Giant Endoplasmic Reticulum vesicles (GERVs), a novel model membrane tool

Artificial giant vesicles have proven highly useful as membrane models in a large variety of biophysical and biochemical studies. They feature accessibility for manipulation and detection, but lack the compositional complexity needed to reconstitute complicated cellular processes. For the plasma membrane (PM), this gap was bridged by the establishment of giant PM vesicles (GPMVs). These native membranes have facilitated studies of protein and lipid diffusion, protein interactions, electrophysiology, fluorescence analysis of lateral domain formation and protein and lipid partitioning as well as mechanical membrane properties and remodeling. The endoplasmic reticulum (ER) is key to a plethora of biological processes in any eukaryotic cell. However, its intracellular location and dynamic and intricate tubular morphology makes it experimentally even less accessible than the PM. A model membrane, which will allow the afore-mentioned types of studies on GPMVs to be performed on ER membranes outside the cell, is therefore genuinely needed. Here, we introduce the formation of giant ER vesicles, termed GERVs, as a new tool for biochemistry and biophysics. To obtain GERVs, we have isolated ER membranes from Saccharomyces cerevisiae and fused them by exploiting the atlastin-like fusion protein Sey1p. We demonstrate the production of GERVs and their utility for further studies.


Results and Discussion
Purification and fusion of microsomes. S. cerevisiae cells that express Sey1p were grown and harvested.
Cell walls were digested, the resulting spheroplasts disrupted and ER membranes purified by subcellular fractionation according to Wuestehube & Schekman (1992) 21 with modifications. During the isolation process, the intricate ER membrane network fragments into ER-derived vesicles called microsomes. Marker proteins for the different organelles 22 were used to optimize the preparation and show the successful purification of microsomes (Fig. 1b, Supplementary Fig. S1). The GTPase Sey1p is known to fuse opposing membranes by dimerization upon GTP binding 18,19 . Addition of GTP to isolated Sey1p-overexpressing ER membranes caused fusion and resulted in GERVs (Fig. 1c). GERVs were also formed when purified ER membranes were genetically enriched with Sey1p and a further ER-membrane protein (Bet1p-mCherry, Fig. 1d).
Optimization of fusion conditions. To establish optimal fusion conditions for GERV formation, GTP concentration was varied. Fluorescently labeled microsomes were incubated with 0 to 50 mM GTP (Fig. 2). The highest yield of GERVs was obtained at 5 mM GTP. As small vesicles are indistinguishable from unfused microsomes, only vesicles larger than 2 µm were counted. Most GERVs had diameters up to 3 µm while some measured up to 10 µm in diameter (Fig. 2a). At higher GTP concentrations, the overall yield of GERVs declined. Hence, all further experiments were carried out at 5 mM GTP.
Next, we tested if, once formed, GERVs are stable in the absence of GTP. To this end, the enzyme apyrase, which breaks down GTP to GMP and phosphate ( Supplementary Fig. S2), was added to preformed GERVs. Stability was monitored by assessing the number and sizes of GERVs at different time points (Fig. 2b). Even 4 hours after apyrase addition, there is still a considerable number of GERVs of all the sizes. Hence, after formation, excess GTP is no longer necessary to maintain GERV structure. The quality of the GERV lipid bilayer membranes was routinely judged by visual inspection of confocal overview images (Fig. 1d, Fig. S4a). It can be confirmed by quantitative image analysis (Fig. S4c). Areas with adhering aggregates are clearly distinguished from areas consisting of uniform bilayer membranes.
Proof-of-principle: GERVs as a membrane model. To demonstrate the utility and versatility of the new, native model membrane, GERVs were employed in three types of fluorescence microscopy-based experiments. Firstly, using a classical immunostaining approach, the translocon, which translocates newly synthesized peptides into the ER, was visualized with a non-fluorescent primary (1°) anti-Sec61 antibody in combination with a red fluorescent secondary (2°) antibody. The Sec61 translocon colocalized with the green-labeled GERV bilayer (Fig. 3a-c). Binding specificity was checked in two control experiments: The single band at the molecular weight of Sec61p in the western blot showed that anti-Sec61p binding is specific to Sec61p (Fig. 3d). Omitting the 1° antibody from the immunostaining of the GERVs showed that the fluorescent 2° antibody was no longer enriched at the membrane, arguing against unspecific binding of the 2° antibody (Fig. 3e,f). The immunostaining experiment shows that GERV membranes contain Sec61p and could be used for studies of protein translocation.
Secondly, the feasibility of incorporating additional membrane proteins into GERVs by genetic means was explored. Unlike proteo-GUV preparations, GERV preparations do not require proteins to be purified and reconstituted, thereby reducing both labor and potential loss of protein structure and function. We chose two transmembrane proteins for constructing fluorescent fusions: the SNARE protein Bet1p, which is involved in trafficking between ER and Golgi 23,24 , and the guanine nucleotide-exchange factor, Sec12p, which localizes to the GERVs larger than 2 µm in diameter and with at least one third of their perimeter free of aggregates were considered adequate for further experiments and considered. Diameters were measured in micrometers and rounded to integers for classification. Incidence values are averages from four independent preparations of GERVs. From each of the four preparations, aliquots were taken and subjected to nucleotide concentrations between 0 to 50 mM GTP. In three out of the four microsome preparations, the 5 mM GTP condition yielded the largest density of GERVs. In one out of the four preparations, 10 mM GTP was most successful. (b) GERV stability. The number and size distribution of the GERVs were evaluated without apyrase (0 h) and 0.5 h, 2 h, and 4 h after addition of 0.01 U ml −1 apyrase. Quantification criteria were applied as described for (a). Values are averages from two apyrase assays. (2020) 10:3100 | https://doi.org/10.1038/s41598-020-59700-1 www.nature.com/scientificreports www.nature.com/scientificreports/ ER 25 . GERV-formation from microsomes of Bet1p-mCherry expressing cells (Fig. 1d) shows that the incorporation of an additional membrane-protein did not obstruct GERV formation.
To study multiple membrane proteins of interest, GERVs offer a flexible way of incorporating multiple membrane proteins by exploiting the fusion between microsome populations (Fig. 4). Microsomes purified from Sey1p-cells expressing red-fluorescent Bet1p-mCherry and those from Sey1p-cells expressing green-fluorescent Sec12p-sfGFP were mixed and observed to fuse to each other in the presence of GTP, generating double-labeled GERVs, which contained both Bet1p-mCherry and Sec12p-sfGFP (Fig. 4).
Thirdly, we analyzed the diffusion of a transmembrane protein in GERVs by fluorescence correlation spectroscopy (FCS). FCS has been used for measuring the mobility of membrane components in many applications. It is readily performed on the PM, on GPMVs, on GUVs and on other model membranes 6,[26][27][28][29] . FCS and its dual-color cross-correlation variant also allow analyzing binding of molecules to native and artificial membranes [29][30][31] . In contrast to the PM, the topology of the ER does not allow a straight-forward application of FCS and related  www.nature.com/scientificreports www.nature.com/scientificreports/ techniques to quantitate molecular mobility and binding. We therefore tested if GERVs with their quasi-planar topology can serve for FCS.
Since FCS requires a low density of fluorescent particles, whereas in confocal imaging higher concentrations are preferred, microsomes from Sey1p-cells expressing green fluorescent Bet1p-sfGFP and microsomes from Sey1p-cells expressing Bet1p-mCherry were mixed at a 1: 4000 ratio (based on total protein concentrations). This approach again highlights the flexibility bestowed by fusing microsomes from separate cellular preparations. Resulting GERVs were imaged in the red channel (Fig. 5a,b) and FCS measurements performed in the green sfGFP-channel (Fig. 5c), yielding a diffusion coefficient of D = (0.28 ± 0.1) µm 2 s −1 . The diffusion of the single span transmembrane protein Bet1p-sfGFP in the GERVs was approximately 9-fold slower compared to the diffusion of Alexa488-labeled Bet1p in artificial GUVs, prepared from 'major-minor mix' 32 , a mixture of predominantly unsaturated lipids (Supplementary Fig. S3).
In GPMVs, Worch et al. 29 found the diffusion of a single-span transmembrane protein to be slowed down by a factor of 5.5 compared to GUVs from unsaturated lipids. In analogy to GPMVs, the feasibility of FCS measurements on GERVs lays the foundation for comparative analyses of the diffusion of membrane components in GERVs and GUVs, including investigations of heterogeneity and compartmentalization. Moreover, recruitment and affinities of proteins interacting with the ER could be quantitated using this novel tool, whose complexity lies in between cells and artificial model membranes.

conclusion
GERVs are introduced as a new model membrane tool for investigating the plethora of processes connected to the ER membrane. Proof-of-principle applications involving fluorescent immunostaining as well as combinations of fluorescent membrane protein fusions are demonstrated. The membranes are amenable to confocal imaging as well as diffusion analysis by FCS. Further applications can be envisioned in analogy to and beyond GPMVs 33 . GERVs may be used to investigate enzyme functions linked to the ER membrane, lipid metabolism, amyloid fibril formation and effects of drugs. They may facilitate membrane protein production and serve as starting material for other model membranes, such as continuous supported membranes. In conclusion, we expect that this membrane tool will be highly useful in a large range of future studies in the field of membranes.

Material and Methods
Strains and vectors. The sequence of Sey1p was purchased from Dharmacon (Horizon Discovery) in a BG1805 vector. A stop codon was included between the Sey1p sequence and tag-sequences via polymerase chain reaction (PCR) with the following primers: 5′-GCAAAAAGAAAAA TGA AACCCAGCTTTCT and 5′AGAAAGCTGGGTT TCA TTTTTCTTTTT GC. Sec12p-sfGFP and Bet1p-sfGFP sequences were embedded into the GAL1-promotor controlled single copy vector pGAL413 34 . Bet1p-mCherry was embedded in pGAL415 34 . Cloning was performed using the conventional restriction site cloning procedure for Bet1p-sfGFP and the InFusion Cloning Kit (Takara) for Sec12p-sfGFP and Bet1p-mCherry. Used primers were: Bet1p-mCherry 5′-GGA TTC TAG AAC TAG TAT GTC AAG TAG ATT TGC AGG  The code for an alanine was exchanged against the code for lysine to prevent dimerization 35 . Vectors were transformed into BY4547 cells kindly provided by Prof. Karin Breunig (Institute of Genetics, University of Halle-Wittenberg, Germany) using the protocol by Akada et al. 36 with the modification that salmon sperm DNA (Thermo Fisher) was used instead of RNA. Sequence of resulting vectors were verified by sequencing. www.nature.com/scientificreports www.nature.com/scientificreports/ Cell culture. Yeast cells were grown in minimal medium with 2% (w/v) raffinose as carbon source at 30 °C, shaking at 120 rpm until an optical density of 0.6 at 600 nm was reached. For gene expression 2% (w/v) galactose were added. Cultures were incubated for 14 h at 20 °C with shaking.
ER-membrane preparation. ER membranes (microsomes) were purified as described by Wuestehube and Schekman in 1992 21 with the following modifications: For cell wall digestion, in addition to lyticase, chitinase (0.5 U ml −1 ) was added and the incubation time prolonged to two hours. After the sucrose gradient centrifugation, the microsome fraction was pelleted and resuspended in 19% (v/v) OptiPrep (Sigma-Aldrich), which was part of a nine step OptiPrep gradient with concentrations ranging from 24% to 10% (v/v) OptiPrep. The gradient was centrifuged for 16 h at 4 °C at 100.000 × g (acc5/dec7) in an MLS50 swing out rotor (Optima Max-XP, Beckmann). The membrane fraction with the highest density was harvested, pelleted and resuspended in B88-buffer (20 mM HEPES, pH 6.8, 150 mM potassium acetate, 5 mM magnesium acetate, 250 mM sorbitol) for further use. To confirm the purity of the ER fraction, organelle-specific marker proteins were quantitated by either a western blot or a functional enzyme assay. Western blots were carried out with antibodies against Sec61p as an ER marker (anti-Sec61p kindly provided by Prof. Martin Spiess), against Kex2 for the Golgi (abcam), against Nop9 for the nuclear membrane (Anti-Fibrillarin, Antikoerper-online.de) and against V-ATPase1 for the plasma membrane (Thermo Scientific). Enzyme assays were performed for the vacuolar marker γ-glutamyltransferase (BioVision) and the mitochondrial protein succinate dehydrogenase (Sigma Aldrich). For each marker, the ratio of the signals obtained on the final fraction (i.e., the harvested optiprep fraction) and on the starting fraction (i.e., the spheroplasts) was calculated in order to evaluate the degree of purification of the ER membranes. A marker ratio above one represents enrichment and a marker ratio below one represents depletion of the respective organelle in the final fraction. Immunostaining procedure. FM1-43 labeled GERVs were grown at 5 mM GTP for 2 h in a 96-well plate with glass coverslip bottom, filled with 150 µl of a microsomal membrane suspension. The supernatant was carefully reduced and replaced by a solution of anti-Sec61p antibody from rabbit (kindly provided by Prof. Martin Spieß) and 3% (w/v) bovine serum albumin (BSA) in B88-buffer (20 mM HEPES, pH 6.8, 150 mM potassium acetate, 5 mM magnesium acetate, 250 mM sorbitol). After 1 h of incubation the sample was washed 3 times with B88-buffer. After each buffer exchange the sample was allowed to rest for 15 min. Afterwards, the secondary antibody (anti-rabbit-AlexaFluor647, from abcam) in B88-buffer with 3% BSA was added and incubated for 1 h. Again, the sample was washed 3 times with B88-buffer.
Confocal fluorescence microscopy. Membranes were imaged on an LSM710/ConfoCor3 setup (Carl-Zeiss, Germany) using a 40 × /1.2 N.A. water immersion objective. FM1-43 and sfGFP were excited with a 488 nm laser line, mCherry was excited with a 561 nm laser and AlexaFluor647 with a 633 nm laser. A 488/561 or 488/561/633 main beam splitter was used. Two-color images were taken sequentially in different tracks. Fluorescence was detected using photomultiplier (PMT) detectors. For sfGFP and FM1-43, fluorescence was collected in the range of 495 to 595 nm, for mCherry from 585 to 740 nm and for AlexaFluor647 from 655 to 740 nm. Using the Carl-Zeiss ZEN2009 software, a non-linear intensity look-up table with γ = 0.45 was applied in Fig. 1c  (right panel only), 3a-c, 3e-f, and 4a-c to facilitate discernibility of membranes.

Fluorescence correlation spectroscopy (FCS). Microsomes purified from Sey1p-cells expressing
Bet1p-sfGFP and those purified from Sey1p-cells expressing Bet1p-mCherry were mixed at a 1: 4000 ratio and incubated with 5 mM GTP for 2 h at room temperature. The ratio was chosen to ensure that the resulting GERVs have a low density of green-fluorescent Bet1p-sfGFP that is suitable for FCS and a higher density of red-fluorescent Bet1p-mCherry that facilitates visualization of the GERVs by confocal microscopy.
FCS analysis using the LSM710/ConfoCor3 setup was performed on 8 GERVs (from two organelle preparations) and 6 GUVs, which were at least 4.5 µm in diameter. For the diffusion measurements, the membrane at the top of the Bet1p-sfGFP-GERV or Bet1p-Alexa488-GUV (see SI) was placed in the center of the FCS detection volume using confocal imaging, followed by an axial scan of the FCS detection volume to find the maximum count-rate. FCS measurements were performed using a 40 × /1.2 N.A. water immersion objective, the 488 nm argon ion laser line, 5.9 µW laser power for sfGFP and 47 µW for Alexa488 (see SI). A 488/561 main beam splitter and an emission filter of 505-540 nm was used for sfGFP and a 488 main beam splitter and a longpass emission filter (505 nm) for Alexa488. An avalanche photo diode was used for detection.
Measurements were performed for at least two times 30 s. The fluorescence fluctuations were software-correlated and fit with the standard FCS model equation G(τ) for 2D-diffusion and fluorophore blinking using the ZEN2009 software, (2020) 10 where N is the average number of particles, F dark the average fraction of fluorophores in the dark state, τ dark the dark state relaxation time and τ diff the diffusion time. The resulting diffusion time τ diff was used to calculate the diffusion coefficient D, where ω o represents the lateral 1/e² radius of the detection volume.
To calibrate the size of the detection volume, the diffusion of Alexa488-hydrazide was measured. The resulting ω o was determined using a diffusion coefficient of Alexa488-hydrazide of 435 µm 2 s −1 37 .