Leaping into the Research Potential of Xenopus Frogs

Written By Jadon-Sean Sobejana

Jadon-Sean Sobejana

Illustrations by Anna Bishop

Picture a mother frog laying her eggs in a tranquil pond, a scene we often see in nature documentaries. Now, picture a human mother cradling her newborn baby. At first glance, it may be difficult to spot any similarities between the two scenes. However, the process of development from a single cell to an embryo and finally to a developed organism is strikingly similar for tadpoles and human infants [1]. One species of frog that exhibits this type of development is a western clawed frog species named Xenopus tropicalis, a promising new model for studying human neural development and associated disorders [1, 2, 3]. When it comes to researching the genetic basis of neurodevelopmental disorders, animal research models are especially useful [4, 5]. The majority of current research utilizes rodent models, but X. tropicalis — a unique biological model — offers new perspectives on the brain and genetic changes linked to conditions such as autism spectrum disorder (ASD) [1, 6]. ASD — a neurodevelopmental disorder — impacts how people communicate and socialize, varying from person to person [7, 8, 9]. Many potential genetic markers have been associated with ASD, but there is still a limited understanding of the disorder’s causes [7, 10, 11, 12]. Utilizing the unique biological model of X. tropicalis presents a new approach to understanding the genetic basis of ASD [1,13].

RIBBETING DISCOVERIES IN DEVELOPMENT & GENETIC ENGINEERING

Important similarities between X. tropicalis frogs and humans are evident during embryonic cell development, the journey by which a single cell becomes a fully functioning being. In its embryonic stage, an organism forms and develops through the division and differentiation of cells [14]. All cells created through cell division have an identical genetic code to the first cell to divide, but cellular differentiation allows individual cells to express distinct genes and perform specific functions [14, 15]. Despite these similarities, X. tropicalis’ embryonic cell development differs from that of humans in a particularly intriguing way: when the first X. tropicalis cell divides into two, one new cell continues dividing to form the right side of the frog’s body, while the other cell continues dividing to form the left side of the frog’s body [6]. For most other animals, including humans, the entire body of the organism develops from the initial cell rather than the left and right sides developing independently [1, 14]. X. tropicalis' unique pattern of embryonic development means that one side of the frog can be genetically modified during cellular division while the other side is left untouched [6].

Genetic engineering is employed to investigate the roles of specific genes by creating genetic modifications at the cellular level and observing how modifications affect an organism [16, 17]. Standard genetic engineering experiments modify genes in an embryo that will develop into an animal with the genetic mutation expressed in all of its cells [17]. Then, a group of modified organisms is compared to a group of organisms whose genes have not been altered [17]. Observing differences between the two groups allows us to determine the extent to which specific genes underlie a certain function [17]. A popular method of genetic engineering is CRISPR — a technology that involves injecting embryonic cells with a modified gene of interest [18]. After injection, cells continue to divide, with newly divided cells carrying the mutation [18]. Genetic modification of X. tropicalis utilizes CRISPR to edit one of the two cells that form when the first embryonic cell divides [18]. If the modified gene is injected into the cell that will form the left side of the frog’s body, all cells on the left side of the frog’s body and brain will express the injected gene, but cells on the right side of the frog’s body will not [1]. If we think of the process of gene editing as making a pizza, genetic modifications are like adding or removing toppings. In most animal models, genetic alterations would have to be made to the entire organism, which could be akin to adding toppings to an entire pizza. Each individual comparison in a research study would then require multiple animals: some with modified genes and some unmodified as a control [19, 20]. In the X. tropicalis model, genetic alterations can be made to just one-half of its body, similar to adding toppings to half of a pizza. With the advantage of genetically altering only one-half of its body, the X. tropicalis model itself acts as its own control. Since the same individual is used for comparison, there is no need to control for genetic variation between organisms. The unique embryonic development in X. tropicalis, in tandem with cutting-edge genetic engineering methods, allows us to utilize new technology to explore the complex neurology of ASD [2, 3].

NEURAL FROG-GENITOR CELLS: THE ALTERED X. TROPICALIS BRAIN

Though the exact origins of ASD remain uncertain, a disruption in the formation of connections between nerve cells, or neurons, may be connected to the development of the disorder. This correlation is observable in both X. tropicalis and human brains [3, 21, 22, 23]. Neurons perform a variety of roles and form connections with each other. Before neurons are assigned a specific role, they are called neural progenitor cells (NPCs), which we can think of as ‘blank slates’ that eventually specialize to perform many different functions in the brain [21, 22]. ASD in humans is associated with abnormally increased numbers of NPCs in the brain and a disruption in the specialization and differentiation of these NPCs, which can manifest as an increase in brain size [22, 24, 25, 26]. The combination of increased NPC numbers and disrupted differentiation has been theorized to contribute to the behavioral symptoms of ASD in humans [25].

In addition to X. tropicalis’ ability to act as their own control, X. tropicalis brains develop similarly to human brains, which means that we can use this model to study neurodevelopmental abnormalities displayed by some humans with ASD [1]. When animals are genetically modified to express genetic differences commonly associated with ASD, abnormal brain growth and a disproportionate number of NPCs are evident, both of which are also observed in humans with ASD [22, 27, 28]. In order to insert genes linked to ASD, CRISPR is to modify X. tropicalis by selectively altering the DNA in one of the two cells formed after the first embryonic cell splits [23]. The abnormally large development observed in one hemisphere of the brain serves as a biomarker for the successful application of CRISPR gene-editing techniques [23]. CRISPR has been used across several studies to implement different ASD-linked genes. In all instances, an increase in NPCs was observed, strengthening the correlation between ASD-linked genes and disruptions of NPC specialization [23, 29]. With X. tropicalis, we can control for variation between individual organisms by comparing brain size since the half of the brain that develops from the modified cell may be a different size than the half of the brain that develops from the unmodified cell [29]. The presence of similar abnormalities in the brains of genetically altered X. tropicalis and the brains of humans with ASD supports the utility of X. tropicalis as a neurological model to study ASD [6].

JUMPING ON THE XENOPUS BANDWAGON

When it comes to studying brain development, rodents are commonly used because their DNA closely resembles that of humans; however, the rodent model has specific disadvantages that the X. tropicalis model does not [6, 19, 20]. For one, due to the difficulty of directly editing genes in rodent embryos, two rodents carrying the mutation of interest are bred to produce offspring [6, 30]. An average litter of rodents consists of eight offspring, and of that litter, only a small number will carry the genetically modified trait of interest, requiring labs to breed more rodents to create a workable sample size [6]. On the other hand, a female X. tropicalis frog can lay thousands of eggs at once. We can also directly edit the genes of the tadpole embryos so that all modified X. tropicalis offspring will carry the trait of interest [18]. Another disadvantage of the rodent model is that rodents must be euthanized prior to investigating their pathology, as their brain structure can only be studied after death. To examine rodent brain pathology at multiple moments in development, we need brain samples from multiple rodents euthanized at different ages. Alternatively, X. tropicalis brains can be imaged while the frog is still alive [3, 6]. An advanced technique called two-photon imaging allows us to inject a light-sensitive dye into the live animal, which illuminates brain structures, making them visible through the frog’s transparent skin [31, 32]. Unlike in rodent models, the same individual X. tropicalis brain can be imaged throughout multiple stages of development [32]. Due to the ease of observation, X. tropicalis models augment our research toolbox by allowing for more efficient conduction of certain studies, such as longitudinal studies that follow subjects over time.

IT’S NOT EASY BEING GREEN: THE LIMITATIONS OF XENOPUS

While the possibilities afforded by X. tropicalis as a tool for genetic research are enticing, the model still has some drawbacks [1, 3, 16]. The diagnostic criteria for ASD are based on behavioral changes observed in humans; ASD is a strictly human disorder, and no model organism can successfully replicate ASD’s behavioral symptoms [33, 34]. Although rodent behavior does not manifest in the same way as human behavior, rodent models allow us to test variables such as anxiety-like behavior [35, 36]. For example, rodents that carry a specific genetic mutation associated with ASD display more anxious behavior than rodents without this mutation, as measured by hyperactivity in an open arena [35, 37, 38]. In frogs, standardized behavioral tests to measure anxiety-like behavior and memory do not exist [3, 6]. Therefore, research involving the X. tropicalis model is limited to the potential pathological and genetic mechanisms that are associated with ASD. The inability of X. tropicalis to reflect behavioral symptoms may seem like a significant drawback, but the opportunities presented by the model for augmenting neurological research cannot be understated.

A HOPPORTUNITY FOR THE FUTURE

Over the last decade, our understanding of ASD has improved significantly thanks to new scientific discoveries [39, 40]. Imaging techniques and technology have advanced and revealed specific neural structures and activities correlated with ASD [40, 41, 42]. We have been able to use advanced technology to identify genes that potentially contribute to the development of ASD [40, 43]. However, despite recent advancements, there is a lot left to discover. In an attempt to fill in the gaps in our knowledge, alternative methods and models are being employed [1, 2]. The ability of a single X. tropicalis subject to act as both a mutated subject and a control subject presents exciting possibilities for neurodevelopmental research [6]. Though they are starkly different from humans, X. tropicalis frogs offer an innovative and promising way to study the links between genes and neurodevelopmental disorders such as ASD [1, 2, 23]. X. tropicalis might not immediately answer all of our questions about ASD, but it allows us to leap toward greater advancements in the future.

REFERENCES

  1. Exner, C. R. T., & Willsey, H. R. (2020). Xenopus leads the way: frogs as a pioneering model to understand the human brain. Genesis, 59(1-2). doi: 10.1002/dvg.23405

  2. Nenni, M. J., Fisher, M. E., James-Zorn, C., Pells, T. J., Ponferrada, V., Chu, S., Fortriede, J. D., Burns, K. A., Wang, Y., Lotay, V. S., Wang, D. Z., Segerdell, E., Chaturvedi, P., Karimi, K., Vize, P. D., & Zorn, A. M. (2019). Xenbase: facilitating the use of Xenopus to model human disease. Frontiers in Physiology, 10. doi: 10.3389/fphys.2019.00154

  3. Pratt, K. G., & Khakhalin, A. S. (2013). Modeling human neurodevelopmental disorders in the Xenopus tadpole: from mechanisms to therapeutic targets. Disease Models & Mechanisms, 6(5), 1057–1065. doi: 10.1242/dmm.012138

  4. Yu, Y., Zhang, B., Ji, P., Zuo, Z., Huang, Y., Wang, N., Liu, C., Liu, S.-J., & Zhao, F. (2022). Changes to gut amino acid transporters and microbiome associated with increased E/I ratio in Chd8+/− mouse model of ASD-like behavior. Nature Communications, 13(1). doi: 10.1038/s41467-022-28746-2

  5. Hörnberg, H., Pérez-Garci, E., Schreiner, D., Hatstatt-Burklé, L., Magara, F., Baudouin, S., Matter, A., Nacro, K., Pecho-Vrieseling, E., & Scheiffele, P. (2020). Rescue of oxytocin response and social behaviour in a mouse model of autism. Nature, 584(7820), 252–256. doi: 10.1038/s41586-020-2563-7

  6. Blum, M., & Ott, T. (2019). Xenopus: an undervalued model organism to study and model human genetic disease. Cells Tissues Organs, 205(5-6), 303–313. doi: 10.1159/000490898

  7. Gialloreti, L., & Curatolo, P. (2018). Autism spectrum disorder: why do we know so little? Frontiers in Neurology, 9. doi: 10.3389/fneur.2018.00670

  8. Hodges, H., Fealko, C., & Soares, N. (2020). Autism spectrum disorder: Definition, epidemiology, causes, and clinical evaluation. Translational Pediatrics, 9(1), S55–S65. doi: 10.21037/tp.2019.09.09

  9. American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text revision). doi: 10.1176/appi.books.9780890425787

  10. Lai, M.-C., & Baron-Cohen, S. (2015). Identifying the lost generation of adults with autism spectrum conditions. The Lancet Psychiatry, 2(11), 1013–1027. doi: 10.1016/s2215-0366(15)00277-1

  11. Lyall, K., Croen, L., Daniels, J., Fallin, M. D., Ladd-Acosta, C., Lee, B. K., Park, B. Y., Snyder, N. W., Schendel, D., Volk, H., Windham, G. C., & Newschaffer, C. (2017). The changing epidemiology of autism spectrum disorders. Annual Review of Public Health, 38(1), 81–102. doi: 10.1146/annurev-publhealth-031816-044318

  12. Richards, C., Jones, C., Groves, L., Moss, J., & Oliver, C. (2015). Prevalence of autism spectrum disorder phenomenology in genetic disorders: a systematic review and meta-analysis. The Lancet Psychiatry, 2(10), 909–916. doi: 10.1016/s2215-0366(15)00376-4

  13. Thurm, A., & Swedo, S. (2012). The importance of autism research. Autism and Related Developmental Disorders, 14(3), 219–222. doi: 10.31887/dcns.2012.14.3/athurm

  14. Khan, Y. S., & Ackerman, K. M. (2023). Embryology, Week 1. PubMed; StatPearls Publishing. PMID: 32119449

  15. Rehman, B., & Muzio, M. R. (2023). Embryology, Week 2-3. PubMed; StatPearls Publishing. PMID: 31536285

  16. Kakebeen, A., & Wills, A. (2019). Advancing genetic and genomic technologies deepen the pool for discovery in Xenopus tropicalis. Developmental Dynamics, 248(8), 620–625. doi: 10.1002/dvdy.80

  17. Lanigan, T. M., Kopera, H. C., & Saunders, T. L. (2020). Principles of genetic engineering. Genes, 11(3), 291. doi: 10.3390/genes11030291

  18. Nakayama, T., Blitz, I. L., Fish, M. B., Odeleye, A. O., Manohar, S., Cho, K. W. Y., & Grainger, R. M. (2014). Cas9-Based genome editing in Xenopus tropicalis. Methods in Enzymology, 546, 355–375. doi: 10.1016/B978-0-12-801185-0.00017-9

  19. Li, Z., Zhu, Y.-X., Gu, L.-J., & Cheng, Y. (2021). Understanding autism spectrum disorders with animal models: applications, insights, and perspectives. Zoological Research, 42(6), 800–823. doi: 10.24272/j.issn.2095-8137.2021.251

  20. DeLay, B. D., Corkins, M. E., Hanania, H. L., Salanga, M., Deng, J. M., Sudou, N., Taira, M., Horb, M. E., & Miller, R. K. (2018). Tissue-specific gene inactivation in Xenopus laevis: knockout of lhx1 in the kidney with CRISPR/Cas9. Genetics, 208(2), 673–686. doi: 10.1534/genetics.117.300468

  21. Gilbert, J., & Man, H.-Y. (2017). Fundamental elements in autism: from neurogenesis and neurite growth to synaptic plasticity. Frontiers in Cellular Neuroscience, 11. doi: 10.3389/fncel.2017.00359

  22. Hashem, S., Nisar, S., Bhat, A. A., Yadav, S. K., Azeem, M. W., Bagga, P., Fakhro, K., Reddy, R., Frenneaux, M. P., & Haris, M. (2020). Genetics of structural and functional brain changes in autism spectrum disorder. Translational Psychiatry, 10(1), 1–17. doi: 10.1038/s41398-020-00921-3

  23. Willsey, H. R., Exner, C. R. T., Xu, Y., Everitt, A., Sun, N., Wang, B., Dea, J., Schmunk, G., Zaltsman, Y., Teerikorpi, N., Kim, A., Anderson, A. S., Shin, D., Seyler, M., Nowakowski, T. J., Harland, R. M., Willsey, A. J., & State, M. W. (2021). Parallel in vivo analysis of large-effect autism genes implicates cortical neurogenesis and estrogen in risk and resilience. Neuron, 109(5), 788-804.e8. doi: 10.1016/j.neuron.2021.01.002

  24. Connacher, R., Williams, M., Prem, S., Yeung, P. L., Matteson, P., Mehta, M., Markov, A., Peng, C., Zhou, X., McDermott, C. R., Pang, Z. P., Flax, J., Brzustowicz, L., Lu, C.-W., Millonig, J. H., & DiCicco-Bloom, E. (2022). Autism NPCs from both idiopathic and CNV 16p11.2 deletion patients exhibit dysregulation of proliferation and mitogenic responses. Stem Cell Reports, 17(6), 1380–1394. doi: 10.1016/j.stemcr.2022.04.019

  25. Marchetto, M. C., Belinson, H., Tian, Y., Freitas, B. C., Fu, C., Vadodaria, K. C., Beltrao-Braga, P. C., Trujillo, C. A., Mendes, A. P. D., Padmanabhan, K., Nunez, Y., Ou, J., Ghosh, H., Wright, R., Brennand, K. J., Pierce, K., Eichenfield, L., Pramparo, T., Eyler, L. T., & Barnes, C. C. (2017). Altered proliferation and networks in neural cells derived from idiopathic autistic individuals. Molecular Psychiatry, 22(6), 820–835. doi: 10.1038/mp.2016.95

  26. Pretzsch, C. M., & Ecker, C. (2023). Structural neuroimaging phenotypes and associated molecular and genomic underpinnings in autism: a review. Frontiers in Neuroscience, 17. doi: 10.3389/fnins.2023.1172779

  27. Wang, M., Wei, P.-C., Lim, C. K., Gallina, I. S., Marshall, S., Marchetto, M. C., Alt, F. W., & Gage, F. H. (2020). Increased neural progenitor proliferation in a hiPSC model of autism induces replication stress-associated genome instability. Cell Stem Cell, 26(2), 221-233.e6. doi: 10.1016/j.stem.2019.12.013

  28. Kaushik, G., & Zarbalis, K. S. (2016). Prenatal neurogenesis in autism spectrum disorders. Frontiers in Chemistry, 4. doi: 10.3389/fchem.2016.00012

  29. Willsey, H. R., Xu, Y., Everitt, A., Dea, J., Exner, C. R. T., Willsey, A. J., State, M. W., & Harland, R. M. (2020). The neurodevelopmental disorder risk gene DYRK1A is required for ciliogenesis and brain size in Xenopus embryos. Development. doi: 10.1242/dev.189290

  30. Kumar, T. R., Larson, M., Wang, H., McDermott, J., & Bronshteyn, I. (2009). Transgenic mouse technology: principles and methods. Methods in Molecular Biology, 590, 335–362. doi: 10.1007/978-1-60327-378-7_22

  31. Ueki, H., Wang, I-Hsuan., Zhao, D., Gunzer, M., & Kawaoka, Y. (2020). Multicolor two-photon imaging of in vivo cellular pathophysiology upon influenza virus infection using the two-photon IMPRESS. Nature Protocols, 15(3), 1041–1065. doi: 10.1038/s41596-019-0275-y

  32. Cline, H. T. (2022). Imaging structural and functional dynamics in Xenopus neurons. CSH Protocols, 2022(2), pdb.top106773–pdb.top106773. doi: 10.1101/pdb.top106773

  33. Ruhela, R. K., Prakash, A., & Medhi, B. (2015). An urgent need of experimental animal model of autism in drug development. Annals of Neurosciences, 22(1). doi: 10.5214/ans.0972.7531.220210

  34. Meyza, K. Z., Defensor, E. B., Jensen, A. L., Corley, M. J., Pearson, B. L., Pobbe, R. L. H., Bolivar, V. J., Blanchard, D. C., & Blanchard, R. J. (2013). The BTBR T+tf/J mouse model for autism spectrum disorders–in search of biomarkers. Behavioural Brain Research, 251, 25–34. doi: 10.1016/j.bbr.2012.07.021

  35. Kazdoba, T. M., Leach, P. T., Yang, M., Silverman, J. L., Solomon, M., & Crawley, J. N. (2015). Translational mouse models of autism: advancing toward pharmacological therapeutics. Current Topics in Behavioral Neurosciences, 28, 1–52. doi: 10.1007/7854_2015_5003

  36. Amodeo, D. A., Yi, J., Sweeney, J. A., & Ragozzino, M. E. (2014). Oxotremorine treatment reduces repetitive behaviors in BTBR T+ tf/J mice. Frontiers in Synaptic Neuroscience, 6. doi: 10.3389/fnsyn.2014.00017

  37. Seibenhener, M. L., & Wooten, M. C. (2015). Use of the open field maze to measure locomotor and anxiety-like behavior in mice. Journal of Visualized Experiments, 96. doi: 10.3791/52434

  38. Lázaro, M. T., & Golshani, P. (2015). The utility of rodent models of autism spectrum disorders. Current Opinion in Neurology, 28(2), 103–109. doi: 10.1097/wco.0000000000000183

  39. Jiang, M., Lu, T., Yang, K., Li, X., Zhao, L., Zhang, D., Li, J., & Wang, L. (2023). Autism spectrum disorder research: knowledge mapping of progress and focus between 2011 and 2022. 14. doi: 10.3389/fpsyt.2023.1096769

  40. Damiano, C. R., Mazefsky, C. A., White, S. W., & Dichter, G. S. (2014). Future directions for research in autism spectrum disorders. Journal of Clinical Child & Adolescent Psychology, 43(5), 828–843. doi: 10.1080/15374416.2014.945214

  41. Ecker, C., & Murphy, D. (2014). Neuroimaging in autism—from basic science to translational research. Nature Reviews Neurology, 10(2), 82–91. doi: 10.1038/nrneurol.2013.276

  42. Aoki, Y., Abe, O., Nippashi, Y., & Yamasue, H. (2013). Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: a meta-analysis of diffusion tensor imaging tractography studies. Molecular Autism, 4(1), 25. doi: 10.1186/2040-2392-4-25

  43. Jeste, S. S., & Geschwind, D. H. (2014). Disentangling the heterogeneity of autism spectrum disorder through genetic findings. Nature Reviews Neurology, 10(2), 74–81. doi: 10.1038/nrneurol.2013.278

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