t) movies"? (a fifth independent variable?)

    Significance

    The mechanism of proneural-Notch interplay is evolutionarily conserved, so this study of its temporal dynamics is valuable and will interest a broad audience in the field of animal developmental biology. The rich data collected by the authors should contain enough information to make a big contribution to the field, but the presentation in the manuscript stops a little short of that. The fact that Sc expression is highly dynamic was already known - now we have quantitative measurements of this variability. Same holds for Notch signaling. The authors should try to integrate their data better to make a complete timeline of events that leads to SOP specification, using the panoply of fluorescent markers at their disposal.

    1. The authors show that Sc displays a SB event leading to FDI of 0.08 and the Notch reporter displays another SB (SBN) leading to a much more pronounced FDI of -0.2. Are these two events (the hike of Sc levels and the plummeting of Notch signal) contemporaneous or does one precede the other? Having both tagged with GFP makes it impossible to image simultaneously, but the authors could register each reporter's dynamics relative to the time of SOP division (as done in Fig. 5C) to get a sense of their relative order.
    2. Where in the above timeline is the SOP fate definitively adopted? neur-nlsGFP, Ac-RFP, m3Cherry and Sens detection in Figs. 1 and 7 give us a rough idea that these other markers appear around the time of Sc FDI peaking, around 3h after the initial SB. But this is not presented in an organized fashion - the reader collects this information sporadically. A reanalysis of the already existing data attempting to place these various markers in an integrated timeline would be of great importance in understanding the details of this cell fate specification process. Which is the earliest SB event? sc, neur or Notch? How long does it take from that early SB until definitive SOP markers (Sens) first appear?
    3. More genetic perturbations could be performed to solidify the model of cell-cell communication during lateral inhibition. Two obvious ones come to mind: (a) How would the Sc-GFP dynamics change in a Notch-RNAi background? (b) How would the NRE-deGFP dynamics change in a sc-RNAi background?
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    Referee #2

    Evidence, reproducibility and clarity

    Understanding cell fate is crucial for various biological processes, including development, tissue regeneration, and disease progression. In this manuscript, colleagues in the team of François Schweisguth provide high-quality live cell observations demonstrating how SOP (Sensory Organ Precursor) cells are determined from a cluster of proneuronal cells via symmetry breaking (SB), which is key in the process of lateral inhibition. Although the process of lateral inhibition has been proposed long ago, no studies have been conducted to demonstrate it using live imaging. Using Drosophila abdominal epidermis as a model, the authors showed how the levels of the main neuronal determinants are expressed during SOP cell determination. The team uses a tagged version of one of the cell fate determinants, Scute, to follow the dynamics of this process, which is then further supported by genetic experiments showing that cell-to-cell variations in Scute expression levels promote fate divergence and patterning. This paper provides a new perspective on how dynamic expression of proneural factors determines cell fate acquisition from the equivalent population of cells. The data is presented very clearly, and the methods are adequately detailed, with suitable experiments and statistical analysis, as well as convincing key conclusions.

    Major points:

    1. Despite "symmetry breaking" being the main focus of the paper, in the Introduction, the authors do not explain what this term means and do not provide any description of this process. This is a critical point that makes understanding of the goals of the paper difficult. Therefore, the authors are encouraged to provide more information and a clear description of this term/phenomenon.
    2. The role of Achaete in the story is not clear. Even though both factors are required for SOP determination, the authors mainly focus on Scute, so it is not very clear what the role of Achaete in this process is, if there is any. As shown in the paper, Achaete is expressed later when heterogeneity is promoting cell fate divergence. Is Achaete maybe contributing to cell heterogeneity/ cell fate divergence? Minor points:
    3. Symmetry Breaking (SB) should be abbreviated in the Abstract. The authors initially use the full term without abbreviation, and only on page 5, the abbreviation is finally defined; however, it should be introduced much earlier.
    4. The second-to-last sentence in the abstract, "These lateral inhibition defects were correlated via cellular rearrangements," is unclear regarding what defects the authors are referring to.
    5. For clarity, being more specific in the text in regards to description of the figure panels would be beneficial (e.g. page 3 Fig 1C-E); referring to C-E together makes it hard to understand what does each panel shows.
    6. In many instances, the movies are not properly referenced (e.g. on page 5, third row simply states "movies"), making it difficult to discern which movie should be checked. On page 8, when authors refer to movie 3, they likely meant movie 5.
    7. Figure S1 requires some corrections. The authors use the short name "scute" initially and then switch to the shortened version "sc'. Additionally, the nlsRFP (blue) is difficult to see; adjusting the levels or changing colors/showing separate channels may improve visibility. The authors mention clone borders, but none are shown. It would greatly help to outline the borders in all figures. Genotypes of the samples should be indicated, and clarification is needed regarding what "n" represents (number of cells, clones, or flies). What do the arrows in the panel B show? It is also recommended to display important channels as separate black and white images. Additionally, the use of RNAi against GFP instead of RNAi against scute should be justified; using RNAi GFP as the genotype on the graph could be interpreted as a control genotype rather than downregulation of scute.
    8. In the Figure 2 Legend, the authors use "std" as an abbreviation to define standard deviation. Typically, this is abbreviated as SD.
    9. In Figure 4E, the authors do not explain on why there are points on the x-axis that correspond to a decimal number of cells.

    Reviewer Cross-Commenting

    I fully agree with the comments provided by the other reviewers, most of which were complementary and overlapping with mine. Their comments are well-reasoned and highlight certain aspects that I overlooked. I agree that conducting additional genetic analyses would enhance our understanding of the progression fate divergence and its impact on lateral inhibition in real-time. Specifically, exploring the spatial and temporal dynamics of Ac and Sc in Notch mutants, as well as Notch dynamics in Sc and Ac mutants, could strengthen the proposed model of cell-cell communication during lateral inhibition.

    Significance

    Understanding cell fate is crucial for various biological processes, including development, tissue regeneration, and disease progression. In this manuscript, colleagues in the team of François Schweisguth provide high-quality live cell observations demonstrating how SOP (Sensory Organ Precursor) cells are determined from a cluster of proneuronal cells via symmetry breaking (SB), which is key in the process of lateral inhibition. Although the process of lateral inhibition has been proposed long ago, no studies have been conducted to demonstrate it using live imaging. Using Drosophila abdominal epidermis as a model, the authors showed how the levels of the main neuronal determinants are expressed during SOP cell determination. The team uses a tagged version of one of the cell fate determinants, Scute, to follow the dynamics of this process, which is then further supported by genetic experiments showing that cell-to-cell variations in Scute expression levels promote fate divergence and patterning. This paper provides a new perspective on how dynamic expression of proneural factors determines cell fate acquisition from the equivalent population of cells. The data is presented very clearly, and the methods are adequately detailed, with suitable experiments and statistical analysis, as well as convincing key conclusions.

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    Referee #1

    Evidence, reproducibility and clarity

    Summary

    In this manuscript, the authors addressed when and how fate symmetry breaking occurs during lateral inhibition using live imaging of Drosophila pupal abdomen as a model system. Using quantitative live imaging of a GFP tagged version of the proneural gene scute (sc), the authors demonstrated that GFP-Sc expression appears first along the posterior margin of the anterior dorsal histoblast nest (ADHN) and later in the central region of ADHN, suggesting that posterior cues regulate early proneural expression in this region, which is consistent with previous findings. By tracking the temporal expression of GFP-Sc in the sensory organ precursor cells (SOPs), the authors further showed that SOPs emerge within a 2 hour time frame around 17h APF in the ADHN. Moreover, the presumptive SOP and its surrounding histoblasts showed a weak and slowly increasing GFP-Sc signal until the presumptive SOP showed a rapid increase in GFP-Sc accumulation, whereas GFP-Sc levels remained relatively constant in non-selected histoblasts. Interestingly, using symmetry breaking as a reference point, the authors found that the onset of fate divergence took place at low levels of Sc, soon after the onset of proneural gene expression and was not preceded by a prolonged phase of Sc accumulation. The authors also demonstrated that lateral inhibition in the pupal abdomen failed to single out SOPs in around 10% of the cell clusters that are in direct contact with each other during symmetry breaking and that pattern refinement involving cellular rearrangements were required to correct these defects. By manipulating the heterogeneity of Sc in genetically mosaic pupae, the authors successfully showed that increasing the heterogeneity of Sc positively correlated with an increased rate of fate divergence, suggesting that cell-to-cell variations in Sc levels promote fate divergence during lateral inhibition. Although earlier modelling suggested that differences in apical cell area may serve as a possible source of bias for Notch-based decisions, the authors found no significant difference in the apical area of the presumptive SOP compared to the mean area of its neighbouring cells, suggesting that apical cell shape does not bias Notch-mediated cell fate decisions in this developmental context. Finally, examination of Notch activity dynamics using a destabilized GFP expressed downstream of a Notch-Responsive Element as well as analysing the expression of the E(spl)m3 Notch target gene, the authors demonstrate that Notch activity was minimal around the time of SOP emergence as E(spl)m3 was detected after the onset of Sc expression but not prior to SOP emergence, indicating that SOP selection in the abdominal epidermis took place at low levels of Notch signalling.

    Major comments:

    • Are the key conclusions convincing?

    Yes, the key conclusions are convincing with quantitative live imaging and proper explanations on how the analyses were carried out.

    • Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

    No.

    • Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation.
    1. The authors conclude that RFP-Ac expression is restricted to emerging SOPs and surroundings cells at 18h APF, indicating that Ac is activated later than Sc. Can the authors provide images for RFP-Ac expression at 10h and 16h APF similar to GFP-Sc as shown in their figures. Do the SOPs that contain high levels of both Ac and Sc (as some SOPs have Sc expression but not Ac) undergo fate divergence and SB faster than the SOPs containing higher levels of only Sc?
    2. It would be interesting to see the spatial and temporal dynamics of Ac and Sc in Notch mutants or even Notch dynamics in Sc and Ac mutants to better understand the progression fate divergence and its effect on lateral inhibition in real time.
    • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

    Yes, I believe the suggested experiments are realistic in terms of time and resources, with an estimation of 3-4 months to complete the experiments.

    • Are the data and the methods presented in such a way that they can be reproduced?

    Yes.

    • Are the experiments adequately replicated and statistical analysis adequate?

    The experiments are straight forward and were performed with a good number of n values for their live imaging and supported by quantifications.

    Minor comments:

    • Specific experimental issues that are easily addressable.
    1. In figure 1F and F', the authors mention GFP-Sc is not expressed prior to 14h, however, there is still GFP signal detected in their imaging. Can the authors comment what would be the cause of this GFP signal or was it due to non-specific background signal during their imaging analysis?
    2. In the materials and methods, the authors mention that prior to imaging the larvae and pupae are grown at 18, 21 or 25C. Is there a reason why the larvae and pupae are grown at different temperatures for different experiments? Can the authors specify (i.e. in the figure legends) in which experiments different temperatures were used?
    3. The citations need to have a better format as they show up as each citation within a single bracket which makes it a little hard to read when multiple references are cited in a single sentence.
    4. In the abstract, the sentence 'Unexpectedly, we observed at low frequency (10%) pairs of cells that are in direct contact at the time of SB'. SB should be replaced with "Symmetry breaking", as it appeared for the first time in the manuscript and should be written out in full.
    5. Throughout the manuscript there are instances where the abbreviations are written in full with the abbreviation in brackets after they have already been introduced in the introduction which can be changed to just the abbreviation itself.
    6. In the discussion on page 11, 'our observation...', our needs to be changed to Our.
    • Are prior studies referenced appropriately?

    Yes.

    • Are the text and figures clear and accurate?
    1. It would be nice to have arrow heads or dotted lines around the cells or areas on interest in both, all the figures and movies, so that it will be easier to follow the results. The videos have a lot of background due to fragmented apoptotic nuclei, etc. as mentioned by the authors, hence arrow heads or dotted lines would bring viewers focus on the areas of interest.
    2. It would be helpful to have anterior - posterior axis (i.e. with an arrow) shown on top of all the figures.
    3. Scale bars are missing in all figures, videos, and figure legends.
    4. Only movies 1 and 3 are referenced in the text.
    5. Keeping the colors in the movies and figures consistent and same would be helpful. For example, Movie 2 Histone3.3-mIFP marker is in blue but in figure 3 it is in magenta.
    • Do you have suggestions that would help the authors improve the presentation of their data and conclusions?

    As mentioned above, it would be helpful if the authors have arrow heads or dotted lines around the cells or areas of interest in both the figures and movies for better representation of their data. For example, movie 1 shows a larger area of imaging than shown in figure 2A, which makes it hard to follow the cells of interest in the movie.

    Significance

    Since the dynamics of fate acquisition has mostly been studied in fixed samples in Drosophila, this is an interesting study to understand the spatial and temporal dynamics of Notch signalling as well as proneural activity during lateral inhibition using Drosophila pupal abdomen as a model. Using quantitative live imaging the authors provide key evidence on how and when SB occurs during lateral inhibition, providing experimental support for the intracellular feedback model. Most importantly, they show that fate selection occurred early and was not preceded by a detectable phase of mutual inhibition, but instead, the initial bias in Sc expression and heterogeneity might play a significant role in in SB.

    • Place the work in the context of the existing literature (provide references, where appropriate).

    So far, most work in this field has focused on the dynamics of fate acquisition using fixed samples and mathematical remodelling, with some live imaging analysis (Skeath and Carol, 1991; Collier et al, 1996; Castro et al, 2005; Corson et al, 2017; Couturier et al, 2019; Troost et al, 2023). Here, considering previous literature, the authors move one step forward, using quantitative live imaging of proneural factors Scute to determine fate SB and monitor fate divergence during lateral inhibition. This study though not entirely conceptually novel provides important new insights into SB and fate divergence in the pupal abdomen, wherein symmetry breaking occurred at low Sc levels and that fate divergence was not preceded by a prolonged phase of low or intermediate level of Sc accumulation. Furthermore, the relative size of the apical area did not influence this fate choice but cell-to-cell variations in Sc levels promoted fate divergence, thereby providing experimental support for the intercellular negative feedback loop model.

    • State what audience might be interested in and influenced by the reported findings.

    Developmental and cell biologists.

    • Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate.

    Stem cells, developmental biology.

  5. Version published to 10.1101/2024.03.11.583933 on bioRxiv