In the previous experiment, where all the tubes were tested individually, we saw different distributions between this subgroups. Therefor I wanted to test the activity and in particular the speed of single flies of each of this subgroups, to see if this result could be explained by a difference of these parameters. For that I started doing first the Benzer-paradigm to split the flies. Then I took random flies of each of the 6 tubes, cut their wings under cold-anesthesia with 24 hours recovery and after that, tested them in the Buridan.

Below there are the transitionplots of all the different tubes tested (Fig.1-Fig.6). You can see that the flies of the different subgroups seem to have quite similar Transitionplots.

 

In addition I had a look on the activitytime per minute (Fig.7+8), the distance traveled per minute (Fig.9), the pause duration and lengh (Fig.10+11), the number of pauses (Fig.12+13) and the median speed (Fig.14). All activity metrics were calculated in two different ways, the first computation (time-threshold: TT) considers every movement as activity and every absence of movement lasting longer than 1 s as a pause. The second approach (speed threshold: ST) uses the distance traveled by the fly in a sliding window of 1 second duration, measuring its mean velocity during that second.

The activitytime of the flies of the tubes 1, 2,3 and 5 is very similar, however in the tubes 0 and 4 it seems to be more elevated. (Fig. 7+8) If we compare these results to the traveled distance (Fig. 9) we see that tubes 4 shows a higher distance as well, tube 0, in this case, is more similar to the tubes 1, 2,3 and 5.  For the flies of tube 4 this can be explained by the pause duration and the number of pauses per minute (Fig. 10+12+12) because they show less pauses per minute and a slightly reduced duration of this pauses. In addition  we see that the median speed (Fig.14) is lower in the flies of the tube 0, the rest of the tubes are quite similar.

 

 

 

CeTrAn is our software to analyse trajectory data, written in R it is free and open source . It was designed to analyse data obtained in the Buridan’s experiment setup. I am now trying to have a larger scope and incorporate different type of data:, for instance:

– Buridan’s experiment done with a different tracker

– Walking honeybee tracking in a rectangular arena, with a rewarded target

– Animal (flies/bees) walking on a ball, using open- or closed-loop experiment setup

– trajectory data obtained from the pysolo software (flies)

– larval crawling data

I want to include an automatic depository of the data in a database. Automatic entries in Figshare is for instance possible. (see older posts). My problem is to find a way to treat the data such that:

1. the raw data is uploaded

2. all data is uploaded also if we use only the centroid displacement (in some data file the head position is also given)

3. the data can be reused and data obtained in different lab, animal, setup can be compared. (data should be organized such that it can be searched and queried).

4. probably other elements that I do not think of….

 

My main problem: I have nearly no experience in data management/design, ontology or semantic web. Here is a first draft of a database structure that I have thought of. Every feedback would be welcome:

A lot of things I learned at the neurofly. First my old friend Benjamin is doing a great postdoc in Bruno van Swinderen lab. It was great to see his data on isoflurane effects and the correlation between sleep disorder and sensitivity to anesthesia.

More related to our interests, I learned that Paul Tchénio has now a prototype to visualize neuronal activity in about half of the fly brain at a decent frequency. It may be interesting to get in touch with him again.

Andre Fiala is doing/has already done the TDC-Flp construct and is using his own UAS-stop-TRPA1 line to get a subset of octopaminergic neurons. Christine will contact him soon to have more information and maybe start a collaboration with him. The student was not at his/her poster when we went there, and we could not talk directly to him/her.

I nice talk by F. Mohammad (Singapore) showed that centrophobism can be associated with anxiety: the majority of treatments used with mices (for instance immobilisation in a pipet tip) also induce more (or less for some treatments) centrophobisms in flies. I told him about the CeTrAn, he said he will look at it. (his flies were in a squared box, with their wings untouched).

Jhl21 (receptor for JH) change of larval behavior at the  wandering stage (go slower and turn more): it acts at the NMJ to change the clustering of glutamate receptors. Similar thing may happen during the first hour of life of the fly, when they become phototactic ?

A nice poster from the Heisenberg’s lab show that flies do have a preferred 0 torque. Even when giving some closed loop drift, the histogram of torque suggest that the preference for the 0 torque is still there (non-uniform distribution around the +1 torque which stabilize the drift. It seems the distribution around the 0 torque is seen only if you have long enough data, I told them I would ask Satish to look at his distributions. This emphasizes why we need to be very careful in preparing the fly for our experiments…

I may have to look at the OK6 Gal4 line for motorneurons, and new RNAi lines seem to be available for PKC53e and FoxP…

I also talked to Flybase people, David was there. It seems the Buridan results should lead to 2 different entries: one linking each genotype to a dichotomic description of the phenotype (“mutant1” – “has larger”- “median_speed”) and one to the raw data and analysis. This will not be easy to automatize, but looks interesting.

I am probably forgetting a couple of things in addition to my discussion with Anette Schenk and her student Anna about FoxP..

The new version of the analysis software is online. It should be clean and will be the version coming with the paper.

I checked the putative non-flying flies we ordered. All are normal when grown at 18°. While developing at 25°, different phenotypes can be seen:
CyK: those flies have curled wings, but can fly.
U2: those flies have curled wings, cannot fly, but still beat their wings while walking (like if they could not figure out that they cannot fly ?).

other flies show no phenotype at all.

buridan analysis v.2.5 online:
analysis of single flies added, produce a different pdf file.
several minor changes accordingly to this analysis.

By looking at a way to simulate activity/inactivity pattern in the computer generated walk, I found this:

“Fractal time in animal behaviour: the movement activity of Drosophila” Blaine J. Cole 1993

I read it, now I need to search more in order to understand it: maybe we can find ideas to perform more analyses (or corrections to the version we have) and to get better simulated data (how to determine mu in the levy walks)

“Foraging Fruit Flies: Lagrangian and Eulerian, Descriptions of Insect Swarming”
Joseph D. Majkut
phd Thesis

 

mu has to be lower or equal to 3: that’s already some information!

ohh science: the closer we look, the most complex it becomes… I love it!