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Organellar Omics—A Reviving Strategy to Untangle the Biomolecular Complexity of the Cell
Author(s) -
Tharkeshwar Arun Kumar,
Gevaert Kris,
Annaert Wim
Publication year - 2018
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201700113
Subject(s) - organelle , computational biology , endocytic cycle , biology , biomolecule , cell , microbiology and biotechnology , biochemistry , endocytosis
Abstract A eukaryotic cell encompasses many membrane‐enclosed organelles, each of these holding several types of biomolecules that exhibit tremendous diversity in terms of their localization and expression. Despite the development of increasingly sensitive analytical tools, the enormous biomolecular complexity that exists within a cell cannot yet be fully resolved as low abundant molecules often remain unrecognized. Moreover, a drawback of whole cell analysis is that it does not provide spatial information and therefore it is not capable of assigning distinct biomolecules to specific compartments or analyzing changes in the composition of these compartments. Reduction of the biomolecular complexity of a sample helps to identify low abundant molecules, but such a reductionist approach requires methods that enable proper isolation and purification of individual cellular organelles. Decades of research have led to the development of a plethora of isolation methods for a broad range of subcellular organelles; yet, in particular, intrinsically dynamic compartments belonging to the endocytic machinery, including the plasma membrane, remain difficult to isolate in a sufficiently pure fraction. In this review, we discuss various methods that are commonly used to isolate subcellular organelles from cells and evaluate their advantages and disadvantages.

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