Team 7

Gregory Teng, Audrey White, Jillian Tan, Gabriela Fragozo

Introduction

ALS (Amyotrophic Lateral Sclerosis) is neurodegenerative disease that affects both the brain and locomotor functions.  It attacks the nervous system and primarily causes muscle weakness which in turn can visibly seen through failure in physical movements. This deterioration of muscle movement can ultimately impact walking, swallowing, and even breathing. Medication breakthroughs have been created to slow down its symptoms or relieve some of its discomfort but ultimately there is no cure. Our research purpose is to investigate specific fly genes present in ALS to study its effects on fly behavior.



Our Gene

UAS-NRX-1 (aka "Dark Enlightenment")

We chose NRX-1 based off the Catanese dataset (significant gene data set was FUS) as well as how well NRX-1 presented in ALS. Specifically, we looked at the Average Expression, t-value, and the adjusted p-value. NRX-1 was also extremely attractive to us given its pronounced presence in Drosophila, especially since Neurexin (NRX-1) is required for synapse formation as they are polymorphic cell-surface adhesive molecules in neurons.  


UAS-NRX-1 Data Set from Catanese Data Set for FUS


UAS-Raptor 


We originally chose Raptor as our gene of interest due to gene importance in neuronal activity however we changed our gene of interest due to lack of data statistics supporting Raptor. Raptor is a key part of the rapamycin complex 1 (mTORC1) and is found to play a role in cell growth, protein synthesis, and autophagy. These are all traits of neurons that ALS directly affects.



Genotypes

The parents we used for our gene of interest were vglut-GAL4/vglut-GAL4, +/+ and +/+, UAS-NRX-1/UAS-NRX-1

which is shown in the punnet squares below. 

We also had vglut/+, UAS-TDP43/+ as a control group. 

Setting Up Crosses

To set up our crosses we needed to differentiate between male and female flies, and identify virgin flies. 

Analysis:

We used animalTA to track the flies' movements in the petri dish. AnimalTA gave the average speed of each fly which we then used for ANOVA to determine differences between ages and genotypes. Although videos were recorded for two minutes, some parts of the videos were hard to analyze and therefore some of the analysis times were shorter. 

Tips for AnimalTA:

Do not use the lights, they create glare

You can analyze multiple videos within a project, we chose to keep videos of flies of the same age and genotype in one project. 


Methods

We analyzed the movement of flies by putting small groups in petri dishes and filming them before analyzing the speed of their movement using AnimalTA. 

Steps for Filming Behavior:

1) Flies should have been previously collected and seperated into groups of somewhere between 2 and 7

2) Flip flies into a vial with no food before putting them in ice for 2 minutes

3) Use two funnels taped together to pour cold flies into a petri dish and quickly cover with a white disk

4) Allow the flies to wake up for at least 5 minutes, during this time write important information (age, date, number, genotype) on a napkin

5) Balance a phone, face up, below a microscope stand with the microscope removed, show the napkin, then place the petri dish on the stand and film for two minutes 

6) To transfer flies back to the orignal vial, put the petri dish on ice for a few minutes, then use a single funnel to transfer them back to a vial

Results

vglut-GAL4/+, TDP43/+ by Age

vglut-GAL4,/vglut-GAL4, +/+ by Age

Controls

vgut-GAL4/+, UAS-TDP43/+ and vglut-GAL4/vglut-GAL4, +/+ by age 

We did not have many control flies becuase when we switched to  UAS-NRX-1 from UAS-Raptor, we focused on getting data for UAS-NRX-1 and did not have as much time for the control crosses. We chose not to do any statistical analyses, such as ANOVA, other than mean and standard deviation because we felt we did not have enough flies for it. 

Conclusion

Upon analyzation of our one-way ANOVA results, we can determine that there is a statistically significant difference in the amount of flies (expressed with NRX-1) that show a decline in velocity the older the fly (in weeks) is. However, this is from a split amount of time in experimenting/analyzing so we do not believe our results are generalizable. 

Accounting for the "Dip" in Week 2 NRX-1 Fly Speed

There are two reasons why we assumed this "dip" could have occurred in a seemingly expected linear downwards trend from age (in weeks) and average speed:


NRX-1's interactions with proteins like Neuroligins can affect synaptic plasticity which is critical for the dynamic regulation of synaptic strength/functionality (Südhof, 2008)  NRX-1 expression can change based off different developmental stages, which can reflect its importance in synapse formation. Homeostatic synaptic plasticity is a mechanism in which neurons can maintain stable activity despite neural circuitry changes in which synaptic materials can be mobilized to maintain neurotransmission efficiency (Hong et al., 2020). This could explain how changes in NRX-1 expression might trigger synaptic adjustments to stabilize motor functions in past week 2. However, note that this stabilization seems to occur past week 2. In week 2, it has been seen that extensive synaptic remodeling at the neuromuscular junction, (Chou et al., 2020). The expression of a synapse adhesion gene (NRX-1) can affect synapse remodeling at the neuromuscular junction causing a rapid decrease in motor function until plasticity and other regulatory events stabilize motor function.

Next Steps

Other Genes of Interest 


Limitations 



Citations

Chou, V.T., Johnson, S.A. & Van Vactor, D. Synapse development and maturation at the drosophila neuromuscular junction. Neural Dev 15, 11 (2020). https://doi.org/10.1186/s13064-020-00147-5 

Huilin Hong, Kai Zhao, Shiyan Huang, Sheng Huang, Aiyu Yao, Yuqiang Jiang, Stephan Sigrist, Lu Zhao, Yong Q. Zhang. Journal of Neuroscience 1 April 2020, 40 (14) 2817-2827; DOI: 10.1523/JNEUROSCI.2002-19.2020

Südhof T. C. (2008). Neuroligins and neurexins link synaptic function to cognitive disease. Nature, 455(7215), 903–911. https://doi.org/10.1038/nature07456