Towards a higher-throughput Chemobehavioural Phenomics using small model organisms
Creators: name: Bai, Yutao
Publisher: name: RMIT University
Year: 2024
Subjects: classificationCode: 310906
subject: Animal neurobiology
classificationCode: 310910
subject: Animal physiology - systems
classificationCode: 320999
subject: Neurosciences not elsewhere classified

description: As a highly integrative and physiologically relevant screening approach, chemobehavioral phenotyping using small aquatic proxy organisms is being increasingly adopted across multiple disciplines ranging from neuroactive drug discovery, predictive neurotoxicology, and behavioural ecotoxicology. However, there is a profound lack of innovative neurobehavioral assays and automated analytical workflows that enable the study of complex behavioral endpoints in a high-throughput format and efficient extraction of biometric data. Herein, this thesis presents research aimed at developing innovative laboratory hardware and software automation systems, to address the challenges towards high-throughput neuro-behavioral studies utilizing small aquatic model organisms.
 
In chapter 1, I review the research background and highlight recent advances in this budding new interdisciplinary field of research. I also outline the existing challenges and provide an outlook on the evolving field of neurobehavioral ecotoxicology.
 
In chapter 2, I focus on utilizing the advantages of microfluidic Lab-on-a-Chip (LOC) technology for studying chemosensory behaviors. I present a proof-of-concept microperfusion chip device that is capable of manipulating the chemical microenvironment via laminar flow at a low Reynold (Re) number, which is merely possible to achieve using conventional laboratory techniques, to form and maintain a binary fluidic zone with distinct chemical conditions for the specimen caged within the device chamber. The device is integrated with high-definition video acquisition instruments to enable time-resolved video data analysis on selected behavioral parameters. I validate the system by assessing the chemosensory avoidance responses of native Australian marine amphipods Allorchestes compressa against a panel of environmental stressors and highlight for the first time that the chemotaxis response of marine crustacean species can be studied under dynamic flow-through conditions. This work also provided a very first demonstration of integration between millifluidics, video imaging and animal tracking with direct applications in ecotoxicology and aquatic risk assessment.
 
Following the experimental framework established in chapter 2, I advance the utilization of chip-based devices and video tracking-based analytical protocols to investigate photosensory behaviors. In chapter 3, I describe the proof-of-concept development of a high-throughput and automated conditioning chip-based system for the studies of phototactic behaviors of small aquatic invertebrates. This research exploits more sophisticated design and integration of hardware and software to enable accurate spatial-temporal delivery of photic stimuli, as well as to forward standardization of high-throughput video analysis workflow. I demonstrated the system can be successfully applied in analyzing the phototactic behavioral responses of marine shrimp Artemia franciscana to assess the impact of neurotoxicants exposure upon organisms. The methodologies presented in this work provided a novel avenue for the development of quantitative neurobehavioural assays.

Chapter 3 illustrated the vast potential of coupling open-architecture platforms with a dedicated bioinformatic approach in accelerating high-throughput analysis of behavioral phenotypes. Such a combination is particularly important in enabling real-time operant conditioning experiments to facilitate the investigation of higher-order behavioral endpoints, such as learning and memory. In Chapter 4, I present the development of a video-based animal tracking framework with capabilities of interfacing high-definition video recording devices and programmable microcontrollers to enable the implementation of various control strategies to perform the real-time closed-loop animal behavioral experiment, namely TrackingBot software, to address the challenges of lacking automated neuro-behavioral analysis applications that are inexpensive and applicable for cognitive studies on small aquatic invertebrate models. This work provides turn-key user-friendly applications in advanced cognitive experiments with fish and amphibians and prospectively new paradigms of chemobehavioural phenotyping in aquatic ecotoxicology, predictive neurotoxicology as well as the application for discovery of new neuro-modulation pharmaceuticals.