Copica, an open-source easy-to-use protein copy number mass spectrometry database

Recent advances in mass spectrometry (MS) make it possible to profile the proteome over ten orders of dynamic range starting with as little as 10 ng of material. Such datasets provide important insights into the relative abundance of proteins in cells as well as tissues. To help researchers more easily analyze, visualize, and compare analyzed MS data, we have created Copica. This database enables a facile comparison of relative protein abundance calculated as copies per cell, across different samples and experiments. Researchers can compare the copy number of proteins of interest between different datasets and/or upload their MS data that has been processed using major MS search engines such as MaxQuant. Copica allows the option of the protein copy number of all kinases, phosphatases and LRRK2 signalling components to be automatically highlighted in sample. Copica calculates the protein copy number/cell of every identified protein using the Proteomic Ruler algorithm, that compares levels of proteins with histones that are present at the same number in each cell. The Copica database currently contains proteomic datasets of widely used cell lines (HEK293, A549, mouse primary embryonic fibroblasts), iPSC derived dopaminergic neurons, cortical neurons, and tissues derived from different mouse brain regions. We intend to additional cells and tissues from analysis we obtain in our ASAP collaboration. We aim for Copica to be a general resource available for all and are happy to include other MS datasets that are of interest to ASAP researchers.