2015AIP conference proceedingsRequires access

A probabilistic method to quantify the colocalization of markers on intracellular vesicular structures visualized by light microscopy

Yannis Kalaidzidis, Inna Kalaidzidis, Marino Zerial

Open publisher page 23 citations

Abstract

The intracellular localization of proteins to their specific compartments is a rich source of information for the study of biological processes. The colocalization of a protein with an established compartment marker is routinely measured from multi-color fluorescent microscopy images. Unfortunately, the apparent colocalization is a mixture of real and random colocalization. Random colocalization results from the limited resolution of the light microscope and the close location or occlusion of objects in the crowded cytoplasmic environment. Commonly used methods for the correction of random colocalization work well if the random colocalization is significantly smaller than the real colocalization. In the case where they have comparable values, the final result could be a senseless negative value. To solve this problem, we first developed a probabilistic model for the estimation of random colocalization and demonstrated that it produces results that coincide with the standard scramble method. Second, we developed a probabilistic model for the correction of random colocalization for the double and multiple colocalization of intracellular markers on vesicular structures. Our probabilistic method of estimation of real colocalization has two main advantages: 1) it never gives a negative colocalization value and 2) provides the estimation of colocalization uncertainty.

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What this paper is about

The intracellular localization of proteins to their specific compartments is a rich source of information for the study of biological processes. The colocalization of a protein with an established compartment marker is routinely measured from multi-color fluorescent microscopy images. Unfortunately, the apparent colocalization is a mixture of real and random colocalization. Random colocalization results from the limited resolution of the light microscope and the close location or occlusion of objects in the crowded cytoplasmic environment. Commonly used methods for the correction of random colocalization work well if the random colocalization is significantly smaller than the real colocalization. In the case where they have comparable values, the final result could be a senseless negative value. To solve this problem, we first developed a probabilistic model for the estimation of random colocalization and demonstrated that it produces results that coincide with the standard scramble method. Second, we developed a probabilistic model for the correction of random colocalization for the double and multiple colocalization of intracellular markers on vesicular structures. Our probabilistic method of estimation of real colocalization has two main advantages: 1) it never gives a negative colocalization value and 2) provides the estimation of colocalization uncertainty.

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Available abstract

The intracellular localization of proteins to their specific compartments is a rich source of information for the study of biological processes. The colocalization of a protein with an established compartment marker is routinely measured from multi-color fluorescent microscopy images. Unfortunately, the apparent colocalization is a mixture of real and random colocalization. Random colocalization results from the limited resolution of the light microscope and the close location or occlusion of objects in the crowded cytoplasmic environment. Commonly used methods for the correction of random colocalization work well if the random colocalization is significantly smaller than the real colocalization. In the case where they have comparable values, the final result could be a senseless negative value. To solve this problem, we first developed a probabilistic model for the estimation of random colocalization and demonstrated that it produces results that coincide with the standard scramble method. Second, we developed a probabilistic model for the correction of random colocalization for the double and multiple colocalization of intracellular markers on vesicular structures. Our probabilistic method of estimation of real colocalization has two main advantages: 1) it never gives a negative colocalization value and 2) provides the estimation of colocalization uncertainty.

Key concepts: Colocalization, Probabilistic logic, Biological system, Biology, Computer science, Biophysics, Cell biology, Physics

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