Abstract
The plant Golgi apparatus and trans-Golgi network are major endomembrane trafficking hubs within the plant cell and are involved in a diverse and vital series of functions to maintain plant growth and development. Recently, a series of disparate technical approaches have been used to isolate and characterize components of these complex organelles by mass spectrometry in the model plant Arabidopsis thaliana. Collectively, these studies have increased the number of Golgi and vesicular localized proteins identified by mass spectrometry to nearly 500 proteins. We have sought to provide a brief overview of these technical approaches and bring the datasets together to examine how they can reveal insights into the secretory pathway.
BACKGROUND
At its simplest level, subcellular proteomics attempts to identify all proteins in a particular compartment. However, even with such a basic definition in mind, the Golgi proteome presents conceptual difficulties; functional proteins in the Golgi may also be functional elsewhere (Ondzighi et al., 2008), whilst endoplasmic reticulum (ER)–Golgi connections () makes absolute divisions between the proteomes of these compartments somewhat futile. A number of proteins are known to form functional associations on the cytoplasmic face of cisternae but are part of the cytosol (Ito et al., 2011), so the very definition of the Golgi proteomes is problematic. Furthermore, in such an architecturally heterogeneous organelle, simply identifying all the proteins present in the Golgi is not that helpful unless we can classify them according to sub-Golgi location, post-Golgi compartments, cargo, resident, or dual-localized proteins. The plant Golgi poses a challenge in terms of isolation, not least because of its fragmented morphology. In mammalian cells Golgi stacks tend to be less numerous per cell with fewer, longer cisternae which are less tightly associated with the ER and could be relatively easily isolated (Morre and Mollenhauer, 2009). Excepting highly conserved pathways such as protein N-linked glycan processing, few similarities exist between plant and mammalian Golgi. Thus assuming Golgi-residency between the two systems based on homology alone is not possible. Earlier work on Golgi from rat liver was therefore of limited help either in terms of providing an isolation strategy or a comprehensive bank of marker proteins (Taylor et al., 1997). The plant Golgi is much less structurally defined during and after cell homogenization than, for example, plastids or mitochondria. Consequently, quality control of and improvements to isolation strategies have been tricky and therefore purity limited when using sucrose density centrifugation strategies (Morre and Mollenhauer, 1964). In short, it is easy to understand why progress in Golgi proteomics has trailed behind other subcellular compartments in plants. In light of the shortcomings of sucrose density centrifugation for plant Golgi purification, two more technical but very different approaches have been successfully applied, namely localization of organelle proteins by isotope tagging (LOPIT) and free-flow electrophoresis (FFE). The LOPIT approach does not distinguish between Golgi and the trans-Golgi network (TGN) localized proteins but identifies resident proteins (, ; Nikolovski et al., 2012), whilst the FFE approach identified proteins in fractions of purified Golgi, that were estimated to be enriched in medial Golgi cisternae (Parsons et al., 2012a). Immunoisolation of compartments has recently been used to great effect in separating components of the TGN, enabling comparative proteomics at the sub-Golgi level (). Characterization of Golgi-enriched fractions has been attempted in various plant systems (Tanaka et al., 2004; ; Mast et al., 2010), major, large-scale proteomic characterizations have exclusively occurred in the model plant Arabidopsis thaliana.
AN OVERVIEW OF THE Arabidopsis GOLGI–TGN PROTEOMES
Initial attempts to characterize the Arabidopsis Golgi by mass spectrometry were undertaken nearly a decade ago with the aim of distinguishing between ER- and Golgi-resident proteins (). The LOPIT approach involves quantitative mass spectrometry of proteins labeled with isotope tags. A cell homogenate separated along a linear gradient is fractionated and pairwise comparisons of fractions allow abundance ratios of isotope masses to be calculated for each protein. Proteins physically located in the same compartment will have similar ratios and so cluster together during partial least squares discriminant analysis (Figure 1). Using LOPIT, 89 proteins were initially localized to the Golgi () but the requirement that proteins carry all four tags limited the number of proteins for which a statistically credible localization could be assigned. Recent reanalysis and analysis of existing and new datasets, incorporating values for “missing” tags assigned using partial least squares regression models and training sets based on fully tagged proteins, enabled the collective localization of 204 proteins to the Golgi/TGN (; Nikolovski et al., 2012).
FIGURE 1
Although a major motivation for the development of LOPIT was the difficulty in separating the Golgi, particularly from ER contaminants, a recent study has managed to isolate Golgi vesicles with an estimated 80% purity based on protein composition. This was achieved using a combination of sucrose density centrifugation and FFE (Parsons et al., 2012a). The power of FFE for organelle isolation was demonstrated in plants several years ago when applied to the separation of mitochondria and peroxisomes, two organelles which are typically hard to separate using density centrifugation alone (
A dissection of the complexity of the Golgi proteome was recently attempted using immunoisolation of specific TGN trafficking populations. Affinity purified TGN compartments from plants expressing a syntaxin from plants (SYP61)-CFP construct were enriched for the TGN by sucrose density centrifugation then exposed to anti-FP antibodies coupled to agarose beads and analyzed by mass spectrometry (
THE SIZE OF THE PLANT GOLGI PROTEOME
In total, 452 proteins have been characterized by mass spectrometry to the Golgi apparatus and 145 to the TGN from the model plant Arabidopsis. An ever-present question in subcellular proteomics concerns the total number of proteins present in an organelle. Given the residential/transitory definitions raised above, this is an especially difficult question to answer in the case of the Golgi and TGN, since proteins with ambiguous localization profile cannot be clearly assigned to a particular sub-compartment. Therefore dual-localized but Golgi-functional proteins or those at the cis-Golgi extremity will potentially be excluded from many analyses. Given the extensive subcellular localization data in the model plant Arabidopsis and the collection of subcellular prediction algorithms that are outlined in the SUBA database (
Table 1
| Predictor | Predicted Golgi Arabidopsis | Expt. any location (575) | Expt. in Golgi (575) | Expt. non-Golgi | FNR Golgi prediction | Est. correct predictions | FNR Golgi prediction | Predicted Golgi | Non-predictable expt. Golgi | Reference |
|---|---|---|---|---|---|---|---|---|---|---|
| AdaBoost | 66 | 13 | 2 | 11 | 0.85 | 10 | 1.00 | 2919 | 2909 | Niu et al. (2008) |
| BaCelLo | 5178 | 1101 | 104 | 997 | 0.91 | 489 | 0.82 | 2704 | 2215 | Pierleoni et al. (2006) |
| EpiLoc | 290 | 121 | 30 | 91 | 0.75 | 72 | 0.95 | 1378 | 1306 | |
| iPSORT | 5688 | 1439 | 177 | 1262 | 0.88 | 700 | 0.69 | 2273 | 1573 | |
| MultiLoc2 | 916 | 299 | 114 | 185 | 0.62 | 349 | 0.80 | 1762 | 1412 | |
| Plant-mPLoc | 1074 | 330 | 100 | 230 | 0.70 | 325 | 0.83 | 1871 | 1546 | |
| Predotar | 5851 | 1438 | 186 | 1252 | 0.87 | 757 | 0.68 | 2340 | 1583 | Small et al. (2004) |
| PredSL | 8780 | 2082 | 259 | 1823 | 0.88 | 1092 | 0.55 | 2425 | 1333 | Unpublished |
| PProwler | 8885 | 2121 | 296 | 1825 | 0.86 | 1240 | 0.49 | 2409 | 1169 | |
| SLPFA | 7738 | 1733 | 142 | 1591 | 0.92 | 634 | 0.75 | 2567 | 1933 | Tamura and Akutsu (2007) |
| SLP-Local | 7406 | 1599 | 167 | 1432 | 0.90 | 773 | 0.71 | 2663 | 1890 | Matsuda et al. (2005) |
| TargetP | 6492 | 1574 | 200 | 1374 | 0.87 | 825 | 0.65 | 2372 | 1547 | |
| WoLF PSORT | 112 | 45 | 11 | 34 | 0.76 | 27 | 0.98 | 1431 | 1404 | |
| YLoc | 1235 | 318 | 105 | 213 | 0.67 | 408 | 0.82 | 2233 | 1825 |
Estimated size of the Arabidopsis Golgi/TGN proteomes utilizing data in the SUBA database and the current integrated proteome (575) employing the abilities of subcellular prediction algorithms.
Predicted Golgi Arabidopsis: All proteins predicted to be Golgi in Arabidopsis (TAIR10).
Expt. any location (575): Predicted Golgi and experimentally determined to be in any location by MS or FP (SUBA) or Golgi (575).
Expt. in Golgi (575): Predicted Golgi and experimentally determined to be in Golgi (575).
Expt. non-Golgi: Predicted Golgi but experimentally found to be non-Golgi [(Expt. any location) - (Expt. non-Golgi)].
FPR Golgi prediction: False positive rate for Golgi prediction. [(Expt. non-Golgi)/(Expt. in Golgi)].
Est. correct predictions: Estimation of correct predictions from total Golgi predictions in Arabidopsis [(Expt. any location) - (Expt. any location) × (FPR Golgi prediction)].
FNR Golgi prediction: False negative rate for Golgi prediction [1 - (Expt. in Golgi)/575].
Predicted Golgi: The predicted size of the proteome based on validated performance for each predictor program [(Expt. any location) × (1 - FPR)/(1-FNR)].
Non-predictable expt. Golgi: The size of the unpredictable Golgi proteome [(Predicted Golgi) - (Est. correct predictions)].
Employing the relational capabilities of the SUBA database, it is possible to compute a size estimate of the Golgi/TGN proteome based on each algorithms performance. The overall performance of each prediction program can vary considerably with regard to the total predicted “Golgi” proteins in Arabidopsis (contrast AdaBoost, 66 Golgi and PProwler, 8885 Golgi) and positive prediction rate of the experimental proteome (contrast AdaBoost <1% and PProwler >50%). However, after calculating false positive and false negative rates for each program, the final predicted Golgi proteomes are remarkably similar. Based on this analysis, the Arabidopsis Golgi/TGN proteome is estimated to be 2239 ± 465, employing the average of the predicted proteomes of these 14 subcellular prediction programs.
USING THE PROTEOME: WHAT ARE THE ROLES OF UNCHARACTERIZED PROTEIN FAMILIES?
A number of large gene families have been identified by both the FFE and LOPIT studies (Nikolovski et al., 2012; Parsons et al., 2012a). The quantitative mass spectrometry performed when applying LOPIT (Nikolovski et al., 2012) and spectral counts from FFE isolates (Parsons et al., 2012a), combined with localization data (
The cyclophilin-like peptidyl-prolyl cis–trans isomerase family is consistently represented in the Golgi proteomes. These are known to catalyze conversion of cis to trans conformation of peptide bonds preceding prolyl residues in newly synthesized peptides (
The prenylated RAB acceptor B2 (PRA1.B2, AT2G40380) is found in both Golgi proteomes (FFE and LOPIT) but not the TGN, implying involvement with cisternal-specific interactions and vesicle docking. Examining proteins present uniquely in the TGN, besides those involved in trafficking such as the RAB GTPases, soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNARE;
Many functionally important Golgi proteins may actually be the sole members of their protein family. Of the 111 proteins not assigned to a functional protein category in the FFE proteome, 30 were also identified by LOPIT studies and many different protein families were represented. Amongst datasets such as these, dataset overlaps can provide a means to shortlist potentially important proteins about which little information is available.
Interestingly, although the proteomes comprised by the LOPIT studies and Parsons et al. (2012a) were both derived from similar starting tissues, a number of proteins are found in Parsons et al. (2012a) but not LOPIT studies and vice versa. Parsons et al. (2012a) identified more proteins overall and results included cargo proteins, unlike in LOPIT studies. Nevertheless after eliminating those annotated by Parsons et al. (2012a) as either transient or involved in protein synthesis, 81 proteins identified by LOPIT are not found in Parsons et al. (2012a) and 205 are in Parsons et al. (2012a) but not LOPIT. No clear pattern, e.g., protein abundance, exists between the proteins observed in either study; most probably differences arise from variations in methodologies, highlighting the value of multi-facetted approaches to proteomic characterization of the Golgi.
WHAT IS MISSING FROM THE EXPERIMENTAL GOLGI PROTEOME?
Specific questions concerning what has not been identified so far are obviously difficult to answer but they can be addressed in part by examining what sorts of protein have been localized by fluorescent tagging but not identified by subcellular proteomic techniques. Fluorescent localization of proteins is generally motivated by interest in a specific protein and so is more likely to represent low-abundant polypeptides. It therefore provides an initial guide to the completeness of subcellular proteomic approaches.
Notably absent from proteomic surveys, but localized to the Golgi stack by fluorescent tagging are the Golgins and GRIP domain proteins (Latijnhouwers et al., 2007). Several glycosyltransferases such as cellulose synthase-like D5 (CSLD5;
Several RAB GTPases have been localized by fluorescent protein assay to the Golgi stack (
Judging from these inconsistencies between the subcellular proteomics data and fluorescent protein localizations, it is clear that Golgi proteomics must be applied to other tissue types if the proteome is to be “completed.” This presents an even greater technical challenge as young, softer tissues are more easily homogenized to maintain Golgi stack integrity (Morre and Mollenhauer, 2009). However, useful information may be gleaned from less pure preparations using tougher, challenging tissue types, or preparations which are less pure but contains Golgi-associated and Golgi matrix proteins, as there is now a sufficiently broad base of proteins from which to compile ever more extensive markers and training sets.
SUB-GOLGI PROTEOMICS AND THE GOLGI IN AN ENDOMEMBRANE CONTEXT
Comparative analyses such as those discussed above can now be formulated since a post-Golgi compartment has been characterized. The potential for distinguishing resident and cargo Golgi components can also be applied. Almost 30% of proteins identified in the TGN proteome comprise non-Golgi proteins as determined by the LOPIT approach (
CONCLUDING REMARKS
Although one of the most technically challenging organelles to isolate, a diversity of technologies have led to two Golgi proteomes and one proteome of TGN vesicles, resulting in nearly 500 proteins now localized to the Golgi and/or TGN by mass spectrometry. As the hub of protein trafficking, its proteome is best understood within the context of other proteomes; comparisons between these compartments bring a new level of understanding to protein distribution through the endomembrane system and show the potential for expansion through proteomic analysis of other post-Golgi compartments. It is estimated here that only about 20% of Golgi proteins have been identified thus far by mass spectrometry. So far all studies have been carried out in rapidly dividing, developing tissue (either cell suspension culture or liquid-grown plantlets). Exploration of other tissue types is needed to increase the coverage of the Golgi proteome. Efforts must also be concentrated in getting the proteomes of cis-, medial-, and trans-Golgi sub-compartments and specific vesicle populations. This will incur further technical challenges but will help identify more lowly expressed proteins and provide invaluable insight into plant Golgi functions.
Statements
Acknowledgments
This work conducted by the Joint BioEnergy Institute was supported by the Office of Science, Office of Biological and Environmental Research, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The work conducted by
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
Golgi, trans-Golgi network, proteomics, LOPIT, free-flow electrophoresis, Arabidopsis, SYP61
Citation
Parsons HT, Drakakaki G and Heazlewood JL (2013) Proteomic dissection of the Arabidopsis Golgi and trans-Golgi network. Front. Plant Sci. 3:298. doi: 10.3389/fpls.2012.00298
Received
30 October 2012
Accepted
12 December 2012
Published
03 January 2013
Volume
3 - 2012
Edited by
Nicolas L. Taylor, The University of Western Australia, Australia
Reviewed by
Holger Eubel, Leibniz Universität Hannover, Germany; Karine Gallardo, National Institute for Agronomic Research, France
Copyright
© Parsons, Drakakaki and Heazlewood.
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
*Correspondence: Harriet T. Parsons, Department of Plant and Environmental Sciences, University of Copenhagen, Thorvaldsensvej 40, 1871 Frederiksberg C, Copenhagen, Denmark. e-mail: htpa@life.ku.dk
This article was submitted to Frontiers in Plant Proteomics, a specialty of Frontiers in Plant Science.
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