A dynamic and expandable digital 3D-atlas maker for monitoring the temporal changes in tissue growth during hindbrain morphogenesis

  1. Matthias Blanc
  2. Giovanni Dalmasso
  3. Frederic Udina
  4. Cristina Pujades

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    Evaluation Summary:

    This methodological manuscript is of potential interest to the audience in the fields of neural development, tissue morphogenesis, and image analysis technologies. The authors developed an image registration tool and created a digital atlas to reflect the anatomical distribution of neuronal birthdates in the developing zebrafish hindbrain. The manuscript would further benefit from better documentation of the claimed temporal dynamics, the methods, and the validity of biological inference.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #3 agreed to share their name with the authors.)

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Abstract

Reconstruction of prototypic three-dimensional (3D) atlases at the scale of whole tissues or organs requires specific methods to be developed. We have established a digital 3D-atlas maker (DAMAKER) and built a digital 3D-atlas to monitor the changes in the growth of the neuronal differentiation domain in the zebrafish hindbrain upon time. DAMAKER integrates spatial and temporal data of cell populations, neuronal differentiation and brain morphogenesis, through in vivo imaging techniques paired with image analyses and segmentation tools. First, we generated a 3D-reference from several imaged hindbrains and segmented them using a trainable tool; these were aligned using rigid registration, revealing distribution of neuronal differentiation growth patterns along the axes. Second, we quantified the dynamic growth of the neuronal differentiation domain by in vivo neuronal birthdating experiments. We generated digital neuronal birthdating 3D-maps and revealed that the temporal order of neuronal differentiation prefigured the spatial distribution of neurons in the tissue, with an inner-outer differentiation gradient. Last, we applied it to specific differentiated neuronal populations such as glutamatergic and GABAergic neurons, as proof-of-concept that the digital birthdating 3D-maps could be used as a proxy to infer neuronal birthdate. As this protocol uses open-access tools and algorithms, it can be shared for standardized, accessible, tissue-wide cell population atlas construction.

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  1. Version published to 10.7554/elife.78300 on eLife
  2. eLife

    Evaluation Summary:

    This methodological manuscript is of potential interest to the audience in the fields of neural development, tissue morphogenesis, and image analysis technologies. The authors developed an image registration tool and created a digital atlas to reflect the anatomical distribution of neuronal birthdates in the developing zebrafish hindbrain. The manuscript would further benefit from better documentation of the claimed temporal dynamics, the methods, and the validity of biological inference.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #3 agreed to share their name with the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    In this manuscript, Blanc et al. developed a tool to align different larval zebrafish brains with pan-neural markers and additional birthdate labeling into a common atlas. By aligning transgenic lines into this reference atlas, the authors tried to infer the birth date and growth patterns of different neuron populations. The intention of providing an open-access tool and developmental atlas is good, especially considering most of the current zebrafish brain atlases were made for adult or larval zebrafish more than 5 days old. However, the key features claimed by the authors i.e., the "temporal dynamic" is essentially missing from the atlas. The tool was still built for a single development stage and reflected no information on growth patterns except the neuronal birthdate. Moreover, the accuracy of the registration method, the rationality of the birthdate labeling, and the validity of the proof-of-concept inference were also not sufficiently demonstrated in the experimental design.

    Overall, I believe the manuscript has the potential to be a useful tool and an impactful developmental atlas for the community, but it would need substantial improvement in method design, experimental validation, and data/software availability.

    Major points:

    1. The authors claimed to have made a "3D-temporal" atlas for developing zebrafish hindbrain. However, the "temporal" component was solely birthdate inferred from temporal labeling. Images were still acquired at the same developmental stage, which makes the atlas and registration method not substantially different from the other existing atlases (e.g. ViBE-Z (Ronneberger 2012), Z-Brain (Randlett 2015), ZBB (Tabor 2019), Mapzebrain (Kunst 2019) - note not all of these tools were cited in introduction). The authors would have to either add temporal tracing of the population and provide registration between different developmental stages, or tune down the "temporal" term only to "birthdating".

    2. Rigid registration was used to align the images from different individuals, as opposed to the more complicated non-linear registration used by all the tools above. The accuracy of such registration needs to be measured to justify the choice of method, by measuring the inter-individual variability using different registration methods. Variability should be quantified in 3D rather than along specific anatomical axes.

    3. Birthdate labeling was achieved by photoconverting Kaede at different stages (24, 36, 48 hpf) and imaging at 72hpf. This method suffers from an intrinsic bias: the Kaede-red was subject to different time windows for diluting and metabolizing over development, making the age labeling incomparable between different labeling lengths. To verify the experimental design, the authors should 1) demonstrate that the red cells labeled in an early conversion are strictly included in the red cells labeled in a late conversion, and 2) provide an additional age-labeling method like BrdU treatment, to show the new cells incorporated between the two time points are reflected in the growing photoconverted population.

    4. Proof-of-concept inference of GABAergic neuron birth date in Figure 5 is very vague. No link was shown between the red cells in Fig 5B and the gad1b in situ-positive cells in Fig 5D. If tracing the fate of these cells from 24-72hpf is not possible, the authors should at least demonstrate that they are 1) post-mitotic at 24hpf, i.e. HuC-positive; and 2) appear in similar numbers and similar neighborhood context as the red cells in Fig 5B. I also want to point out that while it is true that mRNAs are expressed earlier than fluorescent proteins in the transgenic line, an early-born cell expressing a specific gene late development does not mean it would express the gene early on. A gene can be ON early on and turned OFF later; Conversely, a gene can express late in the differentiation process while the cell is committed and went through terminal division early in the lineage.

    5. It is mentioned many times that the platform is "open-access" and "expandable", but no source or browsable atlas was provided (maybe I was wrong, but I did not find the Fiji macro and R code on the provided website). The software and data availability should be improved, and more demonstration is needed to show its "expendability" -guidelines should be provided on how to upload users' own data to use this platform, and what kind of additional data is supported.

  4. eLife

    Reviewer #2 (Public Review):

    The manuscript describes the development of a new digital 3D tool to monitor spatial and temporal changes in the neural tube, using hindbrain morphogenesis as a proof of concept tissue. The conclusions of the manuscript are supported by the results and the quality of the data is excellent.

    Strengths

    1. The data and results of the manuscript have been meticulously prepared and support the author's conclusions.

    2. Open-access, novel, and user-friendly protocols for digitalizing spatial and temporal changes of tissue growth are in demand and will clearly contribute to the relevant scientific communities

    3. Inclusion of 3D temporal information to the already existing 3D-spatial atlases is missing. The new methodology developed in this manuscript will open the door for collecting valuable information (which is currently limited) on normal and perturbed brain development in time and space.

    4. The quality of the presented data is very good.

    5. The development of the hindbrain is a fascinating process that is less studied in comparison to higher brain areas. As proper hindbrain development is the foundation upon which the brainstem will later form, novel knowledge on hindbrain morphogenesis and neurogenesis is of clear importance.

    Weaknesses

    1. Compared to other methodology-based papers on brain image analysis (i.e., Chow et al., 2020; Jaggard et al., 2020; Kenney et al., 2021; Ronneberger et al., 2012; Tabor et al., 2019; Dsilva et al., 2015; Fernandez and Moisy, 2020), the manuscript is a bit narrow in its overall information. For instance, this manuscript uses different transgenic lines to quantify cells of different neuronal subpopulations at several time points to (elegantly) show their differentiation dynamics. Yet, the magnifications are very low so that the provided data is an overview of the entire hindbrain without tracing the cell's behavior at a much higher 3D resolution. This is at variance from some of the above-cited papers which imaged cell domains at much higher magnifications.

    2. The temporal component (emphasized by the authors as their main novelty) did not integrate data from ongoing time-lapse imaging of color-converted cells, (although expected when reading the Introduction and Abstract). Rather, the analysis was based on a comparison of fixated brains at 3 different stages from different fishes. Without diminishing the importance of this comparison (which was elegantly done), putting the temporal-based analysis in the forefront of the methodology is a bit misleading, as it occupies only a small part of the manuscript.

    3. The paper does not take the newly developed protocols one step further to serve as a proof-of-concept study by using fish with normal or aberrant neurogenesis. This diminishes the powerfulness of the suggested technology. Such types of analyses have been provided in some other papers which developed recent 3D digital atlases of the brain, where the technologies were utilized to answer developmental/behavioral questions.

    4 . In general, the many efforts used in this study to develop the imaging technologies did not seem to yield a significant amount of novel information, when compared to more standard imaging techniques (that the authors present). Hence, more substantial data is needed to convince how the DAMAKER is a "game-changer" in the field of neural development.

  5. eLife

    Reviewer #3 (Public Review):

    By use of in vivo fluorescence imaging and image analysis tools, Blanc et al. have established an automatic pipeline to build a digital 3D-temporal atlas of zebrafish hindbrain. Based on the common fluorescence labelling with HuCD the authors first established a pipeline and a reference atlas of the hindbrain. The pipeline is based on the already established tools in Fiji for registration of multi-modal data, such as Fijiyama plugin, and automatic segmentation of the data, in particular Weka 3D segmentation. By use of this pipeline, the authors then mapped rhombomeres markers Mu4127, precursor cell populations by nestin, Neural basic helix-loop-helix (bHLH) transcription factor neurog1 expressed in proliferating cells, motoneurons by isl1, and glutamatergic and GABAergic neurons via vglut2 and gad1b correspondingly. All these cell populations were mapped precisely from 24 to 72 hpf of zebrafish brain development. By comparison of fluorescent marker expression in a temporal manner, the authors demonstrate that one can approximate the birthdate of cells for which reporter expression is delayed and becomes present only later.

    Strengths:
    Free and easy access to Fiji plugins used and developed in this work makes the building of digital 3D atlases accessible for many labs, potentially also in other settings. The analysis of marker expressions in space, that is anterior-posterior and mediolateral is simple (without the need for high computational power or specialized and expensive software) and at the same time biologically relevant.

    Weaknesses:
    Due to the use of fluorescence imaging, the pipeline is limited to easily accessible and rather transparent tissues. Additionally need for one channel as a common reference is time and labour extensive in terms of experimental work. In terms of the 3D digital atlas maker, the use of user supervised training limits the "easiness" and widespread use of the pipeline in the future.

  10. Version published to 10.1101/2021.03.29.437592v2 on bioRxiv
  11. Version published to 10.1101/2021.03.29.437592v1 on bioRxiv