Closed-form density-based framework for automatic detection of cellular morphology changes

Abstract

A primary method for studying cellular function is to examine cell morphology after a given manipulation. Fluorescent markers attached to proteins/intracellular structures of interest in conjunction with 3D fluorescent microscopy are frequently exploited for functional analysis. Despite the central role of morphology comparisons in cell biological approaches, few statistical tools are available that allow biological scientists without a high level of statistical training to quantify the similarity or difference of fluorescent images containing multifactorial information. We transform intracellular structures into kernels and develop a multivariate two-sample test that is nonparametric and asymptotically normal to directly and quantitatively compare cellular morphologies. The asymptotic normality bypasses the computationally intensive calculations used by the usual resampling techniques to compute the P-value. Because all parameters required for the statistical test are estimated directly from the data, it does not require any subjective decisions. Thus, we provide a black-box method for unbiased, automated comparison of cell morphology. We validate the performance of our test statistic for finite synthetic samples and experimental data. Employing our test for the comparison of the morphology of intracellular multivesicular bodies, we detect changes in their distribution after disruption of the cellular microtubule cytoskeleton with high statistical significance in fixed samples and live cell analysis. These results demonstrate that density-based comparison of multivariate image information is a powerful tool for automated detection of cell morphology changes. Moreover, the underlying mathematics of our test statistic is a general technique, which can be applied in situations where two data samples are compared.hypothesis test | integrated density functional | optimal bandwidth selection | quantitative cell comparison F luorescent markers attached to proteins of interest in conjunction with modern fluorescent microscopy technologies are a useful proxy for studying subcellular compartments and their behavior after a given manipulation. Treatment with chemical compounds or specific gene silencing by RNA interference are commonly used at the scale of individual experiments to highthroughput studies. Visual inspection by expert biologists has been performed for several decades, ranging from early studies by microscopists like Ramon y Cajal to contemporary large scale, high-throughput screens (1-4). Although human observation may be very accurate, the three major drawbacks are that (i) it lacks quantitative measures, (ii) it may be biased, and (iii) it is time consuming.The structural features of cells and the topological relationships between the numerous intracellular compartments give rise to multivariate data whose unbiased, automatic comparison is a major challenge. Importantly, alterations in cellular morphology also occur in many diseases, including cancer, requiring quantitative tools for their detection. Give...

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