Light Sheet Microscopy Imaging and Mounting Strategies for Early Zebrafish Embryos.

Light sheet microscopy has become the methodology of choice for live imaging of zebrafish embryos over long time scales with minimal phototoxicity. In particular, a multiview system, which allows sample rotation, enables imaging of entire embryos from different angles. However, in most imaging sessions with a multiview system, sample mounting is a troublesome process as samples are usually prepared in a polymer tube. To aid in this process, this protocol describes basic mounting strategies for imaging early zebrafish development between the 70% epiboly and early somite stages. Specifically, the study provides statistics on the various positions the embryos default to at the 70% epiboly and bud stages within the chorion. Furthermore, it discusses the optimum number of angles and the interval between angles required for imaging whole zebrafish embryos at the early stages of development so that cellular-scale information can be extracted by fusing the different views. Finally, since the embryo covers the entire field of view of the camera, which is required to obtain a cellular-scale resolution, this protocol details the process of using bead information from above or below the embryo for the registration of the different views.

End-to-end computational approach to the design of RNA biosensors for detecting miRNA biomarkers of cervical cancer.

Cervical cancer is a global public health subject as it affects women in the reproductive ages, and accounts for the second largest burden among cancer patients worldwide with an unforgiving 50% mortality rate. Relatively scant awareness and limited access to effective diagnosis have led to this enormous disease burden, calling for point-of-care, minimally invasive diagnosis methods. Here, an end-to-end quantitative unified pipeline for diagnosis has been developed, beginning with identification of optimal biomarkers, concurrent design of toehold switch sensors, and finally simulation of the designed diagnostic circuits to assess performance. Using miRNA expression data in the public domain, we identified miR-21-5p and miR-20a-5p as blood-based miRNA biomarkers specific to early-stage cervical cancer employing a multi-tier algorithmic screening. Synthetic riboregulators called toehold switches specific to the biomarker panel were then designed. To predict the dynamic range of toehold switches for use in genetic circuits as biosensors, we used a generic grammar of these switches, and built a neural network model of dynamic range using thermodynamic features derived from mRNA secondary structure and interaction. Second-generation toehold switches were used to overcome the design challenges associated with miRNA biomarkers. The resultant model yielded an adj. R2 ∼0.71, outperforming earlier models of toehold-switch dynamic range. Reaction kinetics modelling was performed to predict the sensitivity of the second-generation toehold switches to the miRNA biomarkers. Simulations showed a linear response between 10 nM and 100 nM before saturation. Our study demonstrates an end-to-end computational workflow for the efficient design of genetic circuits geared towards the effective detection of unique genomic/nucleic-acid signatures. The approach has the potential to replace iterative experimental trial and error, and focus time, money, and efforts. All software including the toehold grammar parser, neural network model and reaction kinetics simulation are available as open-source software (https://github.com/SASTRA-iGEM2019) under GNU GPLv3 licence.