Membranous lipid bilayers act as sophisticated barriers in biology by facilitating intracellular compartmentalization of different functions as well as separation of individual cells. The selectivity of these barriers is achieved by a diverse set of proteins traversing these membranes, which fulfill functions like nutrient, ion, or metabolite transport, communication, or adhesion. Many of these functions, in particular the transport of large macromolecules like proteins, DNA, or RNA, require very large multi-subunit complexes that sometimes span several biological membranes. To understand functional mechanisms of these complexes on a molecular level, structural information of the macromolecules involved is indispensable and so the obtainment of a high-resolution structure for a given protein assembly is often the ‘Holy Grail’. While the solution of high-resolution structures has seen enormous successes in the last decade, most recently due to major enabling improvements in cryo electron microscopy (EM) (Callaway, 2015), the analysis of very large complexes, in particular of large transmembrane complexes, remains very challenging. In this review, we will point out the major difficulties in structure determination of large transmembrane complexes and present solutions to determine the stoichiometry of these complexes as an important first step towards structure elucidation if high resolution structures remain unachieved. The topic is illustrated by focussing on four different transmembrane complexes: the 650 kDa Thermus thermophilus V-ATPase (TtATPase), the 3 MDa type III secretion system (T3SS) found in Gram-negative pathogens, the 5 MDa plant cellulose synthesis complex and lastly the 50 MDa (yeast) to 110 MDa (human) nuclear pore complex (Table 1). Figure 1 illustrates the size range and complexity of three of these large transmembrane complexes addressed in this review.
Challenges for high-resolution structural analysis of large transmembrane complexes
The major obstacles for the structural analysis of large transmembrane complexes are (a) the sheer size of these complexes, often exceeding 1 MDa (Figure 1); (b) the pronounced hydrophobicity of their transmembrane domains; (c) the structural complexity involving many different complex components; and (d) the dynamic heterogeneity many complexes exhibit during their functional cycles. For these reasons, it is often difficult to obtain high-resolution structures of large transmembrane complexes with the methods currently available, even more so, if structures of different functional states are required to elucidate functional mechanisms at the molecular level.
Both electron and X-ray crystallography depend on the successful crystallization of proteins and protein complexes. There have been many improvements in the production of membrane proteins for crystallization (Clark et al., 2011; Schlegel et al., 2014) and the formation and stabilization of crystals (Carpenter et al., 2008; Klara et al., 2016). However, as seen in crystal structures of components of the TtATPase, different subunits of type III secretion systems, as well as the nuclear pore complex (Lee et al., 2010; Worrall et al., 2010; Stuwe et al., 2015), mostly structures of soluble components or extramembrane domains of transmembrane proteins have been solved for large membrane-spanning complexes. While providing immense help in the elucidation of their overall structure and function, lack of structural information on the hydrophobic core of these complexes impedes a complete understanding of their molecular mechanisms.
Single particle cryo EM, a method in which datasets of many 2D electron micrographs of single particles are averaged to generate a high resolution 3D map (Lau and Rubinstein 2010), is playing an increasingly important role in structural analysis of proteins and has been used successfully to gain a better understanding of the makeup of many membrane-spanning macromolecular complexes. A 16 Å resolution 3D map of the 0.65 MDa Tt-V-ATPase was generated using single particle cryo EM. A surface view of the 3 MDa needle complex of a Salmonella type III secretion system was reconstructed to a resolution of 10 Å, helping to establish the stoichiometry of the three transmembrane ring forming elements (Schraidt and Marlovits, 2011). Furthermore, aided by cryo EM maps, the 110 MDa human nuclear pore complex could be reconstructed to a resolution of 23 Å (von Appen et al., 2015) (Figure 1). Significant improvements in direct electron detection have most recently boosted single particle cryo EM analysis and have enabled the solution of structures at sub-nanometer resolution down to 3.4 Å, even for some transmembrane domains (Bai et al., 2015; De Zorzi et al., 2016). Despite these important improvements, flexibility of protein domains and bound lipids and detergents limit the power of cryo EM for many macromolecular complexes, in particular in their transmembrane regions.
Solid state nuclear magnetic resonance (ssNMR) spectroscopy enables the study of membrane protein structures in their native or native-like environment. While in theory molecular weight is not a limiting factor in ssNMR (Brown and Ladizhansky, 2015) and large improvements have been made in sample preparation, hardware and experimental design, such as magic angle spinning, no structures of large membrane-spanning macromolecular complexes have been solved using this method, so far (Shahid et al., 2012; Goldbourt, 2013; Ward et al., 2014).
Stoichiometry determination as a first step towards structure elucidation
As high-resolution structures are out of reach for many large transmembrane complexes at the moment, an important first step towards structural and functional understanding of these macromolecular assemblies is the determination of the stoichiometry of their components.
Towards this end, the only available direct strategy is subunit counting by single-molecule fluorescence photobleaching. Photobleaching of protein complexes reduces their fluorescence intensity in increments that correspond to the number of fluorescent protein-tagged protomers in the complex at hand (Ulbrich and Isacoff, 2007). The notable advantage of this approach is the ability to count complex components in their native context, without the need of prior purification. This even allows analysis of less stable complexes that resist purification as well as dynamically associated complex components (Diepold et al., 2015). However, the approach requires the functional fusion of a fluorescent protein to complex component of interest, a premise that is often not met for very hydrophobic proteins or components buried deeply within their respective complex. Nonetheless, counting by single-molecule photobleaching has been used successfully to resolve the stoichiometry of transmembrane proteins of different transmembrane channels (Hines, 2013) as well as type III secretion and flagellar components (Leake et al., 2006; Morimoto et al., 2014; Romano et al., 2016), TAT translocon components (Leake et al., 2008), or components of the Arabidopsis thaliana cellulose synthesis complex (Chen et al., 2014).
For components of membrane-spanning macromolecular complexes that are incompatible with direct counting by single-molecule photobleaching, indirect approaches of stoichiometry determination have to be employed. As a first step, most indirect approaches require the prior isolation of a homogeneous preparation of the complex of interest and the identification of the components contained therein. The extraction of membrane protein complexes from the lipid bilayer is facilitated by detergents and thus the choice of detergents plays a critical role in complex purification. Typically, mild, non-ionic detergents like dodecyl-maltoside are prefered, however, the detergent that optimally retains the integrity of the transmembrane complex of interest needs to be identified empirically (Arnold and Linke, 2008). Isolation of the complex is best achieved by affinity purification strategies, where the bait is a component that assembles last into the complex and requires the presence of all other components for its own assembly. This strategy ensures isolation of completely assembled complexes and avoids handling of a heterogeneous mixture of assembly intermediates. Often a final size-based separation of affinity-purified complexes is necessary to obtain a homogeneous preparation of only one complex species. Towards this end, size exclusion chromatography (SEC) is suitable for complexes in solution while blue native PAGE (see details below) is well-suited for separation of membrane protein complexes and subsequent in gel digestion for analysis by mass spectrometry. Blue native PAGE in combination with mass spectrometry or immunoblotting is also well suited as a measure of compositional analysis and quality control of isolated complexes. A visual inspection of the complexes is best achieved by EM of negative stained material.
The determination of complex stoichiometry by most means requires the separate analysis of complex mass and component ratios, from which the stoichiometry can be calculated. Below, we first present a brief overview of approaches to determine the mass of protein complexes and subsequently discuss the analysis of the ratio of protein components in more detail.
Analysis of the molecular mass of protein complexes
Blue native PAGE is a commonly used technique to analyze the composition and mass of membrane protein complexes in a relatively simple format that does not require prior purification of the analyte. The technique utilizes the size-dependent differential migration of Coomassie G-charged membrane protein complexes in polyacrylamide gradient gels under non-denaturing conditions (Schägger and von Jagow, 1991). It allows for the separation of protein complexes between 20 kDa and 10 MDa (Wittig et al., 2006; Weiland et al., 2014), however, the resolution of the technique is very limited, in particular above 1 MDa. Its analytic power is further limited by the fact that bound lipids, detergents, and Coomassie affect the migration behavior of membrane proteins, which often leads to an overestimation of the mass of analyzed complexes (Stenberg et al., 2005; Hill et al., 2014). Blue native PAGE has been used extensively for the analysis of composition and assembly of complexes of bacterial type III, IV, and VII secretion systems (Krall et al., 2002; Wagner et al., 2010; Houben et al., 2012; Kuroda et al., 2015), however, due to the large size of these complexes, reliable masses or stoichiometry could not be determined. Over all, blue native PAGE is a suitable technique to obtain an estimate of complex size and composition but it cannot be used for a mass analysis that is sufficiently accurate to support stoichiometry determination.
Size exclusion chromatography (SEC) is another commonly employed method to determine the molecular mass of purified soluble proteins up to 2 MDa, however, like for blue native PAGE, bound lipids and detergents alter the stokes radius of membrane proteins and thus compromise the use of SEC for the accurate estimation of their mass (Slotboom et al., 2008). This problem can be partially overcome by complementing the on-line measurement of the absorbance of SEC-separated protein complexes with measurements of their light scattering and refractive index (a.k.a. SEC-multi angle laser light scattering, SEC-MALLS). This approach allows to separately calculate the masses of protein and detergent content (Folta-Stogniew, 2006) for non-ionic detergents that are transparent at a wavelength of 280 nm (Arnold and Linke, 2008). The typical mass error of SEC-MALLS is 5–10% for membrane protein-detergent complexes, which makes the technique suitable for determination of the oligomeric state of complexes made of up to 20 components (Slotboom et al., 2008).
Analytical ultracentrifugation allows the determination of sedimentation velocity or sedimentation equilibrium of macromolecular particles, which can be used to calculate the size, mass, composition and interaction of macromolecules in solution (Ebel, 2011). For the analysis of membrane protein-detergent complexes, the analysis of sedimentation velocity is preferred over sedimentation equilibrium, since it has fewer constraints in terms of homogeneity and stability of the sample (Ebel, 2011; Zhao et al., 2013). Depending on the centrifugation set-up proteins of a size between 100 Da and 100 MDa can be studied (Zhao et al., 2013); for instance part of the TonB-dependent energy transduction system of ~260–520 kDa was analyzed using measurements of its sedimentation velocity.
The most accurate approach for mass determination of protein complexes is native mass spectrometry in which (membrane) protein (-detergent) complexes are brought into the gas phase by direct electrospray ionization (ESI) (Fenn et al., 1989; Laganowsky et al., 2014). Membrane proteins are liberated of detergent by collision-induced dissociation in an inert gas, after which their mass can be analyzed accurately (Barrera et al., 2008; Borysik and Robinson, 2012; Reading et al., 2015). Collision-induced dissociation does not only remove detergents but can also dissociate complexes and thus enable their compositional analysis (Laganowsky et al., 2014). Native mass spectrometry requires only small amounts of purified complexes (pmol or less) (Wohlgemuth et al., 2015) and allows for the mass determination of membrane protein complexes of up to 700 kDa as exemplified by the analysis of V-type ATPases from T. thermophilus and Enterococcus hirae (Zhou et al., 2011).
Analysis of component ratios of protein complexes
Once the constituting components of a complex and its mass have been determined, the ratio of components needs to be resolved in order to enable the calculation of their stoichiometry.
Densitometry of Coomassie-stained protein bands of SDS PAGE-resolved components of purified protein complexes is a commonly employed approach to estimate the ratio of complex components. While this approach is technically very simple, quick, and does not demand specialized equipment, accuracy suffers from differential staining efficiencies of different proteins. These depend on the extent of unfolding in the gel, bound detergent, and number of basic residues. Independent of these shortcomings is the use of [35S]-Met/Cys labeling for autoradiography of protein samples, which also features a high dynamic range and a linear relationship between detection signal and protein amount. This classical approach has been used for instance for the first estimation of the stoichiometry of bacterial flagella (Jones et al., 1990). Also immunoblotting of complex components instead of staining offers a more robust basis for quantification but requires well-characterized specific antibodies or the use of epitope tags for each protein studied as well as purified individual complex components for generation of a standard curve. A major obstacle in quantitative immunoblotting is the low dynamic range and quick band saturation of chemiluminescence-based detection systems, for which reason the detection via (near-infrared-)fluorescent secondary antibodies is preferable. A more detailed discussion of the strengths and weaknesses of quantitative immunoblotting has recently been presented by McDonough et al. (2014). Its use for stoichiometry determination is exemplified by a report of a 1:1:1 ratio of the three different CESA proteins of the cellulose synthesis complex (Hill et al., 2014).
Mass spectrometry-based approaches
Because of their high precision, quantitative power, and multiplexing capability, mass spectrometric approaches are the preferred choice for the determination of ratios of complex components. State of the art is the use of stable isotope-labeled standards for direct ratiometric or absolute quantification of complex components. The strategy is based on co-analyzing stable isotope-labeled standard peptides of complex components together with a non-labeled sample of the complete complex to determine the ratio between labeled and non-labeled material (Figure 2A). Besides a homogeneous and well-defined preparation of the analyte complex, this approach also requires a careful selection of standard peptides, which can be challenging for membrane-spanning complexes. Hydrophobic transmembrane proteins tend to have few tryptic peptides due to the sparsity of positively charged arginine and lysine residues in the transmembrane segments. Additionally, SDS-resistant secondary structures of transmembrane domains often reduce digestion efficiency thus leading to frequent missed cleavages. Even though sequence coverage has been significantly improved by the use of alternative enzymes like thermolysin or alternative chromatographic or SDS PAGE separations, some transmembrane domains remain resistant to detection and analysis (Whitelegge, 2013).
Stable isotope-labeled standard peptide strategies exist in three principle variations, which are described in more detail below: Absolute quantification (AQUA) peptides (Gerber et al., 2003), QconCAT artificial proteins (Pratt et al., 2006), or peptide concatenated standards (PCS) (Kito et al., 2007).
For the AQUA strategy, synthetic stable isotope-labeled, i.e. ‘heavy’, peptides are used as standards. These peptides, selected from tryptic peptides of the proteins of interest, are accurately quantified and spiked into the unlabeled, i.e. ‘light’, purified complex for subsequent mass spectrometry-based ratiometric or absolute quantification. This method has been used very successfully in quantifying the level of posttranslational modifications (Gerber et al., 2003; Chahrour et al., 2015), in analyzing complexes of lower stoichiometric range (Schmidt et al., 2010; Wohlgemuth et al., 2015), and in defining part of the human nuclear pore complex (von Appen et al., 2015). While this approach is well suited for absolute quantification, it bears the risk of obtaining a skewed stoichiometry of complex components since the spiking with synthetic peptides does not take into account differences in digestion efficiencies that occur in particular for transmembrane proteins. A major drawback of the approach is also the high cost factor of quantified synthetic isotope-labeled peptides.
QconCAT (previously termed QCAT) uses standard peptides of components of the complex of interest concatenated into one artificial protein at a 1:1 ratio. As the artificial standard protein is labeled with heavy isotopes by the SILAC approach (Ong, 2002), the production of the standard is very cost-efficient. The 1:1 ratio of concatenated standard peptides allows for ratiometric quantification when the heavy standard protein and the light complex are co-digested and analyzed by mass spectrometry. If the difference in protein concentration in the complex of interest is greater than one order of magnitude, it becomes advisable to design several QconCAT proteins with peptides grouped according to their estimated abundance (Pratt et al., 2006). The QconCAT strategy has been used to determine the stoichiometry of several membrane associated protein complexes (Nanavati et al., 2008; Olinares et al., 2011) but not for transmembrane complexes.
The PCS strategy takes an approach very similar to QconCAT. However, in addition to just the tryptic peptides of interest, native flanking regions upstream and downstream of each peptide are also included in the concatenated standard (Kito et al., 2007). Since flanking regions influence the efficiency of tryptic digestion, this trick results in a more similar digestion behavior of sample and standard, in particular for transmembrane complexes (Kito and Ito, 2008). We were able to use the PCS strategy to determine the stoichiometry of the complete needle complex of a type III secretion system of Salmonella Typhimurium, a multi-MDa transmembrane complex with a stoichiometric range of 1–24 (disregarding the needle filament itself) (Zilkenat et al., 2016). Knowledge of the stoichiometry of three of its components (Schraidt and Marlovits, 2011) allowed the calculation of absolute numbers per complex from protein:protein ratios obtained by the PCS approach.
Both, PCS and AQUA approaches have been refined to cover a wider dynamic range of ratios (Figure 2B). The equimolarity through equalizer peptide (EtEP) strategy adds a non-native equalizing peptide to each synthesized, stable isotope labeled standard peptide, separable by a trypsin cleavage site. This allows quantification of all standard peptides while knowing only the absolute amount of the non-labeled version of this equalizer peptide (Holzmann et al., 2009). This feature improves the cost efficiency of the AQUA approach and allows for more accurate results since a higher number of peptides from the same protein can be analyzed in parallel.
Hierarchical PCS were introduced to quantify more proteins over a wider dynamic range (Kito et al., 2016). Each stable isotope-labeled primary PCS is extended by a unique ID-tag peptide, which sequence is not part of the complex of interest. The ID-tags of different PCSs are then concatenated in a non-labeled secondary PCS. The peptides are grouped in different PCSs according to the estimated abundance of the respective complex components. This allows the adjustment of the concentration of the standards so that every single ratio of labeled:unlabeled peptides remains below 10, as ratios above 10 have been reported to lead to measurement errors in complex mixtures (Hanke et al., 2008). As this method has been published very recently, no data on its use on transmembrane complexes is available yet. However, based on our good experience with the standard PCS strategy, hierarchical PCS should be a powerful development.
In the last decade, immense improvements have been made towards the determination of membrane protein structures (Hendrickson, 2016) but the study of large structures in the MDa range remains challenging, even though the number of tools available to researchers has been significantly expanded (Table 2). Cryo-EM and crystallography can offer great insights on atomic details, however, obtaining high resolution images of membrane protein complexes above 0.5 MDa is often difficult and even if atomic resolution structures can be achieved, parts of the structure, especially transmembrane domains, may remain unresolved (Schraidt and Marlovits, 2011; Stuwe et al., 2015). Elucidating the stoichiometry of the components comprised in a complex by other methods can both support the structural efforts as well as answer unresolved questions. Especially for ‘ill-behaving’ membrane complexes, it is worth to study the components making up the structure of a complex in parallel to pursuing an atomic resolution structure.
To resolve the stoichiometry of a complex, the mass of the total complex as well as the ratio of each protein towards each other has to be known. Recent progress in native MS has led to the capability of measuring greater masses, allowing for calculation of complete complexes. However, investigations of membrane complexes have not yet reached the same mass range as, e.g. bacteriophage particles (Chait et al., 2016). For very large transmembrane protein complexes, analytical ultracentrifugation is a very suitable choice for mass determination while smaller complexes below 1 MDa are also approachable by SEC-MALLS. To determine the ratios of transmembrane complex proteins, stable isotope-labeled standard mass spectrometry based approaches are promising as ratios of all complex components can be analyzed in one multiplex run. We were able to obtain stoichiometries ranging from 1 to 24 for a 3 MDa complex, using an AQUA-complemented PCS strategy (Zilkenat et al., 2016). Exploiting the recently introduced hierarchical standards may further improve both range and error margins of this approach and thus may facilitate the robust and accurate stoichiometry determination of large membrane-spanning protein complexes.
Work in the laboratory of S.W. relevant to this review was supported by the Alexander von Humboldt Foundation in the framework of the Sofja Kovalevskaja Award endowed by the Federal Ministry of Education and Research.
Alber, F., Dokudovskaya, S., Veenhoff, L.M., Zhang, W., Kipper, J., Devos, D., Suprapto, A., Karni-Schmidt, O., Williams, R., Chait, B.T., et al. (2007). Determining the architectures of macromolecular assemblies. Nature 450, 683–694. Google Scholar
Arnold, T. and Linke, D. (2008). The use of detergents to purify membrane proteins. Curr. Protoc. Protein Sci. 53, 4.8.1–4.8.30. Google Scholar
Bai, X., Yan, C., Yang, G., Lu, P., Ma, D., Sun, L., Zhou, R., Scheres, S.H.W., and Shi, Y. (2015). An atomic structure of human γ-secretase Xiao-chen. Nature 512, 212–217. Google Scholar
Barrera, N.P., Di Bartolo, N., Booth, P.J., and Robinson, C.V. (2008). Micelles protect membrane complexes from solution to vacuum. Science 321, 243–247. Google Scholar
Bergeron, J.R.C., Worrall, L.J., De, S., Sgourakis, N.G., Cheung, A.H., Lameignere, E., Okon, M., Wasney, G.A., Baker, D., McIntosh, L.P., et al. (2015). The modular structure of the inner-membrane ring component prgk facilitates assembly of the type III secretion system basal body. Cell 23, 161–172. Google Scholar
Borysik, A.J. and Robinson, C.V. (2012). The ‘sticky business’ of cleaning gas-phase membrane proteins: a detergent oriented perspective. Phys. Chem. Chem. Phys. 14, 14439–14449. Google Scholar
Brown, L.S. and Ladizhansky, V. (2015). Membrane proteins in their native habitat as seen by solid-state NMR spectroscopy. Protein Sci. 24, 1333–1346. Google Scholar
Callaway, E. (2015). The revolution wiill not be crystallized. Nature 525, 172–174. Google Scholar
Carpenter, E.P., Beis, K., Cameron, A.D., and Iwata, S. (2008). Overcoming the challenges of membrane protein crystallography. Curr. Opin. Struct. Biol. 18, 581–586. Google Scholar
Chahrour, O., Cobice, D., and Malone, J. (2015). Stable isotope labelling methods in mass spectrometry-based quantitative proteomics. J. Pharm. Biomed. Anal. 113, 2–20. Google Scholar
Chait, B.T., Cadene, M., Olinares, P.D., Rout, M.P., and Shi, Y. (2016). Revealing higher order protein structure using mass spectrometry. J. Am. Soc. Mass Spectrom. 27, 952–965. Google Scholar
Chen, Y., Deffenbaugh, N.C., Anderson, C.T., and Hancock, W.O. (2014). Molecular counting by photobleaching in protein complexes with many subunits: best practices and application to the cellulose synthesis complex. Mol. Biol. Cell 25, 3630–3642. Google Scholar
Clark, K.M., Fedoriw, N., Robinson, K., Connelly, S.M., Randles, J., Malkowski, M.G., Detitta, G.T., and Dumont, M.E. (2011). Purification of transmembrane protein from Saccharomyces cerevisiae for X-ray crystallography. Protein Expr. Purif. 71, 207–223. Google Scholar
Demers, J.-P., Habenstein, B., Loquet, A., Kumar Vasa, S., Giller, K., Becker, S., Baker, D., Lange, A., and Sgourakis, N.G. (2014). High-resolution structure of the Shigella type-III secretion needle by solid-state NMR and cryo-electron microscopy. Nat Commun 5, 4976. Google Scholar
De Zorzi, R., Mi, W., Liao, M., and Walz, T. (2016). Single-particle electron microscopy in the study of membrane protein structure. Microscopy 65, 81–96. Google Scholar
Diepold, A., Kudryashev, M., Delalez, N.J., and Berry, R.M. (2015). Composition, formation, and regulation of the cytosolic C-ring, a dynamic component of the type III secretion injectisome. PLoS Biol. 13, 1–21. Google Scholar
Ebel, C. (2011). Sedimentation velocity to characterize surfactants and solubilized membrane proteins. Methods 54, 56–66. Google Scholar
Eisenstein, M. (2016). The field that came in from the cold. Nat. Methods 13, 19–22. Google Scholar
Erba, E.B., and Petosa, C. (2015). The emerging role of native mass spectrometry in characterizing the structure and dynamics of macromolecular complexes. Protein Sci. 24, 1176–1192. Google Scholar
Fenn, J.B., Mann, M., Meng, C.K.A.I., Wong, S.F., and Whitehouse, C.M. (1989). Electrospray ionization for mass spectrometry of large biomolecules. Science 246, 64–71. Google Scholar
Folta-Stogniew, E. (2006). Oligomeric states of proteins determined by size-exclusion chromatography coupled with light scattering, absorbance, and refractive index detectors. Methods Mol. Biol. 328, 97–112. Google Scholar
Gerber, S.A., Rush, J., Stemman, O., Kirschner, M.W., and Gygi, S.P. (2003). Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc. Natl. Acad Sci. USA 100, 6940–6945. Google Scholar
Goldbourt, A. (2013). Biomolecular magic-angle spinning solid-state NMR: recent methods and applications. Curr. Opin. Biotechnol. 24, 705–715. Google Scholar
Hanke, S., Besir, H., Oesterhelt, D., and Mann, M. (2008). Absolute SILAC for accurate quantitation of proteins in complex mixtures down to the attomole level. J. Proteome Res. 7, 1118–1130. Google Scholar
Heck, A.J.R. (2008). Native mass spectrometry: a bridge between interactomics and structural biology. Nat. Methods 5, 927–933. Google Scholar
Hendrickson, W.A. (2016). Atomic-level analysis of membrane-protein structure. Nat. Struct. Mol. Biol. 23, 464–467. Google Scholar
Hill, J.L., Hammudi, M.B., and Tien, M. (2014). The Arabidopsis cellulose synthase complex: a proposed hexamer of CESA trimers in an equimolar stoichiometry. Plant Cell 26, 4834–4842. Google Scholar
Hines, K.E. (2013). Inferring subunit stoichiometry from single molecule photobleaching. J. Gen. Physiol. 141, 737–746. Google Scholar
Hite, R.K., Li, Z., and Walz, T. (2010). Principles of membrane protein interactions with annular lipids deduced from aquaporin-0 2D crystals. EMBO J. 29, 1652–1658. Google Scholar
Holzmann, J., Pichler, P., Madalinski, M., Kurzbauer, R., and Mechtler, K. (2009). Stoichiometry determination of the MP1-p14 complex using a novel and cost-efficient method to produce an equimolar mixture of standard peptides. Anal. Chem. 81, 10254–10261. Google Scholar
Houben, E.N.G., Bestebroer, J., Ummels, R., Wilson, L., Piersma, S.R., Jiménez, C.R., Ottenhoff, T.H.M., Luirink, J., and Bitter, W. (2012). Composition of the type VII secretion system membrane complex. Mol. Microbiol. 86, 472–484. Google Scholar
Humphrey, W., Dalke, A., and Schulten, K. (1996). VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38, 27–28. Google Scholar
Inagakia, S., Ghirlandob, R., and Grisshammer, R. (2014). Biophysical characterization of membrane proteins in nanodiscs. Methods 59, 287–300. Google Scholar
Jones, C.J., Macnab, R.M., Okino, H., and Aizawa, S.I. (1990). Stoichiometric analysis of the flagellar hook-(basal-body) complex of Salmonella typhimurium. J. Mol. Biol. 212, 377–387. Google Scholar
Kimura, S., Laosinchai, W., Itoh, T., Cui, X., Linder, C., and Brown, R. (1999). Immunogold labeling of rosette terminal cellulose-synthesizing complexes in the vascular plant vigna angularis. Plant Cell 11, 2075–2086. Google Scholar
Kito, K. and Ito, T. (2008). Mass spectrometry-based approaches toward absolute quantitative proteomics. Curr. Genomics 9, 263–274. Google Scholar
Kito, K., Ota, K., Fujita, T., and Ito, T. (2007). A synthetic protein approach toward accurate mass spectrometric quantification of component stoichiometry of multiprotein complexes. J. Proteome Res. 6, 792–800. Google Scholar
Kito, K., Mitsuhiro, O., Ishibashi, Y., Okada, S., and Ito, T. (2016). A strategy for absolute proteome quantification with mass spectrometry by hierarchical use of peptide-concatenated standards. Proteomics 16, 1457–1473. Google Scholar
Kosinski, J., Mosalaganti, S., von Appen, A., Teimer, R., Diguilio, A.L., Wan, W., Bui, K.H., Hagen, W.J., Briggs, J.A., Glavy, J.S., et al. (2016). Molecular architecture of the inner ring scaffold of the human nuclear pore complex. Science 352, 363–365. Google Scholar
Klara, S.S., Saboe, P.O., Sines, I.T., Babaei, M., Chiu, P.L., Dezorzi, R., Dayal, K., Walz, T., Kumar, M., and Mauter, M.S. (2016). Magnetically directed two-dimensional crystallization of ompf membrane proteins in block copolymers. J. Am. Chem. Soc. 138, 28–31. Google Scholar
Krall, L., Wiedemann, U., Unsin, G., Weiss, S., Domke, N., and Baron, C. (2002). Detergent extraction identifies different VirB protein subassemblies of the type IV secretion machinery in the membranes of Agrobacterium tumefaciens. Proc. Natl. Acad Sci. USA 99, 11405–11410. Google Scholar
Kuroda, T., Kubori, T., Thanh Bui, X., Hyakutake, A., Uchida, Y., Imada, K., and Nagai, H. (2015). Molecular and structural analysis of Legionella DotI gives insights into an inner membrane complex essential for type IV secretion. Sci Rep 5, 10912. Google Scholar
Laganowsky, A., Reading, E., Hopper, J.T.S., and Robinson, C.V. (2014). Mass spectrometry of intact membrane protein complexes. Nat. Protoc. 8, 639–651. Google Scholar
Lau, W.C.Y. and Rubinstein, J.L. (2010). Structure of intact Thermus thermophilus V-ATPase by cryo-EM reveals organization of the membrane-bound V(O) motor. Proc. Natl. Acad Sci. USA 107, 1367–72. Google Scholar
Lau, W.C.Y. and Rubinstein, J.L. (2011). Subnanometre-resolution structure of the intact Thermus thermophilus H+-driven ATP synthase. Nature 481, 214–218. Google Scholar
Leake, M.C., Chandler, J.H., Wadhams, G.H., Bai, F., Berry, R.M., and Armitage, J.P. (2006). Stoichiometry and turnover in single, functioning membrane protein complexes. Nature 443, 355–358. Google Scholar
Leake, M.C., Greene, N.P., Godun, R.M., Granjon, T., Buchanan, G., Chen, S., Berry, R.M., Palmer, T., and Berks, B.C. (2008). Variable stoichiometry of the TatA component of the twin-arginine protein transport system observed by in vivo single-molecule imaging. Proc. Natl. Acad Sci. USA 105, 15376–15381. Google Scholar
Lee, L.K., Stewart, A.G., Donohoe, M., Bernal, R.A., and Stock, D. (2010). The structure of the peripheral stalk of Thermus thermophilus H+-ATPase/synthase. Nat. Struct. Mol. Biol. 17, 373–378. Google Scholar
Lin, D.H., Stuwe, T., Schilbach, S., Rundlet, E.J., Perriches, T., Mobbs, G., Fan, Y., Thierbach, K., Huber, F.M., Collins, L.N., et al. (2016). Architecture of the symmetric core of the nuclear pore. Science 352, aaf1015–aaf1015. Google Scholar
McDonough, A.A., Veiras, L.C., Minas, J.N., and Ralph, D.L. (2014). Considerations when quantitating protein abundance by immunoblot. Am. J. Physiol. Cell Physiol. 308, C426–C433. Google Scholar
Morimoto, Y.V., Ito, M., Hiraoka, K.D., Che, Y., Bai, F., Kami-ike, N., Namba, K., and Minamino, T. (2014). Assembly and stoichiometry of FliF and FlhA in Salmonella flagellar basal body. Mol. Microbiol. 91, 1214–1226. Google Scholar
Nanavati, D., Gucek, M., Milne, J.L.S., Subramaniam, S., and Markey, S.P. (2008). Stoichiometry and absolute quantification of proteins with mass spectrometry using fluorescent and isotope-labeled concatenated peptide standards. Mol. Cell Proteomics 7, 442–447. Google Scholar
Olinares, P.D.B., Kim, J., Davis, J.I., and Van Wijk, K.J. (2011). Subunit stoichiometry, evolution, and functional implications of an asymmetric plant plastid ClpP/R protease complex in Arabidopsis. Plant Cell 23, 2348–2361. Google Scholar
Ong, S.-E. (2002). Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell Proteomics 1, 376–386. Google Scholar
Pratt, J.M., Simpson, D.M., Doherty, M.K., Rivers, J., Gaskell, S.J., and Beynon, R.J. (2006). Multiplexed absolute quantification for proteomics using concatenated signature peptides encoded by QconCAT genes. Nat. Protoc. 1, 1029–1043. Google Scholar
Radics, J., Königsmaier, L., and Marlovits, T.C. (2013). Structure of a pathogenic type 3 secretion system in action. Nat. Struct. Mol. Biol. 21, 82–87. Google Scholar
Reading, E., Liko, I., Allison, T.M., Benesch, J.L.P., Laganowsky, A., and Robinson, C. V. (2015). The role of the detergent micelle in preserving the structure of membrane proteins in the gas phase. Angew. Chem. Int. Ed. 54, 4577–4581. Google Scholar
Romano, F.B., Tang, Y., Rossi, K.C., Monopoli, K.R., Ross, J.L., and Heuck, A.P. (2016). Type 3 Secretion translocators spontaneously assemble a hexadecameric transmembrane complex. J. Biol. Chem. 291, 6304–6315. Google Scholar
Rout, M.P., Aitchison, J.D., Suprapto, A., Hjertaas, K., Zhao, Y., and Chait, B.T. (2000). The yeast nuclear pore complex: composition, architecture, and transport mechanism. J. Cell Biol. 148, 635–651. Google Scholar
Salvay, A.G., Santamaria, M., Le Maire, M., and Ebel, C. (2007). Analytical ultracentrifugation sedimentation velocity for the characterization of detergent-solubilized membrane proteins Ca ++-ATPase and ExbB. J. Biol. Phys. 33, 399–419. Google Scholar
Schägger, H., and von Jagow, G. (1991). Blue native electrophoresis for isolation of membrane protein complexes in enzymatically active form. Anal. Biochem. 199, 223–231. Google Scholar
Schlegel, S., Hjelm, A., Baumgarten, T., Vikström, D., and De Gier, J. (2014). Bacterial-based membrane protein production. Biochim. Biophys. Acta Mol. Cell Res. 1843, 1739–1749. Google Scholar
Schmidt, C., Lenz, C., Grote, M., Luhrmann, R., and Urlaub, H. (2010). Determination of protein stoichiometry within protein complexes using absolute quantification and multiple reaction monitoring. Anal. Chem. 82, 2784–2796. Google Scholar
Schraidt, O. and Marlovits, T.C. (2011). Three-dimensional model of Salmonella’s needle complex at subnanometer resolution. Science 331, 1192–1195. Google Scholar
Shahid, S.A., Bardiaux, B., Franks, W.T., Krabben, L., Habeck, M., van Rossum, B.J., and Linke, D. (2012). Membrane-protein structure determination by solid-state NMR spectroscopy of microcrystals. Nat. Methods 9, 1212–1217. Google Scholar
Slotboom, D.J., Duurkens, R.H., Olieman, K., and Erkens, G.B. (2008). Static light scattering to characterize membrane proteins in detergent solution. Methods 46, 73–82. Google Scholar
Stenberg, F., Chovanec, P., Maslen, S.L., Robinson, C. V., Ilag, L.L., Von Heijne, G., and Daley, D.O. (2005). Protein complexes of the Escherichia coli cell envelope. J. Biol. Chem. 280, 34409–34419. Google Scholar
Stuwe, T., Correia, A.R., Lin, D.H., Paduch, M., Lu, V.T., and Kossiakoff, A.A. (2015). Architecture of the nuclear pore complex coat. Science 347, 1148–1152. Google Scholar
Ulbrich, M.H. and Isacoff, E.Y. (2007). Subunit counting in membrane-bound proteins. Nat. Methods 4, 319–321. Google Scholar
von Appen, A., Kosinski, J., Sparks, L., Ori, A., DiGuilio, A.L., Vollmer, B., Mackmull, M.-T., Banterle, N., Parca, L., Kastritis, P., et al. (2015). In situ structural analysis of the human nuclear pore complex. Nature 526, 140–143. Google Scholar
Wagner, S., Königsmaier, L., Lara-tejero, M., Lefebre, M., Marlovits, T.C., and Galán, J.E. (2010). Organization and coordinated assembly of the type III secretion export apparatus. Proc. Natl. Acad Sci. USA 107, 17745–17750. Google Scholar
Ward, M.E., Wang, S., Krishnamurthy, S., Hutchins, H., Fey, M., Brown, L.S., and Ladizhansky, V. (2014). High-resolution paramagnetically enhanced solid-state NMR spectroscopy of membrane proteins at fast magic angle spinning. J. Biomol NMR 58, 37–47. Google Scholar
Weiland, F., Zammit, C.M., Reith, F., and Hoffmann, P. (2014). High resolution two-dimensional electrophoresis of native proteins. Electrophoresis 35, 1893–1902. Google Scholar
Whitelegge, J.P. (2013). Integral membrane proteins and bilayer proteomics. Anal. Chem. 85, 2558–68. Google Scholar
Wisedchaisri, G., Reichow, S.L., and Gonen, T. (2011). Advances in structural and functional analysis of membrane proteins by electron crystallography. Structure 19, 1381–1393. Google Scholar
Wittig, I., Braun, H., and Scha, H. (2006). Blue native PAGE. Nat. Protoc. 1, 418–428. Google Scholar
Wohlgemuth, I., Lenz, C., and Urlaub, H. (2015). Studying macromolecular complex stoichiometries by peptide-based mass spectrometry. Proteomics 15, 862–879. Google Scholar
Worrall, L.J., Vuckovic, M., and Strynadka, N.C.J. (2010). Crystal structure of the C-terminal domain of the Salmonella type III secretion system export apparatus protein InvA. Protein Sci. 19, 1091–1096. Google Scholar
Zhao, H., Brautigam, C.A., Ghirlando, R., and Schuck, P. (2013). Overview of current methods in sedimentation velocity and sedimentation equili brium analytical ultracentrifugation. Curr. Protoc. Protein Sci. 71, 1–52. Google Scholar
Zhou, M., Morgner, N., Barrera, N.P., Politis, A., and Shoshanna, C. (2011). Mass spectrometry of intact V-type ATPases reveals bound lipids and the effects of nucleotide binding. Science 334, 380–385. Google Scholar
Zilkenat, S., Franz-Wachtel, M., Stierhof, Y.-D., Galán, J.E., Macek, B., and Wagner, S. (2016). Determination of the stoichiometry of the complete bacterial type III secretion needle complex using a combined quantitative proteomic approach. Mol. Cell Proteomics 15, 1598–1609. Google Scholar
About the article
Published Online: 2016-09-23
Published in Print: 2017-02-01