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

<div><p>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 <a href="https://github.com/i-git/FIMTrack" target="_blank">https://github.com/i-git/FIMTrack</a> and pre-compiled binaries for Windows and Mac are available at <a href="http://fim.uni-muenster.de" target="_blank">http://fim.uni-muenster.de</a>.</p></div

Assessing motor-related phenotypes of Caenorhabditis elegans with the wide field-of-view nematode tracking platform

Caenorhabditis elegans is a valuable model organism in biomedical research that has led to major discoveries in the fields of neurodegeneration, cancer and aging. Because movement phenotypes are commonly used and represent strong indicators of C. elegans fitness, there is an increasing need to replace manual assessments of worm motility with automated measurements to increase throughput and minimize observer biases. Here, we provide a protocol for the implementation of the improved wide field-of-view nematode tracking platform (WF-NTP), which enables the simultaneous analysis of hundreds of worms with respect to multiple behavioral parameters. The protocol takes only a few hours to complete, excluding the time spent culturing C. elegans, and includes (i) experimental design and preparation of samples, (ii) data recording, (iii) software management with appropriate parameter choices and (iv) post-experimental data analysis. We compare the WF-NTP with other existing worm trackers, including those having high spatial resolution. The main benefits of WF-NTP relate to the high number of worms that can be assessed at the same time on a whole-plate basis and the number of phenotypes that can be screened for simultaneously

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 (FIM(2c)), 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

Drug discovery: Insights from the invertebrate Caenorhabditis elegans

Therapeutic drug development is a long, expensive, and complex process that usually takes 12–15 years. In the early phases of drug discovery, in particular, there is a growing need for animal models that ensure the reduction in both cost and time. Caenorhabditis elegans has been traditionally used to address fundamental aspects of key biological processes, such as apoptosis, aging, and gene expression regulation. During the last decade, with the advent of large-scale platforms for screenings, this invertebrate has also emerged as an essential tool in the pharmaceutical research industry to identify novel drugs and drug targets. In this review, we discuss the reasons why C. elegans has been positioned as an outstanding cost-effective option for drug discovery, highlighting both the advantages and drawbacks of this model. Particular attention is paid to the suitability of this nematode in large-scale genetic and pharmacological screenings. High-throughput screenings in C. elegans have indeed contributed to the breakthrough of a wide variety of candidate compounds involved in extensive fields including neurodegeneration, pathogen infections and metabolic disorders. The versatility of this nematode, which enables its instrumentation as a model of human diseases, is another attribute also herein underscored. As illustrative examples, we discuss the utility of C. elegans models of both human neurodegenerative diseases and parasitic nematodes in the drug discovery industry. Summing up, this review aims to demonstrate the impact of C. elegans models on the drug discovery pipeline.Fil: Giunti, Sebastián. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Andersen, Natalia Denise. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: Rayes, Diego Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; ArgentinaFil: de Rosa, Maria Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Bioquímicas de Bahía Blanca. Universidad Nacional del Sur. Instituto de Investigaciones Bioquímicas de Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Biología, Bioquímica y Farmacia; Argentin

Dissecting cause and effect in host-microbiome interactions using the combined worm-bug model system

High-throughput molecular studies are greatly advancing our knowledge of the human microbiome and its specific role in governing health and disease states. A myriad of ongoing studies aim at identifying links between microbial community disequilibria (dysbiosis) and human diseases. However, due to the inherent complexity and heterogeneity of the human microbiome we need robust experimental models that allow the systematic manipulation of variables to test the multitude of hypotheses arisen from large-scale ‘meta-omic’ projects. The nematode C. elegans combined with bacterial models offers an avenue to dissect cause and effect in host-microbiome interactions. This combined model allows the genetic manipulation of both host and microbial genetics and the use of a variety of tools, to identify pathways affecting host health. A number of recent high impact studies have used C. elegans to identify microbial pathways affecting ageing and longevity, demonstrating the power of the combined C. elegans-bacterial model. Here I will review the current state of the field, what we have learned from using C. elegans to study gut microbiome and host interactions, and the potential of using this model system in the future

JAABA: interactive machine learning for automatic annotation of animal behavior

We present a machine learning-based system for automatically computing interpretable, quantitative measures of animal behavior. Through our interactive system, users encode their intuition about behavior by annotating a small set of video frames. These manual labels are converted into classifiers that can automatically annotate behaviors in screen-scale data sets. Our general-purpose system can create a variety of accurate individual and social behavior classifiers for different organisms, including mice and adult and larval Drosophila