1. Biochemistry and Chemical Biology
  2. Structural Biology and Molecular Biophysics
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Homo-oligomerization of the human adenosine A2A receptor is driven by the intrinsically disordered C-terminus

  1. Khanh Dinh Quoc Nguyen
  2. Michael Vigers
  3. Eric Sefah
  4. Susanna Seppälä
  5. Jennifer Paige Hoover
  6. Nicole Star Schonenbach
  7. Blake Mertz
  8. Michelle Ann O'Malley  Is a corresponding author
  9. Songi Han  Is a corresponding author
  1. Department of Chemistry and Biochemistry, University of California, Santa Barbara, United States
  2. Department of Chemical Engineering, University of California, Santa Barbara, United States
  3. C. Eugene Bennett Department of Chemistry, West Virginia University, United States
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Cite this article as: eLife 2021;10:e66662 doi: 10.7554/eLife.66662

Abstract

G protein-coupled receptors (GPCRs) have long been shown to exist as oligomers with functional properties distinct from those of the monomeric counterparts, but the driving factors of oligomerization remain relatively unexplored. Herein, we focus on the human adenosine A2A receptor (A2AR), a model GPCR that forms oligomers both in vitro and in vivo. Combining experimental and computational approaches, we discover that the intrinsically disordered C-terminus of A2AR drives receptor homo-oligomerization. The formation of A2AR oligomers declines progressively with the shortening of the C-terminus. Multiple interaction types are responsible for A2AR oligomerization, including disulfide linkages, hydrogen bonds, electrostatic interactions, and hydrophobic interactions. These interactions are enhanced by depletion interactions, giving rise to a tunable network of bonds that allow A2AR oligomers to adopt multiple interfaces. This study uncovers the disordered C-terminus as a prominent driving factor for the oligomerization of a GPCR, offering important insight into the effect of C-terminus modification on receptor oligomerization of A2AR and other GPCRs reconstituted in vitro for biophysical studies.

Introduction

G protein-coupled receptors (GPCRs) have long been studied as monomeric units, but accumulating evidence demonstrates that these receptors can also form homo- and hetero-oligomers with far-reaching functional implications. The properties emerging from these oligomers can be distinct from those of the monomeric protomers in ligand binding (El-Asmar et al., 2005; Casadó-Anguera et al., 2016; Guitart et al., 2014; Yoshioka et al., 2001), G protein coupling (Cristóvão-Ferreira et al., 2013; Cordomí et al., 2015; González-Maeso et al., 2007; Lee et al., 2004; Rashid et al., 2007), downstream signaling (Liu et al., 2016; Hilairet et al., 2003; Rozenfeld and Devi, 2007; Borroto-Escuela et al., 2010), and receptor internalization/desensitization (Ecke et al., 2008; Stanasila et al., 2003; Faklaris et al., 2015). With the vast number of genes identified in the human genome (Takeda et al., 2002), GPCRs are able to form a daunting number of combinations with unprecedented functional consequences. The existence of this intricate network of interactions among GPCRs presents major challenges and opportunities for the development of novel therapeutic approaches (Dorsam and Gutkind, 2007; Farran, 2017; Schonenbach et al., 2015; Ferré et al., 2014; Bräuner-Osborne et al., 2007; George et al., 2002). Hence, it is crucial to identify the driving factors of GPCR oligomerization, such that this process can be more deliberately controlled to facilitate structure-function studies of GPCRs.

GPCR oligomers with multiple interfaces (Song et al., 2020; Ghosh et al., 2014; Periole et al., 2012; Fanelli and Felline, 2011; Liu et al., 2012) can give rise to myriad ways by which these complexes can be formed and their functions modulated. In the crystal structure of the turkey β1-adrenergic receptor (β1AR), the receptor appears to dimerize via two different interfaces, one formed via TM4/TM5 (transmembrane domains 4/5) and the other via TM1/TM2/H8 (helix 8) contacts (Huang et al., 2013). Similarly, in the crystal structure of the antagonist-bound μ-opioid receptor (μ-OR), the protomers also dimerize via two interfaces; however, only one of them is predicted to induce a steric hindrance that prevents activation of both protomers (Manglik et al., 2012), hinting at interface-specific functional consequences. A recent computational study predicted that the adenosine A2A receptor (A2AR) forms homodimers via three different interfaces and that the resulting dimeric architectures can modulate receptor function in different or even opposite ways (Fanelli and Felline, 2011). All the above-mentioned interfaces are symmetric, meaning that the two protomers are in face-to-face orientations, hence forming strictly dimers. Asymmetric interfaces, reported in M3 muscarinic receptor (Thorsen et al., 2014), rhodopsin (Fotiadis et al., 2006; Fotiadis et al., 2003; Liang et al., 2003), and opsin (Liang et al., 2003), are in contrast formed with the protomers positioning face-to-back, possibly enabling the association of higher-order oligomers.

Not only do GPCRs adopt multiple oligomeric interfaces, but various studies also suggest that these interfaces may dynamically rearrange to activate receptor function (Xue et al., 2015). According to a recent computational study, A2AR oligomers can adopt eight different interfaces that interconvert when the receptor is activated or when there are changes in the local membrane environment (Song et al., 2020). Similarly, a recent study that combined experimental and computational data proposed that neurotensin receptor 1 (NTS1R) dimer is formed by ‘rolling’ interfaces that coexist and interconvert when the receptor is activated (Dijkman et al., 2018). Clearly, meaningful functional studies of GPCRs require exploring their dynamic, heterogeneous oligomeric interfaces.

The variable nature of GPCR oligomeric interfaces suggests that protomers of GPCR oligomers may be connected by tunable interactions. In this study, we explore the role of an intrinsically disordered region (IDR) of a model GPCR that could engage in diverse non-covalent interactions, such as electrostatic interactions, hydrogen bonds, or hydrophobic interactions. These non-covalent interactions are readily tunable by external factors, such as pH, salts, and solutes, and further can be entropically enhanced by depletion interactions (Asakura and Oosawa, 1958; Yodh et al., 2001; Marenduzzo et al., 2006), leading to structure formation and assembly (Milles et al., 2018; Wicky et al., 2017; Szasz et al., 2011; Goldenberg and Argyle, 2014; Qin and Zhou, 2013; Cino et al., 2012; Soranno et al., 2014; Zosel et al., 2020). In a system where large protein molecules and small solute particles typically coexist in solution, assembly of the protein molecules causes their excluded volumes to overlap and the solvent volume accessible to the non-protein solutes to increase, raising the entropy of the system. The type and concentration of solutes or ions can also remove water from the hydration shell around the proteins, further enhancing entropy-driven protein-protein association in what is known as the hydrophobic effect (Tanford, 1980; Tanford, 1978; Pratt and Chandler, 1977; van der Vegt et al., 2017). This phenomenon is applied in the precipitation of proteins upon addition of so-called salting-out ions according to the Hofmeister series (Hofmeister, 1888; Hyde et al., 2017; Yang, 2009). The ability of IDRs to readily engage in these non-covalent interactions motivates our focus on the potential role of IDRs in driving GPCR oligomerization.

The cytosolic carboxy (C-)terminus of GPCRs is usually an IDR (Tovo-Rodrigues et al., 2014; Jaakola et al., 2005). Varying in length among different GPCRs, the C-terminus is commonly removed in structural studies of GPCRs to enhance receptor stability and conformational homogeneity. A striking example is A2AR, a model GPCR with a particularly long, 122-residue, C-terminus that is truncated in all published structural biology studies (Song et al., 2020; Fanelli and Felline, 2011; García-Nafría et al., 2018; Sun et al., 2017; Lebon et al., 2011; Xu et al., 2011; Doré et al., 2011; Jaakola et al., 2008; Carpenter et al., 2016; Hino et al., 2012). However, evidence is accumulating that such truncations—shown to affect GPCR downstream signaling (Koretz et al., 2021; Navarro et al., 2018a; Jain and McGraw, 2020)—may abolish receptor oligomerization (Schonenbach et al., 2016; Svetlana and Devi, 1997). A study using immunofluorescence has demonstrated that C-terminally truncated A2AR does not show protein aggregation or clustering on the cell surface, a process readily observed in the wild-type form (Burgueño et al., 2003). Our recent study employing a tandem three-step chromatography approach uncovered the impact of a single-residue substitution of a C-terminal cysteine, C394S, in reducing the receptor homo-oligomerization in vitro (Schonenbach et al., 2016). In the context of heteromerization, mass spectrometry and pull-down experiments have demonstrated that A2AR-D2R dimerization occurs via direct electrostatic interactions between the C-terminus of A2AR and the third intracellular loop of D2R (Ciruela et al., 2004). These results all suggest that the C-terminus may participate in A2AR oligomer formation. However, no studies to date have directly and systematically investigated the role of the C-terminus, or any IDRs, in GPCR oligomerization.

This study focuses on the homo-oligomerization of the human adenosine A2AR, a model GPCR, and seeks to address (i) whether the C-terminus engages in A2AR oligomerization, and if so, (ii) whether the C-terminus forms multiple oligomeric interfaces. We use size-exclusion chromatography (SEC) to assess the oligomerization levels of A2AR variants with strategic C-terminal modifications: mutations of a cysteine residue C394 and a cluster of charged residues 355ERR357, as well as systematic truncations at eight different sites along its length. We complemented our experimental study with an independent molecular dynamics (MD) simulation study of A2AR dimers of five C-terminally truncated A2AR variants designed to mirror the experimental constructs. We furthermore examined the oligomerization level of select C-terminally modified A2AR variants under conditions of varying ionic strength ranging from 0.15 to 0.95 M. To verify whether the A2AR oligomer populations are thermodynamic products, we performed a series of SEC analyses on SEC-separated monomer and dimer/oligomer populations to observe their repopulation into monomer and dimer/oligomer populations. Finally, to test whether the C-termini directly and independently promote A2AR oligomerization, we recombinantly expressed the entire A2AR C-terminal segment sans the transmembrane portion of the receptor and investigated its solubility and assembly properties with increasing ion concentration and temperature. This is the first study designed to uncover the role of the intrinsically disordered C-terminus on the oligomerization of a GPCR.

Results

This study systematically investigates the role of the C-terminus on A2AR oligomerization and the nature of the involved interactions through strategic mutations and truncations at the C-terminus as well as modulation of the ionic strength of solvent. All experiments were done at 4°C unless stated otherwise. The experimental assessment of A2AR oligomerization relies on SEC analysis.

SEC quantifies A2AR oligomerization

We performed SEC analysis on a mixture of ligand-active A2AR purified from a custom synthesized antagonist affinity column (Figure 1—figure supplement 1A). Distinct oligomeric species were separated and eluted in the following order: high-molecular-weight (HMW) oligomer, dimer, and monomer (Figure 1 and Figure 1—figure supplement 1B). This peak assignment has been verified with SEC-MALS (multi-angle light scattering) experiments, as detailed in a previous publication (Schonenbach et al., 2016). The population of each oligomeric species was quantified as the integral of each Gaussian from a multiple-Gaussian curve fit of the SEC signal. The reported standard errors were calculated from the variance of the fit that do not correspond to experimental errors (see Supplementary file 1 and Figure 1—figure supplement 2 for SEC data corresponding to all A2AR variants in this study). As this study sought to identify the factors that promote A2AR oligomerization, the populations with oligomeric interfaces (i.e., dimer and HMW oligomer) were compared with those without such interfaces (i.e., monomer). Hence, the populations of the HMW oligomer and dimer were expressed relative to the monomer population in arbitrary units as monomer-equivalent concentration ratios, henceforth referred to as population levels (Figure 1).

Figure 1 with 2 supplements see all
Method for collecting size-exclusion chromatography (SEC) data and assessing A2AR oligomerization.

The SEC data is recorded every second as absorbance at 280 nm. The baseline is corrected to ensure uniform fitting and integration across the peaks. The areas under the curve, resulting from a multiple-Gaussian curve fit, express the population of each oligomeric species. The reported standard errors of integration are within a 95% confidence interval and are calculated from the variance of the fit, not experimental errors. The levels of high-molecular-weight oligomer and dimer are expressed relative to the monomeric population in arbitrary units. A representative calculation defining the oligomer levels is given in the box.

C-terminal amino acid residue C394 contributes to A2AR oligomerization

To investigate whether the C-terminus of A2AR is involved in receptor oligomerization, we first examined the role of residue C394 as a previous study demonstrated that the mutation C394S dramatically reduced A2AR oligomer levels (Schonenbach et al., 2016). The C394S mutation was replicated in our experiments, alongside other amino acid substitutions for the cysteine, namely alanine, leucine, methionine, or valine, generating five A2AR-C394X variants. The HMW oligomer and dimer levels of A2AR wild-type (WT) were compared with those of the A2AR-C394X variants. We found that the dimer level of A2AR-WT was significantly higher than that of the A2AR-C394X variants (WT: 1.14; C394X: 0.24–0.57; Figure 2A). A similar result, though less pronounced, was observed when the HMW oligomer and dimer levels were considered together (WT: 1.34; C394X: 0.59–1.21; Figure 2A). This suggests that residue C394 plays a role in A2AR oligomerization, and even more prominently in A2AR dimerization.

Residue C394 helps stabilize A2AR oligomerization via disulfide bonds.

(A) The effect of C394X substitutions on A2AR oligomerization. The levels of dimer (dark colors) and high-molecular-weight oligomer (light colors) are expressed relative to the monomeric population in arbitrary units, with reported errors calculated from the variance of the fit, not experimental variation. (B) Line densitometry of western blot bands on size-exclusion chromatography (SEC)-separated dimeric populations of A2AR-WT and Q372ΔC with and without 5 mM TCEP. The level of dimer is expressed relative to the monomeric population in arbitrary units similarly to the SEC analysis. MagicMark protein ladder (LC5602) is used as the molecular weight standard.

Figure 2—source data 1

Raw western blot of size-exclusion chromatography-separated dimeric populations of A2AR-WT with and without 5 mM TCEP.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data1-v2.tif.zip
Figure 2—source data 2

Raw western blot of size-exclusion chromatography-separated dimeric populations of A2AR-WT with and without 5 mM TCEP.

MagicMark protein ladder (LC5602) is used as the molecular weight standard.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data2-v2.tif.zip
Figure 2—source data 3

Raw western blot of size-exclusion chromatography-separated dimeric populations of A2AR-Q372ΔC with and without 5 mM TCEP.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data3-v2.tif.zip
Figure 2—source data 4

Raw western blot of size-exclusion chromatography-separated dimeric populations of A2AR-Q372ΔC with and without 5 mM TCEP.

MagicMark protein ladder (LC5602) is used as the molecular weight standard.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data4-v2.tif.zip
Figure 2—source data 5

Raw size-exclusion chromatography data of A2AR-WT and C394X variants.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig2-data5-v2.xlsx

To test whether residue C394 stabilizes A2AR dimerization by forming disulfide linkages, we incubated the SEC-separated dimers of A2AR-WT and A2AR-Q372ΔC with 5 mM of the reducing agent TCEP, followed by SDS-PAGE and western blotting. The population of each species was determined as the area under the densitometric trace. The dimer level was then expressed as monomer-equivalent concentration ratios in a manner similar to that of the SEC experiment described above. Upon incubation with TCEP, the dimer level of the A2AR-WT sample decreased from 1.14 to 0.51 (Figure 2B). This indicates that disulfide bond formation via residue C394 is one possible mechanism for A2AR dimerization. Interestingly, the dimer level of the A2AR-Q372ΔC sample also decreased from 0.68 to 0.22 (Figure 2B). This suggests that there may exist other inter-A2AR disulfide bonds that do not involve residue C394. Still, in both cases, a clearly visible population of A2AR dimer persists, even after reduction of disulfide bonds via TCEP (Figure 2B), suggesting that there must be additional interfacial sites that help drive A2AR dimer/oligomerization.

C-terminus truncation systematically reduces A2AR oligomerization

To determine which interfacial sites in the C-terminus other than the disulfide-bonded cysteines drive A2AR dimer/oligomerization, we carried out systematic truncations at eight sites along the C-terminus (A316, V334, G344, G349, P354, N359, Q372, and P395), generating eight A2AR-ΔC variants (Figure 3A). The A2AR-A316ΔC variant corresponds to the removal of the entire disordered C-terminal region and is used in all published structural studies of A2AR (Martynowycz et al., 2020; Song et al., 2020; García-Nafría et al., 2018; Sun et al., 2017; Carpenter et al., 2016; Hino et al., 2012; Xu et al., 2011; Lebon et al., 2011; Doré et al., 2011; Jaakola et al., 2008; Fanelli and Felline, 2011). Using the SEC analysis described earlier (Figure 1), we evaluated the HMW oligomer and dimer levels of the A2AR-ΔC variants relative to that of the A2AR full-length-wild-type (FL-WT) control. Both the dimer and the total oligomer levels of A2AR decreased progressively with the shortening of the C-terminus, with almost no oligomerization detected upon complete truncation of the C-terminus at site A316 (Figure 3B). This result shows that the C-terminus drives A2AR oligomerization, with multiple potential interaction sites positioned along much of its length.

Truncating the C-terminus systematically affects A2AR oligomerization.

(A) Depiction of where the truncation points are located on the C-terminus, with region 354–359 highlighted (in black) showing critical residues. (B) The levels of dimer and high-molecular-weight (HMW) oligomer are expressed relative to the monomeric population as an arbitrary unit and plotted against the residue number of the truncation sites, with reported errors calculated from the variance of the fit, not experimental variation. Region 354–359 is emphasized (in black and gray) due to a drastic change in the dimer and HMW oligomer levels. (C) The dependence of A2AR oligomerization on three consecutive charged residues 355ERR357. The substitution of residues 355ERR357 to 355AAA357 is referred to as the ERR:AAA mutations. The levels of dimer and HMW oligomer are expressed relative to the monomeric population as an arbitrary unit, with reported errors calculated from the variance of the fit, not experimental variation.

Figure 3—source data 1

Raw size-exclusion chromatography data of A2AR-WT and C-terminally truncated ΔC variants.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig3-data1-v2.xlsx

Interestingly, there occurred a dramatic decrease in the dimer level between the N359 and P354 truncation sites, from a value of 0.81 to 0.19, respectively (Figure 3B). A similar result, though less pronounced, was observed on the total oligomer level, with a decrease from 1.09 to 0.62 for the N359 and P354 truncation sites, respectively (Figure 3B). Clearly, the C-terminal segment encompassing residues 354–359 (highlighted in black in Figure 3A) is a key constituent of the A2AR oligomeric interface.

Since segment 354–359 contains three consecutive charged residues (355ERR357; Figure 3A), which could be involved in electrostatic interactions, we hypothesized that this 355ERR357 cluster could strengthen inter-protomer A2AR-A2AR association. To test this hypothesis, residues 355ERR357 were substituted by 355AAA357 on A2AR-FL-WT and A2AR-N359ΔC to generate A2AR-ERR:AAA variants (Figure 3C). We then compared the HMW oligomer and dimer levels of the resulting variants with controls (same A2AR variants but without the ERR:AAA mutations). We found that the ERR:AAA mutations had varied effects on the dimer level: decreasing for A2AR-FL-WT (ctrl: 0.49; ERR:AAA: 0.29) but increasing for A2AR-N359ΔC (ctrl: 0.33; ERR:AAA: 0.48) (Figure 3C). In contrast, the ERR:AAA mutations reduced the HMW oligomer level of both A2AR-FL-WT (ctrl: 0.88; ERR:AAA: 0.66) and A2AR-N359ΔC (ctrl: 0.68; ERR:AAA: 0.38) (Figure 3C). Consistently, the ERR:AAA mutation lowered the total oligomer level of both A2AR-FL-WT (ctrl: 1.37; ERR:AAA: 0.94) and A2AR-N359ΔC (ctrl: 1.01; ERR:AAA: 0.85) (Figure 3C). These results suggest that the charged residues 355ERR357 participate in A2AR oligomerization, with a greater effect in the context of a longer C-terminus and for forming higher-order oligomers. The question then arises as to what types of interactions are formed along the C-terminus that help stabilize A2AR oligomerization.

C-terminus truncation disrupts complex network of non-bonded interactions necessary for A2AR dimerization

Given that the structure of A2AR dimers or oligomers is unknown, we next used MD simulations to seek molecular-level insights into the role of the C-terminus in driving A2AR dimerization and to gain an understanding of what types of interactions and sites may be involved in this process. First, to explore A2AR dimeric interface, we performed coarse-grained (CG) MD simulations using the Martini force field (see Materials and methods for details). The Martini force field can access the length and time scales relevant to membrane protein oligomerization, albeit at the expense of atomic-level details. We carried out a series of CGMD simulations on five A2AR-ΔC variants designed to mirror the experiments by systematic truncation at five sites along the C-terminus (A316, V334, P354, N359, and C394). Our results revealed that A2AR dimers were formed with multiple interfaces, all involving the C-terminus only (Figure 4A). The transmembrane heptahelical bundles were not a part of the dimeric interfaces as they all showed distances greater than the minimum distance criterion of 7 Å for interacting helices. The vast majority of A2AR dimers were symmetric, with the C-termini of the protomers directly interacting with each other. A smaller fraction of the dimers had asymmetric orientations, with the C-terminus of one protomer interacting with other parts of the other protomer, such as ICL2 (the second intracellular loop) and ICL3 (Figure 4A).

Non-bonded interactions of the extended C-terminus of A2AR play a critical role in stabilization of the dimeric interface.

(A) Dimer configurations from cluster analysis in GROMACS of the 394-residue variant identify two major clusters involving either (1) the C-terminus of one protomer and the C-terminus, ICL2, and ICL3 of the second protomer or (2) the C-terminus of one protomer and ICL2, ICL3, and ECL2 of the second protomer. Spheres: residues forming intermolecular electrostatic contacts. (B) Average number of residues that form electrostatic contacts as a function of sequence length of A2AR. (C) Average number of residues that form hydrogen bonds as a function of sequence length of A2AR. The criteria for designating inter-A2AR contacts as electrostatic interactions or hydrogen bonds are described in detail in Materials and methods.

Figure 4—source data 1

Detailed data regarding the multiple interfaces of A2AR and the network of non-bonded interactions that stabilize these interfaces.

(A) Dimer configurations from cluster analysis in GROMACS of the 394-residue variant. (B) Average number of residues that form electrostatic contacts as a function of sequence length of A2AR. (C) Average number of residues that form hydrogen bonds as a function of sequence length of A2AR.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig4-data1-v2.xlsx

Our observation of multiple A2AR oligomeric interfaces, which is consistent with previous studies (Fanelli and Felline, 2011; Song et al., 2020), suggests that tunable, non-covalent intermolecular interactions may be involved in receptor dimerization. We first dissected two key non-covalent interaction types: electrostatic and hydrogen bonding interactions. Electrostatic interactions were calculated from CGMD simulations, while hydrogen bonds were quantified from atomistic MD simulation as the CG model merges all hydrogens into a CG bead and hence cannot report on hydrogen bonds. This analysis was performed on the symmetric dimers as they constituted the more dominant population. With the least truncated A2AR variant containing the longest C-terminus, A2AR-C394ΔC, we observed an average of 15.9 electrostatic contacts (Figure 4B) and 26.7 hydrogen bonds (Figure 4C) between the C-termini of the protomers. This result shows that both electrostatic interactions and hydrogen bonds can play important roles in A2AR dimer formation.

Upon further C-terminus truncation, the average number of both electrostatic contacts and hydrogen bonds involving C-terminal residues progressively declined, respectively reaching 5.4 and 6.0 for A2AR-A316ΔC (in which the disordered region of the C-terminus is removed) (Figure 4B, C). This result is consistent with the experimental result, which demonstrated a progressive decrease of A2AR oligomerization with the shortening of the C-terminus (Figure 3B). Interestingly, upon systematic truncation of the C-terminal segment 335–394, we observed in segment 291–334 a steady decrease in the average number of electrostatic contacts, from 10.4 to 7.4 (Figure 4B). This trend was even more pronounced with hydrogen bonding contacts involving segment 291–334 decreasing drastically from 21.0 to 7.0 as segment 335–394 was gradually removed (Figure 4C). This observation that truncation of a C-terminal segment reduces inter-A2AR contacts elsewhere along the C-terminus indicates that an allosteric mechanism of dimerization exists, in which an extended C-terminus of A2AR stabilizes inter-A2AR interactions near the heptahelical bundles of the dimeric complex. These results demonstrate that A2AR dimers can be formed via multiple interfaces and stabilized by an allosteric network of electrostatic interactions and hydrogen bonds along much of its C-terminus.

Ionic strength modulates oligomerization of C-terminally truncated A2AR variants

So far, we have demonstrated that the C-terminus clearly plays a role in forming A2AR oligomeric interfaces. However, it remains unclear what the driving factors of A2AR oligomerization are and whether the oligomeric populations are thermodynamic products. The variable nature of A2AR oligomeric interfaces suggests that the main driving forces must be non-covalent interactions, such as electrostatic interactions and hydrogen bonds. Modulating the solvent ionic strength is an effective method to identify the types of non-covalent interaction(s) at play. Specifically, with increasing ionic strength, electrostatic interactions are weakened (based on Debye–Hückel theory, most electrostatic bonds at a distance greater than 5 Å are screened out at an ionic strength of 0.34 M at 4°C) and depletion interactions are enhanced with salting-out salts, while hydrogen bonds remain relatively impervious. For this reason, we subjected various A2AR variants (FL-WT, FL-ERR:AAA, N359ΔC, and V334ΔC) to ionic strength ranging from 0.15 to 0.95 M by adding NaCl (buffer composition shown in Materials and methods). The HMW oligomer and dimer levels of the four A2AR variants were determined and plotted as a function of ionic strengths.

The low ionic strength of 0.15 M should not affect hydrogen bonds or electrostatic interactions if present. We found that the dimer and total oligomer levels of all four variants were near zero (Figure 5). This is a striking experimental observation: despite being shown to play a role in stabilizing A2AR dimers according to our MD simulations (Figure 4B, C), we can conclude that electrostatic and hydrogen-bonding interactions are not the dominant driving force for A2AR association. The question remains whether depletion interactions could facilitate A2AR oligomerization.

Figure 5 with 1 supplement see all
The effects of ionic strength on the oligomerization of various A2AR variants reveal the involvement of depletion interactions.

The levels of (A) dimer and (B) high-molecular-weight oligomer + dimer are expressed relative to the monomeric population as an arbitrary unit and plotted against ionic strength, with reported errors calculated from the variance of the fit, not experimental variation. NaCl concentration is varied to achieve ionic strengths of 0.15, 0.45, and 0.95 M.

Figure 5—source data 1

Raw size-exclusion chromatography data of various A2AR variants under different ionic strengths of 0.15, 0.45, and 0.95 M.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig5-data1-v2.xlsx

At higher ionic strengths of 0.45 M and 0.95 M, the dimer and total oligomer levels of A2AR-V334ΔC still remained near zero (Figure 5). In contrast, we observed a progressive and significant increase in the dimer and total oligomer levels of A2AR-FL-WT with increasing ionic strength (Figure 5). This result indicates that A2AR oligomerization is driven by depletion interactions enhanced with increasing ionic strength and that these interactions must involve the C-terminal segment after residue V334.

Upon closer examination, we recognize that at the very high ionic strength of 0.95 M the increase in the dimer and total oligomer levels was robust for A2AR-FL-WT, but less pronounced for A2AR-FL-ERR:AAA (Figure 5). Furthermore, this high ionic strength even had an opposite effect on A2AR-N359ΔC, with both its dimer and total oligomer levels abolished (Figure 5). These results indicate that the charged cluster 355ERR357 and the C-terminal segment after residue N359 promote the depletion interactions to drive A2AR oligomerization. Taken together, we can conclude that A2AR oligomerization is more robust when the C-terminus is fully present and the ionic strength higher, suggesting that depletion interactions via the C-terminus are strong driving factors of A2AR oligomerization.

The discussion of depletion interactions as driving factors assumes that A2AR dimer/oligomer populations are thermodynamic products at equilibrium with the A2AR monomer population. However, some of the A2AR dimer/oligomer populations may be kinetically stabilized. To address this question, we tested the stability and reversibility of A2AR oligomers by performing a second round of SEC on the monomer and dimer/oligomer populations of the A2AR-WT and Q372ΔC variants. We found that the SEC-separated monomers repopulate into dimer/oligomer, with the total oligomer level after redistribution comparable with that of the initial samples for both A2AR-WT (initial: 2.87; redistributed: 1.60) and Q372ΔC (initial: 1.49; redistributed: 1.40) (Figure 5—figure supplement 1A). This observation indicates that A2AR oligomer is a thermodynamic product with a lower free energy compared with that of the monomer (Figure 5—figure supplement 1B). This agrees with the results we have shown in Supplementary file 1 that the oligomer levels of A2AR-WT are consistent among replicates (1.34–2.05) and that A2AR oligomerization can be modulated with ionic strengths via depletion interactions (Figure 5).

In contrast, the SEC-separated dimer/oligomer populations do not repopulate to form monomers (Figure 5—figure supplement 1A). This observation is consistent with a published study of ours on A2AR dimers (Schonenbach et al., 2016), indicating that once the oligomers are formed, some are kinetically trapped and thus cannot redistribute into monomers. We believe that disulfide linkages are likely candidates to kinetically stabilize A2AR oligomers, as demonstrated by their redistribution into monomers only in the presence of a reducing agent (Figure 2B).

Taken together, we suggest that A2AR oligomerization is a thermodynamic process (Figure 5—figure supplement 1B), with the free energy of the dimer/oligomers lowered by depletion forces that hence increase their population relative to that of the monomers (there always exists a distribution between the two). Once formed, the redistributed dimer/oligomer populations may be kinetically stabilized by disulfide linkages. The question then arises whether inter-A2AR interactions are primarily a result of the C-termini directly interacting with one another. This question motivated us to carry out a study focused on investigating the behavior of A2AR C-terminus sans the transmembrane domains.

The isolated A2AR C-terminus is prone to aggregation

To test whether A2AR oligomerization is driven by direct depletion interactions among the C-termini of the protomers, we assayed the solubility and assembly properties of the stand-alone A2AR C-terminus—an intrinsically disordered peptide—sans the upstream transmembrane regions. Since depletion interactions can be manifested via the hydrophobic effect (van der Vegt et al., 2017), we examined whether this effect can also drive the assembly of the A2AR C-terminal peptides.

It is an active debate whether the hydrophobic effect can be promoted or suppressed by ions with salting-out or salting-in tendency, respectively (Thomas and Elcock, 2007; Graziano, 2010; Zangi et al., 2007; Grover and Ryall, 2005). We increased the solvent ionic strength using either sodium (salting-out) or guanidinium (salting-in) ions and assessed the aggregation propensity of the C-terminal peptides using UV-Vis absorption at 450 nm, which indicates the turbidity of the solution. We first observed the behavior of the C-terminus with increasing salting-out NaCl concentrations. At NaCl concentrations below 1 M, the peptide was dominantly soluble, despite showing slight aggregation at NaCl concentrations between 250 and 500 mM (Figure 6A). At NaCl concentrations above 1 M, A2AR C-terminal peptides strongly associated into insoluble aggregates (Figure 6A). Consistent with the observations made with the intact receptor (Figure 5), the A2AR C-terminus showed the tendency to progressively associate and eventually precipitate with increasing ionic strengths, suggesting that depletion interactions drive the association and precipitation of the peptides. We next observed the behavior of the C-terminus with increasing concentrations of guanidine hydrochloride (GdnHCl), which contains salting-in cations that do not induce precipitation and instead facilitate the solubilization of proteins (Heyda et al., 2017; Baldwin, 1996). Our results demonstrated that the A2AR C-terminus incubated in 4 M GdnHCl showed no aggregation propensity (Figure 6A), validating our expectation that salting-in salts do not enhance depletion interactions. These observations demonstrate that the C-terminal peptide in and of itself, outside the context of the lipid membrane and TM domain, can directly interact with other C-terminal peptides to form self-aggregates in the presence of ions, and presumably solutes, that have salting-out effects.

Figure 6 with 1 supplement see all
The A2AR C-terminus is prone to aggregation.

(A) Absorbance at 450 nm of the A2AR C-terminus in solution, with NaCl and GdnHCl concentrations varied to achieve ionic strengths 0–4 M. Inset: the solution at ionic strength 4 M achieved with NaCl. The Hofmeister series is provided to show the ability of cations to salt-out (blue) or salt-in (red) proteins. (B) SYPRO orange fluorescence of solutions containing the A2AR C-terminus as the temperature was varied from 20°C to 70°C (gray). The change in fluorescence, measured in relative fluorescence unit (RFU), was calculated by taking the first derivative of the fluorescence curve (black).

Figure 6—source data 1

Detailed data showing the propensity of A2AR C-terminus to aggregate.

(A) Absorbance at 450 nm of the A2AR C-terminus in solution, with NaCl and GdnHCl concentrations varied to achieve ionic strengths 0–4 M. (B) SYPRO orange fluorescence of solutions containing the A2AR C-terminus as the temperature was varied from 20°C to 70°C (gray). The change in fluorescence, measured in relative fluorescence unit (RFU), was calculated by taking the first derivative of the fluorescence values.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig6-data1-v2.xlsx

Attractive hydrophobic interactions among the hydrophobic residues are further enhanced when the water that solvate the protein surface have more favorable interactions with other water molecules, ions, or solutes than with the protein surface, here the truncated C-terminus (Larsen et al., 1998; Tsai and Nussinov, 1997; Tsai et al., 1997). We explored the possible contribution of hydrophobic interactions to the aggregation of the C-terminal peptides using both experimental and computational approaches. Using differential scanning fluorimetry (DSF), we gradually increased the temperature to melt the C-terminal peptides, exposing any previously buried hydrophobic residues (Figure 6—figure supplement 1A, B), which then bound to the SYPRO orange fluorophore, resulting in an increase in fluorescence signal. Our results showed that as the temperature increased, a steady rise in fluorescence was observed (Figure 6B), indicating that multiple hydrophobic residues were gradually exposed to the SYPRO dye. However, at approximately 65°C, the melt peak signal was abruptly quenched (Figure 6B), indicating that the hydrophobic residues were no longer exposed to the dye. This observation suggests that, at 65°C, enough hydrophobic residues in the C-terminal peptides become exposed such that they collapse on one another (thus expelling the bound dye molecules), resulting in aggregation. This experimental result is further supported by our CGMD computational analysis of C-terminal non-polar contacts found in A2AR symmetrical dimers (Figure 6—figure supplement 1C). Specifically, we observed an average of 60 non-polar contacts for A2AR-C394ΔC. This number progressively declined upon further C-terminus truncation, reaching 15 for A2AR-A316ΔC. Clearly, the hydrophobic effect can cause A2AR C-terminal peptides to directly associate. These results demonstrate that A2AR oligomer formation can be driven by depletion interactions among the C-termini of the protomers by non-polar contacts.

Discussion

The key finding of this study is that the C-terminus of A2AR, removed in all previously published structural studies, is directly responsible for receptor oligomerization. Using a combination of experimental and computational approaches, we demonstrate that the C-terminus stabilizes A2AR oligomers via a combination of disulfide linkages, hydrogen bonds, electrostatic interactions, and hydrophobic interactions. This diverse combination of interactions is greatly enhanced by depletion interactions, forming a network of malleable bonds that drives A2AR oligomerization and gives rise to multiple oligomeric interfaces.

Intermolecular disulfide linkages play a role in A2AR oligomerization, potentially by kinetically trapping the receptor oligomers. Among the seven cysteines that do not form intramolecular disulfide bonds (De Filippo et al., 2016; Naranjo et al., 2015; O'Malley et al., 2010), residue C394 is largely involved in stabilizing A2AR oligomers (Figure 2A). Indeed, this cysteine is highly conserved and a C-terminal cysteine is almost always present in A2AR homologs (Pándy-Szekeres et al., 2018), suggesting that it may serve an important role in vivo. There may also exist inter-A2AR disulfide linkages that do not involve residue C394 at all as the SEC-separated dimer/oligomer populations of A2AR-Q372ΔC, which lack residue C394, were still resistant to TCEP reduction (Figure 2B) and appear to be kinetically trapped (Figure 5—figure supplement 1). Such disulfide linkages may involve other cysteines in the hydrophobic core of A2AR, namely C281.54, C823.30, C1284.49, C1855.46, C2456.47, or C2546.56. Many examples exist where disulfide linkages help drive GPCR oligomerization, including the CaR-mGluR1 heterodimer (Gama et al., 2001), homodimers of mGluR5 (Romano et al., 1996), M3R (Zeng and Wess, 1999), V2R (Zhu and Wess, 1998), 5-HT4R (Berthouze et al., 2007) and 5-HT1DR (Lee et al., 2000), and even higher-order oligomers of D2R (Guo et al., 2008). Although unconventional cytoplasmic disulfide bonds have been reported (Saaranen and Ruddock, 2013; Locker and Griffiths, 1999), no study has shown how such linkages would be formed in vivo as the cytoplasm lacks the conditions and machinery required for disulfide bond formation (Gaut and Hendershot, 1993; Hwang et al., 1992; Helenius et al., 1992; Creighton et al., 1980).

The electrostatic interactions that stabilize A2AR oligomer formation come from multiple sites along the C-terminus. From a representative snapshot of a A2AR-C394ΔC dimer from our MD simulations (Figure 7A), we could visualize not only the intermolecular interactions calculated from the CGMD simulations (Figure 4B), but also intramolecular salt bridges. In particular, the 355ERR357 cluster of charged residues lies distal from the dimeric interface but still forms several salt bridges (Figure 7A, inset). This observation is supported by our experimental results showing that substituting this charged cluster with alanines reduces the total A2AR oligomer levels (Figure 3C). However, it is unclear how such salt bridges involving this 355ERR357 cluster are enhanced by depletion interactions (Figure 5) as electrostatic interactions are usually screened out at high ionic strengths. In our MD simulations, we also observed networks of salt bridges along the dimeric interface, for example, between K315 of one monomer and D382 and E384 of the other monomer (Figure 7A, inset). The innate flexibility of the C-terminus could facilitate the formation of such salt bridges, which then help stabilize A2AR dimers.

Figure 7 with 1 supplement see all
Visualizing A2AR dimeric interface and observing conformational changes of the TM7 using MD simulations.

(A) Representative snapshot of A2AR-C394ΔC dimers shows salt bridge formation between a sample trajectory. The insets are closeups of the salt bridges, which can be both intra- and intermolecular. The last inset shows a network of salt bridges with the charged cluster 355ERR357 involved. (B) Helical tilt angles for TM7 helix in A2AR as a function of protein length. Systematic truncations of the C-terminus lead to rearrangement of the heptahelical bundle. The participation of the C-terminus in A2AR dimerization increases the tilting of the TM7 domain, which is in closest proximity to the C-terminus.

Figure 7—source data 1

MD simulations data used to visualize A2AR dimeric interface and observe the conformational changes of the TM7.

(A) List of all C-terminal residue pairs of A2AR-C394ΔC dimers engaging in electrostatic interactions. (B) Helical tilt angles for TM7 helix in A2AR as a function of protein length.

https://cdn.elifesciences.org/articles/66662/elife-66662-fig7-data1-v2.xlsx

Our finding that A2AR forms homo-oligomers via multiple interfaces (Figure 4A) agrees with the increasing number of studies reporting multiple and interconverting oligomeric interfaces in A2AR and other GPCRs (Song et al., 2020; Ghosh et al., 2014; Periole et al., 2012; Fanelli and Felline, 2011; Liu et al., 2012; Huang et al., 2013; Manglik et al., 2012; Thorsen et al., 2014; Fotiadis et al., 2006; Fotiadis et al., 2003; Liang et al., 2003; Xue et al., 2015; Dijkman et al., 2018). When translated to in vivo situations, GPCR oligomers can also transiently associate and dissociate (Kasai et al., 2018; Tabor et al., 2016; Möller et al., 2020; Vilardaga et al., 2008). Such conformational changes require that the oligomeric interfaces be formed by interactions that can easily be modulated. This is consistent with our study, which demonstrates that depletion interactions via the intrinsically disordered, malleable C-terminus drive A2AR oligomerization. Because depletion interactions can be readily tuned by environmental factors, such as ionic strength, molecular crowding, and temperature, the formation of GPCR oligomeric complexes could be dynamically modulated in response to environmental cues to regulate receptor function.

Not only did we find multiple A2AR oligomeric interfaces, we also found that these interfaces can be either symmetric or asymmetric. This finding is supported by a growing body of evidence that there exists both symmetric and asymmetric oligomeric interfaces for A2AR (Song et al., 2020) and many other GPCRs. Studies using various biochemical and biophysical techniques have shown that heterotetrameric GPCR complexes can be formed by dimers of dimers, including μOR-δOR (Golebiewska et al., 2011), CXC4R-CC2R (Armando et al., 2014), CB1R/D2R (Bagher et al., 2017), as well as those involving A2AR, such as A1R-A2AR (Navarro et al., 2018a; Navarro et al., 2016) and A2AR-D2R (Navarro et al., 2018b). The quaternary structures identified in these studies required specific orientations of each protomer, with the most viable model involving a stagger of homodimers with symmetric interfaces (DelaCuesta-Barrutia et al., 2020). On the other hand, since symmetric interfaces limit the degree of receptor association to dimers, the HMW oligomer of A2AR observed in this (Song et al., 2020) and other studies (Schonenbach et al., 2016; Vidi et al., 2008) can only be formed via asymmetric interfaces. It is indeed tempting to suggest that the formation of the HMW oligomer of A2AR may even arise from combinations of different interfaces. In any case, the wide variation of GPCR oligomerization requires the existence of both symmetric and asymmetric oligomeric interfaces.

The ultimate question to answer is how oligomerization alters A2AR function. In the case of A2AR, displacement of the transmembrane domains has been demonstrated to be the hallmark of receptor activation (Eddy et al., 2018; Sušac et al., 2018; Prosser et al., 2017; Ye et al., 2016), but no studies have linked receptor oligomerization with the arrangement of the TM bundles in A2AR. Our MD simulations revealed that C-terminus truncation resulted in structural changes in the heptahelical bundles of A2AR dimers. Specifically, as more of the C-terminus was preserved, we observed a progressive increase in the helical tilt of TM7 (Figure 7B). This change in helical tilt occurred for the entire heptahelical bundle, with an increase in tilt for TM1, TM2, TM3, TM5, and TM7, and a decrease in tilt for TM4 and TM6 (Figure 7—figure supplement 1). The longer C-terminus in the full-length A2AR permits greater rearrangements in the transmembrane regions, leading to the observed change in helical tilt. Furthermore, in the cellular context, it has been demonstrated that truncation of the C-terminus significantly reduced receptor association with Gαs and cAMP production in cellular assays (Koretz et al., 2021). These results hint at potential conformational changes of A2AR upon oligomerization, necessitating future investigation on functional consequences.

Like all biophysical studies of membrane proteins in non-native environments, a drawback in our study is the question whether the above results, conducted in detergent micelles, can be translated to bilayer or cellular context. It has been demonstrated that the propensity of membrane proteins to associate and oligomerize is greater in lipid bilayers compared to that in detergent micelles (Popot and Engelman, 1990). Furthermore, in the cellular context, A2AR has been shown to assemble into homo-oligomers in transfected HEK293 cells (Canals et al., 2003) and in Cath.A differentiated neuronal cells (Vidi et al., 2008), while C-terminally truncated A2AR shows no protein aggregation or clustering on the cell surface, in contrast with its WT form (Burgueño et al., 2003). Therefore, we speculate that A2AR oligomerization will be present in the lipid bilayer and cellular environment. Regardless, given that most biophysical structure-function studies of GPCRs are conducted in detergent micelles and other artificial membrane mimetics, it is critical to understand the role of the C-terminus in the oligomerization of A2AR reconstituted in detergent micelles.

C-terminal truncations prior to crystallization and structural studies may be the main reason for the scarcity of GPCR structures featuring oligomers. In that context, this study offers valuable insights and approaches into how the oligomerization of A2AR and potentially of other GPCRs can be tuned by modifying the intrinsically disordered C-terminus and varying salt types and concentrations. The presence of A2AR oligomeric populations with partial C-terminal truncations means that one can now study its oligomerization with less perturbation from the C-terminus. We also present evidence that the multiple C-terminal interactions that drive A2AR oligomerization can be easily modulated by ionic strength and specific salts (Figures 5 and 6). Given that ~75% and ~15% of all class A GPCRs possess a C-terminus of >50 and >100 amino acid residues (Mirzadegan et al., 2003), respectively, it will be worthwhile to explore the prospect of tuning GPCR oligomerization not only by shortening the C-terminus but also with simpler approaches such as modulating ionic strength and the surrounding salt environment.

Conclusion

This study emphasizes for the first time the definite impact of the C-terminus on A2AR oligomerization, which can be extended to include the oligomers formed by other GPCRs with a protracted C-terminus. We have shown that the oligomerization of A2AR is strongly driven by depletion interactions along the C-terminus, further modulating and enhancing the multiple interfaces formed via a combination of hydrogen, electrostatic, hydrophobic, and covalent disulfide interactions. The task remains to link A2AR oligomerization to functional roles of the receptor. From a structural biology standpoint, visualizing the multiple oligomeric interfaces of A2AR in the presence of the full-length C-terminus is key to investigating whether these interfaces give rise to different oligomer functions.

Materials and methods

Key resources table
Reagent type
(species)
or resource
DesignationSource or
reference
IdentifiersAdditional
information
Recombinant DNA reagentpITy (plasmid)Parekh et al., 1996
Strain, strain background (Saccharomyces cerevisiae)BJ5464Robinson Lab – Carnegie Mellon University
Strain, strain background (Escherichia coli)BL21 (DE3)Sigma, St. Louis, MO, USA#CMC0014
Chemical compound, drugDDMAnatrace, Maumee, OH, USA#D310
Chemical compound, drugCHAPSAnatrace, Maumee, OH, USA#C216
Chemical compound, drugCHSAnatrace, Maumee, OH, USA#CH210
Chemical compound, drugXanthine amine congenerSigma, St. Louis, MO, USA#X103
Chemical compound, drugTheophyllineSigma, St. Louis, MO, USA#T1633
Commercial assay, kitAffigel 10 resinBioRad, Hercules, CA, USA#1536099
Commercial assay, kitTricorn Superdex 200 10/300 GL columnGE Healthcare, Pittsburgh, PA, USA#17-5175-01
AntibodyAnti-A2AR, clone 7F6-G5-A2 (Mouse monoclonal)Millipore, Burlington, MA, USA#05-717(1:500) dilution
AntibodyAnti-Mouse IgG H&L DyLight 550 (Goat monoclonal)Abcam, Cambridge, MA, USA#ab96880(1:600) dilution
Software, algorithmMODELLER 9.23Eswar et al., 2006
Software, algorithmmartinize.py scriptde Jong et al., 2013
Software, algorithmELNeDyn elastic networkPeriole et al., 2009
Software, algorithmMARTINI coarse-grained force field v2.2Monticelli et al., 2008
Software, algorithmGROMACS 2016Abraham et al., 2015
Software, algorithmbackward.py scriptWassenaar et al., 2014
Software, algorithmLINCSHess et al., 1997
Software, algorithmCHARMM36 and TIP3P force fieldsBest et al., 2012; Jorgensen et al., 1983
Software, algorithmLOOSRomo and Grossfield, 2009
Software, algorithmVMDHumphrey et al., 1996

Cloning, gene expression, and protein purification

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The multi-integrating pITy plasmid (Parekh et al., 1996), previously used for overexpression of A2AR in Saccharomyces cerevisiae (O'Malley et al., 2009), was employed in this study. pITy contains a Gal1–10 promoter for galactose-induced expression, a synthetic pre-pro leader sequence that directs protein trafficking (Clements et al., 1991; Parekh et al., 1995), and the yeast alpha terminator. The genes encoding A2AR variants with 10-His C-terminal tag were cloned into pITy downstream of the pre-pro leader sequence using either splice overlapping extension (Bryksin and Matsumura, 2010) or USER cloning using X7 polymerase (Nørholm, 2010; Nour-Eldin et al., 2006). The plasmids were then transformed into S. cerevisiae strain BJ5464 (MATα ura3-52 trp1 leu2∆1 his3∆200 pep4::HIS3 prb1∆1.6R can1 GAL) (provided by the lab of Anne Robinson at Carnegie Mellon University) using the lithium-acetate/PEG method (Gietz, 2014). Transformants were selected on YPD G-418 plates (1% yeast extract, 2% peptone, 2% dextrose, 2.0 mg/mL G-418).

Receptor was expressed and purified following the previously described protocol (Niebauer and Robinson, 2006). In brief, from freshly streaked YPD plates (1% yeast extract, 2% peptone, 2% dextrose), single colonies were grown in 5 mL YPD cultures overnight at 30°C. From these 5 mL cultures, 50 mL cultures were grown with a starting OD of 0.5 overnight at 30°C. To induce expression, yeast cells from these 50 mL cultures were centrifuged at 3000 × g to remove YPD before resuspended in YPG medium (1% yeast, 2% peptone, 2% D-galactose) at a starting OD of 0.5. The receptor was expressed for 24 hr overnight at 30°C with 250 rpm shaking. Cells were pelleted by centrifugation at 3000 × g, washed in sterile PBS buffer, and pelleted again before storage at –80°C until purification.

Mechanical bead lysis of cells was done, per 250 mL of cell culture, by performing 12 pulses of 60 s intense vortexing (with at least 60 s of rest in between pulses) in 10 mL 0.5 mm zirconia silica beads (BioSpec, Bartlesville, OK, USA; #11079105z), 25 mL of lysis buffer (50 mM sodium phosphate, 300 mM sodium chloride, 10% [v/v] glycerol, pH = 8.0, 2% [w/v] n-dodecyl-β-D-maltopyranoside [DDM; Anatrace, Maumee, OH, USA; #D310], 1% [w/v] 3-[(3-cholamidopropyl)dimethylammonio]−1-propanesulfonate [CHAPS; Anatrace; #C216], and 0.2% [w/v] cholesteryl hemisuccinate [CHS; Anatrace; #CH210] and an appropriate amount of 100× Pierce Halt EDTA-free protease inhibitor [Pierce, Rockford, IL, USA; #78439]). Beads were separated using a Kontex column. Unlysed cells were removed by centrifugation at 3220 × g for 10 min. Receptor was let solubilized on rotary mixer for 3 hr before cell debris was removed by centrifugation at 10,000 × g for 30 min. Solubilized protein was incubated with Ni-NTA resin (Pierce; #88221) overnight. Protein-resin mixture was then washed extensively in purification buffer (50 mM sodium phosphate, 300 mM sodium chloride, 10% [v/v] glycerol, 0.1% [w/v] DDM, 0.1% [w/v] CHAPS and 0.02% [w/v] CHS, pH = 8.0) containing low imidazole concentrations (20–50 mM). A2AR was eluted into purification buffer containing 500 mM imidazole. Prior to further chromatographic purification, imidazole was removed using a PD-10 desalting column (GE Healthcare, Pittsburgh, PA, USA; #17085101).

Ligand affinity resin was prepared as previously described for purification of active A2AR (O'Malley et al., 2007; Weiß and Grisshammer, 2002). In brief, 8 mL of isopropanol-washed Affigel 10 resin (BioRad, Hercules, CA, USA; #1536099) was mixed gently in an Erlenmeyer flask for 20 hr at room temperature with 48 mL of DMSO containing 24 mg of xanthine amine congener (XAC, high-affinity A2AR antagonist, KD = 32 nM; Sigma, St. Louis, MO, USA; #X103). The absorbance at 310 nm of the XAC-DMSO solution before and after the coupling reaction was measured in 10 mM HCl and compared to a standard curve. The amount of resin bound to ligand was estimated to be 5.6 μM. The coupling reaction was quenched by washing the resin with DMSO, then with Tris-HCl 50 mM (pH = 7.4), then with 20% (v/v) ethanol. The resin was packed into a Tricorn 10/50 column (GE Healthcare) under pressure via a BioRad Duoflow FPLC (BioRad).

For purification of active A2AR, the column was equilibrated with 4 CV of purification buffer. The IMAC-purified A2AR was desalted and diluted to 5.5 mL before applied to a 5 mL sample loop on the BioRad Duoflow FPLC, from which the sample was loaded onto the column at a rate of 0.1 mL/min. Inactive A2AR was washed from the column by flowing 10 mL of purification buffer at 0.2 mL/min, followed by 16 mL at 0.4 mL/min. Active A2AR was eluted from the column by flowing purification buffer containing 20 mM theophylline (low-affinity A2AR antagonist, KD = 1.6 μM; Sigma; #T1633). Western blot analysis was performed to determine 4 mL fractions with active A2AR collected with a BioFrac fraction collector (BioRad), which were then concentrated through a 30 kDa MWCO centrifugal filter (Millipore, Billerica, MA, USA; #UFC803096) and desalted to remove excess theophylline. For the experiments where the salt concentrations were varied, the buffer exchange was done also by this last desalting step.

Size-exclusion chromatography

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To separate oligomeric species of active A2AR, a prepacked Tricorn Superdex 200 10/300 GL column (GE Healthcare; #17-5175-01) connected to a BioRad Duoflow FPLC was equilibrated with 60 mL of running buffer (150 mM sodium chloride except for the ionic strength experiments where NaCl concentration is adjusted to achieve the desired ionic strengths, 50 mM sodium phosphate, 10% [v/v] glycerol, 0.1% [w/v] DDM, 0.1% [w/v] CHAPS, 0.02% [w/v] CHS, pH = 8.0) at a flow rate of 0.2 mL/min. 0.5 mL fractions were collected with a BioFrac fraction collector in 30 mL of running buffer at the same flow rate. The subsequent SEC analysis performed on the SEC-separated oligomeric populations also followed this protocol.

SEC peak analysis

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SEC chromatograms were analyzed using OriginLab using the nonlinear curve fit (Gaussian) function. The area under the curve and the peak width were manually defined in cases where the SNR of the SEC trace were too low. The R2 values reached > 0.96 for most cases. The population of each oligomeric species was expressed as the integral of each Gaussian this curve fit of the SEC signal. The HMW oligomer peak in some cases could not be fitted with one curve and thus was fitted with two curves instead. The reported standard errors were calculated from the variance of the fit and did not correspond to experimental errors. The results are detailed in Figure 1—figure supplement 2 and Supplementary file 1.

SDS-PAGE and western blotting

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10% SDS-PAGE gels were hand-casted in BioRad Criterion empty cassettes (BioRad; #3459902, 3459903). Lysate controls were prepared by lysis of 5 OD cell pellets with 35 μL of YPER (Fisher Scientific, Waltham, MA, USA; #8990) at RT for 20 min, incubation with 2× Laemmli buffer (4% [w/v] SDS, 16% [v/v] glycerol, 0.02% [w/v] bromophenol blue, 167 M Tris, pH 6.8) at 37°C for 1 hr, and centrifugation at 3000 × g for 1 min to pellet cell debris. Protein samples were prepared by incubation with 2× Laemmli buffer at 37°C for 30 min. For all samples, 14 μL (for 26-well gel) or 20 μL (for 18-well gel) was loaded per lane, except for 7 μL of Magic Mark XP Western protein ladder (Thermo Scientific, Waltham, MA, USA; #LC5602) as a standard. Electrophoresis was carried out at 120 V for 100 min. Proteins were transferred to 0.2 μm nitrocellulose membranes (BioRad; #170-4159) via electroblotting using a BioRad Transblot Turbo, mixed MW protocol. Membranes were blocked in Tris-buffered saline with Tween (TBST; 150 mM sodium chloride, 15.2 mM Tris-HCl, 4.6 mM Tris base, pH = 7.4, 0.1% [v/v] Tween 20 [BioRad; #1706531]) containing 5% (w/v) dry milk, then probed with anti-A2AR antibody, clone 7F6-G5-A2, mouse monoclonal (Millipore, Burlington, MA, USA; #05-717) at 1:500 in TBST with 0.5% (w/v) dry milk. Probing with secondary antibody was done with a fluorescent anti-mouse IgG H&L DyLight 550 antibody (Abcam, Cambridge, MA, USA; #ab96880) at 1:600 in TBST containing 0.5% (w/v) milk.

Western blot was analyzed with Image Lab 6.1 software (BioRad), with built-in tool to define each sample lane and to generate an intensity profile. Peaks were manually selected and integrated with the measure tool to determine the amount of protein present.

CGMD simulations

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Initial configuration of A2AR was based on the crystal structure of the receptor in the active state (PDB 5G53). Since this structure does not include the entire C-terminus, we resorted to using homology modeling software (i.e., MODELLER 9.23) (Eswar et al., 2006) to predict the structures of the C-terminus. After removing all non-receptor components, the first segment of the C-terminus consisting of residues 291–314 was modeled as a helical segment parallel to the cytoplasmic membrane surface while the rest of the C-terminus was modeled as intrinsically disordered. MODELLER is much more accurate in structural predictions for segments less than 20 residues. This limitation necessitated that we run an equilibrium MD simulation for 2 µs to obtain a well-equilibrated structure that possesses a more viable starting conformation. To validate our models of all potential variants of A2AR, we calculated the RMSD and RMSF for each respective system. Default protonation states of ionizable residues were used. The resulting structure was converted to MARTINI CG topology using the martinize.py script (de Jong et al., 2013). The ELNeDyn elastic network (Periole et al., 2009) was used to constrain protein secondary and tertiary structures with a force constant of 500 kJ/mol/nm2 and a cutoff of 1.5 nm. To optimize loop refinement of the model, a single copy was embedded in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer using the insane.py script, solvated with MARTINI polarizable water, neutralized with 0.15 M NaCl, and a short MD (1.5 µs) run to equilibrate the loop regions. Subsequently, two monomers of the equilibrated A2AR were randomly rotated and placed at the center of a 13 nm × 13 nm × 11 nm (xyz) box, 3.5 nm apart, with their principal transmembrane axis aligned parallel to the z axis. The proteins were then embedded in a POPC bilayer using the insane.py script. Sodium and chloride ions were added to neutralize the system and obtain a concentration of 0.15 M NaCl. Total system size was typically in the range of 34,000 CG particles, with a 280:1 lipid:protein ratio. Ten independent copies were generated for each A2AR truncated variant. v2.2 of the MARTINI CG force field (Monticelli et al., 2008) was used for the protein and water, and v2.0 was used for POPC. All CG simulations were carried out in GROMACS 2016 (Abraham et al., 2015) in the NPT ensemble (P = 1 atm, T = 310 K). The Bussi velocity rescaling thermostat was used for temperature control with a coupling constant of τt = 1.0 ps (Bussi et al., 2007), while the Parrinello–Rahman barostat (Martonák et al., 2003) was used to control the pressure semi-isotropically with a coupling constant of τt = 12.0 ps and compressibility of 3 × 10–4 bar–1. Reaction field electrostatics was used with Coulomb cutoff of 1.1 nm. Non-bonded Lennard–Jones interactions were treated with a cutoff of 1.1 nm. All simulations were run with a 15 fs time step, updating neighbor lists every 10 steps. Cubic periodic boundary conditions along the x, y, and z axes were used. Each simulation was run for 8 µs.

Atomistic MD simulations

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Three snapshots of symmetric dimers of A2AR for each respective truncated variant were randomly selected from the CG simulations as starting structures for backmapping. CG systems were converted to atomistic resolution using the backward.py script (Wassenaar et al., 2014). All simulations were run in Gromacs2019 in the NPT ensemble (P = 1 bar, T = 310 K) with all bonds restrained using the LINCS method (Hess et al., 1997). The Parrinello–Rahman barostat was used to control the pressure semi-isotropically with a coupling constant of τt = 1.0 ps and a compressibility of 4.5 × 10–5 bar–1, while the Bussi velocity rescaling thermostat was used for temperature control with a coupling constant of τt = 0.1 ps. Proteins, lipids, and solvents were separately coupled to the thermostat. The CHARMM36 and TIP3P force fields (Best et al., 2012; Jorgensen et al., 1983) were used to model all molecular interactions. Periodic boundary conditions were set in the x, y, and z directions. Particle mesh Ewald (PME) electrostatics was used with a cutoff of 1.0 nm. A 2-fs time step was used for all atomistic runs, and each simulation was run for 50 ns.

Analysis of computational results

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All trajectories were postprocessed using gromacs tools and in-house scripts. We ran a clustering analysis of all dimer frames from the CG simulations using Daura et al.’s clustering algorithm (Daura et al., 1999) implemented in GROMACS, with an RMSD cutoff of 1.5 Å. An interface was considered dimeric if the minimum center of mass distance between the protomers was less than 5 Å. This method uses an RMSD cutoff to group all conformations with the largest number of neighbors into a cluster and eliminates these from the pool, then repeats the process until the pool is empty. We focused our analysis on the most populated cluster from each truncated variant. Electrostatic interactions in the dimer were calculated from CG systems with LOOS (Romo and Grossfield, 2009) using a distance cutoff of 5.0 Å. Transmembrane helical tilt angles were also calculated in LOOS from CG simulations. Hydrogen bonds were calculated from AA simulations using the hydrogen bonds plugin in VMD (Humphrey et al., 1996), with a distance cutoff of 3.5 Å and an angle cutoff of 20°. Only C-terminal residues were included in hydrogen bond analysis. PyMOL (The PyMOL Molecular Graphics System, version 2.0, Schrödinger, LLC, 2020) was used for molecular visualizations.

Assessing A2AR oligomerization with increasing ionic strength

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Na2HPO4 and NaH2PO4 in the buffer make up an ionic strength of 0.15 M, to which NaCl was added to increase the ionic strength to 0.45 M and furthermore to 0.95 M. The A2AR variants were purified at 0.45 M ionic strength and then exchanged into buffers of different ionic strengths using a PD-10 desalting column prior to subjecting the samples to SEC. The buffer composition is detailed below.

BuffersComponentsConcentration (mM)Ionic strength (mM)
0.15 M ionic strengthNaCl00
NaH2PO444
Na2HPO449146
0.45 M ionic strengthNaCl300300
NaH2PO444
Na2HPO449146
0.95 M ionic strengthNaCl800800
NaH2PO444
Na2HPO449146

Isolated C-terminus purification

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Escherichia coli BL21 (DE3) cells (Sigma; #CMC0014) were transfected with pET28a DNA plasmids containing the desired A2AR sequence with a 6x His tag attached for purification. Cells from glycerol stock were grown in 10 mL luria broth (LB, Sigma Aldrich, L3022) overnight at 37°C and then used to inoculate 1 L of fresh LB and 10 μg/mL kanamycin (Fisher Scientific, BP906). Growth of cells was performed at 37°C, 200 rpm until optical density at λ = 600 nm reached 0.6–0.8. Expression was induced by incubation with 1 mM isopropyl-β-D-thiogalactoside (Fisher Bioreagents, BP175510) for 3 hr.

Cells were harvested with centrifugation at 5000 rpm for 30 min. Harvested cells were resuspended in 25 mL Tris-HCl, pH = 7.4, 100 mM NaCl, 0.5 mM DTT, 0.1 mM EDTA with 1 Pierce protease inhibitor tablet (Thermo Scientific, A32965), 1 mM PMSF, 2 mg/mL lysozyme, 20 μg/mL DNase (Sigma, DN25) and 10 mM MgCl2, and incubated on ice for 30 min. Samples were then incubated at 30°C for 20 min, then flash frozen and thawed three times in LN2. Samples were then centrifuged at 10,000 rpm for 10 min to remove cell debris. 1 mM PMSF was added again and the resulting supernatant was incubated while rotating for at least 4 hr with Ni-NTA resin. The resin was loaded to a column and washed with 25 mL 20 mM sodium phosphate, pH = 7.0, 1 M NaCl, 20 mM imidazole, 0.5 mM DTT, 100 μM EDTA. Purified protein was eluted with 15 mL of 20 mM sodium phosphate, pH = 7.0, 0.5 mM DTT, 100 mM NaCl, 300 mM imidazole. The protein was concentrated to a volume of 2.5 mL and was buffer exchanged into 20 mM ammonium acetate buffer, pH = 7.4, 100 mM NaCl using a GE PD-10 desalting column. Purity of sample was confirmed with SDS-PAGE and western blot.

Aggregation assay to assess A2AR C-terminus assembly

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Absorbance was measured at 450 nm using a Shimadzu UV-1601 spectrophotometer with 120 µL sample size. Prior to reading, samples were incubated at 40°C for 5 min. Samples were vigorously pipetted to homogenize any precipitate before absorbance was measured. Protein concentration was 50 µM in a 20 mM ammonium acetate buffer (pH = 7.4).

Differential scanning fluorimetry (DSF)

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DSF was conducted with a BioRad CFX90 real-time PCR machine. A starting temperature of 20°C was increased at a rate of 0.5°C per 30 s to a final temperature of 85°C. All samples contained 40 μL of 40 µM A2AR C-terminus, 9x SYPRO orange (ThermoFisher S6650), 200 mM NaCl, and 20 mM MES. Fluorescence was detected in real time at 570 nm. All samples were conducted in triplicate.

Hydrophobicity and charge profile of C-terminus

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The hydrophobicity profile reported in Figure 6—figure supplement 1 was determined with ProtScale using method described by Kyte and Doolittle, 1982, window size of 3.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

References

  1. Book
    1. Gietz RD
    (2014) “Yeast Transformation by the LiAc/SS Carrier DNA/PEG Method
    In: Xiao W, editors. Yeast ProtocolsMethods in Molecular Biology. New York: Springer. pp. 33–44.
    https://doi.org/10.1385/0896033198
    1. Hofmeister F
    (1888) Zur Lehre yon der wirkung der salze
    Archiv Für Experimentelle Pathologie Und Pharmakologie 24:247–260.
    https://doi.org/10.1007/BF01918191
  2. Conference
    1. Romo TD
    2. Grossfield A
    (2009) LOOS: an extensible platform for the structural analysis of simulations
    2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
    https://doi.org/10.1109/IEMBS.2009.5335065

Decision letter

  1. Heedeok Hong
    Reviewing Editor; Michigan State University, United States
  2. Olga Boudker
    Senior Editor; Weill Cornell Medicine, United States
  3. Heedeok Hong
    Reviewer; Michigan State University, United States
  4. Antonella Di Pizio
    Reviewer; Technical University Munich, Germany

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Acceptance summary:

This is a wonderful study that advances our understanding of GPCR oligomerization and provides new physical insights into GPCR-mediated cellular signaling.

Decision letter after peer review:

Thank you for submitting your article "Oligomerization of the Human Adenosine A2A Receptor Is Driven by the Intrinsically Disordered C-Terminus" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Heedeok Hong as the Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Olga Boudker as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Antonella Di Pizio (Reviewer #3).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1. On the rigor and validity of size-exclusion chromatography (SEC)

(1a) Justifying the peak assignment in the SEC data as monomer, dimer and HMW oligomers (Figure 1 and Figure S1):

While the UV signals on the SEC profiles suggest the existence of well-resolved peaks of oligomers, dimers and monomers, the SDS-PAGE and Western blotting results that were carried out in a denaturing environment (SDS) predominantly display monomers in the "dimer" and "HMW" fractions. An alternative method may be needed to verify the assignment (e.g., crosslinking, an assignment based on the standard curve-i.e., mobility vs MW standard, analytical ultracentrifuge, native gel, etc.).

(1b) Ensuring that oligomer distributions are thermodynamic products:

The clarification of this point seems necessary to support the conclusion that multiple types of molecular forces serve as "driving forces" in oligomerization. Probably, it would be helpful to rerun SEC for the fractions of each major peak (possibly C394X mutants) and investigate the dependence of oligomer distribution on protein and detergent concentrations, the presence of deca-His tag and the length of storage. It would also be important to confirm that "UV in arbitrary units" scales with the protein concentration in the fractions.

(1c) Strengthening the rigor of statistical analysis:

Reported experimental uncertainties of content of oligomerized receptor fractions are solely based on reproducibility of fits of a single elution profile. It may underestimate experimental error limits. How reproducible are results when chromatographic experiments are repeated using the same protein stock?

2. Verifying the influence of mutation and C-terminal truncation on ligand binding capability.

3. Providing further details and additional analysis of MD simulation.

(3a) More detailed descriptions for initial modeling and its evaluation procedures (please see Reviewer 3's comments). For example, which was(were) template(s) used for the modelling of the initial state and how was the reliability of the model evaluated?

(3b) Please, address reviewers' concerns about how the system equilibration was ensured (simulation sufficiently long or repeated sufficiently with a variation of initial conditions to yield results that are not biased by initial conditions) and report time-dependent RMSDs that can provide the information on the equilibration and dynamics of the system.

(3c) Additional analysis will help further strengthening the conclusion: (i) statistical analysis of properties of interaction sites between neighbored molecules; (ii) the role of protein segments other than the C-terminus for oligomerization; (iii) statistical analysis of intra- and intermolecular "nonpolar" contacts to support authors' claim that the hydrophobic interaction is one of the key driving forces in oligomerization.

4. Clarifying the putative disulfide bridge involving C394.

It would be useful to provide a list of Cys residues that potentially can interact with Cys394 and discuss the validity of authors' claim on the formation of putative disulfide bridge.

5. Addressing additional major scientific concerns from reviewers:

(5a) Is the result obtained in micelles relevant in the lipid bilayer or cellular context?

(5b) What is the basis of claiming the "cooperativity" in the C-terminal domain interactions?

6. Please, address reviewers' major concerns that have been brought up (see below) but not listed above.

Reviewer #1 (Recommendations for the authors):

I have several suggestions that may help.

1. How relevant is the peak assignment in the SEC data as monomer, dimer and HMW oligomers (Figure 1)?

Although the assignment is supported by SDS-PAGE and Western blotting (Figure S1), SDS provides a denaturing environment. As seen in the data (Figure S1), the proteins in the "dimer" and "HMW" fractions on SEC dominantly migrate as monomers on SDS-PAGE, which indicates that SDS destabilizes oligomers or, if not, each peak contains a significant portion of monomer. An alternative method may be needed to verify the assignment (for example, crosslinking, an assignment based on the standard curve- mobility vs MW standards, analytical ultracentrifuge or native gel).

2. Ensuring that the oligomer distributions are thermodynamic products.

Probably, it might be helpful to rerun SEC with the fractions of each major peak (possibly C394X mutants) and see if the redistribution of oligomeric states occurs.

3. On the contribution of the hydrophobic interactions to oligomerization.

(3a) Since it has been suggested that the hydrophobic effect is one of the key driving forces for oligomerization, it would be informative to (3a-i) show the fraction of nonpolar residues in the C-term tail and (3a-ii) analyze the number of nonpolar contacts during CGMD simulations

(3b) What are the RMSDs of the IDRs during simulation? This analysis will be highly informative with regards to the equilibration of the system, the dynamics of the IDR, and the effect of truncation on the dynamics.

Reviewer #2 (Recommendations for the authors):

I am concerned about inconsistencies between UV absorbance and Western Blot analysis of eluted fractions in Figure S1B. While the UV signal suggests existence of well-resolved peaks of oligomers, dimers and monomers, the Western blots show high concentration of monomers underneath the dimer peak. What is the cause for this discrepancy? What are the protein concentration applied to the column and concentrations in the eluted fractions? Does aggregation behavior depend on protein concentration, detergent concentration, temperature, length of storage? Did the protein denature partially on the column? Did the authors repeat experiments on concentrated eluted fractions? Could it be that baseline correction of UV absorbance obscured a broad peak of monomer elution?

The use of the term "UV in arbitrary units" when reporting ratios of protein in oligo-, di- and monomers is ambiguous. Does protein concentration in the fractions scale with integral intensity of UV absorbance traces? If yes, the ratios would faithfully report relative differences in protein content of those fractions.

Reported experimental uncertainties of content of oligomerized receptor fractions are solely based on reproducibility of fits of a single elution profile. It yields experimental error limits that are rather low. How reproducible are results when chromatographic experiments are repeated using the same protein stock?

The authors report evidence for disulfide bond formation between neighbored molecules at C394. The level of disulfide bond formation is known to depend on cofactors including protein concentration, oxygen exposure, pH, the presence of oxidizing or reducing agents, temperature, time, etc. Were those variables controlled?

Does the deca-His tag influence oligomerization of the protein?

Does truncation of the receptor influence its function? Did the authors observe differences in ligand binding affinity and G protein activation rates for truncated/mutated receptor? Does protein truncation influence expression yield? Does truncation influence thermal stability of the expressed protein? Are eluted protein fractions obtained by size exclusion chromatography ligand binding- and G protein activation competent?

Experimental results are accompanied by an impressive set of molecular simulations. Were simulations sufficiently long or repeated sufficiently often with variation of initial conditions to yield results that are not biased by initial conditions? Would it be possible to conduct a statistical analysis of properties of interaction sites between neighbored molecules? What is the role of protein segments other than the C-terminus for aggregation?

Reviewer #3 (Recommendations for the authors):

1. The putative disulfide bridge involving C394 should be further investigated.

– In light of the suggested C-terminus/C-terminus interaction in absence of the TM domain, the Cys partner might be in the C-terminus. It would be useful to provide a list of Cys residue that potentially can interact with Cys394 and experimentally validate these hypotheses

– The discussion in lines 338-391 should be extended accordingly: 'A previous study showed that residue C394 in A2AR dimer is available for nitroxide spin labelling(Schonenbach et al. 2016), suggesting that some of these disulfide bonds may be between 390 residue C394 and another cysteine in the hydrophobic core of A2AR that do not form intramolecular disulfide bonds(De Filippo et al. 2016; Naranjo et al. 2015; O'Malley et al. 2010)'

– Moreover, in some parts of the manuscript the putative disulfide bridge is ignored, es: Lines 86-87: 'a model GPCR that could engage in diverse non-covalent interactions, such as electrostatic interactions, hydrogen bonds, or hydrophobic interactions. These non covalent interactions are readily tunable by external factors', Lines 291-293: 'The variable 13 291 nature of A2AR oligomeric interfaces suggests that the main driving forces must be non-covalent interactions, such as electrostatic interactions and hydrogen bonds as identified by the above MD simulations'

2. MD simulations

The C-terminus is not present in any of the A2AR crystal structures and is very long (Lines 104-105: A striking example is A2AR, a model GPCR with a particularly long, 122-residue, C-terminus that is truncated in all published structural biology studies).

The C-terminus is therefore modelled, however, the only reference to the C-terminus modelling I could find is in Lines 594-595: 'missing residues added using MODELLER 9.23(Eswar et al. 2006)'. Which template(s) was(were) used for the modelling and which is the sequence similarity? The detailed modelling procedure and the computational evaluation should be provided.

Results of the MD are highly dependent of the input model. Moreover, the information about the disulfide bridge is not incorporated in the models but this is an important structural feature to be considered.

Also, the conclusions about the role of the ERR motif are based on the modelling, but we do not have information to judge the modelling.

Lines 409-410: 'This observation is supported by our experimental results showing that substituting this charged cluster with alanines reduces the total A2AR oligomer levels' – the experimental results suggest the involvement of these residues on the oligomerization process, but do not say a lot about the molecular mechanisms – localizing these residues far from the interacting surface and the intramolecular interactions are hypotheses based on the modelling.

3. The impact of findings is weakly stated, some related sentences in the paper are very general:

– Line 38 in the abstract: 'offering important guidance for structure-function studies of A2AR and other GPCRs'

– Lines 55-56: 'it is crucial to identify the driving factors that govern the oligomerization of GPCRs, such that the properties of GPCR oligomers can be understood'

– Lines 473-475: 'In that context, this study offers valuable insights and approaches to tune the oligomerization of A2AR and potentially of other GPCRs using its intrinsically disordered C-terminus'

4. I suggest labeling TM residues with BW numbering, so it will be easier to distinguish between TM residues and C-terminus residues in the figures and the text.

5. Title: 'homo-oligomerization' should replace 'oligomerization'

https://doi.org/10.7554/eLife.66662.sa1

Author response

Reviewer #1 (Recommendations for the authors):

I have several suggestions that may help.

1. How relevant is the peak assignment in the SEC data as monomer, dimer and HMW oligomers (Figure 1)?

Although the assignment is supported by SDS-PAGE and Western blotting (Figure S1), SDS provides a denaturing environment. As seen in the data (Figure S1), the proteins in the "dimer" and "HMW" fractions on SEC dominantly migrate as monomers on SDS-PAGE, which indicates that SDS destabilizes oligomers or, if not, each peak contains a significant portion of monomer. An alternative method may be needed to verify the assignment (for example, crosslinking, an assignment based on the standard curve- mobility vs MW standards, analytical ultracentrifuge or native gel).

We are aware of this issue, which is why we did not use SDS-PAGE and Western blotting results as the primary method to assign the SEC peaks. Instead, we used these methods to verify that the protein is pure and indeed corresponds to A2AR.

Rigorous experiments have been done to justify the peak assignment in the SEC data. The surfactant used in our study can bind to solubilized receptors and alter both the apparent molecular weight and the hydrodynamic radius of the receptors, thus compromising our ability to estimate the size of the eluting species by comparing to SEC standards. For this reason, we used multiangle light scattering (MALS) coupled with SEC to estimate the molecular weights of the SEC-separated A2AR species. The analyses of A2AR-WT showed that the approximate molecular weights of the monomer, dimer, and HMW oligomer are 49.5, 109.2, and 332.3 kDa. These data compared well with the expected molecular weights of A2AR monomer (46.8 kDa), dimer (93.6 kDa), and heptamer (327.6 kDa). The results were published in one of our previous studies (Schonenbach et al., FEBS Lett 2016, 590, 3295–3306).

2. Ensuring that the oligomer distributions are thermodynamic products.

Probably, it might be helpful to rerun SEC with the fractions of each major peak (possibly C394X mutants) and see if the redistribution of oligomeric states occurs.

We did perform new experiments to test the stability and reversibility of the A2AR monomer and dimer/oligomer population, of both the A2AR-WT and A2AR-Q372ΔC variants (Figure 5—figure supplement 1A). We find that the SEC-separated monomers repopulate measurably into dimer/oligomer, with the total oligomer level after redistribution comparable with that of the initial samples for both A2ARWT (initial: 2.87; redistributed: 1.60) and A2AR-Q372ΔC (initial: 1.49; redistributed: 1.40) (Figure 5—figure supplement 1A). This observation indicates that A2AR oligomer is a thermodynamic product with a lower free energy compared with that of the monomer. This is consistent with the results we have shown in the manuscript that the oligomer levels of A2AR-WT are consistent (1.34–2.87; Table S1) and that A2AR oligomerization can be modulated with ionic strengths via depletion interactions (Figure 5).

Interestingly, the SEC-separated dimer/oligomer populations do not repopulate to form monomers (Figure 5—figure supplement 1A). This observation is consistent with a published study of ours on A2AR dimers (Schonenbach et al., FEBS Lett 2016, 590, 3295–3306). This indicates that once the oligomers are formed, some are kinetically trapped and thus cannot redistribute into monomers. We believe that it is disulfide linkages that kinetically stabilize A2AR oligomers, as demonstrated by their redistribution into monomers only in the presence of a reducing agent (Figure 2B).

Taken together, we suggest that A2AR oligomerization is a thermodynamic process (Figure 5—figure supplement 1B), with the monomer overcoming the activation energy (EA) by depletion interactions to repopulate into dimer/oligomer with a slightly lower free energy. Once formed, the redistributed dimer/oligomer populations can be kinetically stabilized by disulfide linkages. The results are summarized in the figure now included in the manuscript as Figure 5—figure supplement 1. We will also include this argument in the Discussion section.

3. On the contribution of the hydrophobic interactions to oligomerization.

(3a) Since it has been suggested that the hydrophobic effect is one of the key driving forces for oligomerization, it would be informative to (3a-i) show the fraction of nonpolar residues in the C-term tail and (3a-ii) analyze the number of nonpolar contacts during CGMD simulations

(i) Thank you for your suggestion. We have included a new figure to show this, and we also refer to this figure in our manuscript now as Figure 6—figure supplement 1B.

(ii) We analyzed the number of nonpolar contacts in our CGMD simulations and found that there is a general correlation between the length of the C-terminus and the number of contacts between nonpolar residues. The results are now included in the manuscript as Figure 6—figure supplement 1C. Since these interactions are very weak in nature and further diminished due to the coarse-graining resolution, we need to further investigate this issue via atomistic MD simulations (which is outside the scope of the current study).

(3b) What are the RMSDs of the IDRs during simulation? This analysis will be highly informative with regards to the equilibration of the system, the dynamics of the IDR, and the effect of truncation on the dynamics.

We agree with the reviewer’s comment and have conducted this analysis (see our detailed answer above).

Reviewer #2 (Recommendations for the authors):

I am concerned about inconsistencies between UV absorbance and Western Blot analysis of eluted fractions in Figure S1B. While the UV signal suggests existence of well-resolved peaks of oligomers, dimers and monomers, the Western blots show high concentration of monomers underneath the dimer peak. What is the cause for this discrepancy? What is the protein concentration applied to the column and concentrations in the eluted fractions? Does aggregation behavior depend on protein concentration, detergent concentration, temperature, length of storage? Did the protein denature partially on the column? Did the authors repeat experiments on concentrated eluted fractions? Could it be that baseline correction of UV absorbance obscured a broad peak of monomer elution?

Thank you for your questions. We will answer each one in order:

– The discrepancy is caused by SDS partially destabilizing the oligomeric species. Therefore, the SDS-PAGE and Western blotting results are only used to demonstrate the purity and the identity of the purified A2AR, and not to justify peak assignment. Rigorous experiments have been done to justify the peak assignment in the SEC data. We used multiangle light scattering (MALS) coupled with SEC to estimate the molecular weights of the SEC-separated A2AR species. The analyses of A2AR-WT showed that the approximate molecular weights of the monomer, dimer, and HMW oligomer are 49.5, 109.2, and 332.3 kDa. These data compared well with the expected molecular weights of A2AR monomer (46.8 kDa), dimer (93.6 kDa), and heptamer (327.6 kDa). The results were published in one of our previous studies (Schonenbach et al., FEBS Lett 2016, 590, 3295–3306). We now have these experiment referred to in line 153–155 in the manuscript for clarification.

– The concentration before SEC is about 5 mg/mL, while after SEC it is diluted about 20-fold.

– We have not done any experiment that shows changes in the oligomerization pattern with protein concentration, detergent concentration, temperature, or length of storage. The protein concentration is varied between experiments, but there has not been any correlation with dimer/oligomer levels. Detergent concentration and temperature are always kept the same. If the protein is stored for too long (~1 week), the C-terminus is cleaved off, certainly excluding oligomerization; hence, we only use freshly prepared proteins.

– We have not seen any evidence of denaturation.

– Yes, we have run SEC experiments on SEC-separated dimer/oligomer vs. monomer fractions of A2AR-WT and Q372ΔC (Figure 5—figure supplement 1). We found that the dimer/oligomer population from SEC elution remained dimer/oligomer, with little to no redistribution into other oligomeric states. This implies that dimer formation is a protein-intrinsic property of A2AR, not a property imposed by the solution environment. Meanwhile, the monomer population did repopulate into oligomers. Taken together, these results imply that the formed dimers are thermodynamically highly stable, state, while the formation of A2AR dimer/oligomer is an activated process that requires the lowering of an energy barrier to proceed.

– There should not be any broad trailing monomer peak after that. We have run Western blots of fractions of fractions eluted after the monomer fractions and detected no protein.

The use of the term "UV in arbitrary units" when reporting ratios of protein in oligo-, di- and monomers is ambiguous. Does protein concentration in the fractions scale with integral intensity of UV absorbance traces? If yes, the ratios would faithfully report relative differences in protein content of those fractions.

Thank you for your question. Yes, the protein concentration does scale with integral intensity of UV absorbance traces.

Reported experimental uncertainties of content of oligomerized receptor fractions are solely based on reproducibility of fits of a single elution profile. It yields experimental error limits that are rather low. How reproducible are results when chromatographic experiments are repeated using the same protein stock?

We are aware that the reported uncertainties are low. Therefore, we repeatedly emphasized in the manuscript that the uncertainties are the results of the curve-fitting process, and not experimental errors. Limited time and resources during the pandemic (UCSB research operation were shut down for 3 months, and subsequently limited to critical research operation in shifts for 9 months) have not allowed us to repeat every experiment multiple times. Instead, we included Figure 1—figure supplement 2B to demonstrate the reproducibility of the experiments.

The authors report evidence for disulfide bond formation between neighbored molecules at C394. The level of disulfide bond formation is known to depend on cofactors including protein concentration, oxygen exposure, pH, the presence of oxidizing or reducing agents, temperature, time, etc. Were those variables controlled?

Thank you for your questions. We have not done experiments to conclusively demonstrate the dependence of disulfide bond formation on protein concentration. On the other hand, we kept oxygen exposure, pH, temperature, and time consistent across the experiments. Regarding the presence of oxidizing or reducing agents, Figure 2B demonstrates that TCEP can be used to destabilize A2AR dimers.

Does the deca-His tag influence oligomerization of the protein?

Thank you for your question. We understand that since the study emphasizes the impact of the C-terminus, any modifications should be carefully considered, including the deca-His tag. However, we do not expect the His tag to majorly engage in inter-A2AR interactions in the absence of metal cations.

Does truncation of the receptor influence its function? Did the authors observe differences in ligand binding affinity and G protein activation rates for truncated/mutated receptor? Does protein truncation influence expression yield? Does truncation influence thermal stability of the expressed protein? Are eluted protein fractions obtained by size exclusion chromatography ligand binding- and G protein activation competent?

We understand that a study of function of truncated A2AR and its different oligomeric species is a priority. We are currently developing systems and tools that can serve as functional readouts for A2AR variants reconstituted in vitro.

Nevertheless, we have answers to some of the questions:

– We do not know yet whether truncation of the receptor influence A2AR function.

– Using densitometry on Western blots of XAC inactive and active fractions of different A2AR variants, we observed no significant difference in XAC affinity among the variants presented in this study. We do not have data on G protein activation rates.

– The expression yield is reduced upon truncation and mutation compared with the WT form but is still high enough for us to obtain enough for SEC analysis.

– We do not have data regarding the thermal stability of the truncated/mutated protein.

– We did not perform post-SEC functional analyses. However, since the protein was selected by a XAC ligand-affinity column prior to SEC, we believe that A2AR of the SEC eluent is capable of binding XAC.

Experimental results are accompanied by an impressive set of molecular simulations. Were simulations sufficiently long or repeated sufficiently often with variation of initial conditions to yield results that are not biased by initial conditions? Would it be possible to conduct a statistical analysis of properties of interaction sites between neighbored molecules? What is the role of protein segments other than the C-terminus for aggregation?

In response to the reviewer, we have carried out a decorrelation analysis to show that our simulations are not biased by our initial conditions. Our decorrelation time is about 4 µs, meaning that the systems are independent of the starting conformation after this point in time. With respect to interaction sites, our current analysis already captures all potential interaction sites, since the C-terminal segments are the portions of A2AR that predominantly form the dimerization interface. With respect to the heptahelical bundle of A2AR, based on our MD simulations, they play little or no role in receptor oligomerization since the length of the C-terminal tail sterically prohibits this interaction from taking place. Essentially, what this means is that the heptahelical bundles are not closer than 7 Å at any point in time in our simulations. This is a novel and distinct result from all previous MD simulations of A2AR (for example, Song et al., Biorxiv, https://doi.org/10.1101/2020.06.24.168260); because they did not include the full-length C-terminus of A2AR, dimerization interactions were observed between the TM helices of each protein.

Author response image 1
Decorrelation time calculated from representative trajectories of each A2AR truncated system.

Reviewer #3 (Recommendations for the authors):

1. The putative disulfide bridge involving C394 should be further investigated.

–In light of the suggested C-terminus/C-terminus interaction in absence of the TM domain, the Cys partner might be in the C-terminus. It would be useful to provide a list of Cys residue that potentially can interact with Cys394 and experimentally validate these hypotheses.

We now include a list of cysteine residues that potentially can interact with C394 (namely residues C28, C82, C128, C185, C245, C254 in the TM domain). However, only C394 on the C-terminus is fully solventexposed, while the other cysteines are thought to be buried within the TM region of A2A. Experimental validation of these hypotheses involves repeating an exhaustive list of experiments for six different variants containing single mutants to test their potential interaction with C394. The pandemic has limited our time and resources such that such experiments could prove difficult (UCSB research operation was shut down for 3 months, and subsequently limited to critical research operation in shifts for 9 months).

An analysis of our MD simulations to monitor residue-residue distances between cysteines could be done as a secondary validation. Unfortunately, we do not expect them to be revealed in simulations since they only stabilize A2AR oligomers by kinetically trapping them after they are formed, as suggested in response to Reviewer #1 (Figure 5—figure supplement 1). A distance-based analysis for all potential cysteine pairs showed a complete lack of interactions that could potentially lead to formation of a disulfide bond (i.e., < 7 Å).

– The discussion in lines 338-391 should be extended accordingly: 'A previous study showed that residue C394 in A2AR dimer is available for nitroxide spin labelling(Schonenbach et al. 2016), suggesting that some of these disulfide bonds may be between 390 residue C394 and another cysteine in the hydrophobic core of A2AR that do not form intramolecular disulfide bonds(De Filippo et al. 2016; Naranjo et al. 2015; O'Malley et al. 2010)'

Thank you for your suggestion. We have modified the manuscript accordingly.

– Moreover, in some parts of the manuscript the putative disulfide bridge is ignored, es: Lines 86-87: 'a model GPCR that could engage in diverse non-covalent interactions, such as electrostatic interactions, hydrogen bonds, or hydrophobic interactions. These non-covalent interactions are readily tunable by external factors', Lines 291-293: 'The variable 13 291 nature of A2AR oligomeric interfaces suggests that the main driving forces must be non-covalent interactions, such as electrostatic interactions and hydrogen bonds as identified by the above MD simulations'.

Thank you for your comment. We indeed found that disulfide bonds are an important, non-negligible, force that can stabilize A2AR oligomers. However, we decided not to emphasize its role as a key driving force for A2AR dimerization/oligomerization for a few reasons. First, breaking off all disulfide bonds with TCEP only partially destabilized A2AR oligomers, while a significant dimer/oligomer population persisted (Figure 2B). Second, disulfide bonds should not be modulated by varying ionic strengths that, however, we have demonstrated directly alters the extent of A2AR oligomerization. Third, we isolated dimer/oligomer population of truncated A2AR and resuspended it in solution and subjected it to a second round of SEC, as described earlier. We found the dimer/oligomer population of A2AR lacking C394 to be equally stable and behave similarly as the A2AR WT population (Figure 5—figure supplement 1A). Given that, we can confidently conclude that disulfide bond formation is not the major driver of A2AR dimer/oligomer formation and stability.

It is also worth noting that the cytoplasm lacks the conditions and machinery required for disulfide bond formation, and hence disulfide formation is less important in the cellular context. Only few cases have been reported where cytoplasmic disulfide bonds are formed (Saaranen et al., Antioxidants and Redox Signaling 2013, 19 (1), 46–53; Locker et al., J Cell Biol 1999, 144 (2), 267–279), but how that occurs remains unknown.

2. MD simulations

The C-terminus is not present in any of the A2AR crystal structures and is very long (Lines 104-105: A striking example is A2AR, a model GPCR with a particularly long, 122-residue, C-terminus that is truncated in all published structural biology studies).

The C-terminus is therefore modelled, however, the only reference to the C-terminus modelling I could find is in Lines 594-595: 'missing residues added using MODELLER 9.23 (Eswar et al. 2006)'. Which template(s) was(were) used for the modelling and which is the sequence similarity? The detailed modelling procedure and the computational evaluation should be provided.

Thank you for your suggestion. To clarify, we only used the 5G53 structure as our template, and any additional residues beyond the C-terminus of the 5G53 sequence were generated by MODELLER. No other template structures were used. We have updated the methods section in the manuscript to reflect this. Since there is no biophysical data about the conformation of the C-terminus, we allowed MODELLER to generate a “best guess” conformation, followed by long timescale (microseconds) equilibrium MD simulations to allow the C-termini to sample all possible conformations. Please refer to our earlier response to reviewer #1 for additional details.

Results of the MD are highly dependent of the input model. Moreover, the information about the disulfide bridge is not incorporated in the models but this is an important structural feature to be considered.

We completely agree with the reviewer on the dependence of the input model. Explicitly modeling disulfide bridges in a coarse-grained system is inherently difficult and may introduce uncertainty in sampling of the dimer interface. Since we do not have any detailed structural information on the monomer-monomer interactions of A2AR that could inform potential orientations that facilitate disulfide bridge formation, we focused rather on modeling fully non-bonded monomer-monomer interactions. Other issues with the input model have either already been outlined in the methods or addressed in Rev. #1’s comments.

Also, the conclusions about the role of the ERR motif are based on the modelling, but we do not have information to judge the modelling.

We agree with the reviewer and have done our best to address this issue with respect to analysis of RMSD and RMSF. Please see our response(s) above.

Lines 409-410: 'This observation is supported by our experimental results showing that substituting this charged cluster with alanines reduces the total A2AR oligomer levels' – the experimental results suggest the involvement of these residues on the oligomerization process, but do not say a lot about the molecular mechanisms – localizing these residues far from the interacting surface and the intramolecular interactions are hypotheses based on the modelling.

Thank you for your suggestion. We agree that studying the molecular mechanisms of receptor oligomerization is critical in understanding and controlling this process. However, we think such an experimental study requires a lot of efforts and is out of the scope of this paper.

3. The impact of findings is weakly stated, some related sentences in the paper are very general:

– Line 38 in the abstract: 'offering important guidance for structure-function studies of A2AR and other GPCRs'

– Lines 55-56: 'it is crucial to identify the driving factors that govern the oligomerization of GPCRs, such that the properties of GPCR oligomers can be understood'

– Lines 473-475: 'In that context, this study offers valuable insights and approaches to tune the oligomerization of A2AR and potentially of other GPCRs using its intrinsically disordered C-terminus'

Thank you for your suggestions. We have amended the manuscript as follows:

– Line 37–38 in the abstract: ‘offering important guidance on how to modify the C-terminus and tune receptor oligomerization for structure-function studies of A2AR and other GPCRs’.

– Line 55–56: ‘it is crucial to identify the driving factors of GPCR oligomerization, such that this process can be more deliberately controlled to facilitate structure-function studies of GPCRs.’

– Line 502–505: ‘In that context, this study offers valuable insights and approaches into how the oligomerization of A2AR and potentially of other GPCRs can be tuned by modifying the intrinsically disordered C-terminus and varying salt types and concentrations.’

4. I suggest labeling TM residues with BW numbering, so it will be easier to distinguish between TM residues and C-terminus residues in the figures and the text.

Thanks for the suggestion. We have modified the manuscript.

5. Title: 'homo-oligomerization' should replace 'oligomerization'.

Thank you. We have adjusted the title.

https://doi.org/10.7554/eLife.66662.sa2

Article and author information

Author details

  1. Khanh Dinh Quoc Nguyen

    Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9367-499X
  2. Michael Vigers

    Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Validation, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
  3. Eric Sefah

    C. Eugene Bennett Department of Chemistry, West Virginia University, Morgantown, United States
    Contribution
    Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  4. Susanna Seppälä

    Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Conceptualization, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Jennifer Paige Hoover

    Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Data curation, Investigation
    Competing interests
    No competing interests declared
  6. Nicole Star Schonenbach

    Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Writing - review and editing
    Competing interests
    No competing interests declared
  7. Blake Mertz

    C. Eugene Bennett Department of Chemistry, West Virginia University, Morgantown, United States
    Contribution
    Conceptualization, Software, Supervision, Funding acquisition, Validation, Writing - review and editing
    Competing interests
    No competing interests declared
  8. Michelle Ann O'Malley

    Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing - review and editing
    For correspondence
    momalley@engineering.ucsb.edu
    Competing interests
    No competing interests declared
  9. Songi Han

    1. Department of Chemistry and Biochemistry, University of California, Santa Barbara, Santa Barbara, United States
    2. Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Writing - original draft, Writing - review and editing
    For correspondence
    songi@chem.ucsb.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6489-6246

Funding

National Institute of General Medical Sciences (R35GM136411)

  • Khanh Dinh Quoc Nguyen
  • Michael Vigers
  • Susanna Seppälä
  • Nicole Star Schonenbach
  • Michelle Ann O'Malley
  • Songi Han

National Institute of Mental Health (1R43MH119906-01)

  • Khanh Dinh Quoc Nguyen
  • Jennifer Paige Hoover
  • Michelle Ann O'Malley
  • Songi Han

National Science Foundation (MCB-1714888)

  • Eric Sefah
  • Blake Mertz

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

Acknowledgements

This material is based upon work supported by (1) the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM136411, (2) the National Institute of Mental Health of the National Institutes of Health under Small Business Innovation Research Award Number 1R43MH119906-01, and (3) the National Science Foundation under Award Number MCB-1714888 (ES and BM). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Many of the experiments were completed with the assistance from Rohan Katpally. The pITy expression vector and S. cerevisiae BJ5464 strain were generously provided by Prof. Anne Robinson's lab at Carnegie Mellon University. The X7 polymerase was a gift from Dr. Morten Nørholm, Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark. Computational time was provided through WVU Research Computing and XSEDE allocation no. TG-MCB130040.

Senior Editor

  1. Olga Boudker, Weill Cornell Medicine, United States

Reviewing Editor

  1. Heedeok Hong, Michigan State University, United States

Reviewers

  1. Heedeok Hong, Michigan State University, United States
  2. Antonella Di Pizio, Technical University Munich, Germany

Publication history

  1. Preprint posted: December 22, 2020 (view preprint)
  2. Received: January 18, 2021
  3. Accepted: July 15, 2021
  4. Accepted Manuscript published: July 16, 2021 (version 1)
  5. Version of Record published: August 2, 2021 (version 2)

Copyright

© 2021, Nguyen 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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