The Backyard Brains 2018 Summer Research Fellowship is coming to a close, but not before we get some real-world scientific experience in! Our research fellows are nearing the end of their residency at the Backyard Brains lab, and they are about to begin their tenure as neuroscience advocates and Backyard Brains ambassadors. The fellows dropped in on University of Michigan’s Undergraduate Research Opportunity Program (UROP) Symposium during their final week of the fellowship, and each scientist gave a quick poster presentation about the work they’d been doing this summer! The fellows synthesized their data into the time-honored poster format and gave lightning-round pitches of their work to attendees. BYB is in the business of creating citizen scientists, and this real-world application is always a highlight of our fellowship. Check out their posters below!
Hello, everyone! Welcome back to the last installment of silkmoth updates. Things are starting to wrap up here this summer, and I’ve begun to analyze the data I have been collecting.
Behavioral Data Analysis
Last post, I explained the behavior assay that I am using with the moths to demonstrate how the sex pheromone bombykol can alter behavior. I have run over 100 trials since then and have been working on visualizing my data set. The Google Sheets pivot table feature has been a serious life saver for quick filtering and data wrangling. If you haven’t used it before, do it! Or I can force you to sit through an overly-enthusiastic demo like the rest of my labmates (sorry guys).
The moths have three choices during the experiment: they can choose the stimulus side, the control side, or have no response. No response is defined as no movement after 30 seconds of being placed in the chamber. Overall, the moths tend not to move unless they have a really good reason to expend their limited energy. Thankfully, this makes my job as an observer fairly easy, although boring at times, and the behavior response to bombykol very obvious.
My first visualization was to show the spatial preferences of the moths in the arena for each stimulus. Below is a schematic of the arena paired with horizontal bar charts for males and females for each stimulus.
Schematic of behavior task. B. Choice results for all female trials. C. Choice results for all male trials
For the females, behavior does not appear to be influenced by stimulus type- overall the bars look about the same with the majority of the time ‘no choice’ being made. For the males, it can be seen that when a female or synthetic bombykol is present, there is a greater amount of response. I believe the bombykol response is more profound than the female response for two reasons. First, the concentration of synthetic bombykol I’m using is very high. Second, sometimes when a female is in the arena she does not protrude her gland that releases bombykol, which makes it impossible for the males to know she is there.
Although the plots above do a good job with spatial representation, they not account for what I truly care about- reproductive behavior. Sometimes a male can be doing reproductive behavior and will be so excited that he dances around the arena and ends up on the control side by the end of the trial. To account for this, I’ve made a second plot with average frequency of reproductive behavior for each stimulus type. It can be seen that bombykol and females induce far more reproductive behavior than linalool or mineral oil. Linalool and mineral oil should technically have no reproductive behavior, but sometimes things can get contaminated even while I’m using separate chambers. By the end of some days, I’m pretty sure I am covered in bombykol, so I have become more careful in what order I run experiments.
Average reproductive behavior frequency observed during behavior assay for male moths.
Now that the data has been visualized, I am working to run statistical analysis on it. I will need to run a model that accounts for testing cohorts of moths multiple times (versus each trial having a new sample). This will likely be a repeated measures analysis of variance (RM-ANOVA) with post hoc Tukey test. I’ve been communicating with one of my teachers back at Westminster to determine which model is most appropriate for my dataset and will have those results soon.
Electrophysiology Problems & Solutions
Now onto electrophysiology! Last time I checked in, I was having difficulties recording consistent electroantennogram (EAG) data from the moth antenna. I was able to determine that the issue I was having was due to a poor connection between the electrode and the antenna. I determined this through a variety of experiments using a resistor instead of the antenna and applying various types of conductive gels and pastes. When the connection was good, the resistor would flat line and have no response to any of the stimuli blown on it (as it should since it’s not alive). When the connection was poor, it would give inconsistent, biological-ish responses due to the connection moving around, gel interacting with different substances and additional unknown factors.
For a few days I thought the EAG portion of my project was done- how could I determine if the connection was ‘good’ if a poor connection gave something that could easily be mistaken as biological? After running many troubleshooting trials and reaching out to a variety of resources, it turns out that when I blow on the antenna and it gives a large, high frequency spike, the connection is poor. So, I sporadically blow on the prep throughout the trial to make sure things are going well. I also switched from using an electrode gel to a more expensive electrode paste that appears to last much longer and create a better connection.
With these new methods I have begun to collect data that is much more consistent. I am only testing 3 compounds now: mineral oil (solvent/negative control), linalool (positive control) and bombykol (sex pheromone). Last week I ran trials in males and females and observed different responses. The females have a larger response to linalool and no response to bombykol or mineral oil, while the males response to linalool and bombykol. Seen below is an overlay of raw data from a trial with males on the left and females on the right that displays the response. This is similar to what has been found in research and has given me full confidence that my new method is working.
As you can see, this data lacks alignment, which makes further analysis very difficult. To align the data, I created a DIY laser beam with an LED and photoresistor that indicates when the stimulus is present.
Image of set up. Cotton ball blocking light signal across LED and photoresistor. Stimulus is on cotton ball and pulled into fan by air current.
This setup allows me to align each trial to stimulus onset. I am currently working with Ben on a code in Python that will automatically sort through the data and the statistical values we need to run analysis. Below is an image of the raw data in spike recorder. The red line is the stimulus marker and the green line is the recording from the antenna. You can see that when the stimulus (bombykol) is presented there is a slow hyperpolarization in the antenna as seen in previous literature.
Raw EAG response to bombykol. Red line is stimulus onset and green line is antenna.
I am psyched with the progress I have made since the last post. While I’m collecting additional data this week I will also be building a poster and preparing the classroom manuals and visuals for my project. I believe communicating one’s work is often the most difficult, yet important part of the scientific process. I’m looking forward to sharing my work and receiving some feedback on how to make it better. I hope to have more updates as I continue to work on this project while finishing up my bachelors degree this Fall. Thanks for following along and stay tuned!
Hello, everyone! It’s Jess again. Since I last wrote, I have shifted all my work from cockroaches over to silk moths. I’ve had to make a few modifications to my protocols, but overall the transition has been smooth. Working with the silk moths has been far more enjoyable than the cockroaches (no offense roaches, but you freak me out), and I’ve really settled into my role as a moth mom. The moths will hang out anywhere you put them–sometimes I even walk around with them on my shoulder when I am getting ready for experiments and have to carry other things!
Left: Female silk moth perched on her cup.
Right: silk moth along for a ride
Behavior
In my last post I mentioned how the experiment has two parts: behavioral observation and electrophysiology. Unlike the cockroach experiment, designing a behavioral paradigm for the moths was fairly simple because the male silk moth’s response to the sex pheromone bombykol is extremely profound. I suppose if you’re only alive for five days reproduction is kind of a huge deal?
For my assay, I use a binary choice paradigm. The materials are simple, dixie cups (to raise the chemicals off the ground so moths can’t touch them), multiple tupperware containers, and the compounds of your choice.
Three females starting the behavior task
For the experiment, I place a stimulant and corresponding control dixie cups on opposite ends of the tupperware, place a group of same sex moths in the middle and record what half of the arena they are in after 5 minutes have passed. Sometimes, the moths will not move for the full 5 minute trial, so they receive a ‘no choice’ score. All trials are recorded to ensure correct scoring and for the potential to be used in Anastasiya’s awesome tracking program when it’s complete.
In addition to scoring how many moths end up on the stimulant or control side, I also record how many moths are performing reproductive behavior. When the females emit the pheromone from a gland in their posterior, the males begin to rapidly flap their wings and spin around in circles as they orient themselves to the location of the female. It looks like this:
Three males responding to a female emitting bombykol
Males also have this same response when I place synthetic bombykol in the arena. In addition to bombykol, I am testing linalool (plant terpene found in the Mulberry leaves silkworms eat), ethanol (accessible positive control for electrophysiology), de-ionized water (ethanol solvent), mineral oil (linalool and bombykol solvent), in male moths and female moths. I’ve run 40 trails, and it appears that bombykol and female moths are the only things that change behavior in the males, and the females have no response to any of the stimulants. By the next blog post, I will have a visualization of my results.
Electrophysiology
Observing consistent electrophysiology result has been (and still is) the challenge of this project. The silk moth antenna is significantly more sensitive to mechanosensation than the cockroach and can quickly become overstimulated. Additionally, many of the compounds are oil-based, so they coat the interior of the syringe and make deployment difficult and inconsistent. I’ve come up with a couple solutions to my problems, and now I just need to figure out how work them together.
First, have modified a fan from the BYB office using a milk jug container to direct light airflow on the prep. This reduces the noise from other wind artifacts (literally breathing on the prep gives signal). Second, using a sponge soaked in DI water, I have humidified the airstream to make the prep last longer.
Modified fan and humidified air set-up
The last, most challenging step has been determining how to deliver the stimulus. Ideally, I would like to inject it into the airstream, but as I mentioned above, the deployment of the syringes does not work well. I have tried blowing air through the syringe onto the prep, and soaking sponges with stimulant and placing them in the airstream. This week I will be prototyping some new ideas.
Some days my data is beautiful, and some days it looks like shit. A bit of the variation I am seeing is also due to the hardware. I am currently deciding which BYB board will work best to record at the low frequencies I need and this alone can distort the signal from preparation to preparation.
Example of two ethanol trials looking very different just a few minutes apart.
The good news is that I have plenty of time and moths to figure this out. Also, not getting consistent data is frustrating, but this is one of the best part of research- when nothing really makes sense, you kind of hate the procedure, and then one day after you’ve tried it enough times, it miraculously works and you want to do it all over again. I made some good progress today, I’m sure I’ll make good progress tomorrow, and hopefully by the next post I’ll have some consistent data to show you all!