Normalization of large-scale behavioural data collected from zebrafish

Tensor analysis of animal behavior by matricization and feature selection

Contemporary neurobehavior research often collects multi-dimensional tensor (MDT) data, consisting of time-series measurements for multiple features from multiple animals subjected to various perturbations. Proper analysis of the MDT data can facilitate the dissection of the underlying neural circuitry driving the behavior. However, many common approaches for MDT analysis, such as tensor decomposition, often yield results that are difficult to interpret and not directly compatible with standard multivariate analysis (MVA), which is designed for simpler, lower-dimensional data structures. To address this issue, dimensionality reduction techniques, including matricization methods such as Index Construction and Feature Concatenation, are applied to transform all or a subset of the features in the MDT into a lower-dimensional tensor, commonly a 2-dimensional tensor (2DT), that is compatible with MVA. However, the matricization methods may exclude information from the MDT features or create too many 2DT features that introduce spurious noise to the downstream analyses. Their impacts on the downstream MVA performance remain elusive. In this study, we systematically evaluated different approaches for matricization and feature selection and their impacts on MVA performance using an MDT dataset of zebrafish visual- motor response collected from wild-types (WTs) and visually-impaired mutants. We matricized the MDT dataset using various Index Construction and Feature Concatenation methods, then identified informative 2DT features using the filter and embedded methods. To evaluate these feature-selection approaches, we conducted a classification task distinguishing WT and visually-impaired zebrafish by multiple classifiers. We then assessed classification performance with cross-validation and holdout validation. We found that most classifiers performed the best when using all 2DT features matricized by Feature Concatenation and selected by the embedded method. The results also revealed unique behavioral differences between the WTs and visually-impaired mutants that were not identified by standard MVA or MDT analysis. Our results demonstrate the utility of analyzing MDT behavioral data by matricization and feature selection.

A unified approach to investigating 4 dpf zebrafish larval behaviour through a standardised light/dark assay

Zebrafish are a dynamic research model in the domains of neuropsychopharmacology, biological psychiatry and behaviour. Working with larvae ≤4 days post-fertilisation (dpf) offers an avenue for high-throughput investigation whilst aligning with the 3Rs principles of animal research. The light/dark assay, which is the most widely used behavioural assay for larval neuropharmacology research, lacks experimental reliability and standardisation. This study aimed to formulate a robust, reproducible and standardised light/dark behavioural assay using 4 dpf zebrafish larvae. Considerable between-batch and inter-individual variability was found, which we rectified with a normalisation approach to ensure a reliable foundation for analysis. We then identified that 5-min light/dark transition periods are optimal for locomotor activity. We also found that a 30-min acclimation in the light was found to produce significantly increased dark phase larval locomotion. Next, we confirmed the pharmacological predictivity of the standardised assay using ethanol which, as predicted, caused hyperlocomotion at low concentrations and hypolocomotion at high concentrations. Finally, the assay was validated by assessing the behavioural phenotype of hyperactive transgenic (adgrl3.1-/-) larvae, which was rescued with psychostimulant medications. Our standardised assay not only provides a clear experimental and analytical framework to work with 4 dpf larvae, but also facilitates between-laboratory collaboration using our normalisation approach.

Scalable Neuroanatomical and Behavioral Phenotyping of Radio Frequency Radiation on Young Zebrafish

Objective: In our wireless-centric world, evaluating the health effects of radio frequency electromagnetic radiation (RF-EMR) is crucial. An existing research gap pertains to the replication of real-world specific absorption rates (SAR) for RF-EMR, especially within aquatic environments. We aimed to bridge this gap using an innovative TEM cell platform to replicate realistic SAR conditions in water and assess RF-EMR's impact on neuroanatomical and behavioral changes. Results: We examined RF-EMR effects on zebrafish embryos exposed to RF-EMR during the 4-58 hours post-fertilization phase. Temporary neuroanatomical enlargements and minor behavioral shifts were observed, diminishing by day 8 post-fertilization. Conclusion: Short-term RF-EMR exposure at tested levels did not yield significant long-term effects. Nevertheless, investigating prolonged exposure remains imperative. Our study serves as a pioneering model for future investigations into the biological consequences of RF-EMR exposure, highlighting the importance of assessing its health implications in our wireless-centric world.

Rapid analysis of meat floss origin using a supervised machine learning-based electronic nose towards food authentication

Authentication of meat floss origin has been highly critical for its consumers due to existing potential risks of having allergic diseases or religion perspective related to pork-containing foods. Herein, we developed and assessed a compact portable electronic nose (e-nose) comprising gas sensor array and supervised machine learning with a window time slicing method to sniff and to classify different meat floss products. We evaluated four different supervised learning methods for data classification (i.e., linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbors (k-NN), and random forest (RF)). Among them, an LDA model equipped with five-window-extracted feature yielded the highest accuracy values of >99% for both validation and testing data in discriminating beef, chicken, and pork flosses. The obtained e-nose results were correlated and confirmed with the spectral data from Fourier-transform infrared (FTIR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) measurements. We found that beef and chicken had similar compound groups (i.e., hydrocarbons and alcohol). Meanwhile, aldehyde compounds (e.g., dodecanal and 9-octadecanal) were found to be dominant in pork products. Based on its performance evaluation, the developed e-nose system shows promising results in food authenticity testing, which paves the way for ubiquitously detecting deception and food fraud attempts.

Optimizing assays of zebrafish larvae swimming performance for drug discovery

INTRODUCTION

Zebrafish larvae are one of the few vertebrates amenable to large-scale drug discovery screens. Larval swimming behavior is often used as an outcome variable and many fields of study have developed assays for evaluating swimming performance. An unintended consequence of this wide interest is that details related to assay methodology and interpretation become scattered across the literature. The aim of this review is to consolidate this information, particularly as it relates to high-throughput approaches.

AREAS COVERED

The authors describe larval swimming behaviors as this forms the basis for understanding their experimentally evoked swimming or spontaneous activity. Next, they detail how swimming activity can serve as an outcome variable, particularly in the multi-well formats used in large-scale screening studies. They also highlight biological and technical factors that can impact the sensitivity and variability of these measurements.

EXPERT OPINION

Careful attention to animal husbandry, experimental design, data acquisition, and interpretation of results can improve screen outcomes by maximizing swimming activity while minimizing intra- and inter-larval variability. The development of more sensitive, quantitative methods of assessing swimming performance that can be incorporated into high-throughput workflows will be important in order to take full advantage of the zebrafish model.

Gap junction Delta-2b (gjd2b/Cx35.1) depletion causes hyperopia and visual-motor deficiencies in the zebrafish

The zebrafish is a powerful model to investigate the developmental roles of electrical synapses because many signaling pathways that regulate the development of the nervous system are highly conserved from fish to humans. Here, we provide evidence linking the mammalian connexin-36 (Cx36) ortholog gjd2b/Cx35.1, a major component of electrical synapses in the zebrafish, with a refractive error in the context of morphological, molecular, and behavioral changes of zebrafish larvae. Two abnormalities were identified. The optical coherence tomography analysis of the adult retina confirmed changes to the refractive properties caused by eye axial length reduction, leading to hyperopic shifts. The gjd2b/Cx35.1 depletion was also correlated with morphological changes to the head and body ratios in larvae. The differential expression of Wnt/ß-catenin signaling genes, connexins, and dopamine receptors suggested a contribution to the observed phenotypic differences. The alteration of visual-motor behavioral responses to abrupt light transitions was aggravated in larvae, providing evidence that cone photoreceptor cell activity was enhanced when gjd2b/Cx35.1 was depleted. The visual disturbances were reversed under low light conditions in gjd2b ^-/- /Cx35.1^-/- larvae. Since qRT-PCR data demonstrated that two rhodopsin genes were downregulated, we speculated that rod photoreceptor cells in gjd2b/Cx35.1^-/- larvae were less sensitive to bright light transitions, thus providing additional evidence that a cone-mediated process caused the VMR light-ON hyperactivity after losing Cx35.1 expression. Together, this study provides evidence for the role of gjd2b/Cx35.1 in the development of the visual system and visually guided behaviors.

Drug screening with zebrafish visual behavior identifies carvedilol as a potential treatment for an autosomal dominant form of retinitis pigmentosa

Retinitis Pigmentosa (RP) is a mostly incurable inherited retinal degeneration affecting approximately 1 in 4000 individuals globally. The goal of this work was to identify drugs that can help patients suffering from the disease. To accomplish this, we screened drugs on a zebrafish autosomal dominant RP model. This model expresses a truncated human rhodopsin transgene (Q344X) causing significant rod degeneration by 7 days post-fertilization (dpf). Consequently, the larvae displayed a deficit in visual motor response (VMR) under scotopic condition. The diminished VMR was leveraged to screen an ENZO SCREEN-WELL REDOX library since oxidative stress is postulated to play a role in RP progression. Our screening identified a beta-blocker, carvedilol, that ameliorated the deficient VMR of the RP larvae and increased their rod number. Carvedilol may directly on rods as it affected the adrenergic pathway in the photoreceptor-like human Y79 cell line. Since carvedilol is an FDA-approved drug, our findings suggest that carvedilol can potentially be repurposed to treat autosomal dominant RP patients.