High-Resolution, Parallelized Imaging of Freely Swimming Zebrafish with a Gigapixel Microscope

SignificanceHigh throughput optical microscopy is currently transforming the research fields of geneticsdrug discovery and neuroscienceLarge scale optical assays now routinely use thousands of high resolution images to offer critical insights into the human bodyour brain and the diseases that affect usTodayandapos s optical microscopeshoweverare still far from idealDue to challenges with large lens designno standard microscope can capture more thanmegapixels per image snapshotwhich makes it impossible to simultaneously image at cellular resolution over a multi centimeter viewing areafield of viewFOVFor screening and monitoring zebrafish in vivothis resolution FOV tradeoff is a critical bottleneckeach organism must be constrained or paralyzed to image at high resolutionfreely swimming organisms can only be viewed at low resolutionand no setups yet can monitor multiple swimming zebrafish at cellular resolution in parallelProposalOptical Wavefront LaboratoriesLLCOWLhas developed a new microscope that overcomes these limitationsIts Phase Imicro camera array microscopeprototypethe MCAMconsists ofmicro camera units and associated electronics to capture sub cellular resolution images over an entire large petri dishgigapixel imagesIn Phase IIOWL will produce a market ready productthe MCAMwith improved specifications and software for acquiring both bright field and fluorescence videosThe MCAMwill significantly improve the efficiency of high throughput microscope screeningreduce the complexity of current setupsand enable completely new biological experimentse gSASAOptimize MCAMhardwareOWL will create a market ready MCAMdevice that achievesm resolution imaging across ancmFOV atframes secfpsSoftware options will allow video imaging rates to approachfps over a reduced areaThe MCAMoffersX more pixels per imagegigapixelsthan top competing microscopesSADevelop electronics and software for high speed digital trackingWorking with the Engert Lab at HarvardOWL will dramatically reduce the amount of data saved by the MCAM using automated digital trackingThis new software will segment each larva from images and discard all residual pixelsdecreasing memory requirements byX and facilitatingfps single organism video trackingIn additionOWL will add several image analysis functions to its current Python software interfacee gD positioneye positiontail curvatureoffering state of the art accuracyandlterrorminSADemonstrate fluorescence imaging of neural activityWorking with the Naumann Lab at Duke UniversityOWL will improve the MCAMandapos s sensitivity and accuracy of fluorescence detectionDedicated hardware add onsan excitation source and emission filter arraywill provide a fluorescence image signal to noise ratio ofin stationary and freely moving transgenic larvaeCalibrated videos of freely swimming transgenic larvae with pan neuronal GCaMP s expression will verify the MCAMcan non invasively measure neural activity in andgtorganisms simultaneously during natural interactionsSAConduct user trials and gather feedbackOWL will provide MCAMprototypes toresearch groups for detailed feedback via questionnaires over amonth trialOWL will then incorporate comments into a finalized productThe outcome of this Phase II project will be a flagship MCAMdevice and software ready for medium scale production Current microscopes cannot form images with cellular scale resolution over an area larger than a few square centimeterswhich fundamentally limits our ability to monitor the detailed movements of living systemsIn this projectOptical Wavefront LaboratoriesLLCOWLwill continue to develop a new micro camera array microscopeMCAMto overcome these limitations and offer cellular level detail over an area the size of a large petri dishWe will finalize the production of an MCAM prototypethe MCAMthat offers videos withm resolution over acmarea and will apply it to monitor the movement and neural activity of multiple freely swimming zebrafish at cellular resolution for the first time