Co-Density Distribution Maps for Advanced Molecule Colocalization and Co-Distribution Analysis

Sensors

Alessandro Bevilacqua¹  Ilaria De Santis²  Luca Lorenzini³  Elisa Martella⁴  Marzia Moretti⁵  Laura Calzà⁵  Enrico Lucarelli⁶ 

[1] Advanced Research Center on Electronic Systems (ARCES) for Information and Communication Technologies “E. De Castro”, Alma Mater Studiorum—University of Bologna, I-40125 Bologna, Italy;Department of Medical and Surgical Sciences (DIMEC), Alma Mater Studiorum—University of Bologna, I-40138 Bologna, Italy;Department of Veterinary Medical Sciences (DIMEVET), Alma Mater Studiorum—University of Bologna, I-40064 Ozzano Emilia, Italy;Institute of Organic Synthesis and Photoreactivity (ISOF), National Research Council (CNR), I-40129 Bologna, Italy;Iret Foundation, I-40064 Ozzano Emilia, Italy;Regenerative Therapies in Oncology, IRCCS Istituto Ortopedico Rizzoli, I-40136 Bologna, Italy;

关键词: local density;    local co-density;    co-occurrence;    correlation;    colocalization quantification;    data visualization;   

DOI  :  10.3390/s21196385

来源: DOAJ

【 摘 要 】

Cellular and subcellular spatial colocalization of structures and molecules in biological specimens is an important indicator of their co-compartmentalization and interaction. Presently, colocalization in biomedical images is addressed with visual inspection and quantified by co-occurrence and correlation coefficients. However, such measures alone cannot capture the complexity of the interactions, which does not limit itself to signal intensity. On top of the previously developed density distribution maps (DDMs), here, we present a method for advancing current colocalization analysis by introducing co-density distribution maps (cDDMs), which, uniquely, provide information about molecules absolute and relative position and local abundance. We exemplify the benefits of our method by developing cDDMs-integrated pipelines for the analysis of molecules pairs co-distribution in three different real-case image datasets. First, cDDMs are shown to be indicators of colocalization and degree, able to increase the reliability of correlation coefficients currently used to detect the presence of colocalization. In addition, they provide a simultaneously visual and quantitative support, which opens for new investigation paths and biomedical considerations. Finally, thanks to the coDDMaker software we developed, cDDMs become an enabling tool for the quasi real time monitoring of experiments and a potential improvement for a large number of biomedical studies.

【 授权许可】

Unknown