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Published online by Cambridge University Press: 18 July 2025
Organ morphogenesis is a complex process and numerous factors must be considered while choosing a method for its quantitative investigation. Few methods facilitate in vivo imaging. These are sequential replica methods combined with scanning electron microscopy and sequential confocal microscopy imaging. The latter is now the most used method to study spatiotemporal changes of organ geometry, growth and involvement of molecular factors in regulating organ development. The time-lapse confocal imaging combined with quantitative analysis of the spatiotemporal pattern of auxin efflux proteins (PIN-FORMED) was used to investigate growth and morphogenesis of Arabidopsis gynoecium and enabled detailed insight into gynoecium development. Yet time-lapse imaging of the gynoecium, concealed within a flower bud, presents challenges in ensuring high-quality data during all the stages of such investigations (sample preparation, maintenance of growing organ during the relatively long time of its development, laser exposure time, etc.). Analysis of vast quantitative data was facilitated by MorphoGraphX.
Associate Editor: Dr. Ali Ferjani
Table 1 Comparison of methods used for imaging plant organ development
Figure 1. Segmented mesh of gynoecium 7 DAI (a) and after 8 DAI (b) with Bezier grid overlaid on its surface. Bezier grid enabled quantification of the cell growth rate in the area along the gynoecium axis (c). Growth heat map obtained using the Bezier grid is shown in (d). Source: Images kindly provided by Daniel Kierzkowski.
Dear Editor,
I would like to submit the insight paper titled “Time-lapse imaging of plant development – application and challenges” to the special collection - Plant Morphogenesis: Quantitative Aspects and Emerging Novel Concepts.
In the manuscript, I present various methods used for plant development studies, with a particular focus on confocal time-lapse imaging. I discuss the technical challenges that may arise during time-lapse observations, as well as the advantages of this method.
The article also addresses methods for analyzing confocal z-stacks, including both quantitative and qualitative approaches.
Sincerely yours
Wiktoria Wodniok
The manuscript by Wiktoria Wodniok provides an overview of time-lapse imaging techniques applied to Arabidopsis gynoecium development, specifically focusing on the study by Gómez et al. (2024). The manuscript effectively summarizes the imaging and analytical techniques used and addresses practical challenges associated with these methods. This work holds potential value for advancing understanding of image analysis in plant morphogenesis and may contribute insights within the field of quantitative plant biology. However, I believe substantial revisions are required before the manuscript can be considered for publication. My main comments are listed below.
Major Points:
1. Alignment of title, abstract, and content
The title and abstract of this manuscript suggest a comprehensive discussion of time-lapse imaging methodologies and challenges across plant morphogenesis studies. However, the main text predominantly focuses on Arabidopsis gynoecium development as investigated in Gómez et al. (2024), with limited discussion of other methodologies and studies. While I understand that a comprehensive review may not be necessary under the “Insights” category, I recommend revising the title and abstract to better align with the manuscript’s content. Specifically, a title and abstract that reflect the primary focus on Gómez et al. (2024) would more accurately convey the scope to readers.
2. Clarity and appropriateness of Table 1
Table 1 presents information on “Sample size,” but there is no corresponding explanation in the main text. Information included in the table should be supplemented within the text to prevent ambiguity, particularly regarding “Sample size.” Additionally, “Cell wall labeling requirement” implies a universal need for cell wall labeling, which may not always be necessary and depends on the study’s objective. To avoid misinterpretation, I suggest adding explanations for “Sample size” in the main text and reconsidering the appropriateness of including “Cell wall labeling requirement” as a fixed category.
3. Usefulness and content of Figure 1
Figure 1 visually represents different imaging methods used in plant morphogenesis studies (Replica method, Confocal time-lapse imaging, SEM imaging). However, the figure lacks a detailed legend, and the specific purpose and advantages of each technique are not clearly conveyed. Additionally, the content may be too basic for plant cell biology specialists and does not provide new insights. I suggest replacing it with a figure that demonstrates specific examples of visualization or quantitative analysis using software, which could offer readers a fresh perspective.
Furthermore, there is no need to restrict the discussion to confocal time-lapse imaging, as other techniques, such as light-sheet microscopy and conventional wide-field fluorescence microscopy, may be more appropriate depending on the materials and objectives. Examples of analyses using these alternative methods exist, and expanding the discussion to consider other imaging techniques in both the text and figure would provide a broader view and deepen the discussion.
4. Description of MorphoGraphX and alternative software
The manuscript describes MorphoGraphX as a “perfect” software solution for image analysis but lacks mention of alternative software or approaches. An over-reliance on a single software may affect the balance of the review. Additionally, other tools may be more suitable depending on the analysis purpose or data characteristics. For example, Fiji, Imaris, Amira, and AIVIA are also available and commonly used in plant morphogenesis studies. A brief comparison of these tools’ strengths and applicability would help readers make informed choices about software selection.
Minor Point:
In line 159, the year of publication for Silveira et al. is incorrectly listed as “2021” and should be corrected to “2022.”
This paper, entitled “Time-lapse imaging of plant development - application and challenges”, discusses the effectiveness and difficulties of time-lapse observation using confocal microscopy in plant developmental biology. This paper focuses on the recent research of Gomez et al. (2024), especially on the technical aspect of long time-lapse imaging of the gynoecium and the analysis using the MorphoGraphX software. Overall, the contents of the paper is very limited to the research of Gomez et al. (2024) and the title and abstract are obviously inadequate. The analysis of plant tissues with MorphoGraphX is already well known in the field, although Gomez et al. (2024) used the latest version of the software. It is true that the research of Gomez et al. is excellent. However, in recent years, many technical challenges have been reported in plant biology, including multiphoton microscopy, light-sheet microscopy, super-resolution microscopy, and automatic tracking using artificial intelligence. This paper does not present any of these challenges. The scope of this paper is too narrow to provide insights into time-lapse imaging of plant development. The present manuscript is rather a commentary on the work of Gomez et al. and would be better submitted in that category after rewriting the title and abstract to reflect the main contents of the paper.
Dear authors,
In this manuscript, Wiktoria Wodniok provides an overview of time-lapse imaging techniques applied to Arabidopsis gynoecium development, by specifically focusing on the study by Gómez et al. (2024). The manuscript effectively summarizes the imaging and analytical techniques used and addresses practical challenges associated with these methods.
Now we have received the comments of two reviewers experts in the field. They found that while this manuscript holds potential value for advancing understanding of image analysis in plant morphogenesis and may contribute insights within the field of quantitative plant biology, they also found that certain aspects require further attention. Therefore a substantial revision is required before the manuscript can be considered for publication in QPB. Their major comments are
(1). Alignment of title, abstract, and manuscript contents.
(2). Clarity and appropriateness of Table 1.
(3). Usefulness and content of Figure 1.
(4). Description of MorphoGraphX and alternative software.
More specifically, although this paper, discusses the effectiveness and difficulties of time-lapse observation using confocal microscopy in plant developmental biology, it focuses only on the recent research of Gomez et al. (2024), especially on the technical aspect of long time-lapse imaging of the gynoecium and the analysis using the MorphoGraphX software. Overall, the contents of the paper is very limited to the research of Gomez et al. (2024) which makes the title and abstract obviously inadequate.
The analysis of plant tissues with MorphoGraphX is already well known in the field, although Gomez et al. (2024) used the latest version of the software. It is true that the research of Gomez et al. is excellent. However, in recent years, many technical challenges have been reported in plant biology, including multiphoton microscopy, light-sheet microscopy, super-resolution microscopy, and automatic tracking using artificial intelligence. Unfortunately, this paper does not present any of these challenges.
The scope of this paper is too narrow to provide insights into time-lapse imaging of plant development in its wider context. The present manuscript is rather a commentary on the work of Gomez et al. and would be better submitted in “Insights” category after rewriting the title and abstract to reflect the main contents of the paper.
As you may have appreciated , the reviewers have raised critical points about the whole manuscript, the most important of it is its narrow scope. As a minimum requirement the authors are invited to extensively revise the manuscript based on the suggestion of both reviewers.
Thank you again for submitting your work to QPB, and I am looking forward to receiving your revised manuscript.
Ali FERJANI
Associate Editor of QPB
No accompanying comment.
Dear Editors,
I would like to submit the revised insight manuscript titled “Time-lapse confocal imaging helps to reveal a secret behind gynoecium development” (previous title “Time-lapse imaging of plant development – application and challenges”) to the special collection - Plant Morphogenesis: Quantitative Aspects and Emerging Novel Concepts. I have incorporated most of the Reviewers' suggestions when
preparing the revised manuscript.
In the manuscript, I present various methods used for plant development studies, with a particular focus on confocal time-lapse imaging.
I discuss the technical challenges that may arise during time-lapse observations, as well as the advantages of this method based on the gynoecium development study.
Sincerely yours,
Wiktoria Wodniok
I have carefully read the revised manuscript by Wiktoria Wodniok, which I previously reviewed.
I appreciate the authors’ thorough revisions in response to my previous comments. The manuscript has significantly improved in clarity and depth, and I am confident that its quality as a review article has been enhanced.
The expanded discussion on software tools has made the manuscript more balanced and comprehensive, offering a fairer perspective on the topic. Additionally, the newly added Figure 1 is not only visually appealing but also highly insightful, effectively conveying key concepts in an intuitive manner.
In light of these improvements, I fully support the publication of this review article.
This paper describes insights into the effectiveness of long-term time-lapse microscopy on plant organ development. In this paper, the author first provides general information about microscopy in plant developmental biology and then focuses on the recently published paper by Gomez-Felipe et al. (2024), which describes the long-term observation of gynoecium development by CLSM and the computational analysis of the data using MorphoGraphX. I think the manuscript is well written and provides a good introduction to the long-term observation approach to plant organ development. I have only a few minor suggestions as listed below.
1. line #110, light-sheet microscope (LSM) should be light-sheet fluorescence microscope (LSFM).
2. Line#118, there are more examples of super-resolution microscopy in plants, such as Ovečka et al. 2022 Plant Physiol (review), Higa et al. 2024 Nature Plants, Ziqiang Li et al. 2024 Science, etc, some of which could be included in the reference.
3. Line#128, research on Arabidopsis zygote could be a good example of MPM, such as Kimata et al. 2016 PNAS and Gooh et al. 2015 Dev Cell.
4. Table I should be reorganized. EM and light microscopy should be separated into different rows. One-time light microscopy is not a classification of microscopy. I suggest the authors compare the techniques of microscopy such as CLSM, CLFM, MPM, SRM, and SEM for a more comprehensive understanding of microscopy in plant developmental biology. Signal of molecular markers in SEM imaging is no?
Dear authors,
Now we have received the comments from the reviewers on he manuscript QPB-2024-0052.R1.
I really appreciate the authors’ thorough revisions in response to the reviewer’s suggestions and comments. The reviewers found that the manuscript has significantly improved in clarity and depth, and I am confident that its quality as a review article has been enhanced too.
The expanded discussion on software tools has made the manuscript more balanced and comprehensive, offering a fairer perspective on the topic. Additionally, the newly added Figure 1 is not only visually appealing but also highly insightful, effectively conveying key concepts in an intuitive manner. However, one of the two reviewers has suggested minor issues to e considered before formal Acceptance of the manuscript (please see his/her minor comments below).
In the light of the above, I am happy to fully support the publication of this review article once the minor issues have been addressed.
No accompanying comment.
Dear Editors,
I would like to submit the revised insight manuscript titled “Time-lapse confocal imaging helps to reveal a secret behind gynoecium development” to the special collection - Plant Morphogenesis: Quantitative Aspects and Emerging Novel Concepts. I have incorporated most of the Reviewers' suggestions when preparing the revised manuscript.
In the manuscript, I present various methods used for plant development studies, with a particular focus on confocal time-lapse imaging. I discuss the technical challenges that may arise during time-lapse observations, as well as the advantages of this method based on the gynoecium development study.
Sincerely,
Wiktoria Wodniok
I am satisfied with the authors’ responses and the improvements made. I have no further comments and recommend the manuscript for publication.
I found that the author appropriately revised the manuscript. But I just wonder that, in table 1, “signal from molecular markers” of one-time light microscope might be “possible”, if it includes fluorescence light microscopy.
Dear Dr. Wodniok Wiktoria,
Thank you for resubmitting your revised manuscript. Based on the reviewer’s feedback and on my own evaluation I am happy to recommend your insights paper for publication in QPB.
Thank you again for submitting your nice work to QPB
Ali FERJANI
No accompanying comment.
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Morphogenesis is a highly controlled process of forming an organism through developing tissues and organs of a particular shape (Sampathkumar, Reference Sampathkumar2020). Plant organ development starts at meristems, where the so-called initial cells (analogues of animal stem cells) are located. Divisions of initial cells are asymmetric in terms of daughter cell identity: one of the daughter cells and its progeny will all differentiate while the other will preserve initial cell identity. Thus, the initial cells always remain in the meristem and give rise to all the new organs. During the transition from the vegetative to reproductive phase of development, the shoot apical meristem transforms into the inflorescence meristem (or less often into the flower meristem), which will give rise to flowers. Flower development starts with the formation of flower primordium. While the flower primordium develops sepal primordia are first to be initiated but soon they enclose the flower primordium. Stamen and petal primordia begin to emerge next (in Arabidopsis, stamens are initiated before petals). At this stage of flower development, sepals cover the whole flower primordium. Finally, a future gynoecium starts to appear at the centre of the bud (Smyth et al., Reference Smyth, Bowman and Meyerowitz1990). Gynoecium is the female part of the Angiosperm flower. It is made up of free or fused carpels, which are considered to be modified leaves, and consists of the ovary, the style and the stigma. In Arabidopsis, the gynoecium is made up of two fused carpels (Herrera-Ubaldo & de Folter, Reference Herrera-Ubaldo and de Folter2022). During its development, the walls of the carpels form the lateral domains and become the valves; after pollination, they will be attached to the replum (Herrera-Ubaldo & de Folter, Reference Herrera-Ubaldo and de Folter2022). The marginal meristem of carpel gives rise to the placenta, ovules, septum and transmitting tract. The gynoecium, which develops as an open tube, at this stage undergoes closure at the tip, which will give rise to the style and the stigma during later stages of development.
Studying plant morphogenesis can be easier compared to animals due to the lack of cell migration that enables reconstruction of cell divisions and expansion based on one-time observation of cell wall pattern (Crawford et al., Reference Crawford, Nath, Carpenter and Coen2004; Hejnowicz & Włoch, Reference Hejnowicz and Włoch1979; Silk et al., Reference Silk, Lord and Eckard1989; Zagórska-Marek & Turzańska, Reference Zagórska-Marek and Turzańska2000). Such clonal analysis is straightforward as long as the organ growth is steady, like in root apex. Otherwise, time-lapse observations (sequential in vivo imaging) of the cell wall pattern are necessary. Studies of organs development such as gynoecium, which is hidden in the flower bud, are technically challenging. For this reason, gynoecium development was long veiled in mystery. Choosing the proper method to study such complex processes in hard-to-access organs is crucial. Different sequential in vivo imaging techniques are used for studying plant development (Table 1). One of those techniques uses the scanning electron microscope (SEM). The SEM used in direct way requires special sample preparation and fixation, which excludes sequential imaging. This obstacle has been overcome by a replica method (Green et al., Reference Green, Havelange and Bernier1991; Hernández et al., Reference Hernández, Havelange, Bernier and Green1991., Kwiatkowska & Dumais, Reference Kwiatkowska and Dumais2003, Kwiatkowska & Burian, Reference Kwiatkowska and Burian2014). In this technique, a silicone dental impression polymer is applied onto the growing tissue (e.g. shoot apex, young leaf) in order to obtain a mould of the sample surface. Epoxy resin casts made using the mould can then be trimmed and observed using the SEM after sputter coating. The size (dimensions) of an analysed sample is limited only by the SEM technical parameters (image aberrations at minimum magnification, chamber size, etc.). The advantage of replica method is that it eliminates the need for labelling; however, it only allows for the observation of the organ’s surface. The replica technique was used to follow surface growth of an individual plant organ for up to 15 days (one replica per day) without any damage observed (Green et al., Reference Green, Havelange and Bernier1991). However, modern studies on plant development require measurements of not only cell divisions and growth but also gene expression levels, using, for example, reporter lines. This creates the need for imaging methods that enable tracking of cell wall pattern in vivo (without fixation) while observing expression of reporter genes in the same tissue. Various types of microscopes have been used for in vivo observation such as the confocal scanning laser microscope (CSLM), multiphoton microscope (MPM), light-sheet fluorescence microscope (LSFM) and super-resolution microscope (SRM). The CSLM is widely used in plant biology (Hoermayer et al., Reference Hoermayer, Montesinos, Trozzi, Spona, Yoshida, Marhava and Friml2024; Li, Jenke, et al., Reference Li, Jenke, Strauss, Bazakos, Mosca, Lymbouridou and Tsiantis2024a; Mollier et al., Reference Mollier, Skrzydeł, Borowska-Wykręt, Majda, Bayle, Battu and Boudaoud2023; Skrzydeł et al., Reference Skrzydeł, Borowska-Wykręt and Kwiatkowska2021; Vijayan et al., Reference Vijayan, Tofanelli, Strauss, Cerrone, Wolny, Strohmeier and Schneitz2021) since it enables deep sample penetration using a laser beam, as well as optical sectioning for 3D reconstructions of imaged samples (Elliott, Reference Elliott2020). CSLM is an important tool for in vivo imaging, including observation of spatiotemporal changes using a time-lapse technique. It is an excellent tool for observation and imaging at the cellular scale. For subcellular scale imaging, SRM may be a better choice due to its high resolution. The SRM has been used for imaging organelles’ and microtubules’ organization within cells (Higa et al., Reference Higa, Kijima, Sasaki, Takatani, Asano, Kondo and Oda2024; Li, Moreau, et al., Reference Li, Moreau, Petit, Moraes, Smokvarska, Pérez-Sancho and Bayer2024b; Molines et al., Reference Molines, Marion, Chabout, Besse, Dompierre, Mouille and Coquelle2018; Ovečka et al., Reference Ovečka, Sojka, Tichá, Komis, Basheer, Marchetti and Šamaj2022; Vavrdová et al., Reference Vavrdová, Křenek, Ovečka, Šamajová, Floková, Illešová and Komis2020 ).
Table 1 Comparison of methods used for imaging plant organ development
One of the limiting factors of the CSLM is the sample size and thickness. This obstacle has been overcome by LSFM which enables observation of samples ranging in size from tens of micrometers to several millimeters (Ovečka et al., Reference Ovečka, von Wangenheim, Tomančák, Šamajová, Komis and Šamaj2018). The LSFM has gained popularity in plant research (Capua & Eshed, Reference Capua and Eshed2017; Vyplelová et al., Reference Vyplelová, Ovečka and Šamaj2017) not only because it can be used for observations of larger samples but also because it causes less sample damage. The LSFM, like CSLM, has been utilised for sequential in vivo imaging (Valuchova et al., Reference Valuchova, Mikulkova, Pecinkova, Klimova, Krumnikl, Bainar and Riha2020). The MPM in turn uses near-infrared pulsed lasers, which like in the case of CSLM, facilitate penetration of the sample with an advantage of lower phototoxicity. For this reason, it is a useful tool for in vivo imaging of various biological samples (Czymmek et al., Reference Czymmek, Fogg, Powell, Sweigard, Park and Kang2007; Giri et al., Reference Giri, Bhosale, Huang, Pandey, Parker, Zappala and Bennett2018; Gooh et al., Reference Gooh, Ueda, Aruga, Park, Arata, Higashiyama and Kurihara2015; Kimata et al., Reference Kimata, Higaki, Kawashima, Kurihara, Sato, Yamada and Ueda2016).
To summarize, a number of factors need to be considered while choosing the proper method to study complex processes such as organ growth and morphogenesis. One should select the type of microscope preferable for the study (SEM, CSLM, MPM, LSFM or SRM) based on the organ size and accessibility as well as on the required and available labelling (cell walls, reporter genes, etc.). As an example of plant development study using cutting-edge imaging and computational methods, below I am presenting a study by Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024), which focuses on analysing gynoecium growth and cell differentiation using in vivo time-lapse imaging. I will use the opportunity to discuss the various technical difficulties that may be encountered while conducting this type of study, related in particular to: sample preparation; sample growth condition between imaging; time-lapse imaging; and imaging data analysis (tools for confocal microscope z-stack data analysis).
In the study by Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024), inflorescences from 3-week-old Arabidopsis plants were isolated. To uncover gynoecium, the oldest floral buds, as well as sepals, petals and stamens already initiated on the flower bud of interest, were removed using fine tweezers and needles under a stereoscopic microscope. Gynoecium development was imaged in vivo for up to 13 days. Hence, it was crucial not to damage future gynoecium cells during the isolation process. This is especially problematic when working on the model plant Arabidopsis, the flowers of which are very small. Such isolation, therefore, requires very precise tools and operation since the slightest misstep can lead to tissue damage. In the case of time-lapse imaging, this is crucial, as we want the object of study to survive as long as possible and under the least stressful conditions possible. All this added together makes the sample preparation process challenging and time-consuming.
As mentioned before, Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) conducted observation for 13 days, which is a long time for time-lapse imaging, especially taking into account that the sample has been isolated from the rest of the plant and has been imaged at 24-hour intervals. To keep isolated plant organs alive for such a long time period in stressful conditions, selecting a suitable medium and the right growth conditions is critical. Isolated organ needs not only to survive between imaging but also to keep growing in a manner as similar to intact organs as possible. In the discussed paper, plants were kept in a growth chamber under long-day conditions, which are preferable conditions for Arabidopsis to flower.
While imaging, it is essential to choose the correct parameters of the laser, such that, on the one hand, they provide a good image quality and high enough resolution while, on the other hand, do not lead to tissue damage. Hence, laser power and exposure time need to be adjusted appropriately. Another difficulty is the proper positioning of the sample in the medium so that it is well exposed, does not move, and is not damaged in any way by the placement. Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) placed an isolated inflorescence on a petri dish with agar medium in which a cavity had been made so that the medium immobilises the sample. Imaging the sample using a long-distance working objective makes moving of the sample unnecessary (any movement of the sample poses a risk of damage). Additionally, the horizontal placement of an inflorescence enables imaging of only one (chosen beforehand) side of the sample which ensures that the same portion of the sample is imaged every time (Silveira et al., Reference Silveira, Le Gloanec, Gómez-Felipe, Routier-Kierzkowska and Kierzkowski2022).
Even though time-lapse confocal imaging is an excellent method for studying plant development, the amount of data obtained can be overwhelming. There are various commercially available programs for confocal microscope z-stacks analysis, such as Amira (Thermo Fisher Scientific), AIVIA (Leica Microsystems) or Imaris (Oxford Instruments). Amira is a software which allows for 3D reconstructions and measurements (cell area, length, volume, sphericity) of organelles and organ structure from SEM images, as well as confocal z-stacks, and has been used previously in plant biology (Moreno et al., Reference Moreno, Bougourd, Haseloff and Feijó2006). AIVIA enables visualisation and analysis of images and z-stacks from 2D to 5D using machine learning as one of its tools. Imaris is a software dedicated to the analysis of 3D images. It enables visualisation of cell organelles and calculation of volume, area or sphericity. One of the most popular free-of-charge software is Fiji (ImageJ), which enables image processing (e.g. geometry operations, colour processing) and analyses such as measuring area, length or stack processing. All of these software packages are useful tools for visualisation and quantitative analysis of confocal z-stacks but none is dedicated to growth quantification. However, current studies on organ development require complex analyses of temporal and spatial interplay between tissue and cell growth, morphogenesis, and gene/protein expression. The perfect software for this is a freely available MorphoGraphX that enables analysis and, more importantly, quantification of various growth and geometry parameters from confocal image stacks together with gene/protein expression patterns. The main advantage of MorphoGraphX is that the majority of analyses are performed on a curved (2.5D) surface and can be conducted over multiple time points (Barbier de Reuille et al., Reference Barbier de Reuille, Routier-Kierzkowska, Kierzkowski, Bassel, Schüpbach, Tauriello and Smith2015) while 3D reconstruction of cell volume is also enabled.
Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) used MorphoGraphX for the quantification of growth rates and anisotropy (principal growth rates and directions), cell divisions and geometry. They also employed tools for analysis of growth rates along longitudinal and mediolateral axes of the developing organ, reverse lineage tracking, and for creating heatmaps of PIN protein localization in the membrane. Calculating growth rates along both axes was conducted using one of the newest functions of the software – the Bezier grid (Figure 1). The Bezier grid, placed on a mesh surface, allows aligning cell axis calculations in a specific direction. This method enabled authors to conclude that gynoecium growth is controlled by two orthogonal gradients (longitudinal and mediolateral).
Figure 1. Segmented mesh of gynoecium 7 DAI (a) and after 8 DAI (b) with Bezier grid overlaid on its surface. Bezier grid enabled quantification of the cell growth rate in the area along the gynoecium axis (c). Growth heat map obtained using the Bezier grid is shown in (d). Source: Images kindly provided by Daniel Kierzkowski.
One of the key functions of MorphoGraphX, as a tool for time-lapse image analysis, facilitates easy recognition of cell lineage (by assigning “parents”). On this basis, correspondence between data from different time points is obtained and clones derived from the cells present at the beginning of observations are identified for consecutive time points. This allows for the tracking of changes of various parameters from one time point to another in the same group of cells. The parent function can be used for lineage tracking analysis. This allowed the tracking of cells from different regions of an organ (gynoecium, stamen) by computing corresponding cell lineages over multiple time points (Gómez-Felipe et al., Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024; Silveira et al., Reference Silveira, Le Gloanec, Gómez-Felipe, Routier-Kierzkowska and Kierzkowski2022). The origin of the different regions of the gynoecium was characterised using lineage tracking and by finding points in the early stages of the organ development where particular groups of cells contributed exclusively to the development of a given region (Silveira et al., Reference Silveira, Le Gloanec, Gómez-Felipe, Routier-Kierzkowska and Kierzkowski2022). In the case of Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) study, lineage tracking was used to track cells from different parts of the gynoecium, such as replum, valves and style. Cell lineage tracking is a practical and widely used tool in plant development biology (Burian et al., Reference Burian, De Reuille and Kuhlemeier2016; Kierzkowski et al., Reference Kierzkowski, Runions, Vuolo, Strauss, Lymbouridou, Routier-Kierzkowska and Tsiantis2019; Mollier et al., Reference Mollier, Skrzydeł, Borowska-Wykręt, Majda, Bayle, Battu and Boudaoud2023; Silveira et al., Reference Silveira, Le Gloanec, Gómez-Felipe, Routier-Kierzkowska and Kierzkowski2022; Zhang et al., Reference Zhang, Runions, Mentink, Kierzkowski, Karady, Hashemi and Tsiantis2020). Additionally, the software facilitates the generation of heatmaps based on the calculated data obtained from the interval between the two time points (like various growth parameters) or for the individual time-points (e.g. local curvature or intensity of reporter gene signal), which helps visualise results in a clear and accessible way.
MorphoGraphX allows the user also to overlap images from two different channels. This function helps track fluorescent landmarks (Elsner et al., Reference Elsner, Lipowczan and Kwiatkowska2018) or fluorescent protein expression produced in the analysed portion of a sample. By overlapping two confocal images, the user can analyse data on cell expansion and protein expression by combining geometry/growth maps with fluorescent signals. Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) used the image overlapping to show PIN localization in plasma membranes and to create heatmaps of signal intensity. To determine auxin’s role in controlling orthogonal gradients of gynoecium differentiation, they used reporter lines to visualise response to auxin and compared expression of PIN proteins with growth and differentiation of style cells. This observation proved that auxin is responsible for the longitudinal gradient in the style. To test a hypothesis that the second (mediolateral) gradient is specific to the valve, Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) inhibited valve formation using NPA. After NPA treatment, plants were devoid of valves and showed lack of mediolateral gradient. Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) created heatmaps showing PIN protein signal intensity by using one of the MorphoGraphX functions (signal) which facilitates quantification of an average signal intensity per cell. Such signals represented local auxin concentration and biosynthesis.
To sum up, Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) used in vivo imaging of high spatial and temporal resolutions and sophisticated computer analysis for identification of growth and differentiation gradients that were not yet reported for Arabidopsis gynoecium. These gradients can be interpreted as a modification of gradient-based control of leaf morphogenesis. Auxin is putatively involved in establishment of one of the gradients.
It is noteworthy that the time-frame of in vivo imaging performed by Gómez-Felipe et al. (Reference Gómez-Felipe, Branchini, Wang, Marconi, Bertrand-Rakusová, Stan and Kierzkowski2024) was such wide that the first gynoecium stacks consisted of approximately 70 cells, whereas at the last time point, there were around 11000 cells. Manual processing of such an amount of data would obviously be impossible and thus a software like MorphoGraphX, which allows processing of huge amounts of data for time-lapse imaging, was crucial for such analysis.
Open peer review
To view the open peer review materials for this article, please visit http://doi.org/10.1017/qpb.2025.10009.
Data availability statement
No data or code were developed for this manuscript.
Acknowledgements
I thank Prof. Dorota Kwiatkowska for the critical reading of the manuscript and Dr. Daniel Kierzkowski for sharing unpublished images of Arabidopsis gynoecium.
Author contributions
This manuscript was conceived and written by W.W.
Funding statement
This work is supported by research grant OPUS24 2022/47/B/NZ3/01972 from the Polish National Science Centre.
Competing interest
The author declares none.