Team 3
Kelci, Tommy, & Sergio
Introduction
ALS Overview/Purpose
We are focusing on studying the influence of specific genes linked to amyotrophic lateral sclerosis (ALS) on neurons and glia by altering their presence in Drosophila (fruit flies). Through successive generations of flies, we introduce these disease-related genes, monitor disease advancement using locomotor tests, and gather relevant data as the flies age. This research aims to elucidate how these genes contribute to the onset of ALS and affect its symptoms. Ultimately, we look to identify and target genes that could play a role in motor deficits in ALS patients.
General Fly information
Differences between male and female Drosophila
Males are smaller, with a shorter abdomen and less thickened stripes. They also have a sex comb present on the fourth segments of the front leg. (Shown in image A below)
Female flies are larger, with a longer abdomen and finer stripes. They also have a spike present on the dorsal surface at the rear side. (Shown in image A below)
Stubble phenotype
Show below is an image depicting the differences between a fly with the stubble phenotype and without
Why are Drosophila a good model organism?
There are multiple technical benefits to utilizing Drosophila compared to vertebrate models. They are simple and cost-effective to cultivate under laboratory conditions, possess a considerably shorter life cycle, generate abundant externally laid embryos, and offer extensive possibilities for genetic modifications. Drosophila genome is 60% homologous to that of humans, less redundant, and about 75% of the genes responsible for human diseases have homologs in flies.
How to determine wild-type from stubble (Sb)
Wild-type has longer thinner strands of "hair" while the flies with stubble have shorter, thicker strand of "hair" that looks similar to when you shave your face and let it grow out a bit.
*Above also displays what a female virgin Drosophila looks like*
Methods
Locomotive Testing
Procedure
Before we begin the locomotive testing it is important that we note all the materials we need.
Graduated cylinder with tape marking the 110 mL line
A box or paper to mark the foreground
A note card including; Team name, date the test occurred, birthdate of the flies, genotype, n value (how many flies are alive).
Parafilm to cover the graduated cylinder.
A camera and tripod adjusted to the level to clearly record the marked label on the cylinder (it is helpful to mark this spot with a piece of tape).
Once you have selected the vial of flies that you want to run a locomotive test on, you will transfer them into the graduated cylinder.
Next you will make sure that the parafilm is secured across the top of the cylinder with no gaps.
Now you will turn on the camera and start recording, you will want to record the completed notecard initially.
Tap the cylinder 6 times gently in a sporadic pattern on a relatively cushioned surface.
Place the cylinder in line with the angle of the camera aligned with the tape marked prior.
Once the cylinder is places set a timer to 2 min note the behavior of the flies.
Transfer flies back to original vial using funnel, then either dispose or put back for further testing.
Video Analysis
Procedure
For sake of organization we used two folders, one with the tile Analyzed videos and another titled Need to be analyzed.
First pick a video in the Need to be analyzed folder.
Next you will start by recording all of the data listed on the index card in the genotype. So you will recording Team name, date the test occurred, birthdate of the flies, genotype, n value (how many flies are alive), in the sheets that lines up with the genotype.
It is easiest as we found, to use the slider to accurately count how many flies pass the line. We will do this in increments of 10 seconds starting from 0- 120 seconds.
Record your findings within the respective Sheets page that corresponds with the information you recorded prior.
Repeat this process for all videos that need to be analyzed
Coding Processing
Data Set Selected: Ziff et.al
Team 3 was given the data set ziff et al. As you can see within the table we were given the gene name listed on the left, along with the p value and the Log2FoldChange. These are important values as the p value indicates significance, the lower the p-value the more significant the gene is regarding implications of of ALS.
Using google colab we had issues converting our dataset into google sheets to integrate into our code. So in order to make sure our genes selected showed phenotypes that we were specifically looking for we opted to look at the data set manually. We compared our gene selected to flybase information to make sure there was a fly ortholog and to ensure there were stocks from bloomington that we could purchase.
How did we Pick Our Genes?
Flybase was a necessary website we used that included all the information we would need to know about our genes. We ended up integrating this process into how we would pick our genes. First we picked a gene with a low p-value (preferably on in the top 300 genes listed). Then we would manually search for the gene in flybase to see if there was a fly ortholog. This ended up being a tedious, time extensive process but it did end up working out in the end.
Once we found a gene that had a fly ortholog, stocks specifically at bloomington, and phenotypes that are not directly lethal. We felt confident in the gene selected. We would even take it a step further, researching our gene to see if it had any direct implications regarding ALS motor functions. All of these methods helped us determine which gene to pick directly from our data set.
Target Genes Identified
RAB1
General Info: Rabs regulate vesicle trafficking including cargo selection, vesicle budding, transport, docking and targeting
Relation to ALS: Encodes a small GTPase which regulates endoplasmic reticulum to Golgi and intra Golgi trafficking. Involved in Notch signaling, cell migration, autophagy. The Notch signaling pathway has been reported to be dysfunctional in neurodegenerative diseases
For these reasons we suspect that this gene is: Downregulated
DDX25
General Info: DDX25 is a part of the Deadbox family of proteins. Involved in the alteration of RNA secondary structure. Pre mRNA splicing. Required in translation initiation, Involved in mRNA export from nucleus, Gene Expression. Specific to certain genes.
Relation to ALS: Processed mRNA is crucial for protein synthesis. Dead box helicases could play a role in regulating protein levels within cells, as a protein cannot be translated unless the mRNA coding for it has been processed.
For these reasons we suspect this gene to be: Upregulated
PSEN1
General Info: PSEN1 is a catalytic subunit of the gamma-secretase complex. Notch receptor processing. Notch signaling pathway. Required for S3 cleavage of Notch, which releases activated Notch protein from the cell membrane. Important role in learning & memory.
Relation to ALS: PSEN1 is likely to be downregulated in ALS as it reduced notch signaling which decreases neuroprotection and increases apoptosis of neurons, weakening muscle and impacting physical function (ALS symptoms)
For these reasons we suspect that this gene is: Downregulated
Gene Crosses
Double Balancer Cross- DDx25
For this cross we are aiming to use a gene that we believe is specifically upregulated within ALS. We would want to see if this gene is able to rescue the phenotype.
Wild Type Cross (PSEN1 + RAB1)
For this cross we are experimenting with the function of our gene in the wild-type (+/+) background.
Results - vglutGAL4;+ vs vglutGAL4;UAS-TDP43 - wks 1&2
Methods for collecting:
Locomotor trials were organized by genotype of fly and age by week. Each week of each genotype was averaged out and organized into the graph below. One-way ANOVA was used for a 4-way comparison at each time point, measuring variance in performance from each genotype and age at each time point. The P-values from the analysis can be found in the table below.
Please note: We did not get the chance to test out our target genotypes. All of the data shown below is concerning our control genotypes, which were vglutGAL4; + and vglutGAL4; UAS-TDP43.
Additional Graphs:
The two graphs below show plots of individual locomotor tests for each genotype. The legends on the right indicate the age of the flies in each trial. There is a clear relationship shown between age and a decline in performance within the vglut;+ flies
Conclusion & Next Steps
Conclusion
The conclusions below cover the data we got from our control tests (vglut;+, vglut;TDP).
One of the main points of data that sticks out for us is our high p-values. Most time points for our locomotor trials had p-values in the 0.20-0.30 range. This creates cause to analyze what may be responsible for this.
Looking at the graph comparing vglut;+ and vglut;TDP flies for weeks 1 & 2 shows that the worst performing flies, on average, were the vglut;+ week 2 flies. This contrasts with our initial expectations of vglut;TDP flies possess the worst performance as age, as we expect the TDP gene to lead to ALS development, and lower performance in locomotor trials should represent the motor function decline that comes with ALS development.
46 individual locomotor trials were used to create the averages seen in the vglut;+ and vglut;TDP flies for weeks 1 & 2, averaging ~11 flies per genotype/week, however, we still believe that collecting more data could be helpful. Behavior can be a difficult measure to quantify, but getting more trials beneath our analysis can help us with confidence in what we are presenting. In our present state, our high p-values combined with our surprising results leave us in a state of needing more data before making reliable conclusions.
Next Steps
This semester we weren't able to get as far as we wanted in terms of actually completing, and testing our genetic crosses. We would like to be able to set up these crosses next semester as we feel each of our genes (RAB1A, PSEN1, DDX25) all show significance in relation to ALS. In regard to the confidence in our findings, unfortunately I think the only thing that would bring our team confidence would be repeating trials a significant amount of times to confirm a trend.
I think the biggest limitations of our study was time. This seems to be a running theme in research, where you aren't able to get enough data within a specific time-frame. I also think another limitation we had was resources as a whole, but I do think this is a factor in which we as students do not have significant input. I mean this by saying more cameras, stations, etc. would also help expedite the process of collecting data. We also acknowledge that due to the restrictive time-frame, we weren't able to consistently maintain or check up on stocks. This is especially relevant in regard to our stocks that we wished to test.
