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Dendrite tip: A Neuron Growth Engine

Work done in the lab of Prof. Jonathon Howard at Yale University

About author

Sonal was trained in molecular and structural biology and completed her doctorate in Dr. R. Ravishankar’s lab at the Central Drug Research Institute, Lucknow,

Sonal Shree

India. During her doctoral training she identified a Mycobacterium metabolic enzyme, SerB (serine phosphatases) role as an ‘invasin protein’. She also purified SerB protein and submitted its crystal structures at RSCB protein data bank (PDB). She is working at Joe Howard’s lab to characterize branching morphogenesis in sensory neurons using Drosophila as a model system. She is interested in how complex arbors form and how molecular players such as microtubules and associated proteins (MAPs) regulate branching, growth, and

Sabyasachi Sutradhar

intracellular transport. She is utilizing tissue specific CRISPR, Drosophila genetics, and a spinning disk confocal microscope to understand the underlying mechanism of dendrite branching morphogenesis.

Interview

How would you explain your research outcomes to the non-scientific community?

We perceive the world around us through billions of specialized cells present in our body called “neurons”. Neurons have two different compartments: dendrites and axons. The dendrites act like an antenna and are often highly branched to increase their receptive field. Proper neuronal morphology is extremely important for its function and altered morphology leads to several neurological and neurodevelopmental diseases (e.g. schizophrenia, Down’s syndrome etc.). However, the human brain is complex machinery composed of billions of neurons.  Hence, in our current study, we focused on Class IV sensory neurons of Drosophila. These individual neurons have tree-like branches covering the larval surface and grow from ~50 microns (~100 branches) at 24 hr to ~500 microns (over 3000 branches) at 120 hr. While growing, the tree-like dendrite structure creates a tight meshwork of branches to cover the larval body. We discovered that individual dendrite tips of these neurons are highly dynamic and randomly switch between growth, shrinkage, and paused states acting like growth engines. Apart from this dynamicity, the dendrites also spawn new daughter branches and do not cross each other (a phenomenon called self-avoidance). All these events happen at very short timescales (minutes) and length scales (microns). However, these simple rules are sufficient to explain the overall complex dendrite morphology that is hundreds of microns in size and takes days to develop. Employing these tip growth, branching and self-avoidance rules, we have developed a computational model that recapitulates the observed morphology of Drosophila Class IV sensory neurons.

Drosophila class IV sensory neurons develop complex dendritic morphology over development time. We discovered that these tips transitions stochastically switch between three states - growing, shrinking, and paused. The short timescale and length scale dynamics happening at local dendritic tips eventually give rise to the complex arbor structure.
Drosophila class IV sensory neurons develop complex dendritic morphology over development time. We discovered that these tips transitions stochastically switch between three states – growing, shrinking, and paused. The short timescale and length scale dynamics happening at local dendritic tips eventually give rise to the complex arbor structure.

How do these findings contribute to your research area?

We believe our model can be generalized in other neuronal types as well as other branched cellular systems. We have shown that our model can recapitulate wide ranges of morphologies (Purkinje, amacrine starburst, retinal ganglion etc.). The rule of development  defines the neuronal morphology and knowing these rules will provide priors that constrain connectome maps (structure of brain with all the neuronal connections), just as Ramachandran plots constrain and validate protein structures. Additionally, alteration of these rules by perturbing different protein molecules will allow us to uncover the mechanisms by which these proteins regulate the overall morphology.

“The rule of development  defines the neuronal morphology and knowing these rules will provide priors that constrain connectome maps (structure of brain with all the neuronal connections), just as Ramachandran plots constrain and validate protein structures. ”

What was the exciting moment during your research?

Sonal: Watching these neurons grow on the larval body under microscope just like they grow in a natural environment. These neurons are mechanoreceptors and very sensitive to any kind of pressure or stress, so imaging them in spinning disk confocal for hours was a huge success. Also, whenever my 4-year-old daughter sees these neuron growth movies, she becomes so amazed and says “wow!!! tree with a green firework.” This very sentence fills me with excitement.

Sabya: Analyzing the dendrite tip dynamics data and how well the data was described by our three-state model (growth-pause-shrinkage) was the most exciting part. Furthermore, it was an enormous pleasure seeing the simulated dendrite structures that looked very similar to the experimental data.

What do you hope to do next?

As we said earlier, we are trying to understand how molecules regulate the dendrite tip dynamics and that eventually leads to altered morphologies. Neuronal development plays a crucial role in the etiology of many neuronal diseases such as autism, hereditary spastic paraplegia, lissencephaly etc. that are associated with alterations in dendritic morphology due to perturbation of cytoskeletal proteins. A major difficulty, however, is that it is currently not possible to predict quantitatively how developmental processes occurring at the molecular and subcellular levels determine the morphology of the entire dendritic arbor.

We have been probing the morphology by perturbing different cytoskeletal proteins and trying to understand what aspect of the tip dynamics was altered. Finally, can our data driven computational model generate similar morphology with the altered parameters? Can we bridge the gap between molecules to morphology?

Where do you seek scientific inspiration from?

Our supervisor Prof. Jonathon Howard is a big inspiration to us. The natural world around us, especially collective behaviors , such as bird flocking, fish school etc.  and the way the scientific community tried to explain these phenomena. Our current study is somewhat similar and can be viewed as collective behavior of the dendritic tips.

How do you intend to help Indian science improve?

Sonal: Indian science has improved significantly in recent years. However, I feel there is a great need to introduce and flourish STEM (Science, Technology, Engineering, and Mathematics) education at the level of schools. I had and would like to take part in the outreach program in India to instill interest among the young generation to choose “Science” as their career choice. It should not be the leftover choice after not getting into a prestigious Medical and Engineering program. I would also like to advocate gender equality in the field of science. Also, one should never forget that along with translational research, basic science is very important. It helps us to understand fundamental phenomena of life sciences.

Sabya: There is no denying that many research institutes and universities in India are of international quality. However, in my experience, Indian science still lacks to create a healthy atmosphere of interdisciplinary sciences. I am a biophysicist. Being an interdisciplinary scientist, I would like to see people from different backgrounds and expertise come together to dissect a problem from diverse perspectives. In my opinion, we should reach out to the new generation of students from an early age to inform them about this cross-talk of different scientific fields.

Reference

Sonal Shree, Sabyasachi Sutradhar, Olivier Trottier Yuhai Tu, Xin Liang and Jonathon Howard. Dynamic instability of dendrite tips generates the highly branched morphologies of sensory neurons. Science Advances. Jun 2022, Vol 8, Issue 26, DOI: 10.1126/sciadv.abn00

Copy Editor: Dolly Singh

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