Image provided by the MRC National Mouse Genetics Network. For permission to reproduce, contact the MRC National Mouse Genetics Network.
The September issue of our journal Disease Models & Mechanisms (DMM) has a focus on how researchers can best leverage model organisms to improve our understanding of human health and disease. Here, we highlight some of the articles and encourage you to visit the journal website, where all the articles are available to read Open Access.
The issue includes a Special Article by Keith Cheng, Hugo Bellen and colleagues on the importance of promoting validation and cross-phylogenetic integration in model organism research. The article draws on a discussion series organised by the National Institutes of Health (NIH) to gather opinions on how researchers can further extend the utility of model organisms in the future. The authors discuss some of the key ideas identified by the NIH discussions, including:
Developing new tools and technologies. Ideas include humanising model organisms to better model human diseases, generating reference atlases to allow comparison between model organism and human data, and developing new reagents such as species-specific antibodies.
Broadening the range of model organism species used in research. Different species offer specific advantages for modelling human disease. For example, hamsters share similar lung physiology to humans so have proved useful in COVID-19 studies. Expanding the range of species used in disease research could therefore offer researchers greater access to useful models that have been previously overlooked or underused.
Increasing genetic variation. Laboratory animal strains are often inbred to reduce variation. However, humans have a great deal of genetic diversity, so it will be important to use a suite of diverse models to better reflect the variation in human disease.
Integration between different disciplines and organisms. It will be important to integrate phenotypic data from different disciplines (such as biochemistry, cell biology, genomics and behavioural studies) as well as data from studies in different model organism species. This will help to form a more complete picture of the disease phenotype.
Owen Sansom, Director of the Cancer Research UK Beatson Institute and the MRC National Mouse Genetics Network.
An example of a new initiative that aims to improve integration across disciplines is the UK Medical Research Council (MRC) National Mouse Genetics Network. You can read more about this in Owen Sansom’s Editorial. Owen explains that the Network will comprise seven research clusters, each focusing on different yet complementary research areas. The aim is to share data, techniques and resources, and to encourage collaboration within the mouse model community.
A figure from the JAX group’s paper showing tumour growth in a human leukaemia xenograft over time in three different host mouse strains (blue, green, black). Tumour size (measured using bioluminescence) is shown on the y-axis, with time in days marked on the x-axis. The results show that the NR strain (blue) supports the most extensive tumour growth.
The September issue of DMM also contains a study from Muneer Hasham and colleagues at the Jackson Laboratory (JAX), USA, which expands the genetic diversity of mouse models available for xenografting experiments. Xenografting human cancer cells in mice is a well-established method for studying tumour development and testing potential therapeutic drugs. These mice must lack B- and T-lymphocytes for xenografting to be successful, and researchers can achieve this by generating mouse strains that are Rag1 deficient. However, the genetic diversity of available Rag1-/- mouse strains is limited.
In their paper, the JAX group generate five genetically diverse Rag1-/- mouse strains. Together, these strains cover 90% of the known allelic diversity in the mouse genome. They show that the genetic background of the host strain plays an important role in the outcome of the xenograft; for example, they find that tumour size varies between the five different host strains. This article was also highlighted as the DMM Editor’s Choice.
You can read a response to the work by Dr Hasham and colleagues in the same issue of DMM, where Ryan Devlin and Ed Roberts tackle the question of how researchers can build a healthy mouse model system to better interrogate cancer biology. Taking the JAX lab paper as a case study, they suggest implementing a ‘Swiss cheese model’ to design better experiments. This model is already used in accident prevention strategies, where the concept of layering multiple strategies (each with their own weaknesses, as represented by holes in the slice of cheese) is employed to reduce the chance of an accident.
An individual model can be represented as a slice of Swiss cheese (A), where the holes represent limitations that might cause failure of a potential treatment in a clinical trial. As models are refined, these holes become smaller (B), and increasing the genetic diversity of the model increases the size of the slice (C). Layering multiple models (D) can allow researchers to prevent misleading results that may be influenced by a limitation in one model.
This figure from the JAX Perspective illustrates key strategies for improving translation of animal models. These include establishment of common research standards, use of diverse genetic backgrounds within a species, requiring adequate statistical power and better access to public databases to facilitate meta-analyses of multi-omics data.
In a similar vein, Ryan and Ed suggest that researchers can layer a suite of different mouse models, rather than trying to identify the ‘best’ model. This is because each model has its own weaknesses so, by combining models that complement one another, scientists can reduce the chances of a harmful or ineffective chemotherapeutic drug reaching the clinical trial stage.
Finally, researchers from JAX have also provided a Perspective for the October issue of DMM. In the article, Karen Svenson and colleagues respond to the NIH’s 2021 recommendations to improve the reproducibility of animal studies. They share their own experiences of addressing this issue, with a specific focus on mouse models.
Want to keep up with the latest news from DMM? Visit the DMM website and follow the journal on Twitter and/or Mastodon to find out more.
“We’re testing the air for tigers and digging up dead bodies as we explore the exciting new field of environmental DNA”
Dr Sally Le Page
In the latest episode of the Genetics Unzipped podcast, we’re testing the air for tigers and digging up dead bodies as we explore the exciting new field of environmental DNA. Dr Sally Le Page chats with Prof. Elizabeth Clare about sampling the DNA of rare species from the air, and Dr Kirstin Meyer-Kaiser and Charles Konsitzke tells us about their project using eDNA to recover the missing bodies of fallen service personnel.
By Zoe Mann, Ahmed Mahmoud, Ana Rita Diogo Robelo and Neha Agrawal
Hidden away in the beautiful countryside, a group of scientists gathered at Buxted Park to brainstorm the roles of metabolism in the developmental origins of health and disease (DOHaD). In this peaceful setting, early career researchers (ECRs) had the opportunity to network and exchange ideas with leaders in their respective fields. Being one of the first in-person workshops since the pandemic, energy levels and excitement were high.
The program, which was well organized by Alex Gould and Sally Dunwoodie, was filled with interdisciplinary presentations and stimulating, fruitful discussions between scientists, which continued throughout the day over lunch, coffee breaks, long leisurely walks and well into the evening over dinner and drinks. The venue and small size of the Workshop promoted engagement between participants in a way that is not possible at larger scientific meetings. Also, attendees were encouraged to present unpublished data, which prompted useful and interesting discussions about the most recent advances in DOHaD. For the majority, this workshop bore new collaborations, ideas and friendships.
Throughout the week, we listened to outstanding talks exploring the role of developmental metabolism in worms, flies, xenopus, birds, mice and humans. The interdisciplinary nature of this Workshop revealed that regardless of the model system and field of study pursued by the participating scientists, a common theme remained consistent, which is the importance of the DOHaD in their respective fields. Furthermore, it was fascinating and refreshing to hear many works that bridge together transcriptomics, proteomics and metabolomics for a comprehensive understanding of how genetics, nutrition and environment can modulate metabolism and, consequently, development. For example, metabolic disruptions in the placenta can have a defining role in disease manifestation in multiple organs later in life. Similarly, early exposure to hypoxia during development can have lasting detrimental metabolic effects on offspring. Understanding these processes is therefore informative not only for developmental biology, but also for informing clinical research and public health policy.
A ‘hot topics’ discussion on the penultimate day was helpful in identifying important ideas and focus areas for further development in this field. The role of cutting-edge technologies, such as spatial metabolomics and assessing metabolomes at single cell resolution, was highlighted. In particular, the need to communicate the importance of DOHaD in both research and clinical settings was strongly emphasized throughout the meeting. Indeed, broadening our view will allow the scientific community to acknowledge that, not only the genetic background, but also the metabolic state of an organism, can be associated with and even drive developmental defects or tumorigenesis. Additionally, a major conclusion from the Workshop was the need to advocate for increased awareness of DOHaD, even amongst developmental biologists.
In this focused setting, the friendly environment and small community inspired new interdisciplinary research aimed at uncovering the mechanistic links between early-life metabolism and adult health and disease. Should the chance to take part in one of these Company of Biologists Workshops arise, do not hesitate to apply. You will hear about cutting-edge research, build new and inspiring collaborations, network with leaders in the field and, above all, have fun.
Developmental metabolism and the origins of health and disease Workshop (2 votes) Loading...
In the past couple of weeks, #ScienceTwitter was full of tweets starting with ‘If Twitter ends today, can we all agree that…’, professing their love for a particular model organism, and whether qPCR is essential for validation! Of course, Twitter hasn’t collapsed but the #devbio community, including ourselves, have been trying Mastodon as an alternative. Read on to find out some of the talking points that caught our attention.
To move or not to move?
Question: what is the trigger point at which we should all leave Twitter? Maybe when it functions as a platform upon which the amount of disinformation amplified exceeds the amount of information? Has that just happened?
We’re at @the_node@mstdn.science, and we’re still building our community on Mastodon, but below are some of our favourites so far. Let us know who we should be adding to our list!
We have just released Mastodon beta-26. This release sums the work of the past 2 years and results in major changes in feature for the users. I describe some of the new features below, but for more info, check https://t.co/6etC6mVmBcpic.twitter.com/NfNv1152se
Investigating the rules of cell-to-cell interaction during pre-somitic mesoderm elongation
I discovered the field of developmental biology through independent reading during the first year of my undergraduate biomedical sciences program. I was fascinated by the process through which embryos develop, and the more I learned, the more questions I had. As Lewis Wolpert said, “Understanding the process of development in no way removes that sense of wonder”. I knew I wanted to gain some experience in working with embryos and I had the amazing opportunity to work in Ben Steventon’s lab at the Department of Genetics, University of Cambridge.
During development, cells interact with one another to generate collective migration. For example, cranial neural crest cells counterbalance contact inhibition of locomotion and coattraction to migrate through the embryo (Carmona-Fontaine et al., 2009; Carmona-Fontaine et al., 2011). The interactions between the cells of the pre-somitic mesoderm during vertebrate elongation are not understood as well. I focused on investigating the behaviour of the medial somite progenitor (MSP) population, using chick embryos as a model system.
I started by taking stage HH4 chick embryos out of eggs and placing them in PBS. Using a small syringe needle I then explanted the MSP region, which is located in the anterior primitive streak just below Hensen’s node. I transferred each explant on a dish coated with fibronectin and I imaged them every 10 minutes for 20 hours. After watching how the cells migrate in the dish (figure 1, movie 1), I wanted to find out how different explants would interact. I decided to culture two explants from the same region (anterior streak) next to each other, as well as an explant from the anterior region and an explant from the posterior region.
Figure 1 – Migration of cells from the MSP region, imaged at 10x for 20 hours.
Movie 1 – Migration of cells from the MSP region, imaged at 10x for 20 hours
Surprisingly, in both situations, the cells did not mix. The anterior streak explants attracted each other in some cases (figure 2, movie 2), while the posterior streak explant seemed to be attracted by the anterior streak explant (figure 3, movie 3). There is no significant difference between the average timing of migration onset in anterior and posterior explants (figure 4A). To measure the rate of migration, I calculated the rate of change of diameter, and again there was no significant difference between the two populations (figure 4B). The attraction is not likely to be influenced by the distance, as there is no significant difference between the mean initial distance separating the explants in the cases where attraction occurs or does not. However, there seems to be a weak positive correlation between the initial size of the explant with the rate of migration. Explants with a larger initial diameter generally have a greater rate of change of diameter. This is true for both anterior explants (figure 4C) and posterior explants (figure 4D).
Figure 2 – Two anterior streak explants from different embryos cultured together, imaged at 10x for 20 hours. The explants attract each other; however, the cells do not mix.
Movie 2 – Two anterior streak explants from different embryos cultured together, imaged at 10x for 20 hours.
Figure 3 – Anterior streak explant (unlabelled) and posterior streak explant (GFP) from different embryos cultured together, imaged at 10x for 20 hours. The posterior explant is attracted by the anterior explant; however, the cells do not mix.
Movie 3 – Anterior streak explant (unlabelled) and posterior streak explant (GFP) from different embryos cultured together, imaged at 10x for 20 hours.
Figure 4 – Features of migration
A – Mean timing of migration onset in anterior and posterior streak explants. A T test was performed, and there is no significant difference between the onset of migration (p = 0.529).
B – Mean rate of change of diameter of posterior and anterior explants. A T test was performed, and there is no significant difference between the rate of change of diameter (p = 0.819).
C – Variation of the rate of change of diameter against initial diameter in anterior streak explants. There is a positive correlation between the initial diameter and the rate of change of diameter.
D – Variation of the rate of change of diameter against initial diameter in posterior streak explants. There is a positive correlation between the initial diameter and the rate of change of diameter.
I had an amazing experience working in the lab. Initially, I found it tricky to remove the embryos out of the egg and explant the region. I ended up breaking a few embryos and losing some explants. However, practicing the techniques every day helped me improve quickly. Each week I got more and more comfortable doing my experiments and my movies have significantly improved. The people in the lab were very friendly and always happy to help, so I had great support throughout my placement. I enjoyed the lab environment and the weeks passed by incredibly quickly. If I had more time, I would have liked to investigate the role of FGF signalling in the migration of these cells. I would have liked to inhibit FGF receptors to find whether the explants still attract or not, since streak cells are attracted by FGF4 and repelled by FGF8 (Yang et al., 2002). However, there seems to be more FGF8 and less FGF4 in the MSP region (Lawson et al., 2001; Shamim and Mason, 1999), so the fact that the explants attract seems to oppose this evidence.
I am interested in pursuing a PhD and my experience from this summer has only made me more determined. I gained valuable insights into the reality of working in research. I had encountered some difficulties with my experiments and spent some time troubleshooting, however that did not put me off. Moreover, it made the results so much more rewarding, giving me a realistic view of what it is like to start a new project and how long experiments take. I appreciate the freedom I had in deciding which experiments to perform, how I would analyse the data, and the general structure of my day.
I think everybody who is curious about research should apply for a BSDB summer studentship. There is nothing like experiencing research first-hand. I would like to thank Ben for hosting me in his lab, Tim for encouraging me to apply for this scheme in the first place, and everybody in the lab for teaching me various skills and being patient with me.
References
Carmona-Fontaine, C., Matthews, H., Kuriyama, S., Moreno, M., Dunn, G., Parsons, M., Stern, C. and Mayor, R., 2008. Contact inhibition of locomotion in vivo controls neural crest directional migration. Nature, 456(7224), pp.957-961.
Carmona-Fontaine, C., Theveneau, E., Tzekou, A., Tada, M., Woods, M., Page, K., Parsons, M., Lambris, J. and Mayor, R., 2011. Complement Fragment C3a Controls Mutual Cell Attraction during Collective Cell Migration. Developmental Cell, 21(6), pp.1026- 1037.
Lawson, A., Colas, J. and Schoenwolf, G., 2001. Classification scheme for genes expressed during formation and progression of the avian primitive streak. The Anatomical Record, 262(2), pp.221-226.
Shamim, H. and Mason, I., 1999. Expression of Fgf4 during early development of the chick embryo. Mechanisms of Development, 85(1-2), pp.189-192.
Wolpert, L., 2008. The triumph of the embryo. Mineola, N.Y.: Dover Publications, p.199.
Yang, X., Dormann, D., Münsterberg, A. and Weijer, C., 2002. Cell Movement Patterns during Gastrulation in the Chick Are Controlled by Positive and Negative Chemotaxis Mediated by FGF4 and FGF8. Developmental Cell, 3(3), pp.425-437.
Epithelial Outgrowth Through Mesenchymal Rings Drives Alveologenesis Nicholas M. Negretti, Yeongseo Son, Philip Crooke, Erin J. Plosa, John T. Benjamin, Christopher S. Jetter, Claire Bunn, Nicholas Mignemi, John Marini, Alice N. Hackett, Meaghan Ransom, David Nichols, Susan H. Guttentag, Heather H. Pua, Timothy S. Blackwell, William Zacharias, David B. Frank, John A. Kozub, Anita Mahadevan-Jansen, Jonathan A. Kropski, Christopher V.E. Wright, Bryan Millis, Jennifer M. S. Sucre
Sequencing and chromosome-scale assembly of the giant Pleurodeles waltl genome Thomas Brown, Ahmed Elewa, Svetlana Iarovenko, Elaiyaraja Subramanian, Alberto Joven Araus, Andreas Petzold, Miyuki Susuki, Ken-ichi T. Suzuki, Toshinori Hayashi, Atsushi Toyoda, Catarina Oliveira, Ekaterina Osipova, Nicholas D. Leigh, Andras Simon, Maximina H. Yun
PCLAF-DREAM Drives Alveolar Cell Plasticity for Lung Regeneration Bongjun Kim, Yuanjian Huang, Kyung-Pil Ko, Shengzhe Zhang, Gengyi Zou, Jie Zhang, Moon Jong Kim, Danielle Little, Lisandra Vila Ellis, Margherita Paschini, Sohee Jun, Kwon-Sik Park, Jichao Chen, Carla Kim, Jae-Il Park
A stem cell zoo uncovers intracellular scaling of developmental tempo across mammals Jorge Lázaro, Maria Costanzo, Marina Sanaki-Matsumiya, Charles Girardot, Masafumi Hayashi, Katsuhiko Hayashi, Sebastian Diecke, Thomas B. Hildebrandt, Giovanna Lazzari, Jun Wu, Stoyan Petkov, Rüdiger Behr, Vikas Trivedi, Mitsuhiro Matsuda, Miki Ebisuya
A Canine Model of Chronic Ischemic Heart Failure Muhammad S. Khan, Douglas Smego, Yuki Ishidoya, Annie M. Hirahara, Emmanuel Offei, Sofia R. Castillo, Omar Gharbia, Joseph A. Palatinus, Lauren Krueger, TingTing Hong, Guillaume L. Hoareau, Ravi Ranjan, Craig Selzman, Robin Shaw, Derek J. Dosdall
In vivo generation of heart and vascular system by blastocyst complementation Giulia Coppiello, Paula Barlabé, Marta Moya-Jódar, Gloria Abizanda, Carolina Barreda, Elena Iglesias, Javier Linares, Estibaliz Arellano-Viera, Adrian Ruiz-Villalba, Eduardo Larequi, Xonia Carvajal-Vergara, Beatriz Pelacho, Felipe Prósper, Xabier L. Aranguren
Single-cell transcriptomic atlas reveals increased regeneration in diseased human inner ears Tian Wang, Angela H. Ling, Sara E. Billings, Davood K. Hosseini, Yona Vaisbuch, Grace S. Kim, Patrick J. Atkinson, Zahra N. Sayyid, Ksenia A. Aaron, Dhananjay Wagh, Nicole Pham, Mirko Scheibinger, Akira Ishiyama, Peter Santa Maria, Nikolas H. Blevins, Robert K. Jackler, Stefan Heller, Ivan A. Lopez, Nicolas Grillet, Taha A. Jan, Alan G. Cheng
RAPTOR: A Five-Safes approach to a secure, cloud native and serverless genomics data repository Chih Chuan Shih, Jieqi Chen, Ai Shan Lee, Nicolas Bertin, Maxime Hebrard, Chiea Chuen Khor, Zheng Li, Joanna Hui Juan Tan, Wee Yang Meah, Su Qin Peh, Shi Qi Mok, Kar Seng Sim, Jianjun Liu, Ling Wang, Eleanor Wong, Jingmei Li, Aung Tin, Ching-Yu Chen, Chew-Kiat Heng, Jian-Min Yuan, Woon-Puay Koh, Seang Mei Saw, Yechiel Friedlander, Xueling Sim, Jin Fang Chai, Yap Seng Chong, Sonia Davila, Liuh Ling Goh, Eng Sing Lee, Tien Yin Wong, Neerja Karnani, Khai Pang Leong, Khung Keong Yeo, John C Chambers, Su Chi Lim, Rick Siow Mong Goh, Patrick Tan, Rajkumar Dorajoo
Rabbit Development as a Model for Single Cell Comparative Genomics Mai-Linh N. Ton, Daniel Keitley, Bart Theeuwes, Carolina Guibentif, Jonas Ahnfelt-Rønne, Thomas Kjærgaard Andreassen, Fernando J. Calero-Nieto, Ivan Imaz-Rosshandler, Blanca Pijuan-Sala, Jennifer Nichols, Èlia Benito-Gutiérrez, John C. Marioni, Berthold Göttgens
Comprehensive cell atlas of the first-trimester developing human brain Emelie Braun, Miri Danan-Gotthold, Lars E. Borm, Elin Vinsland, Ka Wai Lee, Peter Lönnerberg, Lijuan Hu, Xiaofei Li, Xiaoling He, Žaneta Andrusivová, Joakim Lundeberg, Ernest Arenas, Roger A. Barker, Erik Sundström, Sten Linnarsson
Please find out more about the Special Issue on our call for papers page on the Development website. The deadline for submission is 15 May 2023.
Natalia López Anguita (PhD student in the Stem Cell Chromatin Groupat the Max Planck Institute for Molecular Genetics) ‘Role of hypoxia in pluripotent cells and during differentiation via gastruloid formation’
Hannah Brunsdon (Postdoctoral Research Fellowin Liz Patton’s group at theIGC, University of Edinburgh) ‘Aldh2 is a metabolic gatekeeper in melanocyte stem cells’
Benjamin Jackson (MD-PhD Candidate in Lydia Finley‘s group at Memorial Sloan Kettering Cancer Center) ‘A non-canonical tricarboxylic acid cycle underlies cellular identity’
“Whatever the species – whether insects, birds, mammals or fish – and however far the distance, somehow these animals know when to leave and where to go. So is this behaviour hardwired into their genetic code?”
Dr Kat Arney
In the latest episode of the Genetics Unzipped podcast, we’re taking a look at the birds and the bees – not like that! – from the unusual migratory habits of European blackcaps and the ‘greatest shoal on earth’ to the division of labour in a beehive, we’ll be exploring the role that genetics plays in shaping animal behaviours.
In their recent manuscript, published in Developmental Cell, Vijina Varapparambath, Mabel Maria Mathew, Anju Pallipurath Shanmukhan, and colleagues explore the mechanism underlying de novo shoot regeneration. They discover that mechanical feedback between two populations of juxtaposed cells – one which will eventually become the shoot and the other its neighbors – is what propels fate changes and sculpts the regenerating shoot meristem. Now, one of the co-first authors and the co-corresponding author, Mabel, gives us some insights into the story behind the paper.
What was already known about the topic?
Tissue culture-induced de novo shoot regeneration is one of the many remarkable regenerative abilities of plants. It relies on the right balance of phytohormones, auxin and cytokinin, to exploit the totipotency of plant cells and generate entire shoot and/root systems from any tissue. High auxin promotes the formation of undifferentiated callus from which shoots arise. Notably, only a few cells of the callus could reprogram and develop into a complete shoot system (Gordon et al., 2007; Kareem et al., 2015).
How did you get started on this project?
We called the sub-population of callus cells that have the potential to make the shoot ‘progenitors’. These cells were marked with the expression of polar auxin efflux carrier, PINFORMED1 (PIN1). We were curious about the stochastic selection of certain cells to become progenitors and how they progress into the shoot (Fig 1A). To understand this, we followed hundreds of progenitors in real-time by confocal-based live imaging and found that around one fourth of these progenitors did not make shoot meristem. Why some sub-populations succeeded in making shoot meristem while others failed intrigued us. This was where the project started.
When doing the research, did you have any particular result or eureka moment that has stuck with you?
Contrary to popular expectation, our investigations revealed that the reason why some progenitors aborted was not the lack of the shoot stem cell regulator, WUSCHEL. The observation was striking; even though WUS is necessary (Zhang et al., 2017), its abundance alone does not guarantee successful shoot regeneration. Rather it was the localization pattern of cell polarity markers such as PIN1, that predicted successful shoot regeneration. The next goal was to identify the mechanism by which these progenitors achieved shoot regeneration. We performed a comparative transcriptome analysis using several genetically engineered backgrounds; some of which could regenerate shoot and others that could not. While profiling the changes in gene expression during the onset of progenitor formation, we identified an over-representation of XYLOGLUCAN ENDOTRANSGLUCOSYLASE/HYDROLASE 9(XTH9) in the backgrounds that could regenerate shoot. XTH9 encodes an enzyme for cell wall loosening and had an unexpected spatial expression. We found it to be expressed solely in a shell of cells (which we refer to as the non-progenitor cells) encapsulating the progenitor, that underwent stretching. As opposed to the commonly held notion that stretching cells often divide, these surrounding cells hardly divided. This was a hypothesis-generating result and turned out to be a key milestone for the story.
What was the key experiment?
We were curious about what causes the specific local expression of XTH9. Through extensive follow-up genetic and biochemical approaches including ChIP seq, we discovered that a transcription factor and shoot-promoting factor, CUP-SHAPED COTYLEDON 2 (CUC2), activated XTH9 expression solely in non-progenitor cells. We further established that the CUC2-XTH9 regulatory axis promoted cell polarity in the progenitor non-cell autonomously. In parallel, Anju modulated the components of the regulatory axis with the challenging inducible system, which allowed us to capture even their temporal necessity and their transient behavior. Thus, we were able to identify the biochemical component that conferred productive fate to the regenerating progenitors. This exciting result made us even more intrigued to investigate how the coordination between the progenitor and its neighbors is able to generate the precise biochemical output for shoot regeneration. We asked what is the nature of this coordinated interaction between the progenitor and neighboring non-progenitor cells? What happens if you disrupt it? To answer this, we undertook a series of approaches. We tracked the growth of the progenitor cells and the neighboring non-progenitor cells at single-cell resolution. Then, we analyzed their differential growth rate using MorphoGraphX. We studied the differential stress patterns between the progenitor cells and their neighbors by visualizing their microtubule orientation. And finally, we disrupted the coordination by targeted laser ablation of either the progenitor or their neighboring cells. These key experiments led us to the following two conclusions: First, there is a mechanical conflict between the progenitor cells and their neighbors. Second, feedback between mechanical and biochemical properties of the cells is crucial to self-organize the cells of shoot progenitors in the absence of any tissue patterning cues. By this time, it was clear that we needed a model to interpret these conclusions. We proposed four models and eliminated three of them. It was most exciting as we steered closer to that one model that all our experimental evidence aligned with. Through this model, we proposed that the expanding non-progenitor cells act as a ‘constriction shell’ similar to a rubber band serving a dual role. First, to facilitate the enclosed progenitor cells to grow and divide, and second to provide a mechanical constriction causing the progenitor cells to bulge out. Meanwhile, the growth of the progenitor cells likely feeds back on the non-progenitor and further triggers its expansion (Fig. 1B-1C) (Varapparambath et al., 2022).
Figure 1: shoot progenitors arise stochastically from undifferentiated callus (A), and abide by the model of “mechanical-conflict” (B) to eventually become a shoot (C).
And what about the flipside: any moments of frustration or despair?
The progenitors, during their early stages, will be buried beneath 2-3 layers of callus cells which makes the progenitor detection and their real-time tracking challenging. This, in addition to the irregular topology of the callus, makes it easy to miss the progenitors. But unfortunately, that was not all. We all could uniformly agree that after performing a whole genome transcriptome approach, you will always end up with more than what you need. This happened to us as well. After much struggle and a marathon of efforts by one of the co-first authors, Vijina, to lead several follow-up genetic experiments and ChIP seq, we landed on a single target, XTH9.
Where will this story take the lab?
This is the first study to integrate the feedback between tissue mechanics and biochemical pathways for specifying cell identity during plant regeneration. But that is just the tip of the iceberg. The lab’s long-term goal will be to seek answers to some of the fundamental questions such as the link between cell division and cell polarity during de novo organogenesis. The lab is also in the process of branching out into exploring cellular heterogeneity using de novo shoot regeneration as a model.
What is next for you after this paper?
After working on this story, I developed an inclination toward the relationship between mechanics, cell polarity, and cell fate. I look forward to exploring it further through theory and modelling-based approaches. Co-first author Vijina aspires to step into the field of evolutionary development. The other co-first author, Anju has her mind fixed on delving deeper into the cell biology of fundamental life processes not just in plants, but also in other organisms.
References
Gordon, S. P., Heisler, M. G., Reddy, G. V, Ohno, C., Das, P. and Meyerowitz, E. M. (2007). Pattern formation during de novo assembly of the Arabidopsis shoot meristem. Development134, 3539–3548.
Kareem, A., Durgaprasad, K., Sugimoto, K., Du, Y., Pulianmackal, A. J., Trivedi, Z. B., Abhayadev, P. V, Pinon, V., Meyerowitz, E. M., Scheres, B., et al. (2015). PLETHORA Genes Control Regeneration by a Two-Step Mechanism. Curr Biol25, 1017–1030.
Varapparambath, V., Mathew, M. M., Shanmukhan, A. P., Radhakrishnan, D., Kareem, A., Verma, S., Ramalho, J. J., Manoj, B., Vellandath, A. R. and Aiyaz, M. (2022). Mechanical conflict caused by a cell-wall-loosening enzyme activates de novo shoot regeneration. Dev. Cell57, 2063–2080.
Zhang, T.-Q., Lian, H., Zhou, C.-M., Xu, L., Jiao, Y. and Wang, J.-W. (2017). A Two-Step Model for de Novo Activation of <em>WUSCHEL</em> during Plant Shoot Regeneration. Plant Cell29, 1073 LP – 1087.
The big news on #ScienceTwitter (and indeed Twitter more broadly) surrounds the flock becoming a herd as the community hedges with more and more users opening accounts on Mastodon.
There is plenty of great advice out there if you are considering moving, or would like to open your first account. We found the top thread useful, and you’ll find us on Mastodon soon. However, while we are learning to toot and boost, it’ll be important to see how moderation works in the herd.
People saying it doesn’t matter which Mastodon instance you join are being misleading: 1. Each one has different moderation policies 2. Not every one allows you to formally “move” there 3. Who is on that instance and who they follow determines your federated timeline content
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