CAREER: ABI-Innovation: CiliaWeb: Integrated platform for foundational and reproducible ciliary beat pattern analysis

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Cilia are microscopic hairs that protrude from nearly every cell in the human body, including those in the throat, nose, lungs, kidneys, and brain. Cilia move in regular, rhythmic patterns in order to transport materials outside the cells. These movements of the cilia are important at every stage of life, from early embryonic development to reproduction and regular healthy maintenance; in short, healthy cilia are a critical component of overall health of an organism. Consequently, when cilia move abnormally, numerous debilitating conditions can result, encompassing disorders ranging from developmental shortcomings in the embryo to adult pathologies such as infertility and lung scarring. Therefore, the key question this proposal seeks to answer is: by observing the motion of cilia, is it possible to predict whether the morphology or behavior is abnormal, and if so, whether that particular abnormality is associated with a specific condition? The answer to this question has implications not only in human health, but also in building fundamental knowledge of the biology around how cilia are constructed and maintained. To address this question, we are building the CiliaWeb platform, which will include new algorithms for analyzing videos of cilia and shedding light on the statistics of ciliary motion. The algorithms will take advantage of the regular back-and-forth movements of cilia and be built to incorporate crowdsourced feedback from users to improve the models of ciliary motion. As its name implies, CiliaWeb will be internet-accessible for researchers and clinicians to upload datasets, conduct analyses, and visualize results. The ultimate goal of CiliaWeb is to provide a standardized platform for ciliary motion analysis that can be reproduced and validated by others, encouraging collaboration and catalyzing new discoveries in fundamental cilia research as well as connections to health and well-being.Cilia are microscopic hairs that protrude from eukaryotic cells and are critical components in development, reproduction, and homeostasis. Cilia beat in synchronous waves to generate fluid flow and clear particulates; disruptions of these motions result in a spectrum of pathologies. However, no quantitative, reproducible, and validated method exists for assessing ciliary motion from high-speed videomicroscopy. Without such a method, beat pattern phenotype cannot be used to conclusively advance our understanding of the fundamental biology of cilia (construction and maintenance), nor the precise role of beat pattern in organismal health (examples being signaling, development, fertility). This proposal aims to create the CiliaWeb framework to establish an objective measure of motion phenotypes, enable new lines of inquiry into biophysical mechanisms of ciliary motion and discover the biological roles of specific motion phenotypes, as well as make possible cross-institutional collaborations, large-scale genotype-phenotype association studies, and longitudinal biomedical studies. The CiliaWeb platform will incorporate tightly-integrated and openly-available tools for processing ciliary motion, including: a novel unsupervised dynamic texture segmentation algorithm for automatically identifying cilia in high-speed digital videos; a hierarchical encoding scheme for quantifying ciliary motion at multiple spatiotemporal scales; a crowdsourcing module to solicit targeted feedback on the learned motion patterns that are fully interactive and automated. CiliaWeb will contribute methodological advancements in computational bioimaging and establish baseline data through the release of open source code and validated datasets, in addition to hands-on outreach and training for students in the form of workshops and hackathons. Project updates: https://quinngroup.github.ioThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.