1. Biochemistry and Chemical Biology
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A non-linear system patterns Rab5 GTPase on the membrane

  1. Alice Cezanne
  2. Janelle Lauer
  3. Anastasia Solomatina
  4. Ivo F Sbalzarini
  5. Marino Zerial  Is a corresponding author
  1. Max-Planck Institute of Molecular Cell Biology and Genetics, Germany
  2. Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, Germany
  3. MOSAIC Group, Center for Systems Biology Dresden, Germany
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Cite this article as: eLife 2020;9:e54434 doi: 10.7554/eLife.54434

Abstract

Proteins can self-organize into spatial patterns via non-linear dynamic interactions on cellular membranes. Modelling and simulations have shown that small GTPases can generate patterns by coupling guanine nucleotide exchange factors (GEF) to effectors, generating a positive feedback of GTPase activation and membrane recruitment. Here, we reconstituted the patterning of the small GTPase Rab5 and its GEF/effector complex Rabex5/Rabaptin5 on supported lipid bilayers. We demonstrate a ‘handover’ of Rab5 from Rabex5 to Rabaptin5 upon nucleotide exchange. A minimal system consisting of Rab5, RabGDI and a complex of full length Rabex5/Rabaptin5 was necessary to pattern Rab5 into membrane domains. Rab5 patterning required a lipid membrane composition mimicking that of early endosomes, with PI(3)P enhancing membrane recruitment of Rab5 and acyl chain packing being critical for domain formation. The prevalence of GEF/effector coupling in nature suggests a possible universal system for small GTPase patterning involving both protein and lipid interactions.

Introduction

Membrane compartmentalization is of central importance for a variety of biological functions at multiple scales, from sub-cellular structures to multi-cellular organisms. Processes such as cell polarization, protein and lipid sorting within sub-cellular organelles or cell and tissue morphogenesis depend on the emergence of patterns (Turing, 1952; Halatek et al., 2018). In Caenorhabditis elegans, symmetry breaking of the plasma membrane is caused by PAR proteins that sort into distinct anterior and posterior cortical domains and generate cell polarity (Kemphues et al., 1988; Motegi and Seydoux, 2013). In budding yeast, the site of bud formation is marked by a single, discrete domain of Cdc42 on the plasma membrane (PM) (Ziman et al., 1993; Chen et al., 1997; Leberer et al., 1997). In xylem cells, ROP11 is organized into multiple domains on the PM where it interacts with cortical microtubules to regulate cell wall architecture (Yang and Lavagi, 2012; Oda and Fukuda, 2012). Membrane compartmentalization is not limited to the plasma membrane but occurs also on cytoplasmic organelles. On early endosomes (EE), Rab5 exists in domains where it regulates vesicle tethering and fusion (McBride et al., 1999; Sönnichsen et al., 2000; Franke et al., 2019).

Cdc42, ROP11 and Rab5 are small GTPases, a class of molecules that play an important role in symmetry breaking and membrane compartmentalization. Small GTPases use GTP/GDP binding to act as an ON/OFF switch. The cycling between GTP and GDP-bound states is regulated by guanine nucleotide exchange factors (GEFs) and GTPase activating proteins (GAPs) (Bos et al., 2007; Cherfils and Zeghouf, 2013). Most small GTPases are post-translationally modified by lipid chains which allow them to associate with membranes (Wang and Casey, 2016). The inactive GTPase forms a high-affinity complex with guanine dissociation inhibitor (GDI), regulating membrane cycling (Sasaki et al., 1990; Ghomashchi et al., 1995; Cherfils and Zeghouf, 2013). Nucleotide exchange to GTP or a GTP analogue prevents interaction with GDI and frees the GTPase to interact with the membrane, where it can recruit effector proteins and mediate downstream activities (Wu et al., 2010; Langemeyer et al., 2018). Upon hydrolysis of GTP to GDP the GTPase is once again available for extraction from the membrane by GDI (Rak et al., 2004; Ghomashchi et al., 1995; Pylypenko et al., 2006).

It has been proposed that small GTPase patterning can arise from the coupling of GEF activity and effector binding (Horiuchi et al., 1997; Zerial and McBride, 2001). In this way, an active GTPase can recruit its own GEF, creating a local, positive feedback loop of GTPase activation and membrane recruitment. In general, self-organizing systems that form spatial patterns on membranes often exhibit such non-linear dynamics of membrane recruitment and activation (Halatek et al., 2018). The prevalence of GEF/effector coupling in small GTPase systems suggests that this may be a general mechanism for symmetry breaking and spatial organization of GTPases (Goryachev and Leda, 2019). The Rab5 GEF, Rabex5 is found in complex with the Rab5 effector Rabaptin5. (Horiuchi et al., 1997). Similarly, the Cdc42 GEF Cdc24 is coupled to the effector Bem1 (Chenevert et al., 1992). Computational modelling revealed a Turing-type mechanism of pattern formation by a minimal system composed of Cdc42, the Bem1/Cdc24 complex and GDI (Goryachev and Pokhilko, 2008; Goryachev and Leda, 2017). In plants, the ROP11 GEF, ROPGEF4, forms a dimer that catalyzes nucleotide exchange but also interacts with the active ROP11 (Nagashima et al., 2018). We focus on Rab5, its GEF/effector complex Rabex5/Rabaptin5, and RabGDI (hereafter referred to as GDI) in order to investigate general mechanisms for the spatial organization of peripheral membrane proteins.

Rabex5/Rabaptin5 is one of the best characterized GEF/effector complexes in eukaryotes. Rabex5 is a 57 kDa Vps9 domain containing GEF for Rab5 (Horiuchi et al., 1997; Delprato and Lambright, 2007; Lauer et al., 2019). Rabaptin5 is a 99 kDa protein with multiple protein-protein interaction sites that colocalizes with Rab5 on EE and is essential for endosome fusion (Stenmark et al., 1995; Horiuchi et al., 1997). As Rabaptin5 forms a dimer in solution, the complex is a tetramer of two Rabaptin5 and two Rabex5 subunits (Lauer et al., 2019). The interaction with Rabaptin5 has been shown to increase Rabex5 GEF activity and produce structural rearrangements in Rabex5 (Delprato et al., 2004; Delprato and Lambright, 2007; Lippé et al., 2001; Horiuchi et al., 1997; Zhang et al., 2014; Lauer et al., 2019). By binding active Rab5, Rabaptin5 localizes the enhanced GEF activity of Rabex5 in the vicinity of active Rab5, thereby creating the positive feedback loop. In addition, Rabex5 can be recruited to EE via binding to Ubiquitin via two distinct Ubiquitin binding domains near the N-terminus (Penengo et al., 2006). Interestingly, Ubiquitin binding enhances GEF activity toward Rab5 helping to initiate the positive feedback loop on endosomes carrying ubiquitinated cargo (Lauer et al., 2019). Blümer et al., 2013 observed that artificially targeting Rabex5 to mitochondria resulted in Rab5 recruitment to these organelles, suggesting that Rabex5 can be sufficient for localizing Rab5 to a membrane compartment. Rab5 associates with the membrane by two 20-carbon geranylgeranyl chains attached at the C-terminus of the protein (Farnsworth et al., 1994). Molecular dynamics simulations showed that both cholesterol and PI(3)P accumulate in the vicinity of Rab5, and predicted a direct interaction with PI(3)P mediated by an Arg located in the flexible hypervariable region (HVR) between the C-terminal lipidation and the conserved GTPase domain (Edler et al., 2017a).

Elucidating the precise mechanisms of self-organization of peripheral membrane proteins is critical to understanding endomembrane identity and functionality. We hypothesize that, similar to what has been observed for Cdc42 in silico, Rab5, Rabex5/Rabaptin5 and GDI comprise a minimal system that is capable of spatially organizing Rab5. We made use of in vitro reconstitution to test this hypothesis and elucidate the contributions of individual components to membrane association and organization. Our biochemical reconstitution system allowed for in-depth study of the biochemical interactions underlying the self-organization of Rab5 and its interacting molecules on the membrane.

Results

Upon GDP/GTP exchange Rab5 is directly transferred from Rabex5 to Rabaptin5 - a mechanistic basis for positive feedback of Rab5 activation

To directly test the positive feedback loop model, we investigated the structural rearrangements occurring in Rab5 and Rabex5/Rabaptin5 in the course of nucleotide exchange by Hydrogen Deuterium Exchange Mass Spectrometry (HDX-MS). Rabex5/Rabaptin5 was first premixed with Rab5:GDP and the resulting ternary complex diluted into deuterated buffer in the absence (Figure 1A top) or presence (Figure 1A bottom) of GTPγS and incubated for 1, 5 and 15 min. In this way, we could monitor structural rearrangement occurring in the early stages of the nucleotide exchange reaction. Focusing first on Rab5, we could see evidence of nucleotide exchange from the dramatic stabilization of Val24-Leu38, Leu130-Leu137 and Met160-Met168, encompassing the P-loop and parts of β 5, α4 and β 6 (Figure 1B and Figure 1—figure supplement 1A: dark blue), which, together, make up most of the direct interaction sites with GTP. In addition, we saw stabilization of Gln60-Phe71, parts of β 2 and β 3 (sky blue and pale green), consistent with the binding of Rabaptin5 (Zhu et al., 2004). Indication of binding to Rabaptin5 was observed after only 1 min of reaction, thus providing evidence of a direct hand-off of active Rab5 from the Rabex5 catalytic domain to Rabaptin5 (See Figure 1C). Interestingly, we also saw a destabilization of Ile177-Asp200, α5 (yellow), suggesting a structural rearrangement of the C-terminal HVR. Figure 1D shows the alterations in deuterium exchange for Rabaptin5 (See also Figure 1—figure supplement 1B). Since there is no available structural model for Rabaptin5 the data are represented as a graph in which each peptide showing statistically significant alterations in deuterium uptake is assigned a value for the percent alteration. We saw stabilization in both of the regions known to bind Rab5, thus providing further evidence of Rab5 binding to Rabaptin5 after the nucleotide exchange reaction. This provides a putative structural mechanism for positive feedback loop formation and the need to couple GEF and effector activities. Next, we set out to test the hypothesis that such positive feedback is sufficient to induce the recruitment and localized accumulation of membrane-bound Rab5.

Figure 1 with 1 supplement see all
Rab5 backbone dynamics during nucleotide exchange.

(A) Scheme of reaction. The ternary complex (Rab5/Rabex5/Rabaptin5) was incubated in D2O for 1, 5 or 15 min in the presence or absence of GTPγS. (B) Crystal structure of Rab5:GTP (PDBID: 3MJH) pseudocolored to show differential uptake of ternary complex (Rab5/Rabex5/Rabaptin5)±GTPγS (average of 1 min, 5 min and 15 min timepoints). The Mg2+ ion is shown as a sphere (magenta) and GTPγS as a line structure. Color scheme: regions that are protected from exchange, i.e. stabilization, are colored with cool colors; regions with enhanced exchange with warm colors; regions with no statistically different uptake are colored in grey; and regions with no peptide coverage are white. (C) Deuterium incorporation over time in Rab5 β2 (aa 58–63, colored blue in B), in the ternary complex (Rab5/Rabex5/Rabaptin5)±GTPγS (n = 3) (D) Differential deuterium incorporation in Rabaptin5 during the nucleotide exchange reaction. Two areas of protection (decrease in deuterium uptake) correspond with the Rab5 binding sites.

Reconstituting Rab5 domain formation in vitro

To reconstitute Rab5 membrane recruitment and organization, we developed an in vitro system consisting of recombinant proteins and synthetic membranes. The lipid composition of the synthetic membrane was chosen based on the lipid composition of an enriched early endosomal fraction determined in a previous study (Perini, 2012). Briefly, an enriched early endosomal fraction was prepared as described (Horiuchi et al., 1997). Lipid extracts of this fraction were prepared in a final solution of CHCl3:MeOH (1:2), as described by Kalvodova et al., 2009. The lipid extracts were then subjected to quantitative lipid analysis as described by Sampaio et al., 2011. The results are broadly in agreement with previous studies investigating the lipid composition of the plasma membrane which is known to be similar to that of the early endosome (Casares et al., 2019). Lipids constituting over 1 mol% of this lipid composition were utilized (EE, See Table 1). In order to test a wide number of experimental conditions, we designed the following workflow: small unilamellar vesicles with the EE-like lipid composition (EE-SUV) were deposited onto silica beads of 10 µm in diameter to form membrane-coated beads (EE-MCB). EE-MCBs were incubated with recombinant proteins, some of which were fluorescently tagged allowing us to monitor protein recruitment and spatial organization using confocal microscopy. EE-MCBs were segmented and visualized as Mollweide map projections. For visualization, the EE-MCBs are presented as equatorial slices in GFP/RFP and DiD channels, and the reconstructed bead surface as a Mollweide map projection of the GFP/RFP signal (Mollweide map projections of the DiD signal can be found in the corresponding supplementary figures).

Table 1
Lipid compositions used in this study.
EE-MCB (mol%)PC/PS/CH/PI(3)P/SM-MCB (mol%)PC/PS/CH/PI(3)P/PlasmPE-MCB (mol%)PC/PS/CH-MCB (mol%)PC/PS-MCB (mol%)
Cholesterol32.232.232.232.2-
DOPC16.6/15.639.138.851.784.9/83.9
Ethanolamine plasmalogen12.9-12.9--
Sphingomyelin12.612.6---
GM39----
DOPS6.115151515
DOPE6.8----
Choline plasmalogen3.6----
PI(3)P0/1110/10/1
DiD0.10.10.10.10.1

EE-MCBs incubated with 10 nM GFP-Rab5/GDI showed membrane recruitment of GFP-Rab5 with a random distribution (see Figure 2A and Figure 2—figure supplement 1A). The addition of GDI and Rabex5/Rabaptin5-RFP in the presence GDP removed GFP-Rab5 from the membrane (see Figure 2B and Figure 2—figure supplement 1B). However, the same reaction in the presence of GTP produced a striking redistribution of GFP-Rab5 on the membrane into discrete clusters or domains (see Figure 2C, and Figure 2—figure supplement 1C and Figure 2—Video 1). GDI was provided in excess to allow for efficient flux of Rab5 between the membrane and soluble fraction and, although catalytically active at much lower GTPase:GEF ratios, Rabex5/Rabaptin5 was provided in excess in order to allow for efficient binding between Rab5:GTP and Rabaptin5. Interestingly, the formation of GFP-Rab5 domains required GDI in a concentration-dependent manner (see Figure 2D–F and Figure 2—figure supplement 1D-F). GFP-Rab5 domains were segmented using Squassh (Rizk et al., 2014) on the surface of the bead (see Figure 2—figure supplement 1G), and the segmented structures were then characterized in terms of size and fluorescence intensity. Table 2 summarizes the characteristics of GFP-Rab5 domains from experiments shown in Figure 2. Domains with a mean diameter of 1.32 µm were detected on MCBs incubated with GFP-Rab5/GDI, GDI, Rabex5/Rabaptin5, and GTP but not GDP. They formed with a characteristic density of ~4.7 domains/EE-MCB and were rarely found adjacent to one another. A critical hallmark of the reconstituted domains is a marked increase in GFP-Rab5 signal within the segmented domain as compared to the area outside (See Figure 2G). Comparison between GFP-Rab5 and DiD signals revealed that the occasional apparent clusters of GFP-Rab5 in the absence of other factors (see Figure 2A and Figure 2—figure supplement 1A) were due to membrane inhomogeneity characterized by lower DiD signal, unlike GFP-Rab5 domains.

Figure 2 with 3 supplements see all
Rab5 domains can be reconstituted in vitro.

EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI A) and supplemented with 1 μM GDI, 100 nM Rabex5/Rabaptin5-RFP and 1 mM GDP (B) or GTP (C). (D–F) GDI is necessary for Rab5 domain formation. EE MCBs were incubated with 10 nM GFP-Rab5/GDI complex, 100 nM Rabex5/Rabaptin5 1 mM GTP and 0 nM (D), 100 nM (E) or 500 nM (F) GDI. Beads are presented as equatorial slices in GFP and DiD channels (left) and a Mollweide projection of the GFP channel (right). Scale Bar = 10 µm. (G) Mean GFP-Rab5 signal intensity outside of and within segmented domains in C) (See also Table 2) (p=<0.0001) (H) EE MCBs were at 23 °C with 10 nM GFP-Rab5/GDI 1 μM GDI, 100 nM Rabex5/Rabaptin5 and 1 mM GTP and imaged in 1 min intervals for a total of 15 min. Graph presents mean GFP-Rab5 signal intensity outside of and within segmented domains over time (n = 63).). (I) EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI 1 μM GDI, 100 nM Rabex5/Rabaptin5 and 1 mM GTP (panel 1; ‚t = 0‘) then bleached (panel 2; ‚FRAP‘) and imaged in 1 min intervals for a total of 15 min. Shown here are stills from Figure 2—Video 2 (panels 1–3) and average intensity within segmented domains over time (panel 4; n = 27).

Table 2
Rab5 domains can be reconstituted in vitro.

EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI and supplemented with 1 μM GDI, 100 nM Rabex5/Rabaptin5-RFP and 1 mM GDP or GTP.

10 nM GFP-Rab5/GDI10 nM GFP-Rab5/GDI,
100 nM Rabex5/Rabaptin5,
1 µM GDI, 1 mM GDP
10 nM GFP-Rab5/GDI,
100 nM Rabex5/Rabaptin5,
1 µM GDI, 1 mM GTP
# Domains00449
# Beads304496
Mean # Domains/Bead004.7
Mean intensity/Bead (a.u.)212.31 ± 67.04128.40 ± 4.91447.96 ± 403.41
Mean Standard Deviation/Bead46.70 ± 21.260.36 ± 0.04237.24 ± 225.54
Mean Intensity/Domain--1326.95 ± 1026.96
Mean Intensity/Outside212.31 ± 67.04128.40 ± 4.91454.63 ± 364.79
Mean domain area, µm2--1.741.00+4.74
Mean domain diameter, µm--1.32

In order to understand how these domains form, we monitored EE-MCBs over time (See Figure 2H, Figure 2—Video 2). Domains appear to be nucleated within the first minute of the reaction (which we could not capture due to the imaging setup) and then grow linearly in intensity until ~5 min after initiation of the reaction. After this point individual domains increase in GFP-Rab5 signal intensity slowly or not at all, suggesting that some domains reach saturation. Interestingly, when whole MCBs were bleached domains recovered in the same locations after photobleaching indicating that there is a constant exchange of GFP-Rab5 with solution (See Figure 2I, Figure 2—Video 2).

Rabex5/Rabaptin5 is essential for Rab5 domain formation in vitro

In order to understand the mechanisms by which Rab5 domains form, we dissected the contribution of each component of our reconstituted system. GDI delivers and extracts Rab5, as seen in Figure 2, and is essential for domain formation. We observed that, similar to GDI, Rab5 domain formation requires Rabex5/Rabaptin5 in a concentration-dependent manner (see Figure 3A–E, Figure 3—figure supplement 1A-E and Table 3, which summarizes the conditions shown in Figure 3A,B & C).

Figure 3 with 1 supplement see all
Rabex5/Rabaptin5 is essential for Rab5 domain formation in vitro.

(A - E) Domain formation is dependent on concentration of Rabex5/Rabaptin5. EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI, 1 μM GDI, 1 mM GTP and 0 nM (A), 50 nM (B), 100 nM (C), or 500 nM (D) Rabex5/Rabaptin5-RFP. (E) Mean GFP-Rab5 signal intensity outside of and within segmented domains as a function of Rabex5/Rabaptin5 concentration (50 nM Rabex5/Rabaptin5 p=0.001, n = 95; 100 nM Rabex5/Rabaptin5 p=<0.0001) See also Table 3) (F – J) Rabex5/Rabaptin5 cannot be split into component parts and still form domains. EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI, 1 μM GDI, 1 mM GTP and 100 nM Rabex (F), 100 nM RabexCAT (G), 100 nM Rabaptin5 (H), 100 nM Rabex5CAT and Rabaptin5 (I), or 100 nM Rabex5/Rabaptin5 (J). Beads are presented as equatorial slices in GFP and DiD channels (left) and a Mollweide projection of the GFP channel (right). Scale Bar = 10 µm.

Table 3
Domain formation is dependent on concentration of Rabex5/Rabaptin5.

EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI, 1 μM GDI, 1 mM GTP and 0 nM, 50 nM, 100 nM Rabex5/Rabaptin5-RFP. Beads incubated with 10 nM GFP-Rab5/GDI, 1 μM GDI, 1 mM GTP and 500 nM Rabex5/Rabaptin5-RFP could not be properly segmented due to the high GFP-Rab5 signal on the bead (See Figure 3D).

10 nM GFP-Rab5/GDI, 1 µM GDI, 1 mM GTP10 nM GFP-Rab5/GDI, 50 nM Rabex5/Rabaptin5,
1 µM GDI, 1 mM GTP
10 nM GFP-Rab5/GDI, 100 nM Rabex5/Rabaptin5,
1 µM GDI, 1 mM GTP
# Domains09690
# Beads172316
Mean # Domains/Bead04.175.63
Mean intensity/Bead (a.u.)132.95 ± 6.23164.66 ± 24.13946.76 ± 669.27
Mean Standard Deviation/Bead13.14 ± 2.6841.63 ± 17.87526.77 ± 332.23
Mean Intensity/Domain-282.58 ± 96.682767.14 ± 1039.34
Mean Intensity/Outside132.95 ± 6.23159.56 ± 18.33856.22 ± 573.11
Mean domain area, µm2-1.710.95+3.361.971.26+6.22
Mean domain diameter, µm-1.311.40

Next, we verified that the Rabex5/Rabaptin5 complex indeed localizes to the Rab5 domain. For this, we used a fluorescent Rabex5/Rabaptin5-RFP complex and observed both enrichment of Rabaptin5-RFP signal inside the domain (See Figure 4A) and colocalization with GFP-Rab5 (See Figure 4B). Rabex5/Rabaptin5-RFP also showed some degree of membrane association in the absence of other factors (See Figure 3—figure supplement 1F), however this was significantly lower than the signal observed inside the GFP-Rab5 domains.

Rabex5/Rabaptin5 localises to the reconstituted Rab5 domain.

EE MCBs were incubated for 15 min at 23 °C with 10 nM GFP-Rab5/GDI, 1 μM GDI, 1 mM GTP and 50 nM or 100 nM Rabex5/Rabaptin5-RFP (See Figure 3A–E). (A) Rabaptin5-RFP signal is enriched in domains. (50 nM Rabaex5/Rabaptin5 p=0.001, n = 96; 100 nM Rabex5/Rabaptin5 p=0.0017, n = 90). Corresponding GFP enrichment in presented in Figure 3E. (B) Equatorial slices and mollweide representations of GFP signal (top), RFP signal (bottom) and pixelwise GFP-RFP colocalization (bottom). Beads are presented as equatorial slices (left) and Mollweide projections (right). Scale Bar = 10 µm.

We next wanted to investigate whether the full Rabex5/Rabaptin5 complex was necessary for domain formation (Figure 3F–J and Figure 3—figure supplement 1G-K). In the presence of Rab5, GDI and GTP, neither full-length Rabex5 nor the Rabex5 catalytic domain (Rabex5CAT) alone were sufficient to form domains (Figure 3F,G). Similarly, Rabaptin5 alone was not capable of forming domains (Figure 3H). Unlike the full length Rabex5/Rabaptin5 complex, Rabex5CAT plus full-length Rabaptin5 did not support Rab5 domain formation (compare Figure 3J and I). This suggests that direct coupling of GEF activity and effector binding is essential for Rab5 domain formation.

Finally, we quantified the domain size distribution as a function of concentration of the components in the reaction. Interestingly, neither the domain diameter nor the area differed significantly when decreasing Rabex5/Rabaptin5 concentration, but the mean intensity of domains decreased with decreasing concentration of Rabex5/Rabaptin5 (See Figure 3E and Table 3).

Rab5 domain formation is influenced by membrane composition

In addition to protein-protein interactions, protein-lipid and lipid-lipid interactions also play a role in Rab5 domain formation. The above experiments (Figures 2 and 3) were all conducted with the EE lipid composition containing 1 mol% PI(3)P. The rearrangements in Rab5 during nucleotide exchange reveal a destabilization of α5 that may alter membrane contacts or orientation of the protein with respect to the membrane in the GDP- vs GTP-bound conformation (See Figure 1B). Previous work using molecular dynamics simulations suggested an interaction between the Rab5 HVR and PI(3)P as well as cholesterol (Edler and Stein, 2017b). To investigate the contribution of lipids, specifically PI(3)P and cholesterol, to GFP-Rab5 domain formation, EE-MCBs as well as MCBs with a simple PC/PS lipid composition were made with either 1 mol% or 0 mol% PI(3)P (PC/PS-MCB; See Table 1). Geranylgeranylated GFP-Rab5 was recruited similarly to EE-MCBs and PC/PS-MCBs that included 1 mol% PI(3)P (see Figure 5A,B E and Figure 5—figure supplement 1A B). However, recruitment of GFP-Rab5 to both membranes lacking PI(3)P was greatly diminished (see Figure 5C–E and Figure 5—figure supplement 1C D). This suggests that the presence of PI(3)P enhances Rab5 recruitment, either by facilitating the dissociation of Rab5 from GDI or by inhibiting the extraction of Rab5 by GDI. The presence of cholesterol (CH) appeared to also improve Rab5 recruitment to the simple lipid composition, although to a lesser degree than PI(3)P (See Figure 5F; PC/PS/CH-MCB vs PC/PS-MCB, See Table 1). Similar investigation of the contribution of cholesterol in the EE-like lipid composition was not possible in this system as membrane integrity was greatly compromised without cholesterol (data not shown).

Figure 5 with 1 supplement see all
Recruitment of geranylgeranylated GFP-Rab5 to EE and PC/PS bilayers is enhanced by PI(3)P.

MCBs with PC/PS and EE lipid composition containing 1 mol% PI(3)P (A) and B) respectively) and MCBs with PC/PS and EE lipid composition containing 0 mol% PI(3)P (C) and D) respectively) were incubated with 10 nM GFP-Rab5/GDI for 15 min at 23 °C. Beads are presented as equatorial slices in GFP and DiD channels (left) and Mollweide projection of the GFP channel (right). Scale Bar = 10 µm. (E) Mean equatorial GFP signal intensity in A–D). (p=<0.0001; n = 20) (F) MCBs with PC/PS and PC/PS/CH lipid composition (0 mol% PI(3)P) incubated with 10 nM GFP-Rab5/GDI for 15 min at 23 °C. Graph presents mean equatorial GFP signal intensity (p=0.005; n = 25). For both E) and F) GFP signal intensity is normalized to DiD signal intensity, however the same pattern can be seen in the raw intensity values.

In order to determine whether these interactions have an effect on domain formation, the same MCBs were incubated with Rab5/GDI, Rabex5/Rabaptin5, GDI and GTP. Strikingly, domain formation was most efficient on EE-MCBs with 1 mol% PI(3)P, less efficient on EE-MCBs with 0 mol% PI(3)P and completely abolished on PC/PS membranes regardless of PI(3)P content (see Figure 6, Figure 6—figure supplement 1 and Table 4 which summarizes the conditions shown in Figure 6). Domains formed on EE membranes in the absence of PI(3)P had a drastically reduced mean domain intensity (508.32 ± 143.37) compared to domains formed in the presence of PI(3)P (mean domain intensity 1269.32 ± 556.54) (See Figure 6E). Importantly, the membrane association of Rabex5/Rabaptin5-RFP was not found to be similarly lipid composition-dependent (See Figure 3—figure supplement 1F).

Figure 6 with 1 supplement see all
Rab5 domain formation in vitro is influenced by membrane composition.

MCBs with PC/PS and EE lipid composition containing 1 mol% PI(3)P (A) and B) respectively) and MCBs with PC/PS and EE lipid composition containing 0 mol% PI(3)P (C) and D) respectively) were incubated with 10 nM GFP-Rab5/GDI, 1 μM GDI, 100 nM Rabex5/Rabaptin5-RFP and 1 mM GTP for 15 min at 23 °C. Beads are presented as equatorial slices in GFP and DiD channels (left) and Mollweide projection of the GFP channel (right). Scale Bar = 10 µm. (E) Mean GFP-Rab5 signal intensity outside of and within segmented domains in B) and D) (p=<0.0001) (See also Table 2). (F) Mean GFP-Rab5 signal intensity outside of and within segmented domains on MCBs with PC/PS/CH/PlasmPE and PC/PS/CH/SM lipid composition containing 1 mol% PI(3)P (p=<0.0046) (See also Table 5).

Table 4
Rab5 domain formation in vitro is influenced by membrane composition.

MCBs with EE and PC/PS lipid composition containing 1 mol% PI(3)P and MCBs with EE and PC/PS lipid composition containing 0 mol% PI(3)P were incubated with 10 nM GFP-Rab5/GDI, 1 μM GDI, 100 nM Rabex5/Rabaptin5-RFP and 1 mM GTP for 15 min at 23 °C.

PC/PS
(0% PI(3)P)
PC/PS
(1% PI(3)P)
EE
(0% PI(3)P)
EE
(1% PI(3)P)
# Domains0013164
# Beads33382440
Mean # Domains/Bead000.544.1
Mean intensity/Bead (a.u.)135.48 ± 14.69129.54 ± 11.79140.88 ± 39.73429.23 ± 217.66
Mean Standard Deviation/Bead16.69 ± 8.6013.23 ± 6.0226.05 ± 25.50245.40 ± 120.62
Mean Intensity/Domain--508.32 ± 143.371269.32 ± 556.54
Mean Intensity/Outside135.48 ± 14.69129.54 ± 11.79138.59 ± 32.05393.35 ± 194.66
Mean domain area, µm2--2.121.21+4.761.420.73+2.67
Mean domain diameter, µm--1.461.19

To investigate further which components of the EE lipid composition contribute to domain formation, the simple PC/PS lipid composition was sequentially modified to include the three most abundant lipids in the EE lipid composition: cholesterol (32.3 mol%), sphingomyelin (SM; 12.6 mol%) and ethanolamine plasmalogen (PlasmPE; 12.9 mol%) (See Figure 6FTable 5). PI(3)P was included due to the aforementioned effect on Rab5 recruitment. Interestingly, no domain formation could be observed for PC/PS-MCBs while both PC/PS/CH-MCBs and PC/PS/CH/PlasmPE-MCBs showed infrequent and only low-intensity domains compared to EE-MCBs. Only PC/PS/CH/SM-MCBs were able to recapitulate domains with a GFP signal intensity similar to that observed on EE-MCBs, although the prevalence of domains on PC/PS/CH/SM-MCBs was still reduced. Staining EE-MCBs with C-laurdan in the absence of proteins and imaging by confocal microscopy, as described by Dodes Traian et al., 2012 did not reveal the presence of macroscopic pre-existing liquid ordered (LO) domains (data not shown).

Table 5
Acyl chain ordering influences Rab5 domain formation.

MCBs with EE, PC/PS, PC/PS/CH, PC/PS/CH/PlasmPE and PC/PS/CH/SM lipid composition, each containing 1 mol% PI(3)P, were incubated with 10 nM GFP-Rab5/GDI, 1 μM GDI, 100 nM Rabex5/Rabaptin5-RFP and 1 mM GTP for 15 min at 23 °C.

PC/PS
(1% PI(3)P)
PC/PS/CH
(1% PI(3)P)
PC/PS/CH/PlasmPE
(1% PI(3)P)
PC/PS/CH/SM
(1% PI(3)P)
EE
(1% PI(3)P)
# Domains0807887163
# Beads1830212532
Mean # Domains/Bead02.673.713.485.09
Mean intensity/Bead (a.u.)144.70±20.92171.03±64.72181.34±79.51301.41±175.91525.67±181.34
Mean Standard Deviation/Bead18.88±8.4544.18±41.9450.59±35.40146.88±89.56189.43±63.05
Mean Intensity/Domain-303.44±129.53381.67±178.58743.88±400.00830.66±323.40
Mean Intensity/Outside144.70±20.92163.96±53.54139.62±111.45265.97±170.82512.97±181.20
Mean domain area, µm2-2.451.54+5.352.261.33+4.202.091.23+5.002.521.55+3.43
Mean domain diameter, µm-1.571.501.451.59

The observation that Rab5 can be recruited efficiently to PC/PS/PI(3)P membranes but cannot be organized into domains in the presence of Rabex5/Rabaptin5, excess GDI, and GTP suggest that Rab5 interacts differently with the complex EE membrane that with a simple PC/PS membrane. Our results demonstrate that PI(3)P enhances recruitment of Rab5 to MCBs and the presence of lipids that contribute to acyl chain packing (cholesterol, sphingomyelin; Kaiser et al., 2009) are necessary to drive Rab5 domain formation.

Discussion

GEF/effector coupling and the resulting positive feedback loop of GTPase activation and membrane recruitment are common to many small GTPase systems and have been implicated in their spatial patterning. In this study, we demonstrated that membrane recruitment and extraction (via GDI) together with coupling of GEF and effector activities (via Rabex5/Rabaptin5) are sufficient to reconstitute domain organization of Rab5 in vitro. Geranylgeranylated Rab5 was observed to be recruited to EE-like membranes from the Rab5/GDI complex. Whereas in the absence of other factors Rab5 was randomly distributed in the plane of the membrane, upon the addition of GDI, Rabex5/Rabaptin5 and GTP, it reorganized into discrete domains in a GTP-dependent manner. Key to Rab5 domain formation was the ‘handover’ of Rab5 from Rabex5 to Rabaptin5 and the lipid composition of early endosomes, suggesting a hitherto unknown cooperativity between lipids and Rab-dependent membrane self-organization.

Self-organizing systems that form spatial patterns on membranes often depend on non-linear dynamics (Halatek et al., 2018). In our system, a key feature is the membrane recruitment and activation of Rab5, regulated by the Rabex5/Rabaptin5 complex. Neither GEF activity nor effector binding alone were capable of supporting domain formation unless physically coupled in a complex. We found that, in the course of nucleotide exchange, newly activated Rab5 is released from Rabex5 and immediately binds Rabaptin5 suggesting there is a direct delivery or ‘handover’ of Rab5 from Rabex5 to Rabaptin5. This ‘handover’ is likely facilitated by the dimerization of the Rabex5/Rabaptin5 complex and presents a structural mechanism by which a positive feedback loop of Rab5 activation could be generated. Other Rab5 GEFs that localize and recruit Rab5 to different intracellular compartments (e.g. GAPVD1 or RIN1 on clathrin-coated vesicles and the plasma membrane; Tall et al., 2001; Semerdjieva et al., 2008 have as of yet not been found to be coupled to effector activity. In vivo Rabex5/Rabaptin5 can be targeted to the EE by interaction of Rabex5 with ubiquitinated receptors and the binding of Ubiquitin to Rabex5 enhances nucleotide exchange activity (Lee et al., 2006; Mattera et al., 2006; Penengo et al., 2006; Lauer et al., 2019). This implies that ubiquitinated cargo can act not only to recruit Rabex5/Rabaptin5 but also potentially contribute to Rab5 domain formation and/or localization on the EE.

The membrane diffusion of multiple small GTPases has been shown to be integral in their capacity to self-organize (Goryachev and Pokhilko, 2008; Bruurs et al., 2015 and Bruurs et al., 2017). An important new finding of this study is the role of lipids in Rab5 domain formation. In our reconstituted system, PI(3)P and cholesterol enhanced the membrane recruitment of Rab5. In molecular dynamics simulations, Edler et al., 2017a suggest a direct interaction between Rab5 and PI(3)P and also observed accumulation of cholesterol in the proximity of Rab5. The requirement for PI(3)P has important implications for the in vivo formation of Rab5 domains. On the EE, PI(3)P is mainly produced by the activity of the class II PI3K complex, Vps34/Vps15, which is regulated by a direct interaction between Rab5 and Vps15 (Christoforidis et al., 1999a; Christoforidis et al., 1999b; Murray et al., 2002; Falasca and Maffucci, 2012). This suggests that Rab5 directly modifies the local lipid environment to stabilize itself on the membrane, thus providing yet another level of positive feedback in vivo.

Similar to Rab5 recruitment, domain formation was lipid composition dependent and most strongly observed on membranes containing the full EE lipid mixture. The observation that simple, highly diffusive, PC/PS membranes do not support domain formation suggests that the EE lipid composition facilitates lateral lipid packing and protein-lipid interactions that are necessary for domain formation. Lebrand et al., 2002 reported that cholesterol regulates the membrane association and activity of Rab7 on late endosomes in vivo and decreases GDI extraction of Rab7 in vitro. The requirement of cholesterol for stabilizing Rab5 on the membrane provides support to the idea that lipid packing serves to adapt to the longer chain length of the geranylgeranyl anchor. Increasing the complexity of the PC/PS lipid composition by adding cholesterol allowed for the formation of few domains of low GFP signal intensity. The addition of sphingomyelin but not ethanolamine plasmalogen was sufficient to produce domains with a high GFP-Rab5 signal intensity, as observed with the EE lipid composition. Other than being the next most abundant lipids (after cholesterol) in the EE lipid composition, both sphingomyelin and ethanolamine plasmalogen increase the rigidity of the membrane. This increased rigidity occurs via the saturated acyl chains of sphingomyelin and the small headgroup of the ethanolamine plasmalogen, two very different mechanisms that both reduce diffusivity of the membrane. The observation that sphingomyelin was necessary for domain formation with intensity values comparable to the EE lipid mixture, but ethanolamine plasmalogen was not, suggests that it is not a reduction in global membrane diffusivity that enables domain formation, but the presence of saturated acyl chains and capacity for lateral lipid packing (Kaiser et al., 2009). This may allow for dense packing of geranylgeranyl chains and stabilize a nascent domain by locally reducing the diffusion of Rab5. Further, the destabilization of α5, which extends into the HVR, observed in Rab5 by HDX-MS may alter the conformation of membrane-bound Rab5 upon nucleotide exchange. In molecular dynamics simulations, Edler and Stein, 2017b observed a rotation within the membrane of Rab5:GTP with respect to Rab5:GDP, that not only exposes the effector binding site but also suggests that Rab5 makes different membrane contacts depending on its nucleotide state. Further molecular dynamics simulations showed that this nucleotide state-dependent orientation, as well as correct insertion of the geranylgeranyl anchors into the lipid bilayer, is only supported by an EE-like membrane, containing PI(3)P, cholesterol, sphingomyelin and charged lipids (Edler and Stein, 2017b; Münzberg and Stein, 2019). However, the EE-lipid composition alone did not yield macroscopic LO domains. Rab5 domain formation therefore requires the synergy between the Rab5 minimal machinery and lateral lipid packing. We suggest that the EE lipid composition supports Rab5 domain formation in our in vitro system through a combination of 1) direct interactions between Rab5 and PI(3)P enhancing recruitment to the membrane, 2) cholesterol stabilizing the geranylgeranyl anchor insertions to support a nucleotide-dependent orientation of Rab5 relative to the membrane, and 3) the presence of saturated lipids allowing for dense packing of geranylgeranyl chains, contributing to domain stabilization and growth.

The non-linearity of the nucleotide cycle coupled to specific lipid interactions make small GTPases widespread regulators of membrane self-organization. K-Ras for example, has long been known to cluster and alter the local lipid environment, e.g. by forming nanoclusters of PI(4,5)P2 on the PM (Zhou et al., 2017). However, with the same design, different GTPase systems can form one (e.g. Cdc42) or multiple domains (e.g. ROP11, Rab5). Our in vitro system recapitulates the formation of multiple Rab5 domains on the same membrane. In the reconstituted system, Rab5 domains were formed with a characteristic density of ~4.7 domains/EE-MCB surface and a mean area of 1.74 µm2 (which would be estimated to contain up to ~10,000 molecules of Rab5). Chiou et al., 2018 propose that coexistence of multiple GTPase domains can arise if the density of active GTPase in the domain reaches a ‘saturation’ point. This would slow competition between domains, allowing multiple domains to exist simultaneously, and could occur via multiple biologically relevant mechanisms (e.g. local depletion of components or strong negative feedback). In our reconstituted system, we indeed saw both characteristic spacing of domains and saturation of GFP-Rab5 signal, indicating that such a ‘saturation’ point can be reached. From the domain intensity we could observe two phases in domain growth, an initial phase characterized by rapid increase in GFP signal intensity over time, and a second phase characterized by slow increase or even saturation in signal intensity. We suggest that fast growth is dominated by reorganization of the local lipid environment and rapid recruitment of proteins from solution. Upon depletion of the critical components from the local membrane, domains stabilize and reach a second, slow-growing or saturated phase. We suggest that in this phase, domains reach dynamic equilibrium where domain size has stabilized but the domain continues to exchange proteins with the soluble pool, as suggested by the observation that domains recover in the same location after photobleaching. It may therefore be the interaction with the lipid membrane that stabilizes and determines the size of the domains obtained in our system. Further, it is apparent during purification that recombinant Rab5 dimerizes at high concentrations and this dimerization is enhanced by geranylgeranylation (data not shown). Given that domains create a locally high concentration of protein, Rab5 dimerization may also contribute to stabilization of a Rab5 domain. How domain growth is regulated and by what means biological systems can produce a variety of spatial patterns based on common design principles has been the subject of multiple recent in silico models and simulations (Chiou et al., 2018; Halatek et al., 2018; Jacobs et al., 2019). For Turing-type reaction-diffusion systems, theory can predict regions in the parameter space where the system either can form dynamically stable patterns or support oscillatory behavior such as travelling waves. In our reconstituted system, we did not observe such oscillatory behavior. This may either be a limitation of the experimental set-up (e.g. too low resolution in time and space) or an intrinsic property of the system we investigated. The design principles of biochemical oscillators require delayed negative feedback (Novák and Tyson, 2008) which might not be achieved by the linear GTP to GDP hydrolysis and GDI extraction reconstituted in our reactions. Further adaptation of the system (e.g. the addition of GAP activity) may allow for wave-like behavior and remains for future investigation. Our results imply that the specific interaction of proteins with lipids in the membrane must also be considered in in silico studies of pattern formation.

Herein, we reconstituted a minimal system for the formation of Rab5 GTPase domains in vitro and demonstrated that both GEF/effector coupling and lipid interactions contribute to the self-organization of Rab5 on the membrane, where the lipid composition plays an important role beyond that of a solvent for lipidated proteins. This appears to be a universal system deploying small GTPases to pattern membranes from mono-cellular to multi-cellular organisms.

Materials and methods

Key resources table
Reagent type
(species) or resource
DesignationSource or referenceIdentifiersAdditional information
Recombinant DNA reagentpOEM-1 N-HisOxford Expression Technologies, MPI-CBG PEP facilityvector, NotI and AscI sites used for ligation
Recombinant DNA reagentpOEM-1 N-GSTOxford Expression Technologies, MPI-CBG PEP facilityvector, NotI and AscI sites used for ligation
Recombinant DNA reagentpOEM-1 N-His-eGFPOxford Expression Technologies, MPI-CBG PEP facilityvector, NotI and AscI sites used for ligation
Recombinant DNA reagentpOEM-1 C-His-tagRFPOxford Expression Technologies, MPI-CBG PEP facilityvector, NotI and AscI sites used for ligation
Transfected construct (Homo sapiens)Rab5aThis paperIn vector pOEM-1 N-His-eGFP
Transfected construct (Bos taurus)Rabex5 (pOEM-1 N-His)Lauer et al., 2019In vector pOEM-1 N-His
Transfected construct (Bos taurus)Rabex5CAT (pOEM-1 N-His)Lauer et al., 2019In vector pOEM-1 N-His
Transfected construct (Homo sapiens)Rabaptin5 (pOEM-1 N-GST)Lauer et al., 2019In vector pOEM-1 N-GST
Transfected construct (Homo sapiens)Rabaptin5-RFP-6xHisThis paperpOEM-1 C-His-tagRFP
Transfected construct (Homo sapiens)GDIA (pOEM-1 N-His)This paperIn vector pOEM-1 N-His
Commercial assay or kitSilica Beads (10 μm)CorpuscularC-SIO-10.010 μm standard microspheres for microscopy
Commercial assay or kitNi-NTA AgaroseQiagen
Commercial assay or kitGlutathione Sepharose 4B ResionGE
Commercial assay or kitBCA assayThermo Scientific23225
OtherGTPSigma10106399001
OtherCholesterol (ovine wool)Avanti700000
Other18:1 (Δ9-Cis) PC (DOPC) (1,2-dioleoyl-sn-glycero-3-phosphocholine)Avanti850375
OtherC18(Plasm)−18:1 PC (1-(1Z-octadecenyl)−2-oleoyl-sn-glycero-3-phosphocholine)Avanti852467
OtherSphingomyelin (Egg, Chicken)Avanti860061
OtherGM3 Ganglioside (Milk, Bovine-Ammonium Salt)Avanti860058
Other18:1 PS (DOPS) (1,2-dioleoyl-sn-glycero-3-phospho-L-serine (sodium salt))Avanti840035
Other18:1 (Δ9-Cis) PE (DOPE) (1,2-dioleoyl-sn-glycero-3-phosphoethanolamine)Avanti850725
OtherC18(Plasm)−18:1 PE (1-(1Z-octadecenyl)−2-oleoyl-sn-glycero-3-phosphoethanolamine)Avanti852758
OtherPhosphatidylinositol 3-phosphate diC16 (PI(3)P diC16)EchelonP-3016
OtherDiD [DiIC18(5); 1,1’-dioctadecyl-3,3,3’,3’-tetramethylindodicar-bocyanine, 4-chlorobenzenesulfonate salt]Thermo FischerD7757

Cloning

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Rab5, Rabex5, Rabaptin5, and GDI were cloned into pOEM series vectors (Oxford Expression Technologies), modified to contain a Human Rhino Virus (HRV) 3C cleavable tag at either the Nor C-terminus, followed by a protease cleavage site (Not1 at N-terminus, Asc1 at C-terminus) for insect (SF9) cell expression. Cleavable tags consisted of either 6x-Histidine (6xHis), for Rab5 and Rabex5, or Gluthathione S-Transferase (GST), for GDI and Rabaptin5. In order to monitor membrane association and organization, fluorescent Rab5 and Rabaptin5 constructs were created. The proteins were cloned into SF9 expression vectors containing either an N or C-terminal fluorescent tag (GFP or RFP) attached to the protein by a 13 amino acid flexible linker (N-terminal linker: GSAGSAAGSGAAA; C-terminal: linker: GAPGSAGSAAGSG). As the addition of a fluorescent tag to a protein always carries the risk of altering protein behavior by interfering with protein folding, fluorescent proteins were compared to non-fluorescent constructs known to fold properly by Hydrogen Deuterium Exchange Mass Spectrometry (HDX-MS) and discarded if they showed any aberrant dynamics. The following constructs were used in this study: 6xHis-GFP-Rab5, GST-GDI, GST-Rabaptin5, Rabex5-6xHis, RFP-Rabaptin5, 6xHis-RabexCAT.

Protein expression and purification

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SF9 cells were grown in ESF921 media (Expression Systems) and co-transfected with linearised viral genome and expression plasmid. P1 and P2 virus was generated per manufacturers protocol and yield was optimised by expression screens and infection time course experiments. The P2 virus was used to infect SF9 cells (grown to a density of 1 million cells/ml) at 1% (v/v). Rabex5/Rabaptin5 and geranylgeranylatedRab5/GDI complexes were produced by co-infection. Cells were harvested after 30–40 hr by spinning in a tabletop centrifuge at 500 g for 10 min. Cell pellets were resuspended in Standard Buffer (20 mM Tris pH7.5, 150 mM NaCl, 5 mM MgCl2, 0.5 mM TCEP; STD) supplemented with DNAse one and protease inhibitor cocktail (chymostatin 6 μg/mL, leupeptin 0.5 μg/mL, antipain-HCl 10 μg/mL, aprotinin 2 μg/mL, pepstatin 0.7 μg/mL, APMSF 10 μg/mL). Pellets were flash frozen and stored at −80◦C. All subsequent steps performed at 4◦C or on ice. Cells were thawed on ice and lysed by sonication (previously frozen SF9 cell pellets were not sonicated as freeze-thawing is sufficient for lysis). Cell lysates were spun with a JA 25.50 rotor at 22500 rpm for 20 min at 4◦C. Histidine-tagged proteins were bound to Ni-NTA Agarose resin (1L of culture = 1 mL resin) in the presence of 20 mM Imidazole. Resin was washed with STD buffer supplemented with 20 mM Imidazole. Proteins were eluted using 200 mM Imidazole only followed by Histidine-tag cleavage during overnight dialysis with 3C protease. GST tagged proteins were bound to Glutathione Sepharose resin (GS-4B, GE Healthcare) for 2 hr at 4◦C, washed with Standard Buffer and cleaved from resin overnight with a GST-3C protease. Rabex5/Rabaptin5 and Rab5/GDI complexes were purified by both His- and GST-tag affinity purification to obtain pure complex. Size Exclusion Chromatography was performed in STD on a Superdex200 Increase 10/30. Concentrations were determined by a bicinchoninic acid protein Assay (Pierce BCA Protein Assay Kit, ThermoFischer) and purity was assessed by SDS-PAGE followed by colloidal Coomassie staining. Proteins were aliquoted, flash frozen in liquid nitrogen and stored at −80◦C.

Liposome preparation

The lipids listed below were purchased and resuspended in either CHCl3, CHCl3:MeOH (2:1 for GM3) or CHCl3:MeOH:H2O (1:2:0.8 for PI(3)P) as per manufacturer’s instructions and stored at −20◦C. To form liposomes, lipids were mixed together and the solvent was evaporated under a stream of nitrogen. Residual solvent was removed by drying under vacuum overnight in a desiccator. Lipids were rehydrated for at 37◦C in SLB Buffer (20 mM TRIS, 150 mM NaCl) and vortexed to form a stock solution of 1 mM lipid. Small unilamellar vesicles (SUV) were prepared by freeze-thaw cycles (10x snap freezing and thawing at 37◦C). Vesicles were stored at −20◦C and sized by sonication before each application. Size distribution of liposome preparations was assessed by Dynamic Light Scattering using a Zetasizer Nano ZSP Malvern.

EE lipid composition

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DOPC(1,2-dioleoyl-sn-glycero-3-phosphocholine):DOPS(1,2-dioleoyl-sn-glycero-3-phospho-L-serine):DOPE(1,2-dioleoyl-sn-glycero-3-phosphoethanolamine):Sphingomyelin:Cholesterol:ethanolamine plasmalogen (1-(1Z-octadecenyl)−2-oleoyl-sn-glycero-3-phosphoethanolamine):choline plasmalogen (1-(1Z-octadecenyl)−2-oleoyl-sn-glycero-3-phosphocholine):GM3: PI(3P) (diC16 Phosphatidylinositol 3-phosphate): DiD [DiIC18(5); 1,1’-dioctadecyl-3,3,3’,3’-tetramethylindodicar-bocyanine, 4-chlorobenzenesulfonate salt] (13.8:6.1:6.8:12.6:32.3:12.9:3.6:9:1:0.1) (See Table 1).

PC/PS lipid composition

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DOPC(1,2-dioleoyl-sn-glycero-3-phosphocholine): DOPS(1,2-dioleoyl-sn-glycero-3-phospho-L-serine): Phosphatidylinositol 3-phosphate (PI(3P)diC16): DiD [DiIC18(5); 1,1’-dioctadecyl-3,3,3’,3’-tetramethylindodicar-bocyanine, 4-chlorobenzenesulfonate salt] (83.95:15:1:0.1) (See Table 1).

MCB preparation

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Silica beads (10 μm standard microspheres for microscopy) were coated with a supported lipid bilayer as described (Neumann et al., 2013) with minor modifications to ensure a tight lipid membrane. Beads were incubated with either 800 mM NaCl and 250 μM EE liposomes or 375 µM PC/PS liposomes (Z average diameter 100–120 nm by SLS) for 15 min RT on a rotator wheel. MCBs were washed with 1ml H20 and 2 × 1 mL Standard Buffer, centrifuging at 2000rpm for 1 min in a tabletop centrifuge. Membrane integrity was assessed at different time points and after increasing centrifugation steps. MCBs were found to be robust at 13000 rpm washing steps and up to 4 hr at RT. MCBs were consequently used within 3 hr of formation. The formation protocol was adapted for PC/PS membranes in order to produce MCBs with similar amounts of membrane as compared to EE-MCBs in order to make direct comparisons of GFP-Rab5 recruitment.

Confocal microscopy

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Microscopy experiments were performed on either Nikon TiE (manual imaging, for high resolution and 3D reconstructions) or Cell Voyager 7000S (CV7000S) (automated imaging for time lapse experiments). For manual imaging in Nikon TiE, reactions were prepared in an 8-well NuncTM Lab-TekTM Chamber Slide for imaging. Images were acquired with a Nikon TiE equipped with a 100x/1.45NA Plan Apochromat, DIC oil immersion objective, Yokogawa CSU-X1 scan head and Andor DU-897 back-illuminated CCD. Images were acquired with 80 ms exposure at λ 488, 561 and 660 with the following laser intensities: 15% 488; 5% 561; and 2% 660. For automated imaging, reactions were prepared in a Greiner Square bottom 384 well plate. Images were acquired with Cell Voyager 7000S (CV7000S) equipped with a 60x/1.2NA water immersion objective at 30% 488 and 660 laser. Color and illumination corrections were applied though CV7000S software. Imaging support by M. Stöter (TDS, MPI-CBG).

Image analysis

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Intensity quantifications at MCB equators were performed manually in FIJI (Schindelin et al., 2012). Beads were segmented manually and intensity values along the surface were extracted by determining line profiles 10 pixels wide along the surface of the bead as defined by DiD signal. Intensity in 488 and 561 was normalized to the intensity in the 660 channel in a pixelwise manner to account for potential differences in membrane amount between beads and lipid compositions. Box and whiskers plots show median (line), 25/75 quartiles (box boundaries), and min/max values (error bars). Unpaired t-tests were performed to test statistical significance.

To quantify size, intensity, and number of domains on MCBs, a novel image analysis pipeline was developed. The pipeline consists of the following steps, illustrated in Figure 2—figure supplement 1G:

  1. The membrane surface wass extracted by selecting all pixels in the upper 0.5% intensity percentile for the membrane channel. The sphere center and radius were fitted using a linear least-squares solver with the normal residuals as cost function. Next, particles were distributed on the fitted sphere on a latitude-longitude mesh with 3 resolution in both azimuthal and polar directions. The particles were thereafter extended from the surface into a narrow band around it by replicating the particles in the radial direction with 1 pixel spacing until a distance of 5 pixels from the surface. Next, GFP-Rab5 intensity values were interpolated from pixels to particles in the narrow band using moment-conserving interpolation schemes (Monaghan, 1985). Finally, the particle intensity values were maximum-projected in the radial direction.

  2. Uneven background in the tangent space of beads was corrected using a ‘rolling ball’ algorithm, with a radius of 2 μm (Sternberg, 1983).

  3. Rab5 domains were segmented using a globally optimal model-based method Squassh (Rizk et al., 2014). The segmentation was applied on pixels after replacing all pixel values with intensities obtained by interpolating back from the particles to pixels to yield a clean pixel image with denoised and background-corrected intensities. All segmentations were performed using the following parameters in Squassh: regularization parameter 0.35 and minimum object intensity 0.3. In addition, sub-pixel segmentation with 4-fold oversampling was enabled.

  4. A marching cubes algorithm (Lorensen and Cline, 1987) was used to construct a triangulated mesh of the surface of each segmented domain. Next, the triangulated mesh was used to map the segmentation to the particles in the narrow band. Each particle within the triangulated mesh was orthogonally projected to the surface. For domain size estimation, the projected areas of all in-surface particles belonging to each domain were summed.

Spatial representation of correlation

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Correlation maps were created by computing the normalized mean deviation product (nMDP) as a measure of correlation between the corresponding pair of particles with intensities according to the formula:

nMDP= (Ai A¯ )(Bi B¯)(AmaxA¯)(BmaxB¯)

Ai and Bi – intensity of the given particle on the bead A or bead B

A¯ and B¯ – average intensity of the bead A or bead B

Amax and Bmax – maximum intensity of the bead A or bead B

Hydrogen Deuterium Exchange-Mass Spectrometry (HDX-MS)

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HDX-MS was performed essentially as previously described (He et al., 2015; Mayne et al., 2011; Walters et al., 2012). Proteins (1 uM) are diluted 6:4 with 8M urea, 1% trifluoroacetic acid, passed over an immobilized pepsin column (2.1 mm x 30 mm, ThermoFisher Scientific) in 0.1% trifluoroacetic acid at 15 °C. Peptides are captured on a reversed-phase C8 cartridge, desalted and separated by a Zorbax 300 SB-C18 column (Agilent) at 1 °C using a 5–40% acetonitrile gradient containing 0.1% formic acid over 10 min and electrosprayed directly into an Orbitrap mass spectrometer (LTQ-Orbitrap XL, ThermoFisher Scientific) with a T-piece split flow setup (1:400). Data were collected in profile mode with source parameters: spray voltage 3.4kV, capillary voltage 40V, tube lens 170V, capillary temperature 170 °C. MS/MS CID fragment ions were detected in centroid mode with an AGC target value of 104. CID fragmentation was 35% normalized collision energy (NCE) for 30 ms at Q of 0.25. HCD fragmentation NCE was 35 eV. Peptides were identified using Mascot (Matrix Science) and manually verified to remove ambiguous peptides. For measurement of deuterium uptake, 10 uM protein is diluted 1:9 in Rab5 buffer prepared with deuterated solvent. Samples were incubated for varying times at 22 °C followed by the aforementioned digestion, desalting, separation and mass spectrometry steps. The intensity weighted average m/z value of a peptide’s isotopic envelope is compared plus and minus deuteration using the HDX workbench software platform. Individual peptides are verified by manual inspection. Data are visualized using Pymol. Deuterium uptake is normalized for back-exchange when necessary by comparing deuterium uptake to a sample incubated in 6M urea in deuterated buffer for 12–18 hr at room temperature and processed as indicated above.

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  67. 67
  68. 68
  69. 69
  70. 70
  71. 71

Decision letter

  1. Suzanne R Pfeffer
    Senior and Reviewing Editor; Stanford University School of Medicine, United States
  2. Suzanne R Pfeffer
    Reviewer; Stanford University School of Medicine, United States

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

Rab GTPases are master regulators of membrane trafficking that template the organization and directionality of the secretory and endocytic pathway. Using a reconstitution approach, the authors describe how a molecular feedback loop is created to regulate Rab function in coordination with specific lipids, effector proteins and guanine nucleotide exchange factors. Understanding feedback loops such as that generated in this system is of broad interest and much remains to be learned about how proteins are organized on intracellular membrane surfaces.

Decision letter after peer review:

Thank you for submitting your article "A non-linear system patterns Rab5 GTPase on the membrane" for consideration by eLife. Your article has been reviewed by three peer reviewers, including Suzanne Pfeffer as the Senior and Reviewing Editor. The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

This is a high-quality study in which the authors reconstitute prenylated Rab5 GTPase on bead bound liposomes and reveal macromolecular clustering that depends on a Rab5 GEF and GEF-binding effector. Understanding feedback loops such as that generated in this system is of broad interest and much remains to be learned about how proteins are organized on intracellular membrane surfaces. The surprising result here is that Rab5-GTP alone does not organize but in the presence of the GEF and effector, it does, and the PI3P composition of the membrane is also important.

All the reviewers were highly supportive of the manuscript but suggested various approaches to enhance the significance of the story without too much additional work. We leave it to you to decide how to accomplish this, thus we have included all the reviews--but it would make sense to characterize more fully how PI3P works and add some data more related to lipid composition.

Reviewer #1:

This is a high-quality study in which the authors reconstitute prenylated Rab5 GTPase on bead bound liposomes and reveal macromolecular clustering that depends on a Rab5 GEF and GEF-binding effector. Understanding feedback loops such as that generated in this system is of broad interest and much remains to be learned about how proteins are organized on intracellular membrane surfaces. The surprising result here is that Rab5-GTP alone does not organize but in the presence of the GEF and effector, it does, and the PI3P composition of the membrane is also important. Although there is a large amount of work presented herein, additional experiments would add greatly to the overall impact of the current story. For example, although others proposed in MD simulations a role for an arginine residue in the interaction between Rab5 and PI3P, the authors could easily test this in their system. Not explored is the issue of a catalytic GEF linked to a Rabaptin-5 stoichiometric binding site, suggesting that in this simple system, the GEF may continue to act on a single Rab. This should be discussed more fully and the authors should use standard fluorescent proteins to try to determine the number of molecules in their liposome-bound complexes. What fraction of Rabex is Rabaptin bound in cells, and is it in equilibrium with a soluble pool? If they dimerize the Rabaptin with GFP, do they get twice as large a cluster? And why is there such a great difference between 500nM and 1µM GDI? Is it there to rescue some prenylated proteins that crash out of the system if not able to jump into the membrane? Is there an effect of PRA1 that is so essential for their in vitro endosome fusion reaction? Finally, the authors were not able to remove cholesterol from their system but they could use cholesterol binding protein toxins to segregate cholesterol and look at the effect?

In summary, a slightly deeper consideration of each of the take home messages will add much to this interesting and high-quality study.

Reviewer #2:

In this paper, the authors have used the purified Rabex5/Rabaptin5 complex and supported lipid bilayers to study the association of Rab5 with the bilayer. They report that Rab5 forms domains at the surface of the membrane, that Rabex5 hands Rab5 over to Rabaptin5 upon nucleotide exchange, and that a minimal system consisting of Rab5, RabGDI, and Rabex5/Rabaptin5 is necessary to pattern Rab5 into membrane domains. They also report that early endosomal lipids were required for Rab5 pattern formation. The authors conclude that the prevalence of GEF/effector coupling in nature suggests the existence of a universal system for small GTPase patterning.

The paper is very interesting, because the notion that Rab5, or other small GTPases, forms functional effector domains has broad physiological implications, and was proposed a long time ago by the authors. This is the first, direct in vitro evidence of GTPase domain formation because of a dynamic activation loop controlled by the GEF-GAP-GDI. The study is globally very convincing, but I have a few comments that the authors may wish to address

1) The patterns observed by the authors are dynamically stable. While in a dynamic Turing model of patterning, some area of the phase diagram form stable patterns, it is more likely to obtain travelling waves/spirals in such systems. Did the author observe any propagation or dynamic change of patterns through time? Otherwise, can the author justify using the known time constants or proper feedback loops in their system why it is expected to have a stable pattern rather than travelling waves?

2) The formation of such patterns should strongly depend on the diffusion coefficient of lipids (and proteins), which, I guess is pretty limited onto the supported bilayers used in this study. Did the author try to used GUVs instead of the beads? I would expect that the domains do not form, or that they transform into travelling waves. It would be an important point to make about the role of diffusion in the formation of domains. Diffusion of membrane components on the beads and on the GUVs could also be measured by FRAP, to have an idea of the diffusion change.

3) To reconstitute Rab5 domain formation in vitro, the authors used the lipid composition of enriched early endosomes previously determined by mass spectrometry in Perini (2012). I find it surprising that PC corresponds only to 14 mol% of EE lipids (see Materials and methods). As far as I can remember, PC accounts for 45-55 mol% of all cellular membranes in higher eukaryotes. Also, Perini (2012) is a thesis from the MPI-CBG in Dresden and is not readily available. Sufficient information on fractionation and analysis should be made available in the paper so that readers can evaluate the data. Similarly, the pseudocylindrical projection used to segment and visualized EE-membrane-coated beads is described in a submitted paper (Solomatina et al.).

4) Along the same lines, and due to the high content in sphingolipids and cholesterol in the EE lipid composition used by the authors, how can the authors rule out that Rab5 domains are not formed onto pre-existing lipid domains, in particular because they see domains forming only with the EE composition?

5) I find it a bit difficult to evaluate the projections in Figure 5 A-B, after recruitment of GG-GFP-Rab5 to EE and PC/PS bilayers (without Rabex5/Rabaptin5). I agree with the authors that GFP-Rab5 distribution without Rabex5/Rabaptin5 looks different from the patterns with domains observed in the presence of Rabex5/Rabaptin5 (Figure 6B). Yet, GFP-Rab5 without Rabex5/Rabaptin5 does not seem evenly or randomly distributed on the surface with PI3P (both EE or PC/PS): GFP-Rab5 seems to form numerous, smaller domains. Is this so? Are these domains more or less dynamic by FRAP? Also, GFP-Rab5 fluorescence (Figure 5A-B), but not DiD fluorescence (Figure 5—figure supplement 1), seems to be restricted to the projection above the equator.

Reviewer #3:

The manuscript by Cezanne et al. constitutes a significant breakthrough not only for the narrow field of small GTPases, or even for the cell biology as a whole, but also for the broadest interdisciplinary community interested in biological systems from the systems point of view. Cellular pattern formation and morphogenesis is currently of great interest and is very timely because both the experimental tools and the theoretical methods have reached the needed maturity. The senior author was probably the first to propose, already back in 1997, that the interaction between the GTPase effectors and GEFs can generate positive feedback loops capable of breaking spatial symmetry and generating membrane clusters, the simplest structures to form a prepattern for a great variety of much more complex structures. Zerial and colleagues are again ahead of the competition. Formation of clusters of activated GTPases had been theoretically predicted and computationally modeled for over a decade, but the in vitro reconstitution of this process remained out of reach. Recent tremendous success in reconstituting the MinD system in vitro showed how much can be learned from a reliable, reproducible and controllable in vitro system about cellular morphogenesis. Several groups had been able to reconstitute various Rho GTPases in vitro, but nobody attacked the pattern formation problem. Cezanne et al. do exactly this, they convincingly show that all theoretical predictions were correct, a minimal system consisting of a small GTPase, its GDI and the positive feedback molecule (the effector-GEF complex) is fully competent to break spatial symmetry and generate clusters of activated GTPase.

Therefore, I believe the paper is extremely interesting to a broad readership of eLife, very timely and novel and, thus, should be published by eLife upon some, mostly minor, improvements.

1) The discovery that only the native endocytic lipid mixture (EE), but not the PC/PS artificial membrane, supports the pattern formation is striking but remains unexplained in the manuscript. It is even more surprising given the result that addition of 1% of PI3P rescues the Rab5 recruitment. Although the authors discuss this result at length, the reader is left feeling somehow unsatisfied… I realize that the authors could not remove lipids from the EE without jeopardizing the integrity of the membrane. What about instead modifying/doping the PC/PS mix? One potential explanation of this result is that some specific lipid/ electric charge is required to make a functional membrane. The authors could "add back" some of the natively found lipids (using their lipidomics analysis of the EE mix as a guide) or increase the negative charge by adding more PS and see if this rescues pattern formation. There is also another potential explanation, which is more interesting from the theoretical point of view and the authors could confirm or reject this possibility with the tools/methods they already have in place! Modeling work predicted and some experiments (Bruurs et al., 2017, 2018, the authors should cite these very important papers!) confirmed that pattern formation is very sensitive to the diffusion coefficient of the GTPase on the membrane. The manuscript shows that the authors used oleic acid derivatives for both PC and PS. While this lipid tail is long, it is also unsaturated, which likely supports liquid disordered lipid phase. To change the diffusion coefficient without affecting the chemistry of lipid head groups, the authors could use longer and fully saturated fatty acid derivatives. Addition of cholesterol to this mix should even further increase the thickness of the membrane bilayer and reduce the diffusion coefficient of Rab5. These experiments are doable without any new protein constructs and could significantly increase the impact of the paper.

2) Another suggestion organically follows from the previous one. The authors site a number of modeling studies but, surprisingly, offer no computational model of their dramatic pattern-forming system themselves! A model could increase the impact of the work and assist in understanding the role of molecular transport (GDI) of Rab5, membrane diffusion coefficient, etc.

https://doi.org/10.7554/eLife.54434.sa1

Author response

All the reviewers were highly supportive of the manuscript, but suggested various approaches to enhance the significance of the story without too much additional work. We leave it to you to decide how to accomplish this, thus we have included all the reviews--but it would make sense to characterize more fully how PI3P works and add some data more related to lipid composition.

Reviewer #1:

This is a high-quality study in which the authors reconstitute prenylated Rab5 GTPase on bead bound liposomes and reveal macromolecular clustering that depends on a Rab5 GEF and GEF-binding effector. Understanding feedback loops such as that generated in this system is of broad interest and much remains to be learned about how proteins are organized on intracellular membrane surfaces. The surprising result here is that Rab5-GTP alone does not organize but in the presence of the GEF and effector, it does, and the PI3P composition of the membrane is also important. Although there is a large amount of work presented herein, additional experiments would add greatly to the overall impact of the current story. For example, although others proposed in MD simulations a role for an arginine residue in the interaction between Rab5 and PI3P, the authors could easily test this in their system.

This is an interesting suggestion, unfortunately, due to the Covid-19 crisis which forced us to close the institute, we were unable to complete these experiments for inclusion in this manuscript. We will pursue this as a part of our follow-up work further dissecting the mechanisms controlling Rab5 domain formation.

Not explored is the issue of a catalytic GEF linked to a Rabaptin-5 stoichiometric binding site, suggesting that in this simple system, the GEF may continue to act on a single Rab. This should be discussed more fully and the authors should use standard fluorescent proteins to try to determine the number of molecules in their liposome-bound complexes. What fraction of Rabex is Rabaptin bound in cells, and is it in equilibrium with a soluble pool? If they dimerize the Rabaptin with GFP, do they get twice as large a cluster?

We improved the description of the stoichiometry of the Rabex5/Rabaptin5 complex to make it clearer that it is a heterotetramer composed of two Rabex5 and two Rabaptin5 molecules (Introduction). Rabex5 and Rabaptin5 form a constitutive complex that is stable to gel filtration and we do not observe exchange between a soluble pool of subunits. The precise interaction between these molecules has been investigated in a previous study (Lauer et al., 2019). We also amended the Discussion to include an estimate of the number of Rab5 molecules in our reconstituted domains (paragraph four).

And why is there such a great difference between 500nM and 1µM GDI?

In preliminary experiments we found that 1µM GDI was required to fully remove 10nM GFP-Rab5 from EE-MCBs.

Is it there to rescue some prenylated proteins that crash out of the system if not able to jump into the membrane? Is there an effect of PRA1 that is so essential for their in vitro endosome fusion reaction?

Pra1 was previously included by Ohya et al., 2009, to stimulate the delivery of Rab5 to proteoliposomes and render them fusogenic. We did not look at the addition of Pra1 because we found that a minimal system consisting of GDI and the Rabex5/Rabaptin5 complex was sufficient to create Rab5 domains.

Finally, the authors were not able to remove cholesterol from their system but they could use cholesterol binding protein toxins to segregate cholesterol and look at the effect?

Pra1 was previously included by Ohya et al., 2009, to stimulate the delivery of Rab5 to proteoliposomes and render them fusogenic. We did not look at the addition of Pra1 because we focused on creating a minimal system consisting of GDI and the positive feedback loop provided by the Rabex5/Rabaptin5 complex that was sufficient to create Rab5 domains. In such minimal system the requirement for Pra1 can be bypassed.

Reviewer #2:

In this paper, authors have used the purified Rabex5/Rabaptin5 complex and supported lipid bilayers to study the association of Rab5 with the bilayer. They report that Rab5 forms domains at the surface of the membrane, that Rabex5 hands Rab5 over to Rabaptin5 upon nucleotide exchange, and that a minimal system consisting of Rab5, RabGDI, and Rabex5/Rabaptin5 is necessary to pattern Rab5 into membrane domains. They also report that early endosomal lipids were required for Rab5 pattern formation. The authors conclude that the prevalence of GEF/effector coupling in nature suggests the existence of a universal system for small GTPase patterning.

The paper is very interesting, because the notion that Rab5, or other small GTPases, forms functional effector domains has broad physiological implications, and was proposed a long time ago by the authors. This is the first, direct in vitro evidence of GTPase domain formation because of a dynamic activation loop controlled by the GEF-GAP-GDI. The study is globally very convincing, but I have a few comments that the authors may wish to address

1) The patterns observed by the authors are dynamically stable. While in a dynamic Turing model of patterning, some area of the phase diagram form stable patterns, it is more likely to obtain travelling waves/spirals in such systems. Did the author observe any propagation or dynamic change of patterns through time? Otherwise, can the author justify using the known time constants or proper feedback loops in their system why it is expected to have a stable pattern rather than travelling waves?

We investigated this possibility but did not observe wave-like or other macroscopic dynamic behaviors in our system. However, we cannot exclude the possibility that our system lacks sufficient resolution to detect waves. We amended the Discussion to include a brief discussion of Turing type pattern formation and how stable patterns rather than travelling waves might be formed/observed in our set-up (paragraph five). We are in the process of working on an in-depth computational model to investigate the mechanisms of pattern formation in this system and possible dynamic behaviors.

2) The formation of such patterns should strongly depend on the diffusion coefficient of lipids (and proteins), which, I guess is pretty limited onto the supported bilayers used in this study. Did the author try to used GUVs instead of the beads? I would expect that the domains do not form, or that they transform into travelling waves. It would be an important point to make about the role of diffusion in the formation of domains. Diffusion of membrane components on the beads and on the GUVs could also be measured by FRAP, to have an idea of the diffusion change.

We have not yet tried to use free-standing membranes as this would necessitate another optimization of the system. However, this is something we would like to investigate in future. A consideration here is that the incorporation of 10 lipid components into GUVs is technically challenging. We chose another approach to achieve the same goal. We instead increased the membrane rigidity of the simple PC/PS lipid composition by adding cholesterol, sphingomyelin and ethanolamine plasmalogen (PlasmPE)(Figure 6F and Table 5). Interestingly, we observed that it is not a global change in membrane diffusivity that allows for pattern formation, but most likely local changes induced by increased acyl chain packing and accommodation of the geranylgeranyl anchor.

3) To reconstitute Rab5 domain formation in vitro, the authors used the lipid composition of enriched early endosomes previously determined by mass spectrometry in Perini (2012). I find it surprising that PC corresponds only to 14 mol% of EE lipids (see Materials and methods). As far as I can remember, PC accounts for 45-55 mol% of all cellular membranes in higher eukaryotes. Also, Perini (2012) is a thesis from the MPI-CBG in Dresden and is not readily available. Sufficient information on fractionation and analysis should be made available in the paper so that readers can evaluate the data. Similarly, the pseudocylindrical projection used to segment and visualized EE-membrane-coated beads is described in a submitted paper (Solomatina et al.).

We added a description of our fractionation protocol and our image analysis pipeline (See Materials and methods) to make this information accessible. The image analysis pipeline is further detailed in a separate submitted publication that we hope will be available soon.

While the total phospholipid content of cells is indeed estimated to be composed of 45-55mol% PC, there are significant variations in the PC content between different internal membrane structures. In our EE lipid composition PC and PlasmPC combined make up around 20% of the total phospholipid. This is in agreement with studies reporting the lipid composition of the plasma membrane which is known to be very similar to that of the early endosome and we now comment on this in the Results (subsection “Reconstituting Rab5 domain formation in vitro”). Other endo-membranes, e.g. later steps in the endocytic pathway or the ER, on the other hand have been shown to contain a higher percentage of PC (Casares et al., 2019).

4) Along the same lines, and due to the high content in sphingolipids and cholesterol in the EE lipid composition used by the authors, how can the authors rule out that Rab5 domains are not formed onto pre-existing lipid domains, in particular because they see domains forming only with the EE composition?

This is a plausible interpretation, especially in light of our new findings that cholesterol and sphingomyelin appear to be necessary for Rab5 domain formation. In order to test this, we stained EE-MCBs with C-laurdan. However, we could not detect pre-existing phases of lipid order.

5) I find it a bit difficult to evaluate the projections in Figure 5 A-B, after recruitment of GG-GFP-Rab5 to EE and PC/PS bilayers (without Rabex5/Rabaptin5). I agree with the authors that GFP-Rab5 distribution without Rabex5/Rabaptin5 looks different from the patterns with domains observed in the presence of Rabex5/Rabaptin5 (Figure 6B). Yet, GFP-Rab5 without Rabex5/Rabaptin5 does not seem evenly or randomly distributed on the surface with PI3P (both EE or PC/PS): GFP-Rab5 seems to form numerous, smaller domains. Is this so? Are these domains more or less dynamic by FRAP? Also, GFP-Rab5 fluorescence (Figure 5A-B), but not DiD fluorescence (Figure 5—figure supplement 1), seems to be restricted to the projection above the equator.

We agree that the images originally chosen highlighted inhomogeneity in GFP-Rab5 distribution that might be misleading. To remove a reliance on visual inspection to detect domains, we use automated image analysis methods to detect the presence of domains. We substituted the images in question with other images from the same condition, which are in better agreement with the results from the automated detection algorithm.

Reviewer #3:

The manuscript by Cezanne et al. constitutes a significant breakthrough not only for the narrow field of small GTPases, or even for the cell biology as a whole, but also for the broadest interdisciplinary community interested in biological systems from the systems point of view. Cellular pattern formation and morphogenesis is currently of great interest and is very timely because both the experimental tools and the theoretical methods have reached the needed maturity. The senior author was probably the first to propose, already back in 1997, that the interaction between the GTPase effectors and GEFs can generate positive feedback loops capable of breaking spatial symmetry and generating membrane clusters, the simplest structures to form a prepattern for a great variety of much more complex structures. Zerial and colleagues are again ahead of the competition. Formation of clusters of activated GTPases had been theoretically predicted and computationally modeled for over a decade, but the in vitro reconstitution of this process remained out of reach. Recent tremendous success in reconstituting the MinD system in vitro showed how much can be learned from a reliable, reproducible and controllable in vitro system about cellular morphogenesis. Several groups had been able to reconstitute various Rho GTPases in vitro, but nobody attacked the pattern formation problem. Cezanne et al. do exactly this, they convincingly show that all theoretical predictions were correct, a minimal system consisting of a small GTPase, its GDI and the positive feedback molecule (the effector-GEF complex) is fully competent to break spatial symmetry and generate clusters of activated GTPase.

Therefore, I believe the paper is extremely interesting to a broad readership of eLife, very timely and novel and, thus, should be published by eLife upon some, mostly minor, improvements.

1) The discovery that only the native endocytic lipid mixture (EE), but not the PC/PS artificial membrane, supports the pattern formation is striking but remains unexplained in the manuscript. It is even more surprising given the result that addition of 1% of PI3P rescues the Rab5 recruitment. Although the authors discuss this result at length, the reader is left feeling somehow unsatisfied… I realize that the authors could not remove lipids from the EE without jeopardizing the integrity of the membrane. What about instead modifying/doping the PC/PS mix? One potential explanation of this result is that some specific lipid/ electric charge is required to make a functional membrane. The authors could "add back" some of the natively found lipids (using their lipidomics analysis of the EE mix as a guide) or increase the negative charge by adding more PS and see if this rescues pattern formation.

As the simple PC/PS lipid composition already includes 15mol% DOPS which is a significant amount of negative charge, we modified the PC/PS lipid composition by sequentially adding PI(3)P, cholesterol and either ethanolamine plasmalogen (PlasmPE) or sphingomyelin (the next most abundant lipids in the EE lipid composition which both influence membrane rigidity). We show that the presence of sphingomyelin, but not PlasmPE, is necessary for Rab5 domain formation (Figure 6F and Table 5). We conclude that lipids that are known to mediate acyl chain packing (cholesterol, sphingomyelin) are vital for formation and stability of the Rab5 domain. These points have been expanded in the discussion as well.

There is also another potential explanation, which is more interesting from the theoretical point of view and the authors could confirm or reject this possibility with the tools/methods they already have in place! Modeling work predicted and some experiments (Bruurs et al., 2017, 2018, the authors should cite these very important papers!) confirmed that pattern formation is very sensitive to the diffusion coefficient of the GTPase on the membrane.

The papers mentioned are indeed very interesting and we now cite these papers in the Discussion.

The manuscript shows that the authors used oleic acid derivatives for both PC and PS. While this lipid tail is long, it is also unsaturated, which likely supports liquid disordered lipid phase. To change the diffusion coefficient without affecting the chemistry of lipid head groups, the authors could use longer and fully saturated fatty acid derivatives. Addition of cholesterol to this mix should even further increase the thickness of the membrane bilayer and reduce the diffusion coefficient of Rab5. These experiments are doable without any new protein constructs and could significantly increase the impact of the paper.

We tried to, either fully or partially, replace DOPC(18:1) and DOPS(18:1) with the saturated DSPC(18:0) and DSPS(18:0) species, either fully or partially. Unfortunately, the addition of saturated DSPC and DSPS prevented the formation of stable MCBs in our set up as we conduct experiments at 25°C, well below the Tm of DSPC (55°C) and DSPS (68°C). Instead, we addressed the question of Rab5 diffusion by modifying the simple DOPC/DOPS lipid composition to include cholesterol and other components of the EE lipid composition that influence membrane rigidity, as described above.

In the future, we aim to explore the effect of altering lateral diffusion of Rab5 in the membrane in the framework of the computational model described below.

2) Another suggestion organically follows from the previous one. The authors site a number of modeling studies but, surprisingly, offer no computational model of their dramatic pattern-forming system themselves! A model could increase the impact of the work and assist in understanding the role of molecular transport (GDI) of Rab5, membrane diffusion coefficient, etc.

We have been working on an in-depth computational model of this system. This will be submitted as a separate manuscript as it is a full study on its own. The model will delve into the roles of protein-protein, protein-lipid and lipid-lipid interactions highlighted in this study.

https://doi.org/10.7554/eLife.54434.sa2

Article and author information

Author details

  1. Alice Cezanne

    Max-Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6319-9235
  2. Janelle Lauer

    Max-Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Conceptualization, Data curation, Supervision, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1412-6766
  3. Anastasia Solomatina

    1. Max-Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, Dresden, Germany
    3. MOSAIC Group, Center for Systems Biology Dresden, Dresden, Germany
    Contribution
    Resources, Software, Formal analysis, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
  4. Ivo F Sbalzarini

    1. Max-Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Chair of Scientific Computing for Systems Biology, Faculty of Computer Science, Dresden, Germany
    3. MOSAIC Group, Center for Systems Biology Dresden, Dresden, Germany
    Contribution
    Conceptualization, Supervision, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Marino Zerial

    Max-Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Conceptualization, Supervision, Funding acquisition, Methodology, Project administration, Writing - review and editing
    For correspondence
    zerial@mpi-cbg.de
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7490-4235

Funding

Deutsche Forschungsgemeinschaft (TRR 83 112927078)

  • Marino Zerial

Deutsche Forschungsgemeinschaft (TRR 83 TP23)

  • Marino Zerial

Max-Planck-Gesellschaft

  • Marino Zerial

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We warmly thank David H Murray for training in lipid techniques, discussions and support during the initial stages of the project. We also thank Yannis Kalaidzidis, Robert Ernst, Ünal Coskun and Stephan Grill for their helpful discussions and suggestions, as well as Martin Stöter for help with the timelapse imaging. We would also like to thank the following Services and Facilities of the Max Planck Institute of Molecular Cell Biology and Genetics for their support: Light Microscopy Facility (LMF), Technology Development Studio (TDS) and the Protein Expression Purification and Characterization (PEPC) Facility. This work was financially supported by the Max Planck Society (MPG) and the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – 1) TRR 83 (grant no. 112927078, TP23 M Zerial) and 2) under Germany´s Excellence Strategy – EXC-2068–390729961– Cluster of Excellence Physics of Life of TU Dresden.

Senior and Reviewing Editor

  1. Suzanne R Pfeffer, Stanford University School of Medicine, United States

Reviewer

  1. Suzanne R Pfeffer, Stanford University School of Medicine, United States

Publication history

  1. Received: December 13, 2019
  2. Accepted: May 21, 2020
  3. Version of Record published: June 8, 2020 (version 1)

Copyright

© 2020, Cezanne et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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