High-throughput imaging of zebrafish embryos using a linear-CCD-based flow imaging system

Heterogeneities of zebrafish vasculature development studied by a high throughput light-sheet flow imaging system

Zebrafish is one of the ideal model animals to study the structural and functional heterogeneities in development. However, the lack of high throughput 3D imaging techniques has limited studies to only a few samples, despite zebrafish spawning tens of embryos at once. Here, we report a light-sheet flow imaging system (LS-FIS) based on light-sheet illumination and a continuous flow imager. LS-FIS enables whole-larva 3D imaging of tens of samples within half an hour. The high throughput 3D imaging capability of LS-FIS was demonstrated with the developmental study of the zebrafish vasculature from 3 to 9 days post-fertilization. Statistical analysis shows significant variances in trunk vessel development but less in hyaloid vessel development.

Precise Two-Dimensional Tilt Measurement Sensor with Double-Cylindrical Mirror Structure and Modified Mean-Shift Algorithm for a Confocal Microscopy System

To improve the accuracy of three-dimensional (3D) surface contour measurements of freeform optics, a two-dimensional (2D) tilt measurement sensor for confocal microscopy (CM) systems is proposed based on a double-cylindrical mirror structure. First, the proposed system is accurately modeled. Second, we introduce a modified mean-shift-based peak-extraction algorithm with a novel kernel function (MSN) because the reflectivity of the measured object and fluctuation of the light source affect the measurement accuracy. Third, a partition fitting (PF) strategy is proposed to reduce the fitting error and improve the measurement accuracy. Simulations and experiments reveal that the robustness, speed, and angular prediction accuracy of the system effectively improved as a function of MSN and PF. The developed sensor can measure the 2D tilt, where each tilt is a composition of two separate dimensions, and the mean prediction errors in the 2D plane from -10°-+10° are 0.0134° (0.067% full scale (F.S)) and 0.0142° (0.071% F.S). The sensor enables the optical probe of a traditional CM to obtain accurate and simultaneous estimates of the 2D inclination angle and spatial position coordinates of the measured surface. The proposed sensor has potential in 3D topographic reconstruction and dynamic sampling rate optimization for 3D contour detection.

Assessment of Autism Zebrafish Mutant Models Using a High-Throughput Larval Phenotyping Platform

In recent years, zebrafish have become commonly used as a model for studying human traits and disorders. Their small size, high fecundity, and rapid development allow for more high-throughput experiments compared to other vertebrate models. Given that zebrafish share >70% gene homologs with humans and their genomes can be readily edited using highly efficient CRISPR methods, we are now able to rapidly generate mutations impacting practically any gene of interest. Unfortunately, our ability to phenotype mutant larvae has not kept pace. To address this challenge, we have developed a protocol that obtains multiple phenotypic measurements from individual zebrafish larvae in an automated and parallel fashion, including morphological features (i.e., body length, eye area, and head size) and movement/behavior. By assaying wild-type zebrafish in a variety of conditions, we determined optimal parameters that avoid significant developmental defects or physical damage; these include morphological imaging of larvae at two time points [3 days post fertilization (dpf) and 5 dpf] coupled with motion tracking of behavior at 5 dpf. As a proof-of-principle, we tested our approach on two novel CRISPR-generated mutant zebrafish lines carrying predicted null-alleles of syngap1b and slc7a5, orthologs to two human genes implicated in autism-spectrum disorder, intellectual disability, and epilepsy. Using our optimized high-throughput phenotyping protocol, we recapitulated previously published results from mouse and zebrafish models of these candidate genes. In summary, we describe a rapid parallel pipeline to characterize morphological and behavioral features of individual larvae in a robust and consistent fashion, thereby improving our ability to better identify genes important in human traits and disorders.

Zebrafish: Speeding Up the Cancer Drug Discovery Process

Zebrafish (Danio rerio) is an ideal in vivo model to study a wide variety of human cancer types. In this review, we provide a comprehensive overview of zebrafish in the cancer drug discovery process, from (i) approaches to induce malignant tumors, (ii) techniques to monitor cancer progression, and (iii) strategies for compound administration to (iv) a compilation of the 355 existing case studies showing the impact of zebrafish models on cancer drug discovery, which cover a broad scope of scenarios. Finally, based on the current state-of-the-art analysis, this review presents some highlights about future directions using zebrafish in cancer drug discovery and the potential of this model as a prognostic tool in prospective clinical studies. Cancer Res; 78(21); 6048-58. ©2018 AACR.

Multiscale imaging of plant development by light-sheet fluorescence microscopy

Light-sheet fluorescence microscopy (LSFM) methods collectively represent the major breakthrough in developmental bio-imaging of living multicellular organisms. They are becoming a mainstream approach through the development of both commercial and custom-made LSFM platforms that are adjusted to diverse biological applications. Based on high-speed acquisition rates under conditions of low light exposure and minimal photo-damage of the biological sample, these methods provide ideal means for long-term and in-depth data acquisition during organ imaging at single-cell resolution. The introduction of LSFM methods into biology extended our understanding of pattern formation and developmental progress of multicellular organisms from embryogenesis to adult body. Moreover, LSFM imaging allowed the dynamic visualization of biological processes under almost natural conditions. Here, we review the most important, recent biological applications of LSFM methods in developmental studies of established and emerging plant model species, together with up-to-date methods of data editing and evaluation for modelling of complex biological processes. Recent applications in animal models push LSFM into the forefront of current bio-imaging approaches. Since LSFM is now the single most effective method for fast imaging of multicellular organisms, allowing quantitative analyses of their long-term development, its broader use in plant developmental biology will likely bring new insights.