A Mechanism for Spatial Orientation Based on Sensory Adaptation in Caenorhabditis Elegans

During chemotaxis, animals compute spatial information about odor gradients to make navigational choices for finding or avoiding an odor source. The challenge to the neural circuitry is to interpret and respond to odor concentrations that change over time as animals traverse a gradient. In this thesis, I ask how a nervous system regulates spatial navigation by studying the chemotaxis response of Caenorhabditis elegans to diacetyl. A behavioral analysis demonstrated that AWA sensory neurons drive chemotaxis over several orders of magnitude in odor concentration, providing an entry point for dissecting the mechanistic basis of chemotaxis at the level of neural activity. Precise microfluidic stimulation enabled me to dissociate space from time in the olfactory input to characterize how odor sensing relates to behavior. I systematically measured neuronal responses to odor in the diacetyl chemotaxis circuit, aided by a newly developed imaging system with flexible stimulus delivery and elevated throughput. I found reliable sensory responses to the behaviorally relevant range of odor concentrations. I then followed odor-evoked activity to downstream interneurons that integrate sensory input. Adaptation of neuronal responses to odor yielded a highly sensitive response to small increases in odor concentration at the interneuron level, providing a mechanism for efficient gradient sensing during klinokinesis. Adaptation dynamics at the sensory level were stimulus-dependent and cell-autonomously altered in several classes of mutant animals. Behavioral responses to different concentrations of diacetyl resulted from overlapping contributions from multiple sensory neurons. AWA was specifically required for orientation behavior in response to small increases in odor concentration that are encountered in shallow gradients, demonstrating functional specialization amongst sensory neurons for stimulus characteristics. This work sheds light on an algorithm underlying acute behavioral computation and its biological implementation. The experimental results are presented in two parts: Chapter 2 describes the development of a microscope for high-throughput imaging of neuronal activity in Caenorhabditis elegans. I present a characterization of chemosensory responses to odor and its correlation with behavior. This work has been published (Larsch et al., 2013). Chapter 3 describes the functional architecture of the AWA chemosensory circuit and the role of adaptation in maintaining sensitivity over a wide range of stimulus intensities. This work is currently being prepared for publication

Automated Sustainability Compliance Checking Using Process Mining and Formal Logic

Business processes need to have certain constraints such that they can lead to sustainable outcomes. These constraints can be manifold and their adherence has to be monitored. In the past compliance checking has been applied in several business domains without considering certain sustainability aspects, such as multi-dimensionality and impact level. With my research I want to contribute to the application of compliance checking techniques for the purpose of sustainability compliance. In order to achieve this, I want to analyse and develop data-driven approaches, which allow to automate the task of compliance checking. The way in which this can be achieved, is be combining methods from process mining with formal languages that can express sustainability rules in a machine-readable manner. The main goal is to develop a compliance engine that can be adapted by ERP systems in order to evaluate sustainability conformance in business processes

Oscillatory stimuli differentiate adapting circuit topologies

This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this record.Biology emerges from interactions between molecules, which are challenging to elucidate with current techniques. An orthogonal approach is to probe for 'response signatures' that identify specific circuit motifs. For example, bistability, hysteresis, or irreversibility are used to detect positive feedback loops. For adapting systems, such signatures are not known. Only two circuit motifs generate adaptation: negative feedback loops (NFLs) and incoherent feed-forward loops (IFFLs). On the basis of computational testing and mathematical proofs, we propose differential signatures: in response to oscillatory stimulation, NFLs but not IFFLs show refractory-period stabilization (robustness to changes in stimulus duration) or period skipping. Applying this approach to yeast, we identified the circuit dominating cell cycle timing. In Caenorhabditis elegans AWA neurons, which are crucial for chemotaxis, we uncovered a Ca2+ NFL leading to adaptation that would be difficult to find by other means. These response signatures allow direct access to the outlines of the wiring diagrams of adapting systems.The work was supported by US National Institutes of Health grant 5RO1-GM078153-07 (F.R.C.), NRSA Training Grant CA009673-36A1 (S.J.R.), a Merck Postdoctoral Fellowship at The Rockefeller University (S.J.R.), and the Simons Foundation (S.J.R.). J.L. was supported by a fellowship from the Boehringer Ingelheim Fonds. E.D.S. was partially supported by the US Office of Naval Research (ONR N00014-13-1-0074) and the US Air Force Office of Scientific Research (AFOSR FA9550-14-1-0060)

The effect of activity and novelty on response frequency in a two-choice learning situation.

Originally published in Optics Express on 23 March 2015 (oe-23-6-7734

Everything is INTERRELATED:Teaching Software Engineering for Sustainability

Sustainability has become an important concern across many disciplines,and software systems play an increasingly central role in addressing it. However, teaching students from software engineering and related disciplines to effectively act in this space requires interdisciplinary courses that combines the concep to of sustainability with software engineering practice and principles. Yet, presently little guidance exist on which subjects and materials to cover in such courses and how, combined with a lack of reusable learning objects. This paper describes a summer school course on Software Engineering for Sustainability (SE4S). We provide a blueprint for this course, in the hope that it can help the community develop a shared approach and methods to teaching SE4S. Practical lessons learned from delivery of this course are also reported here, and could help iterate over the course materials, structure, and guidance for future improvements. The course blueprint, availability of used materials and report of the study results make this course viable for replication and further improvement

Regulation of two motor patterns enables the gradual adjustment of locomotion strategy in Caenorhabditis elegans

In animal locomotion a tradeoff exists between stereotypy and flexibility: fast long-distance travelling (LDT) requires coherent regular motions, while local sampling and area-restricted search (ARS) rely on flexible movements. We report here on a posture control system in C. elegans that coordinates these needs. Using quantitative posture analysis we explain worm locomotion as a composite of two modes: regular undulations versus flexible turning. Graded reciprocal regulation of both modes allows animals to flexibly adapt their locomotion strategy under sensory stimulation along a spectrum ranging from LDT to ARS. Using genetics and functional imaging of neural activity we characterize the counteracting interneurons AVK and DVA that utilize FLP-1 and NLP-12 neuropeptides to control both motor modes. Gradual regulation of behaviors via this system is required for spatial navigation during chemotaxis. This work shows how a nervous system controls simple elementary features of posture to generate complex movements for goal-directed locomotion strategies

Oxygen-sensing neurons reciprocally regulate peripheral lipid metabolism via neuropeptide signaling in <i>Caenorhabditis elegans</i>

<div><p>The mechanisms by which the sensory environment influences metabolic homeostasis remains poorly understood. In this report, we show that oxygen, a potent environmental signal, is an important regulator of whole body lipid metabolism. <i>C</i>. <i>elegans</i> oxygen-sensing neurons reciprocally regulate peripheral lipid metabolism under normoxia in the following way: under high oxygen and food absence, URX sensory neurons are activated, and stimulate fat loss in the intestine, the major metabolic organ for <i>C</i>. <i>elegans</i>. Under lower oxygen conditions or when food is present, the BAG sensory neurons respond by repressing the resting properties of the URX neurons. A genetic screen to identify modulators of this effect led to the identification of a BAG-neuron-specific neuropeptide called FLP-17, whose cognate receptor EGL-6 functions in URX neurons. Thus, BAG sensory neurons counterbalance the metabolic effect of tonically active URX neurons via neuropeptide communication. The combined regulatory actions of these neurons serve to precisely tune the rate and extent of fat loss to the availability of food and oxygen, and provides an interesting example of the myriad mechanisms underlying homeostatic control.</p></div

Pheromone-sensing neurons regulate peripheral lipid metabolism in <i>Caenorhabditis elegans</i>

It is now established that the central nervous system plays an important role in regulating whole body metabolism and energy balance. However, the extent to which sensory systems relay environmental information to modulate metabolic events in peripheral tissues has remained poorly understood. In addition, it has been challenging to map the molecular mechanisms underlying discrete sensory modalities with respect to their role in lipid metabolism. In previous work our lab has identified instructive roles for serotonin signaling as a surrogate for food availability, as well as oxygen sensing, in the control of whole body metabolism. In this study, we now identify a role for a pair of pheromone-sensing neurons in regulating fat metabolism in C. elegans, which has emerged as a tractable and highly informative model to study the neurobiology of metabolism. A genetic screen revealed that GPA-3, a member of the Gα family of G proteins, regulates body fat content in the intestine, the major metabolic organ for C. elegans. Genetic and reconstitution studies revealed that the potent body fat phenotype of gpa-3 null mutants is controlled from a pair of neurons called ADL(L/R). We show that cAMP functions as the second messenger in the ADL neurons, and regulates body fat stores via the neurotransmitter acetylcholine, from downstream neurons. We find that the pheromone ascr#3, which is detected by the ADL neurons, regulates body fat stores in a GPA-3-dependent manner. We define here a third sensory modality, pheromone sensing, as a major regulator of body fat metabolism. The pheromone ascr#3 is an indicator of population density, thus we hypothesize that pheromone sensing provides a salient 'denominator' to evaluate the amount of food available within a population and to accordingly adjust metabolic rate and body fat levels

Microfluidic Based Optical Microscopes on Chip

Last decade's advancements in optofluidics allowed obtaining an ever increasing integration of different functionalities in lab on chip devices to culture, analyze, and manipulate single cells and entire biological specimens. Despite the importance of optical imaging for biological sample monitoring in microfluidics, imaging is traditionally achieved by placing microfluidics channels in standard bench-top optical microscopes. Recently, the development of either integrated optical elements or lensless imaging methods allowed optical imaging techniques to be implemented in lab on chip systems, thus increasing their automation, compactness, and portability. In this review, we discuss known solutions to implement microscopes on chip that exploit different optical methods such as bright-field, phase contrast, holographic, and fluorescence microscopy