Table II. Choosing the right spatial proteomics approach.

Research Question			Method		Strength
Single protein	Static	Where is protein X?	Localization database (Table I)		Fast, multiple sources for cross-referencing
	Static/Dynamic	Where is protein X?	[Microscopy]		Multi-compartment localizations and transient interactions captured
		Is protein X associated with compartment Y?	Proximity labelling (APEX, BioID with protein X as bait)
Single subcellular compartment/location	Static/Dynamic	What is the composition of compartment Y?	Proximity labelling (APEX, BioID using organelle-specific markers as baits)		Very sensitive
			Single organelle profiling		No constructs/cell lines
Global–all compartments and locations, the complete spatial proteome	Static	What is the composition of all organelles in a given cell type?	Multi organelle profiling (gradient centrifugation; long gradients for high resolution; differential centrifugation for higher throughput)		No labelling reagents, no tagging/cell line generation; relatively rapid; a single experiment covers thousands of proteins; peptide level data.
			Proximity labelling (multiple baits for every compartment)		Very sensitive, multi-compartment localizations
			Imaging (one cell line or antibody per protein)		Direct visualization, also in relation to other structures/proteins; multi-compartment localizations
	Dynamic	Which proteins change subcellular localization upon a specific perturbation, drug treatment, genetic alteration etc? Which organelles change composition upon perturbation?	Low Resolution	Membrane-nucleus-cytosol split	Simple, robust, deep coverage from one experiment, little MS measurement time
			High Resolution	Multi organelle profiling (most robust by differential centrifugation) (Proximity labelling) – no global study yet (Imaging–global studies with yeast GFP library)	Sensitive, deep coverage from one experiment

See also (5), including the supplemental data, for a detailed discussion.