Biology subjects

Losert, W.

Publications and source records attributed to Losert, W..

3 recordsLinked to original sources

bioRxiv2018

RefCell: Multi-dimensional analysis of image-based high-throughput screens based on ‘typical cells’

BackgroundImage-based high-throughput screening (HTS) reveals a high level of heterogeneity in single cells and multiple cellular states may be observed within a single population. Cutting-edge high-dimensional analysis methods are successful in characterizing cellular heterogeneity, but they suffer from the \"curse of dimensionality\" and non-standardized outputs.\n\nResultsHere we introduce RefCell, a multi-dimensional analysis pipeline for image-based HTS that reproducibly captures cells with typical combinations of features in reference states, and uses these \"typical cells\" as a reference for classification and weighting of metrics. RefCell quantitatively assesses the heterogeneous deviations from typical behavior for each analyzed perturbation or sample.\n\nConclusionsWe apply RefCell to the analysis of data from a high-throughput imaging screen of a library of 320 ubiquitin protein targeted siRNAs selected to gain insights into the mechanisms of premature aging (progeria). RefCell yields results comparable to a more complex clustering based single cell analysis method, which both reveal more potential hits than conventional average based analysis.

bioinformatics↗

bioRxiv2018

CytoBinning: immunological insights from multi-dimensional data

New cytometric techniques continue to push the boundaries of multi-parameter quantitative data acquisition at the single-cell level particularly in immunology and medicine. Sophisticated analysis methods for such ever higher dimensional datasets are rapidly emerging, with advanced data representations and dimensional reduction approaches. However, these are not yet standardized and clinical scientists and cell biologists are not yet experienced in their interpretation. More fundamentally their range of statistical validity is not yet fully established. We therefore propose a new method for the automated and unbiased analysis of high-dimensional single cell datasets that is simple and robust, with the goal of reducing this complex information into a familiar 2D scatter plot representation that is of immediate utility to a range of biomedical and clinical settings. Using publicly available flow cytometry and mass cytometry datasets we demonstrate that this method (termed CytoBinning), recapitulates the results of traditional manual cytometric analyses and leads to new and testable hypotheses.

bioinformatics↗

bioRxiv2017

Particle Tracking facilitates real time Motion Compensation in 2D or 3D two-photon imaging of neuronal activity

The application of 2-photon laser scanning microscopy (TPLSM) techniques to measure the dynamics of cellular calcium signals in populations of neurons is an extremely powerful technique for characterizing neural activity within the central nervous system. The use of TPLSM on awake and behaving subjects promises new insights into how neural circuit elements cooperatively interact to form sensory perceptions and generate behavior. A major challenge in imaging such preparations is animal and tissue movement, which leads to shifts in the imagine location (jitter). Although there are surgical and technical approaches to minimize brain motion under these conditions, it is generally unavoidable. The presence of image motion can lead to artifacts, especially since quantification of TPLSM images involves analysis of fluctuations in fluorescence intensities for each neuron, determined from small regions of interest (ROIs) Here, we validated a new motion correction approach to compensate for motion of TPLSM images in the superficial layers of auditory cortex of awake mice. We use a nominally uniform fluorescent signal as a secondary signal to complement the dynamic signals from genetically encoded calcium indicators. We tested motion correction for single plane time lapse imaging a; well as multiplane (i.e. volume) time lapse imaging of cortical tissue. Our procedure of motion compensation relies on locating the brightest neurons and tracking their positions over time using established techniques of particle finding and tracking. The performance of our techniques both for 2D (single plane) and 3D (volume) image sequences is comparable to established techniques in its ability to suppress false neural signals. Object tracking based motion compensation thus offers an alternative approach for motion compensation, one that is we suited for real time feedback control and for analysis of tissue distortions.

neuroscience↗