Benjamin Risse

FIM, a Novel FTIR-Based Imaging Method for High Throughput Locomotion Analysis

We designed a novel imaging technique based on frustrated total internal reflection (FTIR) to obtain high resolution and high contrast movies. This FTIR-based Imaging Method (FIM) is suitable for a wide range of biological applications and a wide range of organisms. It operates at all wavelengths permitting the in vivo detection of fluorescent proteins. To demonstrate the benefits of FIM, we analyzed large groups of crawling Drosophila larvae. The number of analyzable locomotion tracks was increased by implementing a new software module capable of preserving larval identity during most collision events. This module is integrated in our new tracking program named FIMTrack which subsequently extracts a number of features required for the analysis of complex locomotion phenotypes. FIM enables high throughput screening for even subtle behavioral phenotypes. We tested this newly developed setup by analyzing locomotion deficits caused by the glial knockdown of several genes. Suppression of kinesin heavy chain (khc) or rab30 function led to contraction pattern or head sweeping defects, which escaped in previous analysis. Thus, FIM permits forward genetic screens aimed to unravel the neural basis of behavior.

Kinesin Heavy Chain Function in Drosophila Glial Cells Controls Neuronal Activity

Kinesin heavy chain (Khc) is crucially required for axonal transport and khc mutants show axonal swellings and paralysis. Here, we demonstrate that in Drosophila khc is equally important in glial cells. Glial-specific downregulation of khc by RNA interference suppresses neuronal excitability and results in spastic flies. The specificity of the phenotype was verified by interspecies rescue experiments and further mutant analyses. Khc is mostly required in the subperineurial glia forming the blood–brain barrier. Following glial-specific knockdown, peripheral nerves are swollen with maldistributed mitochondria. To better understand khc function, we determined Khc-dependent Rab proteins in glia and present evidence that Neurexin IV, a well known blood–brain barrier constituent, is one of the relevant cargo proteins. Our work shows that the role of Khc for neuronal excitability must be considered in the light of its necessity for directed transport in glia.

Drosophila pupal macrophages – A versatile tool for combined ex vivo and in vivo imaging of actin dynamics at high resolution

Molecular understanding of actin dynamics requires a genetically traceable model system that allows live cell imaging together with high-resolution microscopy techniques. Here, we used Drosophila pupal macrophages that combine many advantages of cultured cells with a genetic in vivo model system. Using structured illumination microscopy together with advanced spinning disk confocal microscopy we show that these cells provide a powerful system for single gene analysis. It allows forward genetic screens to characterize the regulatory network controlling cell shape and directed cell migration in a physiological context. We knocked down components regulating lamellipodia formation, including WAVE, single subunits of Arp2/3 complex and CPA, one of the two capping protein subunits and demonstrate the advantages of this model system by imaging mutant macrophages ex vivo as well as in vivo upon laser-induced wounding.

FIM Imaging and FIMtrack: Two New Tools Allowing High-throughput and Cost Effective Locomotion Analysis

The analysis of neuronal network function requires a reliable measurement of behavioral traits. Since the behavior of freely moving animals is variable to a certain degree, many animals have to be analyzed, to obtain statistically significant data. This in turn requires a computer assisted automated quantification of locomotion patterns. To obtain high contrast images of almost translucent and small moving objects, a novel imaging technique based on frustrated total internal reflection called FIM was developed. In this setup, animals are only illuminated with infrared light at the very specific position of contact with the underlying crawling surface. This methodology results in very high contrast images. Subsequently, these high contrast images are processed using established contour tracking algorithms. Based on this, we developed the FIMTrack software, which serves to extract a number of features needed to quantitatively describe a large variety of locomotion characteristics. During the development of this software package, we focused our efforts on an open source architecture allowing the easy addition of further modules. The program operates platform independent and is accompanied by an intuitive GUI guiding the user through data analysis. All locomotion parameter values are given in form of csv files allowing further data analyses. In addition, a Results Viewer integrated into the tracking software provides the opportunity to interactively review and adjust the output, as might be needed during stimulus integration. The power of FIM and FIMTrack is demonstrated by studying the locomotion of Drosophila larvae.

Stereo and Motion Based 3D High Density Object Tracking

In order to understand the behavior of adult Drosophila melanogaster (fruit flies), vision-based 3D trajectory reconstruction methods are adopted. To improve the statistical strength of subsequent analysis, high-throughput measurements are necessary. However, ambiguities in both stereo matching and temporal tracking appear more frequently in high density situations, aggravating the complexity of the 3D tracking situation. In this paper we propose a high density object tracking algorithm. Instead of approximating trajectories for all frames in a direct manner, in ambiguous situations, tracking is terminated to generate robust tracklets based on the modified tracking-by-matching method. The terminated tracklets are linked to ongoing (unterminated) tracklets with minimum linking cost in an on-line fashion. Furthermore, we introduce a set of new evaluation metrics to analyze the tracking results. These metrics are used to analyse the effect of detection noise and compare our tracking algorithm with two state-of-the-art 3D tracking methods based on simulated data with hundreds of flies. The results indicate that our proposed algorithm outperforms both, the tracking-by-matching algorithm and a global correspondence selection approach.

FIMTrack: An open source tracking and locomotion analysis software for small animals

Imaging and analyzing the locomotion behavior of small animals such as Drosophila larvae or C. elegans worms has become an integral subject of biological research. In the past we have introduced FIM, a novel imaging system feasible to extract high contrast images. This system in combination with the associated tracking software FIMTrack is already used by many groups all over the world. However, so far there has not been an in-depth discussion of the technical aspects. Here we elaborate on the implementation details of FIMTrack and give an in-depth explanation of the used algorithms. Among others, the software offers several tracking strategies to cover a wide range of different model organisms, locomotion types, and camera properties. Furthermore, the software facilitates stimuli-based analysis in combination with built-in manual tracking and correction functionalities. All features are integrated in an easy-to-use graphical user interface. To demonstrate the potential of FIMTrack we provide an evaluation of its accuracy using manually labeled data. The source code is available under the GNU GPLv3 at https://github.com/i-git/FIMTrack and pre-compiled binaries for Windows and Mac are available at http://fim.uni-muenster.de.

Interactions among Drosophila larvae before and during collision.

In populations of Drosophila larvae, both, an aggregation and a dispersal behavior can be observed. However, the mechanisms coordinating larval locomotion in respect to other animals, especially in close proximity and during/after physical contacts are currently only little understood. Here we test whether relevant information is perceived before or during larva-larva contacts, analyze its influence on behavior and ask whether larvae avoid or pursue collisions. Employing frustrated total internal reflection-based imaging (FIM) we first found that larvae visually detect other moving larvae in a narrow perceptive field and respond with characteristic escape reactions. To decipher larval locomotion not only before but also during the collision we utilized a two color FIM approach (FIM2c), which allowed to faithfully extract the posture and motion of colliding animals. We show that during collision, larval locomotion freezes and sensory information is sampled during a KISS phase (german: Kollisions Induziertes Stopp Syndrom or english: collision induced stop syndrome). Interestingly, larvae react differently to living, dead or artificial larvae, discriminate other Drosophila species and have an increased bending probability for a short period after the collision terminates. Thus, Drosophila larvae evolved means to specify behaviors in response to other larvae.

Quantifying subtle locomotion phenotypes of Drosophila larvae using internal structures based on FIM images

Quantitative analysis of behavioral traits requires precise image acquisition and sophisticated image analysis to detect subtle locomotion phenotypes. In the past, we have established Frustrated Total Internal Reflection (FTIR) to improve the measurability of small animals like insects. This FTIR-based Imaging Method (FIM) results in an excellent foreground/background contrast and even internal organs and other structures are visible without any complicated imaging or labeling techniques. For example, the trachea and muscle organizations are detectable in FIM images. Here these morphological details are incorporated into phenotyping by performing cluster analysis using histogram-based statistics for the first time. We demonstrate that FIM enables the precise quantification of locomotion features namely rolling behavior or muscle contractions. Both were impossible to quantify automatically before. This approach extends the range of FIM applications by enabling advanced automatic phenotyping for particular locomotion patterns.

The Ol1mpiad: concordance of behavioural faculties of stage 1 and stage 3 Drosophila larvae.

ABSTRACT Mapping brain function to brain structure is a fundamental task for neuroscience. For such an endeavour, the Drosophila larva is simple enough to be tractable, yet complex enough to be interesting. It features about 10,000 neurons and is capable of various taxes, kineses and Pavlovian conditioning. All its neurons are currently being mapped into a light-microscopical atlas, and Gal4 strains are being generated to experimentally access neurons one at a time. In addition, an electron microscopic reconstruction of its nervous system seems within reach. Notably, this electron microscope-based connectome is being drafted for a stage 1 larva – because stage 1 larvae are much smaller than stage 3 larvae. However, most behaviour analyses have been performed for stage 3 larvae because their larger size makes them easier to handle and observe. It is therefore warranted to either redo the electron microscopic reconstruction for a stage 3 larva or to survey the behavioural faculties of stage 1 larvae. We provide the latter. In a community-based approach we called the Ol1mpiad, we probed stage 1 Drosophila larvae for free locomotion, feeding, responsiveness to substrate vibration, gentle and nociceptive touch, burrowing, olfactory preference and thermotaxis, light avoidance, gustatory choice of various tastants plus odour–taste associative learning, as well as light/dark–electric shock associative learning. Quantitatively, stage 1 larvae show lower scores in most tasks, arguably because of their smaller size and lower speed. Qualitatively, however, stage 1 larvae perform strikingly similar to stage 3 larvae in almost all cases. These results bolster confidence in mapping brain structure and behaviour across developmental stages. Summary: A community-based survey of the behavioural faculties of stage 1 Drosophila larvae, providing a resource for relating these behavioural faculties to the upcoming connectome of their nervous system.

3D trajectory estimation of simulated fruit flies

This paper addresses 3D trajectory estimation of simulated fruit flies assuming a time-synchronized and calibrated 3-camera system. Because the objects have almost the same appearance, both stereo matching and temporal tracking are challenging. In this paper, a third camera is introduced to verify matching and tracking results based on epipolar geometry and projection consistency. This reduces the ambiguity, fetches missed matches and corrects incorrect matches during tracking. Since matching and tracking affect each other, we process both in interaction instead of separately. Unscented Kalman filters are adopted to track objects by modelling motion information, as no distinguishing appearance features are available.