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. 2024 Feb 22;137(4):jcs261326. doi: 10.1242/jcs.261326

Properties of biomolecular condensates defined by Activator of G-protein Signaling 3

Ali Vural 1,*,‡, Stephen M Lanier 1
PMCID: PMC10911133  PMID: 38264908

ABSTRACT

Activator of G-protein signaling 3 (AGS3; also known as GPSM1), a receptor-independent activator of G-protein signaling, oscillates among defined subcellular compartments and biomolecular condensates (BMCs) in a regulated manner that is likely related to the functional diversity of the protein. We determined the influence of cell stress on the cellular distribution of AGS3 and core material properties of AGS3 BMCs. Cellular stress (oxidative, pHi and thermal) induced the formation of AGS3 BMCs in HeLa and COS-7 cells, as determined by fluorescent microscopy. Oxidative stress-induced AGS3 BMCs were distinct from G3BP1 stress granules and from RNA processing BMCs defined by the P-body protein Dcp1a. Immunoblots indicated that cellular stress shifted AGS3, but not the stress granule protein G3BP1 to a membrane pellet fraction following cell lysis. The stress-induced generation of AGS3 BMCs was reduced by co-expression of the signaling protein Gαi3, but not the AGS3-binding partner DVL2. Fluorescent recovery following photobleaching of individual AGS3 BMCs indicated that there are distinct diffusion kinetics and restricted fluidity for AGS3 BMCs. These data suggest that AGS3 BMCs represent a distinct class of stress granules that serve as a previously unrecognized signal processing node.

Keywords: Activator of G-protein signaling 3, Biomolecular condensates, Processing bodies, P-bodies, Stress granules, Dishevelled-2, Fluorescence recovery after photobleaching

Highlighted Article: AGS3 assembles into distinct biomolecular condensates in response to cell stress, and this assembly is selectively regulated by AGS3-binding partners involved in signal transduction within the cell.

INTRODUCTION

Activators of G-protein signaling (AGS) proteins define a broad panel of biologic regulators that influence G-protein signaling; however, how this regulation mechanistically integrates signals within different systems for physiological system homeostasis and in the context of pathophysiological dysfunction is not fully understood. One member of the AGS family of particular interest is AGS3 (also known as G-protein signaling modulator 1, Gpsm1), a group II AGS protein. AGS3 is implicated in a broad range of functional roles in specific cell types, tissues and organ systems (Blumer and Lanier, 2014; Yan et al., 2022; Descovich et al., 2023); however it has been challenging to define the mechanistic elements of the various functional roles as mentioned above. AGS3 exhibits a tissue-specific expression pattern that is regulated during development and during tissue response or adaptation to various physiological or pathophysiological challenges (Blumer and Lanier, 2014; Yan et al., 2022). AGS3 actually oscillates among different subcellular compartments in a regulated manner [e.g. the cytosol, cell membranes (Oner et al., 2010), biomolecular condensates (Vural et al., 2018; Vural and Lanier, 2020), centrosomes (Blumer et al., 2006), the trans-Golgi network (Oner et al., 2013), pre-aggresomal structures and aggresomes (Vural et al., 2010)]. One premise of our recent work in this area is that understanding which factors regulate the movement of AGS3 among these different subcellular compartments will provide important insight to the functional mechanisms mentioned above.

AGS3 has seven N-terminal tetratricopeptide repeats (TPR) and four C-terminal G-protein regulatory (GPR) motifs connected with a linker domain. TPR repeats influence the intramolecular dynamics and subcellular distribution of AGS3 through interaction with specific binding partners. The GPR motifs in AGS3 act as guanine nucleotide dissociation inhibitors (GDIs) stabilizing the Gα subunit in its GDP-bound conformation, free of Gβγ, and this interaction also influences the subcellular distribution of AGS3 (Blumer and Lanier, 2014).

Of particular interest, AGS3 appears to have an inherent propensity to form distinct, non-membranous punctate structures (200 nm to 2.5 µm) in multiple cell types (Vural et al., 2010, 2018). Single amino acid substitutions within AGS3 lead to dramatic appearance of these punctate entities, which are apparently not associated with defined vesicle or organelle markers (Vural et al., 2010, 2018). Proteins with the propensity to exist as biomolecular condensates (BMCs) exhibit several shared properties including (1) apparent multivalent character in their interaction with various binding partners, (2) regulated localization within cell microdomains, (3) the ability to assemble and disassemble into micron-scale punctate nonmembranous structures that have different biophysical phases and are distinct from defined cell organelles and vesicles, and (4) regions of significant disorder in protein structure (Uversky, 2014; Banani et al., 2017; Erdos and Dosztanyi, 2020; Glauninger et al., 2022). Most of these properties are observed with AGS3 and thus we refer to the punctate structures containing AGS3 as AGS3 BMCs. BMCs generally provide a platform to coordinate the assembly of a specific subset of molecules sequestered from the rest of the cytoplasm to facilitate a wide range of biological and chemical events within the cell (Mitrea et al., 2022). The formation of any given BMC might be regulated by cell stimuli, and various BMCs play various roles in cell signal amplification, storage and trafficking of biomolecules and/or the concentration of biochemical reactions (Mitrea et al., 2022).

We previously identified the regulated engagement of AGS3 with dishevelled-2 (DVL2) signalosomes or DVL2 BMCs (Vural and Lanier, 2020). In various contexts, DVL2 functions as a ‘hub’ or ‘anchor’ protein coordinating Wnt signaling integration (Turm et al., 2010; Sharma et al., 2018). Of note, DVL2 and AGS3 are involved to varying degrees with similar tissue and cell functions and adaptations, including cilia formation (Lee et al., 2012; Yeh et al., 2013), cell polarity (Saadaoui et al., 2017; Sharma et al., 2018; Descovich et al., 2023) and system adaptations associated with addiction (Bowers, 2010; Dias et al., 2015). AGS3 is apparently ‘recruited’ to DVL2 puncta (Vural et al., 2018) and interacts with DVL2 in a phosphorylation-dependent manner. Moreover, the distribution of AGS3 to DVL2 BMCs (hereafter called AGS3–DVL2 BMCs) is regulated by a cell-surface G-protein coupled receptor (Vural et al., 2018; Vural and Lanier, 2020). Interestingly, however, phosphorylation-deficient AGS3 (AGS3-T602A) and AGS3 TPR point mutants exhibit punctate structures that seem to be distinct from DVL2 signaling puncta (Vural et al., 2018).

This publication is part of an expanded focus on the biology and regulation of AGS3 BMCs and the concept of ‘image phenotype profile screens’ or ‘image-signaling system connectivity’ as mentioned in a previous report (Vural and Lanier, 2020). In the current study we addressed (1) the distribution of AGS3 to defined BMCs, (2) the influence of cell stress on BMC generation and its interaction with various binding partners and (3) the mobility or diffusion kinetics for AGS3 in the context of distinct BMCs. The results of these studies suggest that AGS3 BMCs, the formation of which is regulated by both cellular stress and the signaling proteins Gαi3 (also known as GNAI3) and DVL2, define a new type of BMC that might serve as a previously unrecognized signal processing node.

RESULTS

Many proteins associated with biomolecular condensates have regions of intrinsic disorder (Wang et al., 2021). Analysis of AGS3 secondary structure using the IUPred2A algorithm (Dosztanyi, 2018) indicates that AGS3 also exhibits similar features with ∼40% of the AGS3 protein, including the linker and GPR domains, exhibiting such intrinsic disorder (Fig. S1). As also observed with various proteins that assemble in biomolecular condensates, AGS3 also assembles into distinct, non-membranous punctate structures and oscillates between various functional microdomains within the cell in a regulated manner (Blumer et al., 2006; Vural et al., 2010; Oner et al., 2013; Huang et al., 2014; Vural et al., 2018; Vural and Lanier, 2020). As an initial approach to understanding the factors influencing the subcellular distribution of AGS3 in this context, we determined the impact of three environmental stressors (oxidative, pHi and thermal) on AGS3 BMC formation.

Influence of environmental stressors on the cellular distribution of AGS3

Each environmental stressor resulted in the robust generation of a significant number of AGS3 BMCs (Fig. 1A–C). As previously reported for COS-7 cells, and in this study with HeLa cells, ectopically expressed AGS3 predominantly exhibits a non-homogeneous cytosolic distribution (HeLa cells, 89.5±4.7%; COS-7 cells, 88.5±3.9%; mean±s.e.m.), but it also consistently exhibits a clear, punctate distribution in a smaller percentage of the cells (HeLa cells, 9.8±1.7%; COS-7 cells, 17.3±4.4%) (Fig. 1, controls). The introduction of stressors shifted the predominant distribution of AGS3 in the cell to the punctate structures as compared to control cells (Fig. 1). Although not yet fully examined for each environmental stressor, the stress-induced assembly of AGS3 BMCs appeared to occur within the first 2 min of the initiation of pHi stress, as indicated by real-time imaging of cells expressing AGS3–GFP (Movie 1). This stress-induced translocation of AGS3 is on a slower time scale than that observed for (1) the redistribution of AGS3 from the cell cortex to a subdomain of the Golgi complex after activation of a cell-surface G-protein coupled receptor (Oner et al., 2013) and (2) the apparent dissociation of AGS3 from the cell cortex following activation of a cell-surface G-protein coupled receptor as determined by real time continuous measurements of protein interactions with bioluminescent resonance energy transfer studies (Oner et al., 2010).

Fig. 1.

Fig. 1.

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The influence of environmental stressors on the subcellular distribution of AGS3. (A) HeLa cells stably expressing AGS3–GFP were exposed to HBSS without bicarbonate (pHi stress, 30 min), thermal stress (42.5°C, 1 h), and oxidative stress (sodium arsenite; 0.5 mM; 30 min) and processed for immunocytochemistry. (B) COS-7 cells were transfected with pEGFP::AGS3 (250 ng). At 24 h following plasmid transfection, cells were exposed to HBSS without bicarbonate (pH stress, 30 min), thermal stress (42.5°C, 1 h) and oxidative stress (sodium arsenite; 0.5 mM; 30 min) and processed for immunocytochemistry. The images in A and B are representative of five separate experiments and were taken with a 63× objective. Scale bars: 10 µm.(C) 100 cells were counted to determine the percentage of cells with AGS3 BMCs for each independent transfection (n=6) and data are expressed as mean±s.e.m. ****P<0.0001 [one-way ANOVA followed by Dunnett's multiple comparison test; in HeLa cells, the percentage of control cells with AGS3 BMCs (9.8±1.7%) were compared with the percentage of cells with AGS3 BMCs following pH stress (92.5±2.7%), oxidative stress (62.0±3.4%) and thermal stress (73.0±3.0%). The same analysis and comparison was applied for COS-7 cells comparing the percentage of control cells with AGS3 BMCs (17.3±4.4%) with the percentage of cells with AGS3 BMCs following pHi stress (94.5±2.4%), oxidative stress (69.2±4.3%) and thermal stress (76.8±3.5%)].

The AGS3 BMCs generated in response to the environmental stressors in COS-7 and HeLa cells are similar to punctate structures observed for endogenous, non-ectopic expression of AGS3 in various cell and tissue types, including renal epithelial cells isolated from the Balb/c polycystic kidney disease mouse model (Nadella et al., 2010), COS-7 cells following cell stress by incubation with the proteasome inhibitor MG-132 (Vural et al., 2010), primary cultures of hippocampal neurons, the rat adrenal medulla pheochromocytoma cell line PC-12 (Blumer et al., 2002) and for the AGS3-related protein in ventral nerve cord in C. elegans (Cuppen et al., 2003). Of particular note, AGS3 localized specifically to a subpopulation of stress granules distinct from those typically defined with the stress granule marker protein G3BP1 (Marmor-Kollet et al., 2020). A key area of focus in this field is to determine the factors that actually regulate the distribution of AGS3 to different microdomains of the cell with the thought that such information would provide additional insight on the various functional roles associated with this protein.

Cellular distribution of AGS3, stress granule proteins and P-body proteins with and without oxidative cell stress

Given the influence of environmental stressors on the cellular distribution of AGS3, we next asked whether these stress-induced AGS3 structures were related to defined populations of stress granule BMCs or to the AGS3–DVL2 BMCs reported in previous studies (Vural et al., 2018; Vural and Lanier, 2020). As an initial approach, we determined the cellular distribution of AGS3 and BMC biomarkers for the RNA processing BMCs generated in response to oxidative cellular stress (sodium arsenite) (Jiang et al., 2013) in two distinct cell types – a human epithelium cell line (HeLa) and the primate renal fibroblast-like cell line (COS-7). Stress granule BMCs are non-membranous compartments consisting of RNA and RNA-binding proteins (RBPs) that are formed as a response to certain stressors, such as oxidative cell stress or heat shock (Glauninger et al., 2022). Stress granules are one of the first defined BMCs impacting mRNA translation and stability, and have been linked to the pathogenesis of a closely related set of degenerative diseases, including amyotrophic lateral sclerosis, frontotemporal dementia and inclusion body myopathy (Molliex et al., 2015; Wolozin and Ivanov, 2019). Stress granules are typically identified through either an endogenous biomarker (eIF4G) or an exogenously expressed biomarker (G3BP1) and their formation is induced in response to various types of cell or tissue stress (Molliex et al., 2015).

In non-stressed cells, AGS3 and the stress granule BMC marker proteins eIF4G and G3BP1 exhibited a non-homogenous cytosolic or membrane distribution in both HeLa and COS-7 cells (Fig. 2A,B). The cellular distribution of the stress granule BMC marker proteins eIF4G and G3BP1 were not altered by exogenous AGS3 expression. Oxidative cell stress markedly increased the number of cells containing AGS3 BMCs (HeLa, 63.3±3.1% with stressor versus 12.3±1.9% control; COS-7, 66.3±6.3% with stressor versus 21.3±3.2% control; mean±s.e.m.) and stress granule BMCs (HeLa, 92.0±4.2% versus 1.5±0.6% control; COS-7, 84.0±3.6% versus 1.5±0.7% control). However, the oxidative stress-induced AGS3 BMCs and stress granule BMCs did not indicate any colocalization as determined by fluorescent microscopy, indicating that there are distinct subpopulations of BMCs (Fig. 2A,B). Similar results were obtained with the endogenous (eIF4G) and ectopically expressed (G3BP1) protein markers of stress granule BMCs. The AGS3 BMCs observed with cell stress were also distinct from RNA-processing BMCs defined by the presence of P-body protein Dcp1a (Fig. S2A).

Fig. 2.

Fig. 2.

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Determination of the distribution of AGS3 and stress granule proteins with and without oxidative cell stress. (A) HeLa cells stably expressing AGS3–GFP were exposed to oxidative cell stress (0.5 mM sodium arsenite for 30 min) and processed for immunocytochemistry using antibody against the stress granule (SG) marker protein eIF4G (1:100 dilution). 100 cells were counted for each independent treatment (n=4) and data expressed as mean±s.e.m. ****P<0.0001 [two-tailed unpaired Student's t-test; the percentage of control cells with AGS3 BMCs (12.3±1.9%) and eIF4G positive stress granule BMCs (1.5±0.6%) was compared to the percentage of cells exhibiting AGS3 BMCs (63.3±3.1%) and eIF4G positive stress granule BMCs (92.0±4.2%) upon exposure to oxidative stress]. (B) COS-7 cells were transfected with G3BP1–GFP (800 ng) with and without pcDNA3::AGS3 (200 ng). At 24 h following plasmid transfection, cells were exposed to oxidative stress (0.5 mM sodium arsenite for 30 min) and processed for immunocytochemistry using AGS3 (G-2) antibody (1:100 dilution). Fluorescence imaging was performed by confocal microscopy as described in the Materials and Methods. The images are representative of at least four independent experiments and were taken with a 63× objective. 100 cells were counted for each independent treatment (n=4) and data are expressed as mean±s.e.m. ***P<0.001; ****P<0.0001 [two-tailed unpaired Student's t-test; the percentages of control cells with AGS3 BMCs (21.3±3.2%) and G3BP1–GFP-positive stress granule BMCs (1.5±0.7%) were compared to the percentage of cells exhibiting AGS3 BMCs (66.3±6.3%) and G3BP1–GFP-positive stress granule BMCs (84.0±3.6%) upon exposure to oxidative stress]. (C) Cell lysates were fractionated into supernatant (S) and pellet (P) as described in the Materials and Methods and aliquots processed for SDS-PAGE on precast gels (4–20% gradient gel) and subsequent immunoblotting. The images shown are representative of four independent experiments. Scale bars: 10 µm.

The properties of the AGS3 BMCs in comparison to stress granule BMCs were further evaluated by immunoblotting following differential fractionation of cell lysates as described in the Materials and Methods. The SG BMC protein marker G3BP1 was primarily distributed to the soluble fraction of the cell lysate and this was not altered by oxidative cell stress (Fig. 2C). In contrast, in unstressed cells AGS3 was found in both the cell lysate pellet and soluble fractions (Fig. 2C). The distribution of AGS3 to the cell fractions as not altered by co-transfection of G3BP1, consistent with the lack of colocalization of the two proteins as observed by fluorescence microscopy (Fig. 2A,B). Furthermore, although oxidative stress did not cause any changes in G3BP1 fractionation, it significantly shifted AGS3 to the pellet fraction. These data are consistent with the hypothesis that the stress-induced AGS3 BMCs exhibit properties distinct from the stress granule BMCs defined with the marker protein G3BP1. A similar fractionation pattern was obtained when AGS3 was co-expressed with the P-body protein marker Dcp1a (Fig. S2B).

Regulation of stress-induced AGS3 BMCs

As an initial approach to further characterize the AGS3 BMCs generated by oxidative cell stress, we asked two questions. First, is the formation of the stress-induced AGS3 BMCs regulated by protein binding partners involved with signal processing? Second, do the various AGS3 BMCs exhibit different protein diffusion kinetics? As indicated in Fig. 3A, oxidative cell stress failed to generate the AGS3 punctate structures when the AGS3-binding partner Gαi3 was co-expressed in the cells (Fig. 3A). The generation of AGS3 BMCs in response to pHi stress was also prevented by co-expression of the AGS3-binding partner Gαi3 (Fig. 3A). Initial studies indicated that, within the AGS3 BMCs generated in response to cell stress, AGS3 might assemble into a higher order structure through disulfide bridging with other proteins (Fig. S3), based on the differences of migration of the protein through non-reducing denaturing polyacrylamide gels as compared to the migration pattern observed with standard reducing denaturing PAGE. As seen in the fluorescence microscope images in Fig. 3A, the slower migrating higher order assembly of AGS3 observed by gel electrophoresis under non-reducing conditions, was also not observed with co-expression of the AGS3-binding partner Gαi3 (Fig. S3).

Fig. 3.

Fig. 3.

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Influence of signal processing proteins on stress-induced AGS3 BMCs. (A) Influence of G-proteins. COS-7 cells were transfected with pEGFP::AGS3 (250 ng) with and without pcDNA3::Gαi3 (750 ng). At 24 h following plasmid transfection, cells were exposed to oxidative cell stress (0.5 mM sodium arsenite for 30 min) or incubated in Hank's balanced salt solution (HBSS) without bicarbonate (30 min) to alter the intracellular pH and processed for fluorescent microscopy or gel electrophoresis. Fluorescence imaging was performed with confocal microscopy as described in the Materials and Methods. The images are representative of three independent experiments and were taken with a 63× objective. 100 cells were counted for each independent transfection and data were expressed as mean±s.e.m. *P<0.05; **P<0.005; ***P<0.001 [two-tailed unpaired Student's t-test; the percentage of cells with AGS3-BMCs in the absence of Gαi3 co-expression was compared to the percentage of cells with AGS3 BMCs in the presence of Gαi3 co-expression with and without oxidative stress and pHi stress conditions. Control, AGS3 BMCs without Gαi3 co-expression (22.7±4.1%), AGS3-BMCs with Gαi3 co-expression (8.0±2.6%); oxidative stress, AGS3 BMCs without Gαi3 co-expression (62.7±2.7%), AGS3-BMCs with Gαi3 co-expression (12.3±3.7%); pH stress, AGS3 BMCs without Gαi3 co-expression (91.0±3.6%), AGS3-BMCs with Gαi3 co-expression (14.3±4.7%)]. (B) AGS3–DVL2 BMCs and oxidative stress. COS-7 cells were co-transfected with pcDNA3::AGS3 (200 ng) and pRc/CMV2::DVL2 (800 ng) for 24 h and exposed to oxidative cell stress (0.5 mM sodium arsenite for 30 min) and processed for immunocytochemistry using anti-AGS3 (G-2) (1:100 dilution) and anti-DVL2 (1:100 dilution) antibodies. Fluorescence imaging was performed with confocal microscopy as described in the Materials and Methods. Images are representative of at least five independent experiments and were taken with a 63× objective. 100 cells were counted for each independent transfection and data are expressed as mean±s.e.m. ***P<0.001 [two-tailed unpaired Student's t-test; the percentage of cells exhibiting colocalization of AGS3 and DVL2 (AGS3–DVL2 BMCs) in control conditions (53.6±3.3%) was compared to the percentage of cells exhibiting colocalization of AGS3 and DVL2 (AGS3-DVL2 BMCs) following oxidative stress (21.8±4.3%)]. Bottom, cell lysates were fractionated into supernatant (S) and pellet (P) as described in the Materials and Methods and processed for SDS-PAGE (4–20% gradient gel) and immunoblotting. The images shown are representative of five independent experiments. Scale bars: 10 µm.

We also addressed the influence of cell stress on the BMCs containing the DVL2–AGS3 signaling complex (Vural et al., 2018; Vural and Lanier, 2020). In COS-7 cells expressing both DVL2 and AGS3, the two proteins appear to colocalize in defined BMCs (Fig. 3B), as previously reported (Vural et al., 2018; Vural and Lanier, 2020). This apparent colocalization was disrupted with oxidative cell stress (Fig. 3B). Immunoblotting after cell lysis indicated that DVL2 was enriched in the cell lysate pellet and the relative distribution of DVL2 between the supernatant and pellet was not altered by oxidative cell stress (Fig. 3B, immunoblot). By contrast, oxidative cell stress shifted AGS3 to the pellet fraction (Fig. 3B). These data indicate that the stress-induced generation of AGS3 BMCs is regulated by the signaling protein Gαi3, but not by the AGS3-binding partner DVL2.

We next explored the fluidity or rigidity of the stress-induced AGS3 BMCs with respect to the mobility of the AGS3 protein within the cell by evaluating fluorescent recovery of AGS3 signals in different AGS3 BMCs following photobleaching (FRAP). With FRAP, it is inferred that a quick recovery of the fluorescent signal following photobleaching for any specific protein indicates that the protein of interest is ‘mobile’ in the context of the specific microenvironment evaluated. On the other hand, the lack of such recovery of the fluorescent signal indicates limited protein mobility suggesting more of a structurally rigid entity or a segregated microenvironment within the cell.

We addressed this question of AGS3 mobility by evaluating FRAP for oxidative stress-induced AGS3 BMCs, DVL2–AGS3 BMCs and AGS3-T602A BMCs. Mutation of candidate serine/threonine phosphorylation sites in the GPR domain results in the generation of AGS3 punctate structures and the T602 residue (T625 in G-protein-signaling modulator 1 isoform a, NP_653346) was previously identified as a key site for this regulation in that mutation of this single residue directs AGS3 to punctate structures (Vural et al., 2018). For DVL2–AGS3 BMCs, the recovery of the AGS3 fluorescent signal following photobleaching occurred within 18 s, indicating a dynamic and fluid BMC with respect to the specific protein AGS3 (Fig. 4A, upper panel). In contrast, for the AGS3-T602A BMCs and AGS3 BMCs induced by oxidative cell stress (Fig. 4A, middle and lower panels), the recovery of the AGS3 fluorescent signal following photobleaching exhibited markedly different diffusion kinetics (Fig. 4B) indicating restricted mobility of AGS3 within these types of BMCs, which is consistent with more of a biophysically rigid BMC as compared to DVL2–AGS3 BMCs.

Fig. 4.

Fig. 4.

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Mobility of AGS3 in the context of defined BMCs. The FRAP level was determined in COS-7 cells as described in Materials and Methods for (A) AGS3–DVL2 BMCs generated upon co-expression of AGS3–GFP (200 ng) and pRc/CMV2::DVL2 (800 ng), (B) AGS3–BMCs generated upon oxidative cell stress (0.5 mM sodium arsenite for 30 min) and (C) AGS3–BMCs observed with the phosphorylation-deficient mutant AGS3-T602A–GFP. Individual AGS3–DVL2, AGS3-T602A and AGS3–GFP BMCs induced by oxidative cell stress (n= 5–10) were bleached (t=9 s) as shown in the represented enlarged insets for each experimental group and fluorescence intensity was measured at every 3 s for 2 min as described in the Materials and Methods. (B) The fluorescence intensity was normalized and the data presented as the mean ±s.e.m. intensity. Scale bars: 1 µm.

DISCUSSION

Although AGS3 is implicated in a number of diverse cell and system functions, and the biochemistry of AGS3 with respect to structural domains and its interaction with G-proteins has been well investigated, the mechanisms by which the biochemistry of AGS3 signaling is processed and regulated with respect to cell and tissue function is not clear. Similar challenges exist for various signaling transduction systems in that there is simply a level of complexity in terms of ‘translating’ the biochemistry of signaling systems (e.g. protein interactions and signal transduction networks) into specific and defined human phenotypes. This has presented challenges for both understanding disease mechanisms and the development of new therapeutic modalities for any given disease. Toward this end, and with the enabling technologies advanced over the last several years with respect to bio-imaging and protein dynamics within cells, we explored the possibility of using image phenotype profile screens to gain further insight into signal-function processes for the family of AGS proteins (Vural et al., 2010; Oner et al., 2010, 2013; Vural et al., 2016, 2018; Vural and Lanier, 2020). This concept of ‘image-signaling system connectivity’ was recently illustrated with the discovery of the AGS3 interaction with the disheveled signaling nexus (Vural and Lanier, 2020). In the current article, we further expanded this platform to examine the positioning of AGS3 with respect to other types of functional punctate structures in the cell and whether this positioning is regulated by cell stress and signal transducing proteins.

Given the cell biology and protein dynamics of AGS3, its propensity to exist in defined and distinct punctate structures within the cell, and the regulated generation of such punctate structures, we refer to these punctate structures as AGS3 BMCs. BMCs are non-membranous and organelle-sized (i.e. micron-scale) structures formed by liquid–liquid phase separation (Banani et al., 2017). By spatially organizing and coordinating the physical assembly of a specific subset of molecules sequestered from the rest of the cytoplasm, BMCs might have a range of effects on the activity and function of individual proteins or assemblies of various related proteins including (1) enhanced activity through concentrating enzymes and substrates; (2) reduced activity through sequestration; and (3) modulated activity through exclusion of regulatory factors (Case et al., 2019; Lyon et al., 2021; Peeples and Rosen, 2021). Additionally, BMCs exhibit extraordinary sensitivity to solution conditions such as oxidative stress, temperature, pH and ionic strength, where biological systems exploit them as a mechanism to sense environmental challenges and induce appropriate homeostatic responses (Franzmann and Alberti, 2019). These core properties of BMCs might be operational within a wide range of physiological (transcription and genome organization, immune response, neuronal synaptic signaling) and pathological events (neurodegeneration, cancer and viral infections) within the cell (Wang et al., 2021).

Thus, there are two central concepts advanced with this manuscript and our recent work in this area. The first concept is that AGS3 can engage with defined BMCs in a regulated manner. The second concept is that AGS3, given its regulated interaction with key cell signaling proteins, is a core element of a new type of BMCs that serve as previously unappreciated signal processing nodes. Indeed, AGS3 exhibits an inherent propensity to form distinct non-membranous punctate structures, which do not appear to associate with any defined vesicle or organelle markers or be enveloped by a lipid bilayer (Vural et al., 2010, 2018). The linker and GPR regions of AGS3 protein exhibit high intrinsic disorder and a similarly strong intrinsic disorder pattern is observed with the Group II AGS proteins AGS4 (also known as GPSM3) and AGS5 (GPSM2) (Uversky, 2014). Of note, BMCs are suggested to be involved in the role of AGS5 in actin bundling in stereocilia, which might directly relate to the role of this protein in Chudley–McCullough syndrome (Shi et al., 2022).

As reported here, the generation of AGS3 BMCs and stress granule BMCs was markedly increased by oxidative cell stress. However, and of particular note, the AGS3 and stress granule BMCs generated in response to oxidative cell stress were distinct from each other and exhibited different biochemical properties. Upon cell lysis, in non-stressed cells, AGS3 distributed to both a cytosolic supernatant and a membrane pellet fraction, but with oxidative stress AGS3 was primarily found in the membrane pellet. In contrast, oxidative stress did not alter the relative distribution of DVL2, the stress granule BMC protein G3BP1 or the P-body protein Dcp1a in the pellet and supernatant after cell lysis. The AGS3 BMCs induced by stress are distinct from the population of stress granules as defined by the protein marker G3BP1. However, there are likely distinct subpopulations of stress granules that differ in their composition, biophysical properties, and their functional role within the stress granule ecosystem of the cell response to stressors (Jain et al., 2016; Shiina, 2019; Cirillo et al., 2020; Marmor-Kollet et al., 2020). Of note AGS3 (GPSM1) appears to be enriched in a subpopulation of stress granules defined with the marker proteins FMR1 and FXR1 (Marmor-Kollet et al., 2020).

Overall, these data are generally consistent with the concept that AGS3 is capable of defining a distinct population of BMCs. One working hypothesis is that the dynamics of structural organization of AGS3 allows a degree of micro fluidity for the protein within the cell. Two specific observations from the current study have relevance to this hypothesis: (1) the altered fluidity of AGS3 BMCs as compared to AGS3–DVL2 BMCs as determined by FRAP, and (2) the altered migration of immunoreactive AGS3 species as visualized by immunoblotting following non-reducing, denaturing PAGE. Both oxidative cell stress and altered cellular pH resulted in the visualization of immunoreactive AGS3 species of higher apparent Mr in the membranous pellet fraction isolated following cell lysis. Such a migration pattern might represent dimerization or oligomerization of AGS3 protein via intermolecular disulfide bonds or stress-induced rearrangements of structural domains within AGS3 that influence coordination of posttranslational events and protein modifications (Niwa et al., 2007). The prevention of the generation of AGS3 BMCs by Gαi co-expression further suggests that the direct interaction of Gαi with AGS3 stabilizes specific conformations of the protein that then influence its subcellular distribution.

Of particular note, both the AGS3 BMCs generated by oxidative cell stress and the punctate structures observed with a phospho-deficient AGS3 (AGS3-T602A) do not appear to colocalize with DVL2 upon co-expression as is the case for AGS3 in non-stressed cells (Vural et al., 2018). These data suggest that the DVL2–AGS3 BMCs are distinct from the BMCs observed with phospho-deficient AGS3 (AGS3-T602A) and with oxidative cell stress. The FRAP studies reported in this study indicate that this is indeed the case as the AGS3 within the AGS3–DVL2 BMCs clearly existed in a more-fluid state as compared to the AGS3 that localized in the BMCs generated by oxidative cell stress and those observed with the phospho-deficient AGS3 (AGS3-T602A). These data indicate an ongoing internal rearrangement of proteins within AGS3–DVL2 puncta as well as an in-and-out trafficking of AGS3–GFP molecules to and from the puncta suggesting they exist in a dynamic and reversible state. AGS3–DVL2 puncta possess a higher mobility and fusion rate with fluid-like characteristics. On the other hand, the lack or a very-low degree of fluorescence recovery of AGS3 BMCs generated by oxidative cell stress and with phospho-deficient AGS3-T602A suggests a gel-like or less fluid texture.

We have not yet fully investigated the life span of the stress-induced AGS3 BMCs following removal of the stressor. Based on the FRAP results presented here, it is clear that the AGS3 BMCs formed after oxidative stress are fairly rigid with respect to AGS3 fluidity. Preliminary observations suggest that the cell stress-induced AGS3 BMCs are still present several hours after removal of the stressor. However, the decay kinetics for stress-induced AGS3 BMCs have not been quantified and additional well-controlled real-time imaging studies with an appropriate panel of internal controls to allow for full comparative evaluation are required to fully understand this dynamic. We also do not know whether there are actually different subpopulations of the AGS3 BMCs that exhibit a range of decay kinetics. It is of note that there are apparently different functional subpopulations of stress granule BMCs with different turnover rates or decay kinetics and that AGS3 is found in the subpopulation of stress granules with slower decay kinetics (Marmor-Kollet et al., 2020).

Based upon this series of results and current concepts in the BMC field, the fluid association of AGS3 with DVL2 BMCs and the reduced fluidity of AGS3 in the stress-induced AGS3 BMCs might reflect ‘client’ and ‘scaffolding’ roles, respectively, for AGS3 (Espinosa et al., 2020; Lyon et al., 2021).

The apparently more rigid structure of the AGS3 BMCs observed here following oxidative cellular stress appears to differ from the receptor-regulated dynamic movement of AGS3 from the cell cortex. As reported previously, real-time measurements of membrane association of AGS3 with the cell cortex indicates that this subcellular distribution of AGS3 is regulated by a cell surface receptor (Oner et al., 2013, 2010). In these studies, activation of the α2-adrenergic receptor resulted in rapid dissociation of AGS3 from the cell cortex and this was rapidly reversed in real time by the receptor antagonist rauwolscine (Oner et al., 2010). A similar regulated movement of AGS3 from the cell cortex to the Golgi has also been observed by fluorescence microscopy (Oner et al., 2013). The current manuscript, in tandem with previously observed oscillation of AGS3, within the cell provides a potential platform to further dissect the factors influencing the assembly and disassembly of proteins in different domains of the cell.

AGS3 interacts with a number of proteins involved in signal processing pathways including the Gαi family of G-proteins, DVL2 and inscuteable (INSC) in a regulated manner. AGS3 also appears to oscillate among different functional domains within the cell and this dynamic movement is regulated by various factors including cell-surface G-protein-coupled receptors, phosphorylation of AGS3 G-protein regulator motifs, the cell cycle and environmental stressors. AGS3 is also reported to influence the trafficking of membrane proteins to the cell surface and to also exist in urinary exosomes (Groves et al., 2007; Keri et al., 2018; Nie et al., 2020). The relationship between biomolecular condensates in the cell and the generation of exosome structures is an area of active investigation (Liu et al., 2021). Various studies have indicated a functional role for AGS3 in polycystic kidney disease, renal protection in the face of oxidative stress, and system adaptations observed in metabolic and substance-use disorders (Nadella et al., 2010; Bowers, 2010; Kwon et al., 2012; Blumer and Lanier, 2014; Keri et al., 2018; Yan et al., 2022). From a metabolic perspective, mice lacking GPSM1 actually exhibit a lean phenotype with reduced fat mass. The GPSM1-null mice phenotype also suggests a role for AGS3 in the maintenance of vascular tone following drug-induced vasodilation (Blumer et al., 2008). In addition to continued studies to dissect the regulated dynamic movement of AGS3 and related proteins within the cell, further work is needed to mechanistically connect the specific biochemistry and cell biology of AGS3 with the phenotypes associated with the protein. As AGS3 moves through the different cellular or extracellular compartments (e.g. cell cortex, Golgi, biomolecular condensates and exosomes), it likely has a specific functional impact in each of the domains and the disruption of that specific ‘compartment-specific function’ might relate to different phenotypes. Toward this end, there is likely much value and unexpected insight to be gained by approaching these questions with a broader omics ‘lens’ that involves the association of signaling network genes, such as GPSM1, with phenotypes and endophenotypes revealed from the rich data platforms assembled through the UK Biobank (https://www.ukbiobank.ac.uk/ and https://app.genebass.org/), Finngene (https://www.finngen.fi/en), the Taiwan Biobank (https://taiwanview.twbiobank.org.tw/about.php), BioBank Japan (https://pheweb.jp/) and related global initiatives in this area.

MATERIALS AND METHODS

Materials

Sodium (meta)arsenite (NaAsO2, S7400), anti-β-actin-peroxidase antibody (mouse monoclonal, A3854), diamide (D3648) and 2-Mercaptoethanol (M7154) were purchased from MilliporeSigma (Burlington, MA, USA). Antibodies against AGS3 [mouse monoclonal (G-2), sc-271721], DVL2 (mouse monoclonal [10B5], sc-8026), eukaryotic initiation factor 4 γ (eIF4G) [mouse monoclonal (A-10), sc-133155] and mRNA-decapping enzyme 1A (Dcp1a) [mouse monoclonal (56-Y), sc-100706) were purchased from Santa Cruz Biotechnology (Santa Cruz, CA, USA). Polyethyenimine (PEI) (linear, Mr∼25,000) was obtained from Polysciences, Inc. (Warrington, PA, USA). The DC Protein Assay Kit II (5000112) was purchased from Bio-Rad (Hercules, CA). HaltTM protease and phosphatase inhibitor (1861280), BlockerTM BSA in TBS (37520), SpectraTM Multicolor Broad Range Protein Ladder (26634), SuperSignal West Dura Extended Duration Substrate (34075), Prolong Diamond Antifade (P36961) reagent, Novex WedgeWell 4-20% Tris-Glycine Gels (XP04202BOX), iBlot Gel Transfer Stacks, polyvinylidene fluoride (PVDF) - regular (IB401001) and the iBlot Gel Transfer Device (IB1001), DMEM (21063-029), Hank's balanced salt solution [HBSS; catalog number 14025076 (calcium chloride (CaCl2) (anhydrous), magnesium chloride (MgCl2-6H2O), magnesium sulfate (MgSO4-7H2O), potassium chloride (KCl), potassium phosphate monobasic (KH2PO4), sodium bicarbonate (NaHCO3), sodium chloride (NaCl), sodium phosphate dibasic (Na2HPO4) anhydrous and D-Glucose (Dextrose)], and HBSS catalog number 14185052 [potassium chloride (KCl), potassium phosphate monobasic (KH2PO4), sodium chloride (NaCl), sodium phosphate dibasic (Na2HPO4-7H2O), D-Glucose (Dextrose)] were purchased from Thermo Fisher Scientific (Waltham, MA, USA). pRC/CMV::DVL-2-Myc was obtained from Addgene (Cambridge, Massachusetts, USA) (plasmid #42194) as deposited by Robert Lefkowitz and Shin-ichi Yanagawa (Lee et al., 1999). pT7-EGFP-C1-HsDCP1a was Addgene plasmid #25030 deposited by Elisa Izaurralde (Tritschler et al., 2009). Ras GTPase-activating protein-binding protein 1 (G3BP1) phage UbiC G3BP1-GFP-GFP was Addgene plasmid #119950 deposited by Jeffrey Chao (Wilbertz et al., 2019). All other materials were obtained as previously described (Vural and Lanier, 2020).

Cell culture, cellular transfection and cell stress

COS-7 (CRL-1651) and HeLa (CCL-2) cell lines were purchased from American Type Culture Collection (ATCC) (Manassas, VA, USA). Both cell lines were cultured in Dulbecco's modified Eagle's medium (high glucose) supplemented with 2 mM glutamine, 100 units/ml penicillin, 100 μg/ml streptomycin and 10% fetal bovine serum at 37°C 5% CO2. COS-7 cells were transfected using PEI as described previously (Vural et al., 2018). To generate the AGS3-expressing stable HeLa cell lines, wild-type AGS3–GFP plasmid was transfected into HeLa cells using Lipofectamine 2000 as previously described (Vural et al., 2016). The cells were selected with 1000 μg/ml G418 and sorted based on GFP expression and isolated as a pool of GFP-expressing cells. Sorted GFP-positive cells were then further characterized for AGS3 expression by immunoblotting (Vural et al., 2016).

For the series of experiments with environmental stressors, on the day of the experiment cell culture dishes at ∼80% confluence were processed as follows. For oxidative stress, cells were exchanged into full DMEM containing 0.5 mM sodium arsenite (oxidative stress) and incubation continued at 37°C for indicated time periods. For thermal stress, cells were transferred to a separate incubator and cultured at 42.5°C for indicated time periods. For pH stress, cells were exchanged into HBSS 14185052 medium and incubated at 37°C, 5% CO2 for 30 min. HBSS 14185052 medium lacks the ability to buffer pH under standard incubation conditions resulting in a progressive decline in medium pH from 7.4 to 6.2 with 30 min incubation at 37°C, 5% CO2 as determined by monitoring medium pH with pH test strips (pH range from 5 to 10).

Cell fractionation and immunoblotting

Cells were lysed with buffer (250 µl) consisting of 25 mM HEPES pH 7.4, 4% glycerol, 0.5% (v/v) Nonidet P-40, 150 mM NaCl, 2 mM CaCl2 and HaltTM protease and phosphatase inhibitor. Lysates were shaken on ice for 15–20 min followed by centrifugation at 13,000 rpm (16,000 g) for 10 min at 4°C. The supernatant was transferred, and protein concentration was determined using the DC Protein Assay Kit II. The pellet was resuspended in 100 µl of lysis buffer including DNase (10 U/ml) and incubated 30 min at room temperature. Immediately after cell lysis and fractionation, the samples (e.g. 25% of the supernatant fraction and 50% of the pellet fraction) were processed by denaturing PAGE (SDS-PAGE) using Novex 4–20% gradient gels. For SDS-PAGE with standard reducing agents to disrupt sulfhydryl bonds, the protein loading buffer (25 mM Tris-HCl pH 6.8, 5% glycerol, 1% SDS and 0.2% Bromophenol Blue) included 2-mercaptoethanol. For SDS-PAGE under non-reducing conditions, protein loading buffer lacked 2-mercaptoethanol (2.5%). Protein loading buffer (10 µl) was added to the samples (90 µl) and heated for 10 min at 70°C. The proteins were transferred onto the PVDF membrane with P3 program for 10 min (20 V) using the iBlot Gel Transfer Stacks. The membranes were then processed for immunoblotting as previously described (Vural et al., 2018).

In specific series of experiments, we independently analyzed AGS3, actin and biomolecular condensate markers on separate transfer membranes and at different times (Fig. S4). This approach facilitated the processing of multiple sample gel transfers for immunoblotting and avoided any background interference that often occurs during reprobing the membrane blots with multiple antibody preparations. For proteins of higher Mr (e.g. AGS3), gel electrophoresis was conducted with an applied voltage of 90 V for 2 h to obtain maximum resolution. For housekeeping genes of lower Mr (e.g. actin), gel electrophoresis was conducted with an applied voltage of 200 V for 0.5 h to facilitate sample processing.

Fluorescence confocal microscopy, FRAP assays and image analysis

HeLa and COS-7 cells were processed for immunofluorescent microscopy as described previously (Vural et al., 2018; Vural and Lanier, 2020) and cell images captured with a 63× oil immersion objective on a Zeiss LSM 800 confocal microscope (Microscopy, Imaging & Cytometry Resources Core at Wayne State University, USA). For FRAP assays, glass-bottom dishes with COS-7 cells were placed into the environmental chamber (37°C, 5% CO2) of the Zeiss LSM 800 confocal microscope. Using bleaching and time series options in ZEN software, individually selected AGS3 puncta were bleached (i.e. fluorescence intensity was nullified) and the images were captured at every 3 s for a total of 40 cycles. The fluorescence intensity of the AGS3 puncta was measured in each image. The fluorescence intensity was normalized by subtracting the post-bleaching intensity (t=12 s) from the pre-bleaching intensity (t=0 s) for AGS3 puncta from different experiments. All images were obtained from approximately the middle plane of the cells and images were visualized and evaluated through the Adobe Photoshop CC 2018 platform. The researchers doing the FRAP analysis were aware of the experimental conditions.

Statistical analysis

For each experiment, at least 100 individual cells were counted to determine the percentage of cells containing stress granule, DVL2 and AGS3 BMCs. Data are expressed as mean±s.e.m as determined from three or more independent experiments. Data were analyzed with Prism 10 for macOS software (GraphPad Software, San Diego, CA, USA) using either the two-tailed unpaired Student's t-tests or one-way ANOVA, where significant differences between groups were determined by Dunnett's multiple comparison test. P<0.05 was considered statistically significant.

For the FRAP series of experiments, five to ten individual AGS3 BMCs from multiple individual COS-7 cells were photobleached to determine the fluorescence intensity in each individual experimental group. Data are expressed as mean±s.e.m as determined from five or more independent experiments. Data at t=120 s after bleaching were analyzed with Prism 10 for macOS software (GraphPad Software, San Diego, CA, USA) using one-way ANOVA, where significant differences between groups were determined by Tukey's multiple comparison test. P-values were calculated on the t=120 s comparable time point and P<0.05 was considered statistically significant.

Supplementary Material

Supplementary information
joces-137-261326-s1.pdf (11.3MB, pdf)
DOI: 10.1242/joces.261326_sup1

Acknowledgements

A.V. gratefully acknowledges the support of Dr Raymond Mattingly (Chair, Department of Pharmacology, School of Medicine, Wayne State University, Detroit, MI) for his support and encouragement. S.M.L. also acknowledges and is greatly appreciative of the opportunity and support provided by M. Roy Wilson (President, Wayne State University) during his tenure at Wayne State University in Detroit, MI. Cell imaging studies were conducted through the Microscopy, Imaging & Cytometry Resources Core at Wayne State University, Detroit, MI. As always, S.M.L. appreciates the valued suggestions and gracious engagement of the many students, fellows, colleagues, and collaborators that have contributed to the body of work involving Activators of G-protein signaling since their initial discovery.

Footnotes

Author contributions

Conceptualization: A.V., S.M.L.; Methodology: A.V., S.M.L.; Validation: A.V., S.M.L.; Formal analysis: A.V., S.M.L.; Investigation: A.V.; Resources: S.M.L.; Data curation: A.V., S.M.L.; Writing - original draft: A.V., S.M.L.; Writing - review & editing: A.V., S.M.L.; Visualization: A.V.; Supervision: S.M.L.; Funding acquisition: S.M.L.

Funding

The early development of tools and materials used in these studies was supported by National Institutes of Health grants NS24821 and DA025896 to S.M.L. with recent financial support provided through a recruitment package provided to S.M.L. Deposited in PMC for release after 12 months.

Data availability

All relevant data can be found within the article and its supplementary information.

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DOI: 10.1242/joces.261326_sup1

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