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Plant Cell. Jun 2009; 21(6): 1625–1631.
PMCID: PMC2714922

Exploring the Function-Location Nexus: Using Multiple Lines of Evidence in Defining the Subcellular Location of Plant Proteins


Defining the function of all proteins in an organism is one of the major objectives for biology in the coming decades. Here, we assess approaches used to determine subcellular protein location and discuss the relationship between protein location and function. It is important to recognize that targeting, accumulation, and the site of function are not necessarily interchangeable terms with respect to defining the location of a protein. Some proteins have tightly defined locations, whereas others have low specificity targeting and complex accumulation patterns. Location may be essential for function in some cases, but it may be much less important for other proteins. There is no single approach that can be considered entirely adequate for defining the in vivo location of all proteins. By combining approaches that assess targeting and accumulation of proteins, more confidence can be gained about localization. The strengths and weaknesses of different localization technologies are summarized, and some guidelines for performing combined targeting and accumulation assays are outlined.


The compartmentalized organization of the eukaryotic cell allows separation and specialization of function and facilitated the evolution of the diversity of multicellular organisms (Cavalier-Smith, 2009). However, the creation of this complex intracellular organization established the need for a new type of biological apparatus. Compared with the relatively simple prokaryotic cell that contains little or no internal membrane structures, the eukaryotic cell requires mechanisms for targeting and importing proteins to a variety of subcellular compartments. The literature on targeting of proteins suggests that targeting is a highly specific process. This apparent specificity normally is achieved by the presence of targeting signals on proteins that are recognized by cognate import receptors on organelle surfaces (Dyall et al., 2004). There is also evidence that an increasing number of proteins have multiple locations in the cell, and often there is a major and a minor site of accumulation, a phenomenon termed eclipsed distribution (Regev-Rudzki and Pines, 2007). Additionally, ambiguous targeting sequences can lead to specific dual-targeting of proteins to different organelles (Carrie et al., 2009a).

The complete sequencing of Arabidopsis thaliana and Oryza sativa has prompted large-scale efforts to define the functions of all proteins encoded in these genomes (Somerville and Dangl, 2000; Zhang et al., 2008). In this endeavor, defining the intracellular location of a protein product is an important aspect of defining function. The use of postgenomic approaches, such as subcellular proteomics and green fluorescent protein (GFP) tagging, now dwarf the number of direct targeting studies or other traditional approaches to define the location of proteins (Table 1). However, such high-throughput experimental approaches will produce both false-positive and false-negative attribution of protein location and will be confounded further by unclearly, inefficiently, or multiply targeted proteins. The compilation of protein locations from a variety of studies using different methods readily reveals apparent conflicts or discrepancies in location attribution by different researchers (Heazlewood et al., 2007). Additionally, experimental determination of the probable location of a protein is usually approached either by defining its targeting ability or defining where it accumulates in the cell. Although it may be anticipated that these two approaches should produce identical results, the limitations and/or interpretations of different experiments mean that they will not always agree. Furthermore, the degree to which location is associated with or important for protein function is likely to vary considerably across the proteome. Location may be essential in cases such as multiple subunits of large protein complexes, but it may be much less important in cases of enzymes that catalyze reactions using highly permeable substrates or when substrates are available in multiple locations. Here, we consider the strengths and weaknesses of different localization technologies, the need for multiple lines of evidence, and the implications of multitargeting.

Table 1.
The Ability of Various Experimental Approaches to Provide Information on Targeting and Accumulation in Cells


The ability of a protein to be targeted can be assessed by prediction or by experimental analyses (Table 1). Predictors can give different results due to the type of prediction algorithms used (e.g., weight matrix, neural networks, hidden Markov models, and support vector machines), the set of input sequences used in training, the range of locations predicted by each program, the hydrophobicity of the input sequence, and the significance cut-off that is used in the analysis of the output data (Emanuelsson et al., 2007; Chou and Shen, 2008). Predictions are valuable because they are easy to perform and they are unbiased by the user, so they may predict localizations that are unexpected and thus establish new lines of experimental inquiry. For example, a variety of NAD(P)H dehydrogenases have been characterized biochemically and immunologically as being located in mitochondria (Rasmusson et al., 2004) and have been shown to be located in mitochondria using in vitro and in vivo targeting approaches (Michalecka et al., 2003; Elhafez et al., 2006). However, prediction programs revealed a predicted peroxisomal localization (Reumann et al., 2004), and testing of this prediction confirmed targeting and accumulation in peroxisomes as well as mitochondria (Carrie et al., 2008). Thus, prediction may prompt experiments that might not be considered due to the existence of significant and credible data that have established an expectation for a single or alternative location.

Experimental testing of targeting can be performed using either in vitro or in vivo protein uptake or targeting studies. In vitro studies involve purification of the organelle of interest and testing the ability of an exogenously added protein to enter the isolated organelle from the bulk solution. Import of the protein is assessed by observing if the protein incorporated into the organelle is protected from digestion by externally added protease. In vitro import assays have been developed for plastids (Chua and Schmidt, 1978), mitochondria (Rudhe et al., 2002), peroxisomes (Pool et al., 1998), endoplasmic reticulum (ER; Villarejo et al., 2005), and nuclei (Pfeiffer et al., 2008). In vitro import assays typically have low false positive rates, and for the most part only proteins that are found in the organelles can be imported in vitro. An exception to this is the reported in vitro import of some, but notably not all, plastid precursors into isolated pea mitochondria (Cleary et al., 2002; Chew et al., 2003). The mechanistic basis of this particular case of in vitro mistargeting is unclear, but it appears to be overcome if a dual in vitro uptake assay is used where both mitochondria and chloroplasts are available for targeting in a single assay (Rudhe et al., 2002). Thus, in vitro uptake assays using single organelle preparations may not reproduce the complex intracellular environment and thus do not reveal targeting preference between organelles.

There are also technical reasons why in vitro uptake assays can be misinterpreted. First, as organelles need to be purified for this type of assay, it is possible that the receptor subunits may become damaged or lost in this process. Second, addition of too much protease may rupture organelles, and thus no import will be observed, while too little protease may not digest all protein remaining outside the organelle. Combining protease treatment with specific inhibitors of protein uptake can be a good test for the efficacy of protease treatment. An example of using isolated pea mitochondria and insufficient protease digestion is observed with Arabidopsis Ferrocheletase I. On the basis on an in vitro import assay, this protein was reported to be targeted to mitochondria and plastids (Chow et al., 1997). However, subsequent studies using GFP tagging (Lister et al., 2001; Masuda et al., 2003) and antibodies and specific activity assays (Masuda et al., 2003) assigned a location solely in plastids. Thus, in vitro uptake assays are technically complex to interpret because each protein to be tested may require different amounts of protease to ensure digestion, the purification of intact organelles may be difficult, and generally uptake into only a single organelle is tested.

GFP and its variants are now used widely as passenger proteins to assess targeting in vivo (Koroleva et al., 2005; Nelson et al., 2007). In vivo uptake assays have the attraction that they maintain the cellular environment, and uptake into all organelles can be tested at the same time. Major sources of error in these experiments arise from placing the passenger protein (such as GFP) in a position that impairs the targeting ability of the test protein and/or using only a part of the test protein and thus removing sections that contribute to the targeting of the full-length protein. For example, the common practice of using only the N-terminal 50 to 100 amino acids ignores the fact that targeting signals may be located throughout the mature protein, and placing GFP either at the C terminus or N terminus may mask targeting signals. A good example where these three limitations have affected definition of subcellular locations can be gauged from a variety of studies that have defined dual-targeted proteins (Carrie et al., 2009b).

A high-throughput fluorescent tagging approach was developed to overcome these limitations by placing GFP at internal sites in a protein to avoid masking N- or C-terminal targeting signals (Tian et al., 2004). It has been used in a variety of GFP targeting studies in plants (Drakakaki et al., 2006; Anand et al., 2007; Blakeslee et al., 2008). Although the false-positive rate with GFP appears to be low, the false-negative rate may be much higher, depending on the nature of the constructs tested. Many proteins may have been defined as being targeted to a single organelle based on evidence from a single (or limited) number of constructs, when they could in fact be targeted to multiple organelles.

Two final issues are: which translation product should be tested and what tissue or organ should be used to assess in vivo location? Examples of proteins whose locations are changed by splicing include protein isoaspartylmethyltransferase 2 (Dinkins et al., 2008), glutathione S-transferase F8 (Thatcher et al., 2007), and a transcription factor that plays a role in phloem development (Carrie et al., 2009b). Alternative translation initiation sites also seem to be involved in changing targeting for some proteins such as tRNA nucleotidyltransferase (von Braun et al., 2007), protoporphyrinogen oxidase II (Watanabe et al., 2001), and thiamine biosynthesis (TH1) (Chabregas et al., 2003). When making constructs, the use of sequences in the 5′ untranslated region may affect the translation start site. DNA-directed DNA polymerase-2 in Arabidopsis has sequences in the 5′ untranslated region that can affect translation from a CUG codon, seven codons upstream of the AUG codon. This changed the protein from a plastid targeted protein to a protein targeted to mitochondria and plastids (Christensen et al., 2005). Another study on this protein reported that both protein products (i.e., one translated from the native AUG codon and one translated from seven codons upstream of this AUG) were dual-targeted but that dual targeting could only be observed in some tissues (Carrie et al., 2009b). Thus, attention to the details of what is tested, and where, need to be considered in both designing and interpreting in vivo targeting experiments.


The ability of a protein to be targeted to a specific location does not always lead to accumulation in that location. For example, α-carbonic anhydrase follows an authentic transport pathway via the ER and Golgi apparatus to accumulate in plastids (Villarejo et al., 2005). Several proteins found in studies investigating the plastid proteome appear to contain an ER-targeting signal, and it is likely that this pathway is used by a variety of proteins (Villarejo et al., 2005). A number of proteins involved in peroxisomal biogenesis are also initially targeted to the ER and subsequently accumulate in peroxisomes (Tabak et al., 2008). Chimeric constructs that remove or mask secondary sorting signals would not correctly determine the location of these proteins. Additionally, while targeting assays may show that a protein goes to two locations, critical to function will be the degree to which the protein accumulates in each location.

Immunoblotting, immunolocalization, and activity assays are common approaches to define accumulation in different subcellular locations (Table 1). However, these assays must define their specificity before they can be accurately linked to the products of specific genes.

Alternatively, gene-specific measures of accumulation readily can be provided by peptide mass spectrometry approaches. This is often termed subcellular proteomics and involves the cataloguing of the protein composition of isolated organelles and membrane structures isolated following cell disruption. To date, the subcellular location of >4600 specific proteins in Arabidopsis to plastids, mitochondria, peroxisomes, ER, tonoplast, plasma membrane, Golgi apparatus, nuclei, and vacuole have been assigned (Heazlewood et al., 2007). These experiments traditionally have relied on the preparation of highly purified organelle or membrane fractions to avoid the identification of lower level contaminants from other locations. However, this has become increasing difficult due to the sensitivity of mass spectrometers and the increasing use of shotgun, non-gel analysis of samples that can identify even the contaminants of low abundance (Lilley and Dupree, 2007).

In comparison to these developments in mass spectrometry, the technological improvements in the purity of organelle/membrane preparations have been slight. The best solution to date to minimize false-positive claims has been quantitative comparison of fractions with different degrees of enrichment of specific organelles or membranes of interest. This has been performed for analysis of the plasma membrane (Dunkley et al., 2006; Nelson et al., 2006), mitochondria (Huang et al., 2008), peroxisome (Eubel et al., 2008), and Golgi and tonoplast membrane (Dunkley et al., 2006). It has allowed the dissection of subproteomes into proteins enriched with marker proteins and others that appear to be diluted during enrichment of the organelle markers. Both gel-based quantitative comparisons, such as difference gel electrophoresis or non-gel-based liquid chromatography analysis by isobaric tags, isotope labeling, or nonlabeled spectral counting approaches, have provided this kind of quantitative data on organelle location. It should be noted that subcellular proteomics does not provide a complete analysis of protein composition as specific classes of proteins are rarely detected in such studies, for example, the very small, hydrophobic, and/or basic proteins. Hence, this analysis is likely to have a significant false-negative rate if the absence of identification is used as evidence of a protein being absent from a particular location.


It should be recognized that targeting and even accumulation do not necessarily indicate the site of function or the relative importance of the determined location for the function of the protein under investigation. First, it is possible that proteins accumulate in one location but function in another compartment. A number of transcription factors are located in the ER and upon stress are cleaved, and the soluble fragment migrates to the nucleus to function as a transcription factor (Liu et al., 2007; Gao et al., 2008). Cytosolic proteins, such as LSD1, can bind to and retain transcription factors, such as bZIP10, in the cytosol of Arabidopsis, thereby controlling the quantity of bZIP10 in the nucleus and influencing oxidative stress responses and programmed cell death (Kaminaka et al., 2006). Also, phytochromes can move from the cytosol to the nucleus where they activate up to 10 to 20% of Arabidopsis genes (Pfeiffer et al., 2008). Thus, the ability to detect such a protein at its site of function, rather than accumulation, may depend on the rate of turnover in this secondary location and may require specific experimental approaches as outlined in the references above. Second, it is possible for a multitargeted protein that its presence in one location dominates the function of the protein or that it functions in quite different ways in its separate locations. Third, it is possible that location is not critical for function and that a protein can be relocated without hindering its function due to the readily transported characteristics of its substrates and products.

Defining this location-function nexus for each protein can be investigated experimentally but represents a monumental task for a proteome-wide study. For example, a dual-targeted protein can be knocked out and replaced by single location forms to determine the relative importance of the two protein populations. Also, proteins located in one compartment can be knocked out and attempts made to complement mutants with alternatively targeted constructs. Such approaches allow the building of networks of information on the proteome, defining those proteins for which a given location is essential (location dependent) and those for which location can be changed (location independent). In this broader context, protein–protein interaction networks will be important tools for defining subcellular location of plant proteins. Analysis of a predicted interaction network for Arabidopsis, based on orthology to proteins from other species, found that predicted protein–protein interactions were highly enriched with proteins that are located physically in the same cellular organelle (Geisler-Lee et al., 2007). Therefore, as large experimental sets of protein–protein interactions in plants are developed (Morsy et al., 2008), these will provide a large and valuable repository of evidence for both subcellular location and functional interaction.


To reduce errors in defining the location(s) of proteins, a combination of targeting and accumulation assays is recommended (Figure 1). In protein-focused studies, a targeting assay using a fluorescent tagging approach combined with an assay that shows accumulation of the protein not only independently cross validate each other but also give complementary biological information. For example, a protein may have the ability to be targeted to more than one location, but accumulation may be dominant in only one location. Experimental design must ensure that the technical limitations of these assays are considered using appropriate controls (Figure 1).

Figure 1.
A Guideline for Defining the Location of Proteins.

For studies defining the protein composition of a subcellular fraction, quantitative evidence for the enrichment of the protein during the fractionation studies and an estimation of false-positive rates should be obtained. It is important to consider the possibility of multiple locations for proteins (Figure 1). The choice of approach will depend on the study in question and should be influenced by the available predicted and experimental data on the protein of interest.

A variety of other assays outlined in Table 1 can also be used to confirm targeting or accumulation, but they are usually restricted to confirming a single location rather than providing broad information on other possible locations. For example, in vitro uptake assays are good for determining targeting to an organelle in question, but no reported studies have employed a wide variety of in vitro assays to discount multiple locations. Likewise, a variety of protein–protein interactions assays (immuno pull down, fluorescence resonance energy transfer, or bimolecular fluorescence complementation) can confirm location (Ohad et al., 2007), but these depend on knowledge of the interacting protein(s) to generate the complementary tagged proteins and thus are not appropriate as primary methods to determine location.

Therefore, incorporating at least two independent lines of evidence will help to confirm, correct, or discover the nuances in the subcellular location of proteins. Web tools and databases such as The Arabidopsis Information Resource (www.Arabidopsis.org), SUBA (www.plantenergybiology.org/suba2/), and PPDB (ppdb.tc.cornell.edu) offer different compilations of experimental and predicted data sets for location of Arabidopsis proteins. They represent an excellent starting point for researchers in assessing the available evidence before they plan additional experiments to solidify the evidence for the location of proteins of interest.


The accurate determination of protein location is necessary for defining protein function, for systems biology modeling approaches, and for defining organelle functions and pathways of communication between organelles. Furthermore, there is potential to relocate or reroute existing biochemical pathways to overcome limitations that currently exist in the plant cell factory. Good examples can be seen with the targeting of the Escherichia coli glycolate catabolic pathway to plastids, bypassing the need for a complex photorespiratory pathway involving peroxisomes and mitochondria (Kebeish et al., 2007) or the targeting of sesquiterpene synthesis proteins to mitochondria to exploit intermediates in the ubiquinone biosynthesis pathway for synthesis of terpenes that elevate attraction of herbivore predators (Kappers et al., 2005). How many other shortcuts can be achieved by engineering changes in protein location? It seems clear that novel targeting of a preexisting protein can be a powerful trait in evolutionary divergence. The modification of this trait offers substantial opportunities to put the walls and selective passages that compartment cellular function to work as we seek to become true engineers of the eukaryotic cell.


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