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.

 

 

 

For newcomers in the lab and mainly students who want to work on the Buridan setup I wrote a protocol that can be used for all kinds of Buridan experiments. Colorful illustrations will be helpful to easily understand the data processing program. Please, download the protocol here: A General Buridan Protocol

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:

I post these figures here ; we discussed in last meeting about these figures

GRIP on Inter event intervals of Buridan output data ,,, time threshold method,

Inter activity interval

 

 

Inter pause interval

 

 

 

I am receiving GRIP results with NaN (no number available for at least 28 flies and Infinitive for the few more) and I checked twice. I

Basically I am extracting inter event intervals and had it run by GRIP to see the level of randomness.GRIP is based on decimal extension of pi.

The loss of tßh in adult flies leads to decreased walking speed and an increase in stripe fixation. Rescuing the gene by a heat shock construct (flies from Henrike Scholz, Cologne) increases walking speed back to wild type level but cannot change stripe fixation.

It is possible that the phenotype in stripe fixation is not exclusively tßh-dependent but more due to other problems the tßh-mutants have, e.g. developmental defects. That would ask for another heat shock timing.

Results:

–          1^st cross

 

 

 

 

 

 

 

 

 

 

 

 

 

–          2^nd cross